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Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publications. Several approaches have been proposed on improving recommender systems. However, most existing approaches depend on priori user profiles, and thus they cannot recommend papers to new user. Furthermore, the existing approaches utilize non-public contextual information, and thus it cannot adequately find similarities between papers due to copyright restrictions. Also, the existing approaches consider only single level paper-citation relation to identify similarities between papers. Considering the above challenges, this paper presents a collaborative filtering based recommendation approach for scientific papers that does not depend on priori user profiles and which utilizes only public contextual information. Using citation context, we utilized 2-level paper-citation relations to find hidden associations between papers. The rational underlying this approach is that, two papers are co-occurred with same cited paper(s) and two papers are co-occurring with same citing paper(s) are significantly similar to some extent. To evaluate the performance of the proposed approach, publicly available datasets are used to conduct extensive experiments. The experimental results demonstrate that the proposed approach has significantly outperforms the baseline approaches in terms of precision, recall, F1, mean average precision, and mean reciprocal rank, which are commonly used information retrieval metrics. The novelty of this study is that, with the proposed approach, researchers are able to find relevant and useful publications over the internet regardless of their previous research experiences and research area.

The NIST selection process for standardizing Post-Quantum Cryptography Mechanisms is currently running. Many papers already studied their theoretical security, but the resistance in deployed device has not been much investigated so far. In particular, fault attack is a serious threat for algorithms implemented in embedded devices. One particularly powerful technique is to use safe-error attacks. Such attacks exploit the fact that a specific fault may or may not lead to a faulty output depending on a secret value. In this paper, we investigate the resistance of various Post-Quantum candidates algorithms against such attacks.

Most insulation in the power transformers consists of oil and cellulose (paper/pressboard). Mineral oil has been used as an insulating liquid for over a hundred years. However, mineral oil is a non-biodegradable oil and has a serious impact on the environment and the non- renewable energy resources. Therefore, it is important to replace this oil with another alternative insulating liquid, and PFAE was introduced in the year 2006 in Japan. In addition, the ability of an insulating system also depends on the thickness of the monomolecular cellulose fiber on the kraft paper. Hence, it is necessary to determine the appropriate thickness of kraft paper for use as an insulator on the power transformer for this type of oil. This project presents paper-oil (PFAE) charging and discharging current characteristics. The study was carried out through the implementation of experiments in the laboratory. Polarization and Depolarization Current (PDC) test has been carried out to test the conductivity and response function of the insulating materials. It was found that the thickness of kraft paper affecting the capacitance value and the PDC measurement of the tested model. In both dry and wet conditions, the sample of two layers of kraft insulation paper shows the best insulation status as it has the lowest conductivity compared to the other samples. It can be concluded that it is necessary to determine the ideal thickness of insulating paper to ensure that the power transformer has the best insulation.

In this work, Schottky diodes based on amorphous indium-gallium-zinc-oxide (IGZO) were fabricated on cellulose microfiber paper substrate. Silver lines used as the Schottky barrier were printed, in parallel to thermally evaporated Cr/Au ohmic contact, using a dispense printer. The morphological and electrical characteristics of the devices are presented. The fabricated diodes exhibited rectification ratios ranging from 3.4 to 34.9 at ±1V with ON voltages that range from 1.1V to 1.4 V, for device lengths (Ag to Au distance) from 145 µm to 894 µm. The diodes were characterized in a temperature range between 25°C and 80°C. They showed a decrease of the ON current when increasing temperature, which is mainly attributed to the change of the cellulose microstructure. Indeed, an opposite of the ON current behavior was registered when the diode was realized on a polyimide substrate. The realized flexible paper-based diodes offer a potential promising choice for printed environmental-friendly electronics.

The industry of disposables has undergone a huge revolution in this century owing to the busy lifestyles and technological advancements in its production and manufacturing process. Paper cups are one of the widely used products in disposable industry. It has multi utility options that is it can be used to drink water as well as beverages, soups, liquids etc. This paper entirely focuses on increasing the quality factor of production and manufacturing process of these paper cups by adding additional circuitry to the existing machinery to reduce waste of raw materials as well as the per unit cost involved in wastage of electricity. This research work is based on using proximity sensors to sense the materials and molded paper cups infront of machinery and reduce the electric wastage through a relay Mechanism assembly. This is a PLC based live project example of effectively increasing the overall efficiency of the manufacturing plant

For the detection of product color uniformity and seam texture defects in the production process of test paper, detection methods are proposed respectively. For the detection of the color uniformity, a uniformity detection method based on dynamic light correction is proposed. The illumination correction image is used for color dynamic compensation of the test paper image to solve the influence of uneven illumination on the test paper. For the detection of texture defects such as seams, a texture defect detection method based on gray gradient aggregation intensity is proposed. This method uses one-way Gaussian convolution to strengthen features, and then calculates the gradient, divides the region and calculates the gradient extremum aggregation strength to judge texture defects, which can quickly and efficiently find seam defects. The experimental results show that the above methods have obvious effects on the color uniformity and seam detection of the test paper. The color uniformity accuracy rate is 96%, the seam detection accuracy rate is 97%. The total detection time of a single test paper is about 90ms. The algorithm is real-time and accurate, and can be used in actual production detection.

Life expectancy of power transformers is limited by the integrity of insulating cellulosic paper wound around transformer winding. The insulating paper is subjected to thermal, electrical and mechanical stresses. There are three main factors causing degradation in the paper, i.e. moisture, oxygen and temperature. In this work, the degradation rate due to temperature is only discussed. That means that transformer life could be shortened or extended by adjusting loads which results in higher or lower temperature conditions. The temperature, namely the hot-spot temperature is typically used to estimate the relative ageing rate and loss of insulation life. Being able to estimate the hot-spot temperature accurately given load and weather data helps operators to plan about transformer replacement properly. This could also reduce costs of early replacement due to a conservative estimation. In this work, thermal models have been developed using machine learning techniques to learn thermal behavior from historical data. The data are comprised of the hot-spot temperature estimated by winding temperature indicator (WTI), load profiles, ambient temperature, rainfall, wind speed and direction and solar radiation. The proposed method has been validated using data for five 400kV/275kV, four 400kV/132kV and two 275kV/66kV autotransformers and has been shown to work effectively.

In the screening area of the paper mill has the high density impurities which are removed from the pulp and it is stored in the machine chest. The pulp in the machine chest is directly transferred to the head box without removing any medium density sand particles which affects the quality of the pulp. Only if the pulp entering the paper machine is clean and well-mixed with additives a good quality of paper will be produced. So in between the pulp tank and the pulp receiver a medium density cleaner is installed. The pulp in the machine chest is allowed to flow through the round hopper. Due to the circulatory motion and by centrifugal force the high density sand particles will settle in the bottom of the hopper. Due to the centripetal force the pulp is recovered from the hopper. The sand particles that settled in the bottom of the hopper are removed by the periodic opening and closing of the solenoid valves at regular interval of time. The medium density impurities are removed by creating hydro cyclone. These sequential operations are automated and controlled through PLC. So the overall plant efficiency is increased. Since the medium density impurities are removed this ensures the good quality paper production.

Electromagnetic Fault Injection (EMFI) is a well known method of introducing faults for security analysis of digital devices. Such faults can be seen as analogous to the faults which are known to naturally occur in digital devices, a known problem with designing safety-critical systems.Numerous standards have been developed for safety-critical systems, including the development of standards for increasing the rate of naturally occurring faults using particle sources. In this work, we demonstrate that desktop EMFI tooling can be used to accomplish similar testing, but with more control, effectively speeding up the evaluation process.We demonstrate using EMFI tooling for safety evaluation to recreate a highly publicized safety issue present in an automotive ECU – one that could not easily be recreated with other techniques.

Although testing software is paramount to safeguard our digitizing society, students are reluctant to consider a career in the field. A reason could be that dedicated courses on software testing are rare. However, even when such a course exists, students perceive testing as a boring, unrewarding and even dogmatic chore. For more than 10 years, we have been teaching a software testing course at the Vrije Universiteit in Amsterdam. Driven by our belief that an abundant exposure to software bugs makes good testers, we experimented with many ideas to engage students and make them love the topic. The most unorthodox, yet effective interventions we are proud of, were: (1) to scare students by analyzing past, software-related accidents, such as Therac-25 or Boeing 737-MAX; (2) to thrill them using bug-hunting gamification, enabled by the in-house developed VU-BugZoo; (3) to trust them an end-To-end testing of safety-critical software-intensive systems, such as model trains, automatic insulin pumps and even radiotherapy facilities, and (4) to inspire their career, by opening a dialog with test professionals from industry. The result is a mature course, read yearly by 50 computer science graduates, where almost 80% of the participants find the topic interesting and challenging, and 40% consider a future carrier in testing. These positive results make us confident that we found a formula that works. In this position paper, we would like to share our innovative ideas and lessons learned. Also in the future, we will stay committed to educate enthusiastic and responsible software testers.

In this paper, we obtain samples of thermal aging transformer insulation paper at 6 time points through an accelerated thermal aging test that simulates the actual operating state of the transformer. The Raman spectroscopy diagnosis model of transformer insulating paper aging is proposed. The model combines an autoencoder and a linear discriminant analysis algorithm to extract the characteristics of the Raman spectrum, and uses a Naive Bayes classification method to divide the aging stage of the insulating paper. Through the Raman spectroscopy diagnosis model of transformer insulation paper aging designed in this paper, the Raman spectroscopy characteristic quantity extracted by the AE-LDA method can effectively reflect the aging characteristic information of the insulating paper, and the Naive Bayes classification algorithm is used to predict. Research shows that the model has a high predictive accuracy for the assessment of the aging state of insulating paper, and can effectively diagnose the aging state of transformer oil-paper insulation. The Raman spectroscopy used in the diagnosis of the aging of insulating paper has good aging discrimination ability and good application prospects, and provides a new idea for the diagnosis of the aging state of transformer oil-paper insulation.

Because the traditional insulation paper state detection method has some shortcomings, this paper proposes a non-destructive detection method, which uses the texture feature value of insulation paper image to establish a relationship with the degree of polymerization (DP) of insulation paper state, and then indirectly estimates the aging state of insulation paper. Firstly, the insulation paper images in different aging states are collected, and the texture feature values of the images are extracted by gray histogram, gray level co-occurrence matrix and gray level run-length matrix; then, the texture feature values are selected by correlation; then, the validity of the selected texture feature values to represent the insulation paper state is verified by support vector machine (SVM); finally, the multiple linear regression method is used. The relationship between the degree of polymerization and the texture feature value is established and verified by the actual results. The results show that the texture feature value has a good fitting relationship with the degree of polymerization, which verifies the effectiveness of this method in evaluating the state of insulating paper.

The ageing status of the oil-paper insulation is closely related to the operation of the transformers. Recently, near infrared spectroscopy (NIRS) is used to identify the ageing condition of oil-paper insulation for it is a more rapid and nondestructive detection than the traditional viscometry method. However, the identification accuracy of existing quantitative analysis method of NIRS are still insufficient. This paper proposed an improved Linear discriminant analysis (LDA) method to classify the spectra and to identify the ageing condition of the insulating paper. Based on DP measurement, the insulating paper specimens prepared in laboratory are divided into varying ageing groups. The principle of LDA method is introduced. The classic LDA method has been applied to identify the ageing status of specimens respectively from 4 ageing groups and 3 ageing groups. The results show that LDA has a better performance in classifying four groups than three groups. To achieve an accurate ageing condition identification with balanced accuracy of the model and enough categories of ageing status, the improved LDA method is proposed. The identification results show that the improved method has satisfactory performance and indicates great application potentials in the ageing assessment of the oil-paper impregnated insulation.

Prediction and detection of skin diseases have always been a challenging and critical task for health care professionals. There are many clinics and skin practitioners who are offering their services at exorbitant costs. At the same time, skin condition prevails in our country in every part. In the current scenario majority of the skincare practitioners are using traditional methods to diagnose the disease which may take a considerable amount of time. Skin Diseases are serious problems in recent times as it is a matter of environmental factors, socioeconomic factors, lack of full diet, etc. This paper is a comparative study about understanding various skin diseases related to normal skin issues as well as cosmetology. A comparison between oily, dry, and normal skin is also projected in this study. A survey of different papers is done on basis of technologies used, results with accuracy, ethical conduct, number of diseases diagnosed, datasets, etc are done.

In this paper the optimal surface area of an air-to-air plate heat exchanger is determined. The analysis is based on input data obtained by measurement in real operating conditions in board producing paper machine in Belgrade, Serbia. For that purpose effectiveness-NTU method together with previously defined cost functions was applied, taking into account seasonal variations in the parameters of exhaust and fresh atmospheric air. In addition, the total net savings in the consumption of primary energy sources in the factory that can be achieved by applying an optimised system for the use of waste heat were calculated and a simple payback period of the investment was determined.

The purpose of this short position paper is to stimulate a community wide discussion on how situation awareness (SA) technologies may best support the decisions made during pandemics. Currently much of SA is directed towards the critical information needed to make epidemiological and public health decisions; as important as this is, an epidemic also requires doctors and front line medical professional to make numerous decisions regarding individualized patient care. The question is how can SA contribute to both the rapid collection, analysis, and sharing of critical patient information among medical personnel, and then across all levels of decision-making from individual patients to public health policy?

This paper describes approaches to the use of wearables and related monitoring and diagnostic tools to glean and present data to patients and their caregivers in the form of Personal Health Dashboard. Raw data from devices such as fitness watches, blood glucose and blood pressure monitors can be analyzed by machine learning algorithms ensembles over the cloud or at the edge, and the resulting patterns can be presented to allow for actionable responses. The advent of low-cost computational, sensing, monitoring and diagnostic tools allow for cost-effective solutions that can have wide adaptability. The paper draws from prior and ongoing research conducted by the team to present these positions in the advancement of healthcare.

Paper-based strain sensors have attracted attention as a cost-effective and environmentally friendly approach to wearable electronic devices. This paper proposes a paper-based strain sensor created solely using hand-painting, which is a simple, equipment-free process utilized in green electronics. Commercial printing paper is coated with polydimethylsiloxane diluted with heptane, which provides moisture resistance and mechanical robustness while increasing the hydrophobicity of the surface. The electrodes and conduction channels are fabricated using a pencil for graphite deposition and a brush for the deposition of tin-doped indium oxide nanoparticles, respectively. With a gauge factor of 41.98 in tensile strain tests and 21.36 in compressive strain tests, our strain sensor exhibits a good sensitivity that is similar to that of previously reported paper-based sensors. We also demonstrate that our proposed strain sensor can be used as a weak motion detection device for humans and robots.

Cryptography is the methodology in which the information is cast into a form that forestalls the abuse of it. In this advanced time of the wireless, it is imperative to guarantee the safe conveyance of the pertinent information which are otherwise exposed to disgusting goals. The procedure of transformation of plaintext to encode text is known as encryption and its converse is known as decryption. The three kinds of cryptography methods, viz., Asymmetric key, Symmetric-key, and Hash Functions. A huge segment of this contemporary method is the key; which is a specific component of extreme significance, as this is what is utilized while scrambling or descrambling the desired information. In this paper, we have compared the two techniques. Incipiently, Particle Swarm Optimization, a strategy of delivering keys to design a stream figure for text encryption. The tale methodology named Particle Swarm Optimization Key Generation Algorithm (PKGA) uses a character code table for encoding the keys. The essential ideal situation of this procedure is that it diminishes the quantity of keys to be fused and coursed. On the other hand is Ant Colony Optimization Techniques to produce keys for the encryption of the information. This entire philosophy depends on the conduct of the ants in their characteristic inquiry of food. The drawback of using Ant Colony Optimization is to downscale the number of keys to be utilized during encipherment when contrasted with different strategies of cryptography in presence. ACO would warrant the generation of such keys with utmost proficiency.

In this work, we describe the application of the ‘steerable pyramid’ (Portilla and Simoncelli, 2000), a high-dimensional texture descriptor, to the discrimination and classification of a large collection of photographic paper textures. This work is part of a broader effort to bring precise physical measurements to the characterization of photographic papers, and our intended audience includes photograph conservators, curators, and collectors. For our purposes, it is important both to enable fine-grained local comparisons of very similar textures and to identify salient groupings across the entire landscape of photographic papers. The steerable pyramid was developed with the explicit goal of synthesizing textures; as such, it is an overcomplete representation. Its high native dimensionality is an advantage for highly precise local comparisons of texture, as in nearest neighbor search; it is, however, a disadvantage for grouping tasks, which require a well-structured global topology. For grouping tasks, we describe a number of compression and grouping approaches designed to meet a variety of analytical needs. Finally, we validate the steerable pyramid descriptor numerically using ‘one versus all’ classification on an augmented data set that includes multiple samples per paper type.

Chinese folk paper-cutting has a long history of development, and it is a major folk art form created by the working people of all ages in our country in order to meet the needs of material and spiritual life, and Return lived in it. It has become a design art rooted in the folk, and it is entrusted with the beautiful expectation of the broad working group from life. Plane composition is a very important part of modern design foundation. Points, lines and surfaces are not only the basic elements of plane composition, but also create a colorful environment atmosphere through the artistic treatment of points, lines and surfaces in different indoor environment designs. Many artistic inspirations of modern design come from folk paper-cutting, and we get creative inspiration and enlightenment from the structure and composition of paper-cutting. By studying the comparison between folk paper-cut art and modern graphic design, this paper tries to provide an innovative way for modern graphic design.

This paper presents a novel, low cost flexible paper substrate suitable for biosensing applications. A microstrip patch antenna consisting of copper tape foil and a cellulose filter paper as a substrate with thickness of 180 μm is fabricated and tested. The substrate has measured dielectric constant (e r ) of 1.9 and losses (tan δ ) of 0.025. For 3.8 GHz resonance, the antenna has size of 29.5 mm x 38 mm on a ground plane of 50 mm x 60 mm. Measurements of the final design are in excellent agreement with simulations. Moreover, measurements of the patch antenna on the proposed substrate (cellulose filter paper) collected at different bending radii and folding angles demonstrate performance consistency.

The fabrication and characterization of a paper and pencil based resistive touch sensor is carried out in the present work. The sensor detects the effective change in the resistance, when the finger is placed on it. An ash less, low cost, easy to access, bio-degradable, flexible, light weight, easy to fabricate and ultra-thin sensor is developed by drawing interdigitated graphite electrodes on the Whatman filter paper of grade 42. Change in the resistance is due to the path created for flow of electrons, when the finger is placed. Current versus time and $\Delta$ R/Ro versus time characterization of fabricated device is done using Keithley 2450 source meter. Response of the device has made noticeable changes for the finger contact. The measured resistance of the non-touch and touch is found to be 80.154 M $\Omega$ and 4.748 M $\Omega$ respectively. This huge change in resistance is sufficient to detect the touch. The performance and sensitivity of the proposed sensor are evaluated using the test circuit and smart switch is developed on paper substrate.

Triboelectric nanogenerators (TENGs) have been introduced as a rational and effective way of powering the low consuming electronic devices and sensors. Mostly these nanogenerators are manufactured using costly materials and complex fabrication processes that restrict their usage especially in developing countries. In this paper, we have presented an inexpensive and facile TENG for powering the environmental sensor. Readily available and cost-effective materials were used for manufacturing TENG like paper, thread sealant PTFE tape, and pencil. The manufactured paper based TENG produced short circuit current and open circuit voltage of $110\ \mu \mathrm{A}$ and 234 V respectively. The maximum power density of $96.22\ \mu \mathrm{W} /$ cm2 was achieved at 5 M $\Omega$. The rectified signal from TENG was used to charge a capacitor array of $300\ \mu \mathrm{F}$ which was successively used to power the environmental sensor. Temperature and humidity can be measured by powering the environmental sensor with the help of the proposed TENG. This facile and cost-effective TENG can be easily manufactured and deployed in resource limited environment for self-powered sensing systems.

This paper presents the development of a “modified Degree of Polymerization test method” based on IEC 60450 for the DuPont™ Nomex® 910, engineered cellulose composite paper. In order to check how retained tensile strength corresponds to the DP value of 200 for the composite 910 paper, accelerated ageing tests of 910 and TUK were performed and DP vs tensile curves were obtained. Although the thermal insulation system test procedures allow the choice of either DP or percent tensile strength retention as the end-life criteria for cellulose-based papers, our data indicates that the traditional kraft DP of 200 is not a good indication for the composite 910 paper end-of-life criteria.

This paper presents the main disadvantages of receipts printed on thermal paper, underlining the impact that BPA (component of thermal paper) has on the environment and human health. The conceptual solution proposes to use the near-field communication (NFC) protocol available in smartphones, integrating a virtual receipt printing device (called e-receipt) at the end of the contactless payment chain.

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, PB-DMFB manufacturing process may suffer from potential security threats. For example, both Trojan insertion and man-in-the-middle attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hides information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, it serves as a first countermeasure against both Trojan insertion and man-in-the-middle attacks for PB-DMFBs.

The last decade has witnessed an impressive paradigm shift in practically all networking fields: from hardware-based appliances to software-based infrastructures. Network functions traditionally hard-coded in the network devices have been redesigned in software and deployed in virtualized networking scenarios, with impressive advantages in terms of management flexibility and upgradable capability. Still, at a time in which we strive for more and more network processing and computing resources, such a softwarization process risks to bring about a severe toll in terms of performance and energy consumption. We believe, and posit, that programmable hardware architectures tailored for supporting high performance network processing tasks may come to the rescue. With this position paper, after motivating our position, we further briefly review the past and present of programmable hardware for networking, and we discuss its possible evolution towards more comprehensive "higher layer" HW-accelerated processing tasks.

We often point to the relative increase in the amount and sophistication of evaluations of visualization systems versus the earliest days of the field as evidence that we are maturing as a field. I am not so convinced. In particular, I feel that evaluations of visualizations, as they are ordinarily performed in the field or asked for by reviewers, fail to tell us very much that is useful or transferable about visualization systems, regardless of the statistical rigor or ecological validity of the evaluation. Through a series of thought experiments, I show how our current conceptions of visualization evaluations can be incomplete, capricious, or useless for the goal of furthering the field, more in line with the “heroic age” of medical science than the rigorous evidence-based field we might aspire to be. I conclude by suggesting that our models for designing evaluations, and our priorities as a field, should be revisited.

We propose the original automated information technology for transformation of paper archives of drawing and design documentation into electronic 3D model of an object for CALS and BIM ideologies of designing and manufacturing of an object. The technology assumes the full automated cycle of processing of projective kinds from initial paper drawings to electronic frame 3D model of an object. Original models of representation and algorithms of solving the given problem are proposed.

Traction transformers have been withstood the effects of shock load, which would become more than 2~3 times rated load when the train passes, and it can result in the winding insulation under short-term high temperature frequently. And the average load far less than 50% result in relatively low oil temperature, the very uneven rise of temperature lead to the very uneven distribution of insulation aging. In order to evaluate the aging life of oil-paper insulation of traction transformer under shock load effectively, in this paper, Ekenstam aging kinetic model was optimized considering the effect of shock temperature, shock duration and shock interval on cellulose degradation rate of insulating paper. Firstly, the effects of shock temperature, shock duration and shock interval on the parameters of Ekenstam model are analyzed and determined by handing and testing experimental materials. Then, according to the test data, the Ekenstam optimization model considering shock temperature, shock duration and shock interval is obtained. Finally, the optimized model is verified by experiments. The results show that the optimization model can effectively evaluate the aging life of oil-paper insulation of traction transformer under shock load in the temperature range, which provides a basis and reference for the subsequent related research.

Basic repair and maintenance tasks of industrial machines are usually performed by local service personnel at the location of the component to be maintained. Complex maintenance tasks require an expert who travels to the customer to solve a specific problem. This process is time and cost intensive. Augmented Reality (AR) Remote Assistance offers means to support newcomers on site by guiding personnel through the maintenance process with novel visualizations. This paper describes an Augmented Reality based remote assistance tool for industrial purposes. We present the technology and our implementation approach, as well as the challenges and limitations we have encountered. The potential of the tool was evaluated and analyzed in an industry oriented use case for repairing an industrial PC. The results were compared with a maintenance procedure that was carried out using standard paper repair instructions. Our approach enabled the users to perform complex tasks faster and with fewer errors. Overall, the error rate decreased significantly due to the AR-based remote support. We also found that paper-based instructions are still more efficient in solving simple tasks.

Prologue: This paper is written after numerous focus-group meetings with several types of people/experts of many genders. Statements given under are not meant to be insulting any gender, but these are focus-group observations. If you do not like any such statements, we are sorry in that you have missed the points we are trying to convey. This paper addresses various perceptions on genders that concerns abstract entities such as various disciplines of studies. This paper defines genders for disciplines through historical biases and perceptions – e.g., birth, religion, language, region, brought up, to say a few; these were obtained thru’ several focus-group discussions. However, technologies, such as computers, the World Wide Web (WWW), Moodle, sensor networks, Internet of Things (IoT), Virtualization and Immersion technologies are constantly changing the nature of education and learning. As a consequence, and through a series of arguments, we establish that the genders of many popular disciplines are becoming feminine in nature. We also define two terms, namely, Gender Capital and Gender Capitalization, through which respectively one could possibly define and analyze ways and means by which the changing nature of genders of disciplines can be profitably exploited for the global goodness.

The security of software systems relies so heavily on the use of secrets, ranging from credentials, API keys, and tokens to secret keys for cryptographic security. This paper examines approaches for managing and handling secrets in software development life cycle, focusing on mobile applications where software must be distributed to devices and operate in an untrusted environment. This paper points out the shortcomings in activities related to secrets management and handling in mobile application development life cycle and outlines future directions in this area of research.

Microfluidics allows analyzing small volumes of samples, which makes it an ideal technology to build a point-of-care device. Microfluidic paper-based analytical devices (μPADs) have been used on multiple applications. Paper is promising since colorimetric assays could be read with the naked eyed or a cell phone camera. Here we systematically tested several possible readers for bio-assays that use as a base a μPADs biosensors. Specifically, we tested digital imaging of an assay that produces a change of colors, imaging of a fluorescence-based assay, and an automatic scanning based on an in-house Multispectral-image Reconstruction System for colorimetric assays. We used commercial tests, both chemical and enzyme-based tests; as well as an in house test that used the emerging technology of DNA aptamers. Similarly, we evaluated the advantages and disadvantages of each setup and demonstrate how adaptable, fast, and versatile μPADs analysis can be. s. Finally, we suggest points of consideration to develop commercial point-of-care applications based on μPADs.

Disposable low-cost sensors are essential for the detection of urea for environmental and healthcare applications. In this paper, we proposed a hand-drawn electrode paper chip sensor by utilising the enzyme modified cellulose fibre as a sensing and substrate material. Further modified cellulose fibres increase the impedance measurement stability and facilitate for performing detection. By demonstrating detection of the low-level concentration of urea in the micromolar range, it shows that developed paper chip has excellent potential as a low-cost disposable sensor.

Flexible supercapacitors are considered as a promising candidate for power supplementation in wearable electronics due to their high power density. However, effectively fabricate flexible and low-cost supercapacitor electrodes in a big scale is still a key challenge. Herein we demonstrate a scalable fabrication method for hierarchical electrodes via metalizing air-laid paper and loading with MnO2 as cathode active materials. To be specific, we coat a thin layer of Ni on air-laid paper by magnetron sputtering, then deposit Ni nanocone arrays (NNAs) on the Ni sputtered paper and finally deposit MnO2 on the NNAs to obtain the NNAs@MnO2 paper electrode. The as-prepared paper-based electrode possesses high conductivity and fine wettability, which facilitates the electrons and ions transporting through the conductive network. Additionally, this electrode provides large specific surface area with a hierarchical architecture. Thus the electrode shows high capacitance (451 F/g) and favorable cycle performance (92.9% capacity retention after cycling for 5000 times). By coupling with activated carbon (AC) coated on the NNAs conductive paper as anode, an NNAs paper-based asymmetric supercapacitor is constructed. Benefiting from the high mechanical durability and the 3D hierarchical architecture of the electrodes, the asymmetric supercapacitor exhibits excellent mechanical flexibility and high energy density (26.9 μWh/cm2 at 1.08 mW/cm2). This method can be easily scaled up to produce lightweight and low-cost conductive paper electrodes, making it promising for the application of flexible supercapacitors in wearable electronics.

To realize the detection of pesticide, this study developed a paper-based chip involving a 2D to 3D flow channel and automatic time delay for detecting pesticides. The time delay was controlled by different pullulan concentrations. The 3D channel was fabricated by hot embossing (optimized printing parameters were 28 kg at 80°C, and Advantec No. 1 filter paper was used) and transfer printing the hydrophobic material into the paper. Finally, the limit of the detected concentration of the pesticide was 4 ng/mL, which was achieved using 250 U/mL of acetylcholinesterase (AChE) and 2.5% pullulan solution.

The paper presents the research begin modelling and control of the paper drying. The researches have been generated by the investigations of the industrial paper drying plant. The paper is structured in four parts. In first part they are analysed the references of the drying process, modelling process and control process. The second part presents a detailed description of the drying process and industrial paper drying plant. In this part there are analysed the major operating problems of the plant. The third part represents a author's contribution of paper drying process modelling. The last part is destined to design of paper quality control system.

The purpose of this work is to explore the applicability and effectiveness of deep learning methods for the task------moves recognition in abstract of research paper. We firstly build a large corpus for moves recognition. Then we choose the traditional machine learning method SVM as a benchmark, and develop four moves recognition methods based on DNN, LSTM, Attention-BiLSTM and BERT. Finally, we design two groups of experiments with sample size 10,000 and 50,000 and then compare experimental results. The results show that most of the deep learning methods outperform the traditional machine learning method SVM especially in large-scale sample experiments, in which the BERT with a re-pre-trained model achieves the best results in both groups of experiments. Deep learning methods are proved applicable and effective for moves recognition in research paper abstracts.

Machine learning (ML) has increasingly been adopted in safety-critical systems such as autonomous vehicles (AVs) and industrial robotics. In these domains, reliability and safety are important considerations, and hence it is critical to ensure the resilience of ML systems to faults and errors. On the other hand, soft errors are becoming more frequent in commodity computer systems due to the effects of technology scaling and reduced supply voltages. Further, traditional solutions for masking hardware faults such as Triple-Modular Redundancy (TMR) are prohibitively expensive in terms of their energy and performance overheads. Therefore, there is a compelling need to ensure the resilience of ML applications to soft errors on commodity hardware platforms.We first experimentally assess the resilience of safety-critical ML applications to soft errors. We demonstrate through fault injection experiments that even a single bit flip due to a soft error can lead to misclassification in Deep Neural Network (DNN) applications deployed in AVs, leading to safety violations. However, not all the errors in an DNN will result in serve consequences such as safety violations, and hence it is sufficient to protect the DNN from the ones that do. Unfortunately, finding all possible errors that result in safety violations is a very compute intensive task. We propose BinFI, a fault injection approach that efficiently injects critical faults that are highly likely to result in safety violations, based on the unique properties of DNNs. Finally, we propose Ranger, an approach to protect DNNs from critical faults with minimal performance overheads and no accuracy loss. We will conclude by presenting some of our ongoing work, and the future challenges in this area.

The exchange of academic marks between HEIs (Higher Education Institutions) is mandatory in every student mobility programs (i.e. the EU Erasmus Program) but that process remains to present date with insufficient technological support and the absence of a comprehensive reference model that allows the integration of potential technological solutions for the exchange of academic data with existing Academic Information Systems seems to limit greatly the possibility of adopting solutions of this type referred to in the existing literature. This work addresses this issue, conducting an initial bibliographic review aimed at the identification of the fundamental requirements of such an architecture as well as explores some of the technologies that are showing potential for usage in the safe exchange of academic results between partner HEIs, with particular interest in blockchain technology applied in an educational context. info:eu-repo/semantics/publishedVersion

Objective: We propose a MATLAB-based tool to convert electrocardiography (ECG) waveforms from paper-based ECG records into digitized ECG signals that is vendor-agnostic. The tool is packaged as an open source standalone graphical user interface (GUI) based application. Methods and procedures: To reach this objective we: (1) preprocess the ECG records, which includes skew correction, background grid removal and linear filtering; (2) segment ECG signals using Connected Components Analysis (CCA); (3) implement Optical Character Recognition (OCR) for removal of overlapping ECG lead characters and for interfacing of patients’ demographic information with their research records or their electronic medical record (EMR). The ECG digitization results are validated through a reader study where clinically salient features, such as intervals of QRST complex, between the paper ECG records and the digitized ECG records are compared. Results: Comparison of clinically important features between the paper-based ECG records and the digitized ECG signals, reveals intra- and inter-observer correlations of 0.86–0.99 and 0.79–0.94, respectively. The kappa statistic was found to average at 0.86 and 0.72 for intra- and inter-observer correlations, respectively. Conclusion: The clinically salient features of the ECG waveforms such as the intervals of QRST complex, are preserved during the digitization procedure. Clinical and Healthcare Impact: This open-source digitization tool can be used as a research resource to digitize paper ECG records thereby enabling development of new prediction algorithms to risk stratify individuals with cardiovascular disease, and/or allow for development of ECG-based cardiovascular diagnoses relying upon automated digital algorithms.

We envision a richer support from Virtual Reality (VR) development environments than the one available today. We believe this will be part of an Operating System (OS) for VR applications, since those services should be uniform and widespread for all experiences within a VR system, they are generic enough to be part of any application, and possibly they will not have to be developed from scratch. This position paper explores some of the shortcomings in current technology we are identifying while developing an application for the intervention of kids with ADD (Attention Deficit Disorder), and how these OS services might be defined and used.

This paper describes a user identification method conducted across online social networks (OSNs) using information regarding friends’ locations, in contrast to a conventional method based on the similarity of two display names. This latter method encounters the problem of decreased identification accuracy if a user registers different display names across OSNs. Our proposed method aims at addressing this issue by utilizing information on friends’ locations. We convert location information extracted from an OSN to that of such geographic administrative units as country, state and city, and calculate the weighted occurrence frequency of a location pair on the basis of distance between the pair. This is based on the hypothesis that a friend list relatively rarely includes an account pair whose locations are extremely distant from one another. We calculate a similarity score between two accounts’ weighted occurrence frequencies for each geographic administrative unit. Finally, we identify a user on the basis of individual similarity scores or weighted average scores for a given geographic administrative unit. Evaluation experiments show that our proposed method improves performance over that of a conventional method (accuracy: 83.1%$\rightarrow$91.2%).

International audience; Internet of Things (IoT) is a network where several and various interconnected, smart objects continuously generate alarge amount of data transmitted over Internet. Several efforts and research works in IoT focused on hardware constraints, lowcost, application design, as well as good communication technologies. However, due to the intrinsic characteristics of diversity,heterogeneity, large-scale, dynamic and large volume of data generated and various IoT applications needs, using traditionaldatabase management mechanisms and analytics architectures is not generally suitable. Then, it is challenging to provideefficient IoT data storage and query processing mechanisms for satisfying IoT application needs. This paper identifies the mainspecifications and mechanisms of data and query management for IoT and classifies them. Moreover, this work presentsadvances on data and query management mechanisms on IoT, shows their advantages and limits and discusses the challengingopen research issues that need to be addressed for providing guidelines for further contributions.

We report on THz metamaterials for chemical sensing fabricated on low-loss, plastic, flexible substrates. The metamaterial is bonded to a paper sheet, which is saturated with the liquid to be analysed. Liquids in contact with the metamaterial surface with different refractive indices result in a shift of the metamaterial resonant frequency. This shift in frequency can be detected by measuring its complex transmission using a THz vector network analyser, in the frequency range 0.75–1.1 THz. The sensitivity of the metamaterial is 0.0015 refractive index units for a spectral resolution of 1 GHz which is well achievable with the VNA system.

UmpleOnline is a widely used modeling tool that allows practitioners to create class diagrams, state diagrams and several other model types textually, with the option to edit class diagrams graphically. In this paper we propose how UmpleOnline can be used as a tool to conduct modeling empirical studies. UmpleOnline would be instrumented to allow any of its 180,000 annual visitors to volunteer to participate in one of many studies that would be pre-loaded by any member of the modeling research community. Studies could focus on research questions relating to model quality, modeling strategies, modeling errors or many other things. UmpleOnline would be an ideal vehicle for such studies since it is zero-footprint and has demonstrated high usability.

In this article we are presenting a state of the art in the Artificial Intelligence (AI) and Robotics fields, so as to address the problem of autonomy and integration of autonomous heterogeneous systems for decision making autonomy. This state of the art is followed by the presentation of some avenues addressing the issue in order to lead the autonomy of heterogeneous robotic systems in the naval defence environment possible.

The Pulp, Paper, and Forest Industries Conference (PPFIC) sponsored by the IEEE-IAS Pulp and Paper Industry Committee (PPIC) needs more papers from end-users. In an effort to make the process easier, the authors of this paper offer some suggestions. In general, end-users are interested in hearing papers that address concerns and opportunities they experience in their facilities. An excellent way to develop papers that meet the interests of the various end-users is if the end-users themselves write papers on topics that are of interest to them, and therefore of interest to the wider community. For potential authors, this paper suggests a few guidelines that might help in constructing and presenting a paper.

The industry of disposables has undergone an astronomically immense revolution in this century owing to the diligent lifestyles and technological advancements in its engenderment and manufacturing process. Paper cups are one of the widely used products in disposable industry. It has multi utility options that is it can be acclimated to imbibe water as well as beverages, soups, liquids etc. This paper entirely fixates on incrementing the quality factor of engenderment and manufacturing process of these paper cups by integrating adscititious circuitry to the subsisting machinery to truncate waste of raw materials as well as the per unit cost involved in wastage of electricity. There is a necessity to improvise the quality of overall production parameters using automation techniques. Replacing the whole machinery is a very high costing implementation hence economic feasibility of automation can be achieved by adding an additional circuitry and improving the overall perfoemance. This research work is predicated on utilizing proximity sensors to sense the materials and molded paper cups in front of machinery and minimize the electric wastage through a relay Mechanism assembly. This is a PLC predicated live project example of efficaciously incrementing the overall efficiency of the manufacturing plant

Facebook, Twitter, Instagram, and LinkedIn are all popular online social media sites these days. Everyone uses different social media platforms, from children to adults. The use of these social media applications is increasing, which leads to a rise in social media crime. Here is where the word “fake profiles” comes into play; these fake profiles are responsible for distributing misleading details about a particular user or attempting fraudulent activities with bad intentions. Many researchers have been carried in response to the issue of fake profiles that exist in any social media application. There is research available in different directions to get a real problem solution. This paper summarizes all of the research on fake profile identification in social media platforms. This paper gives survey of work, indicating whether the user profile is fake or real.

Paper dating analysis is an important research direction of document inspection, which is widely used in the inspection and identification of cultural relics and ancient books. This article focuses on the analysis of paper dating in ancient books, and proposes a non-destructive inspection and analysis method based on paper fiber texture images. Aiming at the global stacking morphology of paper fibers and the local features of specific types of fiber morphology, we propose a neural network-based hybrid texture feature extraction and representation method: On the one hand, we use convolutional networks to obtain global features of fiber texture; at the same time, we designed a method of extracting and representing local fiber morphological features based on the attention mechanism. By mixing the above two types of features, we realize the extraction and representation of paper fiber features. Furthermore, we use the GRU(Gate Recurrent Unit) model to establish a paper dating time series model and design a new loss function. In order to verify the method, this paper selects 36 domestic books published from 1950 to 2000, and uses the document checker VSC 6000 to collect paper texture images as a dataset, and verifies the effectiveness of the proposed method on this dataset. Experiments prove that the method proposed in this paper has achieved ideal results in paper dating analysis.

The dirty paper wiretap channel, also referred to as the Gaussian wiretap channel with noncausal channel state at the transmitter, plays an important role in wireless physical layer security. In this paper, the dirty paper wiretap channel is revisited by considering actions on the channel state, i.e., the transmitter generates an action sequence that affects the formation of the channel state. Lower and upper bounds on the secrecy capacity of this model are proposed, and numerical results indicate that the actions on the state help to increase the achievable secrecy rate of the dirty paper wiretap channel. The study of this paper offers a new option for enhancing the secrecy rates of the state-dependent wiretap channel models.

Worldwide electronic waste is one of the emerging problems which can adversely affect the human and environment. The paper based flexible eco-friendly, disposable electronics battery is the excellent way to come up with the above mentioned challenge. In this work we reported the development and optimization of a cost, disposable, biodegradable, miniaturized and lightweight conductive polymer coated exfoliated graphite paper battery. Here, anode contains aluminium foil and cathode is made using electrochemically deposited anthraquinone conductive polymers on exfoliated graphite paper with a concentrated sodium chloride salt, as electrolyte. The battery shows a electrochemical response on by applying 40–50 μL of water and produces a maximum capacity of 235 mAh g−1 along with a superior cyclability of up to 500 cycles at 200.0 mA cm−2 current density. The proposed 3–4 battery connected in series powers a LED during approximately 60–90 seconds. Still continuous effort is going on for battery performance improvement. Obtained results allow to planning potential uses to low power consumptions microelectronics such as pacemakers, cosmetics, wearable biomedical devices, and electronics.

A disposable filter paper based electronic tongue using different conducting polymers is developed in this work. Sensors were prepared using Whatman filter papers of dimensions 6 mm × 5 mm coated with different conducting polymers (polyaniline and polypyrrole, both in doped and de-doped form). Two Ag electrodes were deposited with a separation of 4 mm for AC impedance spectroscopic measurements in the frequency range of 10 Hz – 10 kHz with a 100 mV excitation voltage. The developed sensor was subjected to different concentrations of four basic tastants i.e., salty, sweet, sour and umami. The sensitivity of the sensor was found to be better than the human tongue for all the different tastants. The sensors were also used to differentiate between different water samples and fruit juices, with a promising potential for use in food quality monitoring. Use of principal component analysis on the impedance data aided in formation of clusters, thus distinguishing different types of water samples.

Ionic liquid /chitosan-coated paper showed a large specific gate electric-double-layer (EDL) capacitance of ~3.71 μF/cm2 at 1.0 Hz. The coated paper ITO-based TFT showed a low operating voltage, good electrical properties and high stability. Such flexible low-voltage TFTs is suitable for next-generation low-cost and portable new-concept flexible electronics

Paper-based digital microfluidic biochips (PB-DMFBs) provide a promising solution for microfluidic bioassays. Due to the low-cost substrate material and low demand for complicated manufacturing equipment, PB-DMFBs can be fabricated without foundry. On the flip side, convenience of fabrication allows PB-DMFBs to be fabricated everywhere, which makes it is difficult to manage production and distribution of IP (bioassays). As a result, PB-DMFBs are vulnerable to security threats. IP and its creator, the biocoders, may suffer from infringement. To ensure IP protection, in this paper, we proposed the first Digital Rights Management (DRM) scheme to protect IPs of PB-DMFBs from security threats. A chip-level synthesis algorithm is also presented to realize not only complex biochemical operations but also the demand of DRM.

The insertion of mica barrier between coaxial electrodes results in a larger reduction of leakage current than the use of kraft paper insertion. The reduction is influenced by the barrier position and the testing voltage level. When using the kraft paper, there is a certain voltage level beyond which the characteristic of leakage current as a function of barrier position is relatively the image of that under the voltage level. At this level, the leakage current is almost the same wherever the barrier position. The use of mica insertion tends to shift the symmetry axis of the characteristic curves, meaning higher leakage current level.

Laser-cut paper patterns which are suitable for focusing terahertz radiation are presented. Such designs provide an extremely low-cost route for the prototyping and production of terahertz optical components. Diffractive binary Fresnel lenses have been explored using a multilayer paper stack and a liquid absorption method in order to phase shift THz radiation through paper by the optimum 180° The conventional Fresnel lens design has been extended to produce multiple focal spots and explore alternative shapes (e.g. hexagonal).

Currently, racial oil blotting papers are counted by hand. However, it takes a long time and this is hard work. Hence, an automatic counting system is necessary. In order to achieve this, we developed a cheap system using a webcam. This system firstly captures one image of arranged papers by shifting. Secondly, the paper boundaries are obtained as straight lines by utilizing the proposed image processing. By counting the acquired lines, the system outputs the number of papers. However, the captured image has noises such as the change of illumination and shadows. They make the extraction of the accurate boundaries difficult. For the accurate extraction, optimal parameters of the image processing must be set. Since the prediction of the optimal parameters in advance is difficult, the proposed method adopts genetic algorithm (GA). Also, Hough transformation for the straight line detection is improved. By applying the proposed method, the accurate paper counting is possible. For the experiment, 14 images were captured in various environments using a general webcam. Then, the proposed method was compared to a latest related work. As a result, F-measure of each method was 0.995 and 0.945.

International audience; The design of a dipole antenna printed on a paper substrate is presented in this paper. The antenna which integrates a compact balun is devoted for dual-band 2.4/5 GHz WLAN applications. The antenna is based on a double-side printed multilayer paper substrate and is fed with a coaxial cable for the testing. The simulated results of the whole structure are also presented in detail and compared with the measured performances.

Carbon materials are known to be one of the most suitable platforms for the development of cold electron emitters. Here we explore field emission (FE) performance of so-called graphene paper that is a micrometer-thick foil obtained by stacking chemically exfoliated graphene layers. We find, that shaped into triangular form, graphene paper exhibits competitive FE characteristics, such as highcurrent densitys Table in time, and low threshold fields. In addition, we study the degradation of such graphene-based emitters under high emissions currents and discuss possible application for a transmissiontype X-ray source.

To improve the accuracy of user implicit rating prediction, we combine the traditional latent factor model (LFM) and bidirectional gated recurrent unit neural network (BiGRU) model to propose a hybrid model that deeply mines the latent semantics in the unstructured content of the text and generates a more accurate rating matrix. First, we utilize the user’s historical behavior (favorites records) to build a user rating matrix and decompose the matrix to obtain the latent factor vectors of users and literature. We also apply the BERT model for word embedding of the research papers to obtain the sequence of word vectors. Then, we apply the BiGRU with the user attention mechanism to mine the research paper textual content and to generate the new literature latent feature vectors that are used to replace the original literature latent factor vectors decomposed from the rating matrix. Finally, a new rating matrix is generated to obtain users’ ratings of noninteractive research papers and to generate the recommendation list according to the user latent factor vector. We design experiments on the real datasets and verify that the research paper recommendation model is superior to traditional recommendation models in terms of precision, recall, F1-value, coverage, popularity and diversity.

Tight assembly of stator windings with no insulation paper damage is a manufacturing challenge. We evaluate different sets of parts according to the following parameters: magnet wire thickness, stator slot smoothness, length of the straight magnet wire after the slot end, and type and amount of insulation cap at the end of the slot. These parameters have discrete values with small differences between them. The damage criterion is the decrease of the insulation paper breakdown voltage after assembly/disassembly of parts, assembled in a small set of designed experiments. Parameter values, i.e., levels at individual experiments are set by an orthogonal experiment matrix. Repetition of each experiment provides statistical significance. Data analysis shows that the additive model alone is not sufficient due to the high correlation of the parameters’ influences. We extend the model to include interparameter influences, which we model by adding a virtual parameter. The extended additive model generates parameter values that do not degrade the insulation paper breakdown voltage within the manufacturing process. These values are verified by repetitions of the control experiment.

The modern HPC scientific software ecosystem is instrumental to the practice of science. However, software can only fulfill that role if it is readily usable. In this position paper, we discuss usability in the context of scientific software development, how usability engineering can be incorporated into current practice, and how software engineering research can help satisfy that objective.

Smart infrastructure demands resilient data storage, and emerging applications execute queries on this data over time. Typically, time-series databases serve these queries; however, cloud-based time-series storage can be prohibitively expensive. As smart devices proliferate, the amount of computing power and memory available in our connected infrastructure provides the opportunity to move resilient time-series data storage and analytics to the edge. This paper proposes time-series storage in a Distributed Hash Table (DHT), and a novel key-generation technique that provides time-indexed reads and writes for key-value pairs. Experimental results show this technique meets demands for smart infrastructure situations.

Virtual Reality (VR) and 360 film have caught the attention of audiences and content creators and emerged as a new media, however, the market penetration of VR and head mounted hardware has remained slow despite the availability of more affordable mobile options. This has resulted in some audiences turning to VR cinemas, festivals and out-of-home exhibitions. Creating affordable, scalable VR cinemas presents a number of challenges and many of the decisions taken in both developing and facilitating these curated exhibitions directly impact audience's reception of spatial audio soundtracks. This workshop position paper looks to discuss the potential issues and future solutions in the use of current synchronous exhibition applications, the competing formats, standardised Head Related Transfer Functions, headphone build/colourisation, and the on-boarding process.

Usability and the use of automated static analysis tools in the software development process have been an evolving subject of research in the last decades. Several studies shed light on issues like high false positive rates and low comprehensibility, which hinder tool adoption for even software engineers. Yet, the tools' perceived usefulness and ease of use play a much larger role when it comes to untrained software developers, as is usually the case in scientific software development. In this paper, we outline a multi-stage interview study to learn more about how scientists come to accept and use static analysis tools.

Utilizing the in-situ reducing method, a reduced graphene oxide (rGO) paper for 13~14 um was obtained and exhibits great Terahertz (THz) absorbing capability. The absorption of rGO paper exceeds 43% in the whole frequency band from 0.3~1.2 THz and maximum absorption reaches 59.33% at 1.13 THz. This makes it possible to realize ultra-thin broadband THz absorbing materials.

In order to realize smart factory which is appeared in the concepts of Society 5.0 and Industry 4.0, wireless Internet of Things (IoT) becomes a key technology. Inside of the factory, there are heavy DATA traffics exist between moving/movable machine tools/robots/automated guided vehicle (AGV) with wireless access point (AP) and high speed moving/rotating objects/materials with wireless sensor node (SN). Currently, wireless systems used for wireless IoT are limited such as wireless-LAN/Bluetooth/RFID. Since these system’s frequency bands are limited and narrow, the interference between these systems becomes severe. In this paper, we propose a simplified beam forming wireless IoT communication using novel Wi-Fi backscatter system to notify the existence of SN who wants to send its DATA to AP. For Wi-Fi AP with beamforming function, knowing the numbers of existing SNs in each beam area will be a help for efficient beam control. This paper describes the Wi-Fi backscatter system in which the SNs backscatter the Wi-Fi signal transmitted from the AP then the AP detects the backscatter signals from SNs and know the existing SN’s number in its beam area. Since this backscatter system uses Wi-Fi modulated signal, the separation of SNs’ backscatter signals from AP’s transmitting Wi-Fi signal becomes complicated. This paper also describes the transceiver architecture of AP which reduces the complexity of signal processing and improves the dynamic range of reception.

Anstract- While wireless technologies are common solutions to the last mile problem for IoT systems, challenges exist with devices that are in remote locations, sparse deployments, have power and cost constraints, and low data applications as the cost of wireless and the supporting infrastructure presents barriers to entry. This work presents a last mile solution relying on smartphones to bridge the gap between the data generation device and the internet. A unique, low-power solution is presented based on QR codes and e-paper displays that allows a user's smartphone to carry the power and processing burden for data transmission. Utilizing the persistent nature of e-paper displays with low power requirements, QR codes can efficiently communicate data with minimal power impacts to a device's power budget and create large communication windows for user data pickup, leveraging the power of the smartphone without the need for extensive user training and costly infrastructure.

The increased demand for highly sensitive body sensors have created a range of smart wearables. Strain sensors have evolved from semi-rigid to highly, stretchable, and flexible devices that can conform to the human skin. In contrast to complex conventional fabrication methods, this paper proposes a simple and cost-effective technique that combines stencil printing with kirigami cutting to produce flexible, stretchable, linear, disposable sensors using temporary tattoo paper and conductive carbon paste. Here, two sensor designs (straight line and serpentine) were fabricated and analyzed. The number of carbon-ink coatings were also varied to study the effect of number of coating layers to the sensitivities of the sensor. A total of117 samples were fabricated and tested. When tested on skin, the maximum strain that could be measured was 20% for the straight-line patterned sensors and 35% for the Kirigami structured sensors. Both designs demonstrated good adhesion to skin, are stretchable, and flexible. The best performing designs with the most reliable data were straight-line type sensor with width 9 mm and three-layer carbon ink coatings, and Kirigami sensor with width 8 mm and two-layer coatings of carbon ink. Both sensors exhibited high linearity of 0.9956 and 0.9813, but low sensitivities of 0.25 and 0.28. These sensors have potential applications in the biomedical field.

In the last several years, we published several papers to address the problem of Face Identification. The techniques employed in those articles were implemented in transform domains. The Discrete Cosine (DCT) and the Discrete Wavelet (DWT) Transforms were utilized, either combined or individually, to extract features which form the final model for each participant in a given dataset. In this paper, we highlight significant parts of our previous works in order to give a fair comparison among all approaches. The results included here are for the following datasets: ORL, YALE, FERET, FEI, Georgia Tech, and Cropped AR. Features are DWT, DCT, energy-based selected DCT-DWT, and combined DCT-DWT coefficients while the classifier is Euclidean distance, either squared or with power of one.

In recent year, Graphene has witnessed an increasing demand in diversified domains including in realizing various electronic devices due to its unique electrical and mechanical properties. In place of the conventional cumbersome approaches, recently CO 2 laser induced graphene (LIG) on various substrates, like polymers, paper, cloth, have become a reliable alternative to fabricate such devices. Even though, development of LIG zones on diverse substrate and their optimization and implementation has been reported, a process to manifest single-step, cost-effective and scalabel LIG based flexible electronic devices remains a challenge. Herein, a novel process has been demonstrated for fabricating LIG based flexible electronic device on paper and cloth using a low-power blue laser. First, a porous filter paper and a cotton cloth were soaked in liquid polyimide and phenolic resin-polyvinyl alcohol (PR-PVA) respectively. Subsequently, a 3D printer, loaded with a 2.8 W blue laser diode, was appropriately ablated to form paper-based LIG (P-LIG) and cloth-based LIG (C-LIG), with desired designs and conductivity values. P-LIG and C-LIG zones provide optimum conductivity values of 198.54 S/m and 22.23 S/m respectively. Finally, P-LIG and C-LIG were integrated with the capacitive touch sensor and microcontroller modules, and display, to employ both the devices as flexible touch sensors.

Visions have an important role in guiding and legitimizing technical research, as well as contributing to expectations of the general public towards technologies. In this paper we analyze technical robotics papers published between 1998 and 2019 to identify themes, trends and issues with the visions and values promoted by robotics research. In particular, we identify the themes of robotics visions and implicitly normative visions; and we quantify the relative presence of a variety of values and applications within technical papers. We conclude with a discussion of the language of robotics visions, marginalized visions and values, and possible paths forward for the robotics community to better align practice with societal interest. We also discuss implications and future work suggestions for Responsible Robotics and HRI research.

Nowadays, the usage of smartphones keeps increasing day by day and it is also can be used effectively to increase the computational power and the security along with search and rescue. To maintain the attendance records, several organizations are depending on paper-based attendance. Manually recorded attendance for the employees has produced problems that related to information accuracy and workforce performance efficiency. In this paper, reviewed and discussed various methods, applications and systems that can be used by the employer to monitor their staff attendance using fingerprint, Iris, RFID and GPS. The outcome of this survey is getting knowledge on various techniques that used to record and monitor staff’s attendance.

As the demand for low-carbon and eco-friendly energy is increasing and the use of wearable devices is soaring, the triboelectric nanogenerator (TENG), which can economically harvest energy, is in the spotlight. Among many materials, paper is considered a promising substrate and frame material for self-powered TENG due to its high accessibility, flexibility, and biocompatibility. Here, we present a new structure of foldable paper based TENG (FP-TENG) composed of paper and PTFE/Si-rubber. The double-folded FP-TENG generates voltages and currents of 153 V and 2.2 µA, respectively, and shows excellent durability without signal degradation under 5,000 cycles of external force. A watch strap was manufactured with FP-TENG and integrated with an electronic watch pannel to supply power, and several LEDs were turned on. Therefore, FP-TENG is expected to be utilized as a promising eco-friendly energy source for small electronic devices.

Even current OCR technology has made significant progress with the help of deep learning, rapid identification algorithms for specific information in documents still need elaborate design. In this paper, a lightweight operating framework based on deep neural network is established to deal with the extraction of date and time information from paper worksheets used in transformer station. In the framework, YOLOv4-Tiny is employed to detect the locations of the dates and the time in document images which are mixed with printing and handwritten fonts. Since the handwritten dates in pictures are difficult to segment, a novel lightweight CNN named MobileDateNet is proposed that can recognize the date serially without segmentation. The experimental results show that the identification accuracy of the whole framework reaches 92.1% at the average running speed of 36.5 FPS on an NVIDIA 3090 GPU, ensuring the recognition accuracy and the operating efficiency.

Cloud computing is a new paradigm. In recent years, cloud computing has been a popular model for hosting and providing services, as it has gained great popularity in providing multiple services such as storage and cloud hosting. Moreover, the cloud provides a powerful computing platform that enables many individuals and organizations to perform many tasks such as: use of online storage space, approval on business applications, developing custom computer software, and creating a virtual network environment. In previous years, the number of people using cloud services increased dramatically and a lot of data was stored in cloud computing environments. Meanwhile, data breaches of cloud services are also increasing every year due to hackers who are always trying to exploit security holes in the cloud architecture, so the security problems in these systems are horrific because they store a lot of private and confidential data. In this paper, the authors review security and privacy issues, bottlenecks associated with cloud computing, and the specific security issues in cloud computing layers and vulnerabilities, and how to avoid and control them. This paper helps the reader understand the problems related to cloud computing.

China’s packaging industry has formed a packaging big data system from three aspects: implementing information engineering, building a collaborative symbiosis network platform of packaging information resources, and building an industrial chain knowledge map centered on product chain. Packaging big data visualization design uses big data information acquisition, hierarchical division and management, problem and audience, visual transformation and other thinking modes, and adopts text information visualization, multi-dimensional information visualization, hierarchical relationship visualization and other technologies to realize the visual presentation of packaging industry data information. This paper analyzes the network data, extracts the keywords related to the key elements, and then analyzes the construction method of product paper packaging container automation system based on the keywords extraction algorithm. On the one hand, it emphasizes the importance of big data in online shopping commodity packaging design; on the other hand, it explores new ideas and methods of online shopping commodity packaging design through the application of big data in online shopping commodity packaging design.

As a material, cellulose/paper has attracted significant attention for its fibrous and bendable properties. Paper is a renewable resource with the most common forms coming from trees. This brief article describes efforts to create electronics "on" and "in" paper. Examples of electronics on paper include touch sensors and cold plasma-based sanitizers. The skin-like touch sensors use capacitance and patterned resistive networks for passive, scalable sensing with a reduced number of interconnects. When touched or wetted with water, the interdigitated electrodes in the resistive networks detect significant changes in electrical impedance. The plasma generators with layered and patterned sheets of paper use a simple and flexible format for dielectric barrier discharge to create atmospheric plasma without an applied vacuum. Examples of electronics in paper include sheets with tunable electrical conductivity and piezoresistive force sensors, along with functionalized paper-based electrodes capable of detecting small proteins and clinically relevant biomarkers. These papertronic devices have the potential to supply multi-functionality to new forms of smart bandages, skin-like sensing, food packaging, and robotic sensing and actuation.

We report an eco-friendly and easy-going way of fabricating a vast range of passive electronic components and low pass filters. This is achieved by directly writing graphite on paper and cutting and pasting aluminum foil and copper tape on different substrates. Resistance was achieved from 4 kΩ to MΩ(s) by penciling several sustainable layers of different graphite to clay content pencils. Capacitors of capacitance from 2 pF to 10 μF are fabricated using graphite, aluminum foil, and copper tape as conductive materials on printing A4, baking, and butter paper as substrate and dielectric materials as for parallel plate capacitors. Pencil on paper-based interdigitated capacitors is reported to achieve lower capacitance and higher cut-off frequency values of low pass filters. Resistors and capacitors of different values are fabricated in a plane to design low pass filters with 100 Hz – 2 MHz cut-off frequency range. All the components and circuits are fabricated from foldable, eco-friendly, and readily available paper materials as substrates. These paper-based components are helpful for foldable electronics, foldable printed circuit boards, and soft robotics.

Industrial control systems have strict requirements for time-sensitive applications and clock synchronization services. Performance of such applications is adversely impacted by packet delays and jitters. The impact is especially critical in process industries due to harsh environmental conditions. In this paper, we analyze delays and jitters to assess the performance of time-sensitive applications. To this end, we captured and analyzed round trip delay data retrieved from a paper factory. Analysis shows that a sub-millisecond level average delays and the jitters derived from the observed data are sufficient to meet the minimum 10ms update frequency required for most critical control applications. Moreover, the filtered delay variations at the end devices are less than the recommended 150us, which guarantees an adequate time synchronization accuracy in the factory network. Besides, this analysis can provide significant insights into performance bottlenecks for factory applications.

This contribution describes the feasibility of a wireless sensor that uses Micro-Electro-Mechanical Systems (MEMS) on cellulose materials. In particular, the focus is on a paper-aluminum (paper-Al) bimorph cantilever formed by an Al foil glued on top of a paper layer. It is well known that paper relaxes its fibers in the presence of humidity. This means that the length of the paper layer increases (respect to the Al layer) when humidity is absorbed, thus determining the cantilever deflection. Such a mechanism is used to control a capacitor formed by the cantilever itself (Al layer) and by a metal plate printed on a PCB. The capacitor is then applied to a planar notch filter whose resonant frequency is hence determined by the humidity. The preliminary experiments show that the developed circuit features a 2.45 GHz center frequency and a sensitivity of about 3.7 MHz ner each nercent of relative humidity variation.

Forgery of paper invoices and certificates negatively causes huge economic loss every year. In the molding process of paper, plant fibres inside will distribute randomly and form the unique microscopic surface. Accordingly, forensic researchers have presented many techniques to build its feature descriptor for paper anti-counterfeiting. Among those methods, normal vector field and reconstructed surface based on multi-view photos captured by mobile camera have indicated incredibly effectiveness and practicality. However, the inefficiency of existing models using mobile camera is the neck in real time detection scenarios. In this paper, we focus on the efficient microstructure orientation estimation of paper surface for authentication. To address this problem, we investigate the reflection characteristics of rough surface and quantify the light attenuation accurately. Then, we model the entire propagation path of light emitted by flash, and exploit single photo captured by mobile camera to reconstruct microscopic inclination based on beam energy loss. Reduction of required pictures significantly enhances forensics efficiency. Through comparison experiments, we demonstrate that our proposed method can be used for paper discrimination effectively with speedy feature extraction.

In this paper we propose to implements blockchain technology for Internet of Things (IoT) networks that use Practical Byzantine Fault Tolerance (PBFT) consensus algorithm. To eliminate the reliance on a single leader and improve performance, we propose to allow multiple leaders to propose request batches independently and, possibly, concurrently, by using different overlay networks. Nodes participate in parallel consensus rounds without contention, and they only contend with others to reserve the next available spot for the atomic insertion of a new transaction batch or block into the replicated blockchain ledger. We develop an analytical model for the multiple leader PBFT ordering service by using a Discrete-time Markov chain. Our evaluations show that our model outperforms the original multiple entry point PBFT protocol in a wide range of parameter values, and that it scales well with the number of orderer nodes in the PBFT committee and block arrival rate.

Long-term evolution in unlicensed spectrum (LTE-U) can make use of centralized scheduling, interference coordination and other technologies to achieve better spectrum efficiency (SE). As the evolution of cloud computing, mobile edge computing (MEC) sinks the computing and storage capacity from the centralized data center to the edge of the network, which is the key technology to achieve low delay and high speed. However, the traditional centralized scheme in small cell networks (SCNs) structure will bring huge signal overheads. In order to adapt to the complex and changeable network system, this paper proposes a distributed resource and power allocation scheme under MEC environment, which enables small base stations (SBSs) to work autonomously. The SBSs need only little information exchange through the information cloud (IC) and finally obtain the global optimal SE. Simulation results confirm the correctness and effectiveness of the proposed scheme, and demonstrate the superiority of the distributed scheme over the centralized scheme.

The pervasive use of software systems and current threat environment demand that software systems not only survive cyberattacks, but also bounce back better, stronger, and faster. However, what constitutes a modern software system? Where should the security and resilience mechanisms be-in the application software or in the cloud environment where it runs? In this concept paper, we set up a context to pose these questions and present a roadmap to answer them. We describe challenges to achieving resilience and beyond, and outline potential research directions to stimulate discussion in the workshop.

Vitamin D deficiency has been linked to several diseases and adverse outcomes including: diabetes, cardiovascular diseases, and even cancer. At present the clear majority of vitamin D testing is performed in large-scale laboratories at the request of a physician as part of an annual panel of blood tests. Here we present a paper-based microfluidic system for rapid quantification of vitamin D levels on a portable platform. The system consists of a smartphone accessory, an app, and a test strip that allows the colorimetric detection of 25-hydroxyvitamin D using a novel gold nanoparticle-based immunoassay. We show that the system can be used to accurately measure physiological levels of 25-hydroxyvitamin D with accuracy better than 25 nM and a precision of 10 nM. We compare our system with well-established ELISA test kits for serum samples of unknown concentration and demonstrate equivalency of the results.

Heuristic evaluation is a usability inspection method that has been adapted to evaluate visualization applications through the development of specific sets of heuristics. This paper presents an empirical study meant to assess the capacity of the method to anticipate the usability issues noticed by users when using a visualization application. The potential usability problems identified by 20 evaluators were compared with the issues found for the same application by 46 users through a usability test, as well as with the fixes recommended by the experimenters observing those users during the test. Results suggest that using some heuristics may have elicited potential problems that none of the users noticed while using the application; on the other hand, users encountered unpredicted usability issues.

Research on spatio-temporal visualization is driven by the development of novel visualization and data aggregation techniques. Yet, only little research is conducted on the systematic evaluation of such visualizations. Evaluation of such technology is often conducted in real-life settings and thus lacks fundamental requirements for laboratory-based replication. Replication requires other researchers to independently conduct their own experiments to verify your results. In this position paper, we discuss the requirements for replication studies of spatio-temporal visualization systems. These requirements are often impossible to achieve for highly contextual visualizations such as spatio-temporal visualizations. We argue that reproducibility—allowing other researchers to validate your findings from your data—is a better aim for highly contextual visualizations. We provide a sample workflow to ensure reproducibility for spatio-temporal visualization and discuss its implications.

Tukey emphasized decades ago that taking exploratory findings as confirmatory is “destructively foolish”. We reframe recent conversations about the reliability of results from exploratory visual analytics—such as the multiple comparisons problem—in terms of Gelman and Loken’s garden of forking paths to lay out a design space for addressing the forking paths problem in visual analytics. This design space encompasses existing approaches to address the forking paths problem (multiple comparison correction) as well as solutions that have not been applied to exploratory visual analytics (regularization). We also discuss how perceptual bias correction techniques may be used to correct biases induced in analysts’ understanding of their data due to the forking paths problem, and outline how this problem can be cast as a threat to validity within Munzner’s Nested Model of visualization design. Finally, we suggest paper review guidelines to encourage reviewers to consider the forking paths problem when evaluating future designs of visual analytics tools.

In this paper, we discuss the challenges one faces when evaluating authoring systems developed to help people design visualization for communication purposes. We reflect on our own experiences in evaluating the visualization authoring systems that we have developed as well as the evaluation methods used in other recent projects. We also examine alternative approaches for evaluating visualization authoring systems that we believe to be more appropriate than traditional comparative studies. We hope that our discussion is informative, not only for researchers who intend to develop novel visualization authoring systems, but also for reviewers assigned to evaluate the research contributions of these systems. Our discussion concludes with opportunities for facilitating the evaluation and adoption of deployed visualization authoring systems.

Replications are rare in visualization research, but if they were more common, it is not unreasonable to believe that they would show a similar rate of unreproducible results as in the psychological and social sciences. While a replication crisis in visualization research would be a helpful wake-up call, examining and correcting the underlying problems in many studies is ultimately more productive.In this paper, we survey the state of replication in visualization research. We examine six threats to the validity of studies in visualization and suggest ways to address them. Finally, we describe possible models for publishing replications that satisfy the novelty criterion that can keep replications from being accepted.

Machine learning (ML) components are increasingly adopted in many automated systems. Their ability to learn and work with novel input/incomplete knowledge and their generalization capabilities make them highly desirable solutions for complex problems. This has motivated the inclusion of ML techniques/components in products for many industrial domains including automotive systems. Such systems are safety-critical systems since their failure may cause death or injury to humans. Therefore, their safety must be ensured before they are used in their operational environment. However, existing safety standards and Verification and Validation (V&V) techniques do not properly address the special characteristics of ML-based components such as non-determinism, non-transparency, instability. This position paper presents the authors' view on the safety of automotive systems incorporating ML-based components, and it is intended to motivate and sketch a research agenda for extending a safety standard, namely ISO 26262, to address challenges posed by incorporating ML-based components in automotive systems.