Reviewerly/exHarmony huggingface dataset:
DEVELOPING AN EVALUATION INSTRUMENT FOR ASSESSING PUBLIC RELATION PRACTITIONER PERFORMANCE IN EDUCATIONAL INSTITUTIONS

This research aims at developing evaluation instruments to measure PR practitioners' performance in educational institutions.Operationally, the objectives of this study include:(1) developing components, indicators, and instrument items for evaluating PR performance in educational institutions, (2) examining the validity and reliability of the instruments, and (3) investigating the readability of the instruments which has been developed.To achieve this goal, researchers conducted Design and Development research by mixing quantitative and qualitative approaches.The subject of this research, in the first stage namely to design instruments, develop components and indicators, included 10 respondents who were chosen purposively consisting of evaluation experts (2 people), and PR practitioners (8 people).The second stage involved 12 respondents from public relations practitioners intended to reveal the validity and reliability of the instruments.The third stage, to know the readability of the instrument, involved 50 respondents from PR practitioners.The data were collected using Focus Group Discussion technique in the first stage and assessment sheet in the second and third stage.The data analysis technique in the first stage was an interactive analysis of Miles, Huberman, and Saldana (2014).To analyse the validity of the instrument, the researcher employed content validity based on the expert panel assessment, and analysed it with the Aiken V formula.The Cronbach Alpha coefficient criteria with at least 0.7 was applied for reliability test to determine the conformity between the results of the assessment carried out by two assessors (rater).The data analysis technique for examining the feasibility of the instrument viewed from the readability aspect is based on the mean score > 3.4 -4.2 out of 5 or in the feasible classification, referring to the conversion of quantitative data to qualitative data on a scale of 5.The results of the research were: (1) The components of PR practitioners performance in this research include fostering good relations with the internal public, promoting good relations with the external public, and improving the capacity of public relations practitioners; (2) 26 instruments meet the requirements for validity and reliability, the Aiken V validity coefficient is > 0.69 and the reliability coefficient is α = 0.978> 0.7; (3) The readability of instruments is in a good or appropriate category for use as indicated by the mean score of 3.91 out of 5.The implication of this research includes help ease school leaders, industry leaders, and policymakers to evaluate the performance of PR practitioners.
Performance Analysis of Query Terms during Query Phase in Virtual Databases

In early days, the queries may be executed by selecting query plans and linking throughout the execution. The main intention in such case may be to treat query execution as a process of streaming the tuples and systematize the query terms on the basis of tuples. The accuracy of routing of tuples may be obtained through semantic properties of the operators and implementation of join predicates. Considering the huge amounts of data in the dynamic environment, it may be required to locate and extract data implementing different techniques. The primary objective in this work may be to implement the virtualization along with conceptualization approaches to improve the throughput as well as turnaround time and to link to associated real databases. In such scenario, the virtual databases may be associated to enhance the computation capabilities of query plans by optimizing the performance and maintaining consistencies in the databases. Accordingly the query latency may be minimized.
ADR Brief

Alternatives to the High Cost of LitigationVolume 38, Issue 1 p. 2-16 ADR Brief ADR Brief Russ Bleemer, Search for more papers by this author Russ Bleemer, Search for more papers by this author First published: 27 December 2019 https://doi.org/10.1002/alt.21823Read 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 onEmailFacebookTwitterLinked InRedditWechat Volume38, Issue1January 2020Pages 2-16 RelatedInformation
Prediction of user Behavior through Web usage Mining

In real life, many users drew in towards online ticket reservation, so numerous transactions are in websites. A weblog includes sequences of entrances updating often by individual while opening the web site. Based upon the customer interest, it might be categorized as relevant &amp; unassociated information. The relevant information might be thought about as success feedback; however, unassociated data could be deliberated as failing reaction. It analyzes the pattern of individual navigating while searching, for that internet use mining have to be examined. The stages consisting for the procedure of internet usage mining are preprocessing, discovery of pattern, information collection, and pattern analysis. Along these steps this paper gave the user behavior analysis
Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map

This paper described a new method of obstacle mapping in an indoor environment utilizing a Grid-edge-depth map. The Grid-edge-depth map contained the information of distance and relative position of the object in the front of the robot. This mapping method utilized this information to mark off the visible obstacle/s in a particular virtual map. The 2D map created as a representative of the environment using a 300 by 500 pixels image. Every pixel represents a one by one cm of the environment and the obstacle's size. The obstacle's size was 30 by 30 pixels when it mapped by the system. It was a fixed size in the mapping process since the system cannot calculate the dimension of the detected obstacle. If the obstacle detected, the system checked its distance in GED-map. Then the system calculated the obstacle’s position against the goal, and finally map it in the 2D map. In this case, the proposed method in building a 2D map of the obstacle in the indoor environment combined with the rules to decide the direction of the mobile robot. The rules used to avoid the collision to the obstacle. The evaluation of the method showed that the system could map the detected obstacles, the initial position, and the goal’s relatif distance and position. The robot also reaches the goal position while avoiding the collision to the obstacle.
Secure Sum Computation using Threshold Encryption for Semi-Ideal Model

The need of preserving privacy of data arises when multiple parties work together on some common task. In this scenario each of the parties has to provide its sensitive data for a common function evaluation. But, the parties may be worried about the misuse of the data. Here comes the subject of Secure Multiparty Computation (SMC). The area where multiple cooperating parties jointly evaluate a common function of their data while preserving the privacy and getting the correct result is SMC. Here, we devise a new model and algorithm to compute sum of private data of mutually distrustful cooperating parties. We coin the term Semi-Ideal Model as it is hybrid of Ideal model and real model. The computation is secure on insecure network as well.
A Fuzzy AHP Methodology to Analysis the Impact of Employee Motivation in Manufacturing Industry

In this competitive era where employee’s performance and productivity decides his or her value, motivated employees stands on the top priority of every organization. This is because a motivated employee not only adds revenue to its organization but also helps in creating brand value as only a motivated employee can generate customer satisfaction leading to customer brand loyalty. In a developing country like ours Manufacturing sectors play a very important role in the economy of the country. Through its modern implements manufacturing sectors brought great changes in the traits of agriculture which helped the agricultural sector in modernizing itself by introducing various manufacturing tools. A motivated employee through his or her performance and productivity help the manufacturing sector lowering its cost of units produced which directly benefits the society as the product will be available to them in better quality and at cheaper rate. Thus, the performance of the employees in the manufacturing sector directly or indirectly influence the pricing policy of any product. Hence a motivated employee is way more necessary not only for the benefit of organization but for our economy and the society as whole.
Web and Browser Security

We now aim to develop an awareness of what can go wrong on the web, through browser- server interactions as web resources are transferred and displayed to users. When a browser visits a web site, the browser is sent a page (HTML document). The browser renders the document by first assembling the specified pieces and executing embedded executable content (if any), perhaps being redirected to other sites. Much of this occurs without user involvement or understanding. Documents may recursively pull in content from multiple sites (e.g., in support of the Internet’s underlying advertising model), including scripts (active content). Two security foundations discussed in this chapter are the same-origin policy (SOP), and how http traffic is sent over TLS (i.e., https). http proxies and http cookies also play important roles. As representative classes of attacks, we discuss cross-site request forgery, cross-site scripting and sql injection. Many aspects of security from other chapters tie in to web security.
Security Enhancement and Privacy Preserving Of Big Data

Big data is gaining the popularity among the data scientist and the people from the Biology related disciplines. Big Data is very huge in volume and comes very fast from various sources. Millions of tweets or posts are generated per second on social networking sites. Big data has many issues of i.e. nature, storing, management, and processing, privacy and security in disclosing of attributes of the sensitive data in data of healthcare etc. For maintaining the privacy there are k-anonymity, p-sensitive k-anonymity, l-diversity, t-closeness, and k-concealment ways. In this paper an anonymity algorithm is proposed which will be used to enhance the security and privacy preserving of sensitive attributes of big data.
ARTIFICAL INTELLIGENCE FACIAL EXPRESSION RECOGNITION FOR EMOTION DETECTION: PERFORMANCE AND ACCEPTANCE

The understanding of emotions has been an important research topic for many years dating back to almost 150 years to the work of Charles Darwin.Human emotion detection and recognition play an important role in everyday life as a fundamental part in interpersonal communication.Naturally, the relationship between detection and recognition is of high importance in the human computer interaction.Facial expression recognition (FER) systems are a computerbased technology that detects faces, codes expressions, and determines emotional states.This paper discusses the creation and reports the testing of a FER system to determine if machines could more accurately predict emotion than humans.In addition, this study seeks to determine perception of artificial intelligence facial expression recognition.The methods in this study included using a Haar-cascade classifier implemented by OpenCV 2.4.2.Results demonstrated that the AI FER system recognized emotions more accurately and that the human subjects considered the Artificial Intelligence Facial Expression Recognition systems trustworthy and beneficial.
REGIONAL SCHOOLS OF POLITICAL SCIENCE (AT THE EXAMPLE OF THE DEPARTMENTS OF HIGHER EDUCATIONAL INSTITUTIONS IN UKRAINE)

Федорчук О.О., кандидат історичних наук, доцент,
Research on application of cloud computing technology in blended learning based on access control model

Nowadays, with the rapid development of information technology, Internet informatization in the field of education is moving forward in continuous expansion. Educational informatization is an opportunity and challenge that must be met in education and teaching. The MOOC based on information technology based on cloud computing technology platform arises at the historic moment, the web-based storage resource and computing resource technology for large-scale high quality learning experience to create a new environment, and access control model covers all the entities in cloud computing, cloud computing access control is to ensure that the user security access to important aspects of cloud resources. The safe and effective implementation of blended learning is also achieved by cloud computing under access control. Through theoretical and practical analysis, this paper explores whether the blended learning supported by such technology is effective for college students who have more opportunities for independent learning, and studies the effect of blended learning by combining computer model and real questionnaire survey, in order to provide beneficial help for the innovation of education informatization in China.
Prestasi SMP Labschool Jakarta

Prestasi SMP Labschool Jakarta
Tracking Flooding Phase Transitions and Establishing a Passive Hotline with AI-Enabled Social Media Data

Flooding management requires collecting real-time onsite information widely and rapidly.As an emerging data source, social media demonstrates an advantage of providing in-time, rich data in the format of texts and photos and can be used to improve flooding situation awareness.The present study shows that social media data, with additional information processed by Artificial Intelligence (AI) techniques, can be effectively used to track flooding phase transition and locate emergency incidents.To track phase transition, we train a computer vision model that can classify images embedded in social media data into four categoriespreparedness, impact, response, and recovery -that can reflect the phases of disaster event development.To locate emergency incidents, we use a deep learning based natural language processing (NLP) model to recognize locations from textual content of tweets.The geographic coordinates of the recognized locations are assigned by searching through a dedicated local gazetteer rapidly compiled for the disaster affected region based on the GeoNames gazetteer and the US Census data.By combining image and text analysis, we filter the tweets that contain images of the "Impact" category and high-resolution locations to gain the most valuable situation information.We carry out a manual examination step to complement the automatic data processing and find that it can further strengthen the AI-processed results to support comprehensive situation awareness and to establish a passive hotline to inform rescue and search activities.The developed framework is applied to the flood of Hurricane Harvey in the Houston area.
I-THS-1908 A Big Data Electronic Health Record for Patient Care Management and Analytics

The I-THS-1908, a big data electronic health record platform, is capable of establishing its capability as an electronic health record to tackle the large volume of data with high velocity and complex variety of patient data by providing the value to the patient care management and analytics. The further development of I-THS-1908 opens the opportunity to use the electronic health record for patient care management and analytics for all type of health conditions.
How can geologic decision making under uncertainty be improved?

Abstract. In the geosciences, recent attention has been paid to the influence of uncertainty on expert decision making. When making decisions under conditions of uncertainty, people tend to employ heuristics (rules of thumb) based on experience, relying on their prior knowledge and beliefs to intuitively guide choice. Over 50 years of decision making research in cognitive psychology demonstrates that heuristics can lead to less-than-optimal decisions, collectively referred to as biases. For example, a geologist who confidently interprets ambiguous data as representative of a familiar category form their research (e.g., strike slip faults for expert in extensional domains) is exhibiting the availability bias, which occurs when people make judgments based on what is most dominant or accessible in memory. Given the important social and commercial implications of many geoscience decisions, there is a need to develop effective interventions for removing or mitigating decision bias. In this paper, we summarize the key insights from decision making research about how to reduce bias and review the literature on debiasing strategies. First, we define an optimal decision, since improving decision making requires having a standard to work towards. Next, we discuss the cognitive mechanisms underlying decision biases and describe three biases that have been shown to influence geoscientists decision making (availability bias, framing bias, anchoring bias). Finally, we review existing debiasing strategies that have applicability in the geosciences, with special attention given to those strategies that make use of information technology and artificial intelligence (AI). We present two case studies illustrating different applications of intelligent systems for the debiasing of geoscientific decision making, where debiased decision making is an emergent property of the coordinated and integrated processing of human-AI collaborative teams.
Trust for Knowledge Creation in Nepalese Hospitality Industry

This paper examines different factors promoting trust for knowledge creation in the hospitality industry such as hotel, travel and trekking agencies. The study is based on primary data with 382 responses. The self-administered questionnaires is used to collect the perceptive opinions from the respondents. The study concludes that hospitality industry employees’ the “honest and reliable team members” and “truthful employees” are most important factor to trust for knowledge creation while “employees have mutual faith in others’ abilities” influences less. There is no significant difference between response of gender, age groups, educational groups, work experience groups, marital status, current department and current position groups in the context of trust.
THE METHOD PROBLEM IN THE CONTEXT OF PSYCHOLOGICAL KNOWLEDGE INTEGRATION

In psychological science, the «method problem» remains one of the most fundamental and relevant, and a new content shade of this problem is associated with the activation of discussion on the psychological knowledge integration. In this context, the problem acquires an updated content as a problem of a universal method in psychology. There is a reason to believe that the «method problem» is transformed into the «universal method problem» and then into the «universal method integration problem». The efforts to solve these problems are often depreciated due to the ignorance of experimenting and practicing psychologists by methodological knowledge. The possible way to build a universal method for theoretical research in psychology is to use for this purpose a procedural interpretation of theorizing based on set-theoretic process description method. In the article components of theoretical research are considered as the purpose, object, subject, hypothesis of the research, as well as the considered empiricism, theoretical foundations, method of theorizing and research tasks. Two methodological «poles» of theoretical research are identified – the «normative» method and modern research methods, and a variant of analyzing their structures is proposed. To create a universal method suitable for psychological knowledge integration is associated with obstacles, which can be overcome by their systematic analysis. The article outlines a variant of this analysis, in which the causes and sources of these obstacles are differentiated based on the system of concepts used for describing processes. The sources of integration obstacles include components of prototype modi, and the causes are properties of modi functions in the recording of processes as maps of sets. The examples describe the integration obstacles at the two levels of interactions.
Usability in computerised mobile assistance solutions

The awareness of the importance of system usability is in a constant boosting. Considering usability has been more and more recognised as one of the indispensable quality factors in the success of an interactive system. This paper explores in this direction the importance of usability in context-aware user interface design for computerised mobile maintenance solutions. We propose a methodology for incorporating contextualised usability requirements in the development process of mobile applications in industrial maintenance sector. An illustrative case study is presented in a typical industrial environment to validate our proposal. Finally, an experimental evaluation was conducted with end users to evaluate our proposal.
The Performance of English Department Students in Retelling Story (An Anthropolinguistic Study)

The purpose of this research was to find out the performance of English department students in retelling story. The research was using anthropolinguistic approach. The data were utterances of the performances, interview sheet, audio-video recording and observation sheet. The data were collecting by using Sony HD-AVCHD 9.2 MP Handycam, through interviews and observation. The data were analyzed by using interactive model, namely: data displays, data condensation and drawing conclusion/verifying. This research analyzed text, co-text, and context of retelling story and the components of retelling story. The research result showed that the performance of students in retelling story was lack of self-confidence and nervous. It is showed from their body movement and gestures. The performance of students was classified to three parts namely: opening, core and closing (formal situation). The components of retelling story include Actor, Audience, Situation and learning organization, convention and skill of learning.
Speech Recognition Implementation

This paper presents a brief review on Automatic Speech Recognition and provide a technical understanding of ASR system. The objective of this review paper is to elaborate one of the best techniques in the field of speech recognition that is hidden Markov model. Hidden Markov model is very popular technique for speech recognition because speech signal is more like piecewise stationary or short time stationary signal and these models can be trained easily and they are computationally feasible. So, this paper gives a proper implementation of hidden Markov model. After so many years of research, the main challenge in speech recognition field is accuracy. The speech recognition system includes feature extraction, building word template, comparing word and selecting the best with maximum likelihood. Hence, this paper will give a great contribution for understanding the concepts of Automatic Speech Recognition system and hidden Markov model.
Remote navigation signal management and monitoring software development based on data collected from AIS and ENC

The Navigation signal management and monitoring requires a lot of information and needs continuous operation in order to assure the navigation safety, therefore, the signal need to monitoring and managing. To monitoring and managing the navigation signal and navigation control, there are several methods applied such as directly operation by workers, by sensor or by remote control through AIS. Based on the data collected from AIS and ENC, the research group has developed the remote navigation signal managing and monitoring software through the internet. This paper describes the process of the software design and development.