Reviewerly/exHarmony huggingface dataset:
Temporal and Spatial Estimation of Quality Variables of Groundwater Resources Based on Intelligent Methods

Temporal and Spatial Estimation of Quality Variables of Groundwater Resources Based on Intelligent Methods
THE NETWORK SECURITY (NS) OF HEALTHCARE AND MEDICAL FACILITIES: AN ANALYTICAL OVERVIEW OF THE EMERGING CYBERSECURITY THREATS/RISKS AND COUNTERMEASURES

This research study discusses key issues concerning the Network Security (NS) of the healthcare and medical facilities. Particularly, it aims to shed light on the emerging cybersecurity threats and risks encountered by these facilities and the proposed countermeasures that can prevent, detect and respond to security threats (e.g., cyberattacks), vulnerabilities, and risks (e.g., financial or operational risks), and can serve to mitigate any damages and/or disruption caused by the exposure to any of the aforesaid incidents. In the current qualitative study, the researcher adopted the Analytical Approach as the research method that was utilized for the sake of gathering, analysing, interpreting the available literature of the subject -under investigation-, and eventually making inferences and reaching conclusions. Based on carrying out the previously-mentioned Analytical Literature Review, several findings were revealed by this study. Precisely, the study demonstrated that due to the Digital Transformation and the Digitization adopted by the healthcare sector, the vulnerability and fragility of the healthcare and medical facilities security networks and information/operational systems have been increased. Such deficit in the cybersecurity level had eventually led to the exposure of these facilities to several types of cyberattacks, network penetration, and many other cybercrimes. The findings of the study also demonstrated that the cyber threats can take the forms of: Malware, Ransomware, Phishing, and Insider Threats. Similarly, the cyberattacks types include Network Attacks, Wireless Attacks, Malware Attacks, and Social Engineering Attacks. Finally, the study revealed several cyberattacks countermeasures, include: 1) Raising the awareness of the healthcare and medical facilities workforce 2) Keeping the organizations software and systems fully up to date 3) Implementing Endpoint Protection Software 4) Installing a Firewall 5) Backup the organizations data 6) Securing the organizations Wi-Fi network and 7) Managing the healthcare and medical facilities employees personal accounts. Further countermeasures include the implementation of Risk Assessment, Authentication, Data Retention.
Inhance Deep Customizations in a Multi-tenant SaaS Application using the BPMN

A multi-tenant application aims to provide a single instance of an application with the capability for each organization to have its own specific functionalities. Recent researches have proved the efficiency of the intrusive and non-intrusive approaches in providing deep customizations. However, deep customizations are still limited to the features provided for each organization. In order to enhance the deep customization, we propose a BPMN-based customizations to provide to each organization the capability to create its own features. such a method requires an administration module to provide to the organization to create forms, scripts and notifications to be integrated in a BPMN workflow’s tasks. Such a method has proved its capability to introduce new functionalities using understandable graphical representations which reduce the need for the vendors’ intervention.
Quantum State Reconstruction Through Online Shadow Tomography: Theoretical Framework and Simulation Results

The purpose of this research work is to learn the quantum states in an ideal environments analytically, computationally, and graphically. The analysis starts with the learning of quantum states in identity channels with the help of the Regularized Follow the Leader (RFTL) algorithm. Our machine will try to learn the states based on the previous information, which is called the online learning model. The objective of this problem is to minimize regret by utilizing a learning algorithm that successively anticipates quantum states through observed measurements and losses. We have to produce many copies of quantum state ρ to perform analysis on them, which indicates the use of the shadow tomography approach in an ideal situation. Our goal is to learn the shadow of the state ρ by using a series of measurement operators that have two outcomes in nature. Aaronson et al. [1] developed an online setting for a non-realizable case, where the maximum possible loss is O( √ Tn) for the best possible state up to T−measurements . It is noteworthy that this outcome is an extension of the Aaronson PAC-like findings [2]. GANIT J. Bangladesh Math. Soc. 43.1 (2023) 65-74
Human Resource Management Practices and Performances in Nepalese Financial Institutions

Background: This study explores the dynamic relationship between human resource management practices and employee performance in Nepalese financial institutions. It investigates eight key elements, including Financial Compensation, Non-Financial Compensation, Leadership, Coaching, Empowerment, Participation, Organization Culture, and Motivation to address the research objectives. Objectives: The primary aim of this research is to analyse the impact of various human resource practices on employee performance in Nepalese financial institutions. Eight hypotheses are formulated, each targeting the relationship between Employee Performance and one of the essential components. Methods: The primary data collection instrument for this study is a structured questionnaire. This survey is being conducted on employees at various financial institutions in Nepal. The sample comprises 405 respondents. Descriptive and inferential statistical procedures, such as correlation analysis, regression analysis, and One-Way ANOVA, are used to analyse the collected data. Results: Regression analysis reveals a significant positive relationship between financial compensation and employee performance, emphasizing its crucial role. Conversely, no substantial relationships are found between employee performance and non-financial compensation, leadership, coaching, empowerment, participation, organisational culture, or motivation. The ANOVA test highlights the significance of job position, particularly in managerial roles, on employee performance. Conclusions: This study emphasises the critical role of an effective financial compensation system in improving employee performance in Nepalese financial institutions. While several human resource practices showed no significant impact, it emphasises the need to tailor these practices to specific job functions. These findings have significance for Human Resources Managers, guiding them in optimising practices for improved employee performance and organisational productivity. Keywords: Compensation, Leadership, Empowerment, Motivation, Employee Performance Paper Type: Research paper JEL Classification: G21, J32, J33, M52, M54
ANALISIS PERANCANGAN ARSITEKTUR ENTERPRISE DINAS PETERNAKAN MENGGUNAKAN TOGAF ADM 9.2 (STUDI KASUS: FUNGSI VAKSINASI HEWAN PADA DINAS PETERNAKAN BANDUNG BARAT)

This study analyzes and plans an enterprise architecture for the animal vaccination function at the Department of Fisheries and Animal Husbandry of West Bandung Regency. Animal vaccination is a crucial step in maintaining health and protecting animal populations from diseases. The author employs the TOGAF ADM (The Open Group Architecture Framework - Architecture Development Method) approach to analyze the animal vaccination process and identify necessary improvements. The vaccination steps, workflow, and responsibilities of various stakeholders are evaluated using the TOGAF ADM. Stages such as defining business architecture, data, applications, and information technology are applied in this analysis. The current information technology infrastructure is also analyzed to identify the suitable needs of the enterprise architecture. The results are expected to provide recommendations for improving the animal vaccination process at the Department of Fisheries and Animal Husbandry of West Bandung Regency. With an enterprise architecture based on TOGAF ADM, it is anticipated that the efficiency of animal vaccination implementation can be enhanced. These recommendations can serve as a guide for similar institutions in optimizing the animal vaccination process. In other words, this research bridges the theory of enterprise architecture with practical applications in the context of animal vaccination, yielding potential solutions to enhance process efficiency and effectiveness.
Redesign User Interface Dengan Metode Design Thinking: Studi Kasus

Transformation of production and service processes is a form of change in the industrial revolution era that is supported by systems. One of the components in a company's information system is a web page or known as a website. User Interface in website design is a concern at the CV X company which operates in the interior contracting sector. This research aims to redesign the user interface to suit user needs on the CV X website using the design thinking method. The design thinking method has six stages, namely, empathize, define, ideate, prototype, test, and implement. This research carried out four of the six stages of design thinking. Several research results include a collection of companies' desires to change the layout, content and elements on the website, content regarding SVLK, the use of persuasive words, and navigation features in the website footer that are not yet available in the current design. Defining the problem at the define stage is the elimination of be spoke pages, the use of colors that match the characteristics of the company, the addition of interactive animations, and changes to all elements on the website. The results of collecting ideas at the ideate stage were 9 ideas. The realization of ideas at the prototype stage consists of 3 processes, namely the style guideline creation process, the redesign process, and a comparison of the current design with the redesign results. The process of creating a style guideline includes fonts, colors, button elements, website headers and footers. This research focuses on the website user interface only so that the test and implementation stages related to User Experience (UX) are not analyzed.
Peningkatan Kemampuan Keterampilan Menulis Puisi dengan Memanfaatkan Media Audio Visual Siswa Kelas VII UPTD SMP Negeri 8 Gunungsitoli

This research was motivated by the fact that Indonesian language skills were still low or below average among class VII students at UPTD SMP Negeri 8 Gunungsitoli, especially the ability to write poetry. The purpose of this research is to measure the increase in poetry writing sills by utilizing audio visual media. The method used is a description method using a classroom action research (PTK) design. Based on hasti in the learning carried out by teachers, more than 75% of students got a score below the minimum criteria (KKM), namely 75. Seeing this condition, it is necessary to discuss the use of certain learning media to improve students abilities in learning poetry writing in class VII students at UPTD SMP Negeri 8 Gunungsitoli middle schools, the media chosen was audio visual media, the increase in students ability to write poetry can be seen in the result of the first cycle of research which obtained a total of 1.630 whit an average of 36 and 12 people were declared to have passed the KKM (75). In the second cycle the student’s ability to write poems after using the audio-visual media obtained an increase with several 2.380 with an average of 82, zelush cycle 1 and ll can be seen with several 150 and an average of 26. Based on this, awayang is categorized as complete in actus learning, has research 100%. After the research was carried out, it could be concluded that the use of visual audio media could improve the remaining abilities in writing putat
Perbandingan Penginputan Transaksi Secara Manual Menggunakan Accurate pada Laporan Keuangan Input Transaksi Manual dengan Accurate di Laporan Keuangan

This abstract discusses the comparison between manually inputting transactions using Accurate in financial reports. The manual transaction input method involves the process of manually entering data into the accounting system, such as recording purchase, sales and other expenditure transactions. Although this method can produce accurate financial reports, it requires more time and effort from the party doing the inputting. Apart from that, the risk of errors is also higher because data entry is done manually.On the other hand, using Accurate as a transaction input system can increase the efficiency and accuracy of financial reports. Accurate is an accounting software designed to help entrepreneurs or accountants in managing company financial transactions. By using Accurate, transaction input can be done automatically through integration with various data sources, such as the cashier system, purchasing system and sales system. This reduces the need to enter data manually, so the time and effort required can be minimized.Apart from that, Accurate is also equipped with an automatic validation feature which can reduce the risk of human error in inputting transactions. This feature will check the data entered and provide warnings or notifications if there are errors or discrepancies with applicable accounting rules. Thus, the accuracy of financial reports can be improved.In this research, a comparison will be made between manually inputting transactions and using Accurate in financial reports. By comparing these two methods, it is hoped that information can be found that can help entrepreneurs or accountants in choosing the most efficient and accurate transaction input method for their company.
Post-processing of compressed noisy images by BM3D filter

Acquired images are often noisy. Since the amount of such images increases, they should be compressed where lossy compression is often applied for several reasons. Such compression is associated with the phenomena of specific image filtering due to lossy compression and the possible existence of an optimal operation point (OOP). However, such filtering is not perfect, and residual noise can be quite intensive even if an image is compressed at the so-called optimal operation point. Then, additional post-filtering can be applied. Thus, the basic subject of this paper is the post-processing of noisy images compressed in a lossy manner. The main goal of this paper is to consider the possible application of a block-matching 3-dimensional (BM3D) filter to images corrupted by additive white Gaussian noise compressed by a better portable graphics (BPG) coder with a compression ratio smaller than that for the optimal operation point and in OOP neighborhood. The tasks of this paper are to analyze the efficiency of compressed image post-processing depending on noise intensity, image complexity, coder compression parameter Q, and filter threshold parameter β according to different quality metrics and to provide practical recommendations on setting the filter and coder parameters. The main result is that the post-processing efficiency decreases when the coder compression parameter increases and becomes negligible for a coder compression parameter slightly larger than its value for OOP. The post-processing efficiency is larger for simpler structure images and larger noise intensity. Compressed image quality due to post-processing improves according to the standard criterion peak signal-to-noise ratio and visual quality metrics. For larger coder compression parameters, the optimal threshold shifts toward smaller values. In conclusion, we demonstrate the efficiency of post-processing and show that the BM3D filter outperforms the standard discrete cosine-based (DCT) filter. We also provide recommendations for filter parameter setting. We also outline possible research directions for the future.
Genre Analysis of WhatsApp Group Chat among Students at University

Aim: This study examined Whatsapp group chat in connection with its influence on proficiency in English. Methods: Employing purposive sampling and mixed-method (quantitative and qualitative) approach to research, a group chat used for educational purposes by selected students of the University of Cape Coast, was analysed. Findings: the study revealed that most of the group members were not living in the same area within campus. Hence, the use of backchannel signals (Ok) with the sole aim of ascertaining whether communication is progressive and the information passed is well deciphered. Additionally, the study also shows that unlike drama, Oh is sparingly used on Whatsapp chat whereas Ok and its deviant form, were generously used. Ok was used to indicate initialization of conversation, reception of an information or message and closure of a conversational sequence. It was also shown that both Oh and Ok do not affect the truth conditions of the text; neither does it add any special meaning to the propositional content of the chat. Recommendation: In view of the findings that Oh and Ok do not enhance grammaticality of a sentence nor does it create propositional meaning, it was recommended that students should balance their use of Whatsapp messenger because much dependence on it for communication purposes could erode students’ grammatical construction of sentences as well as spellings in the English language. Contribution to the body of knowledge: investigating the use of discourse markers on WhatsApp group chat fills the knowledge gap regarding Whatsapp group chats among university students and educationists. Keywords: Whatsapp, Group Chats, University Students, Discourse Marker, English Language DOI: 10.7176/JEP/14-35-02 Publication date: December 31 st 2023
Study of Computer Vision for Manipulators

In recent years, computer vision technology has made significant progress, expanding its application from simple image recognition tasks to complex real-world problems. One such area where computer vision promises to be is the control of manipulators in various fields such as manufacturing, healthcare and robotics. Manipulators, mechanical arms designed to perform tasks, are traditionally controlled using manual input or a preprogrammed sequence. The purpose of this manuscript is to research and analyze computer vision applicable to improve the control and efficiency of manipulators.
Design and Implementation of an Alumni Management System

Alumni is a vital sector for every higher education institution, which comes to the aid of students in their post-graduation journey. An Alumni information system helps students to identify opportunities that reflect their interests, skills and aspirations, as well as help them to develop their potential and careers. This paper presents the design and development of an Alumni information system for Aleksander Moisiu University (UAMD), which aims to effectively and quickly manage the data of graduated students, their updating and their access by stakeholders. The system will be organized in a software that will be used to add data from the Alumni staff and from a Website which, interactively offers services both to employing companies and to job-seeking students. This paper contributes to the development and digitalization of the Alumni sector and in particular contributes to the development and digitalization of the Alumni sector in UAMD.
Comparative Analysis of Key Generation Algorithms used in Blockchain

Blockchain is a technology that is constantly improving. The encryption algorithms that are used in the blockchain are of particular importance for its security. In the present work, the various algorithms for encryption and key generation - RSA, ECC, EdDSA, and hash functions - are considered. A comparative analysis of the algorithms was made. A survey of cryptographic algorithms was made in terms of message size, hash value size, and security. Each of the algorithms plays an important role in creating secure keys and improving security in blockchain networks. Depending on the desired degree of security and available hardware setup, each of the algorithms has its applicability.
New Strategy for Developing and Enhancing Online Analytical Processing Cubes on Graphs

The growth of data had a profound impact on contemporary databases, leading to the emergence of a variety of No Sql (Not Only SQL) databases, containing those designed for graph data. To seamlessly incorporate graph data into existing decision support systems, there is a need to develop new Data Warehouse (DW) models that harness the advantages of graphs. This study introduces an innovative approach for creating a DW using a graph database. Furthermore, the research suggests employing aggregation algorithms to enhance the effectiveness of data analysis within a DW built upon a graph-oriented framework, addressing the challenge of building optimized OLAP (Online Analytical Processing) models within graph structures and emphasizing the selection of pertinent aggregations to effectively meet the diverse requirements of users.
Call Center Customer Sentiment Analysis Using ML and NLP

In the contemporary digital era, call centers have significantly incorporated automation through callbots, but they often lack an essential aspect of customer service: empathy. This paper explores the integration of sentiment analysis into call center operations to introduce an emotional dimension to callbot interactions. Utilizing natural language processing and machine learning, the paper examines both text-based and signal-based sentiment analysis approaches. The proposed sentiment analysis architecture encompasses data input and output interfaces, preprocessing, sentiment analysis, and a decision manager module that can, for example, escalate calls to a human agent based on sentiment analysis results. The preprocessing steps, both for text and signal analysis, are outlined in detail, along with a review of relevant sentiment analysis algorithms.Through comprehensive experiments, the study demonstrates that the integration of sentiment analysis yields promising outcomes. In text-based analysis, SVM and LSTM models consistently performed well, achieving accuracy scores of 74% and 72%, respectively. For voice-based analysis, the MLP model exhibited the highest accuracy of 0.72 when using mel spectrogram features, while the RF model outperformed others with an accuracy of 0.78 using MFCC features. These results showcase the potential of sentiment analysis in humanizing callbot interactions, thereby enhancing customer satisfaction and service efficiency.
Analytics of ensemble learning-based methods for Arabic text classification

In recent years, the volume of unstructured documents has grown exponentially, necessitating a profound understanding of Machine Learning (ML) methods to accurately classify documents in various domains, including business, media, sports, and more. This study proposes the utilization of ensemble learning methods for the automated classification of new documents. Specifically, ML algorithms and their bagging, boosting, stacking, and voting methods are employed. A comparative analysis of these algorithms is conducted using three benchmark Arabic datasets. The experimental results demonstrate that ensemble learning methods outperform individual learners in terms of accuracy, precision, recall, and F-measure. Among the ensemble learning classifiers, the stacking and voting methods exhibit the most promising performance, achieving the highest accuracy of 95.20% with the ANTCorpus dataset. Additionally, voting has led to improved accuracy of 93.24% for the Khaleej-2004 dataset and 92.15% for the Watan-2004 dataset.