Search

In the tourism industry, the sales of local specialties is an important part, and the package design and integrity of the specialties are very important. This paper first introduced the support vector machine (SVM) algorithm that was used for detecting defects on the surface of paper packages. Then, the design of red wind packages was briefly described, and the simulation experiment was carried out on SVM algorithm using red wine packages with different degrees of surface defects. Proper parameters were tested using the k-fold cross-validation method. The results demonstrated that the properties of paper improved the value of packages and the SVM algorithm had better accuracy than artificial recognition in recognizing different degrees of defects on the surface of packages. In conclusion, this paper describes the application of paper in packages and provides an effective method for the defection of defects on the surface of packages. This study provides an effective references to the improvement of package values and the enhancement of package integrity.

In this paper, the implementation of artificial neural networks (multilayer perceptron [MLP] and radial base functions [RBF]) and the upgraded Markov chain model have been studied and performed to identify the human behavior patterns during rock, paper, and scissors game. The main motivation of this research is the design and construction of an intelligent robot with the ability to defeat a human opponent. MATLAB software has been used to implement intelligent algorithms. After implementing the algorithms, their effectiveness in detecting human behavior pattern has been investigated. To ensure the ideal performance of the implemented model, each player played with the desired algorithms in three different stages. The results showed that the percentage of winning computer with MLP and RBF neural networks and upgraded Markov model, on average in men and women is 59%, 76.66%, and 75%, respectively. Obtained results clearly indicate a very good performance of the RBF neural network and the upgraded Markov model in the mental modeling of the human opponent in the game of rock, paper, and scissors. In the end, the designed game has been employed in both hardware and software which include the Zana intelligent robot and a digital version with a graphical user interface design on the stand. To the best knowledge of the authors, the precision of novel presented method for determining human behavior patterns was the highest precision among all of the previous studies.

Paper folding-and-punching tests are used to measure spatial abilities in humans. This paper presents a qualitative model for paper folding (QPF) and a computer game (Paper Folding Game) developed to apply and show the reasoning capabilities of the QPF model. This interactive game presents paper-folding activities intended to help users train and understand how to fold a paper to get a specific shape. Then, it presents paper-folding-and-punching tests to the players. The Paper Folding Game can automatically generate paper-folding-and-punching questions with varying degrees of difficulty depending on the number of folds and holes made, thus producing additional levels for training. The reasoning mechanisms in the QPF model are used by the Paper Folding Game to infer the right answer to each paper-folding-and-punching question. This reasoning capability allows the game to provide feedback to the players when they are wrong and also to create other plausible answers automatically, so that random question-answers are shown to the players in the master-mode. The Paper Folding Game has been implemented using Unity engine and it is available to download from GooglePlay and AppleStore for everyone to train their spatial reasoning skills.

Directed evolution has become an important method to unleash the latent potential of enzymes to make them uniquely suited for human purposes. However, the need for a large reagent volume and sophisticated instrumentation hampers its broad implementation. In an attempt to address this problem, here we report a paper-based high-throughput screening approach that should find broad application in generating desired enzymes. As an example case, the dehalogenation reaction of the halohydrin dehalogenase was adopted for assay development. In addition to visual detection, quantitative measurements were performed by measuring the color intensity of an image that was photographed by a smartphone and processed using ImageJ free software. The proposed method was first validated using a gold standard method and then applied to mutagenesis library screening with reduced consumption of reagents (i.e., ≤ 10 μl per assay) and a shorter assay time. We identified two active mutants (P135A and G137A) with improved activities toward four tested substrates. The assay not only consumes less reagents but also eliminates the need for expensive instrumentation. The proposed method demonstrates the potential of paper-based whole-cell screening coupled with digital image colorimetry as a promising approach for the discovery of industrially important enzymes.Key Points• A frugal method was developed for directed enzyme evolution.• Mutagenesis libraries were successfully screened on a paper platform.• Smartphone imaging was efficiently used to measure enzyme activities.

The low cost, simplicity, and ease of use of paper microfluidic devices have made them valuable medical diagnostics for applications from pregnancy testing to COVID-19 screening. Meanwhile, the increasing complexity of paper-based microfluidic devices is driving the need to produce new tools and methodologies that enable more robust biological diagnostics and potential therapeutic applications. A new design framework is being used to facilitate both research and fabrication of paper-based microfluidic biological devices to accelerate the investigative process and reduce material utilization and manpower. In this work we present a methodology for this framework to dynamically place and route microfluidic components in a nondiscrete design space where fluid volume usage, surface area utilization, and the timing required to perform specified biological assays are accounted for and optimized while also accelerating the development of potentially lifesaving new devices.

Using similarity software to examine the quality of scientific papers is a nuisance. The significance of a scientific paper should be decided by the acknowledged experts. The practice of using the computer program to decide scientific papers must be rescinded or voided.

Performance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we ask three questions: ➊ does trade-off really exist in different CFI schemes? ➋ if trade-off do exist, how do previous works comply with it? ➌ how can it inspire future research? Although the three questions probably cannot be directly answered, they are inspiring. We find that a deeper understanding of the nature of the trade-off will help answer the three questions. Accordingly, we proposed theGPTconjecture to pinpoint the trade-off in designing CFI schemes, which says that at most two out of three properties (fine granularity, acceptable performance, and preventive protection) could be achieved.

A new tool for the solution of electromigrative separations in paper-based microfluidics devices is presented. The implementation is based on a recently published complete mathematical model for describing these types of separations, and was developed on top of the open-source toolbox electroMicroTransport, based on OpenFOAM® , inheriting all its features as native 3D problem handling, support for parallel computation, and a GNU GPL license . The presented tool includes full support for paper-based electromigrative separations (including EOF and the novel mechanical and electrical dispersion effects), compatibility with a well-recognized electrolyte database, and a novel algorithm for computing and controlling the electric current in arbitrary geometries. Additionally, the installation on any operating system is available due to its novel installation option in the form of a Docker image. A validation example with data from literature is included, and two extra application examples are provided, including a 2D free-flow IEF problem, which demonstrates the capabilities of the toolbox for dealing with computational and physicochemical modeling challenges simultaneously. This tool will enable efficient and reliable numerical prototypes of paper-based electrophoretic devices to accompany the contemporary fast growth in paper-based microfluidics.

The fabrication of underwater devices is necessary for the exploration of water environments and interactions in the Human–Computer Interaction (HCI) field. However, there are fewer approaches to support prototyping used in water environments. The existing prototype methods lack systematic waterproof treatments and provide insufficient software for balance and buoyancy analysis. To address these limitations, we present ElectroPaper, a new approach for the design and fabrication of prototypes used in water environments (surface or beneath) with paper-based electronic interfaces with a crease layer, hardware distribution layer, and hollow-out layer to support physical properties, such as waterproofing, foldability, and conformability. The approach includes a computational design tool for assisting in balance analysis, three-dimensional (3D) model unfolding, and circuit drawing. We describe the design and fabrication process and provide several example applications to illustrate the feasibility and utility of our approach. ElectroPaper provides an inexpensive and effective medium for the fabrication of customized digital prototypes for water environment use.

Molecular simulation technology is a new technology emerging with the rapid development of computer technology. It has the advantages of clear microscopic models, in-depth and precise calculation etc., it has been widely used in the oil–paper insulation system of transformer in recent years. Based on the application of molecular simulation technology in the oil–paper insulation system of transformers in this study, the current research status and progress of molecular simulation in these area are elaborated in detail from the aspects of transformer insulating oil and insulating paper according to the domestic and foreign literature, and the application of molecular simulation technology in plant insulating oil and nano-modified insulating oil is emphatically analysed. The complementing research method of molecular simulation and experiment is pointed out, which provides certain reference for solving many problems existing in the field of oil–paper insulation system of transformers.

Headline generation is a challenging subtask of abstractive text summarization, which its output should be a summary, shorter than one sentence. It would be precious to develop a dataset for the evaluation of abstractive summarization methods on this task in the Persian language. There are several datasets for headline generation in Persian, most of which are not large enough to be used by more sophisticated methods of text summarization, such as deep learning models. Moreover, all of these datasets are focused on daily news and there is no dataset for summarizing scientific Persian papers. In this article, we present “ElmNet,” a headline generation dataset of about 400,000 abstract/headline pairs of scientific papers, gathered from six major publishers for scientific articles in Persian. We, moreover, evaluate the performance of the most important deep learning-based headline generation methods, on the proposed dataset. The results prove the comparability of the performance of the state-of-the-art methods on this task, to their results on the existing English datasets.

A 3D modeling system with all-inclusive functionality is too demanding for a casual 3D modeler to learn. There has been a shift towards more approachable systems, with easy-to-learn, intuitive interfaces. However, most modeling systems still employ mouse and keyboard interfaces, despite the ubiquity of tablet devices and the benefits of multi-touch interfaces. We introduce an alternative 3D modeling and fabrication paradigm using developable surfaces, inspired by traditional papercrafting, and we implement it as a complete system designed for a multi-touch tablet, allowing a user to fabricate 3D scenes. We demonstrate the modeling and fabrication process of assembling complex 3D scenes from a collection of simpler models, in turn shaped through operations applied to virtual paper. Our fabrication method facilitates the assembly of the scene with real paper by automatically converting scenes into a series of cutouts with appropriately added fiducial markers and supporting structures. Our system assists users in creating occluded supporting structures to help maintain the spatial and rigid properties of a scene without compromising its aesthetic qualities. We demonstrate several 3D scenes modeled and fabricated in our system, and evaluate the faithfulness of our fabrications relative to their virtual counterparts and 3D-printed fabrications.

Aiming at the problem of easy tampering and difficult integrity authentication of paper text documents, this paper proposes a robust content authentication method for printed documents based on text watermarking scheme resisting print-and-scan attack. Firstly, an authentication watermark signal sequence related to content of text document is generated based on the Logistic chaotic map model; then, the authentication watermark signal sequence is embedded into printed paper document by using a robust text watermarking scheme; finally, the watermark information is extracted from scanned image of paper document, and compared with the authentication watermark information calculated in real time by the text document content obtained by OCR technology, thereby performing content integrity authentication of the paper text documents. Experimental results show that our method can achieve the robust content integrity authentication of paper text documents, and can also accurately locate the tampering position. In addition, the document after embedding the watermark information has a good visual effect, and the text watermarking scheme has a large information capacity.

Proportional–Integral–Derivative controller technique continues to provide the easiest and effective solutions to most of the industrial applications in recent years. However PID controller is poorly tuned in practice compared to most other tuning methods and is complicated with poor performance. This research presents a multi objective optimization approach involving Genetic Algorithm, Evolutionary Programming, Particle Swarm Optimization and Bacterial foraging optimization. The proposed multi objective optimization algorithm is used to tune the PID controller parameters and their performances have been compared with the conventional methodologies like Ziegler Nichols method. The results proved that the use of multi objective optimization approach based controller tuning improves the performance of process in terms of time domain specifications and performance index, set point tracking and regulatory changes and also provides stability. This paper describes the various multi objective optimization algorithms and its implementation to tune the PID Controller used in paper machine DCS as real time processing of a Pulp and paper industry processes.

Background In Software Engineering (SE), conference publications have high importance both in effective communication and in academic careers. Researchers actively discuss how a paper should be organized to be accepted in mainstream conferences. Aiming This work tackles the problem of generalizing and characterizing the type of papers accepted at SE conferences. Method The paper offers a new perspective in the analysis of SE literature: a categorization scheme for SE papers is obtained by merging, extending and revising related proposals from a few existing studies. The categorization scheme is used to classify the papers accepted at three top-tier SE conferences during five years (2012–2016). Results While a broader experience is certainly needed for validation and fine-tuning, preliminary outcomes can be observed relative to what problems and topics are addressed, what types of contributions are presented and how they are validated. Conclusions The results provide insights to paper writers, paper reviewers and conference organizers in focusing their future efforts, without any intent to provide judgments or authoritative guidelines.

We present a mixed reality-based assistive system for shading paper sketches. Given a paper sketch made by an artist, our interface helps inexperienced users to shade it appropriately. Initially, using a simple Delaunay-triangulation based inflation algorithm, an approximate depth map is computed. The system then highlights areas (to assist shading) based on a rendering of the 2.5-dimensional inflated model of the input contour. With the help of a mixed reality system, we project the highlighted areas back to aid users. The hints given by the system are used for shading and are smudged appropriately to apply an artistic shading to the sketch. The user is given flexibility at various levels to simulate conditions such as height and light position. Experiments show that the proposed system aids novice users in creating sketches with impressive shading.

We propose new solutions that can efficiently address the problem of malicious memory access from pluggable computer peripherals and microcontrollers embedded within a system-on-chip. This problem represents a serious emerging threat to total-system computer security. Previous work has shown that existing defenses are insufficient and poorly deployed, in part due to performance concerns. In this paper we explore the threat and its implications for system architecture. We propose a range of protection techniques, from lightweight to heavyweight, across different classes of systems. We consider how emerging capability architectures (and specifically the CHERI protection model) can enhance protection and provide a convenient bridge to describe interactions among software and hardware components. Finally, we describe how new schemes may be more efficient than existing defenses.

One of the software for compiling a bibliography automatically can take advantage of the facilities of the Mendeley Desktop application. Mendeley Desktop is a reference management software that helps organize scientific articles, namely in creating citations and bibliography. With this software, writers can manage reading sources that are used as references in compiling their writings. The use of Mendeley Desktop can also be integrated with Microsoft Word, so it can be more easily for writers for each scientific paper. The purpose of holding this training activity is to help the teachers of SMP Swasta Gita Surya Eban in order to utilize of the facilities provided by the software and the citations and references on the Mendeley Desktop so that scientific writing can be done more easily, quickly, and efficiently. From the training results, it was found that the training carried out could add knowledge and solutions to the use of Mendeley Desktop with the evaluation results increase significantly. The writers hope that by holding this training, teachers at SMP Swasta Gita Surya Eban can apply the citation / reference software from Mendeley Desktop in writing scientific papers.

Cognitive deficits are a core feature of mental and behavioral disorders, leading to poor treatment adherence and functionality. Virtual reality (VR) methodologies are promising solutions for cognitive interventions in psychiatry once they provide greater ecological validity. This study assessed and compared two content-equivalent cognitive training (CT) interventions, delivered in desktop VR (Reh@City v2.0) and paper-and-pencil (Task Generator (TG)) formats, in patients with mental and behavioral disorders. 30 patients were randomly assigned to the Reh@City v2.0 group and the TG group. Both groups of patients underwent a time-matched 24-sessions intervention. Neuropsychological assessments were performed at baseline, post-intervention, and follow-up. A within-groups analysis revealed significant improvements in visual memory and depressive symptomatology after the Reh@City intervention. The TG group improved in processing speed, verbal memory, and quality of life (social relationships and environmental domains). Between groups, Reh@City led to a greater reduction in depressive symptomatology, whereas the TG group showed higher improvements in social relationships aspects of quality of life. At follow-up, previous gains were maintained and new improvements found in the Reh@City (global cognitive function, language, visuospatial and executive functions) and the TG groups (attention). The Reh@City significantly reduced depressive symptomatology, and the TG led to greater improvements in processing speed, abstraction, and social relationships domain of quality of life at follow-up. Both interventions were associated with important cognitive, emotional, and quality of life benefits, which were maintained after two months. Reh@City and TG should be considered as complementary CT methods for patients with mental and behavioral disorders. Trial registration The trial is registered at ClinicalTrials.gov, number NCT04291586.

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.

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.

In this paper we will discuss about the Automatic sun tracking system which we will implement on metal detectionaobotic system, where robotic spontaneous sun tracing system is a hybrid hardware/software prototype, whichautomatically furnish best positioningof panelwith the sunlight to get maximal electric charge generation through solar panel. It’s active sensors continuously observed the monochromaticrays of sun and spin the panel about the direction where the potential of sun rays is maximal. A micro-controller works on automatic sun tracing deviceconnected with the new solar power transformunit is developed & execute. The automatic sun tracker is executed with a DC motor and a DC Motor controller. The conditions of the hardware subjected to the changes of the environmental conditions. In the new unit of the MAXIMUM POWER POINT is resolved to easy insertion software with a present sweep perspective, with this new perspective the standardization of the transform from solar energy to electric energy at its maximal power point can be develops extra definitive and extra authentication.

In recent years evolution of Internet of Things has brought revolution in many different sectors. The agriculture sector has become efficient and cost effective due to role of IoT. Monitoring systems has become the crucial part of agriculture. In past few years lot of work is been done and many systems has been purposed in this regard. In this paper we are going to make comparison between 4 different agriculture monitoring systems. We are also going to discuss what type of hardware including different sensors are used in those systems. We are also going to discuss software and platform on which those applications run. We will also discuss processing mechanism and what kind of algorithms are used in these systems and in the last we are going to make a comparative table based on these parameters.

With the increasing use of surveillance cameras, face recognition is being studied by many researchers for security purposes. Although high accuracy has been achieved for frontal faces, the existing methods have shown poor performance for occluded and corrupt images. Recently, sparse representation based classification (SRC) has shown the state‐of‐the‐art result in face recognition on corrupt and occluded face images. Several researchers have developed extended SRC methods in the last decade. This paper mainly focuses on SRC and its extended methods of face recognition. SRC methods have been compared on the basis of five issues of face recognition such as linear variation, non‐linear variation, undersampled, pose variation, and low resolution. Detailed analysis of SRC methods for issues of face recognition have been discussed based on experimental results and execution time. Finally, the limitation of SRC methods have been listed to help the researchers to extend the work of existing methods to resolve the unsolved issues.

This study focuses on the student towards paper implementation 3 subject of history. This study use where survey research design as many as 50 from respondent 4 in School orchid, Cheras, chosen by gregarious sample and use instrument in obtaining quantitative data. This research using Social learning theory Albert Bandura, theory of constructivism and also Bloom's Taxonomy model. Data analyzed by using Excel Microsoft software 2010 (Statistic pack) 2.0 (SPSS). Finding of correlation analysis show there is a significant relationship between student attitude approach with students’ knowledge towards paper of 3 history subject (r, =.846=, n=50, p

Although fabrication of colorimetric paper-based analytical devices (PADs) has drawn increasing attention recently, the signal readout method is still a crucial challenge on the way to practical exploitations. We herein introduce an integration of digital image processing with a model PAD for easing and improving the signal readout procedure. The colorimetric detection mechanism of PAD relies on in-situ induced yellowish silver nanoparticles via the interaction of silver ions, poly(vinyl alcohol), and ammonia with isoniazid. The observed color value is related with the concentration of isoniazid. The proposed algorithm is based on mathematical morphology recognition, and minimizes the errors arising from manual area selection. Besides, it allows the recognition of both circle and square shapes in 96-well plate and A4 size array designs. Since this algorithm automatically provides the blank-corrected numerical matrixes and image profiles of red, green and blue channels, further investigations such as outlier classification, construction of regression/prediction models and calculation of detection limit can be easily performed. Comparison of signal readout results of the developed algorithm with ImageJ software demonstrates significant improvements in analysis speed, reproducibility, accuracy and color values. Therefore, application of the proposed algorithm is promising as a robust technique for practical applications.

Paper-based digital microfluidic biochips (or P-DMFBs) are becoming highly impelling due to its low-cost and in-place fabrication of electrodes and control wiring on a single piece of paper having an inkjet printer and conductive ink. Despite enormous advantages, several complex design rules also subsist, such as avoidance of induced control interference, minimum separation among the control lines, and congestion-free wiring on a single layer, which is to be correlated leading toward overall feasibility of the design. Several cost raising issues, such as schedule length, control pin count, and wire length, must be considered for attaining a successful fluid-control codesign. Moreover, design gaps exist among the subtasks of the fluid level, control level, and fluid-control design as a whole, which undeniably impose expensive design cycles increasing overall cost. This article builds a machine learning-based model for the pin-constrained P-DMFBs to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring. This model effectively eliminates the design cycles producing a low-cost platform. The predictive model has been evaluated over a balanced data set. Several benchmarks for assessing the performance are studied.

This paper presents a critical review of laser pyrolysis. Although this technology is almost 60 years old, in literature many researchers, both from academia and industry, are still developing and improving it. On the contrary industrial applications are struggling to take off, if not in very restricted areas, although the technology has undoubted advantages that justify future development. The aim of this work consists in analysing a representative pool of scientific papers (230) and patents (121), from the last 20 years, to have an overview about the evolution of the method and try to understand the efforts spent to improve this technology effectively in academia and in industry. This study is important to provide a complete review about the argument, still missing in the literature. The objective is to provide an overview sufficiently broad and representative in the sources and to capture all the main ways in which laser pyrolysis has been used and with what distribution. The main focuses of the study are the analyses of the functions carried out by laser technologies, the application fields, and the types of used laser (i.e. models, power and fluence). Among the main results, the study showed that the main use of laser pyrolysis is to produce nanoparticles and coatings, the main materials worked by laser pyrolysis are silicon and carbon dioxide and the main searched properties in the products of laser pyrolysis are catalysts activity and electrical conductivity. CO2 lasers are the most used and the have high versatility compared to others. In conclusion, the study showed that laser pyrolysis is a consolidated technology within its main application fields (nanoparticles and coatings) for several years. Within this context, the technology has been developed on very different sizes and processes, obtaining a very wide range of results. Finally, these results may also have stimulated new areas of experimentation that emerged mainly in recent years and which concern biomedical applications, additive manufacturing, and waste disposal. Graphical abstract

Exam paper generation is an indispensable part of teaching. Existing methods focus on the use of question extraction algorithms with labels for each question provided. Obviously, manual labeling is inefficient and cannot avoid label bias. Furthermore, the quality of the exam papers generated by the existing methods is not guaranteed. To address these problems, we propose a novel approach to generating exam papers based on prediction of exam performance. As such, we update the quality of the initially generated questions one by using dynamic programming, as well as in batches by using genetic algorithms. We performed the prediction task by using Deep Knowledge Tracing. Our approach considered the skill weight, difficulty, and distribution of exam scores. By comparisons, experimental results indicate that our approach performed better than the two baselines. Furthermore, it can generate exam papers with adaptive difficulties closely to the expected levels, and the related student exam scores will be guaranteed to be relatively reasonable distribution. In addition, our approach was evaluated in a real learning scenarios and shows advantages.

Near Infrared Spectroscopy (NIRS), as one of analysis technologies, has shown promisingly industrial applications for significant properties for recent decades such as fast response, preciseness, non-intrusion etc. Here, the authors employed NIRS coupled with a series of physical and chemical tests to assess the ageing condition of oil-paper insulation, which is responsible for the main insulation type of high-voltage power transformer. Among these procedures, the data analytic algorithms are of utmost importance to determine the evaluation precision. After plenty of trial-and-error, Savitzky-Golay (S-G) convolution was finally utilised to de-noise samples and improve the spectral data quality. The competitive adaptive reweighted sampling (CARS) was used to select the optimal wavelength combination of NIRS, which is found able to fully extract the effectively spectral information and reduce dimensions of spectral data. Based on the above-mentioned techniques, the quantitative analysis model of NIRS was established by partial least squares (PLS), which could synthetically process the spectral data and the degree of polymerisation (DP) of paper samples. The results indicated that compared with the traditional detection methods, the NIRS analysis is a powerful and informative tool to characterise the condition of oil-paper insulation without intrusion or damage to transformers.

Augmented reality technology is attracting increased attention, given the popularity of the smartphone. The utilisation of the smartphone with AR technology is also enabling mobile augmented reality (MAR) to become accessible. Stereoscopic vision offers users the benefit of depth perception, which can help improve user memory. Therefore, this study aims to investigate the effect on knowledge retention using MAR with stereoscopic vision. An experiment to compare a stereoscopic-based MAR application and a paper-based manual was designed to test the participants’ knowledge retention on a product part and disassembly process. The developed MAR adopted a smartphone and headset case to provide a stereoscopic view to the user. The experiment consisted of both pre-test and post-test phases where the pre-test phase examined the participant’s knowledge about the product, and the post-test phase focused on how much information the participants could recall. The post-test phase was conducted after 48 h following the pre-test phase since long-term memory required several hours in which to stabilise. The results showed that the MAR group had an advantage over the paper-based manual group for both information retentions having a mean score of 8.89 from the MAR group, compared with 6.33 for the paper-based manual group. Moreover, the MAR group was observed to have fewer errors in the post-test with a mean score of 0.53, whereas the paper-based achieved a score of 2.2. This result indicated that the MAR group and the paper-based manual group had equivalent performance in the completion time without the assistance tool. In addition, MAR had a better mean score for the subjective feedback (usefulness = 4.47, ease of use 4.18 and satisfaction = 4.07).

Context: The establishment of the Mining Software Repositories (MSR) data showcase conference track has encouraged researchers to provide data sets as a basis for further empirical studies. Objective: Examine the usage of data papers published in the MSR proceedings in terms of use frequency, users, and use purpose. Method: Data track papers were collected from the MSR data showcase track and through the manual inspection of older MSR proceedings. The use of data papers was established through manual citation searching followed by reading the citing studies and dividing them into strong and weak citations. Contrary to weak, strong citations truly use the data set of a data paper. Data papers were then manually clustered based on their content, whereas their strong citations were classified by hand according to the knowledge areas of the Guide to the Software Engineering Body of Knowledge. A survey study on 108 authors and users of data papers provided further insights regarding motivation and effort in data paper production, encouraging and discouraging factors in data set use, and future desired direction regarding data papers. Results: We found that 65% of the data papers have been used in other studies, with a long-tail distribution in the number of strong citations. Weak citations to data papers usually refer to them as an example. MSR data papers are cited in total less than other MSR papers. A considerable number of the strong citations stem from the teams that authored the data papers. Publications providing Version Control System (VCS) primary and derived data are the most frequent data papers and the most often strongly cited ones. Enhanced developer data papers are the least common ones, and the second least frequently strongly cited. Data paper authors tend to gather data in the context of other research. [...], journal article, 35 pages, 7 figures, 6 tables

SaaS (Software-as-a-Service) is a cloud computing model, which is sometimes referred to as “on-demand software”. Existing SaaS platforms are investigated before building new distributed SaaS platform. The service data mining and evaluation on existing SaaS platforms improve our new SaaS platform. For SaaS that provide various APIs, we analysis their website data in this paper by our data mining method and related software. We wrote a crawler program to obtain data from these websites. The websites include Baidu API and ProgrammableWeb API. After ETL (Extract-Transform-Load), the obtained and processed data is ready to be analyzed. Statistical methods including non-linear regression and outlier detection are used to evaluate the websites performance, and give suggestions to improve the design and development of our API website. All figures and tables in this paper are generated from IBM SPSS statistical software. The work helps us improve our own API website by comprehensively analyzing other successful API websites.

Technology is shaping our lives in a multitude of ways. This is fuelled by a technology infrastructure, both legacy and state of the art, composed of a heterogeneous group of hardware, software, services, and organisations. Such infrastructure faces a diverse range of challenges to its operations that include security, privacy, resilience, and quality of services. Among these, cybersecurity and privacy are taking the centre-stage, especially since the General Data Protection Regulation (GDPR) came into effect. Traditional security and privacy techniques are overstretched and adversarial actors have evolved to design exploitation techniques that circumvent protection. With the ever-increasing complexity of technology infrastructure, security and privacy-preservation specialists have started to look for adaptable and flexible protection methods that can evolve (potentially autonomously) as the adversarial actor changes its techniques. For this, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) were put forward as saviours. In this paper, we look at the promises of AI, ML, and DL stated in academic and industrial literature and evaluate how realistic they are. We also put forward potential challenges a DL based security and privacy protection system has to overcome. Finally, we conclude the paper with a discussion on what steps the DL and the security and privacy-preservation community have to take to ensure that DL is not just going to be hype, but an opportunity to build a secure, reliable, and trusted technology infrastructure on which we can rely on for so much in our lives.

The facility layout is a strategic design that is used for a long time. All manufacturing industries must pay attention to the right layout to increase the productivity of the industry. A prayer paper manufacturing industry located in the Tanjung Morawa area, Medan has an error in the placement of raw materials and the placement of production machines, so that the distance from the temporary warehouse to the printing and cutting work stations is far apart, causing high material handling costs. Seeing these problems, research was carried out to improve the layout of the facilities and redesign. The method used for this research is Systematic Layout Planning (SLP), which is one of the methods used to regulate a workplace in a factory by using two areas with high frequency and logical relationships with each other. And the Computerized Relative Allocation of Facilities Technique (CRAFT) Algorithm is a repair program, which is a program that looks for optimal design by making gradual improvements to the layout. CRAFT evaluates the layout by interchanging departmental locations. Inputs required for the CRAFT algorithm include initial layout, data flow or frequency of movement, cost data per unit distance, and the number of departments that do not change or remain. The CRAFT method is usually applied using Quantitative Systems (QS) software. By comparing the layout between SLP and CRAFT, the optimal result is obtained using the SLP method by reducing the distance between departments by 1.407 meters or a distance efficiency of 39.91%.

Due to the increasing size of s (s), their design and optimization phases (i.e., ) grow increasingly complex. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. At run time, a large configuration space needs to be searched to find the best set of parameters (e.g., voltage/frequency) to further optimize the system. Both spaces are infeasible for exhaustive search typically leading to heuristic optimization algorithms that find some trade-off between design quality and computational overhead. ML can build powerful models that have successfully been employed in related domains. In this survey, we categorize how () may be used and is used for design-time and run-time optimization and exploration strategies of s. A meta-study of published techniques unveils areas in that are well-explored and underexplored with, as well as trends in the employed algorithms. We present a comprehensive categorization and summary of the state of the art on for. Finally, we summarize remaining challenges and promising open research directions.

Elisabeth Bik quit her job to spot errors in research papers — and has become the public face of image sleuthing. Elisabeth Bik quit her job to spot errors in research papers — and has become the public face of image sleuthing.

Paper-based digital microfluidic biochips (P-DMFBs) have recently emerged as a promising low-cost and fast-responsive platform for biochemical assays. In P-DMFBs, electrodes and control lines are printed on a piece of photograph paper using an inkjet printer and carbon nanotubes (CNTs) conductive ink. Compared with traditional digital microfluidic biochips (DMFBs), P-DMFBs enjoy significant advantages, such as faster in-place fabrication with printer and ink, lower costs, and better disposability. Since electrodes and CNT control lines are printed on the same side of this paper, a critical design challenge for P-DMFB is to prevent control interference between moving droplets and the voltages on CNT control lines. Control interference may result in unexpected droplet movements and thus incorrect assay outputs. To address this design challenge, a control-fluidic codesign methodology is proposed in this paper, along with two demonstrative design flows integrating both fluidic design and control design, i.e., the droplet-oriented codesign flow and the electrode-oriented codesign flow. The droplet-oriented flow is suitable for designing biochips with sparse electrodes and relatively larger number of droplets, whereas the electrode-oriented flow is suitable for biochips with dense electrodes and smaller number of droplets. The computational simulation results of real-life bioassays demonstrate the effectiveness of the proposed codesign flows.

In this paper, we propose a novel paper currency defect detection algorithm using quaternion uniform strength. We first build paper currency image preprocessing integration framework which includes intensity balancing, paper currency location, and geometric correction. We then propose a global–local paper currency image registration algorithm by moving key areas within certain range which can eliminate the false difference effectively. Finally, the quaternion uniform strength is calculated by using quaternion convolution edge detector. The defect degree of paper currency is determined by using the quaternion uniform color difference. The proposed algorithm is tested using different datasets from five countries: CNY, USD, EUR, VND, and RUB. The experimental results demonstrate that the proposed algorithm yields better results than the existing state-of-the-art paper currency defect detection techniques. The demo of the proposed paper currency defect detection algorithm will be publicly available.

The aim of this contribution is to show the detection of seminal papers using data mining techniques. To achieve the objective of this research, Rapidminer Studio software and its data mining tools are used, based on data created with information extracted from Google Scholar and Scopus, in three different areas of knowledge. In this process, other softwares such as Microsoft Excel and Publish or Perish are used. Comparing the results obtained for the searches in Knowledge Management, Entrepreneurship and Marketing, it was obtained that there is no marked similarity between the sets of articles that were obtained in Google Scholar and Scopus. The values for the Similarity Index remained below 0.52%, similar between Knowledge Management and Entrepreneurship but decreasing for Marketing. The detection of outliers using Data Mining techniques and in particular using Rapidminer, allowed to determine the seminals papers for the three search terms analyzed and allowed to characterize these in the space, in Google Scholar and Scopus. It was shown that the seminal articles can be different if Google Scholar or Scopus is used. The results suggest determining for other search terms whether the trend found is maintained or not.

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.

Formal specification, model checking and model-based testing are recommended techniques for engineering of mission-critical systems. In the meantime, those techniques struggle to obtain wide adoption due to inherent learning barrier, i.e. it is considered difficult to use those methods. There is also a common difficulty in translating the specifications in natural language, a common practice nowadays, to formal specifications. In this position paper we discuss the concept of an end-to-end methodology that helps identify specifications from various sources, automatically create formal specifications and apply them to verification of cyber-physical systems. Thus, we intent to address the challenges of creation of formal specifications in an efficient automated and tool-supported manner. The novelty of the approach is analyzed through a survey of state of the art. It is currently planned to implement this concept and evaluate it with industrial case studies.

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.

Video cameras are becoming ubiquitous in our daily lives. With the recent advancement of Artificial Intelligence (AI), live video analytics are enabling various useful services, including traffic monitoring and campus surveillance. However, current video analytics systems are highly limited in leveraging the enormous opportunities of the deployed cameras due to (i) centralized processing architecture (i.e., cameras are treated as dumb streaming-only sensors), (ii) hard-coded analytics capabilities from tightly coupled hardware and software, (iii) isolated and fragmented camera deployment from different service providers, and (iv) independent processing of camera streams without any collaboration. In this paper, we envision a full-fledged system for software-defined video analytics with cross-camera collaboration that overcomes the aforementioned limitations. We illustrate its detailed system architecture, carefully analyze the key system requirements with representative app scenarios, and derive potential research issues along with a summary of the status quo of existing works.

In this paper, we demonstrate how to conduct OD analysis based on big taxi trajectory data with XStar in an efficient manner. XStar, originally developed by the first author, is a standalone software system dedicated to trajectory-data users with little programming skills and affordable computing devices. Since its release in Jan. 2019, it has received downloads of over 4000 by May 2021.