Reviewerly/exHarmony huggingface dataset:
The Mediating Role of Organizational Commitment between Organizational Culture and Job Performance in the Telecommunication Sector

This study investigates the impact of organizational culture on job performance and finds the mediating role of organizational commitment among telecommunication employees. The study analyzed 476 valid questionnaires from the employees of three telecommunication companies in Erbil, Iraq. However, the data was analyzed by Smart-PLS. The results indicated that the direct impact of organizational culture on job performance showed a positive and significant impact. Besides, the mediating role of organizational commitment can enhance and increase the impact of organizational culture on job performance among employees in the telecommunication sector. Furthermore, individuals in the workplace will exhibit different behaviors due to the deployment of culture-based strategies for behavior development. Therefore, job performance will increase if individuals and the workplace culture are in sync.
3D Model – Furnish the GreySpace

E-commerce is booming at a breakneck pace in this internet age. People in the industrialized world, as well as an increasing number of people in the developing world, now make daily purchases through e-commerce websites. Even Nevertheless, the spread of e-commerce in the developing world is still limited, and there is much to be desired. Ecommerce combined with the Augmented Reality is a boom to the growing technology. This paper, discusses the various facets of establishing an e-commerce website along with the Augmented Reality by giving the customers/users a realistic experience of the products they intend to buy. The database architecture is also examined, with a focus on relational connectivity. This approach to building an e-commerce website with the Augmented Reality can be simply copied and followed in establishing e-commerce websites in emerging and under- developed countries where resources are limited and expensive due to socio-economic factors. This paper presents the design and implementation of an e-commerce system based on React and AR to make online purchasing more convenient. It primarily covers the online shopping program, online payment, order generation, and product viewing in AR. Keywords— E-commerce, Augmented Reality, 3D, database architecture
Detection and tracking of weakly emitting point objects based on the analysis of a sequence of miniseries of images

This paper discusses the problem of detecting and tracking moving, weakly emitting point objects. It is proposed to solve it by using a sequential two-stage method of processing miniseries of images (frames) obtained by an optoelectronic system. The proposed method includes an original procedure of interframe processing of miniseries of images, a feature of which is to operate with two lists of objects: the main list and an intermediate (buffer) list. The indicated lists are updated after each miniseries of images is processed. The buffer list of objects in this case plays a subsidiary role and is used to filter out (eliminate) the false signals that appear during frame processing of the images. The use of the proposed interframe processing procedure makes it possible to work with low-SNR images, and this is regarded as a substantial advantage of the well-known track-before-detect method. Statistical experiments using miniseries of model frames confirm that the proposed method is workable.
ZIMBABWE: Fixed Exchange Rate Abandoned

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 57, Issue 5 p. 23018B-23019C Policy and Practice ZIMBABWE: Fixed Exchange Rate Abandoned First published: 09 July 2020 https://doi.org/10.1111/j.1467-6346.2020.09541.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume57, Issue5July 2020Pages 23018B-23019C RelatedInformation
Combining Federated Learning and Edge Computing toward Ubiquitous Intelligence in Internet of Things

The rapid development of Internet of Things (IoT) enables a huge amount of data collected from the physical world and then processed by various machine learning-based applications.The highly disperse nature of the big data sources and widely distributed AI applications calls for ubiquitous intelligence in the IoT.Federated learning is an emerging collaborative machine learning approach that allows the highly diverse data generated in IoT to be leveraged for achieving ubiquitous intelligence.Edge computing deploys decentralized cloudlike computing capabilities at the network edges thus offering a platform that may greatly facilitate federated learning in IoT.This talk attempts to present a holistic view of federated learning and edge computing combined toward enabling ubiquitous intelligence in IoT.The state-of-the-art technical developments that allow federated learning to fully leverage edge computing and enable edge computing for supporting federated learning are reviewed.The talk will also discuss open issues and challenges in this area and identify some possible directions for future research.
Personality Difference Associated with the Information Security Performance of Employees’ in the Information Network Security Agency (INSA)

Now a day information security (InfoSec) is a prime focus and critical aspect of all organizations as well as individual users.The major purpose of this study was to assess the association between employees' personality difference and InfoSec performance in the Ethiopian, INSA context.Accordingly, the five-factor personality difference (OCEAN) was treated as the independent variable, while the InfoSec performance was treated as a dependent variable.Based on the quantitative approach, a correlational research design was employed.A total of 320 participants were selected using a stratified random sampling technique.The BFFI and ISP scales were administered to collect the quantitative data.The Independent t-test, one-way ANOVA, Pearson Correlation, and hierarchical multiple regression data analysis methods were performed to address the research questions.Accordingly, the present study revealed the following findings.Firstly, employees InfoSec performance significantly differed by their sex, level of education, job positions, and length of InfoSec training taken.Secondly, age, work experience, and personality difference were significantly related to the employees InfoSec performance.Thirdly, employees' personality difference significantly predicted their InfoSec performance both independently and jointly.Generally, personnel recruiters, employers, trainers, and interventionists were recommended to consider their candidates' background characteristics and personality difference when they deliver their services.
Challenges in implementing extensive reading (ER) programs: Voices from English teachers at Indonesian secondary schools

This article reports on the implementation of extensive reading (ER) among English teachers of secondary schools and the challenges they face as a part of their efforts in supporting the Indonesian government program of school literacy initiative (SLI).The data were obtained from an online survey to a group of English language teachers (N = 22) from 22 different schools in one regency in East Java Province, Indonesia.The survey was then followed by a focused group discussion (FGD).The results show that in general, English teachers have a relatively good knowledge of ER as one way to support the success of SLI, but not all of them implement the programs due to such challenges as lack of support from the government and school administration, the overwhelming workload, and the unavailability of ready-to-use materials and activities.There is, therefore, a definite need for the government and school administration to support the implementation of SLI through ER by giving teachers and students necessary provisions, such as graded readers and structured ER activities.
The Antecedents and Consequence of Supplier Unethical Behaviour in Buyer-Supplier Relationship in Tanzania: Testing using the PLS Approach

Using social exchange theory, this paper investigates the antecedents of supplier unethical practices on continuity of buyer-supplier relation and its consequence on firm performance.The analysis of 130 informants from public entities in Tanzania, the results indicates that two supplier's unethical practices have significant impact on the continuity of buyer-supplier relation which include corruption and supplier deceitful.Using the mediating role continuity of buyer-supplier relationship, the study indicates that corruption and deceitful affect the firm performance (quality and delivery).The research conclude that the public entities should be very careful on the effects of unethical practices on continuity of relationship and managers in public organizations should not take for granted particularly the corruption practices and deceitful.This study provides insightful contribution to practitioners and researchers intended to conducted research on ethical supply chain.
Smart Hospital Chatbot-Virtual Doctor Consultation and Appointment

Healthcare services face a huge challenge of supply-and-demand which you can fix when we create a digital platform. In the traditional healthcare system, patients would go to the hospitals, and they always have to wait for appointments and medical reports. Also, conversation between doctors and patients about their health status and daily lives is not fully remembered by the doctor as well as patients. So, to improve the doctor-patient interaction, we will design and implement a machine learning framework that contains a chatbot, voice transcription and other functionalities. The proposed Medical Chatbot can interact with the users, giving them a realistic experience of chatting with a medical Professional. Our motive is to show that the proposed medical chatbot could be a better alternative to many already existing chatbots in the domain of medicine. An Al enabled conversational UX can deliver personalized experiences to your patients for identifying the illness, scheduling doctor appointments, notifying caregivers about symptoms, monitoring the health status, updating the homecare assistant from time-to time and more. Also, the proposed system converts the voice to text first and then generates prescriptions automatically by extracting the keywords and provides the prescription in the desired format automatically. This system can also generate prescriptions efficiently with just the audio file of the conversation between the doctor and the patient through a phone call.
IP Packaging Filtering in Computer Networks Using Artificial Intelligence in the Regulatory Authority of Electronic and Communications Kosovo

The security of our data is one of the most important challenges, and it is one of the things we must be careful about what we display on the Internet. For the security of this data, computer and cyber networking experts use different methods to prevent these attacks, prevention is done by Firewall techniques, and then by Router where both of these cases are quite popular nowadays today, however, another innovation is that filtering can also be done through Artificial Intelligence. In this paper, research has been done on the application of Artificial Intelligence methods such as those of deep learning on IP packages through Artificial Intelligence where specifically the method of Support Vector Machine with the training of a model through a simulated input corpus, using MATLAB software. From the results of the research by Artificial Intelligence, the source address, destination address, port number, protocol and package size were used as filters. All the practical work was done in over 350 different IP addresses, where 175 IPs were used for algorithm training, as well as 175 IPs were used for testing by combining them with filtering attributes, where in the end the filtering accuracy gained is quite high (83%).
Research on Automatic Extraction Method of Complex Web Page Data

A simple, sensitive and cost effective visible spectrophotometric method has been developed for the determination of Valsartan from bulk and tablet dosage forms.The method is based on the formation of green colored coordination complex by the drug with cobalt thiocyanate which is quantitatively extractable into nitro benzene with an absorption maximum of 605nm.The Regression analysis of Beer's Law plot showed good correlation in a general concentration range of 0.5 -3.0 ml, 400µg/ml with correlation coefficient (r= 0. 992). The proposed method is validated with respect to accuracy, precision, linearity and limit of detection. The suggested procedure is successfully applied to the determination of the drug in pharmaceutical preparation, with high percentage of recovery, good accuracy and precision. The results of analysis have been validated statistically by repeatability and recovery studies. The results are found satisfactory and reproducible. The method is applied successfully for the estimation Valsartan in tablet form without the interference of excipients.
Research on Crime Scene Investigation

This study was conducted to predict the tourists' arrival in the Island of Boracay, Malay, Aklan, Philippines.It adopted the developmental type of research, for it is aimed to come up with a system to predict the arrival of tourist per year and determine the factors affecting such visit. It made use of Linear Regression technique in order to predict the arrival of tourists per year. It was found out to be precise and reliable. Also, it utilized the Multiple Linear Regression Technique in order to know the factors affecting the tourists' visit in the island. These mathematical tools are accorded with Linear Probability Plot, Normal Probability Plot, and Probability Plot. These were used in order to test the reliability of the variables used in the study, especially the 4 'As' of tourism which include, amenities, accommodation, accessibility, and attraction. It was found out that the use of this technique was found to be significant. Residual Plot Analysis was used in the study and found out to be effective and accurate. As proven, the results of the study would validate that when plots are scattered in the horizontal axis would mean that the analysis is found to be precise. Line Fit Plot Analysis was also used in the study, which proved that if there are increasing values of scattered points, it shows significant correlation between the independent and dependent variables. Normal Probability Plot was further utilized where it was proven that if the data are plotted in a theoretical normal and typical distribution in the sample percentile with regards to the number of tourists' arrivals form an approximate or estimated straight line. The general objective of the study was to develop an online application that will predict the tourists' arrival using regression techniques. Specific Objectives: 1. Apply linear regression to predict the tourist arrival per year.2. Implement multiple linear regression to determine the factors affecting tourists' arrival.3. Integrate these regression techniques to the developed online application. Findings: Linear Regression Analysis was used to predict the arrivals of tourists and was found out to be precise and reliable. Multiple Linear Regression Analysis was also utilized to determine the factors affecting tourists' arrivals. This was used in order to test the reliability of the variables used in the study, especially the 4 'As' of tourism which include, amenities, accommodation, accessibility, and attraction. The results proved that the use of this technique was found to be reliable and significant.
An Improved of Accuracy in Soft Tissue Tumor Classification with Random Forests

The tumor is cells that grow out of control in the human body. In this paper, we will focus on Soft Tissue Tumour (STT) which belongs to a group of neoplasms that can cause particular problems in their diagnosis and/or treatment. Zahras, Rustam and Sarwinda (2019) and Rustam, Hartini, Siswatining, Utami and Nadisa (2020) classified STT by using data from Nur Hidayah Hospital, Bantul, Yogyakarta, Indonesia, based on 19 variables and Support Vector Machine, Fuzzy Kernel C-Means, Fuzzy Kernel Possibilistic C-Means as classifiers. Furthermore, this research is novel with used random forest. The result obtained is shown the percentage of accuracy, both in training and testing of random forest, which was 100%. This result shows the best accuracy in contrast with the prior method, even though only 60% of training data set was used. The rare disease needs a method that can only use less percentage of training data, so this is very important.
Blockchain privacy consensus mechanism based on threshold signature

Various industries have proposed to use blockchain technology to solve their own difficulties, but because the underlying database is completely open, user identities and transaction information are at a glance, and privacy leaks are serious. In the blockchain, transaction data is required to be verified by most users before it can be put on the chain. In order to ensure the correctness of the data on the chain, a blockchain privacy consensus mechanism based on threshold signatures (PBTS) is proposed. Under the premise that miners cannot access the plaintext of transaction transactions, the blockchain can still supervise and review the data to reach a consensus.
Information Behavior of Mothers during Pandemics: The Case of COVID-19

The study aims to investigate information behavior of pupils' mothers during COVID-19 pandemic.The study deployed a qualitative approach using semi-structured interviews.The sample of the study consisted of 24 mothers.The data analysis revealed three major themes of mothers' information behavior; these are information needs, exploration and monitoring.The results of this study identifies several implications.First it bridged the gap between theories of information behavior and the various models available and practice of information behavior during pand,emics, particularly mothers' behavior.The study presented suggestions to policymakers and governments in aiding mothers with appropriate support they need in the context of pandemics and public health emergencies.
Does Resource Richness, and Good Governance Institution Are Grace for Human Capital Development in Sub- Saharan African Countries?

Human capital development is acquiring of individuals competence via schooling and incentive-based training.To conduct this study panel data type from 2005-2018 and analysis dynamic panel model has been used.The study authenticated the grace of good institution and disgrace resource on human capital.The study verifying that good governance institution attributed by exercising power based on the principles and meritocracy is gracing human capital.But resource richness is not a guarantee to enhance human capital rather it is a means to ineptitude.Given that the researcher recommended as, a responsible bodies in sub-Saharan African countries should be sound institution that enhance good governance via formulate good governance principles, and develop resource merit institution in the favor of human capital development.
English Language Teaching (ELT) and Evaluation at Higher Secondary Level

Evaluation is the important phase in the process of teaching learning of English as a Second language. It provides feedback to both the teachers and students. But it is a neglected area in our teaching learning process. Our syllabus is completely silent on method of evaluation. The teachers are left to evaluate in their own way which is often affected by individual teacher’s personality, approach and attitude. Teaching mode is a dominant aspect in our teaching learning process. Because of teaching mode our teachers evaluate what the students have not learnt and try to find out errors made by the students so that there will be a scope for teaching. This negative approach to evaluation demotivates our learners and the teaching mode prevents our teachers to switch over to other method of teaching/learning according to the feedback received from evaluation. So there is a need for effective teacher training programme to make the teachers aware of the objectives of evaluation and the method to be followed to evaluate the language skills of the learners.
PROJECT AND RESEARCH WORK OF LEARNERS WITHIN THE ONLINE LEARNING MODULE IN THE ALTERNATIVE EDUCATIONAL ORGANIZATION IN THE CONDITIONS OF DISTANCE LEARNING: PROBLEMS AND OPPORTUNITIES

The article deals with the experience of organizing project and research activities of learners by means of the online learning module in the context of distance learning in the alternative educational organization International Child Center “Artek”. The peculiarities of work of learners using the project and research map “Navigator of Senses” in a distance format are considered. The article describes the essence and structure of the project and research map “Navigator of senses”.
Optimization of System Authentication Services using Blockchain Technology

With the development of the era, one thing that must be considered for security is the Login System. In most cases, user login information is stored on the server. This gives access to sensitive informatio, many hackers easily break into data from users. Based on these problems, this research focuses on data security authentication in the form of usernames and passwords in the login system. Authentication using blockchain is used to reduce malicious access and increase security for the authentication process. One of the innovative technologies that can solve these problems is Blockchain Technology. Using blockchain technology, hackers will find it difficult to change and modify the same data on all computers at the same time because it takes a very long time to crack the encryption code on each block of data in the entire computer network. Data storage or transactions in the blockchain are stored in the form of hashes. This makes it difficult for hackers to break into it. Tests in this study using Wireshark tools and network miner. Based on the research conducted, the test was conducted as many as 5 times with two scenarios, namely authentication of the login system before using the blockchain and after using the blockchain. The results obtained. The, system built using blockchain can secure data. The test results obtained that data in the form of usernames and passwords were converted into hashes and with the immutable nature of the blockchain, data from users could not be changed or replaced by anyone.