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Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline the key aspects of designing, implementing and evaluating these agents. The data sources were empirical studies, including peer‐reviewed conference papers and journal articles, and the most recent publications, from the ACM Digital Library, IEEE Xplore, ProQuest, ScienceDirect, Scopus, SpringerLink, Taylor & Francis Online, Web of Science and Wiley Online Library. The remaining papers underwent a rigorous quality assessment. A filter study meeting the objective was based on keywords. Comparative analysis and synthesis of results were used to handle data and combine study outcomes. Out of 1162 search results, 13 studies were selected. The results indicate that agents promote dialogic learning, proficiency in knowledge domains, personalized feedback and empathic abilities as essential design principles. Most implementations employ a quantitative approach, and two variables are used for evaluation. Feedback types play a vital role in achieving positive results in learning performance and student perceptions. The main limitations and gaps are the time range for literature selection, the level of integration of the empathic field and the lack of a detailed development stage report. Moreover, future directions are the ethical implications of agents operating beyond scheduled learning times and the adoption of Responsible AI principles. In conclusion, this review provides a comprehensive framework of empathic PCAs, mostly in their evaluation. The systematic review registration number is osf.io/3xk6a.Practitioner notesWhat is already known about this topicEmotions play a pivotal role in shaping the interaction process, making it essential to consider them when designing methodological strategies or learning tools.Empathic Pedagogical Conversational Agents (PCAs) have emerged as a crucial approach for enhancing and personalizing the learning experience (24/7) for pupils and supporting human teachers in their teaching process.Despite the creation of numerous empathic PCAs, there is a scarcity of Systematic Literature Reviews (SLRs) on their application in the educational field, particularly concerning the integration of emotional abilities in combination with the competencies of each subject.What this paper addsIt offers new insights into the design principles underlying the integration of the empathic field.It reviews different approaches for incorporating students' prior knowledge in real time.It provides a comprehensive and up‐to‐date overview of the research designs used for implementation, including quantitative, qualitative and mixed methods.It examines the factors that influence the effectiveness of empathic PCA in teaching and learning.It evaluates the types of feedback that enhance the impact of the empathic field on learning outcomes.Implications for practice and/or policyIt is crucial to grasp the topics that this paper introduces in order to effectively integrate new learning tools into any context.Techno‐pedagogical designers seeking to gain insights into empathic PCAs will find immense value in this SLR, as it comprehensively covers each stage of the process.For future research endeavours, this study offers a wealth of ideas to draw upon, enabling researchers to address the challenges outlined and explore new avenues of investigation. [ABSTRACT FROM AUTHOR]

Background: Commercial electroencephalography (EEG) devices have become increasingly available over the last decade. These devices have been used in a wide variety of fields ranging from engineering to cognitive neuroscience. Purpose: The aim of this study was to chart peer-review articles that used consumer-grade EEG devices to collect neural data. We provide an overview of the research conducted with these relatively more affordable and user-friendly devices. We also inform future research by exploring the current and potential scope of consumer-grade EEG. Methods: We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following online databases: PsycINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, experimental research, validation, signal processing, and clinical) and location of use as indexed by the first author's country. Results: We identified 916 studies that used data recorded with consumer-grade EEG: 531 were reported in journal articles and 385 in conference papers. Emotiv devices were used most, followed by the NeuroSky MindWave, OpenBCI, interaXon Muse, and MyndPlay Mindband. The most common usage was for brain-computer interfaces, followed by experimental research, signal processing, validation, and clinical purposes. Conclusions: Consumer-grade EEG is a useful tool for neuroscientific research and will likely continue to be used well into the future. Our study provides a comprehensive review of their application, as well as future directions for researchers who plan to use these devices. [ABSTRACT FROM AUTHOR]

Computer-vision-based gaze estimation refers to techniques that estimate gaze direction directly from video recordings of the eyes or face without the need for an eye tracker. Although many such methods exist, their validation is often found in the technical literature (e.g., computer science conference papers). We aimed to (1) identify which computer-vision-based gaze estimation methods are usable by the average researcher in fields such as psychology or education, and (2) evaluate these methods. We searched for methods that do not require calibration and have clear documentation. Two toolkits, OpenFace and OpenGaze, were found to fulfill these criteria. First, we present an experiment where adult participants fixated on nine stimulus points on a computer screen. We filmed their face with a camera and processed the recorded videos with OpenFace and OpenGaze. We conclude that OpenGaze is accurate and precise enough to be used in screen-based experiments with stimuli separated by at least 11 degrees of gaze angle. OpenFace was not sufficiently accurate for such situations but can potentially be used in sparser environments. We then examined whether OpenFace could be used with horizontally separated stimuli in a sparse environment with infant participants. We compared dwell measures based on OpenFace estimates to the same measures based on manual coding. We conclude that OpenFace gaze estimates may potentially be used with measures such as relative total dwell time to sparse, horizontally separated areas of interest, but should not be used to draw conclusions about measures such as dwell duration. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine customer satisfaction-related studies conducted between 2019 and 2021, focusing solely on articles, conference papers, and book chapters within the national literature context. The aim is to conduct a meta-analysis and analyze the existing dependent/independent variables related to customer satisfaction in terms of effect size, in order to establish a common consensus. After the screening process, 34 studies were included, and after determining the dependent/independent variables from these studies, a total of 7 different variables and 70 data points (k=70) were obtained, with a sample size (N) of 26,442. The collected data was subjected to meta-analysis using the Jamovi 1.6.23 program. Based on the findings, the variable with the highest effect size was customer loyalty with a value of 0.87, while empathy had the lowest effect size with a value of 0.55. The results indicate that the three variables with the largest effect sizes are customer loyalty, trust, and reliability, respectively. Based on this information, when customers trust and perceive a business as reliable, they engage in consuming its products/services, resulting in loyalty towards the business. [ABSTRACT FROM AUTHOR]

Background: Practice-based research networks (PBRNs) have been recognized as essential laboratories and mechanisms for developing primary care research. This scoping review aims to examine and map the features and development trends of productivity, research categories, and methods in original primary care research conducted by global PBRNs between 1991 and 2023. Methods: We have assembled an interdisciplinary team that will undertake this scoping review, following the framework developed by Arksey and O'Malley. Targeted literature includes original primary care research conducted by PBRNs, published from January 1, 1991, to December 31, 2023. An integrated search strategy will gather publications from 3 electronic databases (PubMed, Web of Science, and Embase), 16 major primary health care journals, and 364 relevant organizations. Two experienced researchers will independently screen the titles, keywords, and abstracts of all references and extract data regarding eight key elements. Disagreements between the reviewers will be resolved through group discussions, moderated by a third reviewer. Articles to be included will (1) be conducted in the primary care context, (2) be led by PBRNs, (3) provide a full report of original research, and (4) be published in a peer-reviewed journal between the aforementioned dates in any language. Exclusions encompass reviews, letters, commentaries, case reports, and conference papers. Final data will be displayed using tables and charts according to different conceptual categories. Discussion: This scoping review is one of the initial attempts to delineate the development trends and features of primary care research conducted by PBRNs. This study will provide reference information for researchers in countries/regions that are building their research infrastructure and capacity in general practice, family medicine, and primary care. Systematic review registration: Registered in OSF on July 25, 2022 (https://osf.io/zgv9c). [ABSTRACT FROM AUTHOR]

This paper focuses on the Southern African Association for Research in Mathematics, Science and Technology Education's (SAARMSTE's) role as a platform supporting research dissemination and connecting researchers in early grades mathematics (EGM) in the Southern African region. A review of the Long Papers in SAARMSTE over the last 20 years supports the finding of the other review papers in this Special Issue: that there has been substantial growth of attention to EGM since 2013. However, two distinctions are marked when looking at conference papers rather than journal papers. Firstly, there is a particularly large expansion of work in the last 5 years, with a broadening base of participation in this work. Second, looking across all the formats of conference presentations indicates SAARMSTE's role in supporting and building EGM as a key focus of research attention, and bringing together regional and international groups with interests in this area. Given that conference proceedings usually offer a broader picture of emerging interests than journal papers, we reflect on the range of foci of attention within EGM in the SAARMSTE Proceedings, and trends within this. These trends also help us to point to areas that are likely to be of key interest in the next decade. [ABSTRACT FROM AUTHOR]

Based on a keynote speech at the PCE 2022 conference, this paper responds to the conference theme "How can I be of help?" from the perspective of person-centered therapy. I focus on the kind of help (i.e. the kind of change, or outcome) that clients can expect when participating in person-centered therapy through the lens of "congruent functioning", a contemporary reframing of Rogers' concept of the fully functioning person. This model of congruent functioning was developed from an ongoing research program originally focused on the study of a brief self-report instrument, the Strathclyde Inventory (SI). In this paper, I report findings from this program, including a theoretically coherent hierarchical relationship between SI items identified from the pattern of clients' scoring that may indicate a hypothetical pathway for the development of congruent functioning. I present three different types of supporting evidence for the congruent functioning model, highlighting potential cultural differences, and a case example that considers apparent deterioration in congruent functioning by the end of therapy. Finally, I argue that the model of congruent functioning resonates not only with Rogers' theory concerning the change process underpinning person-centered therapy, but also supports the ongoing commitment to personal development required of person-centered therapists. [ABSTRACT FROM AUTHOR]

To stimulate the development and application of formal methods in industry, we need to promote research and development for the improvement of formal methods and tools for industrial applications, and we need to exchange experiences of the industrial usage of these methods and tools. This special issue of Software Tools for Technology Transfer presents various tools and experience reports that are targeting the use of formal methods in industry. The papers in this special issue are extended versions of selected conference papers from the proceedings of the 27th International Conference on Formal Methods for Industrial Critical Systems (FMICS 2022). [ABSTRACT FROM AUTHOR]

In the age of increasing process automation and data-driven decision-making, ensuring the reliability, transparency and usability of data is of paramount importance. In this context, the concept of "data observability" has aroused the interest of practitioners and there is also a lot of grey content on it. On the other hand, there is a lack of academic effort to define and build on the concept. This conference paper will therefore examine the importance of "data observability" in modern data ecosystems. The focus is on the definition and characterisation of the concept, the differentiation from other concepts (e.g. data quality, data monitoring, data discovery, data operations) and why this concept appears to be so important in an increasingly data-driven world. In addition, the concept of "data observability" is categorised in the dynamically developing research field of data governance. For this purpose, a multivocal literature review (MLR) was conducted, a form of systematic literature review (SLR) which, in addition to the published (formal) literature (e.g. journal and conference papers), also includes and brings together the grey literature (e.g. blog posts, videos and white papers). The results show that the concept of "data observability" has the potential to revolutionise the way companies manage, analyse and derive insights from their data, ultimately leading to more informed and confident decision-making. Nevertheless, there is still plenty of room for further research into the specific contribution to better data and therefore better business processes and decisions. [ABSTRACT FROM AUTHOR]

Introduction/purpose: Anomaly detection-based Network Intrusion Detection Systems (NIDSs) have emerged as a valuable tool, particularly in military fields, for protecting networks against cyberattacks, specifically focusing on Netflow data, to identify normal and abnormal patterns. This study investigates the effectiveness of anomaly-based machine learning (ML) and deep learning (DL) models in NIDSs using the publicly available NF-UQ-NIDS dataset, which utilizes Netflow data, with the aim of enhancing network protection. Methods: The authors Sarhan, M., Layeghy, S., Moustafa, N. and Portmann, M. in the conference paper Big Data Technologies and Applications, in 2021, involve a preprocessing step where 8 features are selected for the training phase out of the 12 available features. Notably, the IP source and destination addresses, as well as their associated ports, are specifically excluded. The novelty of this paper lies in the preprocessing of the excluded features and their inclusion in the training phase, employing various classification ML and DL algorithms such as ExtraTrees, ANN, simple CNN, and VGG16 for binary classification. Results: The performance of the classification models is evaluated using metrics such as accuracy, recall, etc., which provide a comprehensive analysis of the obtained results. The results show that the ExtraTrees ML model outperforms all other models when using our preprocessing features, achieving a classification accuracy of 99.09%, compared to 97.25% in the reference dataset. Conclusion: The study demonstrates the effectiveness of anomalybased ML and DL models in NIDSs using Netflow data. [ABSTRACT FROM AUTHOR]

Aim: We aim to assess the overall survival (OS) in patients with Anaplastic Astrocytoma (AA) undergoing gross total resection (GTR) as compared to partial resection (PR) subtotal resection (STR), or biopsy. Methods: This systematic review followed Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. An electronic search from PubMed/Medline was conducted from their inception to 26th April 2022. We included AA patients undergoing any surgical intervention resulting in GTR, PR, STR or biopsy. We did not include letters, case reports, abstracts, conference papers, reviews, and studies where full text was unavailable. We included only those articles which were published in English. Results: Five cohorts were used in this study. Two studies assessed OS in GTR, PR/STR and biopsy, while one study compared GTR and STR/biopsy. Another study was used to compare OS between GTR and local excision/STR, and another was used to assess the complications/benefits of these surgeries. Three studies showed a significant increase in OS in patients who underwent GTR compared to the other interventions, while one study showed a non-significant effect on OS (p= 0.249). Conclusion: Our study concluded a significant increase in OS when patients with AA had GTR instead of STR, PR or biopsy. Although these surgeries might carry some disadvantages, GTR allows a more positive effect on neurological status. Still, more studies need to be conducted to assess the efficiency of these surgeries. [ABSTRACT FROM AUTHOR]

The International Conference on the History of Records and Archives (ICHORA) has been held since 2003, with the most recent conference, ICHORA10, taking place online in July 2022. The conference aimed to reflect on the centenary of two significant events in recordkeeping history in the UK and Ireland. The conference featured various forms of participation, including short postcards from the past and longer academic presentations. The papers presented at the conference explored the nature of archives and records, highlighting the diversity of perspectives and the importance of historical context. The special issue of the journal includes articles on topics such as recordkeeping pioneers in Malta, recordkeepers in Latin America, and the history of archives in different countries. The conference also raised questions about the unique methods and perspectives involved in studying the history of archives and records. [Extracted from the article]

Purpose: The main objective of this paper is to illustrate an analytical view of different methods of 3D bioprinting, variations, formulations and characteristics of biomaterials. This review also aims to discover all the areas of applications and scopes of further improvement of 3D bioprinters in this era of the Fourth Industrial Revolution. Design/methodology/approach: This paper reviewed a number of papers that carried evaluations of different 3D bioprinting methods with different biomaterials, using different pumps to print 3D scaffolds, living cells, tissue and organs. All the papers and articles are collected from different journals and conference papers from 2014 to 2022. Findings: This paper briefly explains how the concept of a 3D bioprinter was developed from a 3D printer and how it affects the biomedical field and helps to recover the lack of organ donors. It also gives a clear explanation of three basic processes and different strategies of these processes and the criteria of biomaterial selection. This paper gives insights into how 3D bioprinters can be assisted with machine learning to increase their scope of application. Research limitations/implications: The chosen research approach may limit the generalizability of the research findings. As a result, researchers are encouraged to test the proposed hypotheses further. Practical implications: This paper includes implications for developing 3D bioprinters, developing biomaterials and increasing the printability of 3D bioprinters. Originality/value: This paper addresses an identified need by investigating how to enable 3D bioprinting performance. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the risk of miscarriage in IVF cycles in women with PCOS. Methods: Systematic review and meta-analysis. Systematic search of MEDLINE, EMBASE and Google Scholar. The language search was restricted to English, Spanish and French, from 2000 to 2019, with crosschecking of references from relevant articles. Inclusion criteria were: (1) IVF cycles (2) a group of patients with PCOS was considered separately, (3) the miscarriage rate was reported, (4) there was a control group, (5) definition of PCOS according the Rotterdam criteria. Exclusion criteria were been excluded from the meta-analysis: (1) publication prior to the year 2000, (2) animal studies, (3) reviews, (4) abstracts or conference papers, (5) letters, (6) case reports, (7) studies comparing different IVF techniques, (8) studies comparing groups with and without metformin or other treatments, (9) studies on induced abortions. Risk of bias was assessed by the Newcastle–Ottawa score (NOS). All the included studies had a low risk of bias (NOS scores ranging 7–8). The review protocol was registered in PROSPERO (CRD42020186713). Seventeen studies were included in the meta-analysis. There was a total of 10,472 pregnancies (2650 in PCOS and 7822 in controls) of which 1885 were miscarriages (682 in PCOS and 1203 in controls). We considered the miscarriage rate (MR), preclinical MR, early MR, and late MR. Results: In IVF pregnancies the risk of miscarriage was significantly increased when considering miscarriages in total (RR = 1.59; CI = 1.45–1.75), preclinical miscarriages (RR = 1.59; CI = 1.35–1.88), and early miscarriages (RR = 1.44; CI = 1.16–1.79). The increased miscarriage rate persisted in Chinese and Western populations when considered separately. The risk of miscarriage was increased in the subgroup of fresh transfers (RR = 1.21; CI = 1.06–1.39) as well as in the subgroup including either fresh or frozen transfers (RR = 1.95; CI = 1.72–2.22). Conclusion: PCOS is linked to an increased MR in IVF pregnancies both of miscarriages in total, and to an increase in preclinical and early miscarriages. Prospero number: CRD42020186713. [ABSTRACT FROM AUTHOR]

A brief introduction to the papers presented at a conference held at Vanderbilt University in the Fall of 2023, called "John Lachs and American Philosophy," organized by the Philosophy Department and the College of Arts and Sciences. The symposium includes papers by Herman Saatkamp, John Stuhr, Eric Weber, and Chris Skowroński. It is followed by a response from John Lachs written down by Michael Hodges based on conversations. [ABSTRACT FROM AUTHOR]

When flying under visual flight rules, pilots must remain clear of clouds. The exact distance varies by airspace class, and this is determined by specific regulatory requirements found within 14 C.F.R. Section 91.155. But there are important questions about the extent to which pilots comply with this regulation, as determining one's exact distance from clouds is challenging. In this conference paper, we assess the decisions of the National Transportation Safety Board (NTSB) in 20 Federal Aviation Administration (FAA) legal enforcement actions involving a violation of cloud clearance requirements. Among these cases, we examine how 91.155 violations were discovered, the form of sanction imposed by the FAA, the timelines associated with appeals for these cases, and the vote composition of the NTSB in these decisions. [ABSTRACT FROM AUTHOR]

This paper analyses the conference papers published by double first‐class universities from mainland China between 2006 and 2019. The main findings are as follows: first, the number of conference papers from different double first‐class universities varied greatly, with the annual numbers of papers in the China Proceedings of Conferences Full‐text Database (CPCD) and in the Conference Proceedings Citation Index (CPCI) fluctuating during this period. Second, most of the top 10 disciplines of the papers in the CPCD and CPCI were in the natural sciences, with only two in the social sciences. The CPCD papers and CPCI papers had some overlap in their disciplinary distributions. Third, the CPCD and CPCI papers differed little in total number, with the number of CPCI papers being slightly higher than the number of CPCD papers. With the introduction of new regulations from the Ministry of Science and Technology (MST), there will likely be an increase in the number of Chinese‐language conference papers in the future. [ABSTRACT FROM AUTHOR]

This study aims to explore the SCImago Institutional Ranking (SIR) 2022 to gain insight into the profile of Sri Lankan universities. Additionally, the study aims to investigate whether there was consistency between Scopus profiles and SIR. Furthermore, the research delves into various factors that impact the research ranking of an academic institution as defined by SCImago, which goes beyond just the number of publications. The data for the study were retrieved from SIR (2022) and Scopus database (2022) and were systematically analyzed. The author chose the following options to extract the data for overall ranking, Universities as a sector, Sri Lanka as the country and 2022 as the year based on all subject areas. The study found that the number of Sri Lankan universities eligible for the SCImago ranking has gradually increased from 2013 to 2022. According to SIR, the University of Colombo is the top-ranked academic institution in Sri Lanka, followed by Rajarata University of Sri Lanka and the University of Jaffna. Out of the fourteen universities in Sri Lanka, eight were ranked by SIR, with six being in the Q1 (first cluster) and two in the Q2 (second cluster). Interestingly, the Rajarata University of Sri Lanka was ranked 1st in SIR 2022 for its research performance among Sri Lankan universities with their 105 publications indexed in Scopus. Analysis of data shows that there is no relationship between the Scopus profile and the SIR. It is also suggesting that having a high number of articles in the Scopus database does not necessarily guarantee a high rank in SIR. The SIR not only depends on the number of publications but also on other factors related to the quality of the publications. Therefore, universities cannot assume their SIR position by considering only the quantity of Scopus indexed publications. SIR mainly considers the quality of the publications to measure the institutional research performance. The SCImago ranking evaluates the institutional whole performance through three of its indicators, and research performance is measured only through Scopus indexed publication. Sri Lankan publications in local and international journals which are not indexed in Scopus and conference papers were not counted for research performance. The findings of this study will facilitate the institutions to compare their position with other institutions, standardize their research practices, improve the international collaboration to uphold the academic benchmark, regulate their research publications and promote their visibility and finally support government bodies and policymakers regarding fund allocations and strategic planning. [ABSTRACT FROM AUTHOR]

Current literature dealing with the theory of sampling process flows is limited in scope, a situation addressed by papers presented at conferences by the author. This paper provides a summary of methods to quantify process sampling variance in a sound statistical manner. Two methods of calculation of the process sampling variance are presented here with models for robust estimation of the process covariance/variogram. The strategies for process sampling to acquire the data for process characterisation are described. The method for process characterisation can be based on special sampling campaigns, on the analysis of on-line measurement data, or on the analysis of historical data, which may be based on composite samples, such as shift samples. These scenarios are all dealt with as well as methods based on analysis of process dynamics. The latter analysis demonstrates that use of covariance functions drawn from geostatistical practice can be inappropriate for process analysis. The work is supported with plant data examples and quantitative analyses of process conditions. [ABSTRACT FROM AUTHOR]

The papers presented at the conference cut across five thematic areas, including Democracy and Dialogue Engagements in Africa, Historical Perspectives of Democracy and Dialogue in Africa, Biblical Hermeneutics of Dialogue in Africa, Youth Participation in Dialogue and Democracy in Africa, and Indigenous Perspectives on Dialogue and Peace in Africa. The nexus between religion and democracy has hardly been adequately explored. This conference was one of the high points of Dr. Effiong Udo's sabbatical research initiative with the Dialogue Institute (D.I.). [Extracted from the article]

Moving objects databases (MODs) have been extensively studied due to their wide variety of applications including traffic management, tourist service and mobile commerce. However, queries in natural languages are still not supported in MODs. Since most users are not familiar with structured query languages, it is essentially important to bridge the gap between natural languages and the underlying MODs system commands. Motivated by this, we design a natural language interface for moving objects, named NALMO. In general, we use semantic parsing in combination with a location knowledge base and domain-specific rules to interpret natural language queries. We design a corpus of moving objects queries for model training, which is later used to determine the query type. Extracted entities from parsing are mapped through deterministic rules to perform query composition. NALMO is able to well translate moving objects queries into structured (executable) languages. We support five kinds of queries including time interval queries, range queries, nearest neighbor queries, trajectory similarity queries and join queries. We develop the system in a prototype system SECONDO and evaluate our approach using 280 natural language queries extracted from popular conference and journal papers in the domain of moving objects. Four volunteers give the system satisfaction and related suggestions through three rounds of independent tests. Experimental results show that (i) NALMO achieves accuracy and precision 96.8% and 81.1%, respectively, (ii) the average time cost of translating a query is 1.49s, and (iii) the average satisfaction is 95.5%. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Long-acting reversible contraception (LARC) is a feasible solution to reduce unintended pregnancy and abortion rates. Nonetheless, the worldwide prevalence of LARC remains low. The LARC uptake depends heavily on healthcare workers because every LARC insertion requires a clinician's visit, and they are a trusted source of contraceptive information. The study is aimed to explore the trend and distributions of global publications related to LARC and healthcare workers. MATERIALS AND METHODS: Articles related to LARC and healthcare workers were retrieved from the Scopus database. Eligible publications were limited to research articles, reviews, and conference papers published in the English language with no date restriction. The bibliometric data was analysed using Biblioshiny to obtain distributions in terms of the number of publications, journals, countries, institutions, citations, and keywords. RESULTS: A total of 681 eligible publications related to LARC and healthcare workers were retrieved from the Scopus database between 1967 to 2022. The number of publications was low for the first four decades but increased steadily from 2010 onwards. The leading country in this research area was the United States of America and the majority of the most productive institutions were from this country. Half of the frequently cited publications highlighted healthcare workers' bias, attitude, and practice on LARC provision to clients. CONCLUSION: This bibliometric analysis can guide scholars to understand the global overview of research about LARC and healthcare workers. It may be useful for health practitioners and researchers who are interested in exploring this research area. [ABSTRACT FROM AUTHOR]

Some states in the U.S. have traditionally received less federal research funding than other states. The National Science Foundation (NSF) created a program in 1979, called the Experimental Program to Stimulate Competitive Research (EPSCoR) to enhance the research competitiveness in such states. While the geographic disparity in federal research funding is well known, the overall impact of federal funding on the research performance of EPSCoR and non-EPSCoR has not been previously studied. In the current study, we compared the combined research productivity of Ph.D. granting institutions in EPSCoR versus the non-EPSCoR states to better understand the scientific impact of federal investments in sponsored research across all states. The research outputs we measured included journal articles, books, conference papers, patents, and citation count in academic literature. Unsurprisingly, results indicated that the non-EPSCoR states received significantly more federal research funding than their EPSCoR counterparts, which correlated with a higher number of faculty members in the non-EPSCoR versus EPSCoR states. Also, in the overall research productivity expressed on a per capita, the non-EPSCoR states fared better than EPSCoR states. However, when the research output was measured based on per $1M investment of federal research funding, EPSCoR states performed significantly better than the non-EPSCoR states in many research productivity indicators, with the notable exception of patents. Together, this study found preliminary evidence that EPSCoR states achieved a high degree of research productivity despite receiving significantly fewer federal research dollars. The limitations and next steps of this study are also discussed. [ABSTRACT FROM AUTHOR]

Automatic Term Extraction (ATE) systems have been studied for many decades as, among other things, one of the most important tools for tasks such as information retrieval, sentiment analysis, named entity recognition, and others. The interest in this topic has even increased in recent years given the support and improvement of the new neural approaches. In this article, we present a follow-up on the discussions about the pipeline that allows extracting key terms from medical reports, presented at MDTT 2022, and analyze the very last papers about ATE in a systematic review fashion. We analyzed the journal and conference papers published in 2022 (and partially in 2023) about ATE and cluster them into subtopics according to the focus of the papers for a better presentation. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the differences between conference papers and journal papers in the field of computer science based on Bayesian network. This paper investigated the differences between conference papers and journal papers in the field of computer science based on Bayesian network, a knowledge-representative framework that can model relationships among all variables in the network. We defined the variables required for Bayesian networks modeling, calculated the values of each variable based Aminer dataset (a literature data set in the field of computer science), learned the Bayesian network and derived some findings based on network inference. The study found that conferences are more attractive to senior scholars, the academic impact of conference papers is slightly higher than journal papers, and it is uncertain whether conference papers are more innovative than journal papers. The study was limited to the field of computer science and employed Aminer dataset as the sample. Further studies involving more diverse datasets and different fields could provide a more complete picture of the matter. By demonstrating that Bayesian networks can effectively analyze issues in Scientometrics, the study offers valuable insights that may enhance researchers' understanding of the differences between journal and conference in computer science. Academic conferences play a crucial role in facilitating scholarly exchange and knowledge dissemination within the field of computer science. Several studies have been conducted to examine the distinctions between conference papers and journal papers in terms of various factors, such as authors, citations, h-index and others. Those studies were carried out from different (independent) perspectives, lacking a systematic examination of the connections and interactions between multiple perspectives. This paper supplements this deficiency based on Bayesian network modeling. [ABSTRACT FROM AUTHOR]

Diabetes Mellitus (DM) causes global exhaustion, consumes economic resources, and has several risk factors. The bibliometric studies re-evaluate the research efforts on this illness using mathematical and statistical tools to indicate current research and future trends. This study examines KSA's DM research during 2010-2021. Data were acquired from Scopus and analyzed using VOSviewer and MS Excel. Several characteristics were examined to measure the quantity and quality of KSA-related DM articles. In total, 1,919 journal and conference papers were published. DM research included researchers from multidisciplinary sectors. Thirty-seven percent of them have ten or more scientific publications. Al-Daghri, N.M. (King Saud University) leads the pack. In total, 757 (39.44%) research projects got funding from 159 sources within and outside KSA. Memish, Z.A. is the most cited author. The Saudi Medical Journal has the most citations (1214). Al-Daghri, N.M. (KSU) collaborates the most. One hundred forty-one nations aided KSA's diabetes research. Egypt's High Institute of Public Health has the most scientific collaboration with KSA. Authors' and all Keywords analyses indicated a rich knowledge structure. Diabetes Care Journal has the most cocitations with 2,220 and a total link strength of 19,283, followed by The New England Journal of Medicine. The study results will be helpful to stakeholders to understand better the trends and performance of diabetes-related regional research, which will be beneficial. [ABSTRACT FROM AUTHOR]

We consider a stateless 'amnesiac' variant of the stateful distributed network flooding algorithm, expanding on our conference papers [PODC'19, STACS'20]. Flooding begins with a set of source 'initial' nodes I seeking to broadcast a message M in rounds, in a network represented by an undirected graph (G, E) with set of nodes G and edges E. In every round, nodes with M send M to all neighbours from which they did not receive M in the previous round. Nodes do not remember earlier rounds, raising the possibility that M circulates indefinitely. Stateful flooding overcomes this by nodes recording every message circulated and ignoring M if received again. This overhead was assumed to be necessary. We show that almost optimal broadcast can still be achieved without this overhead. We prove that amnesiac flooding terminates on every finite graph and derive sharp bounds for termination times. Define (G, E) to be I-bipartite if the quotient graph, contracting all nodes in I to a single node, is bipartite. We prove that, if d is the diameter and e(I) the eccentricity of the set I, flooding terminates in e(I) rounds if (G, E) is I-bipartite and j rounds with e(I) < j ≤ e (I) + d + 1 ≤ 2 d + 1 if (G, E) is non I-bipartite. The separation in the termination times can be used for distributed discovery of topologies/distances in graphs. Termination is guaranteed if edges are lost during flooding but not, in general, if there is a delay at an edge. However, the cases of single-edge fixed delays of duration τ rounds in single-source bipartite graphs terminate by round 2 d + τ - 1 , and all cases of multiple-edge fixed delays in multiple-source cycles terminate. [ABSTRACT FROM AUTHOR]

Aims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. Method: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. Results: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. Conclusion: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs. [ABSTRACT FROM AUTHOR]

The importance of grey literature as a means of primary, nonconventional communication is accepted in almost every scientific field. Although grey literature covers a wide spectrum of nonconventional documents, both producers and users of grey literature have always considered it to be a primary source of information. The National Library and Archives of Iran (NLAI) was founded in 1937. The main goal of this organization is collecting, preserving, organizing and disseminating information about printed and non-printed works in Iran, and taking measures and making decisions to guarantee the accuracy, ease and speed of research and study in all fields to promote national culture. In order to achieve these goals, and according to the law, all private and public publishers have to deposit a copy of their publications (book and non -book materials) to the NLAI. There are more than 1.790.000 issues in the grey literature in the NLAI, and over 170.000 of them belong to the Medicine group. In this study, the amount of grey resources in the field of medicine, nursing, dentistry, veterinary, paramedical and pharmacology in the NLAI is surveyed. How many grey literatures are there in each medical subject's groups? How many of them have been digitized? How many articles are in the field of medicine group? How many of them are conference papers? [ABSTRACT FROM AUTHOR]

In this paper, a systematic literature review is presented, through a survey of the main digital databases, regarding modelling methods for Short-Term Load Forecasting (STLF) for hourly electricity demand for residential electricity and to realize the performance evolution and impact of Artificial Intelligence (AI) in STLF. With these specific objectives, a conceptual framework on the subject was developed, along with a systematic review of the literature based on scientific publications with high impact and a bibliometric study directed towards the scientific production of AI and STLF. The review of research articles over a 10-year period, which took place between 2012 and 2022, used the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) method. This research resulted in more than 300 articles, available in four databases: Web of Science, IEEE Xplore, Scopus, and Science Direct. The research was organized around three central themes, which were defined through the following keywords: STLF, Electricity, and Residential, along with their corresponding synonyms. In total, 334 research articles were analyzed, and the year of publication, journal, author, geography by continent and country, and the area of application were identified. Of the 335 documents found in the initial research and after applying the inclusion/exclusion criteria, which allowed delimiting the subject addressed in the topics of interest for analysis, 38 (thirty-eight) documents were in English (26 journal articles and 12 conference papers). The results point to a diversity of modelling techniques and associated algorithms. The corresponding performance was measured with different metrics and, therefore, cannot be compared directly. Hence, it is desirable to have a unified dataset, together with a set of benchmarks with well-defined metrics for a clear comparison of all the modelling techniques and the corresponding algorithms. [ABSTRACT FROM AUTHOR]

The basic goal of survivable network design is to build a cheap network that maintains the connectivity between given sets of nodes despite the failure of a few edges/nodes. The connectivity augmentation problem (CAP) is arguably one of the most basic problems in this area: given a k(-edge)-connected graph G and a set of extra edges (links), select a minimum cardinality subset A of links such that adding A to G increases its edge connectivity to k+1. Intuitively, one wants to make an existing network more reliable by augmenting it with extra edges. The best known approximation factor for this NP-hard problem is 2, and this can be achieved with multiple approaches (the first such result is in [G. N. Frederickson and J\'aj\'a, SIAM J. Comput., 10 (1981), pp. 270--283]. It is known [E. A. Dinitz, A. V. Karzanov, and M. V. Lomonosov, Studies in Discrete Optimization, Nauka, Moscow, 1976, pp. 290--306] that CAP can be reduced to the case k = 1, also known as the tree augmentation problem (TAP) for odd k, and to the case k = 2, also known as the cactus augmentation problem (CacAP) for even k. Prior to the conference version of this paper [J. Byrka, F. Grandoni, and A. Jabal Ameli, STOC'20, ACM, New York, 2020, pp. 815--825], several better than 2 approximation algorithms were known for TAP, culminating with a recent 1.458 approximation [F. Grandoni, C. Kalaitzis, and R. Zenklusen, STOC'18, ACM, New York, 1918, pp. 632--645]. However, for CacAP the best known approximation was 2. In this paper we breach the 2 approximation barrier for CacAP, hence, for CAP, by presenting a polynomial-time 2 ln(4) 967 1120 + \varepsilon < 1.91 approximation. From a technical point of view, our approach deviates quite substantially from previous work. In particular, the better-than-2 approximation algorithms for TAP either exploit greedy-style algorithms or are based on rounding carefully designed LPs. We instead use a reduction to the Steiner tree problem which was previously used in parameterized algorithms [Basavaraju et al., ICALP'14, Springer, Berlin, 2014, pp. 800--811]. This reduction is not approximation preserving, and using the current best approximation factor for a Steiner tree [Byrka et al., J. ACM, 60 (2013), 6] as a black box would not be good enough to improve on 2. To achieve the latter goal, we "open the box" and exploit the specific properties of the instances of a Steiner tree arising from CacAP. In our opinion this connection between approximation algorithms for survivable network design and Steiner-type problems is interesting, and might lead to other results in the area. [ABSTRACT FROM AUTHOR]

Preserving customers' expectations and understanding factors affecting their purchasing decisions are crucial in designing effective marketing and advertising strategies. However, constantly and swiftly changing the customers' interests and consumption behaviors make it inevitable to utilize sophisticated tools and approaches based on advanced technologies. Among them, by measuring the customers' physiological and neural signals, studying the customers' cognitive and affective responses to marketing stimuli, neuromarketing provides deep insight into the customers' motivations, preferences, and decisions. Recently, the internet of everything (IoE) has brought many new opportunities to the industry and has attracted the attention of many researchers in recent years. The main objective of this paper is to address how the IoE would empower neuromarketing techniques. Hence, an in-depth understanding of current research issues as well as emerging trends would help meet this goal. In this paper, a comprehensive review has been done by reviewing numerous journal and conference papers from various academic databases (sciencedirect.com, IEEE Xplore, Springer, Elsevier, Wiley, ACM digital library) based on applying various filtrations on specific keywords to identify and categorize the IoE devices in the neuromarketing field. In particular, we discussed the importance and the applications of IoE gadgets and devices, especially wearable medical technologies in eight neuromarketing techniques. Finally, we described critical existing challenges and limitations in neuromarketing and IoE gadgets that researchers have dealt with in this field of research. [ABSTRACT FROM AUTHOR]

The paper provides empirical results on the part of grey literature in the French national open repository HAL. The results are based on a quantitative analysis of 973,968 deposits from 1,272 research laboratories affiliated the ten most important research universities in France (IDEX program). 35% of all deposits (documents and records) are grey literature. The main types of these items are conference papers (71%), PhD theses (11%) and preprints and working papers (8%). Their overall accessibility (degree of openness) is 37%, which is higher than commercial publications. Differences between document types, disciplines and institution are described. Further research is needed for a better understanding of how research laboratories are handling grey literature (licensing ...). A follow-up study in 2021 will provide this insight. [ABSTRACT FROM AUTHOR]

This research focused on using RGB-D images and modifying an existing machine learning network architecture to generate predictions of the location of successfully grasped objects and to optimize the control system for state delays. A five-finger gripper designed to mimic the human palm was tested to demonstrate that it can perform more delicate missions than many two- or three-finger grippers. Experiments were conducted using the 6-DOF robot arm with the five-finger and two-finger grippers to perform at least 100 actual machine grasps, and compared to the results of other studies. Additionally, we investigated state time delays and proposed a control method for a robot manipulator. Many studies on time-delay systems have been conducted, but most focus on input and output delays. One reason for this emphasis is that input and output delays are the most commonly occurring delays in physical or electronic systems. An additional reason is that state delays increase the complexity of the overall control system. Finally, it was demonstrated that our network can perform as well as a deep network architecture with little training data and omitting steps, such as posture evaluation, and when combined with the hardware advantages of the five-finger gripper, it can produce an automated system with a gripping success rate of over 90%. This paper is an extended study of the conference paper. [ABSTRACT FROM AUTHOR]

This special issue of Analytical Letters is devoted to selected articles based on contributions from the Third International Congress of Environmental Chemistry (EnviroChem 2021). The authors have expanded their conference papers and included their latest experimental results in this special edition of Analytical Letters. EnviroChem 2021 has aimed- to promote and disseminate knowledge on various topics and technologies related to Environmental Chemistry. All articles have gone through the standard review process. The EnviroChem 2021 Conference, where chemists, environmental engineers/scientists and researchers from many countries came together, was held in Antalya Kemer, hosted by Erciyes University (ERU), Karadeniz Technical University (KTU), Muğla Sıtkı Koçman University (MSKU), and the Chemists Society (of Turkey). EnviroChem 2011 combined invited lectures, oral sessions, and poster presentations with a total of 9 invited lectures, 46 contributed oral presentations, and 41 posters. The Conference Organizers would like to thank all committee members, invited speakers, and presenters, authors and reviewers of EnviroChem 2021 who generously shared their expertise with us by presenting/reviewing their valuable contributions to this special issue. Finally, we extend our thanks to Professor David Butcher as the Editor-in-Chief of Analytical Letters and the staff of Taylor & Francis. [ABSTRACT FROM AUTHOR]

This article is a follow-up contribution that extends the conference paper (Nxumalo, in: Laarman, Sokolova (eds)Model Checking Software - 27th International Symposium, 2021) which presented the spotlight abstraction method to enable an efficient model checking of schedulability properties of real-time operating systems. Our approach is based on iterative spotlight abstraction whereby the real-time task queue is divided into a so-called spotlight and a shade. Initially, an abstract state space model is generated from the spotlight, which contains a small number of tasks that appear at the front of the queue and the shade contains the remaining tasks. The schedulability of the spotlight tasks is model checked, whereas the behavior of the shade is summarized, and the result is saved for later re-use. If this result is still inconclusive, more tasks are iteratively brought from the shade into the spotlight, with which the model checker can proceed. These steps are repeated until a decisive schedulability result is obtained. In this article, we enrich the encoding of real-time systems into timed automata by separating operations over clock variables from operations based on other variables such as Boolean and integers. We enforce to maintain a reasonable size of the spotlight model by applying counter abstraction to the tasks that were previously confirmed schedulable in the previous iterations. We compare our approach against Timestool and RTLib, an Uppaal template, in the analysis of the schedulability of real-time tasks for the First-In-First-Out and Shortest-Deadline-First scheduling policies. Empirical results show that our approach can handle more tasks than Timestool and RTLib. [ABSTRACT FROM AUTHOR]

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers communicate over a sparse graph, current theory fails to capture important aspects of real-world behavior. First, the 'spectral gap' of the communication graph is not predictive of its empirical performance in (deep) learning. Second, current theory does not explain that collaboration enables larger learning rates than training alone. In fact, it prescribes smaller learning rates, which further decrease as graphs become larger, failing to explain convergence dynamics in infinite graphs. This paper aims to paint an accurate picture of sparsely-connected distributed optimization. We quantify how the graph topology influences convergence in a quadratic toy problem and provide theoretical results for general smooth and (strongly) convex objectives. Our theory matches empirical observations in deep learning, and accurately describes the relative merits of different graph topologies. This paper is an extension of the conference paper by Vogels et al. (2022). Code: github.com/epfml/topology-in-decentralized-learning. [ABSTRACT FROM AUTHOR]

The study intends to presents a Bibliometric analysis of articles presented at the Nigerian Library Association's (NLA's) National Conferences/ AGMs, 2019-2021, it will find out the distribution of articles that were presented in NLA's conferences from 2019-2021, the degree of collaboration among the authors, and collaborative index of articles presented at NLA's National conferences from the year 2019-2021. Data were collected from the NLA's journals. To achieve the purpose of the study, three objectives guided the study. The study adopted descriptive survey design. The data were analyzed using frequency table and simple percentage. The findings of the study reveal that 29 articles were presented of which 17 of the number is multiple authors, and that of single authors is 12. The degree of collaboration of articles presented at NLA's National conferences 2019 to 2021 is 0.59, this indicates that degree of collaboration was positive; this reveals that NLA is presenting high quality articles. And the collaborative index of articles presented at NLA's conference in the year 2019 is 0.25 and in 2021 is 0.54. This indicates that the collaboration among the authors is positive. This indicates that NLA journals are publishing collaborative articles of high quality. The study recommended that measures should be taken to ensure that the invitations for papers reach every nooks and crannies of Nigeria; this can increase the number of contributors. More authors should be motivated to produce collaborative articles. More authors need orientation. [ABSTRACT FROM AUTHOR]

An institutional repository (IR) is a digital collection that archives and provides access to an institution's scholarly and creative output, such as a university, research organization, or museum. The purpose of an IR is to collect, preserve, and share the intellectual work of an institution, making it accessible to a wider audience. An IR typically includes research articles, conference papers, theses and dissertations, preprints, reports, datasets, multimedia, and other scholarly and creative works produced by faculty, staff, and students. An institutional profile in Google Scholar can function as an institutional repository. While it may not have all the features and functionalities of a traditional institutional repository, it can still provide a platform for institutions to share and showcase their research output. [ABSTRACT FROM AUTHOR]

The aim of this review was to analyze and summarize the most common adverse events (AEs) and complications after magnetic resonance-guided focused ultrasound (MRgFUS) therapy in uterine fibroids (UFs) and to establish the risk factors of their occurrence. We searched for original research studies evaluating MRgFUS therapy in UFs with outcomes containing AEs and/or complications in different databases (PubMed/MEDLINE, SCOPUS, COCHRANE) until March 2022. Reviews, editorials, opinions or letters, case studies, conference papers and abstracts were excluded from the analysis. The systematic literature search identified 446 articles, 43 of which were analyzed. According to available evidence, the overall incidence of serious complications in MRgFUS therapy is relatively low. No AEs/complications were reported in 11 out of 43 analyzed studies. The mean occurrence of all AEs in the analyzed material was 24.67%. The most commonly described AEs included pain, skin burns, urinary tract infections and sciatic neuropraxia. Major AEs, such as skin ulcerations or deep vein thrombosis, occurred in 0.41% of cases in the analyzed material. MRgFUS seems to be safe in UF therapy. The occurrence of AEs, especially major ones, is relatively low in comparison with other methods. The new devices and more experience of their users seem to reduce AE rate. The lack of unification in AE reporting and missing data are the main issues in this area. More prospective, randomized studies with unified reporting and long follow-up are needed to determine the safety in a long-term perspective. [ABSTRACT FROM AUTHOR]

The 15th Malaysian General Election (GE-15) took place on 19 November 2022 successfully. This time the general election was held a year earlier than the 5-year maturity period on 16 July 2023, which is the date of the swearing-in of members of Parliament for the 14th term. The GE-15 results show that there is a pattern of voter support based on a specific geographic location. Therefore, the purpose of writing this article is to analyze voter support patterns based on regional factors. Based on data analysis of the GE 2022 results, observations in the field and analysis of secondary sources such as journal articles and conference papers, the findings of the study show that PH continues to dominate the West Coast region of Peninsular Malaysia as well as in Sabah and Sarawak in urban and semi-urban areas with ethnic mix and Chinese majority, PN controls the East and North Coast regions as well as a small part in the West and South of Peninsular Malaysia in the rural areas of the Malay majority, namely in the East Coast Peninsular zone, namely Kelantan, Terengganu and East Pahang and Central Pahang; North of the peninsula, which is Perlis and Kedah and Penang Seberang Prai North and Central, North Perak, Central Perak; the western part of Peninsular namely North Selangor and West Selangor as well as West Melaka and South Melaka while BN remains in power in the rural areas of central Peninsular Malaysia but with a shrinking number of seats. Therefore, regional influence also affects the voting pattern and needs to be taken into account by the relevant parties to implement campaign. [ABSTRACT FROM AUTHOR]

Many problems in imaging and low-level vision can be formulated as nonconvex variational problems. A promising class of approaches to tackle such problems are convex relaxation methods, which consider a lifting of the energy functional to a higher-dimensional space. However, they come with increased memory requirements due to the lifting. The present paper is an extended version of the earlier conference paper by Ye et al. (in: DAGM German conference on pattern recognition (GCPR), 2021) which combined two recent approaches to make lifting more scalable: product-space relaxation and sublabel-accurate discretization. Furthermore, it is shown that a simple cutting-plane method can be used to solve the resulting semi-infinite optimization problem. This journal version extends the previous conference work with additional experiments, a more detailed outline of the complete algorithm and a user-friendly introduction to functional lifting methods. [ABSTRACT FROM AUTHOR]

In this paper, we present a new method for isolating real roots of a bivariate nonlinear system. It is a subdivision method based on analyzing the local geometrical properties of the given system. We propose the concept of opposite monotone system in a box and use it to determine the existence and the uniqueness of a simple real zero of the system in the box. We have implemented our method and the experiments show the effectivity and efficiency of our approach, especially for high degree sparse polynomial systems. This paper is an extended version of the ISSAC'19 conference paper (Cheng and Wen (2019)). [ABSTRACT FROM AUTHOR]

Handwritten signatures are widely used for identity authorization. However, verifying handwritten signatures is cumbersome in practice due to the dependency on extra drawing tools such as a digitizer, and because the false acceptance of a forged signature can cause damage to property. Therefore, exploring a way to balance the security and user experiment of handwritten signatures is critical. In this paper, we propose a handheld signature verification scheme called SilentSign, which leverages acoustic sensors (i.e., microphone and speaker) in mobile devices. Compared to the previous online signature verification system, it provides handy and safe paper-based signature verification services. The prime notion is to utilize the acoustic signals that are bounced back via a pen tip to depict a user's signing pattern. We designed the signal modulation stratagem carefully to guarantee high performance, developed a distance measurement algorithm based on phase shift, and trained a verification model. In comparison with the traditional signature verification scheme, SilentSign allows users to sign more conveniently as well as invisibly. To evaluate SilentSign in various settings, we conducted comprehensive experiments with 35 participants. Our results reveal that SilentSign can attain 98.2 % AUC and 1.25 % EER. We note that a shorter conference version of this paper was presented in Percom (2019). Our initial conference paper did not finish the complete experiment. This manuscript has been revised and provided additional experiments to the conference proceedings; for example, by including System Robustness, Computational Overhead, etc. [ABSTRACT FROM AUTHOR]

It is challenging to design complex structures and calculate their dimensions only on the basis of theory. This issue was resolved efficiently by the FEM. Using the applicable test, the mechanical properties of the materials used in the damper are estimated, effectively guiding the design of the device and boosting its vibration-reducing performance. A large-load unmanned aerial vehicle (UAV) airborne radar is the subject of this research article. According to particular use case, vibration dampers for the radar-mounting platform are designed using passive vibration isolation technology to reduce aircraft vibration transmission to the radar. A conference paper has already presented prior research on the same topic. Earlier research confirmed the vibration-isolating efficacy of the T-type rubber isolator, which can greatly improve the operational conditions of the airborne radar. In contrast, earlier studies relied more on experimental validation and did not use numerical simulations. This research's primary objective is the development of a T-type rubber isolator, whose vibration reduction performance is proven using FEM and experiments. Utilizing a suitable simulation analysis method to investigate the vibration reduction of an unmanned aerial vehicle's (UAV) airborne component is a crucial technical task. By comparing multiple material models, a more precise model for characterizing rubber was developed. [ABSTRACT FROM AUTHOR]