Reviewerly/exHarmony huggingface dataset:
Impact of big five personality traits on the talent- project managements in the Jordanian Northern Private Universities

Purpose – In this paper aimed to figure out the impact of the big five personality traits on the talent management in the Jordanian Private Universities – the northern region. The study used the descriptive, analytical approach due to its suitability to the current study. The sampling unit consisted of the administrative staff in these universities (n. 870) with a sample of 265 members. To collect data, a questionnaire was prepared based on the literature and previous studies examining the study variables, whose validity and reliability were checked. The study concluded that the big five personality traits represented in(extraversion, openness, conscientiousness, and neuroticism) are high among the employees in the Jordanian private universities and that the talent management represented in the (talent acquisition, talent development, and talent retention) are also high in the Jordanian private universities.&#x0D; The study results also showed a statistically significant impact at ( α≥ (0.05 for the big five personality traits with the dimensions of (extraversion, agreeableness, openness, conscientiousness, and neuroticism) on the dimensions of the talent management (talent acquisition, talent development, and talent retention) in the Jordanian private universities – Northern region .The study recommends the need to ascertain the importance of taking the personality traits in the administrative job into consideration due to their major role in talent management and focus on the importance of the talent management aspects in the Jordanian private universities.
Relationship Status Between Schools and Stakeholders: Basis for A Proposed Action Plan on Sustainable School – Community Partnership

This study aimed to investigate the current status of the relationship between schools and stakeholders in the District of Pagsanjan. A quantitative descriptive design was employed, and 288 respondents comprised of school heads, teachers, parents, alumni, local government officials, religious organizations, and non-government organizations were included in the study. Data were gathered using a researcher-made questionnaire. Results showed that the Feeding Program, Gulayan sa Paaralan program, and the Clean-up Drive Program of the Department of Education “Often” encouraged and engaged the school and stakeholders in active partnership. The current status of the relationships between the school and parents, local government officials, alumni, religious organizations, and non-government organizations were “Very Satisfactory.” It was concluded that the programs of the Department of Education have improved the relationship between the school and the community, and have created avenues for the school and community to address common concerns such as health, sanitation, and nutrition. Moreover, schools should involve all sectors of the community in their programs and convince stakeholders of the importance of their assistance in the education and learning process of pupils. Keywords: action plan, stakeholders, community partnership, DepEd programs
Family Factors Affecting Children's Reading Ability

Today, childrens reading ability is seen as an increasingly important personal skill, helping individuals to absorb information and export it as well. While a large number of studies have analyzed the effects of a specific family factor on children's reading ability, few review-type articles have summarized and generalized multiple influences. Thus, this paper analyzes the literature in the past 30 years on family factors that influence children's reading ability from 3 major mediating roles--family socioeconomic status, family cultural environment, and family psychological atmosphere. On this basis, this paper proposes multidimensional practical suggestions, for the family and society regarding the development of children's reading ability, which includes separate advice for children in lower grades and children in higher grades. Effective parent-participate cultural activities may especially work on the development of younger childrens reading comprehension, while the capability of independent reading is essential for children in higher grades. Finally, the author offers an outlook for future researchers.
Exploring the relationship between digital trails of social signals and bitcoin returns

Purpose This study aims to empirically investigate the linkages between digital trails of social signals (content and profile features of bitcoin-related tweets) and bitcoin price return using a VAR-BEKK-GARCH model. Design/methodology/approach Bitcoin-related tweets were collected every hour for six months from September 1, 2020, to February 29, 2021. The analysis involved two steps: first, examining tweet content, profiles, sentiment and emotions; and second, investigating the relationship between social signal volatility and hourly bitcoin price return. Findings Results indicate that bitcoin price changes can impact the sentiment expressed in tweets about bitcoin, and vice versa. While sadness exhibits a bidirectional volatility spillover with bitcoin, fear and anger display a one-period lag. Quartile analyses reveal that only fear in the second quartile shows a bidirectional spillover effect with bitcoin, while all other emotions except sadness demonstrate a unidirectional spillover effect in all remaining quartiles. Originality/value The study uses a novel two-step approach to analyze volatility spillovers between social signals and bitcoin price returns. Findings can guide investors and portfolio managers in making better allocation decisions and assist policymakers and regulators in reducing the adverse effects of bitcoin’s volatility on financial system stability.
Parameterized coherence measure

Quantifying coherence is an essential endeavor for both quantum mechanical foundations and quantum technologies. We present a bona fide measure of quantum coherence by utilizing the Tsallis relative operator (α,β)-entropy. We first prove that the proposed coherence measure fulfills all the criteria of a well defined coherence measure, including the strong monotonicity in the resource theories of quantum coherence. We then study the ordering of the Tsallis relative operator (α,β)-entropy of coherence, Tsallis relative α-entropies of coherence, Rényi α-entropy of coherence and l1 norm of coherence for both pure and mixed qubit states. This provides a new method for defining new coherence measure and entanglement measure, and also provides a new idea for further study of quantum coherence.
CLASSIFICATION OF COLOR BLIND STUDENTS AT SMA NEGERI 1 LHOKSEUMAWE USING NAÏVE BAYES ALGORITHM

This research aims to classify students and determine eye conditions with normal and partial color blindness by using Naïve Bayes algorithm. The research dataset was obtained from students at SMA Negeri 1 Lhokseumawe. The variables used in this research were 24 Plate Ishihara Tests with data collection techniques by using interviews, literature studies and questionnaires. Total data in this research are 140 data and divided into 110 training data and 30 testing data. The results showed that from 110 data trained, there were 69 students included in the normal group and 41 students included in the partial group. Then, the 30 testing data were tested into the classification system for color blind students using Naïve Bayes Algorithm. The accuracy level of the test results was 86.67% and 13.33% error.&#x0D;
Development and Pilot Evaluation of a Virtual Reality Healthcare Simulation Curriculum for Nursing Education: SLS with VR

Introduction.Over the last 15 years, simulation training has become a critical component of cultivating nursing knowledge, skills, and abilities (KSAs). In this study, we discuss the development and pilot evaluation of a next-generation VR simulation training system for nursing education, the Simulation Learning System with VR (SLS with VR). We also discuss the results of a pilot study of the completed system with 135 nursing students across 6 educational institutions.Methods.The project consisted of three phases: 1) selection of scenario content for implementation, 2) implementation and iteration of content, and 3) pilot testing and evaluation of the resulting curriculum. In the first two phases, an initial scenario curriculum was developed and implemented. Then, a pilot evaluation study was performed at six participating nursing education institutions and integrated into routine simulation learning sessions within the curriculum of each site, with data collected from learners and instructors via survey.Results.135 nursing students and 10 instructors across 6 institutions participated in this study. 82% of students perceived the VR simulations were “effective” or “extremely effective,” 14% were “neutral,” and 4% felt that the simulations were “ineffective” or “extremely ineffective.” The overall raw system usability score (SUS) rating from students was 71.64, which is in the “above average” category. Among the 10 instructors, 9 felt the simulations were “effective” or “extremely effective” and 1 felt the simulations were “ineffective.” The overall raw SUS rating from instructors was 75.0, which is in the “above average” category.Conclusions.We successfully demonstrated an approach to enhancing VR simulation training which achieved above average usability scores from both learners and instructors, with the vast majority of learners and instructors rating the simulation system as effective or highly effective.
Strong-Weak Cross-View Interaction Network for Stereo Image Super-Resolution

Recently, super-resolution (SR) performance has been improved by the stereo images since the beneficial information could be provided by another view. Transformer has shown significant performance gains for computer vision tasks, while it needs huge computing resources and training time. To alleviate this problem, we introduce an efficient Transformer feature extraction block, which can efficiently capture long-range pixel interactions with lower resource consumption. There are many kinds of cross-view interaction modules for stereo image SR, and they all have limitations of SR performance in their own models. To address the aforementioned challenge, we first propose the strong-weak cross-view interaction mechanism, which consists of strong cross-view interaction module and weak cross-view interaction module. Benefiting from the proposed mechanism, the SR performance can be improved significantly with a negligible increment of computing cost. We integrate the efficient Transformer feature extraction module and the strong-weak cross-view interaction mechanism into a unified framework named strong-weak cross-view interaction network (SWCVIN), and extensive experiments on three benchmark datasets show the proposed model achieves state-of-the-art results.
Supervised nonnegative matrix factorization model with fused correntropy for tumor recognition

Nonnegative matrix factorization (NMF) is a feature learning method that can achieve nonlinear dimensional approximate reduction with strong interpretation, and it is widely used in the field of tumor recognition. The objective function of the traditional NMF model is based on the Euclidean distance metric, and the performance of the model is easily affected by the noise. Moreover, traditional NMF is an unsupervised feature learning method that does not use the label information of the data. However, it would cause a waste of information without using label information and cannot learn the discriminative features in the data. Therefore, the supervised nonnegative matrix factorization model with fused correntropy (FCSNMF) is proposed in this paper. The FCSNMF model alleviates the effect of noise in the experimental data by fusing the Euclidean distance metric and the maximum correntropy metric. In addition, the label consistency regularization term is skillfully chosen to utilize the label information of the data to obtain discriminative features. The effectiveness of the FCSNMF model is verified by applying it to a gene expression profile dataset for tumor recognition.
Perancangan Mesin Pemutar Gerabah Dengan Kekuatan Tumpuan Maksimal 10 kg

Pottery is an art craft made from clay which besides having a high use value also has a pretty good aesthetic value. Pottery craft business has existed in Indonesia since ancient times until now. This business has a deficiency in the production machine part, where the production machine still uses human power as the main driving force during the rotation during the pottery making process. Therefore, a modification of a better pottery turning machine is needed to support the pottery craft business. The design of this pottery turning machine uses a working drawing design of a pottery turning machine product with a rotating speed that can be adjusted according to work requirements via a speed control pedal. The pottery turning machine has a strong construction with machine specifications of length 760 x width 400 x height 700 mm, with the addition of 2 pulleys with a first pulley diameter of 2.5 inches, and a second pulley diameter of 12 inches with a connecting belt using type A-57. And by using umbrella gears with a ratio of z1 = 25 and z2 = 50 with a maximum pedestal capacity of 10 kg.
THE METHOD OF POTENTIALLY DANGEROUS OBJECTS DETERMINATION, INVOLVED INTO POLLUTANTS EMISSION INTO RIVER BED

Abstract. This article describes a method of determination potentially dangerous objects, that could be involved in pollution based on the specified riverbed monitoring point. A way to solve the problem is considered through the filtration and sorting potentially dangerous objects list algorithm, which applies facts database, that allows to determine a possible rived bed potentially dangerous objects list. There are a number on software models and methods, which allows to determine an approximate or exact rived pollutant spill point in case of determining dangerous and/or rising pollutant concentration level from below downstream. Such methods work by forecasting the situation, or direct analysis of the natural environment. These methods make it possible to find the point of toxic substances spillage on the riverbed. However, it is not possible to find the enterprise/factory that made such an emission. Such problem mostly solved using analytical way. A method, which allows to determine a possible list of riverbed pollution potentially dangerous objects has been developed. Current development validation is a series of test checks and simulations that show the correctness of the neural network. A practical realization is implementation of the river pollution forecasting system in emergency situations informational system, to make a functionality, that determines a possible polluting object list based on the selected point of release of hazardous substances. Method can also be used with methods that allow to determine an approximate or exact rived pollutant spill point to find the enterprise/factory that made such an emission.
CASE-METHOD IN TRAINING BACHELOR DIRECTION "PEDAGOGICAL EDUCATION", PROFILE "MATHEMATICS AND COMPUTER SCIENCE" (ON THE BASIS OF THE USE OF DIGITAL RESOURCE «MATHEMATICAL MODELS IN THE ECONOMY»)

The relevance of the study is due to the lack of digital resources in various disciplines, with the help of which it is possible to form the research skills of future bachelors and the lack of methodologies for implementing the case method to form these skills using digital resources. The article proposes a methodology for the formation of research skills of bachelors in the area of «Pedagogical education, profile Mathematics and Computer Science» based on the case method using the developed digital resource «Mathematical Models in Economics». The general approach to designing cases for conducting a laboratory workshop on the discipline «Аpplication software» is considered. A system of cases for the study of economic models has been developed, options for using the software package in organizing individual, pair and group research activities, and evaluation criteria have been proposed. When organizing pair and group work, networking is used: cloud services and videoconferencing. The proposed methodology and the developed didactic support of the educational process make it possible to more effectively, in comparison with traditional teaching, form the research skills of students.
Visual tracking with confidence correction based on log-polar mapping

Transformer-based object tracking has become mainstream due to its high tracking performance at present. Most transformer-based trackers still classify the foreground and background and then calculate the bounding box by regression. However, we find that the classification confidence of transformer tracking is inaccurate. This leads to the bounding box with the highest confidence is not the closest to the ground truth. To address the problem, we propose a robust visual tracking approach with confidence correction using log-polar mapping. By correcting the confidence, the transformer tracking can obtain the best bounding box and improve the accuracy of the tracker. Extensive experiments on OTB2015, UAV123, and UAV20L show that our tracker is superior to the state-of-the-art trackers.
Klasifikasi Tingkat Keberhasilan Produksi Ayam Broiler di Riau Menggunakan Algoritma K-Nearest Neighbor

Livestock is a crucial component of the Indonesian agriculture sector. One of the most widely practiced types of livestock farming is broiler chicken farming. The production of broiler chickens continues to increase due to the increasing consumption of broiler chickens. Presently, companies are facing an urgent requirement to support farmers, regardless of their level of experience, whether they are newly entering the sector or have been established for some time. Core companies encounter challenges in modeling the success rate of broiler chicken farmer production because of the vast quantity of data coming from collaborating farmers, which makes it arduous for the company to establish the success rate of broiler chicken production. Establishing the level of production success is very helpful in selecting the appropriate farmers to be guided, thus enabling accurate decision-making. A classification procedure utilizing data mining and K-Nearest Neighbor (KNN) algorithm is necessary to manage the growing volume of data. The study examined 927 livestock production data from Riau, where the data was divided into two sets, with 80% allocated for training and the remaining 20% for testing purposes. The findings of the confusion matrix analysis showed that the optimal result was achieved at k = 3, with an accuracy rate of 86.49%, precision of 75.00%, and recall of 70.21%.
A Program Evaluation of M.Ed. English Language Education of Tribhuvan University

The purpose of this research was to review English language education program of Tribhuvan University using Stufflebeam’s CIPP model. The paper investigated university teachers’ and students’ perception on current curriculum of MEd in English language education based on CIPP model. Qualitative research approach was adopted to collect the data. Four research participants were purposely selected from Central Department of Education, Tribhuvan University. The study reports that University teachers’ are positive towards context and product process; but unsatisfied with process and input process. And the students’ are positive towards input and product process; but unsatisfied with process and context process. This requires an immediate attention on the part of curriculum designer and policy maker to internalize the strengths and weakness of the curriculum and redesign accordingly.
Bowl: Anyam Technique on Ceramic

Adding value to works of art is the subject of many discussions, and finding a new aesthetic can be accomplished by innovation and experimenting with the medium and techniques employed. This research attempts to make ceramics utilizing various embodied approaches similar to other manufactured materials. Specifically, bowl-shaped ceramics are formed using a woven technique similar to bamboo and then arranged in an interlocking pattern to resemble woven bamboo. The final result of this application technique is in the form of artistic bowls that have afresh aesthetic value for the development of ceramic art. These bowls are hollow due to the woven fabric and contain many values built-in to ceramic form, including material efficiency, organic form, and artistic form, which was previously unexpected. This serves as an accelerator for future application development of various shaping approaches. This confirms that the creative possibilities for plastic clay are virtually endless.
Multi-sectoral Community of Practice Amongst Librarians

Communities of Practice (CoPs) bring together practitioners who share a common interest and provide a forum for them to improve upon their practice. The City Librarians Community of Practice was formed in late 2019 to fulfil a professional development need among librarians across the city. Librarians from across sectors were invited to join in this multi-sectoral CoP with the intent of it being an opportunity for networking, collaboration, and sharing of best practices. Multi-sectoral communities of practice are not common in the literature, with most CoPs focusing on a narrow subject area of interest or being hosted by a single institution. This study reports on the results of a survey of City librarians, including those who became members of the CoP and those who opted not to join. The survey was intended to garner anonymous feedback on the CoP, to determine its benefits, and to identify potential areas for growth and improvement. While the CoP did not directly impact practice of its members, there have been perceived indirect impacts, including the sharing of information, hearing about librarianship issues from other perspectives, and affective, social elements. Many members preferred an informal, flexible approach over a more rigid, academic slant towards meetings. Regular communication and check-ins with members and potential members is another identified way of handling the natural attrition that comes with CoPs and to continue to keep the CoP relevant and engaging for the librarians of City.
Fake Currency Detection for Differently Abled People

Abstract: For people with visual impairments, identifying various currency denominations and fake currency is difficult. Even though special symbols are engraved on various denominations in India, the process is time-consuming for people with disabilities. The need for a handheld device to distinguish between different denominations and detect counterfeit notes stemmed from the lack of identification and fake detection tools. In this project, the features of the images are compared to all of the currency reference images. If the difference is less than a certain threshold, the numeric portion of the currency is extracted and compared; if it matches, the matched currency denomination is recognized. The 50, 100, 500, 2000, 20, and 10 Indian currency denominations are accepted. Using raspberry pi, the proposed model will automatically identify counterfeit currency and denomination in this project. Basic image processing, template matching, aspect ratio identification, the dominant colour, and feature extraction are all used to distinguish between counterfeit and denomination. Finally, to turn English text into a six-digit braille code, we use solenoid-based valves that are controlled by a Raspberry Pi.