Reviewerly/exHarmony huggingface dataset:
Prevalence of shifted Rayleigh filter for passive surveillance in underwater

Purpose From many decades, bearings-only tracking (BOT) is the interested problem for researchers. This utilises nonlinear filtering methods for state estimation as there is only information about the target, i.e. bearing is a nonlinear measurement. The measurement bearing is tangentially related to the target state vector. There are many nonlinear filtering algorithms developed so far in the literature. Design/methodology/approach In this research work, the recently developed nonlinear filtering algorithm, i.e. shifted Rayleigh filter (SRF), is applied to BOT. Findings The SRF is tested for two-dimensional BOT against various scenarios. The simulation results emphasise that the SRF performs well when compared to the standard nonlinear filtering algorithm, unscented Kalman filter (UKF). Originality/value SRF utilises the nonlinearities present in the bearing measurement through the use of moment matching. The SRF is able to produce the solution in highly noisy environment, long ranges and high dimension tracking.
Impact of formative assessment on autonomous learning in times of covid-19

In 2020, face-to-face education ceased to be applied in colleges and higher education entities, starting virtual education in the framework of the health emergency caused by Covid-19. The research had a non-experimental design, cross-sectional causal correlation. The sample consisted of 405 high school students, selected by random non-probability sampling. Questionnaires were used for both variables measured with a Likert scale from 1 to 5 points; both with 19 items; The first was the SAFL-Q formative assessment scale for students, it has five dimensions; the second was the adapted CETA self-learning questionnaire for students, which has six dimensions. The first questionnaire has an acceptable reliability value (Cronbach's Alpha = 0.941, 95% CI) and the second, self-regulated learning with an acceptable reliability value (Cronbach's Alpha = 0.946, 95% CI). The results indicate that formative assessment significantly influences autonomous learning and its dimensions respectively.
The impact of corporate social responsibility practices on competitive advantage: Vietnamese evidence

This paper analyses the values and effects of corporate social responsibility practices on organisational competitive advantage. The survey was sent to 869 respondents at different levels of manage...
Social Skills of Higher Education Students in Times of a Covid-19 Pandemic

The present work is oriented to review research related to social skills developed by university students in times of covid-19 pandemic. Understanding the management and development of social skills in the process of social interaction is relevant in the university environment to obtain an adequate professional performance. Within the framework of the results, subcategories such as strategies for the development of social skills, interpersonal relationships, collaborative work and self-esteem emerged; all of them revealing that there are, visibly, young people with social deficiencies vulnerable to depressive states or lack of self-esteem. Among the conclusions it is highlighted that, as long as an efficient social development is achieved, at the same time, the student's integral growth will be reinforced; only in this way, the deficiencies in social skills will be overcome.
3rd Pharmacoeconomics and Outcomes Research Virtual Conference 2021

3rd Pharmacoeconomics and Outcomes Research Virtual Conference 202121st – 23rd September 2021
End-to-End Correlation Tracking With Enhanced Multi-Level Feature Fusion

Discriminative correlation filters (DCF) have drawn increasing interest in visual tracking. In particular, a few recent works treat DCF as a special layer and add it into a Siamese network for visual tracking. However, most of them adopt shallow networks to learn target representations, which lack robust semantic information of deeper layers and make these works fail to handle significant appearance changes. In this paper, we design a novel Siamese network to fuse high-level semantic features and low-level spatial detail features for correlation tracking. Specifically, to introduce more semantic information into low-level features, we specially design a residual semantic embedding module to adaptively involve more semantic information from high-level features to guide the feature fusion. Furthermore, we adopt an effective and efficient channel attention mechanism to filter out noise information and make the network focus more on valuable features that are beneficial for visual tracking. The overall architecture is trained end-to-end offline to adaptively learn target representations, which are not only enabled to encode high-level semantic features and low-level spatial detail features, but also closely related to correlation filters. Experimental results on widely used OTB2013, OTB2015, VOT2016, TC-128, and UAV123 benchmarks show that our proposed tracker performs favorably against several state-of-the-art trackers.
Analisis Metode Forward Chaining Pada Sistem Pakar Diagnosa Penyakit Hewan Sapi Berbasis Android

In particular, Sorong Regency, West Papua, where the availability of veterinarians is still relatively low. The problems that occur in the regency make it difficult for experts to deal with a disease that occurs in livestock, especially cattle. This also makes it difficult for people to diagnose certain diseases experienced by their livestock, so that handling becomes slow and resulting in the risk of death for livestock. This research aims to create an application system to diagnose cattle disease base on android to make it easier for breeders to diagnose symptoms of a disease that occurs in their cattle (cow). The process carried out is by interviewing experts consisting of three paramedics, the results obtained are in the form of disease data, symptoms, and solutions which are used as data on the system. The data that has been analyzed using the Forward Chaining method results in an android-based expert system, help breeders’ difficulties in diagnosing cattle diseases. The results obtained are that the system created to produce a disease that is in accordance with the exiting symptoms. The system is very helpful for farmers in Sorong Regency, they hope that ini the future the system can be updated if there are new diseases or symptoms. The data provided by animal husbandry department and experts are very helpful in this research.`
A Systematic Mapping Study of Empirical Studies Performed with Collections of Software Projects

Context: software projects are commonresources in Software Engineering experiments,although these are often selected without following a specific strategy, which reduces the representativeness and replication of the results. An option is the use of preserved collections of software projects, but these must be current, with explicit guidelines that guarante etheir updating over a long period of time. Goal: to carry out a systematic secondary study about the strategies to select software projects in empirical studies to discover the guidelines taken into account, the degree of use of project collections, the meta-data extracted and the subsequent statistical analysis conducted. Method: A systematic mapping study to identify studies published from January 2013 to December 2020. Results: 122 studies were identified, of which the 72% used their own guidelines for project selection and the 27% used existent project collections. Likewise, there was no evidence of a standardized framework for the project selection process, nor the application of statistical methods that relates with the sample collection strategy.
Principles and Characteristics of Quantum Computing

Abstract With the rapid development of science and technology, people tend to have a higher demand for computing. Classical computers can no longer meet part of the computing needs, so quantum information systems have gained more and more attention. Quantum computers have good parallelism, fast information processing speed, large amount of information storage, and performance in many fields far surpasses classical computers. In this article, the author introduces coherent superposition and part of quantum gates and quantum algorithms meanwhile compares classical computers with quantum computers in many aspects. The advantages and disadvantages of quantum computers in principle are also drawn out. Finally, the author proposes future prospects for quantum computers prediction.
video Editing Theory hand out By melaku Alemnew pdf

Editing may be thought of as the coordination of one shot with the next. The film editore liminates unwanted footage, usually by discarding all hut the best terke. The editor also cuts super fluolts trames, such as those showing the clapboard.
A Novel Based 3d Facial Expression Detection Using Recurrent Neural Network

People periodically have diverse facial expressions and disposition changes in this way. Human facial expression acknowledgment plays a really energetic part in social relations. The acknowledgment of feelings has been an dynamic breakdown point from early age. The real-time location of facial expressions like appall, upbeat, pitiful, irate, anxious, astonish. The proposed framework can recognize 6 diverse facial expression. A facial expression acknowledgment framework needs to perform location and change to 3D image, then the facial highlight extraction, and facial expression classification is worn. Out proposed strategy we should be utilizing Recurrent Neural Network (RNN). This RNN show is prepared on JAFEE and Yale database dataset. This framework has capacity to screen individuals’ feelings, to segregate between feelings and name them fittingly.
Using Meta-reasoning for Failure Detection and Recovery in Assembly Domain

Author(s): Parashar, Priyam | Advisor(s): Christensen, Henrik I; Goel, Ashok K | Abstract: Industrial robots have remained the fastest-growing market, within the overall robotics industry sales, in recent times. These robots have shown that when tasked with repetitive, structured tasks under controlled constraints they can contribute to society by ensuring consistent quality and significantly bringing down amortized costs. However, the requirements of the sector itself are moving towards a future where a high mix of customization with production of each type is of value. This high-mix, low-volume setting brings a number of realistic, but yet unattainable, robotics challenges which are summarized by the overarching question of how to transfer known plans for a given task to a similar environment but different in a number of ways?We formulate this as a question of which revises the original plan based on new or contrary observations made by the robot during execution. We assume a nominal plan and base demonstrations for grounding it and solely focus on the problem of how to: autonomously monitor a system for failures, localize the cause of said failure, and recover by repairing the original assembly plan. The recurring theme in this endeavor has been tackling failures of different kinds and at different levels of planning which decrease the overall robustness of the system. We observed that by contextualizing failures using the knowledge of how the task progresses in nominal conditions we were able to reason about the pathology of it and implemented different recovery procedures in our execution framework to deal with them accordingly. This thesis sets out to validate the claim that: Use of meta-reasoning for failure detection, fault localization, and plan repair in assembly robotics requires grounding the meta-knowledge in action and perception. Grounded meta-reasoning for these tasks is more flexible than classical planning and less costly than situated learning.In support of this claim we make the following contributions:1. A multi-resolution planning and monitoring system for assembly planning and execution, assuming complete knowledge 2. Methods for learning task models with incomplete procedural knowledge 3. Methods for repairing task plans with incomplete object or pose-grounding knowledge 4. A schema for a generic meta-reasoning architecture motivated by our key research insights
Monitoring Fake Product Reviews Using Opinion Mining

Product reviews  are crucial in determining whether or not to sell particular items on e-commerce sites or apps such as Flipkart, eBay, Amazon, Meeshow, Snapdeal, and others. We provide context in this document for using smart analytics to detect fraudulent or counterfeit reviews. Sentiment analysis is another term for it. We strive to gather client input via text while assessing sentiment. We first conduct a review and use a decision tree to check if the review is product-specific. Practicing a trash dictionary. to detect spam in comments. In text mining, we use many different algorithms and get specific results based on these algorithms.
PROTOTYPE APLIKASI CUSTOMER RELATIONSHIP MANAGEMENT (CRM) SEBAGAI PENINGKATAN MUTU LAYANAN DI UPN “VETERAN” JAKARTA

Information technology has developed rapidly since entering the era of the Industrial Revolution 4.0. no exception to competition between educational institutions such as State Universities (PTN) or Private Universities (PTS) in Indonesia. With the increasingly intense competition among tertiary institutions in Indonesia, all higher education institutions have to provide the best possible service to their students, either in providing adequate campus facilities or quality learning. One of the competition that occurs is in getting new students in large numbers and with quality. To achieve this goal, a good strategy and management of customer service is needed. Therefore, there is a need for communication between universities and their service users, for example students. One way that can be done is by applying the concept of Customer Relationship Management (CRM).Customer Relationship Management (CRM) can help universities, one of which is UPN Veteran Jakarta, which is a state university with a large number of service users to establish good relationships with its service users. One way to implement the CRM concept is to use a web application where the application can provide insight or information to users and improve customer relationships. The system is built in the form of web-based Electronic Customer Relationship Management (e-CRM) to improve the quality of UPN “Veteran” Jakarta services. With this application, it is expected that there will be a relationship between stakeholders, namely universities and customers, namely users of more communicative services.
The Effect of Using Youtube to Increase the Level of Listening Skills Among Non-Native Students of Arabic Speakers in Malaysian Universities

Learning through YouTube has become one of the main sources of learning in the student's life at the present time which provides illustrative images, scalability of knowledge, and ease of searching for sources of knowledge. It also provides the student with large areas of self-learning and the provision of knowledge according to the desire of the student. On the contrary, other learning sources, where knowledge and goals are limited as well as time and place. Therefore, the current study deals with knowledge of the students' performance in listening skills by using YouTube among students of non-native Arab speakers by adopting Connectivisim Theory. To achieve the objective of this study, the researcher intends to use the questionnaire survey to measure the effect of using youtube to increase the level of listening skills among non-native students of Arabic speakers. The study sample size was 144 students selected through the stratified sampling method from non-Arabic speaking students at the International Islamic Universiti Sultan Abdul Halim Mu’adzam Shah (UniSHAMS). The study used (SPSS,25) to investigate the hypotheses. Furthermore, the study showed that using YouTube has a highly significant impact on increasing listening skills for non-native students of Arabic speakers.
Towards building shared prosperity in Sub-Saharan Africa: How does the effect of economic integration compare to social equity policies?

The debate on the need for Sub-Saharan African (SSA) countries to foster inclusive growth has intensified following the coming into force of the African Continental Free Trade Area (AfCFTA), and the emergence of the coronavirus pandemic. A conspicuous lacuna in the literature is a lack of rigorous empirical work(s) exploring: (1) the joint effect of economic integration and resource allocation, and (2) social equity policies on inclusive growth in SSA. Using data from the World Bank’s World Development Indicators and the Global Consumption and Income Project (1980–2019) for 43 SSA countries, I provide evidence robust to several econometric techniques the fixed-effect, random-effect, and the system generalized method of moments estimators to show that: (1) though economic integration induces inclusive growth, the effect is higher in the presence of greater financial deepening and productive government expenditure; (2) relative to economic integration, social equity policies are rather remarkable in enhancing inclusive growth. Policy recommendations are provided in line with the AfCFTA and the reversals of welfare gains due to the coronavirus pandemic.
Investigating iranian English as a Foreign Language (EFL) students’ writing skills based on principal component analysis

Identifying EFL writing components involves an intricate network of principles and approaches that also involve assessment models. Methods of teaching and assessing writing are normally compatible with the purposes or expectations of writing-specific courses/programs. This study investigated the most important academic writing constructs in Iranian EFL students based on principal component analysis. To this end, an Oxford Placement Test (OPT) was administered and based on its results, 60 (out of 114) Iranian EFL male and female learners from Islamic Azad University, Broujerd Branch, Iran, were randomly selected as the homogeneous sample of the study. Additionally, 100 EFL teachers from four language institutes were asked to participate. Three instruments were used, namely OPT, a survey questionnaire, and writing tasks. The data were analyzed through principal component analysis. The findings revealed that the most important constructs in the Iranian EFL students’ writing skills were “mode”, “assessment”, and “mechanics”, respectively. The findings of the study suggested implications for L2 writing improvement from a practical and theoretical perspective. The findings, more specifically, could shed light on current practices and theories, and could prove useful for practitioners and future studies in the field of second language writing.
Subject Guides: Off-Campus Streaming Guide: Environmental Studies

Use this guide to find streaming alternatives to Media Services DVDs. Streaming films on environmental studies and environmental science
Library Guides: Library Services for Retirees, Alumni, and Community: Ask a Question/Chat

Georgia Southern University Libraries support the University’s mission by providing access to resources designed to meet the scholarly needs of the University and the general public and by promoting independent lifelong learning.
Time Series Forecasting of Bitcoin Trading Price using ARIMA, FB Prophet, XG Boost and LSTM

Bitcoin (BTC) is a fastest growing cryptocurrency with highly turbulent and volatile trends of the highs and lows of BTC trading price. In other words, the BTC prices follows non stationarity tendency, thereby exhibiting variations in the statistical distribution of data over the time period. However, by using technical indicators responsible for fluctuation in BTC price, as an input to the Machine Learning (ML) algorithms, we can forecast future trends in order to assist investors to make wise decisions with regards to investment. In previous studies, linear and regression-based algorithms are used for short-term and mid-term forecast but are ineffective towards highly volatile environment of BTC price. Therefore, in this paper, we presented highly robust ML algorithms including ARIMA, FG Prophet, XG Boost and LSTM networks for predicting BTC price movements in long-terms. Our evaluation results indicate a significantly higher validation accuracy of 95.72% and 95.70% scored by ARIMA and FB Prophet algorithms. These outcomes shows that the implemented algorithms outperformed the existing ones in the literature.
Study of the relationship between organizational commitment and individual work performance

The search for performance engages managers in a process of continuous improvement in several areas. These include prospecting for new customers, retaining existing customers, innovation, etc. However, managers are aware that the room for maneuver on these aspects remains very limited. In this sense, several studies have shown that human resources are a real differentiating factor for the company in a highly competitive market. Consequently, managers must take actions aimed at employees in order to increase their motivation and involvement at work.In this perspective, our research work consists in exploring the relationship between organizational commitment and individual work performance, and tries to provide managers with an idea on the mechanisms able to improve the performance of their employees through the development of their commitment to the organization. To this end, we administered a survey to 480 employees in the automotive sector in the Rabat-Sale-Kenitra region. The structural equation model method was used to explore the relationships between the independent and dependent variables. The results show that organizational commitment has a positive effect on individual work performance.JEL classification: L20, O15Type paper: empirical research
IMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI PRODUK LARIS

Decision Tree C4.5 algorithm is an algorithm that can be used to make a decision tree. Decision tree (Decision Tree) is one method that is quite easily interpreted by humans. However, this algorithm has never been tested for product classification using private data (stock data and sales of goods at PT Cipta Karya Gorontalo). Therefore this study aims to test the accuracy of C4.5 in classifying best-selling products (private data). As a result of the evaluation of product classification models using Decision Tree C4.5 obtained from this study amounted to 90% and AUC value of 0.709 where this value is included in the Good Classification. It can be used as a data mining classification method Decision Tree C4.5 algorithm is accurate in classifying hot-selling products.&#x0D; &#x0D; Keywords— Decision Tree, C4.5, Classification, Best-Selling Product&#x0D;
Social Networking Sites Involvement in Hate Speech Transmission According to Zarqa University's Faculty of Journalism and Media Students Perspective

The study aims to examine the influence of social networking sites Facebook hate speech transmission according to Zarqa University's Faculty of Journalism & Media students' perspective. The descriptive analytical method was used in the study, and a questionnaire was used to collect information from a random sample of 100 individuals who represented 50% of the study population as a whole, which consisted of 200 male and female students from Zarqa University's Faculty of Journalism and Media. The study came to the main conclusion that social networking sites such as Facebook play an intermediate role in the transmission of hate speech.