Reviewerly/exHarmony huggingface dataset:
The Body in Play: Dimensions of Embodiment in Design for Play

Authors:
raw_author_name: Harun Kaygan
raw_affiliation_string: The Department of Design, Media and Educational Science, University of Southern Denmark, Denmark

Abstract: This paper offers an analysis of how design activities engage with the body in the context of teaching embodied methods, and specifically body-centric design for play. Based on the analysis, we propose an empirically grounded framework for describing the various engagements with and considerations around the body as it comes into play in coursework on the use of body-centric design methods.
A Method for Projecting Cloud Shadows Onto a Central Receiver Field to Predict Receiver Damage

Authors:
raw_author_name: Michael Wagner
raw_affiliation_string: University of Wisconsin–Madison

Abstract: This work demonstrates methods of mapping high-spatial-resolution direct normal irradiance (DNI) data from satellites, Total Sky Imagers (TSIs), and analogous data sources onto a heliostat field for characterizing the spatial and temporal variation of the incident flux on a central receiver tower during cloud transient events. The mapping methods are incorporated into an optical software module that interfaces with CoPylot–SolarPILOT’s python API– to provide computationally efficient optical simulation of the heliostat field and the solar power tower. Eventually, this optical model will be incorporated into optimization models whereby a plant operator can understand the effects of cloud transient events on overall power production and receiver lifetime due to creep-fatigue damage and therefore make better informed decisions about receiver shutdown events. By more accurately modelling the effects of cloud events on receiver flux maps, this work may determine the magnitude and frequency of thermal cycling on receiver tubes and panels using actual or realistic cloud shapes instead of averaged DNI values–which may undercount the total cycle number. This work may also prevent unnecessary plant shutdowns due to overly precautionary control strategies and characterize the relative impact of various cloud types on receiver life. We plan to eventually integrate this methodology into the System Advisor Model (SAM) to improve performance model accuracy during periods of cloudiness. In this paper, we demonstrate generating DNI maps and mapping them to a solar field in CoPylot using 10 m resolution data from publicly available Sentinel-2 satellite data over the Crescent Dunes plant.
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective  State Spaces

Authors:
raw_author_name: Tsepa, Oleksii
raw_author_name: Ma, Jun

Abstract: Attention mechanisms have been widely used to capture long-range dependencies among nodes in Graph Transformers. Bottlenecked by the quadratic computational cost, attention mechanisms fail to scale in large graphs. Recent improvements in computational efficiency are mainly achieved by attention sparsification with random or heuristic-based graph subsampling, which falls short in data-dependent context reasoning. State space models (SSMs), such as Mamba, have gained prominence for their effectiveness and efficiency in modeling long-range dependencies in sequential data. However, adapting SSMs to non-sequential graph data presents a notable challenge. In this work, we introduce Graph-Mamba, the first attempt to enhance long-range context modeling in graph networks by integrating a Mamba block with the input-dependent node selection mechanism. Specifically, we formulate graph-centric node prioritization and permutation strategies to enhance context-aware reasoning, leading to a substantial improvement in predictive performance. Extensive experiments on ten benchmark datasets demonstrate that Graph-Mamba outperforms state-of-the-art methods in long-range graph prediction tasks, with a fraction of the computational cost in both FLOPs and GPU memory consumption. The code and models are publicly available at https://github.com/bowang-lab/Graph-Mamba.
Structural constraints on the emergence of oscillations in multi-population neural networks

Authors:
raw_author_name: Jie Zang
raw_affiliation_string: Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden; School of Mathematics, South China University of Technology, Guangdong, China
raw_author_name: Arvind Kumar
raw_affiliation_string: Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden

Abstract: Oscillations arise in many real-world systems and are associated with both functional and dysfunctional states. Whether a network can oscillate can be estimated if we know the strength of interaction between nodes. But in real-world networks (in particular in biological networks) it is usually not possible to know the exact connection weights. Therefore, it is important to determine the structural properties of a network necessary to generate oscillations. Here, we provide a proof that uses dynamical system theory to prove that an odd number of inhibitory nodes and strong enough connections are necessary to generate oscillations in a single cycle threshold-linear network. We illustrate these analytical results in a biologically plausible network with either firing-rate based or spiking neurons. Our work provides structural properties necessary to generate oscillations in a network. We use this knowledge to reconcile recent experimental findings about oscillations in basal ganglia with classical findings.
Decoding Sentiments: Virtue or Vice through Multilingual Paragraph Analysis

Authors:
raw_author_name: None Veena M V
raw_affiliation_string: Global Academy of Technology, Bangalore, India

Abstract: This work provides a comprehensive overview of recent developments in sentiment analysis methodologies. It explores innovative approaches, including the integration of rule-based sentiment dictionaries, machine learning techniques, and deep learning solutions for financial sentiment analysis. Emphasis is placed on key preprocessing steps such as tokenization, lowercasing, stop words removal, and punctuation elimination. Feature extraction techniques like Bag-of-Words, Word2Vec, and TF-IDF are discussed, highlighting their roles in representing textual information. The abstract delves into model selection, covering traditional machine learning models like Naive Bayes, Support Vector Machines, and Random Forests, as well as deep learning models such as Recurrent Neural Networks, Long Short-Term Memory networks, and BERT. The abstract explains these algorithms in detail, emphasizing their application in sentiment analysis. Training the model through supervised learning and evaluating its performance using metrics like accuracy, precision, recall, and F1 score are outlined. Additionally, a structured approach to paraphrasing is introduced, underlining its significance in creating meaningful representations of text.
Stakeholders’ Perceptions on EFL Teacher Professionalism: A Phenomenological Study at a Bachelor Programme in Nepal

Authors:
raw_author_name: Nabaraj Neupane

Abstract: Teaching English as a foreign language (EFL) in the twenty-first century has witnessed several changes, which have sparked tremendous changes in the teachers’ standpoints and the conceptualizations of professionalism. In this context, this study explored the stakeholders’ perceptions of EFL teacher professionalism. For this, the phenomenological research design was adopted. The study site was a Bachelor's Programme on a community campus in Nepal. The informants comprised the real stakeholders of the programme that comprised three EFL teachers, nine students, two administrators, and one member of the campus management committee. To collect the informants’ lived experiences, the researcher used an unstructured interview in a naturalistic setting. The results revealed that EFL teachers’ professionalism can be measured by their roles and skills; teacher-student relationships; and teachers as administrators and change agents. This implies that EFL teachers, like the teachers of other subjects, should be loyal, committed, accountable, and responsible as the success or failure of the autonomous programmes mainly depends on the teachers.
The Influence Of Health Promotion Using Lecture Method Using Comic Media On Dental And Oral Health Knowledge In Class III Students At State Primary School 1 Pangkajene District Sidenreng Rappang

Authors:
raw_author_name: None Rezki Dirman
raw_author_name: None Utari Zulkaidah

Abstract: Introduction: Dental and oral health has a big influence on preventing cavities or caries, gingivitis, perioldolitis, and also preventing bad breath. Diseases affecting the teeth and mouth, causing complaints of pain. School-aged children 6-12 years old are the age category at risk of developing cavities or caries. Age 6-12 years is the age when milk teeth begin to replace permanent teeth. One of the causes of the prevalence of dental and oral diseases in Indonesian children is the low level of knowledge about dental and oral health. Objective: to determine the effect of health promotion using the lecture method using kolmik media on dental and oral health knowledge in class III students at Pangkajene 1 Elementary School, Sidenreng Rapang Regency. Method: This type of research is quantitative research with a research design using a pre-experimental design, namely Olne Group Pretest and Polstest. The sample used was 31 people taken using the Total Sampling technique. Results: Before being given health promotion using the lecture method using comic media with a number of 54 with poor criteria and after being given health promotion using the lecture method using comic media with a number of 80 with good criteria. There was a level of increase in knowledge, namely 26. And the significance value was using the Paired T Test. namely 0.01 &lt; 0.05 so that the null hypothesis (H0) is rejected and the alternative hypothesis (Ha) is accepted
Unconstrained Face Recognition Using Infrared Images

Authors:
raw_author_name: Anwar Ul Haq
raw_affiliation_string: Department of Electrical Engineering, Mirpur University of Science and Technology, Mirpur, AJK 10250, Pakistan

Abstract: Recently, face recognition (FR) has become an important research topic due to increase in video surveillance. However, the surveillance images may have vague non-frontal faces, especially with the unidentifiable face pose or unconstrained environment such as bad illumination and dark environment. As a result, most FR algorithms would not show good performance when they are applied on these images. On the contrary, it is common at surveillance field that only Single Sample per Person (SSPP) is available for identification. In order to resolve such issues, visible spectrum infrared images were used which can work in entirely dark condition without having any light variations. Furthermore, to effectively improve FR for both the low-quality SSPP and unidentifiable pose problem, an approach to synthesize 3D face modeling and pose variations is proposed in this paper. A 2D frontal face image is used to generate a 3D face model. Then several virtual face test images with different poses are synthesized from this model. A well-known Surveillance Camera’s Face (SCface) database is utilized to evaluate the proposed algorithm by using PCA, LDA, KPCA, KFA, RSLDA, LRPP-GRR, deep KNN and DLIB deep learning. The effectiveness of the proposed method is verified through simulations, where increase in average recognition rates up to 10%, 27.69%, 14.62%, 25.38%, 57.46%, 57.43, 37.69% and 63.28%, respectively, for SCface database as observed.
Journeying through Query Verse: A MERN-Stack Implementation for Dynamic Web-based Inquiry

Authors:
raw_author_name: Omkar Pawar

Abstract: Abstract: The recognition of the need for a senior-junior question-answer web application emerged from interactions within educational institutions. Numerous instances of juniors seeking guidance from seniors led to the realization of a gap in information dissemination. The necessity to bridge the gap between students' queries and available answers became evident, Research into existing platforms revealed a limited number of solutions, predominantly Q&amp;A websites and educational forums. Existing online platforms offer general Q&amp;A interactions but fail to cater to the unique mentorship dynamics between seniors and juniors. These platforms lack features tailored to fostering these specific relationships. The implementation of a seniorjunior question-answer web application is essential to formalize the mentorship process. Literature reviews unveiled gaps in platforms catering to such relationships, highlighting the need for a specialized solution. The proposed solution seeks to address these gaps.
Technology in community development: A comparative review of USA and African Projects

Authors:
raw_author_name: None Beatrice Adedayo Okunade
raw_author_name: None Foluke Eyitayo Adediran

Abstract: This paper conducts a comprehensive comparative review of technology-driven community development initiatives in the United States and various regions across Africa. The study aims to shed light on the diverse approaches and outcomes of projects leveraging technology to empower communities in different socio-cultural and economic contexts. The review begins by examining the landscape of community development in both the USA and Africa, emphasizing the challenges faced by urban and rural communities alike. It establishes a foundation for understanding the increasing role of technology in addressing these challenges, framing it as a dynamic and evolving field with vast potential for positive impact. Key findings from the comparative analysis are distilled, emphasizing the importance of context-specific approaches in technology-driven community development. Projects that demonstrate a nuanced understanding of local needs, cultural dynamics, and infrastructural realities exhibit greater success. The review underscores that successful implementation requires more than the transfer of technology; it demands a deep integration into the fabric of community life. The paper also touches upon overarching insights, highlighting the transformative power of technology when thoughtfully applied to community development. It acknowledges the significance of community engagement, adaptability, and a holistic understanding of local nuances as critical factors influencing project success. In concluding remarks, the paper encourages continued research and collaboration. It recognizes the ongoing journey towards harnessing technology's potential for global community empowerment and emphasizes the importance of cross-cultural partnerships, interdisciplinary collaboration, and knowledge sharing. Ultimately, the paper seeks to contribute to the ongoing discourse on technology in community development, offering insights that can inform future projects, policies, and academic pursuits in this dynamic field.
CROSS STYLE IMAGE SYNTHESIS THROUGH SEMI COUPLED DICTIONARY LEARNING AND GENERALIZED CROSS VALIDATION ALGORITHM

Authors:
raw_author_name: Sandeep Malhotra

Abstract: In various Computer vision applications for better visualization, interpretation and better recognition, we frequently want to change an image in one style into another one which is a large research area of compressive sensing. Algorithms on compressed sensing are in demand to create better reconstruction of the images while taking less computational time and requiring less storage capacity. In the present work attempts are put in the same direction and brought an algorithm which includes semi coupled dictionary learning (SCDL) model of compressed sensing with Singular Value Decomposition (SVD) based Generalized Cross Validation (GCV) algorithm. Using this algorithm one can find the different value of regularization parameters for different sizes of images and that helps to get better reconstruction of the images with ease while doing experiments on cross style image synthesis problems.
Design and Build API-Based Multistore Marketplace Using Agile Methodology

Authors:
raw_author_name: Donny Fernando
raw_affiliation_string: Serang Raya University
raw_author_name: Dentik Karyaningsih

Abstract: The business activities of a company require technology that can drive operational efficiency. Marketplaces have become one of the effective marketing channels today for promoting the company's products and services. To reach a broader market, having more than one store on a marketplace is a choice that many companies currently opt for. However, managing multiple stores on marketplaces is not an efficient management approach. This research is an applied study conducted in one startup company (profitto.co.id) that sells developing furniture components, aiming to provide the implementation of an API-based system integration solution to manage multiple stores on Tokopedia and utilizes the Scrum methodology for software development.
Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review

Authors:
raw_author_name: Seyed Shahrestani
raw_affiliation_string: School of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, Australia
raw_author_name: Chun Ruan
raw_affiliation_string: School of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, Australia

Abstract: Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.
Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks

Authors:
raw_author_name: Xinghui Li
raw_affiliation_string: Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, 518055, China

Abstract: Abstract Absolute measurement has consistently been the primary focus in the development of precision linear and angular displacement measurements. The scheme design of binary zero position codes is an important factor for absolute measurement. Designing and optimizing high-bit zero position codes with over 100 bits face considerable challenges. Simultaneously, the working parameters of zero position codes [unit code width ( b ), distance ( d ), and yaw angle ( α )] remarkably affect their post-installation performance, particularly in absolute positioning and limit code application in multi-degree-of-freedom measurement schemes. This study addresses these challenges by proposing a design method for zero position codes that considers diffraction based on generative adversarial networks and aims to explore a design with increased efficiency and accuracy as well as optimization for high-bit zero position codes. Additionally, the tolerance range of zero positioning performance for each working parameter is examined. By leveraging the adversarial network structure, this study generates the optimization of a 150-bit code and processes the tests of the zero position code by using simulation results. The following working parameter ranges for code design are recommended on the basis of theoretical and experimental results: b greater than 10 μm, d and α within 1000 μm and 3490 μrad, and avoidance of intervals with sharp changes in the full width at half maximum. The proposed code design and parameter optimization lay a solid foundation for research and engineering applications in absolute measurement field and have considerable potential for generalization and wide applicability.
Epistemic Logic Programs: A Study of Some Properties

Authors:
raw_author_name: STEFANIA COSTANTINI
raw_affiliation_string: DISIM - Università dell’Aquila, via Vetoio, L’Aquila, Italy
raw_author_name: ANDREA FORMISANO
raw_affiliation_string: DMIF - Università di Udine, via delle Scienze 206, Udine, Italy

Abstract: Abstract Epistemic logic programs (ELPs), extend answer set programming (ASP) with epistemic operators. The semantics of such programs is provided in terms of world views , which are sets of belief sets, that is, syntactically, sets of sets of atoms. Different semantic approaches propose different characterizations of world views. Recent work has introduced semantic properties that should be met by any semantics for ELPs, like the Epistemic Splitting Property , that, if satisfied, allows to modularly compute world views in a bottom-up fashion, analogously to “traditional” ASP. We analyze the possibility of changing the perspective, shifting from a bottom-up to a top-down approach to splitting. We propose a basic top-down approach, which we prove to be equivalent to the bottom-up one. We then propose an extended approach, where our new definition: (i) is provably applicable to many of the existing semantics; (ii) operates similarly to “traditional” ASP; (iii) provably coincides under any semantics with the bottom-up notion of splitting at least on the class of Epistemically Stratified Programs (which are, intuitively, those where the use of epistemic operators is stratified); (iv) better adheres to common ASP programming methodology.
Some new quantum MDS codes with large minimum distance

Authors:
raw_author_name: Lanqiang Li
raw_affiliation_string: Anhui Agricultural University
raw_author_name: Fuyin Tian
raw_affiliation_string: Anhui Agricultural University
raw_author_name: Li Liu
raw_affiliation_string: Hefei University of Technology

Abstract: Abstract The construction of quantum Maximum Distance Separable (MDS) error-correcting codes is of great significance in practical applications, as it plays a vital role in enhancing the reliability and efficiency of quantum communication and quantum computing. As a result, it remains an active research topic in the field of quantum information science. In this paper, based on generalized Reed-Solomon (GRS) codes and Hermitian construction, we construct two new classes of quantum MDS codes. Our constructed quantum MDS codes are novel in the sense that their parameters differ from all previously known codes. Furthermore, most of our codes exhibit significantly larger minimum distance compared to the existing ones of the same length.