Search

This research studied the strategies that players use in sequential adversarial games. We took the Rock-Paper-Scissors (RPS) game as an example and ran players in two experiments. The first experiment involved two humans, who played the RPS together for 100 times. Importantly, our payoff design in the RPS allowed us to differentiate between participants who used a random strategy from those who used a Nash strategy. We found that participants did not play in agreement with the Nash strategy, but rather, their behavior was closer to random. Moreover, the analyses of the participants’ sequential actions indicated heterogeneous cycle-based behaviors: some participants’ actions were independent of their past outcomes, some followed a well-known win-stay/lose-change strategy, and others exhibited the win-change/lose-stay behavior. To understand the sequential patterns of outcome-dependent actions, we designed probabilistic computer algorithms involving specific change actions (i.e., to downgrade or upgrade according to the immediate past outcome): the Win-Downgrade/Lose-Stay (WDLS) or Win-Stay/Lose-Upgrade (WSLU) strategies. Experiment 2 used these strategies against a human player. Our findings show that participants followed a win-stay strategy against the WDLS algorithm and a lose-change strategy against the WSLU algorithm, while they had difficulty in using an upgrade/downgrade direction, suggesting humans’ limited ability to detect and counter the actions of the algorithm. Taken together, our two experiments showed a large diversity of sequential strategies, where the win-stay/lose-change strategy did not describe the majority of human players’ dynamic behaviors in this adversarial situation.

Most of today's graph analytics systems model static graphs and do not support business use cases that require the ability to: (i) query the dynamic graph data for a time-evolving system, (ii) carry out investigations on its historical evolution, and (iii) audit past business decisions made with potentially stale or incorrect data. This position paper presents our vision for bi-temporal dynamic graph analytics, and sketches a design for a system that efficiently supports these requirements.

Artificial Neural Network (ANN) techniques have grown rapidly in recent years, due to high computational rate and a good ability to control nonlinear control. This paper presents classical and ANN controllers for headbox parameters. The ANN is simulated and analyzed using MATLAB Simulink. The neural network controller is used to determine real-time values for headbox parameters. A comparison is made between classical and ANN controllers.

The early diagnosis of Alzheimer’s disease (AD) remains a challenge for medical scientists worldwide, leading to a number of research efforts that focus on biosensor development for AD biomarkers. However, the application of these complicated biosensors is limited in medical diagnosis, due to the difficulties in robust sensing platform development, high costs, and the necessity for technical professionals. We successfully developed a robust straightforward manufacturing process for the fabrication of multi-chamber paper devices using the wax printing method and exploited it to detect amyloid beta 42 oligomers (AβO42, a significant biomarker of AD) using copper-enhanced gold nanoprobe colorimetric immunoblotting. Small hydrophilic reaction chambers could concentrate the target sample to the desired size to improve the sensing performance. The copper-enhanced gold nanoprobe immunoblot using the designed multi-chamber platform exhibited a highly sensitive performance with a limit of detection of 320 pg/mL by the naked eye and 23.7 pg/mL by a smartphone camera. This process from sensing manufacture to sensing conduction is simple to perform whenever medical technicians require time- and cost-savings, without complicated instruments or the need for technical professionals, making it feasible to serve as a diagnostic tool worldwide for the early monitoring of AD and scalable devices for the sensing application of various biomarkers in clinical settings.

Oil-paper insulation is the key insulation structure of the transformers, whose aging condition is closely related to the operations of the equipment. The degree of polymerization (DP) is the direct parameter characterizing the aging condition of oil-paper insulation. Recently, the near infrared spectroscopy (NIRS) measurement powered by quantitative analysis is used to evaluate DP of the insulating papers mainly. While the applications of NIRS for DP evaluation is constrained because the present spectral quantitative analysis method is not accurate and stable enough, especially for onsite tests. In this paper, we propose a Gaussian process regression (GPR) method to predict DP of the oil- paper insulation in laboratory as well as in field. Firstly, the basic principles of GPR algorithm are illustrated. A GPR model for DP prediction is established based on the spectra of differently aged insulating paper samples which are prepared in laboratory. The GPR model show a high prediction accuracy both for training set and testing set. The established GPR model is finally applied on the DP prediction of insulating papers originating from a de-tanked transformer. The accurate predicted DP and the reliable aging assessment results indicate that the established model can be implemented on site.

To explore whether the brain contains pattern differences in the rock–paper–scissors (RPS) imagery task, this paper attempts to classify this task using fNIRS and deep learning. In this study, we designed an RPS task with a total duration of 25 min and 40 s, and recruited 22 volunteers for the experiment. We used the fNIRS acquisition device (FOIRE-3000) to record the cerebral neural activities of these participants in the RPS task. The time series classification (TSC) algorithm was introduced into the time-domain fNIRS signal classification. Experiments show that CNN-based TSC methods can achieve 97% accuracy in RPS classification. CNN-based TSC method is suitable for the classification of fNIRS signals in RPS motor imagery tasks, and may find new application directions for the development of brain–computer interfaces (BCI).

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.

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.

Replication data and results for Langenhorst, Jan/Frommherz, Yannick/Meier-Vieracker, Simon: Keyness in song lyrics. Challenges of highly clumpy data. In: Journal for Language Technology and Computational Linguistics. This data set contains * Python module used to obtain results presented in paper * Jupyter Notebooks to generate results and create plots * Complete keyword/key-ngram lists * A 'shuffled' version of the songkorpus used in our analysis (replication of ngrams not possible, only keywords)

Graphical Abstract Illustration of the assembly, distribution, and point-of-care use of a rapidly-deployable, cell-free COVID-19 biosensor: 1) Assemble: Assembling CFPS reagents by mixing E. coli lysate, murine RNase Inhibitor (mRI), energy sources, cofactors, and toehold switch riboregulator plasmid. 2) Print: aliquoting CFPS reagents onto paper substrates housed in a plastic test cassette. 3) Dehydrate: lyophilizing CFPS reagents on paper substrates. 4) Distribute. 5) Saliva sample: applying saliva samples onto cassette without pretreatments. 6) Reaction: bioluminescent protein expression in presence of target RNA (+), or ribosome detachment in absence of target RNA (-). 7) Visual result: bioluminescent output in the presence of target RNA and NanoLuc luciferase expression., The COVID-19 pandemic has illustrated the global demand for rapid, low-cost, widely distributable and point-of-care nucleic acid diagnostic technologies. Such technologies could help disrupt transmission, sustain economies and preserve health and lives during widespread infection. In contrast, conventional nucleic acid diagnostic procedures require trained personnel, complex laboratories, expensive equipment, and protracted processing times. In this work, lyophilized cell-free protein synthesis (CFPS) and toehold switch riboregulators are employed to develop a promising paper-based nucleic acid diagnostic platform activated simply by the addition of saliva. First, to facilitate distribution and deployment, an economical paper support matrix is identified and a mass-producible test cassette designed with integral saliva sample receptacles. Next, CFPS is optimized in the presence of saliva using murine RNase inhibitor. Finally, original toehold switch riboregulators are engineered to express the bioluminescent reporter NanoLuc in response to SARS-CoV-2 RNA sequences present in saliva samples. The biosensor generates a visible signal in as few as seven minutes following administration of 15 μL saliva enriched with high concentrations of SARS-CoV-2 RNA sequences. The estimated cost of this test is less than 0.50 USD, which could make this platform readily accessible to both the developed and developing world. While additional research is needed to decrease the limit of detection, this work represents important progress toward developing a diagnostic technology that is rapid, low-cost, distributable and deployable at the point-of-care by a layperson.

We attempt to replicate 67 papers published in 13 well-regarded economics journals using author-provided replication files that include both data and code. Some journals in our sample require data and code replication files, and other journals do not require such files. Aside from 6 papers that use confidential data, we obtain data and code replication files for 29 of 35 papers (83%) that are required to provide such files as a condition of publication, compared to 11 of 26 papers (42%) that are not required to provide data and code replication files. We successfully replicate the key qualitative result of 22 of 67 papers (33%) without contacting the authors. Excluding the 6 papers that use confidential data and the 2 papers that use software we do not possess, we replicate 29 of 59 papers (49%) with assistance from the authors. Because we are able to replicate less than half of the papers in our sample even with help from the authors, we assert that economics research is usually not replicable. We conclude with recommendations on improving replication of economics research. JEL Codes: B41; C80; C82; C87; C88; E01

In recent times, it has been witnessed that wireless systems based on IoT-based have developed rapidly in various sectors. The IoT (Internet of Things) is the network in which physical devices, equipment, sensors and other objects can communicate among themselves without human involvement. The WSN (Wireless Sensor Network) is a central component of the IoT, which has proliferated into several different applications in real-time. The IoT and WSNs now have various critical and non-critical applications impacting nearly every area of our everyday life. WSN nodes are usually small and battery-driven machines. Thus, the energy effective data aggregation techniques that increase the lifespan of the network are highly significant. Various approaches and algorithms for energy-efficient data aggregation in IoT-WSN systems were presented. This paper reviews the literature with specific attention to aspects of wireless networking for the preservation of energy and aggregation of data.

We consider the problem of communicating over a channel that randomly “tears” the message block into small pieces of different sizes and shuffles them. For the binary torn-paper channel with block length $n$ and pieces of length ${\mathrm{ Geometric}}(p_{n})$ , we characterize the capacity as $C = e^{-\alpha }$ , where $\alpha = \lim _{n\to \infty } p_{n} \log n$ . Our results show that the case of ${\mathrm{ Geometric}}(p_{n})$ -length fragments and the case of deterministic length- $(1/p_{n})$ fragments are qualitatively different and, surprisingly, the capacity of the former is larger. Intuitively, this is due to the fact that, in the random fragments case, large fragments are sometimes observed, which boosts the capacity.

Triboelectric nanogenerators (TENGs) have been investigated as a promising device to harvest mechanical energy into electricity. At present, paper-based triboelectric nanogenerators (P-TENGs) have been widely researched because paper features with lightweight, low cost, abundance, renewability and biodegradability. In this paper, the operating principles and operation modes of TENGs, the development progress and performance enhancement routes of P-TENGs are comprehensively reviewed. Additionally, the overview, challenges and opportunities of P-TENGs applications are also presented.

The production of enormous quantities of waste papers is evident in any large institution, particularly educational institutions such as schools or universities. It's also feasible to make good use of recycled paper (craft papers, registers etc). So, rather than throwing away the waste papers, recycling them makes sense. A paper-recycling machine that may be operated manually was conceived and built. This was done to allow for the conversion of waste paper into a useful product in the home. The machine unit's design has been created in accordance with all essential component requirements. In addition, the overall cost is minimal, and there is no requirement for power.

The Internet was initially used to transfer data packets between users and data sources with a specific IP address. Due to advancements, the Internet is being used to share data among different small, resource constrained devices connected in billions to constitute the (IOT) Internet of things .In addition, the paper discusses about wireless LAN Wi-Fi technology i.e. wireless local area network protocol and on a larger scale, mobile communication technology, that is used to provide connectivity to the internet, the wide area network. The paper draws an attention towards the background of IOT and its distinction with other technologies, discussion on network optimization in IOT. This paper not only reviews, compares and consolidates the recent related works, but also admires the author’s findings, solutions and discusses its usefulness towards network optimization in IOT. The uniqueness of this paper lies in the review of network optimization issues and challenges in IOT. In this paper, a comprehensive survey on the network optimization in IOT is presented.

One way of exposing predatory journals is to submit a spoof article to see if it gets accepted. We investigate one journal, looking at how it has performed since a spoof paper it accepted came to light. We find that it has published almost 20% more papers following the acceptance of the spoof paper. The journal has a new web site, which appears to show that it did not publish its first paper until 2018. However, there is an old web site that lists 321 papers dating back to 2012. The editors said that this is due to a new workflow system, which meant that previously published papers could not be listed on the new web site. Moreover, the number of papers could be not accommodated, as a high configuration server would be required to provide a responsive web site. We found some plagiarism, which looks quite serious. We conclude that the spoof paper had little effect on the journal, which continues to operate, seven years after the spoof paper was accepted.

PurposeProductivity improvement is key to sustainability performance improvements of organizations. In a real-world scenario, the nature of inputs and outputs is likely to be imprecise and vague, leading to complexity in comparing firms' efficiency measurements. Implementation of fuzzy-logic based measurement systems is a method for dealing with such cases. This paper presents a fuzzy weight objective function to solve Data Envelopment Analysis (DEA) CCR model for measuring paper mills' performance in India for 15 years.Design/methodology/approachAn integrated methodology is proposed to solve DEA models having fuzzy weights. The fuzzy DEA methodology is an extended version of the DEA approach that researchers have used for performance measurement purposes in imprecise and vague scenarios. The ecological performance of the paper industry is evaluated, considering some desirable and undesirable outputs. The effect of non-discretionary input on the performance of a paper mill is also analyzed.FindingsAnalysis suggests that the productivity of the paper industry is improving consistently throughout the period. The comparative evaluation of methods suggests that a diverse cluster of DMUs and integration of DEA with the fuzzy logic increases the diversity in the efficiency score while DEA-DE imitates the results of CCR DEA.Originality/valueProposed a fuzzy DEA-based analytical framework for measuring the paper industry's ecological performance in an imprecise and vague scenario. The model is tested on data from the paper industry in a developing country context and comparative performance analysis using DEA, fuzzy DEA and DE algorithm is done.

The history of printing technology in Korea is studied by investigating existing ancient documents and records and comparing accumulated data and knowledge. Cultural property research requires non-destructive testing and observation with the naked eye or aided by a microscope. Researchers’ experience and knowledge are required even though they cannot guarantee the outcome. For ancient documents and records that are presumed to consist of woodblock printing, wood type printing, metal type printing, or their combinations, each researcher draws various opinions and conclusions. This often causes confusion and divides the opinions of ordinary citizens and field specialists. Among them, the criteria for judging ancient documents or books printed using woodblock and metal movable material are ambiguous. Academic research on the development history of printing technology in ancient Korea has been stagnant, and conflicts among researchers have also erupted. Involvement of national investigative agencies not specialized in cultural properties has exacerbated the situation. In this study, we investigated printing characteristics that are likely to serve as more objective judgment criteria by quantitatively analyzing the experiments of retrieving several sheets of Korean paper (Hanji) using a replicated Hunminjeongeum (訓民正音) woodblock and quantitatively analyzing the images of the printed papers. In addition, the validity and questions for the typical phenomena presented as a method for distinguishing between woodblock and metal print are reviewed. We investigated the possibility of developing new objective judgement criteria through quantitative analysis using image analysis and investigating the printing characteristics of Korean paper through a reproduction experiment of woodblock printing.

This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovation breakthroughs. The potential value of data sharing across industrial domains is estimated at over $100 billion, particularly in view of optimising manufacturing processes. Data sharing across domains however faces a series of well-documented challenges associated with the lack of semantic interoperability and related standards, management of trust and sustainability. Solving bottlenecks in data sharing requires a systemic approach to data management, which can account for all aspects of data use, levels of application, attribution and dynamic exchanges. In this paper we propose a high-level ecosystem approach that integrates societal values with digital affordances of industry's cognitive-assisted processes, remote interfacing, hybrid applications and large-scale value networks. Early development of an Ontology Commons EcoSystem (OCES) is presented as the key enabling framework for Industry Commons interoperability and a series of enabling frameworks form the basis of future research directions in Trusted Data Sharing and Closed-Loop Lifecycle Management for greater sustainability.

PurposeSynergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.Design/methodology/approachThe synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.FindingsThe findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.Originality/valueIn a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.

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.

The use of waste paper as a fibrous semi-finished product in the production of paper and paperboard products makes it possible to somewhat reduce the consumption of cellulose. However, waste paper contains a number of water-polluting components of mineral and organic nature, which were introduced into its composition at the stage of production. One of the issues that may arise in the design of technological systems for the production of a given type of paper or cardboard or in the reconstruction of existing production to reduce losses of fibrous semi-finished products and ensure their optimal use or reduce fresh water consumption is to calculate the pollution and also to determine the impact of cardboard and paper production tanks and treatment plants on the dynamics and level of watercourse pollution. To study and analyze the paper and cardboard production processes, which belong to the class of complex technological systems, a methodology was developed that, using computer technology, allows assessing the state of a technological system until its implementation in action. However, from a practical point of view, methods still should be developed that will allow the designer to find solutions to problems that may arise at the design stage of the technological system for production of a given type of paper or cardboard or in the reconstruction of existing production. These problems are related to the calculation of the pollution level and the determination of impact from cardboard and paper production tanks and treatment facilities. The purpose of this article is to conduct research and forecast calculations based on mathematical models to determine the patterns of influence exerted by tanks on the dynamics and level of watercourse pollution in the production of paper and cardboard. The generalized technological system of cardboard production, which is presented in the form of a material flow graph, is taken as an object for research. Water-soluble contaminants of mineral and organic nature enter the production system together with fibrous raw materials, partly with fresh water, and with chemical additives used to impart certain qualities to the product at the stage of its production and at the stage of mechano-chemical water purification. In order to study their impact, it is necessary to conduct at least two stages of calculations on a personal computer using pre-designed models for the dynamics and level of watercourse pollution. At the first stage, the dynamic characteristics of each element of the technological system were equated to elements that do not have a dynamic delay and for which the passage of all watercourses is subject to the speed at which the cardboard web is cast on the mesh. The number of cycles before equilibrium is 99. In the second stage of calculations, it was taken into account that the four tanks in the technological system of production are characterized by a moment of delay and, therefore, the values ​​of delay factors were chosen based on water reserves that accumulate in these basins. The number of cycles before equilibrium in the second stage increased to 264. The main conclusion from the analysis of two options: the technological system in both cases goes to equilibrium at equal values ​​for all components of water-soluble mineral and organic components. However, there are often situations when, in the process of developing (designing) a complex technological system for the production of paper or cardboard, developers are interested in the weighted average concentration of water-soluble mineral components that most affect the state of water flows, and then the technological system can be simplified and presented as a single container linked to the environment. Analysis of the calculation formula of the time for the technological system to reach equilibrium shows that the time value is largely determined by the ratio of the water capacity (W) of the process system to the amount of water (BS) removed from the system. The greater the water capacity of the technological system and the smaller the BS, the longer the time the technological system reaches equilibrium. The next step of the study is to verify the results obtained on the basis of adequate mathematical models in actual production conditions.

Cloud computing is an architecture for facilitating computing service through the internet on requirement and pay per use access to a group of shared resources namely networks, storage, servers, services and applications, without physically acquiring them Cloud DBMS is a distributed database that gives computing as a service. It is sharing of web infrastructure for resources, software and information over a network. The cloud is used as a storage location and database can be accessed and computed from anywhere. In this paper I have discussed about cloud and its use. How we can implement cloud for better performance and different benefits and drawbacks of cloud which we can improve in future Cloud computing has received increasing interest from enterprises since its inception. With its innovative information technology (IT) services delivery model, cloud computing could add technical and strategic business value to enterprises. However, cloud computing poses highly concerning internal (e.g., Top management and experience) and external issues (e.g., regulations and standards). This paper presents a systematic literature review to explore the current key issues related to cloud computing adoption. This is achieved by reviewing 15 articles published about cloud computing adoption. Using the grounded theory approach, articles are classified into eight main categories: in-ternal, external, evaluation, proof of concept, adoption decision, implementation and integration, IT governance, and confirmation. Then, the eight categories are divided into two abstract categories: cloud computing adoption factors and processes, where the former affects the latter. The results of this review indicate that enterprises face serious issues before they decide to adopt cloud computing. Based on the findings, the paper provides a future information systems (IS) research agenda to explore the previously under-investigated areas regarding cloud computing adoption factors and processes. This paper calls for further theoretical, methodological, and empirical contributions to the research area of cloud computing adoption by enterprises.

Activating flux is made up of inorganic material mixed with a volatile medium. The objective of this study is to identify and review the literature in activating flux, and different type of welding techniques. For that purpose, a structured review method is adopted and the Scopus database is used as a primary source for the selection of papers. The papers were identified using the string term of “Activating flux” OR “Activated flux” in the title of papers. And a total of 238 papers were identified for the study. Besides the above few other papers were also reviewed and the materials used, the type of flux used, and the findings of different combinations were highlighted in the form of tables. The findings of the study provide a comprehensive understanding of the different type of welding techniques focusing on TIG welding, and the different combination of flux used and their impact was summarized.

Sistem QCS (Quality Control System) bisa memonitor kualitas kertas secara in-line saat proses produksi. Sistem QCS dapat mengeluarkan data kualitas kertas dalam bentuk log file teks. Data pada log file teks dapat diolah dan dianalisa untuk menjadi informasi kualitas kertas dengan parameter-parameter yang terdiri dari : basis weight (gramature), ash titrasi, moisture content, opasitas dan porositas. Informasi kualitas kertas ini disebut informasi paper profile. sistem Pengolahan Data Log QCS Menjadi Informasi Paper Profile pada penelitian ini dikembangkan dengan menggunakan metodologi prototyping dan bahasa pemrograman Visual Basic .Net. Pengolahan data pada sistem ini menggunakan metoda SPC (Statistical Process Control) dan memanfaatkan fasilitas-fasilitas yang dimiliki oleh Microsoft Excel yaitu pemrograman VBA, fungsi-fungsi statistik dan kemampuan membuat tampilan grafis yang menarik dan sudah sangat dikenal oleh pengguna komputer. Sistem informasi paper profile akan menyimpan dan mendistribusikan informasi paper profile melalui sebuah aplikasi berbasis web kepada pihak-pihak yang berkepentingan. Sehingga informasi paper profile dapat dibuat dan didistribusikan dengan mudah dan cepat . Informasi paper profile ini diperlukan untuk mengetahui kualitas produk dan untuk memonitor kapabilitas proses dalam menghasilkan produk. Kata kunci : QCS, Log File, Paper Profile, Statistical Process Control

These days, we receive most information through digital mediums such as emails and social networking applications. Investigating the characteristics of human-paper interactions can help us design more meaningful interactions and better understand why people use paper documents in the age of digitalization. In this study, the interaction of people with physical documents was studied through a mixed-method of conducting a literature review, gathering expert opinions, interviewing subjects, and analysing Instagram photos. By codifying the gathered information, the human-paper interaction framework was developed. This framework articulates the advantages of physical documents compared to electronic documents and serves researchers and practitioners by providing insightful human factors about human-document interaction. Finally, we propose six design themes as the solutions to the findings of this study. These implications can provide practical foundations for future design and research.

Space Resource Utilization could reduce the mass, cost, and risks of future space activities. The many nonlinear and compounding effects mean that seemingly insignificant concept of operations choices can invalidate the conclusions of sophisticated analyses. Here we successively relax self-imposed constraints in a recent publication to demonstrate that the proximity of a market and the benefits of aerobraking cannot be omitted.

A point-of-care (POC) can be defined as an in vitro diagnostic test that can provide results within minutes. It has gained enormous attention as a promising tool for biomarkers detection and diagnosis, as well as for screening of chronic noncommunicable diseases such as diabetes mellitus. Diabetes mellitus type 2 is one of the metabolic disorders that has grown exponentially in recent years, becoming one of the greatest challenges to health systems. Early detection and accurate diagnosis of this disorder are essential to provide adequate treatments. However, efforts to reduce incidence should remain not only in these stages but in developing continuous monitoring strategies. Diabetes-monitoring tools must be accessible and affordable; thus, POC platforms are attractive, especially paper-based ones. Paper-based POCs are simple and portable, can use different matrixes, do not require highly trained staff, and are less expensive than other platforms. These advantages enhance the viability of its application in low-income countries and hard-to-reach zones. This review aims to present a critical summary of the main components required to create a sensitive and affordable enzymatic paper-based POC, as well as an oriented analysis to highlight the main limitations and challenges of current POC devices for diabetes type 2 monitoring and future research opportunities in the field.

International audience; Despite predictions of the paperless office, global demand for printing and writing paper remains strong, and paper appears to be here to stay for some time. Not only firms, but also governments, libraries, and archives are in possession of large collections of legacy documents that still must be sorted and scanned. In this study, terahertz-based techniques are demonstrated to address several routine tasks related to the automated paper handling of unsorted legacy documents. Specifically, we demonstrate terahertz-based counting of the number of sheets in unconsolidated paper stacks, as well as locating stapled documents buried in paper stacks.

Text summarization is one problem in natural language processing that generates a brief version of the original document. This research took attention for some researchers in this last decade and growing fast, including Indonesia language. This paper aims to recap summarization text research especially in Indonesia language. As usual, this paper discusses two summarization approaches, extractive and abstractive. In fact, the number of research of extractive is more than abstractive. This paper investigates some methods such as Statistical Based Approach, Graph Based Approach, Machine Learning Approach, Fuzzy Logic Approach, Algebraic Approach, and Hybrid Approach. This paper shows some methods details and summarize the results. Keywords— Text summarization, extractive summary, abstractive summary, natural language processing

Many Indonesian spelling errors occur in research papers published to the public, closely related to academics in all institutions such as research institutions, government, schools, and universities. The spelling errors usually writing punctuation, writing letters, writing words, writing words originating from foreign or regional languages (uptake words), using affixed words, and writing ineffective sentences. The mistakes made by the academics then become a cycle in the academic environment. They usually provide guidance for writing an undergraduate thesis, thesis, dissertations to students, or the other forms of documents and scientific papers. Therefore, the research proposed the application to facilitate all authors of scientific papers in producing quality scientific works based on the General Guidelines for Indonesian Spelling published by the Agency for Development and Language Development. The application is named KEBI 1.0 Checker (Indonesian Spelling Error 1.0 Checker), a web-based application with a built-in algorithm to detect and correct Indonesian Spelling in scientific papers. The experiment result shows that the application has given the best accuracy performance to correct the non-standard words, and typographical errors reached 100% and 55,52%, respectively. The application also has been detected 209 meaningless words. The application processing time is relatively low, the average time needed to correct non-standard words is 0.016 seconds, and typo words are 14.58 seconds. KEBI 1.0 Checker is helpful for the end-user in academics but needs to improve the vocabulary of the large corpus in various fields of science for correcting typo words.

Foundation paper piecing is a popular technique for constructing fabric patchwork quilts using printed paper patterns. But, the construction process imposes constraints on the geometry of the pattern and the order in which the fabric pieces are attached to the quilt. Manually designing foundation paper pieceable patterns that meet all of these constraints is challenging. In this work we mathematically formalize the foundation paper piecing process and use this formalization to develop an algorithm that can automatically check if an input pattern geometry is foundation paper pieceable. Our key insight is that we can represent the geometric pattern design using a certain type of dual hypergraph where nodes represent faces and hyperedges represent seams connecting two or more nodes. We show that determining whether the pattern is paper pieceable is equivalent to checking whether this hypergraph is acyclic, and if it is acyclic, we can apply a leaf-plucking algorithm to the hypergraph to generate viable sewing orders for the pattern geometry. We implement this algorithm in a design tool that allows quilt designers to focus on producing the geometric design of their pattern and let the tool handle the tedious task of determining whether the pattern is foundation paper pieceable.

Summary Objective: To identify and highlight research papers representing noteworthy developments in signals, sensors, and imaging informatics in 2020. Method: A broad literature search was conducted on PubMed and Scopus databases. We combined Medical Subject Heading (MeSH) terms and keywords to construct particular queries for sensors, signals, and image informatics. We only considered papers that have been published in journals providing at least three articles in the query response. Section editors then independently reviewed the titles and abstracts of preselected papers assessed on a three-point Likert scale. Papers were rated from 1 (do not include) to 3 (should be included) for each topical area (sensors, signals, and imaging informatics) and those with an average score of 2 or above were subsequently read and assessed again by two of the three co-editors. Finally, the top 14 papers with the highest combined scores were considered based on consensus. Results: The search for papers was executed in January 2021. After removing duplicates and conference proceedings, the query returned a set of 101, 193, and 529 papers for sensors, signals, and imaging informatics, respectively. We filtered out journals that had less than three papers in the query results, reducing the number of papers to 41, 117, and 333, respectively. From these, the co-editors identified 22 candidate papers with more than 2 Likert points on average, from which 14 candidate best papers were nominated after intensive discussion. At least five external reviewers then rated the remaining papers. The four finalist papers were found using the composite rating of all external reviewers. These best papers were approved by consensus of the International Medical Informatics Association (IMIA) Yearbook editorial board. Conclusions. Sensors, signals, and imaging informatics is a dynamic field of intense research. The four best papers represent advanced approaches for combining, processing, modeling, and analyzing heterogeneous sensor and imaging data. The selected papers demonstrate the combination and fusion of multiple sensors and sensor networks using electrocardiogram (ECG), electroencephalogram (EEG), or photoplethysmogram (PPG) with advanced data processing, deep and machine learning techniques, and present image processing modalities beyond state-of-the-art that significantly support and further improve medical decision making.

PurposeThe industry is relying on the preventive maintenance techniques that can minimize failures and provide industrial plants with effective equipment, but in many companies the maintenance tasks are performed very frequently and not as per plan and do not take into consideration the conditions of the plant and equipments. The failure of each and every component needs to be studied in order to choose the best maintenance strategy. This paper presents a fuzzy VIKOR (Multicriteria Optimization and Compromise Solution) technique which is used in developing a comprehensive approach for maintenance strategy selection in the Deinking plant of the paper industry to choose the appropriate maintenance strategy thereby reducing the unnecessary cost incurred on the maintenance.Design/methodology/approachIn this paper, the Fuzzy VIKOR based methodology was applied for determining the maintenance criticality index of the deinking plant of the paper industry. The effect of failure of components were evaluated by three maintenance experts on five performance criteria that is chance of failure, chance of non-detection, downtime length, severity, spare part criticality. The components were ranked according to the maintenance criticality index and thereby implementing the appropriate maintenance strategy.FindingsThe Fuzzy VIKOR technique was applied to calculate the ranking of various components of paper industry based on the views and judgment of three maintenance experts. The proposed technique suggested the appropriate maintenance strategy for various components taking into consideration the maintenance criticality index of the components.Originality/valueThe proposed technique will help the maintenance managers to solve a discrete problem with non-commensurable and conflicting criteria. The study will help the industries to reduce the unnecessary maintenance tasks and thereby reduce the maintenance cost. This will help the maintenance practitioners in choosing the best and most effective strategy for the organization with regard to the market and company situation especially in the changing business requirement of Industry 4.0.

The printing effect of paper packaging has an impact on the circulation effect of products. Only when the printing effect is good can it attract consumers’ purchasing desire. In this study, based on color management technology, the printing of the designed Bazhong specialty paper packaging was studied. Firstly, the content and process of color management were analyzed, and equipment correction and characterization were introduced. Then, the printing process of Bazhong specialty paper packaging was explored, and the printing equipment and the establishment of the profile file were analyzed. The application of color management achieves a high-quality printing effect, which provides a theoretical reference for its further application in the printing industry.

Paper (or plastic) certificates are considered as a means against different forgery of product quality and brand falsification. It is commonly to use barcodes or data matrices to solve this problem. However such approach does not work usually against such sophisticated attacks as cloning of certificate copies. In the current paper we propose to use a digital watermarking and estimation of inner noises of scanners and printers in order to detect cloning attack effectively. Algorithm of cloning attack detecting is presented. The probabilities of attack missing and false alarm are proved.

Scientific research cooperation and co-authored papers are becoming increasingly popular in the era of big science. However, allocating appropriate credit to each co-author of papers remains a challenge. We consider author contribution declarations according to the contributor roles taxonomy (CRediT) scheme (assigning each co-author to 14 contributor roles) and propose a new method of author contribution to allocate co-authors’ credits reasonably by converting the 14 contributor roles in an article into a binary author-role matrix. Based on the data of PLOS ONE, we further explore the new method’s advantages by comparing with other representative methods: It normalizes the total credits of different articles to 1, avoiding the inflationary bias caused by the increasing number of co-authors; awards different credits per co-author based on the participation rate of contributor roles to avoid the equalization bias; reduces the impact of the increasing number of co-authors on the credit of the first co-author.

Improving the production efficiency is one of the main management tasks for the pulp and paper industry. This can be achieved through the use of automated planning systems, designed to take into account the features and limitations of particular production. Such systems allow, on the basis of orders received from consumers, a voluminous production schedule to be made to take into account the needs for raw materials, the productivity of paper or cardboard machines, and the optimal cutting of the canvas on longitudinal cutting machines. Linear programming method for solving optimization problems. Computer simulation using optimized packages to compare the results with the options used in production. Cutting planning processes were optimized on the basis of standard orders for rolled products of an enterprise in the Kyiv region. The problem of optimizing the cutting planning process and criteria for increasing the production efficiency is formalized. The target function is to increase the profit of production by minimizing material losses in planning the cutting of the master rill and minimizing the storage of related products in production warehouses. To solve the optimization problem, it is proposed to use our own method of calculating the optimal cutting patterns for the manufacture of finished products on a longitudinal cutting machine. The MS Office SOLVER package was used for the calculations. Different cutting options were compared via the target function. Important criteria for this inspection are the fulfillment of the entire order, the availability and storage of related products outside the order, and the minimization of time for the reconfiguration of machines. Longitudinal cutting machines of this production can be adjusted only manually, and it takes a long time. Also, technological restrictions on the allowable width of the edge are an important requirement for cutting patterns. All patterns that do not meet these restrictions cannot be compared. There are three options for comparison. An option is made according to the proposed method and with an optimization package using the Simplex method and a number of technological limitations inherent in this production. An option is selected by the production planner manually taking into account previous experience. And the variant of cutting orders is made by the production management system, which accompanies the process of planning and transfer of tasks for longitudinal cutting machines. The function takes the maximum value in the option offered by the production scheduler. But this option is not optimal, because a person adds rolls to the satellite to improve the cutting map to fulfill all orders. This in turn leads to overfulfillment of orders and production of additional products in a warehouse where they can be stored for years until the expiration date. The option offered by the automotive system does not require the use of accompanying rolls but unfortunately does not meet the requirements for optimal cutting of the material. Automatic cutting leaves a large edge that is already within the maximum allowable limitations of the machines and, moreover, does not lead to the execution of the entire order. This violates the basic requirement for production such as full execution of the order. Therefore, this option cannot be used either. The optimal cut for profit maximization is the option obtained using the roll planning technique. This technique allows the average weight of the roll to be obtained through the use of production history. The estimated weight is used to convert the order from tons to the number of pieces. Cutting patterns for the production of the order in this way are presented and, taking into account the technological limitations of production, can be calculated on the basis of the Simplex method in optimization packages. Such cutting patterns have no satellites and allow the fulfilment of all orders. The roll planning technique reduces the number of clippings and avoids overproduction. The analysed cutting plans show that the use of satellites reduces the profitability of the enterprise and does not always minimize material costs.

In 2018, the community first observed scientific papers in the biomedical literature that seemed to display systematically fabricated data, pointing to the existence of paper mills: unofficial, potentially illegal organizations selling fake scientific manuscripts. In the present article, we share relevant information specifically about the 'raw data' associated with paper mill manuscripts. If a submitted manuscript displays clear indicators of potential paper mill involvement, we found that the raw data at close inspection often raise doubts about their authenticity. In the absence of real data, paper mills may need to fabricate raw data images when responding to requests from journals. Given the necessity to streamline production of fake manuscripts, the alleged raw data might be created using templates. Some potential methods for generating fake Western blot images are discussed. Paying close attention to image data, including graphs, diagrams, plots and tables, ideally at pre-publication stage, can clearly help prevent publication of incorrect and fabricated information.

Social media platforms have had an enormous impact on the dissemination of scientific work and have fared well in covering scientific papers. However, little is known about the general dissemination process from academia to social media and how various factors affect the dissemination of scientific papers at different stages. In this paper, we proposed a two-staged dissemination process to profile the diffusion of scientific papers from academia to social media. A two-step simultaneous equation modeling–artificial neural network approach was adopted to predict the retweet scale of scientific papers on Twitter by combining source-related and content-related factors. The analysis in the field of oncology suggests that the artificial neural network algorithm (ANN) with the input units generated from the simultaneous equation model (3SLS) can predict the retweet scale of scientific papers on Twitter with an accuracy of 78.05%. According to the normalized importance obtained from the ANN, we found that most factors related to the information source play critical roles in promoting the dissemination of scientific papers. The number of first-generation tweets has the most remarkable impact on subsequent dissemination. As for the content-related predictors, tweets attached with more URLs can provide richer information for audiences, thereby increasing the retweet scale of scientific papers. Besides, the influence of research topics on dissemination varies with different audiences. The findings of this study contribute to the literature on the dissemination of scientific papers beyond academia and provide practical implications for scholarly communication.

Text representation is the preliminary work for in-depth analysis and mining of information in scientific papers. It directly affects the effects of downstream tasks such as, scientific papers classification, clustering, and similarity calculation. However, recent researches mainly considered citation network and partial structural information, which is insufficient when representing scientific papers. Therefore, in order to improve the performance of text representation model, this paper proposed MV-HATrans, a text representation model that combines multi-viewpoint information, such as the semantic information of knowledge graph and structural information. This model extracts word information from three aspects, including contextual content, part of speech, and word meaning of WordNet. Based on combination of hierarchical attention mechanism and transformer, the model achieves the full text representation of scientific papers. Finally, this paper uses the binary experimental dataset AAPR, which indicates whether scientific papers are accepted or not, and applies the proposed model of text representation to achieve the goal of automatic quality assessment. Results show that in the quality classification of scientific papers, adopting part-of-speech information and semantic information based on WordNet definitions can effectively achieve the accuracy of prediction as 70.14%. Among all the structural modules, authors and abstracts contributes the most to the quality classification of scientific papers, especially authors as 9.51%.

The Artificial Intelligence (AI) Pet Robot is a combination of various fields of computer science. This paper showcases the various functionalities of our AI Pet. Most of the functionalities showcased use the immage processing modules made available through OpenCV. The pet robot has various features such as emotion recognition, follow routine, mini-game etc. This paper discusses the mini-game aspect of the robot. The game has been developed by using VGG16 convolutional network for identification of the action performed by the user. To improve the accuracy we have made use of background subtraction which gives removes all the unwanted objects from the background and gives a simple cutout of the users hand.