bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Barriers of Sustainable Consumption in Vietnamese Fashion Industry: A Data - Driven Model - Based Grey Theory System
Authors: Nguyen Phi-Hung , Vu Tra-Giang , Duong Hoang-Trieu , Nguyen Nam-Truong , Nguyen Thu-Hoai Thi
Published: September 2023

The fashion industry plays a significant role in global environmental degradation and social inequality due to its unsustainable consumption patterns. Therefore, understanding the barriers hindering the adoption of sustainable consumption practices in this industry is crucial for promoting positive change. This research aims to identify and analyze the barriers to sustainable consumption in the Vietnamese fashion industry using a two-stage data-driven model-based Grey theory system (Grey Delphi- Grey DEMATEL). To achieve this objective, a comprehensive literature review was conducted to identify the key barriers affecting sustainable consumption in the fashion industry. The critical barriers include social and cultural perspective, pricing and affordability, policy and education, perception and image, and supply chain and industry practices by developing a structured questionnaire that was distributed to 16 valid industry experts and professionals in Vietnam. The Grey Delphi technique is applied to validate 30 critical barriers to sustainable consumption in the Vietnamese fashion industry. The Grey DEMATEL model is employed to determine the causal relationships among selected barriers, considering both the direct and indirect influences. Additionally, the Grey theory system with Grey numbers was integrated into the model to address uncertainties and vagueness associated with the data. By employing the proposed model, the research provides a comprehensive understanding of the complex relationships between the identified factors and their impact on sustainable consumption. The outcomes of this research will enable industry stakeholders, policymakers, and researchers to develop targeted strategies and interventions to overcome these barriers and promote sustainable practices in the Vietnamese fashion industry.

Keywords: Sustainable consumption, barriers, fashion industry, Vietnamese, DEMATEL, Grey theory system.
Evaluating the Impact of Wellbeing Practices on Employee Resilience in Service Sectors
Authors: Jesrani Drishti.Rupesh. , Banu Ruksana.
Published: September 2023

An organisation's adaptability under dynamic and uncertain business environments and conditions can be identified by the level of resilience among the employees. Thus, making employee resilience an essential tool in measuring the malleability of an organisation. However, there are limited studies conducted that illustrate how employee resilience can be developed and practised. Additionally, with the recent concept of 'employee-friendly' and 'flexible-working arrangements' concepts the inclusion of employee wellbeing practices at organisations has drastically increased (Karen Tonkin, 2018). Moreover, with radical changes in employee lifestyle; employee wellbeing practices become a significant criterion for any employee choosing their workplace in an organisation. Thus, making the concepts of employee well-being and resilience essential for the organisation. Thus, the purpose of this study is to analyse the impact of employee well-being practices on employee resilience in service sectors (Rauhaus, 2017). Literature studies have conferred that organisations play a vital role in providing wellbeing practices for their employees and these have a greater impact on employee commitment and engagement as well as job satisfaction (Karen Tonkin, 2018). However, limited studies have examined the role of well-being practices and employee resilience, particularly in the context of Oman services sectors. Thus, the main research problem for this study is "how well-being practices impact employee resilience in the Oman services sector".

Keywords: Employee Well-being, Resilience, Services Sectors, Oman.
KIBS spillovers in the knowledge production function of manufacturing and services sub-sectors at the USMCA countries
Authors: Félix  , Fernando
Published: September 2023

In this paper, the knowledge production function is estimated by regressing R&D knowledge spillovers, capital investment and labor productivity on innovation generation, variable measured as filled patents, in the manufacturing and services sectors of each one of the three countries that integrate the USMCA Agreement (United States-Mexico-Canada Agreement). The results state that direct and indirect spillovers of KIBS R&D expenses, reinforced by capital investment and labor productivity measures, have a significative influence on the number of patents filled by each country over the years analyzed on those sub-sectors of the USMCA economy. That positive and causal effect generates knowledge production value chains from KIBS consultancies to the manufacturing and the services subsectors and backwards therefore reinforcing the value creation system of those services; also, by promoting the development of new goods and services by innovating in the production or administrative processes of the enterprises immerse on those subsectors (the embodied effect). The conclusions could serve as basis for the analysis of the sectorial policies that have to be stipulated by the conjunction of the politicians of the three countries, in the institutions already been established by the USMCA agreement in recent years.

Keywords: KIBS, I-O direct and indirect impacts, USMCA, knowledge spillovers, manufacturing and service sectors, patents, innovation, knowledge production function.
Impact of E-Commerce Live Broadcast on Online Purchase Intention: An Empirical Research Based on Social Technology Theory
Authors: Liu Jingfeng , Dasig, Jr Daniel D.
Published: September 2023

The study aimed to determine the impact of a live broadcast on customers online purchase intention based on the social technology theory among financial management students in China. This paper took e-commerce live broadcast as the research object, and tests the overall marketing effect of e-commerce live broadcast and the impact mechanism of e-commerce live broadcast service quality on online purchase intention. This study utilized a descriptive correlational research design. In particular, the descriptive phase will be used in determining the profile of the respondents; in determining the respondents' perception on the impact of e-commerce live broadcast unique technical features on consumer participation; in determining the respondents' perception on the impact of e-commerce live broadcast on service quality; and in determining the respondents' perception on the impact of e-commerce live broadcast characteristics to online purchase intention. In addition, the relevant stages included the testing the relationship and importance of the impact of e-commerce live broadcast on online purchase intention, and testing the impact of respondents' e-commerce live broadcast on online purchase intention, as well as the differences and significance of the above e-commerce live broadcast technical features, service quality, and other relevant features. The research objects of this paper were the 297 students from Minnan Normal University, Fuzhou University of Foreign Studies, and Fuzhou University who watched the live broadcast on the e-commerce platform Taobao (Tmall Live). The researcher used a researcher-made survey questionnaire as the main instrument in data gathering

Keywords: e-commerce live broadcast, online purchase intention, unique technical features, live broadcast service quality, anchors selection strategy, marketing strategy
Adolescents and College Students' Perceptions of the TikTok Platform: An Empirical Study in Vietnam
Authors: NGUYEN Tri Huu , HO Nuong Nguyet , NGUYEN Luan Trong
Published: September 2023

The appearance and development of social networks altered how people communicated and socialized, which has gradually infiltrated the educational environment. E-learning through social networking platforms and online apps is gaining popularity. The young are the most likely to respond dramatically to their presence on social networking platforms, especially the Tiktok app. This study concentrates on teenagers and the young who use TikTok as an educational instrument, which contains short clips with a range of length from 15 to 60 seconds yet is very engaging, imaginative, and creative. The sample of 686 observations utilised convenience sampling from Vietnamese educational institutions such as high schools, colleges, and universities. The findings revealed some noticeable evaluations from respondents about this app. Firstly, most participants prefer using TikTok to other platforms for watching and posting short videos. Secondly, the bulk of people agreed that TikTok is an effective platform for supporting education, especially language learning. Thirdly, they emphasie the benefits TikTok offers regarding being educational, creative, not boring, engaging content creators, and learning a lot. Fourthly, many respondents believe that TikTok will keep growing successfully in the future. The outcomes of the study are beneficial for educational planners and academics in search of innovative teaching techniques that can be implemented in the classroom and used in future studies.

Keywords: TikTok, social networking, E-learning.
Analytical procedures of financial audit at Big Four audit firms in Vietnam
Authors: Nguyen Phuong Thi
Published: September 2023

One of the methods that is highly appreciated for its effectiveness in auditing financial statements and also quite important and popular in audits is the application of analytical procedures in the audit process. In this article, the group of authors use qualitative methods to investigate the perception of Big Four auditors on the importance of analytical procedures in financial audit and how Big Four auditors apply analytical procedures in audit practice. The results indicate that analytical procedures were important and necessary in an audit engagement at Big Four. Big Four employees actively apply these procedures in all three phases of an audit. Managers mainly perform analytical procedures when planning and partners and seniors might involve. The auditors utilize trend analysis, ratio analysis and reasonable testing in planning state, however, trend analysis is the major technique preferred. During the stage of performing the audit, the application of analytical procedures performed depended on the auditors' experience, audit clients size and characteristics. Big Four auditors use simple analytical techniques such as trend analysis, ratios analysis, and reasonable analysis, but do not use advanced techniques such as regression analysis. The analysis at reviewing stage is performed by team leader, executives, partners. At this stage, the auditors apply the analytical procedures to gain the explanations related to the whole financial statement rather than those related to individual items.

Keywords: Big Four; auditors; analytical procedures; analytical techniques; audit work
Factors Affecting Audit Quality: Evidence from Jordan
Authors: Nofal Salih
Published: September 2023

This study aims to recognize the factors that affecting the quality of audit from the perception of external auditors in Jordan, namely (professional competence and auditor qualification, auditor availability and independence, auditor professional experience, auditor aware of the importance of audit quality, audit fees), by analyzing the study variables and showing their impact on the audit quality and making recommendations on raising the level of performance of the profession. To achieve the objectives of the study and test its hypotheses a questionnaire will be designed after reference to previous studies, International Auditing Standards, and legal accounting regulatory Law No. 73 of 2003.

Keywords: audit quality, professionalism, availability, professional experience, audit fees.
How Work From Home and Knowledge Sharing on Job Satisfaction Mediated By Work-Family Conflict: Study in One of the Central Government Agencies in Indonesia
Authors: Aulya Rizki , Rohman Abdul
Published: September 2023

The purpose of this research is to analyze the influence of work from home on job satisfaction, the influence of knowledge sharing on job satisfaction, the influence of work from home on work-family conflict, the influence of work-family conflict on job satisfaction, and the influence of work-family conflict on knowledge sharing. The population in this study is one of the Central Government Institutions of Indonesia in sector II, located in Jakarta, and the sampling technique used is purposive sampling. This research employs quantitative analysis, and the data source used is primary data collected through a questionnaire. The data is analyzed using SmartPLS to obtain the structural equation model (SEM) and test the hypotheses. The results of the analysis indicate that work from home does not have a significant influence on job satisfaction. However, knowledge sharing has a significant influence on job satisfaction. The analysis also shows that work from home significantly affects work-family conflict, and work-family conflict significantly affects job satisfaction. Furthermore, knowledge sharing does not have a significant influence on work-family conflict.

Keywords: Work From Home, Knowledge Sharing, Work-Family Conflict and Job Satisfaction.
Promoting an E-Learning Culture: Exploratory Study of Different Organizational Approaches
Authors: SOUDANE Jalila AIT , EL HAMMOUCHI Maryeme
Published: September 2023

Investing in human capital represents a substantial lever for meeting the challenges organizations face, particularly the exacerbation of competition, competitiveness, and performance. (Baujard, 2006). In this landscape, the knowledge and skills of employees represent a fundamental axis for maintaining competitive advantage and pursuing growth. Consequently, the implementation of training programs would enable organizations to develop the potential of their human capital and engage in a dynamic of innovation. (El Yaacoubi and Bennani, 2022) However, in an increasingly connected world, it's time for private and public organizations to embrace digital transformation. (Bellalij, 2021). This is the case for public and private organizations, where the advent of information and communication technologies has completely overturned their managerial context and human capital management practices (Niniss, 2022). Training is one of the practices that should be part of this movement and adopt a strategy of continuous innovation.

Keywords: E-learning, E-learning culture, Organizational approaches, Promoting, Qualitative study
The Effect of Financial Risk, Operational Risk, Lending Interest Rate, Firm Size, and Inflation on Financial Distress in Ten Telecommunications Companies with the Largest Market Capitalization in Asia 2013-2022 Period
Authors: Akhmad Ms. Widya
Published: September 2023

This study intends to analyze the effect of financial risk, operational risk, lending interest rate, company size, and inflation on financial distress in 10 telecommunications companies with the largest capitalization in Asia 2013-2022 period. The research uses financial data from these 10 telecommunications companies with the largest capitalization in Asia over the past 10 years. This research adopts a quantitative approach with secondary data listed on the Asian stock exchanges. The analysis method used is logistic regression, which is employed to examine the relationship between independent variables and the dependent variable. The research results indicate a negative correlation for lending interest rate and a positive correlation with inflation. A decrease in lending interest rate will increase the risk of financial distress for companies, as seen in the tendency for an increase in current liabilities when there is a decrease in lending interest rate. Inflation has a significant positive effect on financial distress, meaning that an increase in inflation will increase the risk of financial distress. The research results also show that financial risk, operational risk, and company size do not have a significant influence on financial distress in the largest telecommunications companies in Asia during the period 2013-2022.

Keywords: financial distress, financial risk, firm size, inflation, lending interest rate, operational risk, Telecommunications Company.
A comparative analysis of the interrelation between the evolution in the structure of Armenian churches of the 4th-14th centuries and the three-layer “midis” masonry
Authors: Azatyan Karen , Azatyan Ruben , Manukian Anzhelika , Melikyan Mane
Published: October 2023

The article touches upon the interrelations between the structural elements and the building structure in architecture. The aim of the work is to generalize the peculiarities of “midis” masonry formation and to reveal its influence in the evolution process of the structure of Armenian medieval churches by a comparative analysis of different characteristics. In the work: the development of three-layer “midis” masonry was systematized, the phenomenon of shell structure and spatial integrity in the churches of the 4th-14th centuries was highlighted, the tendencies of evolution of the masonry monolithic nature and church structure integrity were revealed by a comparative analysis of volumetric and planning characteristics of different churches. The results allowed to formulate a certain sequence of interactions in different characteristics, which confirmed the relationship between the evolution of the masonry and the structure of the churches: the evolution of “midis” masonry led to the structural monolithic nature of the walls and the forms derived from it, which in turn led to the integrity of the stone building structure. The results can be useful in further research covering structural-compositional interrelations, including both heritage and modern architecture studies.
Architect Hans Poelzig: a project for Ukraine
Authors: Smolenska Svitlana , Nägelke Hans-Dieter
Published: October 2023

The paper examines one of the fragments of the creative heritage of the famous German architect Hans Poelzig: his competition project of the State Ukrainian Theatre of Mass Musical Action for 4000 seats for Kharkiv. The project is viewed through the prism of little-known competitive events of 1930, which makes it possible to decipher its architectural, compositional, urbanistic and functional ideas, to reveal its symbolism. The study is based on the architect’s original drawings preserved in the archive, primary sources of the early 1930s, biographical and critical works of other authors dedicated to the nominees of the Kharkiv competition, as well as on a comparative and meaningful analysis of architectural graphics and textual documentation.
The comparative performance analysis of selected relational database systems
Authors: Schab Szymon
Published: September 2023

The objective of this study was to carry out a performance analysis of the following database systems: MySQL, PostgreSQL and Microsoft SQL Server. For this purpose scripts were used to measure execution times of selecting, updating and inserting data. Furthermore, three data sets were utilized consisting of 100, 1000 and 10000 rows. The experiment included nine cases depending on the query type and the data set. For each case, thirty five test trials were conducted while first five trials were ignored i.a. because of cache storage. The statistical test was performed for the results and the trials in which the DBMS achieved best times were counted. For each case best systems were acknowledged and the most efficient system of the experiment was determined along with systems for each operation type.
An Indoor Positioning System of Bluetooth AoA Using Two-Point Position-Based Uniform Linear Array
Authors: Shu Wenzhao
Published: October 2023

Bluetooth AOA study and Data processing
Codebook Design and Autoencoder-based Codeword Selection for RIS-assisted Communications
Authors: Sahu Khushboo , Sonwani Bhavesh , Shrivastava Amit Kumar , Kherani Arzad Alam
Published: October 2023

In this paper, we designed a one-bit beamforming codebook for reconfigurable intelligent surfaces (RIS). Each codeword in a codebook is a phase pattern at RIS elements that reflects the signal to a desired angle. Those codewords are computed for a specific reflection angle that maximizes the signal-to-noise ratio (SNR) at the receiver (Rx). Since multiple codewords can maximize the SNR, an algorithm to reduce the size of the codebook is proposed. It ensures that the codebook does not contain repetitive codewords. Then, a deep neural network-based codeword selection procedure is performed using an autoencoder (AE) that minimizes the bit error rate (BER) at the receiver. The proposed method shows promising results compared to existing techniques regarding BER with reduced codebook size. 
Automated Emotion Recognition Employing Wearable ECG Sensor and Deep-Learning
Authors: Sweeney-Fanelli Timothy , Imtiaz Masudul
Published: October 2023

Automated Emotion Recognition (AER) is the process of programatically identifying and classifying affective responses to stimuli through the analysis of physiological signals. AER has applications in interpersonal communications via digital mediums, human-computer interactions, third-party monitoring and surveillance, personal health and wellness, and in physical and mental health treatment settings. In this paper, we demonstrate AER using deep learning for automated feature extraction from ECG signals using a novel application of temporal convolutional neural networks (TCNN) to resolve the time-dependent nature of the biomedical signal data. We achieve classification accuracy of 97.8\% for valence, and 100.0\% for arousal, validated using 10-fold cross validation, meeting or exceeding the prior state of the art.
Mass Configuration of Heterogeneous IIoT Nodes: A Proposal and Experimental Evaluation
Authors: Saif Darius , Matrawy Ashraf
Published: October 2023

Pre-Print of a paper entitled 'A Proposal and Experimental Evaluation Towards Mass Configuration of Heterogeneous IIoT Nodes' by Darius Saif and Dr. Ashraf Matrawy.
Automatic Generation of Algebraic Representation for Physics Problems
Authors: Ghosh Krishnendu , Das Sayantan
Published: October 2023

During today’s e-learning era, students often need to opt for self-study sessions to solve word problems. Word problems are generally solved by transforming them into corresponding algebraic equations. This paper presents an approach for automatically generating such algebraic representations for any word problems in the physics domain. The current system first suggests a suitable template to generate an abstract version of the given word problem. These templates are formed with one or more equations, replacing specific values with generic variables. The motivation for choosing such templates was limiting the number of possible templates to the minimum to reduce further ambiguities. Once the templates are predicted, the values for the variables are tagged by parsing the word problems using named entity recognition (NER) based and rule-based approaches. While developing and assessing our system, we collected a database of Physics word problems and asked experts to determine their algebraic representations manually. Inconsistencies are filtered out using proper preprocessing and normalization measures. Although our system is a preliminary step towards automatically solving physics word problems, the template generation and tagging modules performed their corresponding tasks with around 70% accuracy.
HiL Platform for dq Impedance Measurement of High-frequency AC Electrical Power Distribution Systems
Authors: PENG Qilin , Yang Jiajun , guenter sandro , Buticchi Giampaolo , Tan Nadia , Lin Zezhen , Wheeler Patrick
Published: October 2023

In modern Electrical Power Distribution System (EPDS), power electronics devices are gaining more prominence. Three-phase ac/dc converters provide a fully-controlled interface between the onboard ac and dc electrical equipment. In the context of utility ac electrical power systems, impedance-based stability analysis under Synchronous Reference Frame (SRF), or dq impedance has been established as a powerful tool to evaluate stability and optimize control design. However, precise measurement of the dq impedance is challenging in practice especially for high-capacity or high ac fundamental frequency systems. In this paper, a hardware-in-the-loop (HiL) platform is proposed for measuring dq impedance. An aircraft ac EPDS bus is built with a grid forming (GFM) converter and an active front end (AFE) converter to verify the proposed scheme. A comparison is made between the HiL measurement results, the experimental results and the analytical model, validating that dq-impedance measurement with the proposed setup provides a precise and efficient solution that obviates the need for complete hardware experiments.
Demystifying Quantum Computing: A Holistic Non-Technical Overview of the NISQ Paradigm and its Opportunities and Obstacles
Authors: Shah Arnav , Pachisia Tanay
Published: October 2023

Quantum Computing is a field that is gaining recognition at a rapid rate around the world. This review shall address the unique elements of quantum computing with respect to classical computing, the current situation of quantum computing (i.e. Noisy Intermediate Scale Quantum or NISQ era computers) and the potential of such technology for the future. The review further seeks to discuss the problems that need to be overcome to attain quantum computing feasibility and the use of hybrid computing as an alternative that can derive from the benefits of the quantum world.
An Algorithm for Constructing Random Inverses of Non-Square Matrices Across Arbitrary Fields
Authors: Haidary Makoui Farshid , Gulliver Aaron , Dakhilalian Mohammad
Published: October 2023

In the realm of linear algebra, the notion of matrix inversion plays a crucial role. While the inversion of square matrices is well-known and results in a unique inverse, however, the non-square inverse matrice is not unique and in fact, the number of inverses for a non-square matrix can be as vast as q^m(n−m), where q signifies the order of the underlying field. In this paper, we embark on a journey to construct these elusive inverse matrices, harnessing the power of arbitrary fields. Arbitrary fields, including prime fields, finite fields, real fields, and complex fields. These fields find practical applications that are essential to contemporary technology. I have written 5 MATLAB programs that able to construct random inverses in different fields based on the given algorithm. 
An Attention-based Context Fusion Network for Spatiotemporal Prediction of Sea Surface Temperature
Authors: Shi Benyun , Hao Yingjian , Feng Liu , Ge Conghui , Peng Yue , He Hailun
Published: October 2023

Sea surface temperature (SST) is a fundamental parameter in the field of oceanography as it significantly influences various physical, chemical, and biological processes within the marine environment. In this study, we propose an Attention-based Context Fusion Network (ACFN) model for short-term prediction of SST based on the Operational SST and Sea Ice Analysis (OSTIA) data. The ACFN model combines an attention-based context fusion block with the Convolutional Long Short-Term Memory (ConvLSTM) model, enabling the exploration of intricate spatiotemporal correlations between the previous context state and the current input state in ConvLSTM. To assess the performance of the ACFN model,  we apply it to predict SST in the Bohai Sea over lead times spanning from 1 to 10 days. The results demonstrate that our proposed model outperforms several state-of-the-art models, i.e., ConvLSTM, PredRNN, and MoDeRNN, in terms of mean absolute error and coefficient of determination. In particular, our analysis reveals that the prediction errors near the coastal areas exhibit relatively higher values compared to those in the central Bohai Sea.
Reduce Order Modeling of the modular multilevel DC/DC converter (M2DC) for HVDC grid
Authors: Shafique Ghazala , boukhenfouf Johan , Gruson Francois , Samimi Shabab , Delarue Philippe , Le Moigne Philippe , Colas Frédéric , Merlin Michael , Guillaud Xavier
Published: October 2023

The Modular Multi-Level DC-DC Converter (M2DC) is an attractive non-isolated DC-DC converter topology for HVDC grid. In order to carry out MTDC grid stability studies, the development of reduce order models of converters is necessary. This article first presents the M2DC converter. Then, the reduce order model will be developed in the second part. The development of the control of this model will be carried out in the third part. Atlast, the comparison of the reduce order model and its control with the average arm model will be performed in the later section of the paper.
Exploring the Relationship Between Alpine Skiers’ Balance Performance and Cortical Activity Using Signal Leg Stance and Modified Hop Balance Test
Authors: Khan Haroon , Redondo Paolo Victor , Engell Håvard , Ombao Hernando , Mirtaheri Peyman
Published: October 2023

The study investigates the impact on cortical activation during Single-leg Stance (SLS) and Dual-leg Stance (DLS) and its connection to skier balance performance, utilizing functional nearinfrared spectroscopy (fNIRS). In this experiment, nine young skiers participated, performing both SLS and DLS on challenging surfaces while being monitored with fNIRS. We introduced an alpinespecific balance test called the Modified Hop Balance Test (MHBT), designed to assess the balance proficiency of skier’s ability to control the upper body’s vertical orientation during SLS. We employed a statistical model based on a functional mixed-effects framework to analyze hemodynamic response changes across various conditions. The results from the MHBT with open eyes (tests 1 and 2) revealed variations in stability between the left and right foot when moving forward, compared to lateral movements with the same foot (tests 5 and 7). Interestingly, skiers exhibited slightly better overall scores in lateral movements compared to straight-line ones, indicating their proficiency in maintaining stability during sideways skiing. SLS exhibited significantly higher cortical activation than DLS, with no significant difference observed between left and right-leg stances. It appears that tasks demanding greater motor control or higher complexity lead to increased cortical activation. For future research, a longitudinal study is needed to observe how training and corresponding neuromuscular efforts influence cortical activation over time. Furthermore, we hypothesize that as athletes improve their balance skills, the level of cortical activity will become more optimized and similar in both SLS and DLS conditions. Therefore, considering lateralized patterns of cortical activity could be valuable when interpreting postural deficiencies in cases of SLS.
Transformer-CNN Hybrid Network for Improving PET Time Of Flight Prediction
Authors: Feng Xuhui
Published: October 2023

In Positron Emission Tomography (PET) reconstruction, utilizing Time of Flight (TOF) information can significantly enhance the signal-to-noise (SNR) ratio, posing a greater challenge for the precision of TOF. To address this, we employed two distinct waveform datasets for training our developed network. One dataset comprises simulated waveform data obtained through a comprehensive simulation process established using Geant4 and GosSip. The other dataset consists of real waveform data collected from lutetium yttrium orthosilicate (LYSO) scintillators and silicon photomultiplier (SiPM) detectors placed at various positions.  Our network, a combination of Transformer and Convolutional Neural Network (CNN), was developed for predicting the TOF of coincidence events based on waveform data from PET detectors. Our network achieved average full width at half maximum (FWHM) of 189 ps, with reductions of 82 ps and 13 ps compared to constant fraction discriminator (CFD) and CNN, across multiple positions.  Additionally, there was an average bias reduction of 10.3 ps compared to CNN. We visualized the attention map, revealing the remarkable enhancement of Transformer on the rising edge of waveforms. We also demonstrated the robustness of our proposed network by including waveforms with scattered events in the real training dataset.  Data augmentation through translation and flip was investigated and resulted in an improvement of 5 ps.  Furthermore, we analyzed the characteristic differences between real and simulated waveform data, providing valuable insights for generating more realistic simulated data in the future. Our network improved the average FWHM and bias, leading to enhanced SNR and clearer imaging. Data augmentation effectively expanded the dataset and facilitated the data collection process.
Stream Concept-cognitive Computing System for Streaming Data Learning
Authors: Mi Yunlong
Published: October 2023

People can often acquire knowledge dynamically and rapidly from different types of data, yet existing incremental learning algorithms are still computationally time consuming and most of stream learning methods are mainly designed for streaming data while ignoring other types of data. Hence, this paper proposes a novel dynamic concept learning (CL) algorithm by imitating human cognitive learning processes from the perspective of brain logical cognition, which is named stream concept-cognitive computing system (streamC3S). For streamC3S, it mainly consists of three aspects: the concept space, CL process, and model update process. Moreover, considering the concept drift frequently occurs in the streaming data over time, an extended version of streamC3S (namely, streamC3SE) is also proposed in this work. Specifically, we first show the related theories for streamC3S and streamC3SE on the basis of the concept space. Then an overall framework and its corresponding algorithm are shown. Finally, experimental results on various types of datasets, including the standard machine learning datasets, streaming datasets, image datasets, and two traffic data streams, validate the effectiveness of our streamC3S and streamC3SE compared to the state-of-the-art incremental learning and stream learning algorithms. 
A Non-Iterative Design Method for Output LCL Filter with RC Damping in Grid-Connected Inverters
Authors: Mondal Bishal , Karuppaswamy B Arun
Published: October 2023

LCL filters with passive damping are widely used for grid-connected inverter (GCI) applications. This work proposes a novel non-iterative component selection procedure for the LCL filter with passive RC damping. While the primary goal of the filter is to effectively attenuate the switching frequency components of the inverter, there are several other desirable constraints that make the selection procedure challenging. In this work, eight such desirable constraints are identified from the existing literature and the proposed method meets all the identified constraints. Besides being non-iterative, the novelty of the work primarily lies in the selection of the damping resistor Rd and the ratio n in which the total shunt capacitor is split. The primary intent of Rd being to damp the resonance, a methodical approach that ensures a high impact of the resistance at the resonance frequency is proposed. The proposed approach also ascertains a minimum possible quality factor. The selection of the ratio n is leveraged as an additional degree of freedom. An analytical method to find the range for n that offers a critically flat resonance peak is proposed. A critically flat resonance peak is important for control stability. The final value of n is chosen from the available range to meet all the constraints. 
Multi-functional Metasurface as a Transmissive/Reflective FSS and an On-Air Frequency Mixer
Authors: Kumar Anand , Kongari Saikiran , Chandrakapure Yugesh , Sarkar Debdeep
Published: October 2023

In this paper a multi-functional metasurface is proposed which can work as a narrowband transmissive/reflective frequency selective surface (FSS) and an on-air frequency mixer based on its switching response. The metasurface is made up of unit cells with square and circular metallic loops connected by PIN diodes that are controlled by a biasing source. In contrast to typical wideband FSSs, the structure provides 0.55 GHz of narrow stopband (a fractional bandwidth of 22\%) at 2 GHz in the OFF state bias. The bandstop response can be adjusted by varying the reverse bias voltage. The metasurface alternates between its functionalities when in forward bias by providing a passband at the operational frequency. The structure is compact and operates as a transmissive/reflective surface under two different bias conditions (ON and OFF). The design is angularly stable and polarization-insensitive for both TE and TM polarisation. A prototype of the designed structure is developed and the measured results correlate well with the simulated responses. On-air frequency mixing for a wave propagating through the metasurface is experimentally demonstrated and effects of different parameters affecting the mixing are parametrically studied.
PIXIE: A Novel Loss Function for Binary Semantic Segmentation
Authors: Jain Vansh , Parasnis Guruprasad , Purohit Aaryan , Thekedar Saher , Chokshi Anmol , Devadkar Kailas , Bide Pramod
Published: October 2023

This paper introduces PIXIE (Penalised Pixel Intersection Error), a novel loss function aimed at improving model performance through the penalization of error pixels and alignment of the predicted mask with the ground truth mask. We explore the effectiveness of PIXIE alongside U-Net and DeepLabV3 networks. In addition to novel loss functions, this paper conducts model selection studies to understand overestimations and underestimations. We conduct a comprehensive evaluation using diverse datasets spanning medical imaging (breast tumor, COVID-19, Brain MRI) and remote sensing domains (forest fire, water bodies satellite images). Performance metrics, such as Intersection over Union (IoU), Dice Coefficient (DC), Area Error Ratio (AER), precision, and recall are quantitatively assessed. Moreover, we compare PIXIE with traditional loss functions like Jacard loss, Focal loss, and Binary crossentropy. PIXIE demonstrates comparable performance to the traditional loss functions in certain metrics and outperforms them in others, establishing itself as a leading approach in achieving exceptional results across all examined segmentation datasets. These findings represent a substantial contribution to the practical evolution of semantic segmentation in computer vision, offering essential insights into the optimization of loss functions for the development of accurate and robust models.
CroCoS-v1: Enhancing Mask Leakage and Bounding Box Localization for Real-Time Crop/Weed Instance Segmentation
Authors: Franco Robles Jesus , Aviles Mejia Jorge Eduardo , Labbani-Igbida Ouiddad
Published: October 2023

Precision agriculture brings together most innovative topics from research in the fields of vision, artificial intelligence and robotics aimed at developing sustainable and resilient solutions. In this context, crop identification is a crucial issue. This paper exposes a new algorithm to enhance real-time crop/weed instance segmentation, merging a learning-based method for instance segmentation and a feature model-based image processing strategy that relies on the vegetation characteristics of the crops. The proposed algorithm compensates for the shortcomings of each method performing independently. That is, the image processing strategy fulfils crop segmentation by generating finely refined masks; however, some weeds are segmented incorrectly. On the other hand, instance segmentation methods perform well on weeds and crops but, when inaccurate bounding boxes are present, imperfect masks are generated. The experiments are conducted in different evaluation campaigns within the ACRE international competition framework. 
Assessment and Evaluation of Student Participation and Achievement in a Circuit Theory Course
Authors: Enochoghene Samuel
Published: October 2023

Circuit theory cuts across every part of electrical engineering and is a fundamental skill for electrical engineers. However the abstractions involved can present challenges for students. In this work, a problem solving approach was employed to help students motivation and interest in class attendance.  This study looks at performances in the final examination and analyses them with a view to developing better approaches and tools for future delivery of such a course. 
AI - Assisted Learning for NVIDIA SDKs and Toolkits
Authors: Kalakonda Sujith Sai , Srikanth Chaitanya , Deepesh Gondimalla Veera , Bavana Sreevaatsav , Vamshi Bodla Krishna
Published: October 2023

This paper introduces an AI-driven language model (LLM) designed to facilitate users’ comprehension and adept usage of different NVIDIA SDKs (Software Development Kits) and toolkits. The central goal is to provide a LLM which establishes an interactive and intuitive platform that offers inclusive insights, practical illustrations, and expert direction on NVIDIA’s diverse SDKs and toolkits. Harnessing the capabilities of language models and NVIDIA’s toolkits, this study strives to streamline devel- opers’ learning process, enabling them to harness NVIDIA’s technological advancements with enhanced proficiency. 
Rethinking Number Theory, Prime Numbers as Finite Entities and the Topological Constraints on Division in a Real Number Line
Authors: Zaman Budee U
Published: October 2023

In this paper, we challenge the conventional wisdom surrounding prime numbers and their infinite nature, diverging from the Riemann hypothesis. We argue that prime numbers are, in fact, finite entities with profound implications for number theory. Our investigation reveals inherent flaws in number theory’s applicability to the real number line, which comprises an infinite continuum between whole numbers. We explore the connection to modular mathematics, highlighting the topological constraints on number division, ultimately leading to the neglect of the historical significance of whole numbers. Furthermore, we propose a novel perspective on the relationship between prime numbers and the fundamental principles of physics, particularly in the context of general relativity calculus. We assert that spacetime itself may be composed of prime number multiples of particle pairs, providing a solution to the potential consequences of forces acting with an infinite finitude through self-division. This paper challenges conventional mathematical and physical paradigms, offering a fresh perspective on the finite nature of prime numbers and its far-reaching implications for our understanding of the universe.
Control Loops Passivation Design of Weak-Grid-Tied Grid-Following Inverters for Maximum Power Transfer Capability Improvement
Authors: Zhou Weihua , Mohammed Nabil , Bahrani Behrooz
Published: October 2023

The theoretical maximum power transfer capability of the phase-locked loop (PLL)-based grid-following inverters can be limited under weak-grid conditions due to the non passivity of control loops. This article aims to reveal the passivity violation mechanism and develop passivity oriented feed-forward control to cancel out the negative effects of inner current control and PLL on low-frequency passivity. To this end, the contributions of these control loops and the mutual interactions among individual control loops to inverter terminal admittance are identified using the admittance decomposition technique, based on which the nonpassivity effect of each control loop is canceled out using a point of common coupling voltage feed-forward loop. The effectiveness of the presented control loops passivation method is validated by eigenvalue analysis, simulation studies, and experiments.
Improving Network Performance and Coverage Using Contract-based Incentivized V2V Communications
Authors: Saraydar Sepideh , Tabataba Foroogh , omidi mohammad javad
Published: October 2023

In recent years, there has been a significant increase in vehicles, resulting in areas that are unable to supply online connectivity, due to the lack of infrastructure development, and high construction costs. This, in turn, can cause vehicle outages. Therefore, this paper proposes a method to improve coverage using V2V communication and designing promotional contracts for relay vehicles. Relay vehicles are rewarded according to the contract, and the aim of this system model is to select the appropriate relay, allocate power, determine the optimal amount of data to transmit, evaluate of the relay reward, and ultimately maximize the utility of the base station. The paper considers halfduplex (HD) and full-duplex (FD) relays separately. However, optimization problems are NP-hard problems, and to solve this issue, the paper uses successive convex approximation and Taylor expansion to approximate the problem. Additionally, the paper presents an algorithm for relay selection using a simulated annealing algorithm. The simulation results examine the amount of data provided by two models, rewards and objective functions, and the results show that the FD model outperforms the HD one. Furthermore, the system is extended and solved for multi target and multi relay vehicles.
Characterization of Commercial QKD Systems for Multicore Fiber-Based Hybrid Networks
Authors: Fritsch Samuel , Dugre Joshua , Mohan R. Krishna
Published: October 2023

The feasibility of a quantum-classical hybrid network using multicore fiber is explored and key performance metrics of the quantum channel with respect to co-propagating classical light are examined. Multiple commercial time bin quantum key distribution systems from ID Quantique are characterized using direct injection techniques to determine optimal operational parameters for the classical optical channels in order to minimize the quantum bit error rate and maximize secret key generation. A phenomenological model that determines the expected quantum bit error rate for a wide range of injected input wavelengths and powers is utilized to evaluate the quantum key distribution system performance. Analysis shows that the performance limitations exhibited by the tested commercial quantum key distribution systems in a hybrid network based on multicore fiber could be overcome by a strategic choice of the classical channel parameters. 
Analyzing and Comparing the Brain Activity of Alzheimer's Patients with Healthy Subjects
Authors: Metai Aarav
Published: October 2023

Alzheimer’s Disease has been a long standing mental disorder that we have gained a lot of knowledge about. However, no matter how much we have learned, we still are yet to discover a magnitude more about the disease. Alzheimer’s disease is a progressive neurological disorder characterized by cognitive decline, memory loss, and behavioral changes. It is the most common cause of dementia, impacting a person’s ability to perform daily tasks and ultimately affecting their quality of life. We can study this using brainwaves. The 5 types of brainwaves each correlate to a different type of mental activity, which gives more information on various diseases like Alzheimer’s. Through this paper, we hope to find common trends on the brainwaves of an Alzheimer’s patient compared to a control subject with no mental disorders. All patterns will be tried to conclude to the reason behind that data. The Muse 2 Headband was used to collect the recordings of brainwave data in this study. Recordings of two subjects (one of which is the control) in two different conditions (active and resting) will be tested. The EEG data will then be compiled by MATLAB and put on a Spectral Plot to analyze the Electrical Brain Responses. The results show that readings in all brain waves other than Beta and Gamma were inactive and similar between both subjects. Beta and Gamma wave analysis proves that the Alzheimer’s Disease subject had lower activations in their brain due to a higher log of frequency power in those waves.