Conclusion Section Research Articles

Towards Reliable ECG Analysis: Addressing Validation Gaps in the Electrocardiographic R-Peak Detection

Electrocardiographic (ECG) R-peak detection is essential for every sensor-based cardiovascular health monitoring system. To validate R-peak detectors, comparing the predicted results with reference annotations is crucial. This comparison is typically performed using tools provided by the waveform database (WFDB) or custom methods. However, many studies fail to provide detailed information on the validation process. The literature also highlights inconsistencies in reporting window size, a crucial parameter used to compare predictions with expert annotations to distinguish false peaks from the true R-peak. Additionally, there is also a need for uniformity in reporting the total number of beats for individual or collective records of the widely used MIT-BIH arrhythmia database. Thus, we aim to review validation methods of various R-peak detection methodologies before their implementation in real time. This review discusses the impact of non-beat annotations when using a custom validation method, allowable window tolerance, the effects of window size deviations, and implications of varying numbers of beats and skipping segments on ECG testing, providing a comprehensive guide for researchers. Addressing these validation gaps is critical as they can significantly affect validatory outcomes. Finally, the conclusion section proposes a structured concept as a future approach, a guide to integrate WFDB R-peak validation tools for testing any QRS annotated ECG database. Overall, this review underscores the importance of complete transparency in reporting testing procedures, which prevents misleading assessments of R-peak detection algorithms and enables fair methodological comparison.

An overview of graph neural networks for molecular biology: Challenges and solutions

This review explores the application of graph neural networks (GNNs) in molecular biology, with a particular focus on their role in drug discovery. Various use cases, including molecule classification for cardiotoxicity detection and the prediction of molecular properties have been examined. A comprehensive analysis compares methodologies, problem statements, datasets, and findings across different studies. A core themes of review is the intuition to regularize a graph neural network which was proven to be reliable in terms of robustness for drug discovery purposes using noise nodes techniques. In the conclusion section, key insights from the reviewed literature and promising future directions for research have been presented. This work aims to provide a foundational understanding and guide future innovations in leveraging GNNs for molecular applications.

Chip Appearance Inspection Using Machine Learning Techniques

In recent years, the increasing demand for chips has put forward higher requirements for chip production quality and production efficiency. After the chip manufacturing is completed before leaving the factory, it needs to be detected after packaging, which makes the development of chip detection and localization system difficult due to the small size and large number of chips and the high precision requirements for them. Therefore, this paper aims to design a fast, highprecision chip detection and positioning system for the positioning and detection needs of the chip packaging process, the chip detection and positioning system for in-depth research, to achieve the accurate positioning of the chip as well as the deformation produced by the detection of the main work is as follows: the first chapter is mainly about why this paper is mainly aimed at discovering the problems in the chip packaging process. The second chapter is about how to take pictures of the chip. Chapter 3 focuses on the pre-processing of the pictures. Chapter 4 focuses on determining whether the chip is deformed through different machine learning and deep learning techniques. Finally, the conclusion section summarizes the whole paper.

Manufacturing strategies for highly sensitive and self-powered piezoelectric and triboelectric tactile sensors

Abstract Piezoelectric and triboelectric effects are of growing interest for facilitating high-sensitivity and self-powered tactile sensor applications. The working principles of piezoelectric and triboelectric nanogenerators provide strategies for enhancing output voltage signals to achieve high sensitivity. Increasing the piezoelectric constant and surface triboelectric charge density are key factors in this enhancement. Methods such as annealing processes, doping techniques, grain orientation controls, crystallinity controls, and composite structures can effectively enhance the piezoelectric constant. For increasing triboelectric output, surface plasma treatment, charge injection, microstructuring, control of dielectric constant, and structural modification are effective methods. The fabrication methods present significant opportunities in tactile sensor applications. This review article summarizes the overall piezoelectric and triboelectric fabrication processes from materials to device aspects. It highlights applications in pressure, touch, bending, texture, distance, and material recognition sensors. The conclusion section addresses challenges and research opportunities, such as limited flexibility, stretchability, decoupling from multi-stimuli, multifunctional sensors, and data processing.

Multifaceted Interventions to Enable Elimination of Clinician-ordered Blood Smear Reviews: A Rural Academic Medical Center Experience

Abstract Introduction/Objective Blood smears (BS) evaluate a variety of clinical disorders. At Geisinger, clinician ordered pathologist review of blood smears (CBS) have increased despite usage of highly sophisticated hematology analyzers and automatic blood smear (ABS) review criteria. We hypothesized that CBS impact pathologists’ and technologists’ workloads and increase costs and turn-around times, with rare improvement in value-based patient care. This study aimed to analyze CBS ordering practices and improve the utilization of BS review. Methods/Case Report In October 2020, a prospective CBS utilization study was completed by 8 clinical pathologists for 172 CBS. Subsequently, a clinical question was required for CBS orders from January 1, 2022, to January 1, 2023, to investigate clinician ordering practices based on campus, department, and indications. Findings were used to support new interventions including: clinician education; cancellation of repeat BS ordered within 24 hours, creation of alternative tests (schistocyte technologist smear review, clinician order for independent slide review), standardization of morphology reporting, ABS audits, and elimination of orderable CBS replaced by an electronic BS review request, that is reviewed by a clinical pathologist prior to determine if a BS is indicated. Results (if a Case Study enter NA) Part of the Conclusions section for Lab Practice abstract. Conclusion Prospective utilization audit of 172 CBS orders showed 17% changed clinical management. Audit of 3,693 CBS orders demonstrated common reasons for review included tick-borne illness, hemolysis, erythrocytosis, thrombocytosis, and iron deficiency anemia. Systematic implementation of multiple interventions enabled the elimination of CBS, with no known adverse effect on patient management to date. The streamlined BS review guidelines allowed for better-allocation of resources, appropriate patient turn-around times, empowerment of laboratory technologists and reduced hospital costs. We propose maximizing the incorporation of technologist skills to improve the utilization and efficiency of BS reviews and establishing standardized, evidence-based, and institutional- specific guidelines to determine BS reviews.

Time delayed fractional diabetes mellitus model and consistent numerical algorithm

The diabetes mellitus model (DMM) is explored in this study. Many health issues are caused by this disease. For this reason, the integer order DMM is converted into the time delayed fractional order model by fitting the fractional order Caputo differential operator and delay factor in the model. It is proved that the generalized model has the advantage of a unique solution for every time t. Moreover, every solution of the system is positive and bounded. Two equilibrium states of the fractional model are worked out i.e. disease free equilibrium state and the endemic equilibrium state. The risk factor indicator, R0 is computed for the system. The stability analysis is carried out for the underlying system at both the equilibrium states. The key role of R0 is investigated for the disease dynamics and stability of the system. The hybridized finite difference numerical method is formulated for obtaining the numerical solutions of the delayed fractional DMM. The physical features of the numerical method are examined. Simulated graphs are presented to assess the biological behavior of the numerical method. Lastly, the outcomes of the study are furnished in the conclusion section.

Enhancing TVET Education for the Future: A Comprehensive Review of Strategies and Approaches

This systematic literature review investigates the future enhancement of TVET education. The review examines a variety of studies and research articles to gain insight into the role of vocational education in shaping and improving the TVET system. The review begins with an introduction that provides background information on the importance of TVET and vocational education in preparing individuals for the workforce. The review's objective is to analyse and synthesize existing literature to identify the critical role of vocational education in developing the TVET system. In the method section, we describe the systematic approach we used to identify relevant studies and select appropriate articles for review. In this paper, we provide a systematic review analysis based on preferred reporting items for the Systematic Reviews and Meta-Analysis (PRISMA) technique for virtual reality implementation. We conduct advanced searches using two robust databases: Scopus and Eric. Our search finally yielded the primary data (n = 35), which we will analyse using the synthesis approach. Four central themes were decided: (1) career development and employability in TVET; (2) digital transformation in TVET; (3) pedagogy and teaching approaches in TVET; and (4) assessing competency and training in TVET education. The findings section presents the key findings extracted from the selected studies, highlighting vocational education's various roles and contributions to the TVET system. The conclusion section summarizes the review's main findings and provides insights into the importance of vocational education in fostering the growth and effectiveness of the TVET system. The review highlights the need for continued research and collaboration to further enhance the role of vocational education in TVET education and meet the evolving demands of the workforce.

How Organizational Inefficiency Adversely Affects Number-of-Employee Based Production Outputs

Abstract This study uses an analytical approach to investigate the emerging disconnect between firm size and financial performance, as observed recently from a set of long-term data collected from U.S. public firms. By holding all organizational aspects of a firm constant, it confirms the validity of the old saying that the larger a firm is, the better chance it can secure advantages against rivals and the higher returns it can fetch. However, if the assumption about organizational aspects is removed, the present study shows that if a firm employs its assets to increase production output through hiring additional employees, then the consequently increased organizational inefficiency, as caused by interactions of the employees, will soon erase the expected increase in the output. Additionally, it is also shown, among other results, that when a firm hires additional human labor to meet the increasing market demand, the expected profit will decline after first reaching its maximum level. These results crystalize what has been speculated and what have been empirically observed. In the conclusion section, it is recommended that increasing a firm’s size, in terms of the number of employees, is not a realistic, efficient solution to meeting the challenge of increasing market demand. Instead, any genuine solution must satisfy the condition that it does not increase the organization’s inefficiency of the firm, such as increasing the magnitude of automation and/or digitization.

Timber family houses: Potential for digitization and automation

Abstract Wooden constructions have a rich historical background globally. Due to their attributes, modern timber buildings present opportunities for energy efficiency and environmental conservation, thus aiding in mitigating the ecological footprint of the construction sector. This paper aims to compare the diverse methodologies employed in timber construction between the US and Europe and subsequently evaluate the potential for digital transformation and automation within the operations of RD Rýmařov, Czechia’s largest producer of single-family timber residences. The unique aspect of this company is the whole process (design, prefabrication, assembly) is fully controlled by the company itself. This study synthesizes insights from the ongoing research project Automation4Timber, currently in its concluding phase. The methods section delineates the process enhancement initiatives carried out by RD Rýmařov, encompassing preparatory, production, and assembly phases, each comprising various components. All instituted alterations facilitating digitalization and automation are elucidated in the Results section. The subsequent discussion and conclusion sections encapsulate the experiential insights gained from the implementation process, highlighting key aspects and potential challenges. This paper adds value by presenting a tangible case study of a manufacturing enterprise.

Identifying the benefits of recovery programs of aquatic gymnastics, aquatic ludotherapy and therapeutic swimming on human motor, kinetotherapeutic and mental capacity

IntroductionThis study aimed to evaluate the motor, kinetotherapeutic, and psychological benefits of three aquatic therapeutic programs—aquagym recovery (AG), aquatic ludotherapy (ALT), and therapeutic swimming (TS)—for students specializing in balneo-physio-kinetotherapy. MethodsThe study group consisted of 101 students, out of which 43 students from the balneo-physiokinetotherapy study program (BFKT) and 67 master's degree students from physical therapy and functional rehabilitation (PTFR). The questionnaire was named Questionnaire regarding the benefits of therapeutic aquatic programs (QBTAP), and included 3 subscales according to the typology of the targeted objectives, namely: motor, kinetotherapeutic and psychological. The items of each subscale correspond to the objectives identified in the content of the 3 aquatic programs stipulated in the content of the courses corresponding to the disciplines in the education plans of academic study programs (BFK, TRFR). The motor subscale included 8 items, the kinetotherapeutic subscale included 16 items, and the psychological subscale included 10 items. The evaluation of the QBTAP questionnaire 5-point Likert scale. The three evaluated programs were: recovery aquagym (AG), aquatic ludotherapy (ALT) and therapeutic swimming (TS). ResultsThe results and conclusion sections should highlight the main findings succinctly. For example: "The QBTAP showed high internal consistency (Cronbach's Alpha >0.9) across all subscales and programs, with significant differences identified between the three programs (p < 0.05). ConclusionThe study concludes that aquagym most effectively improves motor capacity, aquatic ludotherapy enhances psychological function, and therapeutic swimming is most beneficial for recovery and rehabilitation.

Building Design in Historical Environment-Periodical Study-Haydarpaşa / Seli̇mi̇ye

Turkey&amp;apos;s geography is rich in cultural diversity. The existing diversity is reflected in all areas of life. Among these areas, architecture cannot be ignored both in terms of scale and building stock. In this context, architecture is in constant relationship with cultural heritage. In a professional sense, it is inevitable to produce new buildings in the historical environment and to know how the cultural heritage will form an input to the design. For this reason, studio studies, which are the basis of architectural education, constitute the most important process. In this context, within the scope of the studio 5 course of the 2023-24 fall semester of the Department of Architecture of Yeni Yüzyıl University, “experimental design of a faculty of architecture between 8000-10000m2” was carried out in Haydarpaşa-Selimiye with the participation of 10 students. Haydarpaşa-Selimiye neighborhood is very rich in terms of many types of buildings built in the 19th and 20th centuries of the Ottoman Empire. The aim of this study was to enable the participating students to develop design approaches sensitive to the historical environment. In the first stage; the area determined as the study area was examined and design problems were aimed to be revealed, and the projects created in this direction were questioned by supporting the determined design criteria and environmental analyzes. In the second stage, design approaches were shaped in line with the environmental analysis and the concept, and periodicalstudy examples emerged. Existing texture-historic environment unity, historical environment-new building design approaches were the achievements obtained at the end of the semester. In the conclusion section; in line with the approaches developed by the students, the evaluation of historical environment data and new building design approaches were evaluated, and the importance of new building designs in the historical environment in architectural education was emphasized.

Artistic interventions: Art, community, and media in China and beyond

Artistic interventions in communities have become increasingly prevalent in the context of quality-led urbanization and rural revitalization in China over the past decade. These art practices reflect a narrative of resistance toward the institutionalization, professionalization, and marketization of contemporary art through direct interventions in social reality. Community is the most common site from which public aesthetic action and social activism emerge to increase public awareness and promote community engagement. With the rise of new media technologies, multi-media have gradually been combined in socially engaged art projects, which has blurred the boundaries between concrete materials and virtual media as well as that between physical places and the online community. This article first outlines a literature review on the changing avant-garde spirit in both global and Chinese art history to better understand the concepts of artistic interventions. Second, as a major intervention in this field, the focus on community reflects the interflow of the theoretical search for communicative ethics and community reconstruction movements worldwide. Third, the role of the media in socially engaged art and its future implications are discussed. In the conclusion section, a variety of specific contexts in China and beyond and the various intervention aims and methods of five selected articles are introduced.

PROCESSAMENTO DE LINGUAGEM NATURAL PARA RECONHECIMENTO DE ENTIDADES NOMEADAS EXTRAÍDAS DE CORPUS

This article presents a code implementation to automate the reading, analysis and generation of summaries of unstructured web texts, highlighting the crucial role of Natural Language Processing (NLP). The process was divided into two stages: data collection and pre-processing. In the first stage, a scientific article was selected and relevant data was extracted via web scraping, organized into an HTML page hosted online. In pre-processing, tokenization, normalization, stopword removal and word counting were performed. Using NLTK, the most important sentences were identified and ranked based on keyword frequency, allowing the selection of the most relevant sentences from the introduction, methodology, results/dicussion and conclusion sections. Discrepancies such as links and figure descriptions have been removed to improve the clarity of the abstract. The “most_common()” method was used to select the most relevant words in each section. After additional processing to delete unnecessary words, the final summary was clear and understandable, despite minor flaws. This automated approach provides an efficient way to synthesize information from scientific articles, optimizing the textual analysis process.

HOW THE PERCEIVED ENJOYMENT EFFECT M-PAYMENT ADOPTION IN WEST PAPUA PROVINCE: DELONE AND MCLEAN INFORMATION SYSTEMS SUCCESS MODEL

M-payment is a form of adaptation in payment systems through digital technology. This study aims to determine the influence of perceived enjoyment as a complementary factor to the DeLone and McLean (DM) Information System Success Model of m-payment adoption level in West Papua Province. A total of 244 valid respondents were obtained via a questionnaire using purposive sampling technique and analyzed using PLS-SEM. The results showed that out of eleven hypotheses, eight were accepted, and three were rejected. The result show that the Perceived Enjoyment (PE) significantly influences the m-payment adoption level in West Papua Province. However, service quality is not a determinant of m-payment adoption levels in West Papua Province. Additionally, system quality not a determinant on user satisfaction of the technology. A post-hoc evaluation was also conducted using gender and age as control variables, indicating that the adoption levels varied among the control variable groups. This provides significant insights both theoretical and practical which are discussed in discussion and conclusion section.

The Mediating Role of Employee Voice between Despotic Leadership, Psychological Empowerment and Employee Performance

This research effort aims to address the indispensable factor of employee voice, which impacts employee behavior and causes negative emotions. Despotic leadership is a crucial constituent of the workplace and impedes performance-related outcomes. Psychological empowerment facilitates positive behavioral outcomes, including employee voice and performance. This study contributes to the body of knowledge by explaining the role of employee voice in despotic leadership, psychological empowerment and employee performance. The banking sector of Pakistan is one of the remarkable sectors that provides employment and financial services, but it faces various controversial employee issues including leadership, psychological, and behavioral issues that impede performance. This research paper contributes to bridging the research gap in explaining how employee performance is influenced by despotic leadership and psychological empowerment with the mediation role of employee voice. Despotic leadership is an essential element in determining the working environment; psychological empowerment is important for employees’ behavior that predicts employee performance. Most importantly, employee voice has central importance in at the workplace that predicts and impacts employee performance. employee voice creates the working environment that the firm desires. The mediating role of employee voice tends to establish the relationship between despotic leadership, psychological empowerment and employee performance. The current paper focuses on front-line employees of bank in Punjab, as data was collected by employing a simple random sampling technique; the sample size was 310 employees from different banks in different cities. The collected data was later analyzed on Smart-PLS 4.0 for relationship assessment. The results depicted that despotic leadership negatively impacts employee voice and employee performance, while psychological empowerment positively influences employee voice and employee performance and is mediated by employee voice. Limitations and future research recommendations are given in the conclusion section.

Moves and language expressions of conclusion section of thesis at postgraduate English education study program of Bengkulu University

The conclusion section is a compulsory chapter of a thesis and a dissertation. A good thesis or dissertation conclusion should tell the reader what work has been done and why the issue is being taken. The conclusion section of theses in the field of English language education is a form of a summary statement of the cases investigated. The summary is expressed with certain language expressions, indicating each of the 5-move of the section. The purpose of this research was to describe moves and language expressions of conclusion sections of theses written by the postgraduate English Language Study Program students of Bengkulu University. The study employed the descriptive quantitative method. The subjects of the research were 40 theses of postgraduate students of Bengkulu University which were selected purposively. The data of the conclusion moves were examined based on the five-move model proposed by Bunton (2005), and the language features were analysed based on Morley (2014). The results show that move 3 (Practical application/implications/recommendations embedded elsewhere) and move 4 (recommendations for future research embedded elsewhere) were used by 33 authors (88%) and 35 authors (77.5%) respectively. However, the move formats of the conclusion section were widely varied, nonconforming to Bunton’s model. The language expressions used in the majority of the conclusion sections have adhered to guidelines proposed by Morley (2014), but many authors tended to choose weaker language expressions to emphasize the points. This study concludes that five Move Models of the conclusion section proposed by Bunton (2014) have not been reflected markedly in most of the thesis conclusion sections written by the Postgraduate English Language Study Program students of Bengkulu University, although some moves have been written in suitable language expressions.

A New Solution Technique for Fuzzy Transportation Problem Using Novel Ranking Functions on Heptagonal Fuzzy Numbers: A Case Study of Regional Shipment

This study focuses on the fuzzy transportation problem that manifests as a problem of optimization in an uncertain environment. The idea of fuzziness in the objective of transportation cost is based on real-world decision-making difficulties, and the efficiency is demonstrated using the proposed heptagonal fuzzy number. We propose a new ranking technique to de-fuzzify the Linear heptagonal fuzzy number and the proposed $\alpha$-cut based ranking technique has been compared with the existing ranking technique. In addition, we presented an approach for performing multiplication and division for any two heptagonal fuzzy numbers incorporating an example. Furthermore, we have presented a generalized ranking heptagonal fuzzy method (GRHFM) algorithm to solve the heptagonal fuzzy transportation. This article determines the best transportation cost for vegetable shipment from the markets utilizing heptagonal fuzzy numbers, which further compares the feasible solutions obtained using various strategies for fuzzy transportation problems and provides the result from the algorithm. We have demonstrated the effectiveness of our proposed method through a numerical example of an adopted case study. The conclusions section discusses the suggested GRHFM efficiency, outcomes, decision management and future directions based on the existing transportation study.

INTEGRATING NEURAL NETWORKS INTO SHEET METAL FORMING: A REVIEW OF RECENT ADVANCES AND APPLICATIONS

In order to predict defects, improve performance, and streamline operations, machine learning techniques are becoming ever more indispensable in manufacturing processes, mainly in sheet metal forming. Incorporating neural networks into the process of sheet metal forming is the subject of this article's exhaustive examination of recent developments and applications. Exploring datasets from a variety of sheet metal forming processes, numerous machine learning models, including ensemble and single learning techniques are investigated. The functionality of this method extends to various tasks, including the prediction of springback in cold-rolled anisotropic steel sheets. The review provides a conclusion section that presents the main implementation methodologies and how they address to some manufacturing issues.

Analyses the Strategies for Sustained Membership Growth in Post-COVID-19 China

China's domestic retail industry has been adversely affected by the recent coronavirus pandemic for the past two years. Nevertheless, following the containment of the outbreak, the general condition has ameliorated. The objective of this paper was to examine the factors contributing to the growth of Sam's Club stores in China following the conclusion of the COVID-19 pandemic. Additionally, the paper aims to propose systematic strategies to enhance customer turnout at Sam's Club and other retail establishments in China. This study employed a case study methodology to examine the aspects that could potentially contribute to the expected growth of Sam's Club between 2022 and 2023. The conclusion section of this article analyzes the determinants that impact the sustainable development of Sam's Club. The study included suggestions on how Sam's Club and the Chinese retail industry may adapt in order to sustain the growth of their membership numbers in the near future.

Comparing two crowdsourcing platforms: assessing their potential for mapping Antarctica

sGeographical data acquisition in Antarctic regions is challenging due to the lack of human habitation, harsh environmental conditions, and limited accessibility. This research explores and evaluates the capability of two crowdsourcing platforms in mapping facilities across Antarctic regions. The study presents crowdsourcing projects related to polar regions in the literature. The methodology section outlines the data acquisition techniques employed by Flickr and Happywhale, and the spatial evaluation methods applied to the collected data. In the implementation and results section, the spatiotemporal potential of the data obtained from the two identified crowdsourced platforms is assessed, and the results based on spatial statistical methods are compared. In the discussion and conclusion section, the contribution of the two identified crowdsourced platforms to mapping activities is evaluated in terms of spatial, temporal, and content differences. This study reveals that Happywhale offers data with higher spatial consistency, considering seasonal representation and spatial autocorrelation. Additionally, content restrictions and reliance on GPS enhance spatial accuracy in Happywhale. At the same time, the liberation of data production leads to lower quality but increased quantity, diversity, and spatial coverage, as observed in Flickr. By comparing two crowdsourced platforms, this study enhances data acquisition and evaluation potential in Antarctica.