Reviewerly/exHarmony huggingface dataset:
Attempting a metapsychology for tele-copresence

AbstractAbstractThe concepts of immersion and digital presence have been widely used in the human–computer interaction and virtual environment research fields and have been particularly valuable when it comes to a better understanding of tele-therapy, tele-analysis, and other forms of tele-linking. Using a metapsychological perspective, we will attempt a psychoanalytic interpretation of these phenomena. We will conceptualize them as hypnoid states that reflect a compromise between internal and external conditions, including specific defensive mechanisms and psychic dynamics. This conceptualization will be applied to the tele-analytic situation and other relevant fields of application.Key words: tele-copresencetele-linkingpresenceimmersionvirtual-digital Additional informationNotes on contributorsLucio Alberto Gutiérrez HeraneLucio Alberto Antonio Gutiérrez Herane holds a doctorate in psychotherapy research from Pontificia Universidad Católica de Chile. He is a psychoanalyst and full member of the Chilean Society of Psychoanalysis (ICHPA), as well as an academic and training supervisor. He is a past president of ICHPA and alternate member of the International Federation of Psychoanalytic Societies executive board.Dr. Gutiérrez works in private practice, treating adolescents and adults and consulting parents on issues concerning modern upbringing. He has also established a longstanding line of conceptual and clinical research on how humans interact with the virtual-digital, based on Freudian–Winnicottian metapsychology.Dr. Gutiérrez has published in various local and international journals as well as compilation books. His paper “Silicon in ‘pure gold’? Theoretical contributions and observations on tele-analysis by videoconference” (Gutiérrez, 2016 Gutiérrez, L. (2016). Silicon in ‘pure gold’?: Theoretical contributions and observations on teleanalysis by videoconference. International Journal of Psychoanalysis, 98, 1097–1120.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) reached The International Journal of Psychoanalysis annual selection and was published in English, Spanish, and German.
Detection of fraudulent transactions using artificial neural networks and decision tree methods

The accounting systems generate a large amount of data due to financial transactions. Intentionally fraudulent transactions can occur in high-dimensional and large numbers of emerging data. While many methods can be used for the estimation and detection of fraudulent transactions in accounting, which differ in the audit process, scope and application method, data mining methods can also be used today due to a large number of data and the desire not to narrow the scope of the audit. This study tested the accuracy of detecting fraudulent transactions using artificial neural networks and decision tree methods. According to the results of the analysis test data set for detecting fraud or error risk, 99.7981% accuracy was obtained in the artificial neural networks method and 99.9899% in the decision tree method.
How to Determine The Quality of Game-Based Media for Mathematics Learning?

Development research has become one of the popular studies in the 5.0 society era. Technological sophistication is a driving factor for educators and researchers to create shopisticated learning media. Technology-based learning media comes with their own uniqueness, one of which is game-based media (GBM). GBM has changed students’ perception that learning can be done by playing game. Before GBM is applied in the learning process, it is necessary to evaluate the media. This is intended so that GBM has good quality. GBM with high quality can improve its functions as a learning media. On the other hand, GBM can not only present an element of fun learning, but can also have a positive influence on the cognitive, affective, or psychomotor aspects of students. This literature review research provides theory for educators and other researcher to asses GBM. Overall, there are four aspects that need to be assessed in determining quality of game-based media, validity, practicality, effectiveness, and sophistication. Abstrak Riset pembangunan menjadi salah satu kajian yang populer di era masyarakat 5.0. Kecanggihan teknologi menjadi faktor pendorong bagi para pendidik dan peneliti untuk menciptakan media pembelajaran yang canggih. Media pembelajaran berbasis teknologi hadir dengan keunikan tersendiri, salah satunya adalah media berbasis game (GBM). GBM telah mengubah persepsi siswa bahwa belajar dapat dilakukan dengan bermain game. Sebelum GBM diterapkan dalam proses pembelajaran, perlu dilakukan evaluasi media. Hal ini dimaksudkan agar GBM memiliki kualitas yang baik. GBM dengan kualitas tinggi dapat meningkatkan fungsinya sebagai media pembelajaran. Di sisi lain, GBM tidak hanya dapat menghadirkan unsur pembelajaran yang menyenangkan, tetapi juga dapat memberikan pengaruh positif terhadap aspek kognitif, afektif, atau psikomotor siswa. Penelitian tinjauan pustaka ini memberikan teori bagi pendidik dan peneliti lain untuk menilai GBM. Secara keseluruhan, ada empat aspek yang perlu dinilai dalam menentukan kualitas media berbasis game, validitas, kepraktisan, efektivitas, dan kecanggihan.
QR Sort: A New Non-Comparative Integer-Based Sorting Algorithm

Abstract In this paper, we introduce a new stable, non-comparative integer-based sorting algorithm with an attainable linear time complexity, O(n). This approach utilizes the Quotient Remainder Theorem in conjunction with Counting Sort subroutines. This algorithm divides each input array element by a selected positive integer divisor, d, to generate representative remainder and quotient keys. We perform Counting Sort on the remain-der keys followed by the quotient keys. This method yields a time and space complexity of O(n + d + k/d), where k represents the difference between maximum and minimum array values. If we set the divisor, d, equal to the length of the input array, n, the complexity simplifies to O(n + k/n). As the length of the input array increases and the value of k remains constant, the time complexity converges to O(n). Our results indicate that our algorithm outperforms established integer-based sorting algorithms such as Counting Sort and Least Significant DigitRadix Sort with large input arrays. We present our methodology and comprehensive discussion of our results in the main body of the paper.
Impact of individual competence on agile effort estimation in academic setting

Effort estimation is an important activity in agile software development. The goal of the presented study was to determine the influence of individual competence on software development effort estimation. In particular, we measured both the accuracy of effort estimation and the duration of the estimation process itself, both for three different estimation methods. The subjects of our study were teams of students of a graduate-level software engineering course at the University of Ljubljana, Faculty of Computer and Information Science. Based on the grades that individual students attained in their undergraduate study, we classified each team as ‘high-competence’ or ‘low-competence’ and additionally as ‘heterogeneous’ or ‘homogeneous’ (the criterion here being the variance of the members’ average grades). We found out that there was no significant difference in effort estimation accuracy neither between high-competence and low-competence teams nor between heterogeneous and homogeneous teams, regardless of which estimation method was used. However, high-competence teams spent significantly less time on effort estimation than low-competence ones. Likewise, for two of the employed estimation methods, heterogeneous teams completed effort estimation in a significantly shorter time than homogeneous teams. These results might benefit both academic and professional community.
Evaluation of the Medium-sized Neural Network using Approximative Computations on Zynq FPGA

Integrating artificial intelligence technologies into embedded systems requires efficient implementation of neural networks in hardware. The paper presents a Zynq 7020 FPGA implementation and evaluation of a middle-sized dense neural network based on approximate computation by linearly approximated functions. Three famous benchmarks were used for classification accuracy evaluation and hardware testing. We use our highly pipelined neural hardware architecture that takes weights from block RAMs to save logic resources and enables their update from the processing system. The architecture reaches excellent design scalability, allowing us to estimate the number of neurons implemented in programmable logic based on single-neuron resources. We reached nearly full chip utilization while preserving the high clock freuuency for the FPGA used.
State-Aware Path-Following with Humans Through Force-based Communication via Tethered Physical Aerial Human-Robot Interaction

The area of Aerial Physical Interaction has seen significant advancements, creating the opportunity for aerial robots to physically interact with humans. Our previous works established a framework for safe, human-aware path guidance via a tether, physically connecting a human to an aerial vehicle. However, the previous controller is purely reactive and does not leverage modern path-following methods. Further, its design does not properly account for the non-holonomic nature of the tethered human-robot system. In this paper we improved performance by addressing both problems. First, we incorporate modern path-following methods into our guidance framework to account for path geometry and current system velocity. Second, we propose a polar parametrization of the guidance law to achieve faster convergence of the guidance force to the desired value. Finally, the performance and human comfort of the different extensions is evaluated in simulation. The final method is shown to increase guidance accuracy and comfort, thereby increasing the usefulness of guidance via aerial robot interaction.
Survey of Software Maintenance Metrics: A Systematic Literature Review

The software maintenance area is one of the oldest in software engineering, which is a fundamental role in all development, ensuring the final product quality and stability in the market. However, the control of software maintenance metrics becomes a difficult task, as there are no consistent applicability normalization for these metrics, and it is up to the software maintenance teams to decide which metrics to apply. In order to identify the main metrics used in the software maintenance area, we carried out a systematic review of the literature on the relevant studies published in the period between 1990-2020 into the main search engines in the area of software engineering. According to the keywords and inclusion and exclusion criteria, 44 out of 2145 articles were selected on the IEEE, ACM Digital Library, ScienceDirect, SCOPUS and Wiley Interscience. Thus, the software maintenance metrics were identified in the product, process and resource perspectives more widely directed towards the product, as well as the application validation of these metrics are made through technical experimentation of the measurement, that is, validations in a controlled environment that often do not match the reality of the software maintenance environment. Therefore, it is highlighted that the analysis of software maintenance metrics is a promising area for new researches targeting distinct perspectives, including in a real software maintenance environment.
Cloud and AI Powered MediTrack Application For Elderly and Visually Challenged Person

The increase in illnesses and pandemics has forced doctors to care for patients nonstop, around-the-clock. Despite the fact that many people have used medical applications, none of them offer the full range of services that customers anticipate. This works seeks to helps elderly and visually challenged folks to consult the health practitioner at their convenience. Patients can obtain their medical history and prescriptions by connecting to doctors using the unique Id assigned to each user. We assist elderly and visually impaired persons in making appointments online so they can avoid waiting in huge lines at the hospital. For some reason the doctor couldn't make up with the scheduled appointment and this is where doctor suggestion system comes into picture where we analyze patient's past visits and recommend new appointments with doctors. Doctors can prescribe medicines to patients using the centralized prescription system which is stored using Firebase cloud Realtime Database, and with the Smart reminder, the patient is made sure to consume medicines at the prescribed time. Each and every patient has an electronic record (ER) maintained and stored in the cloud storage which makes sure to record the patient's history when visiting one or more doctors. The application has a center picture for the elderly persons, by the use of Voice assistant to perform necessary actions on the application and use almost all of the elementary functions. When a doctor is prescribing medicine to the patient, Our Smart Drug Interactor (SDI) gives a note suggesting the after-effects when the prescribed medicine is consumed along with other prescribed medicine using the Deep Neural Network
Color Compensation Based Fusion for Enhancement of Weakly Artitifical Illuminated Indoor Images

In this article, a new approach is introduced to enhance the weakly artificial illuminated indoor images by blending three color compensated versions obtained by Color Equalization (CE), Color Mixing (CM) and Gray-World (GW) methods. This method ignores the disadvantages of blue dominancy, green dominancy and black artefacts results respectively due to CE, GW and CM and this forms prior for this fusion approach. To fuse the advantages of all three enhanced versions of low illuminated images, the multi-scale image fusion technique is employed. To get the information of background scenes, contrast limited adaptive histogram equalization (CLAHE) is applied to the blended image. The experimental results illustrate that the approach proposed in this work outperforms the existing methods.
Research on Cloud Side Collaboration Architecture and Lightweight Model of Distribution Network

With the continuous development of the deep learning model, the prediction accuracy of the model has reached a high enough level. The high memory consumption in the prediction of the deep learning model has become a problem that needs to be solved. Moreover, the large size of the model not only brings about the memory capacity problem, but also requires sufficient memory bandwidth. At the same time, when the model is running, the battery will also be rapidly consumed, which is also a test of the endurance of the mobile terminal. In order to solve the above problems, this paper proposes a cloud-side collaboration method based on federated learning, carries out research on deep neural network model compression algorithm, reduces the size of the model under the condition of ensuring the accuracy of the model, so that the prediction effect will not have too much loss, while reducing the requirements for the performance of the edge and end devices, realizes the cloud-side collaboration of the distribution network, and accelerates the digital transformation of the distribution network.
Multimodal Brain Tumor Image Segmentation Based on 3D CTrans U-Net: Replacing Skip Connection with Channel-Wise Attention Module

Automatic segmentation of brain tumors can be used as a powerful auxiliary means for clinical diagnosis, bringing better treatment. In recent years, medical image segmentation technology has mainly developed into two genres: convolution-based and Transformer-based. However, both of them more focus on the design of feature extraction, while less on the role of the skip-connection in the network structure. Based on the analysis of the contributions and disadvantages of skip-connection, the 3D CTrans U-Net is proposed to apply channel-wise cross fusion Transformer (CCT) and channel-wise cross attention (CCA) module to replace the skip-connection in 3D U-Net, which can better integrate multi-scale encoder features and bridge the semantic gap between encoder and decoder. The proposed method has achieved more accurate segmentation results on the BraTS2019 dataset, which has been improved to a certain extent compared with other state-of-the-art methods.
Online university education in the context of the Covid-19 pandemic

The COVID–19 pandemic remarkable affect the educational system, due to this crisis situation we had to adapt urgently. As a consequence, ASEM as many other universities has moved to online education. The survey was developed in order to analyse how students and teachers have adapted to the online system and what technical equipment do they need. Cuvinte-cheie online education, teachers and students, survey, pandemic
Developing a Digital Strategy for the Digitalization and Implementation of Remote and Combined Training in Restoration and Construction

three organizations have been involved in developing the digital strategy: Zalenieki Commercial and Craft School, Panevezys vocational education and training centre and Slovakia secondary vocational school of construction. Two experts from the Latvia University of Life Sciences and Technologies (hereafter – LBTU) were involved in the creation of the digital state. The digital strategy contains the description of the current situation in person and distance learning process, and previous experience in the use of e-learning systems. According to analysis of needs an action plan was drawn up by each school. The plan includes description of distance and blended learning in various modules, and further adult education. Schools have developed guidelines for the development of teaching materials for teachers. All principles were united by a common idea - an educational institution should have a unified student-friendly and future-oriented approach. Structure of e-learning platform was developed. The schools have chosen the most convenient structure based on the structure of the educational institution, or on another structure preferred by the teachers and the administration. In the digital strategy, an analysis of the needs in the digital sphere was conducted. In developing these needs in the digital sphere, the schools based on the results of the survey. During the survey, participants were asked to rate virtual image of the school, digital competencies, IT equipment of education institution and the ability to organize the learning process remotely. SWOT analysis was used to identify strengths, weaknesses, opportunities, and threats of each education institution. Despite the fact that distance learning in 2020 was an unplanned step, both teachers and students found both pros and cons in this process. Several IT tools and platforms have been mastered, but students do not have skills of self-directed learning, which could make the distance learning process more productive. The distance learning was the biggest challenge for profession teachers and students as to provide practical trainings of vocational subject online is very complicated or sometimes even impossible. The study aim is to introduce the creation of a digital strategy.
Online Supplement to “Informing Visual Display Design of Electronic Health Records: A Human Factors Cross-Industry Perspective”

This supplementary material has been provided by the authors to give readers additional information about their work.
Sharad Sathe

Sharad Sathe, 81, died Sept. 14, 2022, in Chesterfield, Missouri. “Besides being a great chemist, Sharad also had a passion for Indian classical music. He published a CD of his compositions in 2010. In retirement, he trained future Tabla (Indian drums) players in the Saint Louis area. But his most favorite role was being ‘Aaba’ to his grandson, Teddy. Sharad loved to travel and had visited over 35 countries and 47 states. His dream of visiting all 50 states remained unfulfilled. He was an avid golfer and tennis player. He lived a very full life. At the end, he chose quality over quantity.”—Usha Sathe, wife Most recent title: Technical director of R&D, Mallinckrodt Education: BSc, chemistry, University of Bombay, 1960; BPharm, pharmacy, Banaras Hindu University, 1963; PhD, chemistry, Indiana University, 1971 Survivors: Wife, Usha; daughters, Swapna and Vandana; one grandson To recognize your late loved one or colleague, submit obituary
Using Edmodo Learning Social Network on Teaching Some Vietnamese Modules in English for Students of Primary Education Major of Tan Trao University

The article is based on the practice of using Edmodo learning social networks in the world and in Vietnam to apply social networks to teach some Vietnamese modules in English for students of Primary Education major of Tan Trao University to adapt to the new normal. The application has created online classes parallel to face-to-face classes; Study guide; Evaluate; Archiving learning materials. Initial results show that: The roles of lecturers and students have changed positively; Learning activities are organized and implemented in a variety of ways; Exploiting effective learning data sources; How to evaluate effectiveness. Therefore, the use of learning social networks in teaching is an effective way to help the teaching process adapt to the new normal.
Action Wizard and JavaScript

Part IV contains a collection of extra lessons that I added to the end of the book for those who are more advanced users of JavaScript.
Digital Signatures and Barcodes

Chapter Goal: I haven’t yet discussed two form fields in great detail in regard to JavaScript: digital signatures and barcodes. Thus, this chapter focuses on them. Let’s first look at how they and other fields relate to security.
FinTech Services Delivery as Determinants of Customer’s Satisfaction: An Analysis of Banking Sector in Jordanian context

With emerging literature on Financial Technology (Fintech) a number of research studies were conducted to analyse and look at the role of fintech services for the growth of several aspects in banking industry. But, limited studies attempted to consider an influence of Fintech services delivery improve the client satisfaction around Jordanian Banks. Thus, this study aims at examine how Fintech services provision improve of client satisfaction in Jordan’s Commercial Banks. A survey design that is cross-sectional design; where 600 questionnaires were personally distributed using convenience sampling technique. Statistical conclusions of this investigation showed Payment services, Accessibility to Fintech services (AC), Availability (AV), Transactionary costs (TC) Fintech service security (SS) to have positive significant influence upon Client’s Satisfaction (CS). The findings recommend technology financial facilities suppliers would advance upon this package and let system produce services distribution to attain consumers' satisfaction at every stage. This study provides practitioners with important measures for evaluation of Fintech services effectiveness.