Reviewerly/exHarmony huggingface dataset:
Performance of computer examination items selection based on grey relational analysis

In this paper, we propose an improved Grey relational analysis (GRA) model to enhance the strategy of tests items selection. In general, the strategy of tests items selection is based on the item response theory (IRT) to select test items by the measuring information of target test items. Five ability levels are used to set out the target information for items selection. Simulation results show that the proposed improved GRA model with scaling factor by 1.5, under the number of items by 10, 15, 20, 25, and 30, performs better than both the average target information (ATI) and random methods in mean square error (MSE). Furthermore, the improved GRA model while the number of items is 20 could largely achieve lower MSE of test information error (TIE) by 0.8 comparing to the 2.6 and 4.2 of ATI and random methods, respectively.
Evaluasi Proses Program Pendidikan Keaksaraan Dasar Perspektif Discrepancy Evaluation Model

The purpose of this study is to find out how to evaluate the process of literacy education programs from the perspective of the discrepancy evaluation model. The method used in this research is qualitative method. The results of this study indicate that there are gaps in the aspects of the program process which have three gaps including the preparation of learning tools (syllabus and lesson plans), improvement of reading culture, assessment of learning processes and assessment of final results. The achievements and impacts of the basic literacy education program have not been maximal in meeting basic literacy education program standards. In conclusion, the program analyzed its gaps and provided problem solving in every aspect based on the stage of the discrepancy evaluation model. &#x0D; Keywords: Process Evaluation, Basic Literacy, Discrepancy Evaluation Model
An Electronic Voting System adopting Blockchain: Interpretation, Characteristics and Investigation

This article offers an E-voting (Electronic Voting) approach that ensures security, privacy, and transparency. We have decided to use the blockchain system. Blockchain technology lowers the cost of centralized Clouds, Datacenters, and Networking Equipment, decreases the need for middlemen, and provides data privacy and transparency; all of which are critical for a fair election.An Architecture and Algorithm are suggested for the blockchain-based voting system. An internet of things (IoT) based system is designed to exchange data from the electronic voting machine and the nodes. Furthermore, we introduced its features, and we concluded with some future investigations.
A Content Analysis Approach to Intellectual Property Research

Abstract This chapter aims to demonstrate the implementation of the content analysis approach in the legal discipline; it argues that this approach is suitable for use by legal scholars, enabling analysis of various legal texts to uncover their connection and to learn about their meaning. Moreover, systematic analysing of legal texts yields insights that fine-tune the various challenges policy-makers and decision-makers are facing. This issue is particularly important in intellectual property (IP) research—a rapidly developing and dynamic legal field that calls for an up-to-date legal response to issues emanating from speedy technological developments. Specifically, the chapter sets forth a content analysis approach to analysing the judicial process in the context of online copyright enforcement cases. I argue that this approach facilitates advanced analysis of the legal process in a way that will help us understand and follow the development of the legal norm and contribute to legal certainty, despite the rapid changes taking place in the online copyright enforcement arena.
An Application of Principal Component Analysis (PCA) using XRF data to delineate the continetality factor over beach sediments from Vengurla, West Coast, Sindhudurg district, Maharashtra, India

We present here a novel approach of PCA to delineate the oceanic versus continental influence during pre-, mid and post monsoon seasons (PRM, MON, POM) over beach sedimentation at Vengurla along the west coast of India in Sindhudurg district, Maharashtra.PCA conducted over the XRF elemental results from 2003-2004 indicate a factor loading F1 for 2003 depicting predominant 'oceanic detrital' process and F2 as 'continental weathering' process.F1 for 2004 indicated 'continental weathering' with subdued 'oceanic detrital' process.F1 for the MON 2003 indicate 'continental detrital' process, and F2 subdued 'continental weathering' process.F1 for 2004 reveals 'continental detrital' and F2 'continental weathering' process.The overwhelming impact of monsoon can be inferred from this correlation.F1 for 2003 and 2004 POM as well can be assigned to 'continental detrital' process, and F2 to subdued 'continental weathering' process.The geochemical changes at Vengurla are season dependent, wherein hinterland is drained by monsoonal precipitation.The factor loading approach on mineral magnetic and geochemical data thus presents a precise semiquantitative method to delineate the continental and oceanic influence on the beach placers.
Design and Development of Alumni Career Information System using PHP MySQL

Alumni data collection at the Electrical Engineering Vocational Education Universitas Sultan Ageng Tirtayasa was still performed manually and there were no career information media about soft skills training and development, tracer studies, and job vacancies information. Therefore, media is needed to accommodate career information and alumni data collection quickly and effectively. The web-based information system using PHP MySQL was developed and tested for feasibility as an information medium for soft skills training and development, tracer studies, job vacancies information, as well as career counseling and consulting. This study used a Modify RD as a development method and the waterfall method as a development model consisted of analysis, design, coding (implementation), and testing. The testing was carried out by 37 people consisted of software experts, admins, alumni, and students of Electrical Engineering Vocational Education. The test was based on the ISO9126 standard with functionality, usability, reliability, and efficiency aspects. Based on the results, the functionality aspect had a score of 77 (very feasible), the usability aspect had a score of 87.8 (very feasible), the reliability aspect had a score of 100% (very feasible) and the average page load time was 3.48 seconds (feasible).
Semantic Segmentation of Hippocampal Subregions With U-Net Architecture

The Automatic semantic segmentation of the hippocampus is an important area of research in which several convolutional neural networks (CNN) models have been used to detect the hippocampus from whole cerebral MRI. In this paper we present two convolutional neural networks the first network ( Hippocampus Segmentation Single Entity HSSE) segmented the hippocampus as a single entity and the second used to detect the hippocampal sub-regions ( Hippocampus Segmentation Multi Class HSMC), these two networks inspire their architecture of the U-net model. Two cohorts were used as training data from (NITRC) (NeuroImaging Tools &amp; Resources Collaboratory (NITRC)) annotated by ITK-SNAP software. We analyze this networks alongside other recent methods that do hippocampal segmentation, the results obtained are encouraging and reach dice scores greater than 0.84
Bank Competition and Credit Access: The Case of Informal Firms in Sub-Saharan Africa

Purpose of the study: This paper investigates the impact of bank competition on access to finance by informal firms in 14 sub-Saharan African countries, using World Bank enterprise survey data. Access to finance is one of the main factors identified as hindering the growth of opaque borrowers, who are generally characterised by poor financial transparency. Methodology: This study uses a discrete binary choice probit model to estimate the probability or likelihood of accessing finance, conditional on the level of bank competition and other firm-level characteristics. Findings: Results show that the impact depends on the competition measure used. The Lerner index shows a positive relationship supporting the information-based hypothesis, while the most robust competition indicator, the Boone index, is negative in line with the market power hypothesis. These results also show that reducing or minimising information asymmetry using public credit registries is good for enhancing financial access. Research implications: Improving the competitiveness of the banking sector by encouraging the entrance of more players should be promoted without compromising the soundness of the sector. Measures should be introduced to control anti-competitive behaviour in the banking industry. Originality: The informal sector contributes close to 50% to Africa’s GDP and 80% towards employment and, therefore, strategies aimed at eliminating the obstacles faced by these firms are important for livelihood protection. Many studies done on the African banking industry have generally found it to be less competitive and this affects financial access since banks tend to be risk averse in such settings. There are also few studies that have analysed the relationship between bank competition and credit access in the informal sector, mostly because publicly available data on these firms are scarce.
Using KNN Algorithms for Determining the Recipient of Smart Indonesia Scholarship Program

The Smart Indonesia Card (KIP) scholarship program is a government scholarship program through the Ministry of Religion of the Republic of Indonesia which is given to students who have a good academic level but have a weak economic level. Sultan Syarif Kasim State Islamic University, Riau accepts new students every year, but the quota for the KIP scholarship program is limited. With the limited quota for the KIP program, a system is needed that is able to classify submission data from students who register for the KIP program, so that the selection process can be carried out, quickly, precisely, and in accordance with the required quota. In this study, the K-Modes and K-Nearest Neighbor (KNN) Algorithms were used by using the achievement variables, report cards, and national exam scores when high school, father's income, parental status, and homeownership status. Reprocessing is carried out before the testing stage, testing is carried out by performing the initial stages, namely clustering using the K-Modes algorithm, then validating or testing data by applying the Grid Search Cross-Validation (GSCV) method, and finally predicting using the KNN algorithm. The test resulted in a performance value of 66.79%
Simulations of text encryption and decryption by applying vertical bit rotation algorithm

Cryptography is the study of hiding text and numbers in the form of codes. Vertical Bit Rotation (VBR) is one of the most widely implemented cryptographic algorithms as a one-way hash function that simplifies the encryption process with a high degree of difficulty in decryption. The purpose of this study is to apply VBR hash algorithm modeling to binary value characters with bit rotation keys 10, 11, 7, 3, 2, 7, 5, and 4. Thus, generating a passcode. The results of the encryption simulation show the code in the form of letters and characters, then the result of the decryption with the opposite rotation to the encryption process returns the value from ciphertext to plaintext based on ASCII characters. Cryptographic algorithms are applied to avoid cryptanalytic experiments in opening encryption codes.
Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index

The Gaussian mechanism (GM) represents a universally employed tool for achieving differential privacy (DP), and a large body of work has been devoted to its analysis. We argue that the three prevailing interpretations of the GM, namely epsilon/delta-DP, f-DP and Rényi DP can be expressed by using a single parameter psi, which we term the sensitivity index. Psi uniquely characterises the GM and its properties by encapsulating its two fundamental quantities: the sensitivity of the query and the magnitude of the noise perturbation. With strong links to the ROC curve and the hypothesis-testing interpretation of DP, psi offers the practitioner a powerful method for interpreting, comparing and communicating the privacy guarantees of Gaussian mechanisms.
Discrete Semantics-Guided Asymmetric Hashing for Large-Scale Multimedia Retrieval

Cross-modal hashing technology is a key technology for real-time retrieval of large-scale multimedia data in real-world applications. Although the existing cross-modal hashing methods have achieved impressive accomplishment, there are still some limitations: (1) some cross-modal hashing methods do not make full consider the rich semantic information and noise information in labels, resulting in a large semantic gap, and (2) some cross-modal hashing methods adopt the relaxation-based or discrete cyclic coordinate descent algorithm to solve the discrete constraint problem, resulting in a large quantization error or time consumption. Therefore, in order to solve these limitations, in this paper, we propose a novel method, named Discrete Semantics-Guided Asymmetric Hashing (DSAH). Specifically, our proposed DSAH leverages both label information and similarity matrix to enhance the semantic information of the learned hash codes, and the ℓ2,1 norm is used to increase the sparsity of matrix to solve the problem of the inevitable noise and subjective factors in labels. Meanwhile, an asymmetric hash learning scheme is proposed to efficiently perform hash learning. In addition, a discrete optimization algorithm is proposed to fast solve the hash code directly and discretely. During the optimization process, the hash code learning and the hash function learning interact, i.e., the learned hash codes can guide the learning process of the hash function and the hash function can also guide the hash code generation simultaneously. Extensive experiments performed on two benchmark datasets highlight the superiority of DSAH over several state-of-the-art methods.
DEIKSIS PADA SLOGAN DALAM INSTAGRAM @KOMINFOMAGELANG DAN KAITANNYA DENGAN BAHAN AJAR TEKS SLOGAN

Social media technology is a place to delivered slogan texts, one of which is through Instagram. This study explains the types and the function of deixis in the @kominfomagelang Instagram slogan that related to slogan text teaching materials. This is certainly interesting to be used as research object so that it becomes a reference for teaching materials in text learning, especially in junior high school. Knowing the deixis and slogan text by following developments in today's modern era is very necessary. This research using a qualitative descriptive method with the @kominfomagelang Instagram as a data sourced. The data collection method using a pragmatic equivalent which is equipped with a data card. Meanwhile, data analysis was carried out using referential equivalents, followed by the basic techniques of PUP (Pilah Unsur Penentu) and advanced techniques of HBS (Hubung Banding). The aim of this research is to find out the various types and functions of deixis contained in the slogan on the @kominfomagelang instagram so it can be used as an alternative teaching material in the slogan text. The results of this research show that in the @kominfomagelang instagram slogan there are three types of deixis, namely: (a) deixis Persona, (b) Place/Space Deixis, and (c) Time Deixis with the showing pronouns of person, thing, thing, temporal, and spatial function. The Indonesian language Learning in, especially in deixis, can be related and can be used as teaching material for slogan texts for VIII gradeÂ of junior high school. The research expected aim is to make students get easier to understand the deixis learning material and slogan text and add the knowledge or skills in the meaning of communication.
Scaling complexity comparison of an ACO-based routing algorithm used as an IoT network core

This paper proposes a routing method that is based on an Ant Colony Algorithm (ACO) for minimizing energy consumption in Wireless Sensor Networks (WSNs). The routing method is used as the backbone of the Internet of Things (IoT) platform. It also considers the critical design issues of a WSN, such as the energy constraint of sensor nodes, network load balancing, and sensor density in the field. Special attention is paid to the impact of network scaling on the performance of the ACO-based routing algorithm.
Effect of Social Capital on SMEs Performance: Does Innovation Matter

The study investigated how social capital influences firms to generate higher performance through innovation among SMEs in Ghana. The study employed a quantitative approach. The study employed stratified sampling to sample 240 respondents from 240 SMEs in the Eastern Region of Ghana. Primary data was gathered using a questionnaire adapted from previously validated instruments. The data gathered was analyzed using Partial Least Square (PLS) of the Structural Equation Model (SEM). The findings proved internal and external factors of the SMEs were found to be strengthened through innovation initiatives of the SMEs. The social capital initiatives of the SMEs positively and significantly enhanced the innovation practices of the SMEs. The result showed internal and external social capital initiatives of the SMEs were positively and significantly associated with the innovation practices of the firms. It concludes that the effect of social capital among SMEs on firm performance is indirectly through their level of innovation practices. The results provide empirical support to the validation of existing theories that a company’s utilization of important values offer some level of competitive advantage for superior performance in an industry. We therefore recommended that Owners and Managers of SMEs take advantage of their internal social resources as well as building strategic external capital in the quest to remain competitive and enhance profitability.&#x0D; &#x0D; Citation:Tetteh, F. K., Mohammed, J. and Teye, E. (2021). Effect of Social Capital on SME: Does Innovation Matter?&#x0D; International Journal of Technology and Management Research (IJTMR), Vol. 6 (2): Pp.21 －37.&#x0D; Received: February 5, 2021&#x0D; Accepted: September 1, 2021
Subject Review: Information Hiding Using Chaotic Map

It is vital to convert information into an unidentifiable form in order to protect your confidential information from intruders.As a result, intruders will be unable to obtain your original information.As a result, security is the most difficult component for all users who wish to share their confidential information.In recent years, because of the quick rise of the internet and quick communication technology, the security and confidentiality of sensitive information has become a top priority and worry.Information concealment is the technique of communicating secret information in a suitable carrier, such as a picture, video, or voice.Various technologies for information concealment, such as encryption, steganography, hashing, and authentication, have been developed and are in use today to safeguard information from unauthorized access.Steganography's principal purpose is to conceal the existence of secure information, making it difficult for an unauthorized person to discover it.Steganography is the art of concealing information sensitive information in any medium in order to send it through a communication network in a secure manner.The main goal of this paper is to examine and describe strategies for hiding information within multimedia using chaotic maps, as well as to compare various methods.
Applicability of online professional education to the conditions of the Arctic zone: the viewpoint of employers

Introduction. Labor markets in the regions of the Arctic zone of the Russian Federation are challenged with the needs for personnel who have to work in the extreme conditions of the Far North. This objective circumstance imposes special, often increased requirements for the qualifications and level of training of job seekers, including the quality of their education. The relevance of this study is due to the increasingly popular online form of education, which is characterized by both advantages associated with the availability of such education and its safety in the era of a pandemic, and disadvantages associated with the quality of education received. The purpose of the study is to analyze the demand for specialists who have received professional education online in the labor market of the regions of the Arctic zone of the Russian Federation. Materials and methods. The information base of the study was the results of surveys of more than 2,200 employers from the territories of all 9 constituent entities of the Russian Federation included in the Arctic zone. The surveys were conducted using online survey methods. The methods of descriptive statistics, system analysis and comparative data analysis were used when processing the survey results. Research results. The applicability of obtaining professional education in online form for the conditions of the Arctic zone is approved by 58% of the surveyed employers, and 42% have a negative attitude to this practice. Only every third employer surveyed considers the online education system existing in the RF AZ as a whole to meet their requirements for this type of training. At the same time, over 40% of employers in all Arctic regions expressed their readiness to hire specialists with a diploma in online education. The results of the survey, presented in the context of the Arctic regions and types of economic activity, showed a heterogeneous attitude of the employers to the issues under study. Discussion and conclusion. The results obtained confirmed the importance for the employers of the RF AZ of personnel training issues using online training, which has both a number of undoubted advantages for the Arctic territories and limitations. An important trend in the development of the study is to assess the capabilities of the existing system of distance online education from the perspective of the subjects of education themselves – universities and colleges located in the Arctic zone of Russia.
English Language Problem-based Learning via user-generated 3D world Roblox Module: Need Analysis

This study aimed to explore the need of a user generated 3D world (Roblox) online game module in English Language Problem-based Learning for Malaysian university students. The researchers used observations, interview, and questionnaire distribution that were implemented to 60 university students studying English Language at Universiti Malaysia Kelantan, Malaysia as well as 4 English Language teachers in the university. The results indicated that the students agreed that learning English language by using Roblox online games was interactive, challenging, exciting and fun. The students also recommended that the activities in the English Language Roblox Module should be easily done and accessed in all platforms including mobile phone, table and computer. Teachers also pointed out that the narrative elements that involve critical thinking skills were needed in the module to help them fostering the students to imply their problem-solving skills related to real-life issues in the learning process. The implications of this study will be significant for the English Language Roblox module developer as the technique for promoting problem solving skills in English Language Learning and to enhance students’ awareness on real-life issues.