Reviewerly/exHarmony huggingface dataset:
An Algorithm for Finding Optimal k-Core in Attribute Networks

As a structural indicator of dense subgraphs, k-core has been widely used in community search due to its concise and efficient calculation. Many community search algorithms have been expanded on the basis of k-core. However, relevant algorithms often set k values based on empirical analysis of datasets or require users to input manually. Once users are not familiar with the graph network structure, they may miss the optimal solution due to an improper k setting. Especially in attribute social networks, characterizing communities with only k-cores may lead to a lack of semantic interpretability of communities. Consequently, this article proposes a method for identifying the optimal k-core with the greatest attribute score in the attribute social network as the target community. The difficulty of the problem is that the query needs to integrate both structural and textual indicators of the community while fully considering the diversity of attribute scoring functions. To effectively reduce computational costs, we incorporate the topological characteristics of the k-core and the attribute characteristics of entities to construct a hierarchical forest. It is worth noting that we name tree nodes in a way similar to pre-order traversal and can maintain the order of all tree nodes during the forest creation process. In such an attribute forest, it is possible to quickly locate the initial solution containing all query vertices and reuse intermediate results during the process of expanding queries. We conducted effectiveness and performance experiments on multiple real datasets. As the results show, attribute scoring functions are not monotonic, and the algorithm proposed in this paper can avoid scores falling into local optima. With the help of the attribute k-core forest, the actual query time of the Advanced algorithm has improved by two orders of magnitude compared to the BaseLine algorithm. In addition, the average F1 score of our target community has increased by 2.04 times and 26.57% compared to ACQ and SFEG, respectively.
Application of Metaverse as an Immersive Teaching Tool in Engineering Technology Classrooms

Abstract Application of Metaverse as an Immersive Teaching Tool in Engineering Technology Classroom The last two years have presented an ever challenging classroom environment for both students and educators, especially when it comes to topics in engineering based on hands-on or case based learning requiring highly interactive class sessions. Online education platforms like Blackboard and Canvas have provided some level of classroom stability by providing a centralized repository for class content, delivery and administration, however whether this translates into a more engaging experience is relatively unknown, especially as classes have moved to a combination of online, hybrid, synchronous and asynchronous models. The Department of Engineering Technology and in particular the "Technology Innovations" class will leverage the metaverse environment in virtual reality (VR) and other highly immersive tools with students. Through the class we want to define a framework for education curriculum design and content delivery in a virtual and highly interactive environment. The development of the metaverse curriculum framework will aim to establish values and principles outlining the parameters for classroom methodology focused on leveraging both current and near future tools to deliver classroom education. Students will have the ability to take the course online through Blackboard and also have the ability to take the course in the metaverse using VR. The course content for both online and metaverse will be the same however the environment and the content delivery methods will be different to test out the level of engagement and knowledge transfer experienced by the student. It is expected, at the end of the course, students will have a valuable skill set in their ability to both learn, present and interact in the metaverse. Finally, as educators we will have an initial evaluation of classroom educational tools for the metaverse.
commonmeta-py now supports metadata lists

This week the commonmeta-py Python library adds an important new feature: metadata lists. With this feature commonmeta-py no longer only operates on metadata for a single scholarly work (e.g. a journal article, book, dataset, software, or blog post), but can handle lists of scholarly works.
Impact of Blockchain Technology on Supply Chain Management Efficiency and Transparency in Pakistan

&#x0D; Abstract&#x0D; Purpose: The aim of the study was to influence the impact of blockchain technology on supply chain management efficiency and transparency&#x0D; Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.&#x0D; Findings: A study on the impact of blockchain technology on supply chain management in Pakistan revealed significant improvements in efficiency and transparency. Through blockchain integration, supply chain processes experienced reduced delays and increased automation, leading to streamlined operations. Transparency was notably enhanced, with real-time tracking of goods and secure data sharing among stakeholders, mitigating risks of fraud and error. These findings suggest that adopting blockchain technology holds promise for enhancing supply chain management in Pakistan by fostering greater efficiency and transparency.&#x0D; Unique Contribution to Theory, Practice and Policy: Diffusion of innovations theory, information processing theory &amp; resource dependency theory may be used to anchor future studies on the impact of block chain technology on supply chain management efficiency and transparency. Encourage supply chain stakeholders to adopt blockchain solutions for enhanced transparency, traceability, and efficiency. Advocate for regulatory frameworks that promote the adoption of blockchain technology in supply chains while addressing concerns related to data privacy, interoperability, and standardization.&#x0D;
A Technical Review of the State-of-the-Art Methods in Aspect-Based Sentiment Analysis

With the advent and rapid advancement of text mining technology, a computer-based approach used to capture sentiment standpoints from data in textual form is increasingly becoming a promising field. Detailed information about sentiment can be provided using aspect-based sentiment analysis, which can be used in better decision-making. This study aims to study, observe, and classify previous methods used in aspect-based sentiment analysis. A systematic review is adopted as the method used to collect and review papers to achieve this research's aim. Papers focused on sentiment analysis, aspect extraction, and aspect aggregation from different academic databases such as Scopus, ScienceDirect, IEEE Explore, and Web of Science were gathered based on the inclusion and exclusion criteria of the study. The gathered papers were further reviewed to answer the stated research questions. The findings from the research show the most used methods for aspect extraction, sentiment analysis, and aspect aggregation in aspect-based sentiment analysis. This research offers a robust synthesis of evidence to guide further academic exploration in sentiment analysis.
Tin (Sn) Geochemical Mapping Based on a Fixed-Value Method: A Case Illustration in Gejiu Area, Southwest China

Geochemical maps play an important role in mineral resource exploration. There are three traditional methods for creating geochemical maps: the cumulative frequency method, the logarithmic interval method, and the Avg±k*Std (where Avg and Std are the abbreviations of average and standard deviation, and k is a multiple of Std) method. However, with the increasing scope of the study area and cumulative data, the limitations of traditional methods, which depend on the amount of data, are exposed. A fixed-value method for Sn geological mapping is proposed to overcome the limitations of traditional methods. In the fixed-value method, Sn concentrations are divided into 19 levels on 18 fixed values ranging from 1 μg/g (corresponding to the detection limit) to 1000 μg/g (corresponding to the cut-off grade of Sn in hard rocks). The 19 levels are mapped in six color tones. The first to fifth levels are the lowest background areas in blue tones, which correspond to Sn concentrations ranging from the minimum to 3.4 μg/g. The sixth to ninth levels are high background areas in yellow tones corresponding to concentrations less than 10 μg/g, the 10th to 12th are low anomaly areas in pink tones less than 28 μg/g, the 13th to 15th are high anomaly areas in red tones less than 200 μg/g (corresponding to the placer cut-off grade), the 16th to 18th in gray tones less than 1000 μg/g, and the 19th level is in black corresponding to Sn ores with Sn concentration not less than 1000 μg/g. The fixed-value method along with three traditional methods was used to contour the Sn geochemical maps in the Gejiu area in Southwest China. The illustration results of the presented fixed-value method and three traditional methods for geochemical mapping of Sn are all feasible for Sn deposit exploration in the Gejiu area, Southwest China. Compared to traditional methods, the presented fixed-value method overcomes the flaws of traditional methods and is also more meaningful in geochemistry.
STR: Secure Computation on Additive Shares Using the Share-Transform-Reveal Strategy

The rapid development of cloud computing has probably benefited each of us. However, the privacy risks brought by untrustworthy cloud servers arise the attention of more and more people and legislatures. In the last two decades, plenty of works seek to outsource various specific tasks while ensuring the security of private data. The tasks to be outsourced are countless; however, the computations involved are similar. In this paper, we construct a series of novel protocols that support the secure computation of various functions on numbers (e.g., the basic elementary functions) and matrices (e.g., the calculation of eigenvectors and eigenvalues) in arbitrary $n\geq 2$ servers. All protocols only require constant rounds of interactions and achieve the low computation complexity. Moreover, the proposed $n$-party protocols ensure the security of private data even though $n-1$ servers collude. The convolutional neural network models are utilized as the case studies to verify the protocols. The theoretical analysis and experimental results demonstrate the correctness, efficiency, and security of the proposed protocols.
Adaptive Collaboration With Training Plan Considering Role Correlation

Based on role-based collaboration (RBC), group role assignment (GRA) optimizes a team’s overall performance by assigning the most appropriate individual agents from the team’s viewpoint based on agents’ role-playing abilities. As an extension of GRA, GRA with a training plan (GRATP) deals with the impact of training on team management. Considering the correlation between roles, the training of one agent on one role also affects the performance of the agent in other roles. Moreover, in the adaptive collaboration (AC) problem, the training time also affects significantly the agent’s ability, as an agent’s ability changes over time. However, the existing GRATP models fail to consider these factors in the collaboration process. Therefore, we aim to address the role-correlation-based adaptive GRATP (RCA-GRATP) in this article. This article contributes two aspects to the literature on AC. 1) RCA-GRATP problem is abstracted based on RBC and GRA. To the best of the authors’ knowledge, this is the first article that explicitly considers role correlation in the RBC problems. 2) A comprehensive formalization of RCA-GRATP and two solving algorithms for diverse situations are proposed to solve the formalized problems. Experiments are carried out to verify the effectiveness of the proposed algorithms in diverse scenarios.
Implementation of Pseudo-Random Number Generator Using LFSR

Abstract Linear Feedback Shift Registers (LFSR) play a vital role to provide cybersecurity for the data communication system. LFSR is a shift register where the input is linear of its previous states. The most important application of LFSR is the device's ability to generate a pseudo-random sequence of values that are used in encryption and decryption to secure personal data. Moreover, LFSR is used in Cyclic Redundancy Check Calculations (CRC) which can help to detect errors and corruption in data communications as LFSR feedback values can be modified. The main objective of the research is to generate the pseudo-random sequence of values in 3-bit, 4-bit, and 8-bit using the multiple registers with XOR as different taps selection. In the research, we used D(Data) flip flops and XOR alternative taps to identify the difference in the values for different arrangements in circuit diagrams using the software Quartus. After the simulation, we test the circuit on the Field Programmable Gate Array (FPGA) board to check the generated binary random number displaying the LED "on" or in "off" state. We would deeply work on CRC and use different approaches such as Verilog or VHDL code.
Virtual Engineering Summer Camp in the age of COVID-19 Pandemic

Abstract COVID-19 pandemic greatly affected the learning experience of students. Prior to the COVID-19 pandemic, many engineering programs worldwide organized engineering summer camps for K-12 students in the summer of every year. These camps benefit K-12 students by providing a good insight into the introduction to engineering and also inducing intellectual curiosity in them through hands-on projects. Most of these sessions usually took place in a face to face setting versus the virtual mode of instruction. In summer 2020, the majority of the engineering summer camps were canceled due to the COVID-19 pandemic. The College of Engineering at the University of Texas Permian Basin organized the virtual engineering summer camp after shipping the required project kits to the students, thereby providing step-by-step instruction of performing the project virtually while also proving hands-on experience for better learning. To our knowledge, this mode of virtual summer camp that provided a hands-on experience to K-12 students was uniquely implemented in the nation by UTPB College of Engineering. This paper provides the ideas implemented to overcome several challenges, the techniques that rightly helped in conducting the virtual summer camp with hands-on experience, and methods to assess student learning.
Design and Development of Augmented Reality Engineering Expeditions - Innovations in Online Engineering Education

Abstract This paper presents a framework for the design of augmented reality expeditions in engineering education settings to motivate student learning of engineering fundamentals and careers. The impact of social distancing has been significant for students of all ages and there is a great need for additional and creative online learning resources. The engineering field has an opportunity to not only motivate and support student learning, but to do so by featuring the very innovative nature of engineering as a tool to develop those experiences. A case study regarding the development of NASA-themed aeronautics virtual tours and virtual field trips highlights the capabilities of various software technologies and offers design considerations. The three developed virtual expeditions serve as an opportunity to engage and educate high school and university students. A research plan to collect student feedback on these experiences is also presented.
Outreach and Recruitment with 3D Printing and CAD

Abstract Society has been changing faster every day to adapt to changes linked to economic, technological, environmental, and social shifts and uncertainties. In times of uncertainties, everything, including education, is affected negatively. To protect and support the education pipeline, educators, departments, and colleges should invest in recruitment and outreach activities more than ever before. For this purpose, at __________, various off-campus, on-campus, and on-line day-long programs, summer camps, certification programs, and other activities for both K-12 students and school teachers are designed and delivered around the concepts of "3D printing and Computer-Aided Design (CAD)". In this study, the activities will be presented in detail. Students' and teachers' attitudes towards the concepts and activities will be discussed. Lastly, the challenges encountered will be shared with suggested solutions.
Automating Project Team Formation with Heterogeneous Project Preferences and Skill Mix Constraints

Abstract It is well established that design team composition is a significant driver of both team member engagement and design project success. Off-the-shelf solutions are available for automating the process of forming design teams with balanced skill mix and diversity profiles. These systems have been successfully applied both at our institution and others to improve student engagement and team performance in design projects with homogenous project opportunities and skill mix requirements (i.e. when forming multiple teams of similar composition to address a common design challenge). However, it has proven challenging to apply available off-the-shelf solutions to form design teams in our Capstone Design program due to heterogeneity in both project opportunities (each project team addresses a unique design challenge) and required skill mixes (which vary by project opportunity). In this paper, we discuss the development and application of a heuristic optimization algorithm that extends the capabilities of existing off-the-shelf project team formation systems, which effectively balance team sizes and diversity profiles within teams, to incorporate students' individual project preferences and project-specific skill mix constraints. Comparing results of applying this algorithm for Capstone Design project team formation with results of applying off-the-shelf solutions for team formation in other design courses with homogenous project opportunities and skill mix requirements, we find that our algorithm satisfies project-specific skill mix constraints and effectively matches students to preferred project opportunities (consistently matching more than 5/6 of students on one of their Top 3 project choices) while offering comparable performance to off-the-shelf project team formation systems in terms of balancing team sizes and diversity profiles within teams. Consistent with findings in prior research, our data indicate that balancing the sizes and diversity of project teams favorably impacts team performance (measured by scores on course assignments) and student engagement (measured by peer evaluations). We are seeking additional insights into these phenomena by incorporating new descriptive variables such as students' project preferences in analyses of Capstone Design project team performance.
Benefits of the virtual platform for K-12 STEM Outreach

Abstract The number of students enrolling and graduating with STEM degrees in the Unites States must increase exponentially in order to meet the predicted job shortages in STEM. Perkins Peer Advisement is a grant funded program at College X committed to increasing enrollment and retention of female and nontraditional students in engineering technology programs. Program activities include professional development, mentoring, faculty development, and community outreach. Community outreach is a critical component of the program as it benefits the undergraduate students hosting the events as well as the K-12 students participating in them. Studies indicate that greater exposure to STEM at early levels contributes to narrowing the STEM gap. The COVID 19 pandemic has forced all aspects of society to transition to a virtual platform. The pandemic has forced children to stay home and has limited their physical ability to participate in field trips and lab experiments; however, today's technology allows for students to expand the opportunities accessible to them through a virtual world. This paper will focus on the transition of the program to a virtual platform and the successful expansion of the community outreach component as a result of this transition. The program offers monthly family STEM workshops at the local elementary school. In February, the program will host its annual Girl Day event in celebration of National Engineers Week. The 2020-2021 academic year was the first time these outreach events were held virtually. Although the transition presented a challenge at first, in the end there are many benefits to the virtual platform. This paper will provide a summary of the STEM Outreach activities and provide conference participants with a tool kit that can be applied at their home institutions and local communities.
Incorporating Information Literacy in MET Design Project: Year 2 Implementation

Abstract This paper describes the authors' two-year effort to introduce and apply a project-based learning (PBL) pedagogy to a fluid mechanics course in our mechanical engineering technology program (MET). The authors continue efforts begun last year; a close collaboration between the engineering and education faculty and the engineering librarian with the goal of increasing the students' information literacy and developing their MET disciplinary competency. Students were required to work in teams to design a HVAC project using information literacy skills to identify relevant engineering codes and standards, such as the ASHRAE standards and codes. The project goals align with the new ABET criterion 3 (student outcomes 1-5) and criterion 5 (curriculum, content C, D and E). Benefits, limitations, and future directions are also discussed.