Reviewerly/exHarmony huggingface dataset:
Evaluation of Lecturers Professional Competency of Students’ Assessment in Tertiary Institutions in Zamfara State

The aim of this study is to examine the lecturers’ assessment competency of learning outcomes in tertiary institutions in Zamfara State. The Survey design was adopted for this study. The population of the study comprised all the 954 academic staff (lecturers/ instructors) in the three (3) Federal Government owned tertiary institutions in Zamfara State, which include Federal University Gusau (FUGUS), Federal College of Education (Technical) Gusau and Federal Polytechnics Kaura Namoda. Federal University Gusau (FUGUS), Federal College of Education (Technical) Gusau and Federal Polytechnics Kaura Namoda have 315, 220 and 419 academic staff respectively. The sample size of the study is 278 academic staff. Proportionate stratified random sampling technique was used to select two hundred and seventy-eight (278) academic staff from the three (3) Federal Government owned tertiary institutions in Zamfara State. The instrument used for data collection is a researcher designed questionnaire termed “Lecturers’ Competency of Assessment of Learning Questionnaire (LCALQ)”. The Data collected were analyzed using both descriptive and inferential statistics of Analysis of Variance, t-test, Standard Deviation and Weighted Mean. The results showed that lecturers’ professional competence in assessment in Zamfara state tertiary institution are adequate in some aspect of assessment which includes competence in choosing assessment methods appropriate for instructional decisions, administering, scoring, and interpreting the results of assessment methods, using assessment results in making decisions about individual students, developing valid students grading procedures, communicating assessment results to students’ parents and recognizing unethical, illegal, and otherwise inappropriate assessment methods, except in the area of developing assessment methods that is inadequate. It was further concluded that no significant difference exists in the level of competence of male and female lecturers in assessment of students’ outcomes, but revealed significance difference across the three federal own tertiary institutions in Zamfara state. Based on these findings, it was recommended that lecturers in tertiary institution should be train on all the components of assessments practices that will benefit undergraduate students learning outcomes.
Kubernetes and Docker Load Balancing: State-of-the-Art Techniques and Challenges

In the ever-evolving landscape of container orchestration, Kubernetes stands out as a leading platform, empowering organizations to deploy, scale, and manage containerized applications seamlessly. This survey paper explores the critical domain of load balancing within Kubernetes, investigating state-of-the-art techniques and the associated challenges. Container-based virtualization has revolutionized cloud computing, and Kubernetes, as a key orchestrator, plays a central role in optimizing resource allocation, scalability, and application performance. Load balancing, a fundamental aspect of distributed systems, becomes paramount in ensuring efficient utilization of resources and maintaining high availability. The study focuses on contemporary methods for achieving effect-ive load balancing on containers, with a specific examination of Docker Swarm and Kubernetes—prominent systems for container deployment and management. The paper illustrates how Docker Swarm and Kubernetes can leverage load bal-ancing techniques to optimize traffic distribution. Load balancing algorithms are introduced and implemented in both Docker and Kubernetes, and their outcomes are systematically compared. The paper concludes by highlighting why Kuber-netes is often the preferred choice over Docker Swarm for load balancing pur-poses.This paper provides a comprehensive overview of the current state-of-the-art techniques employed in Kubernetes load balancing. Challenges inherent to Docker load balancing are addressed, encompassing is-sues related to the dynamic nature of containerized workloads, varying application demands, and the need for real-time adaptability. The survey also explores the role of load balancing in enhancing the scalability and overall performance of applications within Kubernetes clusters. In conclusion, this survey consolidates the current knowledge on Docker and Kubernetes load balancing, offering a state-of-the-art analysis while identifying challenges that pave the way for future research and advancements in the realm of container orchestration and distributed systems.
The impact of ethical leadership and stakeholder orientation on employee CSR participation: A conceptual study

Corporate social responsibility programmes have become the norm today, with most large companies creating separate teams and making significant investments specifically for this purpose. Companies can strategize, allocate funds, and make detailed plans, but it would all be fruitless if employees - one of the critical stakeholders - did not contribute to these activities. After all, the onus of CSR does not lie solely on the leadership, rather employees need to be equally invested in becoming part of the organizational culture. The objective of this study is to devise a framework showing the drivers of employee participation in CSR activities, drawing on the three constructs of ethical leadership, stakeholder orientation, and employee identification.
Appearance and Pose-Conditioned Human photograph generation using Deformable GANs

In this study, we address the challenge of generating images of individuals based on pose and appearance data. Specifically, we take an image, xa, of an individual and a target pose, P (xb), extracted from another image, xb. We then generate a new image of the same individual in the target pose, P (xb), while preserving the visual details from xa. To manage pixel-to-pixel misalignments caused by pose differences between P (xa) and P (xb), we incorporate deformable skip connections in our Generative Adversarial Network’s generator. Additionally, we propose a nearest-neighbour loss as an alternative to the standard L1 and L2 losses to match the texture of the generated image with the target image. Our approach demonstrates competitive quantitative and qualitative results using standard datasets and protocols recently proposed for this task. We also carry out a comprehensive evaluation using off-the-shelf person-identification (Re-id) systems trained with person-generation-based augmented data, a key application for this task. Our experiments reveal that our Deformable GANs can significantly boost Re-id accuracy, surpassing data-augmentation techniques specifically trained using Re-identification losses. index Terms—Conditional GAN, Image Generation, Deformable Objects, Human Pose.
Influencer’s era–the role of experts in the digital world. Do we still need their forecasts and advice?

Influencer’s era–the role of experts in the digital world. Do we still need their forecasts and advice? We live in an information society. Estimates show that by 2025 global data production will increase to over 180 zettabytes. Along with the dissemination of the Internet, the development of digital communication and the reduction of digital exclusion, we are facing a serious crisis of expert culture. Over the years, it is experts who played an important role in society, today we ask where the border between professionals and specialists with specific knowledge, and experts-soremen, who gather hundreds of thousands of thousands of users in front of the screens of mobile devices in front of the screens of mobile devices in front of the screens of mobile devices. In the course of consideration of the above issues, the authors decided to develop a new expert definition based on a review of literature together with the use of the syncretic method and the original research model. The latter was successfully used in previous studies. As part of the considerations on the indicated issues, the authors focus on four key phenomena: Influencer marketing development–as a new variety of the so -called expert sector; virtual exhibitionism in the context of surveillance capitalism; functioning of the expert sector in the Bigdata era; The role of experts- futurists reaching for the models of forecasting the future. Is there still room for experts in the thicket of data? The answer to this question is the key to defining who the expert of the future will be.
Analysis of International Law Regarding Technological Advancements and Cybersecurity in Indonesia

The progress of technology and its applications always has various implications, both for the order of social life, the development of the business world, and the advancement of moral, ethical, and legal values. The following will provide an overview of some technologies considered capable of transforming life globally in all its dimensions. Through multimedia technology, telecommunications have become highly advanced, encompassing basic telecommunications and including other value-added technologies. The widespread penetration of the internet, if not used wisely, can give rise to cybercrimes, a term used to refer to crimes committed in the virtual world or cyberspace. Cybercrime is considered a more advanced development of computer crime. Crimes in the field of information technology are relatively new compared to conventional forms of crime. Information technology crimes emerged concurrently with the advent of the information technology revolution. Additionally, it is characterized by social interactions that minimize physical presence, marking another feature of the information technology revolution. Law enforcement's efforts to counter cybercrime are heavily affected by existing legislation; several laws related to information technology, especially crimes associated with the internet, are regulated under national regulations.
More than data repositories: perceived information needs for the development of social sciences and humanities research infrastructures

Introduction. The digitalization of social sciences and humanities research necessitates research infrastructures. However, this transformation is still incipient, highlighting the need to better understand how to successfully support data-intensive research. Method. Starting from a case study of building a national infrastructure for conducting data-intensive research, this study aims to understand the information needs of digital researchers regarding the facility and explore the importance of evaluation in its development. Analysis. Thirteen semi-structured interviews with social sciences and humanities scholars and computer and data scientists processed through a thematic analysis revealed three themes (developing a research infrastructure, needs and expectations of the research infrastructure, and an approach to user feedback and user interactions). Results. Findings reveal that developing an infrastructure for conducting data-intensive research is a complicated task influenced by contrasting information needs between social sciences and humanities scholars and computer and data scientists, such as the demand for increased support of the former. Findings also highlight the limited role of evaluation in its creation. Conclusions. The development of infrastructures for conducting data-intensive research requires further discussion that particularly considers the disciplinary differences between social sciences and humanities scholars and computer and data scientists. Suggestions on how to better design this kind of facilities are also raised.
MENINGKATKAN KETERAMPILAN BERBICARA BAHASA INGGRIS SISWA MENGGUNAKAN MODEL PEMBELAJARAN RUNNING DICTATION

This research aims to improve students' speaking skills using the Running Dictation learning model. This research was motivated by problems that had been discovered from the results of a preliminary study in the learning process when students spoke English. That the students' speaking skills do not meet the KKM set by the school, namely 75. The research method used is classroom action research (PTK) with three cycles in which each cycle contains two actions. The subjects of this research were 25 class VI students at MI Integrated Ar-Rifqi. The data collection techniques used are performance tests and observation. The speaking skills of class VI MI Integrated Ar-Rifqi students before being given action achieved 32% classical completeness in the poor category. After taking action in cycle I, an average score of 66 was obtained with classical completeness of 54%, in cycle II there was an increase with an average score of 74 with classical completeness of 71% and in cycle III the score was obtained. an average of 81 with a classical completion score of 84%. Based on classical completeness, overall this research has reached ≥75% of the number of students who achieved the KKM, namely 84%. Thus, it shows that students' speaking skills after implementing the Running Dictation model in English learning have improved.
The Effect of Peers and Parents’ Economy on the Interest of Students in Class XII SMA Negeri 2 Semendawai Barat to Continue to Higher Education

This study aims to determine: (1) the influence of peers on interest in continuing to higher education; (2) parents’ economic influence on interest in continuing to higher education; (3) the influence of peers and the economy of parents together on the interests of class XII students of SMA Negeri 2 Semendawai Barat Continuing to Higher Education. The population in this study were class XII students at SMA Negeri 2 Semendawai Barat for the 2022/2023 academic year. The sample in this study amounted to 83 students with probability sampling technique. Data collection techniques using a questionnaire. The data analysis technique in this research is prerequisite test and hypothesis test. The results of this study are: (1) The positive and significant influence of peers on the interest of class XII students at SMA Negeri 2 Semendawai Barat to continue higher education for the 2022/2023 academic year. This is indicated by a t-score of 8.255, a regression coefficient of 0.693, and a significance value of 0.000. Based on these conclusions, it can be said that the better the peers, the greater the interest in continuing to higher education. (2) The positive and significant financial impact on parents’ interest in continuing higher education in class XII students of SMA Negeri 2 Semendawai Barat for the 2022/2023 academic year.
Management of Library Facilities and Infrastructure in Increasing Students’ Interest in Reading at State Vocational High School 1 Lais Musi Banyuasin

This research describes how to manage the Library Sarpras in increasing students’ interest in reading. This study uses qualitative data, namely data expressed in words or symbols which are separated according to categories to draw conclusions. This research is planned to be carried out from July to November 2022. At SMK Negeri 1 Lais it is related to the problem of management of facilities and infrastructure in the library and the problem of reading interest in the library. With data collection techniques by observation, interview and documentation. The result of the research is that the management of library facilities in increasing students’ interest in reading at SMK Negeri 1 Lais Musi Banyuasin is by carrying out reading habituation program activities in the library, diligently visiting the library to read or borrow library materials.
Encryption and enhance medical image using hybrid transform (Ã-module and partial fuzzy Ȟ-transform)

This research provides a novel application for fuzzy partial differential equations in the biomedical and engineering sectors. To create this program, we multiplied the Ã-module by the fuzzy partial F-transform, which yielded a new transform that was then used as a filter in image processing. Around 6 percent of all cancer cases in adults are caused by people under 20, and most cancers begin as acute interstitial pneumonia. In recent years, many oncologists have used mathematical models to draw conclusions and make forecasts. This is by experimental biological models. Based on the newly proposed rational valued cyclic group characters and partial fuzzy transformation, this study proposes a novel method for image processing of diseased cells, which involves solving such concepts as encoding and differentiating parameters, optimizing radiographic images, and converting the idea into a filter. Radiographic image optimization and parameter differentiation were also part of the study. It was shown that the suggested transformation provided much higher levels of intelligibility than the fuzzy partial Laplace transform analysis and categorization of how a patient’s illness trajectory affects their responsiveness to treatment.
Integration of cloud computing and database management systems: A comprehensive review

Cloud computing has emerged as a transformative technology, revolutionizing the way businesses store, process, and manage data. This paper provides a comprehensive review of the integration between cloud computing and database management systems (DBMS). It explores the synergies, challenges, and opportunities that arise when these two technologies converge, offering insights into the current state of the field and future trends.
Medical images utilization for significant data hiding based on machine learning

This paper uses a machine-learning algorithm to suggest a reliable watermarking approach. The watermarked image propagation through the download physical layer (PhyLyr) of WiMAX standards is simulated in this work (WiMAX is based on the IEEE suite of standards 802.16). By downloading the Physical Layer (PhyLyr) through OFDM, transform coefficients of the host image (Hosting-Image) can be embedded there. Data associated with watermarks are initially encrypted. In a medical image, Support Vector Networks (SVN) are used to classify regions of interest (ROI) and regions of no interest (Non-ROI). The findings of this manuscript revealed that greater signal-to-noise ratios might achieve a 106-bit error rate (Bit-Err-Rate), this means that SNR is exceeds 10.4 dB of SNR. The received cover image’s peak SNR (PSNR) for clinical applications is more than 37 dB.
SHA-256 Hash Function on Intel DE10 Lite FPGA

Abstract: The SHA-256 hash function is a standardized and trusted algorithm that takes a set of data and produces a unique, deterministic, and irreversible representation called a hash or digest. A component of other protocols, SHA-256 protects password storage, secures and verifies Bitcoin transactions, and authenticates internet communication. We did a thorough analysis of the hash function and a preexisting Verilog implementation at the algorithmic, architectural, and circuit levels to identify and address the bottlenecks. We propose a new SHA-256 hardware architecture that utilizes binary tree structured adder trees to speed up hash computation. The proposed design targets Intel DE10-Lite FPGA and achieves 23% increase in computation speed. In applications, this can offer faster online communication or a more secure Bitcoin network.
Subject Harmonization of Digital Biomarkers: Improved Detection of Mild Cognitive Impairment from Language Markers

Mild cognitive impairment (MCI) represents the early stage of dementia including Alzheimer's disease (AD) and is a crucial stage for therapeutic interventions and treatment. Early detection of MCI offers opportunities for early intervention and significantly benefits cohort enrichment for clinical trials. Imaging and in vivo markers in plasma and cerebrospinal fluid biomarkers have high detection performance, yet their prohibitive costs and intrusiveness demand more affordable and accessible alternatives. The recent advances in digital biomarkers, especially language markers, have shown great potential, where variables informative to MCI are derived from linguistic and/or speech and later used for predictive modeling. A major challenge in modeling language markers comes from the variability of how each person speaks. As the cohort size for language studies is usually small due to extensive data collection efforts, the variability among persons makes language markers hard to generalize to unseen subjects. In this paper, we propose a novel subject harmonization tool to address the issue of distributional differences in language markers across subjects, thus enhancing the generalization performance of machine learning models. Our empirical results show that machine learning models built on our harmonized features have improved prediction performance on unseen data. The source code and experiment scripts are available at https://github.com/illidanlab/subject_harmonization.
Exploring the Prevalence of Cybercrime in the Banking Industry in KwaZulu-Natal, South Africa

As expenditures in broadband infrastructure in developing countries have increased and barriers to internet access have decreased, this infrastructure has rapidly become a target for cybercrime. Developing countries such as South Africa, Kenya, and India have become the preferred destination for cybercriminals. As banks now rely on digital networks for their business operations, the risk of becoming a cybercrime victim has increased for both the banking industry and its clients. The paper analyses the causes of the increased rate of cybercrime in banks and determines the effectiveness of legislation in addressing the threat posed by cybercrime to the banking industry. This study utilised a qualitative research design using face-to-face interviews with ten participants who were purposively selected. The study revealed the prevalence of internal fraud within the banking industry, poor internal controls, ineffective processes and systems, banking clients’ lack of knowledge and awareness of the looming threat of cybercrime, low conviction rates for cybercriminals; and SAPS officials’ lack of skills in policing cybercrime in KwaZulu- Natal as some of the key factors that exacerbate cybercriminal activities in the banking industry. Based on the transnational character of cybercrime, it had been concluded that the majority of the banks in South Africa and many other countries are under threat of cybercrime, and therefore they need to coordinate and implement a unified effort to tackle the growing threat of cybercriminal activities in the banking industry.
Peningkatan Literasi Siswa Melalui Program Pojok Baca Oleh Kampus Mengajar 6 di Berbagai Sekolah Dasar

Developing and increasing literacy is one of the problems currently being faced. The lack of interest in literacy and interest in reading, especially among children, is caused by, among other things, excessive use of gadgets. With this problem, it is feared that there will be more and more children who have low interest in reading. This research aims to determine the increase in student literacy among children, especially elementary school students, through one of the prestigious independent campus learning (MBKM) programs, namely the Teaching Campus. This increase in literacy will be carried out through one of the work programs implemented, namely the reading corner. The method used in this research is descriptive research. The locations of this research are several elementary schools in West Nusa Tenggara province. The samples used were 5th grade elementary school students and students. The final result of this activity is an increase in reading interest and literacy levels among students at the elementary school level through the Reading Corner program.