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Objective The purpose of this study was to develop a natural language processing (NLP) pipeline to identify incidental thyroid nodules (ITNs) meeting criteria for sonographic follow-up and to assess both adherence rates to white paper recommendations and downstream outcomes related to these incidental findings. Methods 21583 non-contrast chest CT reports from 2017 and 2018 were retrospectively evaluated to identify reports which included either an explicit recommendation for thyroid ultrasound, a description of a nodule ≥ 1.5 cm, or description of a nodule with suspicious features. Reports from 2018 were used to train an NLP algorithm called fastText for automated identification of such reports. Algorithm performance was then evaluated on the 2017 reports. Next, any patient from 2017 with a report meeting criteria for ultrasound follow-up was further evaluated with manual chart review to determine follow-up adherence rates and nodule-related outcomes. Results NLP identified reports with ITNs meeting criteria for sonographic follow-up with an accuracy of 96.5% (95% CI 96.2-96.7) and sensitivity of 92.1% (95% CI 89.8-94.3). In 10006 chest CTs from 2017, ITN follow-up ultrasound was indicated according to white paper criteria in 81 patients (0.8%), explicitly recommended in 46.9% (38/81) of patients, and obtained in less than half of patients in which it was appropriately recommended (17/35, 48.6%). Discussion NLP accurately identified chest CT reports meeting criteria for ITN ultrasound follow-up. Radiologist adherence to white paper guidelines and subsequent referrer adherence to radiologist recommendations showed room for improvement.

Clear legal content of white papers provides certainty, stability and trust in the relations between all the participants in initial coins offering (ICO) procedures and contributes to the successfu...

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

The pulp and paper industry growingly paid attention to the recycling and maintenance of waste paper products. Each paper-making cycle would lead to a sharp drop in the mechanical properties of the cellulosic paper, which was related to the hornification effect. Here, the recycling performance of the holocellulose paper was studied, compared with that of the cellulosic paper. Holocellulose fibers from sisal were fabricated by a gentle delignification method, and the well-preserved cellulose and hemicellulose components hindered the cocrystallization and aggregation of cellulose fibril. Holocellulose paper exhibited much more favorable recycling properties, compared with cellulosic paper. After 5 runs of recycling, holocellulose paper still shown an ultimate strength as high as 25 MPa (reduced from 35 MPa), a decrease of 27.1 %. However, cellulosic paper experienced a substantial loss in ultimate strength from 35 MPa to 9 MPa, a decrease of about 74 %. This can be attributed to the core-shell structure from cellulose and hemicellulose to weaken the hornification effect.

The clinical importance of blood group (BG) antigens is related to their ability to induce immune antibodies that can cause hemolysis. Yet, ABO and D (Rh) are still considered to be the key antigens for healthy blood transfusion and secondary antigens are the next priority. Serological typing is the most widely used typing method. Rapid and accurate blood grouping plays an important role in some clinical conditions, rather than conventional techniques. Hence, developing a simple and economical model for rapid blood grouping would facilitate these tests. In recent decades, paper-based microfluidics such as μPADs has gained much interest in wide application areas such as point-of-care diagnostic. In this study, we evaluated μPADs that are performed for blood grouping and its recent progress. A comprehensive literature search was performed using databases including PUBMED, SCOPUS, Web of Science and Google Scholar. Keywords were blood grouping or typing, paper analytical device, rapid test, etc. After investigation of search results, 16 papers from 2010 to 2020 were included. Further information in detail was classified in Table 1. Generally, two principles for blood typing μPADs are introduced. The lateral chromatographic flow method and the vertical flow-through method that detects BG in a visual-based manner. To detect results with acceptable clarity many factors and challenges like paper, blood sample, buffer, Ab and RBC interaction and also μPADs stability need to be considered, which are discussed. In conclusion, the simplicity, stability, cheapness, portability and biocompatibility of μPADs for blood grouping confirming its utility and also they have the capability to robust, universal blood-grouping platform. Table 1 Summary of blood grouping tests using paper-based analytical devices Antigens Type of diagnosis Validation method Sample No Accuracy Action time Paper type Stability Sample dilution Buffer Ref A, B, Rh Forward volunteers records 5 - - Whatman No. 4 - 1/2 PBS* (Khan et al. 2010) A, B, Rh Forward gel assay test and conventional slide test 100 100% 1 min Whatman No. 4 and Kleeenex paper towel 7 Days in 4 °C 1/1 NSS (Al-Tamimi et al. 2012) A, B, Rh Forward gel card assay 99 100% 20 Sec + Washing Kleeenex paper towel - 1/1 NSS (Li et al. 2012) A, B, Rh Forward - - - - Kleeenex paper towel - 45/100 PSS (Li et al. 2013) A, B, Rh Forward gel card assay 98 100% 1.5 min Kleeenex paper towel - 85/100 PBS (Guan et al. 2014b) C, E, c, e, K, Jka, Jkb, M, N, S, P1, and Lea Forward gel card assay 266 100% - Kleeenex paper towel - 1/1 NSS (Li et al. 2014b) A, B, Rh Forward and Reverse conventional slide test 96 ≈ 91% 10 min Whatman No. 1 21 Days in 4 °C 1/2 NSS (Noiphung et al. 2015) C, c, E, e, K, k, Fya, Fyb, Jka, Jkb, M, N, S and s, P1, Lea and Leb Forward - 478 - - Kleeenex paper towel - 1/1 NSS, PBS (Then et al. 2015) A, B Forward and Reverse conventional slide test 76 100% 5-8 min Whatman No. 4 38 Days in 4 °C 1/4, 1/1 NSS (Songjaroen and Laiwattanapaisal 2016) D, K Forward volunteers records 210 - 7.5 min Kleenex paper towel - 1/1 NSS (Yeow et al. 2016) A, B, c, e, D, C, E, M, N, S, s, P1, Jka, Jkb, Lea, Leb, Fya, and Fyb Forward and Reverse gel card assay 3550 ≈100% 30 s Fiber glass and cotton linter 180 Days in 25 °C 45/100, 1/1 PBS (Zhang et al. 2017) A, B Forward conventional slide test 598 100% 3 min Whatman No. 113 14 Day in 4 °C 1/1 NSS (Songjaroen et al. 2018) A, B, Rh Forward conventional slide test - - 30 Sec + Washing Unrefined sisal paper - 1/2 NSS (Casals-Terré et al. 2019) A, B, Rh Forward - - - - Whatman No.1 - 1/1 NSS (Ansari et al. 2020) ABORh Forward and Reverse conventional slide test - 100% Unrefined Eucalyptus papers - 1/2 NSS, PBS (Casals-Terré et al. 2020) A, B, Rh Forward - - - 30 Sec + Washing Whatman No. 4 modified with chitosan ≥ 100 days in 25 °C 1/1 NSS (Parween et al. 2020)

Due to the increasing use of the Internet and other online resources, there is tremendous growth in the data of text documents. It is not possible to manage this huge data manually. This has led to the growth of fields like text mining and text summarization. This paper presents a title prediction model for research papers using Recursive Recurrent Neural Network (Recursive RNN) and evaluates its performance by comparing it with sequence-to-sequence models. Research papers published between 2018 and 2020 were obtained from a standard repository, viz. Kaggle, to train the title prediction model. The performance of different versions of Recursive RNN and Seq2Seq was evaluated in terms of training and hold-out loss. The experimental results show that Recursive RNN models perform significantly better than the other models.

We present a facile paper-based microfluidic device fabrication technique leveraging off-the-shelf carbon paper for the deposition of hydrophobic barriers using a novel "stencil scratching" method. This exceedingly frugal approach (0.05$) requires practically no technical training to employ. Hydrophobic barriers fabricated using this approach offer a width of 3 mm and a hydrophilic channel width of 849 μm, with an ability to confine major aqueous solvents without leakage. The utility of the device is demonstrated by porting a cell viability assay showing a limit-of-detection (LOD) of 0.6 × 108 CFU mL-1 and bilirubin assay with human serum showing a detection range of 1.76-6.9 mg dL-1 and a limit-of-detection (LOD) of 1.76 mg dL-1. The intuitiveness and economic viability of the fabrication method afford it great potential in the field of point-of-care diagnostics geared towards providing testing infrastructure in resource-scarce regions globally.

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.

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.

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

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.

Cyber Forensics is termed as scientific methods or applications in association with the judiciary or court of laws. The aim behind these methods is to unveil the digital evidence to be utilized in court for solving crime cases. This sort of technology wasn’t practiced before therefore most criminals tend to urge away with their criminal acts without valid proof to incriminate or prosecute them. During that time the oaths, confessions, testimonies from witnesses were the sole determining factors of evidence Crimes committed within electronic or digital domains, particularly within cyberspace, have become common. Criminals are using technology to commit their offenses and make new challenges for law enforcement agents, attorneys, judges, military, and security professionals. Digital forensics has become a vital instrument in identifying and solving computer-based and computerassisted crime. This paper provides a quick introduction to cyber forensics. During this paper we present a typical model for both Incident Response and Computer Forensics processes which mixes their advantages in an exceedingly flexible way: It allows for a management oriented approach in digital investigations while retaining the chance of a rigorous forensics investigation. Keywords: cyber forensics, digital forensic science, computer forensics, evidence, judicial system.

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

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.

Internet of Things (IoT) has drawn important attention in recent years since it has made revolutionary changes in human life. The IoT enables the exchange of information or data in a wide variety of applications such as smart buildings, smart health, smart transport, and so on. As billions of connected things communicate with each other and can interchange sensitive information that may be revealed. Hence, strengthening IoT’s security and preserving users’ privacy is a crucial challenge. The aim of this paper is to provide a comprehensive study of the IoT security. Several IoT security attacks are examined and a taxonomy of the security requirements based on the attacks purposes is proposed. Furthermore, recent security solutions are described and classified based on their application area. Ultimately, open research directions and security challenges are discussed.

Due to the growth of e-commerce, most of the banking transactions are made on the online platform and all these transactions are made on the websites provided by the merchant or the payable apps and because of this the vulnerability of attacks has increased and there are also chances of using fraudulent websites and apps by the attackers though there are many high-security algorithms are been used for safeguarding against vulnerabilities. The way of judging the relation of trust on the online platform has become a major issue, so a proper trust model also needs to be maintained. In this paper, we reviewed various security algorithms which involve cryptographic algorithms, machine learning, anonymization, and masking techniques, blockchain, distributed networks, and many more to provide integrity, privacy, reliability, authentication, security, and risk-less e-commerce platform.

This study explored the relationship between syntactic complexity and rhetorical functions and the relationship between syntactic complexity and level of move/step realization in learner-generated research paper introductions. We created a corpus of 79 introductions written by undergraduate L2 students at intermediate to high-intermediate levels. We annotated the introductions for moves and steps, measured their syntactic complexity at the global, clausal, and phrasal levels, and rated their level of move/step realization across four levels (no, low, intermediate, and high). We conducted one-way MANOVA, one-way ANOVA, Pearson correlation, and stepwise multiple linear regression analyses. We found sentences realizing Reviewing items of previous research function to be significantly longer than other steps in Move1 and to contain significantly more clausal and phrasal complexity features. Sentences performing Claiming centrality function also demonstrated significantly more phrasal complexity features as measured by complex nominals per clause. We also found a higher level of phrasal complexity in introductions with a higher level of move/step realization, which can be attributed to introductions including Step1 and Step3, rather than containing all steps. Our findings imply that there is value in developing explicit instructions on how to use complex structures in performing rhetorical steps in research paper introductions. © 2021 Elsevier Ltd

Purpose Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers. Design/methodology/approach This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords. Findings Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich. Originality/value This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

The Making Introductory Courses Real while Online (MICRO) laboratory project was developed to meet the need for hands-on experiments, focused on topics in analytical chemistry, to be delivered safely remotely or in a socially distanced in-person lab. Unlike more traditional lab experiments, MICRO laboratories use only microgram or nanogram amounts of chemicals; paper microfluidic technology is used to store and mix reactants. Instructional materials use an inquiry-based approach and are situated in a context that highlights the human impacts of the scientific analysis. To support broader-scale implementation of the experiments and promote a shift to more inquiry-based laboratory instruction, an array of supports were developed, including adaptable instructional materials, instructional videos for lab preparation, resource guides, and an introductory workshop. A cohort of nine institutions implemented MICRO laboratories both remotely and in person during Fall 2020. Students were able to successfully complete the experiments, and the inquiry nature of the laboratories led to an increased comfort with the trial-and-error nature of authentic scientific practice. Additionally, most faculty participants indicated a commitment to an increased degree of inquiry in their laboratory pedagogy.

With the arrival of the Internet and social media, at the same time as masses of humans have benefitted from the full-size reassets of records available, there was an full-size boom with inside the upward push of cyber-crimes, mainly targeted closer to women. According to a 2019 file with inside the Economics Times, India has witnessed a 457% upward push in cybercrime with inside the 5 years span among 2011 and 2016. Most speculate that that is because of effect of social media inclusive of Facebook, Instagram and Twitter on our day by day lives. While those simply assist in growing a legitimate social network, advent of consumer debts in those websites normally desires simply an email-id. A actual lifestyles man or woman can create more than one fake IDs and for this reason impostors can effortlessly be made. Unlike the actual international state of affairs in which more than one policies and guidelines are imposed to become aware of oneself in a completely unique manner (as an instance at the same time as issuing one’s passport or driver’s license), with inside the digital international of social media, admission does now no longer require this kind of checks. In this paper, we study the one-of-a-kind debts of Instagram, specifically and try and verify an account as fake or actual the use of Machine Learning strategies specifically Logistic Regression and Random Forest Algorithm.

Smart watches have the potential to support health in everyday living by: enabling self-monitoring of personal activity; obtaining feedback based on activity measures; allowing for in-situ surveys to identify patterns of behavior; and supporting bi-directional communication with health care providers and family members. However, smart watches are an emerging technology and research with these devices is at a nascent stage. Seventy-three studies were returned in the search. Seventeen studies published were included. Included studies were published from 2014 to 2016, with the exception of one published in 2011. Most studies employed the use of consumer-grade smart watches (14/17, 82%). Patient-related studies focused on activity monitoring, heart rate monitoring, speech therapy adherence, diabetes self-management, and detection of seizures, tremors, scratching, eating, and medication-taking behaviors. Most patient-related studies enrolled participants with few exclusion criteria to validate smart watch function (10/17, 58%). Smart watch technical function, acceptability, and effectiveness in supporting health must be validated in larger field studies that enroll actual participants living with the conditions these devices target.

Heart disease has been one of the ruling causes for death for quite some time now. About 31% of all deaths every year in the world take place as a result of cardiovascular diseases [1]. A majority of the patients remain uninformed of their symptoms until quite late while others find it difficult to minimise the effects of risk factors that cause heart diseases. Machine Learning Algorithms have been quite efficacious in producing results with a high level of correctness thereby preventing the onset of heart diseases in many patients and reducing the impact in the ones that are already affected by such diseases. It has helped medical researchers and doctors all over the world in recognising patterns in the patients resulting in early detections of heart diseases.

With the advancement of mobile technology, mobile-assisted language learning (MALL) has significant potential regarding its practical applications and benefits in foreign language learning. Neverth...

In March 2021, the UK Government presented its “Integrated Review of Security, Defence, Development and Foreign Policy.” The launch of this 111-page document had been eagerly awaited by the securit...

The development of microfluidic devices for point-of-care (POC) testing has been widely applied for food quality control, environmental monitoring, and clinical diagnoses. Regarding the latter, microfluidic paper-based analytical devices (µPADs) have a great potential in developing portable and disposable platforms for fast disease-relevant biomarker detection in remote areas. In this work, k-nearest neighbors (k-NN) classifiers were applied to demonstrate the reliability of using chemical data obtained from µPADs for diagnosis of diseases like diabetes mellitus and hyperuricemia. Predictors based on glucose, lactate, and uric acid biomarkers were evaluated to reach this goal. Healthy adults were differentiated from the diagnosed patients with a perfect success rate. Metabolic disorders were suitably predicted with 95.0% overall accuracy. This model also showed sensitivities and specificities in the ranges 75–100% and 93–100%, respectively, indicating that the classification protocol is robust. The k-NN modeling proved the potential of the µPADs to be applied in telemedicine for reliable off-site diagnoses.

In the general framework of knowledge discovery, different techniques were used for information extraction from multi-label documents. As the world is currently facing COVID-19, it has made it more important than ever to have such knowledge extraction from previous documents. Therefore, Natural Language Processing (NLP) can be an essential model for tackling such an issue. By taking into consideration that having such a model plays an essential role to generate new insights in support of the ongoing fight against this infectious disease. This work introduces a sophisticated model that is able to read data from various articles about COVID-19, and finally give the most appropriate answer to the questions asked in order to gain insight information automatically. The model is applied to COVID-19 open research dataset challenge (CORD-19) that's has caught the attention of many researchers and it contains over 400,000 scholarly articles. The result of the proposed model has shown a good achievement, as it is explained in the result section. It was found that NLP is a good choice for tackling this global pandemic for information extraction and it contribute a new insight in support of the ongoing fight against this infectious disease. ©2021 Seventh Sense Research Group.

This work is centered on the paper making process in an industrial paper mill. There exist plenty of sub-processes in a paper mill for transformation of raw material to finished product. A particular process that is taken up in this research is paper basis weight control process, which is very important for good quality paper production. But the controller design for this process is very challenging due to the involvement of severe dead time value, which in addition to delaying the control output, makes the control system unstable. So, two different approaches are used here, in MATLAB, for controller design, one is the dead time approximation using Pade approximation technique and the other is dead time compensation using Smith predictor technique. Hence, the performance of the designed control systems is compared.

Contains fulltext : 237435.pdf (Publisher’s version ) (Open Access) Objective: We evaluated reporting completeness and transparency in randomised controlled trials (RCTs) conducted using administrative data based on 2021 CONSORT Extension for Trials Conducted Using Cohorts and Routinely Collected Data (CONSORT-ROUTINE) criteria. Study Design and Setting: MEDLINE and the Cochrane Methodology Register were searched (2011 and 2018). Eligible RCTs used administrative databases for identifying eligible participants or collecting outcomes. We evaluated reporting based on CONSORT-ROUTINE, which modified eight items from CONSORT 2010 and added five new items. Results: Of 33 included trials (76% used administrative databases for outcomes, 3% for identifying participants, 21% both), most were conducted in the United States (55%), Canada (18%), or the United Kingdom (12%). Of eight items modified in the extension; six were adequately reported in a majority (>50%) of trials. For the CONSORT-ROUTINE modification portion of those items, three items were reported adequately in >50% of trials, two in

Due to data loss rate during communication may be high and vary from time to time. Now a days, there is the possibility to hack and change your data while you are sending from one place to another. To solve this Problem , Many Approaches are proposed to provide security to Original Message. In this paper, We Provide a survey of different Approaches used for Secure Data transmission Like VSS Scheme, Visual Cryptography, Watermarking, Stenography, etc.

This companion paper is to support the replication of paper "Campus3D: A Photogrammetry Point Cloud Benchmark for Outdoor Scene Hierarchical Understanding", which was presented at ACM Multimedia 2020. The supported paper's main purpose was to provide a photogrammetry point cloud-based dataset with hierarchical multilabels to facilitate the area of 3D deep learning. Based on this provided dataset and source code, in this work, we build a complete package to reimplement the proposed methods and experiments (i.e., the hierarchical learning framework and the benchmarks of the hierarchical semantic segmentation task). Specifically, this paper contains the technical details of the package, including file structure, dataset preparation, installation package, and the conduction of the experiment. We also present the replicated experiment results and indicate our contributions to the original implementation.

In this companion paper, we provide the details of the reproducibility artifacts of the paper "Visual Relation of Interest Detection" presented at MM'20. Visual Relation of Interest Detection (VROID) aims to detect visual relations that are important for conveying the main content of an image. In this paper, we explain the file structure of the source code and publish the details of our ViROI dataset, which can be used to retrain the model with custom parameters. We also detail the scripts for component analysis and comparison with other methods and list the parameters that can be modified for custom training and inference.

In this paper we reproduce experimental results presented in our earlier work titled "Describing Subjective Experiment Consistency by $p$-Value P-P Plot" that was presented in the course of the 28th ACM International Conference on Multimedia. The paper aims at verifying the soundness of our prior results and helping others understand our software framework. We present artifacts that help reproduce tables, figures and all the data derived from raw subjective responses that were included in our earlier work. Using the artifacts we show that our results are reproducible. We invite everyone to use our software framework for subjective responses analyses going beyond reproducibility efforts., Comment: Please refer to the original publication: https://dl.acm.org/doi/10.1145/3474085.3477935 Related paper: https://dl.acm.org/doi/abs/10.1145/3394171.3413749 or arXiv:2009.13372

Peran teknologi informasi bagi perusahaan mempunyai peranan penting dan dapat menjadi pusat strategi bisnis untuk memperoleh keunggulan bersaing. Saat ini teknologi informasi sudah menjadi kebutuhan dasar bagi setiap perusahaan. Perusahaan yang ingin dikenal secara luas maupun perusahaan yang ingin menjaga hubungan dengan pelanggannya perlu membuat situs/website yang berisi informasi profil perusahaan maupun jasa/produk yang diberikan. Setiap website pasti memiliki sebuah user interface yang berbeda-beda. Klinik Sehat sama seperti klinik pada umumnya yang memberikan pelayanan yang efektif dan efisien. Untuk meningkatkan pelayanan klinik, pihak klinik ingin membuat website yang dapat digunakan pengguna untuk mudah melihat aktifitas yang sedang berlangsung di klinik. Dengan membuat website klinik, tampilan antarmuka (interface) berperan penting dalam pembuatan website. Interface merupakan hal yang di lihat pertama kali pada saat pengguna membuka website Klinik Sehat. Interface menjadi patokan. Untuk membuat interface yang bersifat user friendly pihak kinik membuat interface dengan metode paper prototype. Paper prototype dapat membantu membuat interface pada awal pengembangannya. Hasil yang di dapat pada paper ini adalah metode paper prototype cocok digunakan untuk membuat tampilan user interface pada website seperti Klinik Sehat, tampilan user interface yang user friendly bagi para pengguna website, Pengguna dapat melakukan ujicoba antarmuka dengan aksi-aksi yang nyata dan juga dapat menentukan sendiri aksi atau tugas apa saja yang bisa dipahami dan dilakukan ketika menggunakan aplikasi/website tersebut secara intuitif.