Reviewerly/exHarmony huggingface dataset:
Antecedents of Organizational Performance: A Literature Review

Organizational performance is an important indicator for the survival and development of organizations, especially nowadays, the spread of the new crown epidemic, the declining international economic situation, and the increasing difficulties in the operation of domestic and international organizations have forced all organizations to actively seek ways to improve organizational performance. The measurement and influencing factors of organizational performance in different times and industries vary for each organization, but there are commonalities. This paper reviews a number of papers that attempt to identify the factors that influence organizational performance as a reference for organizations to improve their own performance. The literature review summarizes four antecedent variables that have a significant impact on organizational performance: organizational risk, organizational human resource management, organizational heterogeneity, and organizational leadership style.
Recovery of Urban and Rural Economy and Vitality under the Background of Post-covid Situation -- Taking Chuanying District of Jilin City as an Example

Since the Covid-19, the recovery of economic vitality has long been the focus of governments at all levels. As an important module of economic revitalization, promoting the growth of its economic system has been a long-term policy of the country. To this end, the country has been putting forward the economic policy of common development of urban and rural areas since the 19th National Congress. Based on the vigorous implementation and continuous deepening of the current policy, this paper, based on the various problems and opportunities faced in the current urban and rural economic development, combined with the accumulation of personal daily work in the Chuanying District of Jilin City, analyzes the reasons in depth, actively improves the plan, and tries to explore effective measures to promote the development of China's agricultural economy, which has a very positive role in promoting the improvement of the quality of national life and promoting the efficient construction of urban and rural economies.
Traffic-Sign-Detection Algorithm Based on SK-EVC-YOLO

Traffic sign detection is an important research direction in the process of intelligent transportation in the Internet era, and plays a crucial role in ensuring traffic safety. The purpose of this research is to propose a traffic-sign-detection algorithm based on the selective kernel attention (SK attention), explicit visual center (EVC), and YOLOv5 model to address the problems of small targets, incomplete detection, and insufficient detection accuracy in natural and complex road situations. First, the feature map with a smaller receptive field in the backbone network is fused with other scale feature maps to increase the small target detection layer. Then, the SK attention mechanism is introduced to extract and weigh features at different scales and levels, enhancing the attention to the target. By fusing the explicit visual center to gather local area features within the layer, the detection effect of small targets is improved. According to the experiment results, the mean average precision (mAP) on the Tsinghua-Tencent Traffic Sign Dataset (TT100K) for the proposed algorithm is 88.5%, which is 4.6% higher than the original model, demonstrating the practicality of the detection of small traffic signs.
Root cause analysis of credit card fraud

Fraud detection has always been a major problem in society, especially in the banking, insurance and medical sectors. As more and more people are using credit cards to pay, the fraud rates tend to get higher. This situation is a considerable risk for the credit card company. At the same time, credit cards and their related industries have become an indispensable part of the economic construction of various countries. Therefore through descriptive analysis, regression and factor analysis, this paper analyzes the root cause of fraudulent transactions and makes simple predictions. Discusses the characteristics of cardholders and influencing factors of fraudulent transactions, The subjective psychological factors have the biggest influence on fraudulent transactions and puts forward some suggestions to prevent fraudulent transactions.
The Effect of Using Media Video Learning to Write News on The Ability to Write News Texts in Class VIII of SMP Negeri VIII Tapung Hulu, Kampar Regency

This study aims to determine: (1) thefeasibility of information literacy-based news writing video media for students of grade VIII SMP Negeri 1 Tapung Hulu Kampar Regency, and (2) comparison ofstudent learning outcomes taught using information literacy-based news writing video media with student learning outcomes taught without information literacy-based news writing video media. The theory that becomes the reference in this research is about video media according to Arsyad, writing news according to Zainurrahman and Djuraid. The method in this research is a quasi-experimental research with anonequivalent control groupdesign.The population of this study were all junior high school students in grade VIII of SMP N 1 Tapung Hulu. The sample of this study amounted to 2 classes with each class totaling 36 students. Class VIII-1 was taught using information literacy-based news writing video media, while class VIII-3 was taught without information literacy-based news writing video media. The object of this research is news writing video media based on information literacy.The results of this study found that: (1) Thethe results of research on the quality of video media writing news based on information literacy both by material experts, media experts, Indonesian language teachers, and students provide an assessment with a very good category, and(2)Student Learning Outcomes taught using video media writing news based on information literacy (80.00 ± 3.87) ( ±SD) were higher than the learning outcomes of students taught without video media writing news based on information literacy (68.47 ± 5.92) (t-count = 9.772; P = 0.000). Thus, learning media is a means that can be used to channel messages, stimulate thoughts, feelings, attention, and willingness of students so as to encourage the learning process in students. So that the Indonesian language learning process using video media writing news based on information literacy can improve the efficiency and effectiveness of the process and student learning outcomes for the better.
Fraud Detection in Sales of Distribution Companies Using Machine Learning

The sales department of a distribution company is one of the places where fraud often occurs. This fraud occurs in various ways and causes massive losses for the company. These frauds have certain patterns. The patterns that occur in these practices are studied by the company's internal auditor experts. The experience of these experts is processed into a system called the Expert System. The support of a technology-based tool is needed in order to detect sales fraud early. The purpose of this research is to be able to provide benefits for companies with early detection of fraud in the sales department. At the time this research was conducted, researchers had not found similar research with the same object.&#x0D; In this research, a comparison of various machine learning algorithm models will be carried out with the aim of knowing whether using machine learning technology can help detect fraud with a high accuracy value. The algorithm method used is supervised learning method. The algorithm models to be compared are Decision Tree, K-Nearest Neighbor, Random Forest, SVM and Logistic Regression. It is expected that by using machine learning technology, fraud can be detected early, so that the level of loss and risk of sales can be minimized.
MOTIVATION OF NEW STUDENTS OF CONTINUING EDUCATION TO STAI ALHIKMAH JAKARTA

This study aims to determine the motivation of students in continuing their education at STAI ALHIKMAH Jakarta. The type of research used is field research using qualitative methods. The results showed that the majority of new students from the 2021/2022 class had intrinsic motivation in continuing their education at STAI ALHIKMAH Jakarta.&#x0D;
Online Stock Trading Workshop In Providing Understanding To The Public To Invest The Indonesia Stock Exchange

Investment is defined as the process of capital investment undertaken by an investor both foreign and domestic investors with the aim of making a profit. Investment is a term that is familiar to the public, both the upper, middle and lower class. However, most people have the perception that being an investor must be people who have a lot of money, especially for investing in large companies that are well known. Actually, this perception can be minimized by inviting people to conduct online trading training and providing an understanding to them that being an investor is not only among people who have a lot of money. Currently, the Indonesia Stock Exchange has made it easy for investors from the lower middle class to be able to act as investors. The solution provided by the Indonesia Stock Exchange is to reduce the number of shares in 1 lot, which is 100 shares. Finally, it is expected that with this online trading training activity, it can attract people to invest in the capital market.
Pengenalan Alfabet SIBI Menggunakan Convolutional Neural Network sebagai Media Pembelajaran Bagi Masyarakat Umum

SIBI is one of the Sign Languages used in Indonesia and has been widely used in the community, especially the school (SLB). Communication limitations of the deaf and speech community cause limited communication with the general public, especially many general public who do not know Sign Language or SIBI. For this reason, this research was conducted in order to become a learning media for the general public in recognizing the SIBI alphabet so that it can support communication with the deaf and speech community. This research was conducted to become a medium that can be used as a learning medium in the introduction of the SIBI alphabet. The method used in this research is CNN. CNN is used because it is a deep learning method that has the most significant results in image recognition. The data used is 2,600 images which are divided into 80% training data and 20% validation data. Training was done ten times by comparing the parameters that produce the best accuracy. The parameters used are batch size and epoch. From ten trials, the best accuracy is obtained using batch size 8 and epoch 50. The best accuracy produced is 85% training accuracy and 87% validation accuracy.
Economic Feasibility Study of Rooftop Solar Power Plant 32 kWp in PT KPJB Office Building, PLTU Tanjung Jati B, Kabupaten Jepara

Strategic initiatives in an effort to increase the role of New and Renewable Energy in the energy mix as a supply of power plants, one of which is the development of Solar Power Plants (PLTS) for own use at PLN's existing Power Plants. In 2021, the percentage of self-use power at PLTU Tanjung Jati B reaches 5.25% or the equivalent of 543 GWh, where PT. KPJB office building is one of the loads that receives self-use from the PLTU grid. Rooftop Solar Power Plant (PLTS) has been implemented on to replace the role of supplying electrical energy from the PLTU to several equipment to support the company's operations. After conducting an economic feasibility study with 3 calculation methods, namely Net Present Value (IDR. 210,436,003.12), Benefit Cost Ratio (1.17), and Payback Period (16.90), theoretically implementing a 32 kWp PLTS Rooftop can indeed said worthy. But with the three calculation results that can be considered very low with an estimated return on investment reaching almost 17 years.
The Challenges and Obstacles of Intellectual Capital among Academics in Jordanian Universities

The current study seeks to know the academic, economic, and administrative obstacles to maximizing the intellectual capital of academics in Jordanian universities, using the descriptive analytical approach, applied to a sample of (600) researchers and academics, during the period from June (2021) to February (2022). The results revealed that administrative obstacles ranked first, to a high degree, due to the large number of teaching loads, the negative impact of routine on conducting research, the length of the decision-making period to support scientific research, the lack of scientific staff, assistance to carry out research, and the complexity of requests for procedures to support scientific research. Economic obstacles came in the second place, to a high degree, represented by the reluctance of the private sector to support scientific research, poor funding for attending international conferences, low financial rewards for researchers, poor university funding for scientific research, and reduced budgets for scientific research provided to researchers. Academic obstacles came in the third place, to a medium degree, represented by the length of the evaluation period, the reclassification of scientific journals from time to time, the length of the publication period, the complexity of publishing procedures, and the complexity of international standards for publication. The results also revealed that there were no statistically significant differences at the level of significance (α≤0.05) in the scientific research obstacles scale, due to the variables: gender, specialization, current academic degree, and marital status. In the scientific research obstacles scale, they are attributed to the variables of age, number of years of experience, and monthly income. Keywords: Scientific research challenges, Intellectual capital, Jordanian universities.
Embedded Wids Kismet Sebagai Perangkat Deteksi Serangan Data Link Layer Wi-Fi Access Point

The rapid development of wireless network technology has an impact with a significant increase of users. Wi-Fi is one of the wireless technologies that is currently used widely by humans as a medium of transmission to exchange information. The increasing in the number of users is directly proportional to the increase the risk of crime occurring. In this case an attack on a Wi-Fi network aimed at taking certain advantage of the user or it’s victim was done by threatening aspects of information security. Wireless Intrusion Detection System (WIDS) is a tool used to detect intrusions that occur against wireless network technology, one of it is Wi-Fi into the form of logs. Kismet is one of the wids that is free and opensource with complete WiFi attack detection capability. The implementation of WIDS Kismet applied to Raspberry Pi 4 was shown as an alternative wids device that has a low cost for use in small Wi-Fi network environments such as home networks or small enterprise. The analysis is done by calculating the performance of accuracy, precision, recall, and f-measure values from the implementation results using confusion matrix method. The result of the calculation obtained by the highest value for each calculated performance with 99.83% accuracy, 97.96% precision, 100% recall, and 98.9% fmeasure. The calculation aims to provide information that can be utilized for users who want to do a similar implementation and use it to detect Wi-Fi networks.
Measuring Team Effectiveness in Scrum

Teams have become building blocks of organizations, leading to an exponential increase in team studies, including team effectiveness studies in Scrum software development. However, research on measuring Scrum team effectiveness based on objective measures, contrary to self-reporting with Likert scales, is absent. Through a design science research methodology with literature review, focus groups, interviews, and an expert panel, 29 objective measures were identified contributing to seven team effectiveness concepts. All measures can be quantified or directly derived from work management systems, such as Jira or Azure DevOps. Examples include the number of solved retrospective items after a new sprint, contributing to the team effectiveness concept ‘Continuous Improvement’, and the number of times a sprint goal has been achieved, contributing to both ‘Team Morale’ and ‘Stakeholder Satisfaction’. In this way, the study offers proof of the benefits of agile, especially Scrum, software development through effective teams as well as providing practitioners a first insight in benchmarking their Scrum team effectiveness.
Quantum as a Service Architecture for Security in a Smart City

Smart Cities are becoming a reality now with ample interest and investment from both government and private entities. As the number of Smart Cities increases, so does the sheer size and variety of data, the major part of which comes from Internet of Things (IoT) sensors embedded in devices. Millions of intelligent devices may be vulnerable to cyberattacks or threats, potentially harming one or more connected devices or exposing sensitive data. Therefore, Smart Cities have Intelligent Operations Centers (IOC), using different machine learning (ML) algorithms to monitor the data and take necessary actions to protect or contain any security incident. The advent of Quantum Computing (QC) has led to many initiatives for using QC in various applications of a Smart City but using Quantum Computing as a service is not yet fully contemplated in this context. In this work, we propose an architecture for Smart City security using Quantum as a Service (QaaS) for analyzing and classifying Smart City data. The proposed architecture uses two different Quantum Classifiers, implemented in the D-Wave Leap Quantum Cloud (QBoost) and IBM Quantum Services (Variational Quantum Classifier), for real-time classification of data and displays security incidents on a conveniently designed dashboard for further actions by the Security Operations Center (SOC) specialist. Further experiments have shown that D-Wave Leap Quantum Cloud-based QBoost performed the best among the quantum classifiers both regarding quality and time.
MR Image Super-Resolution Using Wavelet Diffusion for Predicting Alzheimer’s Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that exerts a substantial influence on individuals worldwide. Magnetic resonance imaging (MRI) can detect and track disease progression. However, the majority of MRI data currently available is characterized by low resolution. The present study introduces a novel approach for MRI super-resolution by integrating diffusion model with wavelet decomposition techniques. The methodology proposed in this study is tailored to address the issue of restricted data availability. It utilizes adversarial training and capitalizes on the advantages of denoising diffusion probabilistic model (DDPM), while simultaneously avoiding the problem of diversity collapse. The proposed method incorporates wavelet decomposition within the latent space to augment the resilience and efficiency of generative models. The experimental findings demonstrate the superior efficacy of our proposed model in contrast to alternative techniques, as indicated by the SSIM and FID metrics. Moreover, our methodology has the potential to enhance the precision of Alzheimer's disease assessment.
What Is Freedom of Speech?

It is important to have a strong, philosophical foundation of understanding regarding what constitutes freedom of speech. Through this, we may find that the justification for freedom of speech on which we are operating is inadequate. It could have blind spots, leading to negative consequences for specific individuals or groups, or it could even become wholly inverted as legitimating grounds for censorship. I explore the work of Plato, John Milton and John Stuart Mill through the lens of the philosopher Alan Haworth in order to come to an understanding of our current free speech justification. I define this justification as epistemic freedom of speech, a justification contending that censorship is dangerous because it denies humanity a chance to discover the truth of matters. I address some of the initial criticisms of this epistemic justification.
An Improved Solution for Sustaining Health Using ADIET Recommender System

A deep understanding of a balanced diet required by our body for the perfect amount of vitamins and nutrients in order to stay fit and healthy and be in a good shape has been taken up by many researchers who primarily work on building an efficient balanced diet recommender system. Moreover, unlike previous works, the focus of our study is not only on just recommending food items at random but also to offer a list of items keeping in mind one’s taste, choice, and/or preference. Such systems provide a tailor-made diet chart with a perfect balance of health requirements and one’s dietary needs without having to keep visiting health and nutrition experts. In this paper, a diet recommender system is proposed using k-modes clustering and RDF (resource description framework) ontology. Here, based on one’s preference and the calories and other nutrition requirements, the food items are recommended. The developed system takes into account the amount of carbohydrates, fats, proteins, etc. required by any individual as per one’s age and vital statistics. For every cluster, the respective centres are created, and the food items are recommended based on the choice made by the user. At the end, the experimental results are shown where it is inferred that the system performs quite well. Thus, the work contributes to the society by implementing proper health management based on optimally balanced diet recommendations. It is high time to define and implement sustainable approaches towards health management with proper nutritional intake to create an efficient food industry that can aid people in adopting healthy habits by transforming the recommendations into simplified dietary advice expressed in terms of food and food patterns.
Hands-on or hands-off: Deciphering the impact of interactivity on embodied learning in VR

Studies suggest that Sense of Embodiment (SoE) enabled by VR promotes embodied and active learning. However, it is unclear what features of VR learning environments tap into the concept of embodied learning. For example, interaction techniques, movement and purely observational scenarios in VR can all play a role in facilitating embodied learning. To understand how these mechanisms impact learning, we conducted 2 studies with a total of 64 participants who had no prior experience in the training task. Participants were taught how to use a table saw in 4 conditions and were tested on their task performance in a fully interactive VR assessment. The conditions were analyzed in pairs; 2 conditions with different interaction techniques, 2 conditions with differing ability to move and a cross-study analysis comparing conditions with purely observational learning to interactive learning. We used a mixed methods approach; Analysis of Variance (ANOVA), pairwise comparison of the learning outcomes in each condition as well as thematic analysis of the interview results. We found that some types of “hands-on” interactions can have a detrimental impact on learning and that observational learning can be as impactful as a fully interactive experience. Based on participant interviews, we explored how these mechanisms of the learning environment can impact participants’ learning ability.