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There is a relative lack of research on the development of creepage discharge in aged oil-paper insulation subjected to AC-DC combined voltage in converter transformers. In this study, based on the physical and chemical properties of oil-paper, we propose a sphere-plate electrode model to study the creepage discharge parameters and characteristic spectra of aged oil-paper subjected to AC-DC combined voltage. The results show that the creepage discharge inception voltage of aged oil-paper is related to the AC voltage component of the AC-DC combined voltage. However, when the DC voltage component is 60 kV, the flashover phenomenon was found to occur in one of the severely aged samples before the AC voltage was applied. Despite being subjected to the same DC voltage, the flashover phenomenon did not occur in three other samples aged to different degrees. Large-amplitude discharges were found to appear earlier in the severely aged samples. At the same creepage discharge stage, as the aging time of the oil-paper increased, the number of large-amplitude discharges was found to rapidly increase, and the time interval between adjacent discharges was found to gradually decrease. At each stage of the creepage discharge, the small-amplitude discharge has a “hump” shaped distribution. The larger the DC voltage component, the shorter the endurance time of aged oil-paper, and the more severe the damage to the oil-paper. The DC voltage component was found to have an accelerating effect on the development of creepage discharge in aged oil-paper insulation.

Water-activated paper-based batteries are expected to be low-cost disposable power sources for paper-based sensor applications. In this study, a disposable paper-based battery was developed. The battery used activated carbon powder loaded on a carbon sheet as the anode. The cathode was coated directly on a paper filter to fabricate an integrated proton exchange membrane cathode. Copper (II) chloride mixed with multiwalled carbon nanotube (CuCl2/CNT) was used as the cathode. Water was injected into the anode electrode to activate the battery. The maximum power density of 134. 6 μ W /cm2 was obtained with the anode loaded 17 mg cm−2 activated carbon powder. The power output of the battery is proportional to the amount of activated carbon loaded on the anode.

As a new type of energy harvesting device, the triboelectric nanogenerator (TENG) can convert mechanical energy into electrical energy effectively. Paper-based materials have gained considerable attention for use in flexible energy harvesting device applications because of their flexibility, environmental friendliness (i.e., they are biodegradable and renewable), and foldability. This work proposes a strategy to use cellulose fibers layer as a spacer of paper-based triboelectric nanogenerator (P-TENG). The P-TENG consists of a three-layer fiber material and a copper electrode. The three-layer fiber material comprises nylon, cellulose, and polypropylene, where the cellulose fiber layer contains millimeter-sized holes and is used as a spacer. Because of its attractive cuttability and flexibility properties, the P-TENG can be applied on a large scale in complex environments (e.g., sports fields, driving training fields) to detect signal changes caused by external pressure This type of device has great potential for application to the large-scale TENG field and may provide a new solution for TENG industrialization.

This paper presents a broadband, simple, re-useable and low-cost approach for noninvasive sweat monitoring using a passive microwave circuit and a cellulose filter paper as a superstrate. The proposed sensor is composed of filter paper with the ability to absorb the sample liquid under test (LUT) placed on top of a coplanar waveguide (CPW) transmission line. Various samples of sodium chloride (NaCl) solutions with concentrations in the range of 0.01-2 mol/L and models of artificial sweat are used to test the proposed sensor. The difference in transmission coefficient (S21) between dry and wet states is used to determine the concentrations of tested solutions in the band of 1-6 GHz. The sensor detects concentrations as low as 0.01 mol/L (0.58 g/L) and quantities as low as 137 μL with a maximum sensitivity of 46.7 dB/g/L. The proposed sensor presents a simple approach to sample and characterize liquids with enhanced sensitivity and consistent performance using microwave signals.

Trap plays an important role in the charge transportation of three-layer oil-paper and the investigation of trap parameters at different degradation degree is of great significance for further research of the partial discharge (PD) mechanism. This article considers the turn-to-turn structure of on-board traction transformer. A defect model of three-layer oil-paper insulation was designed for PD test. The PD degradation samples are selected from the inception of PD to the breakdown of PD to study the characteristics of surface potential decay on degradation samples by using isothermal surface potential decay method. Given that, the trap distribution at different degradation stages was calculated and its influence on PD characteristics was investigated. The result shows that AC fluctuation voltages caused by inter-harmonic has a great influence on PD distribution, surface charge distribution and trap distribution. With the increase of degradation, the decay rate of surface potential increases and the decay rate of AC fluctuation voltages is larger than that pure AC. And also, the number of shallow trap with AC fluctuation voltages is larger than that with pure AC. The rate of free charge increases with the number of shallow trap increasing. More free electrons involves in the process of PD, accelerating the aging rate of three-layer oil paper samples. Therefore, it can be concluded that surface charge and trap distribution are helpful to clarify PD mechanism.

Insulated tubular busbar is a new type of current-carrying equipment with excellent performance. However, the research on this equipment is insufficient because of the short application and the lack of technical digestion, which has resulted in many accidents. In this paper, the full-scale model of epoxy-impregnated-paper insulated tubular busbar with bubble defects was designed and produced, its electrical breakdown process was investigated by withstand voltage test. In the experiment, the failure mode of breakdown caused by gas expansion was found for the first time. The research showed that the electrical-mechanical breakdown process could be divided into two stages: gas increase stage and breakdown threshold stage. The research also obtained the characteristics and the change criterions of the two stages. The gas in the bubble defects generated from epoxy decomposition which caused by partial discharge. When the gas pressure exceeds the critical fracture toughness of the bubble defects wall, the unstable crack extension occurs, therefore, improving the ability about resistance to partial discharge of epoxy resin or improving the fracture toughness of epoxy resin by modifying would enhance the breakdown performance of insulated tubular busbar. The result also has reference significance for other epoxy-impregnated-paper insulated electrical equipment.

This paper presents the design and analysis of a paper-based chipless RFID sensor for wetness content measurement in plant leaves. The sensor is designed using a passive microwave resonator to measure the ambient physical parameter. The resonator is designed with a rectangular loop inductively coupled with an interdigital capacitor. The experimental analysis of the designed sensor is illustrated here to prove its efficacy. The resonator provides adequate backscattered signal for wireless measurement in the microwave frequency band. When interrogated with a couple of UWB antennas and a VNA, it yields accurate leaf wetness response of the plant. The commercial competence of this sensing device is validated through its experimental analysis on three different types of leaf samples. This sensor is suitable for plant health monitoring in any small-scale gardening applications such as nurseries and greenhouses.

The low frequency section of frequency domain spectroscopy (FDS) of oil-paper insu- lation system can effectively reflect the ageing state and moisture of the oil-immersed paper. Meanwhile, steady-state insulation resistance is the one of indexes for the condition of transformer. In actual measurement, these two both are time-consuming and poor accessibility, thereby restraining their field applications. Aim at this problem, this paper analyses the polarization process of the oil-paper insulation in transformer, and adopts a low frequency equivalent circuit model for the oil-paper insulation to characterize the polarization process at low frequency. The simulated annealing particle swarm optimization (SAPSO) algorithm is proposed to identify the parameters in equivalent circuit, which are affected by change of insulation state. Compared with the experimental results, the errors of the steady-state insulation resistance and the tan δ below 10-3 Hz, which are calculated by the identified parameters, are less than 2.5%. This method can avoid the influence from external environment and reduce the measurement time. The time and frequency domain parameters calculated can provide reference for the ageing assessment of oil-immersed paper.

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%.

Oil-immersed insulation paper (OIP) bushing is one of the most important equipment in power transmission and distribution systems. Moisture is one of the most serious factors that affect the insulation status of OIP bushing. In this paper, the OIP bushing was assumed to be in a stable and simplicity condition, and then the transient moisture distribution of capacitor core and its effects on the electric field were studied. First, by dissecting a 110 kV OIP bushing, the specific sizes for modelling were obtained. Afterwards, a moisture diffusion model for OIP bushing was established based on COMSOL Multiphysics software, and it was also verified by moisture diffusion experiment. Then, the moisture distribution for different conditions were obtained and analyzed. Finally, a model for the electric field of OIP bushing was established, and then the effects of moisture on the electric field were studied.

The aging of the transformer oil-paper insulation distributes spatially, which results in changes in paper resistivity in different regions. This paper establishes an iterative inversion algorithm using the finite element method to calculate the oil-immersed paper resistivity in different regions of a transformer. This algorithm sets the transformer dielectric loss factor tan δ at low frequency, the dielectric parameters of the transformer oil as inputs and the oil-immersed paper resistivity as output. The resistivity obtained from inversion can be used as a reference to access the insulation state of the oil-paper insulation. This paper aims at achieving the nondestructive detection of the partial state of the oil-paper insulation.

Transformer insulation paper is a key indicator for transformer remaining operational life. Paper decomposition is evaluated using the degree of polymerization (DP) which calls for samples of insulation paper from operating transformers. Since collecting such paper samples is extremely difficult, other indicators have been used to indirectly reveal the DP value of insulation paper. This includes dissolved gases in transformer oil such as carbon oxides and hydrocarbon gases, furan compounds, methanol, ethanol, and moisture along with some oil characteristics such as interfacial tension. However, for the same oil sample, these individual parameters lead to different DP values. This is attributed to the lack of accuracy of the established mathematical and artificial intelligence models correlating DP with each of the above mentioned individual parameters. This paper presents a self-learning method to estimate the DP value of transformer insulation paper based on multiple transformer oil aging parameters. The proposed method comprises data processing, fuzzy c-means and linear regression. Results reveal that estimating the DP value based on multiple aging parameters is more accurate than estimating it using one single parameter as per the current practice. The proposed method not only helps to understand the correlation between multiple oil aging parameters and the DP value of paper insulation, but also promotes the establishment of more accurate life assessment models for power transformers based on these oil aging parameters.

Globally, the recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields, including economic, education, and scientific research. Different empirical studies have shown that the recommender systems are more effective and reliable than the keyword-based search engines for extracting useful knowledge from massive amounts of data. The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation. Scientific paper recommendation aims to recommend new articles or classical articles that match researchers' interests. It has become an attractive area of study since the number of scholarly papers increases exponentially. In this paper, we first introduce the importance and advantages of the paper recommender systems. Second, we review the recommendation algorithms and methods, such as Content-based, collaborative filtering, graph-based, and hybrid methods. Then, we introduce the evaluation methods of different recommender systems. Finally, we summarize the open issues in the paper recommender systems, including cold start, sparsity, scalability, privacy, serendipity, and unified scholarly data standards. The purpose of this survey is to provide comprehensive reviews on the scholarly paper recommendation. Refereed/Peer-reviewed

D0bleaching wastewater from E. globulus Kraft pulping industry was treated by Fenton and photo-Fenton processes. The aim was to optimize the operational conditions for adsorbable organic halides (AOX) removal, namely oxidant concentration, [H2O2], catalyst concentration, [Fe2＋], and treatment time, using the central composite experimental design (CCED) tool. Temperature and pH were set at 60 ºC and 2, respectively, which are similar to the natural values of the D0bleaching wastewater. Both processes showed potential to remove AOX from D0with 177 - 178 mM H2O2 and 10 min reaction time. Maximum AOX removal was 85 % for the Fenton process with 8.5 mM Fe2＋, and 95 % for the photo-Fenton process with 2.0 mM Fe2＋ and UV irradiance 142 W.m− 2. For both methods, the only statistically significant variable (p=0.05) was the concentration of oxidant, [H2O2]. Keywords: AOX, Bleaching wastewater, CCED, Fenton, Photo-Fenton, Pulp and paper industry

This article adds more information to the problem of natural ester use as an electroinsulating fluid in cellulose paper-oil systems, e.g., for use in power transformers. An accelerated thermal aging (120, 140 and 160 °C) of samples consisting of cellulose paper (transformerboard), a treated natural ester (filtered, basic Al2O3, 0.53% DBPC), a copper plate and moisture was studied. Research was especially focused on the impact of moisture on the aging of the above system. Samples with three different oil moisture levels (80, 143 and 305 ppm water content) were subjected to thermal aging to display the change in a selection of properties (tanδ, acid number, water content). For a study of the polarization effects, broadband dielectric spectroscopy (BDS) was performed to observe the complex permittivity and conductivity dependencies on the temperature and frequency (±30 °C, 0.01-107 Hz). Havriliak-Negami (H-N) diagrams were used to further understand the results. The degradation products during thermal aging were recognized by Fourier transform infrared (FT-IR) spectroscopy. Hydrolysis and hydrogenation occurred in the insulating system with a natural ester aged by elevated temperatures, which is in contrast to CO2 formation in the case of electric aging. The results showed an increase in the acid number, dissipation factor, and number of hydrolysis and hydrogenation products. Furthermore, changes in polarization were observed as a consequence of the thermal aging of paper-natural ester insulation system with the presence of copper and moisture.

© 2013 IEEE. With the rapid growth of scientific publications, it is hard for researchers to acquire appropriate papers that meet their expectations. Recommendation system for scientific articles is an essential technology to overcome this problem. In this paper, we propose a novel low-rank and sparse matrix factorization-based paper recommendation (LSMFPRec) method for authors. The proposed method seamlessly combines low-rank and sparse matrix factorization method with fine-grained paper and author affinity matrixes that are extracted from heterogeneous scientific network. Thus, it can effectively alleviate the sparsity and cold start problems that exist in traditional matrix factorization based collaborative filtering methods. Moreover, LSMFPRec can significantly reduce the error propagated from intermediate outputs. In addition, the proposed method essentially captures the low-rank and sparse characteristics that exist in scientific rating activities; therefore, it can generate more reasonable predicted ratings for influential and uninfluential papers. The effectiveness of the proposed LSMFPRec is demonstrated by the recommendation evaluation conducted on the AAN and CiteULike data sets.

Oil-paper insulation will inevitably endure impulse voltage with a superimposed dc voltage (superimposed voltage) because of introduced lightning or switching, which can induce charge accumulation and trigger flashover during the operation of a converter transformer. Temperature rise is also a nonnegligible factor that can significantly influence the performances of oil-paper insulation. This paper aims to reveal the effects of ambient temperature and superimposed voltage on surface charge and flashover behaviors in an oil-paper insulation system. Surface potential decay (SPD) experiments were performed under superimposed voltage with various polarity and amplitude combinations and at the temperature ranging from 20 °C to 80 °C. The results show that the initial surface potential and decay rate increase as the amplitude of the impulse voltage increases at 20 °C. The initial surface potential declines, and the process of SPD is accelerated at higher temperatures because of the increased concentration of shallow traps. Subsequently, flashover tests were conducted under superimposed voltage. It is found that flashover occurs after applying superimposed voltages even with a rather low dc voltage. In addition, the dc voltage component is primarily responsible for flashover. Weibull results also indicate that it is prone to trigger flashover at higher temperatures, because thermal excitation helps more carriers to escape from deep traps and participate in the process of flashover. Accordingly, the insulation characteristics of oil-paper system can be significantly influenced by superimposed voltage and temperature, which should draw great concern among the power grid.

With the rapid growth of scientific publications, research paper recommendation which suggests relevant research papers to users can bring great benefits to researchers. In this paper, we focus on the problem of recommending conference papers to the conference attendees. While most of the related existing methods depend on the content-based filtering, we propose a unified conference paper recommendation method named $CPRec$ , which exploits both the contents and the authorship information of the papers. In particular, besides the contents, we exploit the relationships between a user and the authors of a paper for recommendation. In our method, we extract several features for a user-paper pair from the citation network, the coauthor network, and the contents, respectively. In addition, we derive a user’s pairwise preference towards the conference papers from the user’s bookmarked papers in each conference. Furthermore, we employ a pairwise learning to rank model which exploits the pairwise user preference to learn a function that predicts a user’s preference towards a paper based on the extracted features. We conduct a recommendation performance evaluation using real-world data and the experimental results demonstrate the effectiveness of our proposed method.

Methanol is regarded as an available indicator to analyze the aging condition of cellulose insulation. However, the diffusion mechanism of methanol molecules in the paper-oil insulation system is still unclear, since it cannot be explored by using only experiments. Given this issue, the molecular dynamics simulations were performed to investigate the diffusion mechanism of methanol molecules. In the current work, the mean square displacement of methanol during the diffusion process was calculated and analyzed, as well as its trajectory tracking. Then, the research on interaction energies and hydrogen bonds in paper/oil system were conducted. Finally, the effect of temperature on the diffusion of methanol molecules was also studied. Findings revealed that the diffusion of methanol in cellulose insulation is faster than that in insulating oil, besides, the presence of hydrogen bonds affects the diffusion rate of methanol molecules in cellulose insulation and insulating oil. Thus, the present findings could support the investigation of the diffusion mechanisms of methanol molecules, by which the aging condition evaluation of cellulose insulation could be also promoted.

Over the decades, the immense growth has been reported in research publications due to continuous developments in science. To date, various approaches have been proposed that find similarity between research papers by applying different similarity measures collectively or individually based on the content of research papers. However, the contemporary schemes are not conceptualized enough to find related research papers in a coherent manner. This paper is aimed at finding related research papers by proposing a comprehensive and conceptualized model via building ontology named COReS: Content-based Ontology for Research Paper Similarity. The ontology is built by finding the explicit relationships (i.e., super-type sub-type, disjointedness, and overlapping) between state-of-the-art similarity techniques. This paper presents the applications of the COReS model in the form of a case study followed by an experiment. The case study uses InText citation-based and vector space-based similarity measures and relationships between these measures as defined in COReS. The experiment focuses on the computation of comprehensive similarity and other content-based similarity measures and rankings of research papers according to these measures. The obtained Spearman correlation coefficient results between ranks of research papers for different similarity measures and user study-based measure, justify the application of COReS for the computation of document similarity. The COReS is in the process of evaluation for ontological errors. In the future, COReS will be enriched to provide more knowledge to improve the process of comprehensive research paper similarity computation.

Accurate modeling and simulation of electric field transients in HVDC cables is an important support to optimize insulation system design and to evaluate the influence of voltage transients and steady-state conditions on accelerated ageing mechanisms and insulation reliability. Traditionally, field models considering time-independent permittivity and conductivity are used, but this approach neglects polarization mechanisms and charge trapping-detrapping phenomena. This article includes polarization dynamics in the field model and shows that its impact on transient electric field simulations in HVDC paper-insulated cables can be significant. A method is presented to infer the model parameters from experimental polarization and depolarization current measurements.

Triboelectric nanogenerators (TENGs) have been investigated as a promising methodology to harvest mechanical energy into electricity. The matching impedance and the transient property of TENGs are important for their practical application. In this work, we proposed novel paper-based methodology for investigation of TENGs. First, we propose a novel method for triggering transience of pencil-on-paper (POP)-TENGs using household microwave oven and commercial graphite pencil. Moreover, a fast, simple and cost-effective approach for measuring the matching impedance of TENG based on paper variable resistor is proposed. The results of this work are beneficial for simple, fast and cost-effective functionalization of TENGs. Keywords: Triboelectric nanogenerator (TENG), Matching impedance

We present a novel implementation of a Rock-Paper-Scissors (RPS) game interaction with a social robot. The framework is tailored to be computationally lightweight, as well as entertaining and visually appealing through collaboration with designers and animators. The fundamental gesture recognition pipeline employs a Leap motion device and two separate machine learning architectures to evaluate kinematic hand data on-the-fly. The first architecture is used to recognize and segment human motion activity in order to initialize the RPS play, and the second architecture is used to classify hand gestures into rock, paper or scissors. The employed tabletop robot interacts in the RPS play through unique animated gestural movements and vocalizations designed by animators which communicate the robot's choices as well as cognitive reflection on winning, losing and draw states. Performance of both learning architectures is carefully evaluated with respect to accuracy, reliability and run time performance under different feature and classifier types. Moreover, we assess our system during an interactive RPS play between robot and human. Experimental results show that the proposed system is robust to user variations and play style in real environment conditions. As such, it offers a powerful application for the subsequent exploration of social human-machine interaction.

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.

This paper presents a sealed ageing study of palm oil (PO) and coconut oil (CO) in the presence of insulation paper. The type of PO under study is refined, bleached, and deodorized palm oil (RBDPO) olein. Three different variations of RBDPO and one sample of CO are aged at temperatures of 90 °C, 110 °C, and 130 °C. The properties of RBDPO and CO as well as paper under ageing are then analysed through dielectric and physicochemical measurements. It is found that the effect of ageing is not significant on the alternating current (AC) breakdown voltages and relative permittivities of RBDPO and CO. There is a slight increment trend of the resistivity for CO, while for all of the RBDPO, the resistivity slightly decreases as the ageing progresses. Only CO shows an apparent reduction of the dielectric dissipation factor. Throughout the ageing time, the acidities of all of the RBDPO and CO remain at low level, while the moisture in oils decreases. The tensile index (TI) of the papers for all of the RBDPO and CO retain more than 50% of the TI. A significant increment of the paper ageing rates of all of the RBDPO and CO is observed at an ageing temperature of 130 °C.

In this paper, we present a new scheme for implementing virtual keyboards, which uses only two to four motion-recognition rings per hand and a two-dimensional keyboard template (e.g., an A4 size paper with printed key positions). It has the benefit of portability, customizability, and low-cost when compared with existing approaches. Essentially, we have shown that wearing two wireless IoT rings on the middle phalanges of two fingers of each hand, users can input the alphabetic characters into a computing device by typing on a flat paper on a desk, and potentially in mid-air. We have demonstrated that two rings are sufficient in capturing the gestures and motions of all fingers in a typing hand for keystrokes recognition. A single wireless IoT ring, which weighs 7.8 grams, consists of a Bluetooth low energy (BLE) unit, a micro inertial measurement unit (mIMU), and a cell battery. The 3-axes attitude angles and the Z-axis acceleration of each ring are adopted as the features for keystroke recognition. The overall keystroke recognition accuracy rate can reach as high as 94.8% when two IoT rings are worn by a user on each hand; this accuracy rate increases to 98.6%, when four rings are worn on each typing hand.

Most existing studies and public datasets for handwritten Chinese text recognition are based on the regular documents with clean and blank background, lacking research reports for handwritten text recognition on challenging areas such as educational documents and financial bills. In this paper, we focus on examination paper text recognition and construct a challenging dataset named examination paper text (SCUT-EPT) dataset, which contains 50 000 text line images (40 000 for training and 10 000 for testing) selected from the examination papers of 2 986 volunteers. The proposed SCUT-EPT dataset presents numerous novel challenges, including character erasure, text line supplement, character/phrase switching, noised background, nonuniform word size, and unbalanced text length. In our experiments, the current advanced text recognition methods, such as convolutional recurrent neural network (CRNN) exhibits poor performance on the proposed SCUT-EPT dataset, proving the challenge and significance of the dataset. Nevertheless, through visualizing and error analysis, we observe that humans can avoid vast majority of the error predictions, which reveal the limitations and drawbacks of the current methods for handwritten Chinese text recognition (HCTR). Finally, three popular sequence transcription methods, connectionist temporal classification (CTC), attention mechanism, and cascaded attention-CTC are investigated for HCTR problem. It is interesting to observe that although the attention mechanism has been proved to be very effective in English scene text recognition, its performance is far inferior to the CTC method in the case of HCTR with large-scale character set.

Color 3D printing allows for 3D-printed parts to represent 3D objects more realistically, but its surface color quality evaluation lacks comprehensive objective verification considering printing materials. In this study, a unique test model was designed and printed using eco-friendly and vivid paper-based full-color 3D printing as an example. By measuring the chromaticity, roughness, glossiness, and whiteness properties of 3D-printed surfaces and by acquiring images of their main viewing surfaces, this work skillfully explores the correlation between the color representation of a paper-based 3D-printed coloring layer and its attached underneath blank layer. Quantitative analysis was performed using ΔE*ab, feature similarity index measure of color image (FSIMc), and improved color-image-difference (iCID) values. The experimental results show that a color difference on color-printed surfaces exhibits a high linear correlation trend with its FSIMc metric and iCID metric. The qualitative analysis of microscopic imaging and the quantitative analysis of the above three surface properties corroborate the prediction of the linear correlation between color difference and image-based metrics. This study can provide inspiration for the development of computational coloring materials for additive manufacturing.

Today, there are many recent developments that focus on improving the electric vehicles and their components, particularly regarding advances in batteries, energy management systems, autonomous features and charging infrastructure. This plays an important role in developing next electric vehicle generations, and encourages more efficient and sustainable eco-system. This paper not only provides insights in the latest knowledge and developments of electric vehicles (EVs), but also the new promising and novel EV technologies based on scientific facts and figures—which could be from a technological point of view feasible by 2030. In this paper, potential design and modelling tools, such as digital twin with connected Internet-of-Things (IoT), are addressed. Furthermore, the potential technological challenges and research gaps in all EV aspects from hard-core battery material sciences, power electronics and powertrain engineering up to environmental assessments and market considerations are addressed. The paper is based on the knowledge of the 140+ FTE counting multidisciplinary research centre MOBI-VUB, that has a 40-year track record in the field of electric vehicles and e-mobility.

This paper presents a thorough review of transmitarray devices particularly aiming antenna beamsteering, gathering some of the most relevant solutions published by the scientific community in the field. First, the background for realizing 1-D and 2-D antenna beamsteering with a transmitarray is introduced. Subsequently, several examples of unit-cells for transmitarray implementation and complete transmitarray designs presented in the literature are outlined. Each solution is analyzed in detail, identifying the nature of its layout, e.g., based on microstrip patches, frequency selective surfaces (FSS), or metamaterials (MMs), and the method employed to enable electronic reconfigurability, e.g., p-i-n diodes, varactor diodes, or microelectromechanical systems (MEMS). In addition, some models with the capability of controlling the wavefront polarization modes are also included herein since these are the base of hybrid transmitarrays, i.e., transmitarray with both electronic beamsteering and polarization control. Finally, all the models are compared against each other in order to highlight their benefits and limitations, summarizing their main characteristics, such as the frequency of operation and bandwidth, insertion loss, physical dimensions, and maximum beamsteering range, when available.

A review of the most important findings for jets impingement on rotating target is presented, the focus is on the heat transfer and flow dynamics in these jets. These jet configurations are encountered in many industrial applications. A significant number of research studies dealing with computational and experimental studies are reviewed. Different parameters are found to influence the flow and enhance mass and energy transfer in several heat configurations such as; Reynolds number (Re), nozzle geometry, spacing between jet exit and the impinging plate, jet impinging angle and the flow regime at the jet exit. There are a few studies that deal with heat transfer of a flow impinging on a rotating disk due to complexity of the flow structure and the challenges to conduct in-depth experimental investigation. Most studies present profiles of heat transfer coefficients, mean velocity and turbulence rates of the impinging flow. Many researches have reported that the LES can predict heat transfer and flow field data for different impinging angles to study the feedback mechanism between the nozzle and the plate.

We present the possibilities and challenges of passive UHF RFID tag antennas manufactured by inkjet printing silver nanoparticle ink on versatile paper-based substrates. The most efficient manufacturing parameters, such as the pattern resolution, were determined and the optimal number of printed layers was evaluated for each substrate material. Next, inkjet-printed passive UHF RFID tags were fabricated on each substrate with the optimized parameters and number of layers. According to our measurements, the tags on different paper substrates showed peak read ranges of 4–6.5 meters and the tags on different cardboard substrates exhibited peak read ranges of 2–6 meters. Based on their wireless performance, these inkjet-printed paper-based passive UHF RFID tags are sufficient for many future wireless applications and comparable to tags fabricated on more traditional substrates, such as polyimide. publishedVersion

A Xi-shaped meta structure, has been introduced in this paper. A modified split-ring resonator (MSRR) and a capacitive loaded strip (CLS) were used to achieve the left-handed property of the metamaterial. The structure was printed using silver metallic nanoparticle ink, using a very low-cost photo paper as a substrate material. Resonators were inkjet-printed using silver nanoparticle metallic ink on paper to make this metamaterial flexible. It is also free from any kind of chemical waste, which makes it eco-friendly. A double negative region from 8.72 GHz to 10.91 GHz (bandwidth of 2.19 GHz) in the X-band microwave spectra was been found. Figure of merit was also obtained to measure any loss in the double negative region. The simulated result was verified by the performance of the fabricated prototype. The total dimensions of the proposed structure were 0.29 λ × 0.29 λ × 0.007 λ. It is a promising unit cell because of its simplicity, cost-effectiveness, and easy fabrication process.

The semantic link network is a semantics modeling method for effective information services. This paper proposes a new text summarization approach that extracts semantic link network from scientific paper consisting of language units of different granularities as nodes and semantic links between the nodes, and then ranks the nodes to select Top-k sentences to compose summary. A set of assumptions for reinforcing representative nodes is set to reflect the core of paper. Then, semantic link networks with different types of node and links are constructed with different combinations of the assumptions. Finally, an iterative ranking algorithm is designed for calculating the weight vectors of the nodes in a converged iteration process. The iteration approximately approaches a stable weight vector of sentence nodes, which is ranked to select Top-k high-rank nodes for composing summary. We designed six types of ranking models on semantic link networks for evaluation. Both objective assessment and intuitive assessment show that ranking semantic link network of language units can significantly help identify the representative sentences. This paper not only provides a new approach to summarizing text based on the extraction of semantic links from text but also verifies the effectiveness of adopting the semantic link network in rendering the core of text. The proposed approach can be applied to implementing other summarization applications such as generating an extended abstract, the mind map, and the bulletin points for making the slides of a given paper. It can be easily extended by incorporating more semantic links to improve text summarization and other information services.

This study designed and fabricated a frequency-selective structure-based security paper for the electromagnetic detection system of a security gate, which aims to prevent leakage of confidential documents. When a functional paper embedded with a frequency-selective pattern that selectively reflects a specific frequency is being leaked out of a security zone, the electromagnetic detection system receives and detects the intensity of the electromagnetic wave reflected from the security paper passing through an antenna gate, which transmits/receives RF signals. A stable detection performance of the security paper can be ensured by improving the incidence angle stability for incident waves and reducing the reflection loss. This study designed a frequency-selective structure with stable frequency reflection properties at the X-band by utilizing a Jerusalem cross structure. The proposed design was realized using the screen printing technique, which could implement a circuit, to print silver ink on a plain paper. To verify the applicability of the frequency-selective structure-based security paper, an RF detection system with a multiple antenna array was constructed and the intensity of the received signals was measured. The measurement was performed for various scenarios, and the result showed that the proposed security paper was well detected.

Phasor Measurement Units (PMUs) have enabled real-time power grid monitoring and control applications realizing an integrated power grid and communication system. The communication network formed by PMUs has strict latency requirements. If PMU measurements cannot reach the control centre within the latency bound, they will be invalid for calculation and may compromise the observability of the whole power grid as well as related applications. To address this issue, this study proposes a model to account for the power grid observability under communication constraints, where effective capacity is adopted to perform a cross-layer statistical analysis in the communication system. Based on this model, three algorithms are proposed for improving power grid observability, which are an observability redundancy algorithm, an observability sensitivity algorithm and an observability probability algorithm. These three algorithms aim at enhancing the power system observability via the optimal communication resource allocation for a given grid infrastructure. Case studies show that the proposed algorithms can improve the power system performance under constrained wireless communication resources.

With the wide application of vegetable insulating oil in power transformers, it is essential to investigate the influence of moisture on the frequency domain dielectric spectrum (FDS) analysis in order to propose an accurate moisture assessment method for vegetable oil-paper insulation system. In this regard, various vegetable oil-paper samples are prepared in a laboratory environment. FDS curves for all samples are obtained at different moisture contents and operating temperatures. A new method to estimate the moisture content in insulation paper is proposed based on the low-frequency characteristic quantity. Also, the effect of operating temperature and water migration between the oil and paper insulation on the FDS analysis is investigated. Based on this analysis, a compensation factor is introduced to eliminate the influence of temperature on paper moisture assessment. Furthermore, an improved normalization method for the temperature effect on the FDS of vegetable oil-paper insulation with different moisture contents is proposed. The proposed moisture assessment and temperature normalization methods are validated thorough their application on an operating power transformer.

The health status monitoring of special transformers is of great significance to ensure the secure operation of the distribution network and the power quality of special transformer users. Given this background, an operation health status monitoring algorithm of special transformers is proposed in this paper based on balanced iterative reducing and clustering using hierarchies (BIRCH) and Gaussian Cloud methods (GCM). The algorithm is composed of two parts, i.e., the offline and online parts. For the offline part, the operating indexes of special transformers are extracted based on historical operating data, and Gaussian clouds of normal operating conditions of the special transformers are determined by BIRCH clustering and Gaussian cloud methods. For the online part, Gaussian clouds of real-time operating conditions of special transformers are determined by BIRCH clustering and Gaussian cloud methods based on real-time operation data. Then, the monitoring results of operating health status are determined by the distance between the standard Gaussian clouds and the real-time Gaussian clouds of special transformers. Finally, case studies for actual special transformers are performed to verify the proposed method, and the results show that the proposed model can effectively identify the abnormal operation of the special transformer.

Biomass torrefaction is a simple and appropriate thermo-chemical treatment/conversion process for upgrading agricultural residues to a high-quality fuel, which could be used as an alternative energy resource to replace fossil fuels. In this paper, reaction kinetics for torrefaction of pelletized agro-residues biomass under dry flue gas conditions were investigated. The two-step mechanism model was used to describe the biomass torrefaction decomposition, and with the experimental data, the kinetic parameters of this model were analyzed. The torrefaction reactions were found to occur in a narrow period of reaction time, and the kinetic parameters were affected by dry flue gas conditions. The model predictions can imitate the thermo-chemical degradation well, and the predicted torrefied solid was shown to contain not only chars but also some intermediate and unreacted fractions. This work provides further insights for understanding torrefaction kinetics of agricultural biomass pellets which are important in designing and operating industrial biomass conversion equipment and apparatus.

Bio-E10 is short for the biofuel made up of 90% gasoline in volume and 10% bio-ethanol, which is the ethanol made from commercially-grown crops such as corn and wheat by the sugar fermentation process. In China, bio-E10 will be supplied nationwide from 2020 as an alternative to conventional gasoline, aiming at ensuring greater energy security and lowering the greenhouse gas emissions. In order to assess the impacts of the upcoming bio-E10 application on the ozone forming potential (OFP) of the emissions from in-use vehicles, this paper examined the carbonyls and volatile organic compounds (VOCs) in the evaporative and tailpipe emissions of three China-4 certified in-use vehicles fueled with a market-available gasoline and two match-blend bio-E10s, and calculated their OFPs using the Maximum Incremental Reactivity (MIR) method. The results revealed that for the evaporative emissions, the use of bio-E10s increased the carbonyl and VOC emissions released within the diurnal-loss stage by 8.5–17.6% and 11.1–78.6% respectively, but decreased the carbonyl and VOC emissions in the hot-soak stage by 47.4%–61.5% and 4.8%–20.6% respectively. Regarding the tailpipe emissions, in comparison to the gasoline baseline, burning bio-E10s increased the carbonyls by 15%–46% while reducing the VOCs by 37%–56% over the New European Driving Cycle (NEDC). Reductions in the tailpipe OFPs up to 47.3% were seen with the application of the bio-E10s, however, there were no clear conclusions with respect to the evaporative OFPs, which varied from −15% to ＋25% compared to the gasoline baseline. Based on the test results and census data, the application of bio-E10 in China is shown to help remove part of ozone contamination from the in-use vehicle sector.

Recently, it has been shown that channel feedback helps to enhance the physical layer security (PLS) of communication systems. The current use of feedback focuses on generating secret keys protecting the transmitted messages, and this feedback scheme is proved to be optimal for some physically degraded channel models. In this paper, we revisit the model of the state-dependent wiretap channel with the noncausal state at the transmitter, which plays an important role in the PLS of the wireless communication systems. We propose a new feedback scheme for this model and show that the proposed new scheme performs better than the already existing secret key-based feedback scheme. The results of this paper are further explained via a Gaussian example.

Voice-over IP (VoIP) technology is a kind of digital transmission technology based on IP network. It is one of the important methods to use voice service in VoIP as steganographic carrier to ensure secure transmission. However, the traditional steganographic code has some problems, such as low embedding efficiency and weak concealment, which cannot meet the requirements of VoIP streaming media information hiding for the security of secret information. Therefore, a steganographic algorithm combining F5 and simplified wet paper code (SWPC) algorithm is proposed. The main idea is to embed secret messages in each row of the carrier matrix using the F5 algorithm, and then the SWPC algorithm is used to embed the columns according to the wet and dry characteristics of the wet paper code without affecting the results before row embedding. We use the VoIP streams encoded by the ITU-T G.729a codec as a carrier to verify the proposed scheme. The experimental results demonstrate that the proposed scheme can achieve relatively better IP speech data steganographic transparency and that it can outperform F5-WPC and SWPC approaches.

The prime objective of this paper was to produce the biogas and biomass pellets from water hyacinth. The leaf and petiole were chopped, grind, squeezed and then separated into two parts as squeezed out juice and remaining fiber. The squeezed out water as water hyacinth juice (SWWH) was used to produce biogas with microorganisms at a ratio of 1: 1 (8 liters of SWWH/8 liters of microorganisms). Water hyacinth fiber (WHF), with a moisture content of 10.57% wet basis, was used to produce biomass pellets. The results showed that a total of 458.44 liters of biogas was produced from SWWH with microorganisms consisting of 68.67% CH4, 18.23% CO2, and 13.10% other gases. Specific methane yield and the potential to biodegrade methane were 237.37 L CH4/kgVSaddedand 51.89%, respectively. Test results of biomass pellets from water hyacinth with water ratio of 10:90 indicated that the bulk density, diameter, durability, fines content, length, and moisture of the pellets met the criteria of the US Standards (PFI standard), except for inorganic ash and chloride contents. Keywords: Biogas, Biomass pellet, Production, Water hyacinth

Production of bio-succinic acid through microbial fermentation using agro-industrial waste has been observed extensively. Large scale production is now being considered since bio-succinic acid has broad range application in several industries including agricultural, food, chemical, metal, and pharmaceutical industry as a precursor, ion chelator, and or additive agent. One of promising microbes able to produce bio-succinic acid in large amount and recognized for industrial production is Actinobacillus succinogenes. However, several factors still need to be considered in order to optimize the fermentation performance. Therefore, this paper aims to review the progress of fermentation methods and discuss the fermentation strategy focused on the influences of different carbon sources, nitrogen sources, pH regulator, and fermentation configuration to the fermentation parameters including concentration, productivity and yield of bio-succinic acid. As a result, combinations of several fermentation strategies are needed to be performed to realize an efficient and effective bio-succinic acid industry. Keywords: Actinobacillus succinogenes, Agro-industrial waste, Bio-succinic acid, Fermentation strategies

This paper reviews and discusses the potential of papaya seed and stone fruit kernel biodiesels — the two sources of 2nd generation transport biodiesels in Australia. The challenges associated with biodiesel production and their possible solutions, particularly on feedstock selection, oil extraction, conversion of oil into biodiesel, biodiesel storage and transport, costs of production and the information needs for commercialising these sources of biodiesels are discussed, along with the eco-friendly attributes of these biodiesels to Australian transport sector. Some researchers report that the use of papaya seed and stone fruit kernel biodiesels reduce engine power only 2 to 5%), however significantly reduce harmful engine emission such as HC reductions of 9 to 19%, PM reductions of 19.5 to 35% and CO reductions of 11 to 29%. Keywords: Papaya seed, Stone fruit kernel, Apricot, RSM, Biodiesel, Renewable energy, Australia, Optimisation, Challenges, Engine performance, Emission, Second generation

The objective of this paper is to optimise the liquid product of pyrolysis from as much as 500 g of polypropylene (PP) plastic waste, using a fixed bed type reactor in a vacuum condition (−3 mm H2O), to minimise the oxygen entering the reactor. The vapour flows through the 4-tray distillation bubble cap plate column for fractionation by utilising heat from the reactor. Process conditions at 500–650 °C and of 580 °C optimum liquid oil yield is 88 wt.%, comprising of kerosene in tray I with a volume of 350 ml, gasoline in tray II and III with a volume of 228 ml, and tray IV had no condensate. Gas yield is 5 wt.% and the rest is char. At the conditions between 500 °C and 560 °C, gasoline yield in 6–67 wt.% comprises of kerosene and gasoline. However, at process conditions between 600 °C and 650 °C yields of 64–83 wt.% comprising of diesel oil was obtained at tray I and II, while kerosene and gasoline were obtained in the next tray. The characteristics of fuel obtained from plastic such as density, viscosity, octane–cetane number, ash content and calorific value have similar properties with those of fossil fuels. Keywords: Bubble cap distillation, Condensate, Plastic, Polypropylene, Pyrolysis

In general, considering standard production, as well as coconut oil production, in oil consumption industries is an important factor. Oil color is an important element, as it is an important factor for consumers or buyers in selecting coconut oil. In the process of producing coconut oil, the cold-pressed method has been chosen to maintain the essential quality of coconut oil. The quality of the coconut oil is inspected from the production process by means of light passing through the coconut oil. Then, the production staff compares the turbidity of coconut oil with the master sample. The turbidity of coconut oil in every production must be compared with a master sample to maintain standards control. According to previous studies, there are many methods for determining coconut oil turbidity. One method that has been utilized is determining turbidity from light passing through the medium in which the transmitted light can be absorbed through the turbidity of the variable medium. This process is applied together with image processing to determine the coconut oil turbidity. In this research, we propose a method for measuring coconut oil turbidity by the Moving Average Median of Hue (MAMoH), which is better in detecting the coconut oil turbidity than the Median of Gray Scale (MoGS) method, Median of Hue (MoH) method, and Random Position Median of Hue (RPMoH) method. In terms of the percentage accuracy of the efficiency test; the MAMoH method has 99 percent accuracy, while the MoGS method is not applicable, the MoH method has 88.04 percent accuracy, and the RPMoH method has 85.91 percent accuracy. Thus, the MAMoH method is considered an appropriate method for measuring coconut oil turbidity.

Waste biomass can be used as an alternative source of energy. However, such use requires prior treatment of the material. This paper describes the physicochemical characteristics of biochar obtained by the thermochemical decomposition of six types of agricultural waste biomass: residues from the production of flavored spirits (a pulp of lime, grapefruit and lemon), beetroot pulp, apple pomace, brewer&rsquo, s spent grain, bark and municipal solid waste (bark, sawdust, off-cuts and wood chips). The biomass conversion process was studied under conditions of limited oxygen access in a reactor. The temperature was raised from 450 to 850 &deg, C over 30 min, followed by a residence time of 60 min. The solid products were characterized in terms of their elemental compositions, mass, energy yield and ash content. The gaseous products from pyrolysis of the biomass were also analyzed and their compositions were characterized by GCMS (Gas Chromatography&ndash, Mass Spectrometry). The carbonization process increased the carbon content by, on average, 1.7 times, from an average percentage of 46.09% &plusmn, 3.65% for biomass to an average percentage of 74.72% &plusmn, 5.36% for biochars. After carbonization, the biochars were found to have a net calorific value of between 27 and 32 MJ/kg, which is comparable or even higher than good-quality coal (eco pea coal 24&ndash, 26 MJ/kg). The net calorific values show that the volatile products can also be considered as a valuable source of energy.

Natrium Hydroxide (NaOH) and Calcium Hydroxide (Ca(OH)2) as an absorbent was used in the filtration system of the mobile anaerobic digester (AD) to improve the quality of biogas from dairy cattle manure. Twelve pilots insulated of mobile AD used in this study. The average temperature inside the digester was 28.37 °C, and in the outer digester 27.16 °C. The average biogas temperature before filtration was 28.37 °C, and after filtration 31.09 °C. The biogas filtration using adsorbent was a very significantly effect (P 0.05). The average biogas production using NaOH was 717.50 mL h−1, Ca(OH)2 715.63 mL h−1, and control 676.25 mL h−1. The adsorbent treatments were very significantly effects (P 0.05) among the type of adsorbent. The NaOH could increase the percentage of methane (CH4) (14.26 %) and oxygen (O2) (22.06 %) content, and reduced carbon dioxide (CO2) (30.86 %) compared with control. However, Ca(OH)2 adsorbent could increase CH4 (7.77 %) and O2(11.22 %) and reduced CO2 (17.88 %). The mobile anaerobic digester is suitable for smallholder farmer because more simple and cheaper.

Microbial fuel cells (MFCs) are a green technology that can directly convert electrical energy from chemical energy contained in organic wastewater. Rice is the most popularly consumed food in Asia. Rice washing before cooking produces an enormous amount of domestic sewage. Rice washing wastewater (RWW) contains various organic matters, minerals, and vitamins. Therefore, in this study, we utilized RWW as biofuel to operate a floating MFC (FMFC). The FMFC was designed with the air-cathode floating on the biofuel and the anode immersed in the biofuel. This design enables the device to float on wastewater sources and to harvest electricity directly from that source. Baker’s yeast and bacteria existing in a natural pond (natural bacteria) were used as biocatalysts. Experimental results showed that the FMFC could generate electricity from RWW using both the baker’s yeast and natural bacteria. The maximum power density ow the FMFC using the baker’s yeast was 1 mW/m2.