Reviewerly/exHarmony huggingface dataset:
On Using GUI Interaction Data to Improve Text Retrieval-based Bug Localization

Authors:
raw_author_name: Junayed Mahmud
raw_affiliation_string: University of Central Florida, Orlando, Florida, USA
raw_author_name: Nadeeshan De Silva
raw_affiliation_string: William &amp; Mary, Williamsburg, Virginia, USA
raw_author_name: S M Hasan Mansur
raw_affiliation_string: George Mason University, Fairfax, Virginia, United States of America
raw_author_name: Oscar Chaparro
raw_affiliation_string: William &amp; Mary, Williamsburg, Virginia, United States of America
raw_author_name: Andrian (Andi) Marcus
raw_affiliation_string: George Mason University, Fairfax, Virginia, United States of America
raw_author_name: Kevin Moran
raw_affiliation_string: University of Central Florida, Orlando, Florida, United States of America

Abstract: One of the most important tasks related to managing bug reports is localizing the fault so that a fix can be applied. As such, prior work has aimed to automate this task of bug localization by formulating it as an information retrieval problem, where potentially buggy files are retrieved and ranked according to their textual similarity with a given bug report. However, there is often a notable semantic gap between the information contained in bug reports and identifiers or natural language contained within source code files. For user-facing software, there is currently a key source of information that could aid in bug localization, but has not been thoroughly investigated - information from the graphical user interface (GUI).
EDEFuzz: A Web API Fuzzer for Excessive Data Exposures

Authors:
raw_author_name: Lianglu Pan
raw_affiliation_string: University of Melbourne, Melbourne, Australia
raw_author_name: Shaanan Cohney
raw_affiliation_string: University of Melbourne, Melbourne, Australia
raw_author_name: Toby Murray
raw_affiliation_string: University of Melbourne, Melbourne, Australia
raw_author_name: Van-Thuan Pham
raw_affiliation_string: University of Melbourne, Melbourne, Australia

Abstract: APIs often transmit far more data to client applications than they need, and in the context of web applications, often do so over public channels. This issue, termed Excessive Data Exposure (EDE), was OWASP's third most significant API vulnerability of 2019. However, there are few automated tools---either in research or industry---to effectively find and remediate such issues. This is unsurprising as the problem lacks an explicit test oracle: the vulnerability does not manifest through explicit abnormal behaviours (e.g., program crashes or memory access violations).
Prescriptive method for fiber polarization compensation in two bases

Authors:
raw_author_name: Teodor Stromberg
raw_affiliation_string: University of Viennahttps://ror.org/03prydq77, Faculty of Physics & Vienna Doctoral School in Physics, Boltzmanngasse 5, A-1090 Vienna, Austria
raw_author_name: Peter Schiansky
raw_affiliation_string: University of Viennahttps://ror.org/03prydq77, Faculty of Physics & Vienna Doctoral School in Physics, Boltzmanngasse 5, A-1090 Vienna, Austria
raw_author_name: Philip Walther
raw_affiliation_string: University of Viennahttps://ror.org/03prydq77, Faculty of Physics & Vienna Doctoral School in Physics, Boltzmanngasse 5, A-1090 Vienna, Austria

Abstract: Single-mode optical fibers exhibit a small but non-negligible birefringence that induces random polarization rotations during light propagation. In classical interferometry these rotations give rise to polarization-induced fading of the interferometric visibility, and in fiber-based polarimetric sensors as well as quantum optics experiments, they scramble the information encoded in the polarization state. Correcting these undesired rotations is consequently an important part of many experiments and applications employing optical fibers. In this Lab Note we review an efficient method for fully compensating fiber polarization rotations for general input states. This method was not originally devised by us, but does, to the best of our knowledge, not appear in the literature, and our interactions with the community have indicated that it is not well known.
An Improved Genetic Algorithm Using Intelligent Symbolic Regression

Authors:
raw_author_name: Dr. Terrence. L Chambers
raw_affiliation_string: Mechanical Engineering Department, University of Louisiana at Lafayette

Abstract: In this paper, an optimization technique based on intelligent symbolic regression is presented.Intelligent symbolic regression methodology seeks to replace implicit functions of the original design optimization problem with an approximation model less expensive to evaluate.In order to address the issue of the high-computational cost of the implicit function evaluation, genetic programming methodology has been investigated to build approximation models of the best possible quality.The goal of genetic programming is to evolve mathematical expressions with no assumption about the structure, which is given as part of the solution.Once the symbolic regression model is available, the Genetic Algorithm, on subsequent runs, searches the inexpensive regression model for the global optimum, only rarely sampling the high-fidelity model.The efficiency of the proposed method has been tested on a set of standard optimization test problems and it was found to reduce the computational overhead by a significant amount without much loss of accuracy.Test results of optimization problems revealed that real-valued representation technique outperforms the binary representation technique.Such a representation is of particular concern for engineering applications, which motivated the present work.
Creating a Framework for Virtual Reality Learning Environment (VRLE) for Studio-Based Learning

Authors:
raw_author_name: Maizatul Hayati Mohamad Yatim
raw_affiliation_string: Faculty of Computing & Meta-Technology, Sultan Idris Education University, 35900, Tanjong Malim, Perak, Malaysia

Abstract: Higher education academics are lacking the knowledge on how to implement Design Thinking (DT) for transdisciplinary design studies that would produce Fourth Industrial Revolution Workforce Skills (4IRSkills), due to the sparsity in literature and implementation guidelines. This article discusses on the creation process of a Teaching and Learning Framework (TLF) for transdisciplinary design studies with a desktop-based Virtual Reality Learning Environment (VRLE) simulation of studio-based learning. The framework was created using a Selander’s Learning Design Sequence (LDS) with DT approach. The LDS helped the researcher to understand the processes of teaching and learning, especially on the affordances of various modes. The DT approach was used to facilitate the process of solving problems through the practice of empathy, reframing, prototyping, experimentation, testing, and redesign. A sequential explanatory mixed method was used, and the data were analyzed through inferential statistical analysis, thematic analysis and convergent coding matrix triangulation protocol. The findings indicated that the TLF with VRLE showed a positive and significant relationship with students' achievement of 4IRSkills. The TLF Design Process and Collaborative Design variables were positively correlated with students' 4IRSkills, while there was no correlation for the VRLE Representational Fidelity and Learner Interaction variables. In conclusion, the TLF with VRLE proves to be an effective and suitable method for guiding the implementation of pedagogies that teaches 4IRSkills at the tertiary level in fully online learning environments.
The Impact of Transfer Learning on AI Performance Across Domains

Authors:
raw_author_name: Md. Mafiqul Islam
raw_affiliation_string: Department of Information Science and Library Management, University of Rajshahi

Abstract: This study investigates the profound impact of transfer learning on the performance of artificial intelligence (AI) models when applied across diverse domains. Transfer learning, a machine learning technique that leverages knowledge gained from one task to improve performance on a related task, has demonstrated remarkable success in various applications. The article explores the underlying principles of transfer learning, its mechanisms, and the ways in which it enhances AI performance. The findings highlight the potential of transfer learning to facilitate knowledge transfer between domains, reduce training data requirements, and accelerate model convergence, ultimately contributing to the broader adaptability and efficiency of AI systems
Towards a more practical analysis of Newton’s rings using deep learning

Authors:
raw_author_name: Ming-Feng Lu
raw_affiliation_string: Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technologyhttps://ror.org/01skt4w74, Beijing 100081, China
raw_author_name: Jin-Min Wu
raw_affiliation_string: School of Automation, Beijing Information Science and Technology University, Beijing 100101, China
raw_author_name: Wenjie He
raw_affiliation_string: Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technologyhttps://ror.org/01skt4w74, Beijing 100081, China
raw_author_name: Feng Zhang
raw_affiliation_string: Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technologyhttps://ror.org/01skt4w74, Beijing 100081, China
raw_author_name: Ran Tao
raw_affiliation_string: Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technologyhttps://ror.org/01skt4w74, Beijing 100081, China

Abstract: As a typical form of optical fringes with a quadratic phase, Newton's ring patterns play an important role in spherical measurements and optical interferometry. A variety of methods have been used to analyze Newton's ring patterns. However, it is still rather challenging to fulfill the analysis. We present a deep-learning-based method to estimate the parameters of Newton's ring patterns and fulfill the analysis accordingly. The experimental results indicate the excellent accuracy, noise robustness, and demodulation efficiency of our method. It provides another applicable approach to analyzing Newton's ring patterns and brings insights into fringe analysis and interferometry-based measurements.
Building S-STEM scholars' knowledge and skills through technical and career-development seminars

Authors:
raw_author_name: Katerina Goseva-Popstojanova
raw_affiliation_string: West Virginia University

Abstract: Abstract This paper first presents an overview of the objectives and the accomplishments of the S-STEM ACCESS project and then focuses on a specific ACCESS program activity - the technical and career-development seminars and panels - which support ACCESS scholars' knowledge and skills development and contribute toward achieving several project objectives. The technical seminars exposed students to state-of-the-art topics and industry practices related to the rapidly evolving field of cybersecurity. The career-development seminars included topics on obtaining security clearances, understanding different cybersecurity workforce career paths, as well as on pursuing graduate degrees and research-centered careers. Since seminars and panels were open to all West Virginia University (WVU) students, they helped publicize the ACCESS program and the B.S. and Area of Emphasis (AoE) in Cybersecurity and therefore also served as a recruitment mechanism. The results of the external evaluation showed that the seminars and panels were of exceptional value to students who unanimously gave them high positive scores. Qualitative responses to the survey and focus group input revealed that students appreciated the seminars for providing opportunities to connect with professionals and peers, to learn about potential career paths, to gain the knowledge and confidence needed to successfully secure an internship position, and other benefits.
Sand Painting Generation Based on Convolutional Neural Networks

Authors:
raw_author_name: Chin-Chen Chang
raw_affiliation_string: Department of Computer Science and Information Engineering, National United University, Miaoli 36003, Taiwan

Abstract: Neural style transfer is an algorithm that transfers the style of one image to another image and converts the style of the second image while preserving its content. In this paper, we propose a style transfer approach for sand painting generation based on convolutional neural networks. The proposed approach aims to improve sand painting generation via neural style transfer, which can address the problem of blurred objects. Furthermore, it can reduce background noise caused by neural style transfers. First, we segment the main objects from the content image. Subsequently, we perform close–open filtering operations on the content image to obtain smooth images. Subsequently, we perform Sobel edge detection to process the images and obtain edge maps. Based on these edge maps and the input style image, we perform neural style transfer to generate sand painting images. Finally, we integrate the generated images to obtain the final stylized sand painting image. The results show that the proposed approach yields good visual effects from sand paintings. Moreover, the proposed approach achieves better visual effects for sand painting than the previous method.
Central Bank Digital Currency (CBDC) in Pakistan

Authors:
raw_author_name: Muhammad Amin
raw_affiliation_string: NED University of Engineering and Technology, Pakistan

Abstract: This chapter explores the implications and prospects of Central Bank digital currencies (CBDC) in Pakistan, focusing on its potential to transform the financial ecosystem. The emergence of blockchain and distributed ledger technologies has incited significant interest in digital currencies, leading central banks worldwide to research and develop CBDCs. In Pakistan, the implementation of CBDC presents opportunities for modernizing the financial infrastructure, enhancing financial inclusion, and fostering economic growth. The study employs a mixed-method approach, integrating qualitative and quantitative analyses. It examines the types of CBDCs, namely wholesale and retail, and their potential impacts on payment safety and efficiency. A thorough literature review provides insights into the multifaceted consequences of CBDCs on payment systems, monetary policy, and financial stability. Additionally, the research explores the challenges of CBDC implementation in Pakistan, including cybersecurity risks, technological limitations, and potential threats to financial stability. The findings highlight the need for comprehensive research, international collaboration, and a robust regulatory framework to mitigate risks and maximize the benefits of CBDCs. This study contributes to the ongoing discourse on digital currencies and their role in shaping the future of money and banking in emerging economies like Pakistan.
Between Partial Translation and Summary Translation in Translating the Sundanese Folklore into English

Authors:
raw_author_name: Erlina Zulkifli Mahmud
raw_affiliation_string: Department of Linguistics, Universitas Padjadjaran, Jatinangor, Indonesia
raw_author_name: Cece Sobarna
raw_affiliation_string: Department of Linguistics, Universitas Padjadjaran, Jatinangor, Indonesia

Abstract: The strategies of partial translation and summary translation are related but not exactly the same. There are some characteristics indicating each of them. This research article is about the translation of the most popular Sundanese folklore, which is written in the Sundanese language and translated into English. It deals with literary translation as the data source is folklore, and folklore is included as literary work. Using content analysis of the descriptive qualitative research method, this research aims to identify what information in the source text is partially translated and which information is summarized. The theory used is one of the pragmatic strategies given by Chesterman: the strategy of partial translation. The results show that the strategies used in identifying the missing information are partial translation, summary translation, and the combination of partial translation and summary translation. The partial translation is used to avoid repetition, eliminate very detailed information or complex information, and change explicit information into implicit information. The summary translation is used to create a short summary of information involving the key points or messages given in the source text by adopting the syntactic form of the target text based on the grammatical rules.
Cryptanalysis and improvement of quantum secure multi-party summation using single photons

Authors:
raw_author_name: Chia-Wei Tsai
raw_affiliation_string: Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, No.129, section 3, Sanmin Rd, North District, Taichung 404, Taiwan
raw_author_name: Jason Lin
raw_affiliation_string: Department of Computer Science and Engineering, National Chung Hsing University, No. 145, Xingda Rd., South District, Taichung 40227, Taiwan
raw_author_name: Chun-Wei Yang
raw_affiliation_string: Master Program for Digital Health Innovation, College of Humanities and Sciences, China Medical University, No. 100, section 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan

Abstract: Abstract A previous study [Entropy 25.4 (2023): 590] proposed a quantum secure multi-party summation protocol wherein n participants could obtain the modulo-2 summation result using single photons and single-particle operations. Owing to the absence of an entanglement state, this protocol was more practical than other quantum summation protocols that used entanglement properties. Thus, this study investigated the claim that this proposed protocol prevented the participants’ secret inputs from being disclosed. It was found that the previously proposed protocol was vulnerable to a quantum Trojan horse attack owing to the circular qubit transmission mode. Using a security loophole, this study proposed an attack strategy that allowed an outside attacker to steal any participant’s secret input without being detected by a third party and participants. In addition, a simulation experiment was conducted to demonstrate the feasibility of the proposed attack and evaluate the number of quantum Trojan horse probes that the attacker must inject into regular qubit sequences. Finally, a solution was proposed by modifying the protocol to securely prevent quantum Trojan horse attacks.
COMPARATIVE ANALYSIS OF MERN, MEAN AND MEVN STACKS IN WEB DEVELOPMENT

Authors:
raw_author_name: Sapna Gupta

Abstract: Choosing a technology stack is a critical decision that affects how software projects progress in the ever- changing field of web development. Regarding web development, a technology stack is a set of tools, frameworks, and programming languages that are utilized in the construction of an application's front end and back end. In addition to making the development process easier, these stacks provide the groundwork for the finished product's performance, scalability, and maintainability. JavaScript-based stacks are becoming serious contenders as businesses and developers search for frameworks that provide efficiency, scalability, and flexibility. Starting with a thorough examination and comparison of three popular JavaScript stacks, this research paper examines MEAN (MongoDB, Express, Angular and Node.js), MERN (MongoDB, Express, React and Node.js) and MEVN (MongoDB, Express, Vue.js and Node.js). Keywords: Web Development, MERN Stack, MEAN Stack, MEVN Stack, ReactJS, AngularJS, VueJS
VERIFYING AND ACCESSING STUDENT PROJECT APPLICATION

Authors:
raw_author_name: IJSREM Journal

Abstract: This abstract presents a conceptual overview of an application design to verify and accessing the project the student project using which maintain the information about the project present in the system that contains project documentation, report, code and so on. It is difficult to maintain and search all this information manually in an Organization as it takes lot of time to do. The proposed app aims to overcome the manual search to avoid difficulty in searching. Owing to the advancement of technology, this project offers a holistic solution to enhance the validation and approval process for project development by students. By fostering collaborations, improving communication, and facilitating efficient workflows, the app aims to elevate the quality of software development outcomes while reducing project timeline and costs. It is potential to transform how project validation is conducted makes it a valuable tool for modern software development teams and organizations.
A Closed-form Algorithm to Shadow Segmentation using a Single Image

Authors:
raw_author_name: Michael Joseph
raw_affiliation_string: University of Bridgeport
raw_author_name: Khaled Elleithy
raw_affiliation_string: University of Bridgeport

Abstract: Abstract Abstract—The presence of shadow in natural scenes continue to pose a challenge to computer vision algorithms. While there have been many proposed approaches to detect and segment shadow in natural scenes, these methods fail to do so in real-time without requiring a priori information. This paper presents a model that can decompose an image into the product of an illumination component L and a reflectance component R and use the reflectance component to segment the shadow region, all in real-time. This is done by exploiting the fact that light intensity has less effect on the reflectance of an image and by assuming there is a single point light source. Our method is highly effective in detecting shadows in an image with a surface material that exhibits both specular and diffuse reflectance properties.
LifeWatch ERIC: papers collection on original datasets and new e-services for the biodiversity and ecosystems’ scientific community

Authors:
raw_author_name: Christos Arvanitidis
raw_affiliation_string: Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Herakleion, Greece Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research Herakleion Greece.; LifeWatch ERIC, Seville, Spain LifeWatch ERIC Seville Spain.
raw_author_name: Alberto Basset
raw_affiliation_string: LifeWatch ERIC, Lecce, Italy LifeWatch ERIC Lecce Italy.; University of Salento, Lecce, Italy University of Salento Lecce Italy.
raw_author_name: Wouter Los
raw_affiliation_string: University of Amsterdam, Amsterdam, Netherlands University of Amsterdam Amsterdam Netherlands.

Abstract: Papers including articles that are produced because of the activities of LifeWatch ERIC, in the context of its second implementation period (2022 - 2026) and through the implementation of its new Strategic Working Plan, are published in this special collection. The articles include data papers, papers describing the development and functioning of analytical services and papers describing any other research outcome, produced either by LifeWatch ERIC or by any collaboration with any other ERIC, Research Infrastructure, global aggregator or other legal entity.