Reviewerly/exHarmony huggingface dataset:
Institutional Governance Practices in Jordan Government Units

Purpose: This research paper aims to examine institutional governance practices in Jordan government units. Design/Methodology/Approach: Institutional governance practices incorporates the following aspects, legislation, structure and organization, policy and decision-making, human capital management, operations and procedures, financial management, resources management, performance management, and institutional culture. These institutional governance practices have been assessed by leaders responsible for institutional development in government institutions and companies listed in Government Units Budgets Law. Findings: The findings indicate that the institutional governance practices and their related aspects exceed the average level. The research concludes that governance practices incorporate conforming to specifications and complying with frameworks, guidelines, and standards. They are improving the quality of delivering services and at the same time optimizing the use of resources, which enhances the trust in institutions and companies. Practical Implications: Similar institutions and companies may use this assessment approach to assess governance practices and bridge the gaps or undertake further enhancements accordingly. Originality/Value: To the best of the author's knowledge, previous studies have concentrated mainly on top management and board of directors' governance and focused on governance aspects. This study examines governance practices at the fundamental institutional level, incorporating the institution set-up, structure, frameworks, systems, processes, and machinery of an institution that ensures good governance efficiency, effectiveness, and overall performance.
The Influence of Job Stress of Social Enterprise Workers on Organizational Citizen Behavior: Focusing on Seoul and Gyeonggi Area

Recently, not only commercial enterprises but also non-profit enterprises (eg, social enterprises) are in a competitive situation. In this competitive situation, companies depend on organizational performance and results for survival and development. As these organizations demand higher tasks from their members and force their performance, job stress is increasing on them. The purpose of this study is to examine the effect of job stress on organizational citizenship behavior through previous studies, and based on this, to empirically study the causal relationship between job stress and organizational citizenship behavior of members of social enterprises. Specifically, first, based on previous studies, we theoretically consider job stress. Second, I would like to review the concept and components of organized citizenship behavior. Third, it analyzes hypothesis setting and empirical research and draws implications according to previous research. As a result of the study, the following implications were revealed First, it was confirmed that job stress is a factor that hinders organizational citizenship behavior in today's growing importance of organized citizenship behavior. Second, unlike general companies, social enterprises pursue both profit creation and social purpose, and the positive influence of influential social enterprises on society is growing. Third, for the development of a company or organization, an organization manager should focus more on organizational citizenship behavior while reducing the job stress of its members.
Development of Socio-cultural Competence in Future Primary School Teachers on the Basis of an Axiological Approach

nThis article deals with the development of socio-cultural competence in future primary school teachers on the basis of an axiological approach. There are some skills about how to use it efficiently.
Research on the Quality and Curriculum Design of Chinese Pre-School Education

Preschool education is a solid foundation for talent enlightenment. With the comprehensive implementation of the new curriculum reform in China, the reform process of preschool education and the improvement of the education quality are accelerating. This paper explores and analyzes preschool education quality improvement and curriculum design development in China, aiming to put forward effective strategies for the preschool education reform.
Contrastive Conditional Transport for Representation Learning.

Contrastive learning (CL) has achieved remarkable success in learning data representations without label supervision. However, the conventional CL loss is sensitive to how many negative samples are included and how they are selected. This paper proposes contrastive conditional transport (CCT) that defines its CL loss over dependent sample-query pairs, which in practice is realized by drawing a random query, randomly selecting positive and negative samples, and contrastively reweighting these samples according to their distances to the query, exerting a greater force to both pull more distant positive samples towards the query and push closer negative samples away from the query. Theoretical analysis shows that this unique contrastive reweighting scheme helps in the representation space to both align the positive samples with the query and reduce the mutual information between the negative sample and query. Extensive large-scale experiments on standard vision tasks show that CCT not only consistently outperforms existing methods on benchmark datasets in contrastive representation learning but also provides interpretable contrastive weights and latent representations. PyTorch code will be provided.
Composition writing skills of senior high school students

This study determines the composition writing skills of senior high school students. The respondents consist of 88 Grade 11 Humanities and Social Science (HUMSS) students representing the Aurora Senior High School. Descriptive correlation design, Pearson r, t test and tabular value were used to analyze the data. The result of the study revealed that self-interest, peers, parents, school administration and teachers’ support, as well as social media are factors that help in improving the writing performance of the students. It was observed that the students are remarkably weak in grammar, paragraph structure and voice but they are good in observing the structure (introduction, body, conclusion, mechanics, word choice) of a written composition. Concomitant to this study, it was found out that not all students having above fair grade in English 11 are good writers. The researchers recommend that the support of teachers, school administration, peers and parents, students’ interest and use of social media should be given consideration for the continuous development of the learners in composition writing. Teachers should give appropriate attention to teaching of grammar, paragraph structure and voice of students’ written composition. The use of gadgets relative to the academic-related activities of the students should be properly monitored and supervised.
The lawsuit of the decade—Google LLC v. Oracle America, Inc.: a victory for interoperability and the future of innovation

Supreme Court of the United States, Google LLC v. Oracle America, Inc., Case No. 18–956, 5 April 2021 In its 6-2 ruling, the US Supreme Court ruled that Google’s use of Oracle’s programming code in creating the Android operating system was covered by the fair use doctrine, thus sparing Google from what could have been a nine billion-dollar damages award. On 5 April 2021, the US Supreme Court decided a case between Alphabet’s Inc’s Google and Oracle Corp, in which Google had been accused of copying 11 500 lines of Oracle’s Java programming language in the Android operating system. By upholding the jury finding that Google’s copying was a legitimate fair use, the Supreme Court sent a clear pro-innovation, pro-consumer message to the software industry and practically put an end to a legal battle between two technology giants that lasted over a decade. Since the case...
Human behavior recognition method based on second order motion description operator

Human behavior trajectory is often submerged in complex background, and it is easy to be disturbed. The traditional dense trajectory behavior recognition method has high track redundancy, so it has a large amount of calculation. A human behavior recognition method based on foreground trajectory and motion differential descriptor is proposed. Firstly, optical flow method is used to estimate the amplitude of moving object in each frame, and then the foreground region is found. Only the foreground region related to behavior is extracted. In order to better describe the relative time information between different behaviors, a motion difference descriptor is introduced to describe the foreground trajectory. By calculating the direction information of the unit time motion difference of the trajectory points, the motion difference direction histogram is constructed. Then, the histogram features are encoded by Fv (Fisher vector) to form feature vectors. Finally, the behavior is classified by support vector machine (SVM). The experimental results on the benchmark data set show that the proposed method can extract human motion trajectory better, and can improve the recognition accuracy compared with the traditional methods.
PENEROKAAN & PENGESAHAN INSTRUMEN PENERIMAAN APLIKASI FLIPGRID BERDASARKAN MODIFIKASI MODEL TAM DALAM PEMBENTANGAN VIDEO PELAJAR: ANALISIS FAKTOR PENEROKAAN (EFA)

This study aims to explore and validate the instrument of Flipgrid acceptance through Modified TAM Model in students’ video presentations. This study is a completely quantitative study that uses survey method using questionnaire procedure. A total of 256 students were involved as respondents in this study. The data were analyzed descriptively using Alpha Cronbach reliability and Explanatory Factor Analysis (EFA). There were 18 respondents have been removed due to outliers in normality analysis. The results of the normality achieved showed that Alpha Cronbach value was 0.974 which was more than 0.60. Results from the exploration factor analysis showed seven factors with Eigen values greater than 1.0. The KMO value (Kaiser-Meyer-Olkin) 0.954>0.6 indicated the items in the variable of Flipgrid acceptance sufficient for inter-correlation. While the Bartlett Test was significant (Chi Square 10295.506, p <0.05). No items were excluded and all the values of factor loading obtained were more than 0.50, a minimum value for new items. The total variance explained by the seven factors was 48.4% which considered as sufficient and acceptable as it did not exceed the minimum 50%. Thus, the overall findings showed that the items for the Flipgrid Acceptance through Modified TAM Model in students’ video presentation can be measured and answered research questions. A total of 44 items were validated and suitable for measuring the construct of Flipgrid Acceptance through Modified TAM Model in students’ video presentation.
A comprehensive analysis of adaptive image restoration techniques in the presence of different noise models

Any deprivation caused in the image signal can be thought as a noise. When any image signal is routed through wireless or wired medium it experiences deterioration because of channel characteristics. By knowing the type of noise interfered in the signal, we can use the pertinent filtering techniques to remove the noise from the image. Restoration of the image signal corrupted by noise is very essential for better communication. This paper provides the digital image handling techniques in MATLAB to restore the corrupted image. In this paper, different filtering methods have been discussed in the presence of two separate noise models that distort images. Four different techniques of filtering, ‘Mean/Average filtering', 'Median filtering', 'Adaptive median filtering' and 'Image Averaging' have been chosen against selected noise models. At the end of the paper we will compare which filtering technique works best for removing a particular noise.
Deceiving Computers in Reverse Turing Test through Deep Learning

It is increasingly becoming difficult for human beings to work on their day to day life without going through the process of reverse Turing test, where the Computers tests the users to be humans or not. Almost every website and service providers today have the process of checking whether their website is being crawled or not by automated bots which could extract valuable information from their site. In the process the bots are getting more intelligent by the use of Deep Learning techniques to decipher those tests and gain unwanted automated access to data while create nuisance by posting spam. Humans spend a considerable amount of time almost every day when trying to decipher CAPTCHAs. The aim of this investigation is to check whether the use of a subset of commonly used CAPTCHAs, known as the text CAPTCHA is a reliable process for verifying their human customers. We mainly focused on the preprocessing step for every CAPTCHA which converts them in binary intensity and removes the confusion as much as possible and developed various models to correctly label as many CAPTCHAs as possible. We also suggested some ways to improve the process of verifying the humans which makes it easy for humans to solve the existing CAPTCHAs and difficult for bots to do the same.
RLD Fisher Information Bound for Multiparameter Estimation of Quantum Channels

One of the fundamental tasks in quantum metrology is to estimate multiple parameters embedded in a noisy process, i.e., a quantum channel. In this paper, we study fundamental limits to quantum channel estimation via the concept of amortization and the right logarithmic derivative (RLD) Fisher information value. Our key technical result is the proof of a chain-rule inequality for the RLD Fisher information value, which implies that amortization, i.e., access to a catalyst state family, does not increase the RLD Fisher information value of quantum channels. This technical result leads to a fundamental and efficiently computable limitation for multiparameter channel estimation in the sequential setting, in terms of the RLD Fisher information value. As a consequence, we conclude that if the RLD Fisher information value is finite, then Heisenberg scaling is unattainable in the multiparameter setting.
PENGAMANAN PESAN MENGGUNAKAN ALGORITMA DATA ENCRYPTION STANDARD (DES)

Cryptography is an encryption technique, where the data to be encrypted will be encrypted using a key to become data that is difficult to read by other parties who do not have a decryption key. The DES algorithm is a symmetric block cipher cryptographic algorithm that uses a block size of 64 bits and a key size of 56 bits. In this study the DES algorithm will be used to encrypt messages. The result of this research is that the length of the file characters is directly proportional to the encryption and decryption process
Contrasting Big Bang with Continuous Integration through Defect Reports

Continuous integration promises earlier defect detection, quality improvements, and more customer value delivered faster. In this case study, we examined development of software for the advanced safety and driver support component of a Swedish vehicle manufacturer in two consecutive projects.
직업 목적 한국어교육 연구 동향 분석 - 언어 네트워크 분석을 중심으로 -

The purpose of this study is to analyze research trends of Korean language education for occupational purpose. For this research, the Research Information Sharing Service(RISS) collected paper related to Korean language education for occupational purpose, and collected a total 261 papers, including 209 academic papers and 52 academic journals. Based on the collected papers, the number of papers was analyzed by paper count course(year, time), network analysis(word cloud, frequency, centrality, word pairs, visualization), and topic modeling, respectively. Based on this, we identified the discussion points and future research trends of occupational Korean language education research. Research began in 2001 and has been focused on 'textbooks', 'development', 'plan' and 'analysis'. Looking at the word pairs, development-textbooks also appeared the most. According to the analysis of the topic modeling, the development and analysis of textbooks(60.5%), curriculum and measures(30.7%), and education status(8.8%) showed a ratio of about 6:3:1. As a result of the above analysis of research trends, I think that first, learners need necessary textbooks, second, development of textbooks for various occupational groups, and finally, the goal of improving learners' Korean language skills.
Chatbot For Disease Prediction And Treatment Recommendation

The hospital is a universal method by which any patient can undergo medical examinations, diagnose diseases and get recommendations for any type of treatment. Most people all over the world follow this custom. People have considered this to be the most suitable and authentic way to keep a check on their physical body state. The proposed system is to find another alternative to this formal way of having to visit a hospital and to make an appointment for a check-up or diagnosis with a doctor. This particular research study will help to apply the concepts of natural language processing and machine learning to create a chatbot application. Just like people interact with each other, here people can easily interact with the chatbot through a series of questions and doubts, meanwhile the chatbot will find and identify the person's symptoms and thereby can predict which disease the person is affected with and suggest the related remedies and treatment. This system can be proved to be of great use especially to people who have to conduct diurnal check- ups, It can also enable people to understand their health and encourage more people to take appropriate measures to maintain their health. This research also suggests that such a system is not very popularly used and people lack knowledge about this. Putting into action this framework can be of great help to people in avoiding long-distance trips to the hospital just by using this free app no matter where you are.
Comparison Of Different Feature Extraction Techniques In Telugu Dialects Identification

The Telugu language is one of the standard and historical languages in India. Like other spoken languages, the Telugu language also contains different dialects i.e., Telangana, Costa Andhra and Rayalaseema. The research in dialects identification (DI) work is very less as compared to other speech processing applications. For the research Dialect identification (DI) in Telugu language, database is very important, but there is no standard database. To carry out the research work in DI, we created the database of Telugu Language with different dialects and we anlyzed different feature extraction techniques to implement system. In this paper, we compare the performance of different models given by applying the different feature extraction techniques such as spatial, temporal, and prosodic features in Telugu dialect identification. We have applied different classification models i.e., K-Nearest Neighbour (K-NN), Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM). It is observed that GMM model provides good accuracy with MFCC+∆MFCC+∆∆MFCC and MFCC+PITCH +LOUDNESS features compare to HMM model.
High Quality Facial Recognition System

High Quality automatic face recognition System may be a web base application. A top quality face recognition System could be a technology capable of identifying or verifying an individual from a digital image or a video frame from a video source. There are multiple methods within which biometric authentication system work, but normally, they work by comparing selected facial expression from given image with faces within a database. it's also described a Biometric AI based application that may uniquely identify someone by analyzing patterns supported the person’s facial, texture and shape. We are using some different features also in our project. Example. Eyes or lips, some people have eyes in different shape or some people have little different, also the lips and nose are different. Means distance between nose and lips are difference off every one. So such features we use. Then in our project two phases are there the primary one is implementation of detection and second is recognition. Face Recognition has become a pretty field in Computer based application developed within the previous few decades. this can be thanks to the big selection of areas during which it's used. additionally, due to the wide various of faces, face recognition from database images, real data, capture Images.
Protecting the Perilous Path of Election Returns: From the Precinct to the News

We consider the vulnerabilities attending the reporting of election results to the public that arise because of the use of technology. Attacks on election reporting capabilities in Knox County, Tennessee in 2018 and Ukraine in 2014 illustrate many aspects of the challenges facing election officials as they try to protect the reporting of election results from malicious attacks. In considering the vulnerabilities that face American systems generally, we start by sketching out a generic description of the election-reporting system in the United States. This sketch highlights both the formal and informal flow of information through the reporting system. The information nodes themselves are vulnerable to attack, but more importantly, information flow at uneven rates, which provides raw material for those bent on causing chaos and undermining confidence in the vote counting. We conclude by considering what might be done to protect the election-return-reporting system against vulnerabilities. We frame that discussion in terms of NIST’s cybersecurity framework of “identification, protection, detection, response, and recovery.” Although there are technological fixes that can help to undergird resilience in this system, attention must be paid to the education of the public and the media about the contingent nature of the election results that are reported in the days immediately following Election Day.
Administrative Innovation Of The Deans Of Colleges In Baghdad Governorate

This research aims to identify the administrative innovation of the deans of the colleges in Baghdad governorate. To achieve the objectives of this research, we built the administrative innovation scale, which consisted of four main domains and (43) final items. The research sample totalled (304) of collaborators, i.e., deputy deans and heads of scientific departments. A set of appropriate statistical methods (SPSS) have been used for data processing. These include: T-test for two independent samples, a T-test for one sample, Pearson Correlation Coefficient, Alpha-Cronbach equation, measures of central tendency, measures of dispersion.Results revealed that the deans of the colleges of the universities in Baghdad province possess good administrative innovation and keep pace with the developments of the time.
Geochemical controls of platinum-group elements distribution patterns in the Patreef, bushveld complex, South Africa: a case study at Zwartfontein farm, Akanani prospect area

The Platreef, is a contact-type pyroxenitic reef in the Northern Limb of the Bushveld Complex, enriched in platinum group elements (PGE) and base metal sulfides (BMS). Relatively subdued mining in the Platreef, compared to RLS, has been attributed to limited knowledge regarding irregular distribution, complex style and genesis of PGE mineralisation in the Platreef. This study was, therefore, aimed at investigating the petrogenesis of the Platreef, particularly to evaluate whether the formation of the ore reefs resulted from a single or multiple sill-like magma intrusions. The study also sought to unveil the interplay of fractional crystallisation, hydrothermal fluid activities, floor rock and crustal contamination on the formation of Platreef types, PGE mineralisation and the magma source.