Reviewerly/exHarmony huggingface dataset:
The Spatial Pattern of the Spread of the COVID-19 Pandemic (Case Study: DKI Jakarta Province)

The COVID-19 pandemic has been running in Indonesia for more than two years. The first case was found in March 2020. DKI Jakarta as the capital city of the country with a high population density and an economic center that was threatened because the area has a high vulnerability to the spread of COVID-19. The number of confirmed cases that continue to soar and the spread that is difficult to be controlled have resulted in the DKI Jakarta government taking policies such as implementing large-scale social restrictions (PSBB), which aims to stop the spread of COVID-19 and to look for patterns of spread of COVID-19. This study uses a geographic information system in looking for patterns of the spread of COVID-19. The analytical method used is spatial autocorrelation, which is carried out using the Moran Index. In addition, the autocorrelation test was also carried out using a Local Indicator of Spatial Autocorrelation (LISA) with the results in the form of a cluster map and a map of significance. The Ordinary Least Squares analysis method is a regression technique that provides a global model for understanding and predicting variables in research. The correlation variables used in this research are Markets, Supermarkets, Buses, and Stations. The result of this study is the spatial autocorrelation of the pattern of spread of COVID-19 between villages and spatially the distribution pattern is clustered. In the OLS regression distribution pattern, the supermarket variable with an R-Squared value of 0.128555 or 12% affects the spread of COVID-19. Based on the calculation of R-Square, Koenker (BP) in addition to the OLS model, the assumption of homoscedasticity is not met, so the model is Ordinary Least Squares not good compared to other models in analyzing the pattern of the spread of COVID-19 in DKI Jakarta.
Knowledge Authoring for Rules and Actions

Abstract Knowledge representation and reasoning (KRR) systems describe and reason with complex concepts and relations in the form of facts and rules. Unfortunately, wide deployment of KRR systems runs into the problem that domain experts have great difficulty constructing correct logical representations of their domain knowledge. Knowledge engineers can help with this construction process, but there is a deficit of such specialists. The earlier Knowledge Authoring Logic Machine (KALM) based on Controlled Natural Language (CNL) was shown to have very high accuracy for authoring facts and questions. More recently, KALM FL , a successor of KALM, replaced CNL with factual English, which is much less restrictive and requires very little training from users. However, KALM FL has limitations in representing certain types of knowledge, such as authoring rules for multi-step reasoning or understanding actions with timestamps. To address these limitations, we propose KALM RA to enable authoring of rules and actions. Our evaluation using the UTI guidelines benchmark shows that KALM RA achieves a high level of correctness (100%) on rule authoring. When used for authoring and reasoning with actions, KALM RA achieves more than 99.3% correctness on the bAbI benchmark, demonstrating its effectiveness in more sophisticated KRR jobs. Finally, we illustrate the logical reasoning capabilities of KALM RA by drawing attention to the problems faced by the recently made famous AI, ChatGPT.
Mediating Role of Trust Between Transformational Leadership, Knowledge Management, and Employee Innovation Among the Employees of Customs Department Dubai

Purpose: The purpose of the study was to identify the mediating role of trust between transformational leadership, knowledge management and employee innovation among the employees of customs department Dubai United Arab Emirates. For meeting the objectives of the study and to test the framework of the study, the current study collected data from the employees of custom department of Dubai. &#x0D; &#x0D; Theoretical framework: Employee innovation is considered as a key participant in organizational success. Leadership plays a significant role in developing employee innovation; however, it becomes successful only when the leader succeeds in developing trust among the employees.&#x0D; &#x0D; Design/methodology/approach: The data has been collected from 371 employees and structural equation modelling has been applied to test the relationships and mediation analysis.&#x0D; &#x0D; Findings: The findings revealed that both leadership and knowledge management have a significant impact over employee innovation. Likewise, trust significantly mediate the relationship between transformational leadership, knowledge management and employee innovation.&#x0D; &#x0D; Research, Practical &amp; Social implications: The research opens the horizons for several other studies to explore other influencing variables for promoting employee innovation&#x0D; &#x0D; Originality/value: Provide a more nuanced and integrated perspective on how leadership and knowledge management affect trust and, eventually, employee innovation by evaluating them together, even though our examination of existing studies reveals that they were evaluated independently so far.
Leadership, Knowledge Management and Employee Commitment: Mediating Role of Crisis Management

Purpose: Using crisis management as a mediator between leadership skills, knowledge management, and employee commitment, the study examines the role of crisis management in UAE public sector organizations. In order to motivate employees and keep them committed, supportive leadership skills and knowledge are required. However, crisis management if managed through proper knowledge and skilled leadership develops employee commitment which is highly needed in the times of crisis.&#x0D; &#x0D; Theoretical framework: Managing knowledge and leadership skills during crisis situations can only be achieved if employees are able to effectively manage them.&#x0D; &#x0D; Design/methodology/approach: Using SMART PLS3, a structural equation modeling approach has been used to analyze the collected data in order to meet the objectives of the study.&#x0D; &#x0D; Findings: Likewise, crisis management significantly moderates the relationship between leadership, knowledge management, and employee commitment. Leadership, knowledge management, and employee commitment are strongly related.&#x0D; &#x0D; Research, Practical &amp; Social implications: Despite genuine efforts, this study constraint persists. First, the study's sole focus is on employee commitment during times of crisis, and knowledge management is a crucial component of this. Also examined were aspects of knowledge management that affect employee commitment in detail.&#x0D; &#x0D; Originality/value: In this study, crisis management as a mediator was added to the theory and the matrix based on the knowledge-based view of crisis response leadership.
Cognitive biases in decision-making: applications on strategic management and rationality improvement

Every decision is faced with the unknown. Decisions with strategic density, more than others, carry by themselves a greater burden of responsibility on the firm performance, crucial to obtain the positive results desired by both managers and shareholders. The scope, space of states of strategies formulation and implementation is, customarily wide, and still, the game is open with other forces of the internal and external environment acting. Many studies have shown that the decision-making, formulation and implementation process, considered in moments as part of the strategy process set, comprises emotional and rational phases. In the decision there are mixtures of emotions, intuitions and empirical elements that in the construction of the process present cognitive biases. The decision maker's previous experiences, the brain circuits involved, notably, somatic markers will be involved in the process. While these biases can creatively contribute to the decision-making process, it is always possible, if not often, that undesired (negative) outcomes derive from this interference of cognitive "guessing" in decision-making. This essay seeks to define cognitive biases in strategic management and how they can influence managers in the decision-making process. This article seeks to analyze the commonalities between the analyzed authors of strategy that deal with the theme. The research also seeks to list the cognitive biases most cited by these authors, with the aim of highlighting which should be considered possibly the most relevant to the decision-making process.
Innovation and Practice of Accounting Teaching Based on Internet Big Data

With the advancement of science and technology, Internet technology affects all aspects of people's production and life.The era of big data has arrived, and the field of education and scientific research has also been greatly affected.As an important position for cultivating talents, colleges and universities should keep abreast of the pulse of the times and innovate the concept of accounting education to meet the needs of society for talents.In this paper, the meaning of "Internet + big data" is combined with the current situation of accounting education in colleges and universities under the mode of "Internet + big data", and the difficulties faced by accounting education in colleges and universities under the mode of "Internet + big data" are analyzed, and the innovation strategy of accounting education in colleges and universities is studied.To give full play to the advantages of information-based accounting education, improve the level of accounting education, and cultivate excellent accounting professionals.
Optimization of English Learning Activity Observation Management Software Based on Openstack Optimization: Based on Extreme Hybrid Testing Algorithm

In this paper, a gray wolf optimization algorithm (BGWO) based on extreme mixture learning algorithm is proposed, which improves the population diversity of GWO in the search process.The training of KELM is completed by iteratively solving the observation of English learning activities with the best fitness function value in the search space.Combined with examples of reading teaching design in the same class and heterogeneous, this paper summarizes the design ideas of high school English reading teaching based on the concept of English learning activities.That is, to refine the main line of the text and construct structured knowledge; to use the 3×3 English subject ability element framework.The proposed multi-objective optimization strategy for virtual machine dynamic migration.This strategy is described from the aspects of system resource monitoring, resource scheduling timing selection, virtual machine selection to be migrated and physical machine migration selection.
Java Data Structure Optimization of Talent Training Performance Evaluation System Based on Distributed Hierarchical Data Clustering Algorithm

In the implementation scheme, the data source uses the message middleware Kafka, and the intermediate results are stored in the memory database Redis through serialization technology.Multi-faceted experimental results and analysis show that social environmental factors, social value orientation utilitarian.Based on this, the following main countermeasures are put forward to enhance the endogenous motivation of applied talents to cultivate college students: to stimulate their own endogenous motivation from the student level, to improve their own subject consciousness, to adjust their own need's structure, and therefore to teach mixed data structure based on Java.Demonstration system for optimized design.First, we should optimize the design of the framework of the hybrid data structure teaching demonstration system, and then optimize the design of the teaching demonstration database, that is, optimize the design of the database tables.
Formation and assessment of medical competencies on a virtual model of the treatment and diagnostic process in cardiology

Background. It is the competence of making diagnostic and therapeutic decisions that is the most important in clinical practice. Digital model of treatment and diagnostic process (TDP) allows provide the remote formation of skills for decision-making. Aim: To provide the methodological support of remote formation of competences, to improve and assess the skills of medical decision-making in cardiology. Methods. Clinical and diagnostic information from different sources was the material for creating virtual models of TDP. Skilled cardiologists were involved to develop technical specification; knowledge engineering methods were used. Fifty virtual patients with linear structure and ten with branched structure were developed. Technical specification was implemented using Web technologies – Java Script (framework Vue.js), Twitter bootstrap, PostgreSQL. Results. In the first phase of this project only a Web-resource was created. All digital models of patients’ TDP were placed in a linear order without any interactivity. To assess the effectiveness of medical decisions in the second phase of the project, branched TDP model with interactivity was created. It covers all stages of medical decision-making: from the patient hospital admission to his discharge. Besides the real invariant treatment of the patient, the model includes “subjunctive” process variants – “how could it be if ...” Among the interactive blocks, experts considered those leading to a change in TDP trajectory. We named them as “trigger” blocks, where the decisions influence upon TDP outcome. To assess the effectiveness of decisionmaking by learners, the rating system has been developed. It makes it possible to calculate not only general, but also particular personal ratings for certain categories of medical and diagnostic decisions. Conclusion. This study suggests the methodology for remote formation and evaluation of doctor’s competencies, which is implemented in the format of virtual TDP models.
Impact of organizational culture and compensation on job satisfaction and employee retention: A case of pharmaceutical industry of Pakistan

The study aimed to examine the effect of compensation and organizational culture on employee retention with the mediating role of job satisfaction in the pharmaceutical sector of Pakistan. Based on survey methodology, the study has gathered 338 responses from SC professionals and executives of pharmaceutical firms in Karachi. The purposive sampling technique was used to choose samples. PLSSEM was used for data analysis through Smart PLS v3. The results showed that job satisfaction has a significant positive effect on employee retention, whereas compensation also has a significant positive effect on job satisfaction. Likewise, organizational culture has a significant positive impact on job satisfaction. In contrast, payment and OC positively and indirectly affect employee retention by mediating job satisfaction. Managers should implement creative and enticing compensation strategies to retain employees and inspire them with various rewards to enhance the individual effort. They should also be aware of the factors that increase ER and raise JS, such as the work environment.
Gamification in Duolingo App on Improving English Listening Proficiency of Junior High School Students

Gamification is considered as a strategy to involve students in solving problems related to learning English, rather than playing games. Duolingo, an application that uses gamification, is suitable for junior high school students as a formal classroom setting in English learning. This study aimed at investigating whether the use of gamification in Duolingo App can improve the listening proficiency of junior high school students in English. This research uses quasi-experimental design with quantitative approach. The data is collected using test and observation and analyzed using SPSS 26 App. The results show that the sig. (2 tailed) indicated is 0.002 meaning that there is difference between post-test of experiment class and control class. It is concluded that gamification in Duolingo app affects English listening proficiency of junior high school students. Hence, Duolingo App has the potential to serve as a valuable tool for educators to enhance their students' listening skills. Additionally, gamification can form the foundation for the development of technological learning resources. However, this study has some limitations, and further research involving different educational levels, media, and longer experiment duration is necessary to obtain detailed and reliable results that can be applied to the broader population.
Secured Mechanism Towards Integrity of Digital Images Using DWT, DCT, LSB and Watermarking Integrations

"Watermarking" is one method in which digital information is buried in a carrier signal; the hidden information should be related to the carrier signal. There are many different types of digital watermarking, including traditional watermarking that uses visible media (such as snaps, images, or video), and a signal may be carrying many watermarks. Any signal that can tolerate noise, such as audio, video, or picture data, can have a digital watermark implanted in it. A digital watermark must be able to withstand changes that can be made to the carrier signal in order to protect copyright information in media files. The goal of digital watermarking is to ensure the integrity of data, whereas steganography focuses on making information undetectable to humans. Watermarking doesn't alter the original digital image, unlike public-key encryption, but rather creates a new one with embedded secured aspects for integrity. There are no residual effects of encryption on decrypted documents. This work focuses on strong digital image watermarking algorithms for copyright protection purposes. Watermarks of various sorts and uses were discussed, as well as a review of current watermarking techniques and assaults. The project shows how to watermark an image in the frequency domain using DCT and DWT, as well as in the spatial domain using the LSB approach. When it comes to noise and compression, frequency-domain approaches are far more resilient than LSB. All of these scenarios necessitate the use of the original picture to remove the watermark. Out of the three, the DWT approach has provided the best results. We can improve the resilience of our watermark while having little to no extra influence on image quality by embedding watermarks in these places.
Development of an Online Inventory System for the Engineering and Sciences Laboratory Office of Asia Pacific College through a Mobile Application with Equipment Serial Number Detection using OCR

Purpose -The Asia Pacific College's School of Engineering (APC-SoE) strongly establishes theories to its students and integrating all their theoretical knowledge through projects.Since the students need both software applications and hardware components, the Engineering and Sciences Laboratory Office (ESLO) supports them their needs and at the same time -is responsible for the maintenance of the said necessities.The ESLO, though capable of its duties, still does not have an inventory system to easily track each equipment.The developed application called SoE Keep is created for the ESLO to keep track of equipment that needs recalibration, create, edit, and delete equipment from the database, view reports that shows damaged, borrowed, approved, and returned items that students used.Methodology -The SoE Keep application was developed using Android Studio to work on devices using Android API 7.1.1 and newer version.SoE Keep's database is directly tied up to the database used by the ESLO Web Services to update the inventory and generate charts pertaining to the statistics of each item.Furthermore, the application uses Android OpenCV to perform the Optical Character Recognition (OCR) function.The OCR includes preprocessing tools such as masking and grayscale transformation for feature extraction.Practical Implications -SoE Keep, in compliance with ISO 2600 standard, provides practical assistance in implementing social obligations while considering cultural, sociological, environmental, and legal variations as well as economic development situations.
MemBridge: Video-Language Pre-Training With Memory-Augmented Inter-Modality Bridge

Video-language pre-training has attracted considerable attention recently for its promising performance on various downstream tasks. Most existing methods utilize the modality-specific or modality-joint representation architectures for the cross-modality pre-training. Different from previous methods, this paper presents a novel architecture named Memory-augmented Inter-Modality Bridge (MemBridge), which uses the learnable intermediate modality representations as the bridge for the interaction between videos and language. Specifically, in the transformer-based cross-modality encoder, we introduce the learnable bridge tokens as the interaction approach, which means the video and language tokens can only perceive information from bridge tokens and themselves. Moreover, a memory bank is proposed to store abundant modality interaction information for adaptively generating bridge tokens according to different cases, enhancing the capacity and robustness of the inter-modality bridge. Through pre-training, MemBridge explicitly models the representations for more sufficient inter-modality interaction. Comprehensive experiments show that our approach achieves competitive performance with previous methods on various downstream tasks including video-text retrieval, video captioning, and video question answering on multiple datasets, demonstrating the effectiveness of the proposed method. The code has been available at https://github.com/jahhaoyang/MemBridge.
FAKE PRODUCT IDENTIFICATION SYSTEM USING BLOCKCHAIN AND DECENTRALISED FINANCE (DEFI)

Counterfeit products pose a significant threat to consumer safety, brand reputation, and the economy. To address this issue, this project proposes a solution that utilizes blockchain technology to create at am per-proof and transparent product identification system. The proposed system aims to enable consumers to verify the authenticity of the products they purchase by storing product data, including manufacturing and supply chain information, on the blockchain. The system also proposes the integration of smart contract-based incentives to encourage consumer participation in the verification process. The project offers the potential to reduce counterfeit products in the market, increase consumer trust, and improve supply chain transparency.
First approach to Digitalize Academic Records in Viet Nam using Blockchain Technology

Schools and departments use modern technologies to store and manage academic records digitally. However, the implementation is inconsistent as many places still rely on traditional ways to proceed with transcripts. It has significant problems like being centralized, third-party required, untraceable, and untrustworthy. This research presents some new problems in applying blockchain to manage student records. First, the study approaches the problem by listing the essential characteristics of a reliable system. Next, the research explains how Blockchain technology, especially Hyperledger Fabric, can be applied to a specific situation. Finally, the study provides three concepts: a centralized system, a multi-school network using blockchain, and a multi-school system that extends the multi-school system and provides storage and management for education departments. This research will be used as a foundation for similar topics and products to implement a system for admission to universities and colleges in Vietnam.