Reviewerly/exHarmony huggingface dataset:
Design Of Online Shopping Application Based On Mobile Devices And Android Studio In PT. Midi Utama Indonesia: Design Of Online Shopping Application Based On Mobile Devices And Android Studio In PT. Midi Utama Indonesia

Self-service is an alternative place to shop. a special place that can meet the daily shopping needs of consumers. Product Ordering for customers remains a constraint if the distance of the place of residence with a minimarket are far apart, or lazy customers out due to rain. Of the few existing cases, Order and delivery system is still done over the phone. The way they have constraints, such customers do not know the Menu and price list that is in the minimart. This research aims to build the application so that the delivery Order and delivery information becomes quickly, accurately, and can Order the Products online via smartphones. This application was built using the software Android Studio as the manufacturer of the application and its data base for the management of SQLite. This application can help consumers to get information about the Product- markets are offered as well as facilitate consumers in the process of Ordering a Product and can help increase sales for companies.
Application and Method Analysis of New Media in University Education Management

In recent years, with the rapid development of China's social economy and the continuous progress of science and technology, new media technology has also been rapid development, and began to be widely used in all fields of people's daily life and work, providing greater convenience for people. Under the background of the wide application of new media technology, efficient education management should be fully integrated with multimedia technology to improve its service quality and work efficiency. This paper studies the method and application of new media in the management of higher education.
Helping Users Succeed Through Consistency

In Chapter 8, you learned the importance of reassuring both user and VUI that a request is correctly understood. There’s an additional piece to user reassurance: feeling in control. If users can navigate a VUI to get what they want, know how to start over, or get help when needed, then they feel comfortable with the whole interaction. The outcome is greater willingness to explore and try new requests and greater success in reaching their goals; it’s greater discoverability and findability. When users feel in control of their own fate, they’re happier users—even when they don’t reach their goal! If you’re familiar with usability heuristics, you’ll recognize several in this chapter: consistency, standards, familiar metaphor and language, help, feedback, and user control. Consistency is reached by
ANALYZING THE LECTURER’S POLITENESS STRATEGIES IN TEACHING-LEARNING INTERACTION

This politeness is the use of an appropriate word or phrase in the appropriate context, which is determined by the rules that are prevalent in society, in a language context, politeness is the use of polite instructions in teaching-learning interaction which the teacher uses to interact with the students, instruct, and guide them in smooth communication. This qualitative study was aimed at analyzing the lecturer’s politeness strategies in teaching-learning interaction. The participants of this study were one class of the 2nd-semester students of STMIK Pringsewu and a lecturer of English subject. In collecting the data, observation and audio-visual material were used. Then, descriptive analysis was used to analyze the lecturer’s politeness strategies in teaching-learning interaction. The results of this study showed that the lecturer mostly used the bald on-record strategy. On the other hand, a negative politeness strategy was rarely used. In conclusion, since the relationship between the lecturer and students is interrelated, therefore, it can be concluded that the more bald on-record strategy is used, the less negative politeness strategy is used.
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives

The recent work by Rendle et al. (2020), based on empirical observations, argues that matrix-factorization collaborative filtering (MCF) compares favorably to neural collaborative filtering (NCF), and conjectures the dot product's superiority over the feed-forward neural network as similarity function. In this paper, we address the comparison rigorously by answering the following questions: 1. what is the limiting expressivity of each model; 2. under the practical gradient descent, to which solution does each optimization path converge; 3. how would the models generalize under the inductive and transductive learning setting. Our results highlight the similar expressivity for the overparameterized NCF and MCF as kernelized predictors, and reveal the relation between their optimization paths. We further show their different generalization behaviors, where MCF and NCF experience specific tradeoff and comparison in the transductive and inductive collaborative filtering setting. Lastly, by showing a novel generalization result, we reveal the critical role of correcting exposure bias for model evaluation in the inductive setting. Our results explain some of the previously observed conflicts, and we provide synthetic and real-data experiments to shed further insights to this topic.
Real-time analyzing of chatbot data with distributed systems

Chatbots are one of the most widely used technologies to implement virtual assistance. Presently, chatbot based virtual assistants are being used by many web administrators to mediate access to data and to carry out generic conversations with the users. Such virtual assistants are getting a lot of attention from the business organizations, as it can help in improving customer care support; reduce the costs in customer service centers and can handle multiple clients at a time. Big data analytics is the process of collecting, organizing and analysing large data sets to discover patterns and unknown correlations hidden in the data, such as usage statistics and customer preferences, which can serve as valuable business information. This paper describes the implementation of a chatbot framework with an interface to big data. This implementation would provide mass knowledge analysis capability to chatbots from distributed environments, which can further the spectrum of usage of such intelligent agents.
The impact of employee empowerment and employee satisfaction on work performance

Improving the performance and productivity of employees is a big challenge to the organizations in this competitive business world. Experts view employee empowerment as an effective tool that to the organizational performance, employee satisfaction and service quality. The present study aims to identify the impact of employee empowerment and employee satisfaction on performance of employees. Data have been gathered following a quantitative survey conducted among 380 employees working in private banks, Coimbatore City. Statistical techniques consisting of descriptive analysis, ANOVA and Chi-Square analysis have been applied. The results of the statistical analysis reveal that employee satisfaction and work performance significantly depend on employee empowerment, and satisfied employees provide better empowerment. The findings of the study reveal that, empowered employees, contribute higher productivity in an organization which in turn increases the level of employee satisfaction.
الفروق في العوامل الخمس الکبرى للشخصية لمستخدمي شبکات الاعلام الاجتماعي من طلاب وطالبات الجامعة

تهدف الدراسة الحالية إلى التعرف على الفروق بين متوسط درجات سمات الشخصية لمستخدمي شبکات الإعلام الاجتماعي، وأيضا التعرف على الفروق بين متوسط درجات سمات الشخصية تبعا لمتغير جنس مستخدمي شبکات الإعلام الاجتماعي. تکونت عينة الدراسة من 680 طالبة وطالبة من دارسي السنة التحضيرية بالجامعات السعودية.، وذلک في الفصل الدراسي الثاني من العام الدراسي  2019/ 2020 م، ولأغراض الدراسة الحالية تم تطبيق مقياس:  قائمة العوامل  الخمس الکبرى للشخصية. أشارت نتائج الدراسة إلى: أن مستخدمي شبکات الإعلام الاجتماعي أعلى من المتوسط في سمات الانبساطية والمقبولية ويقظة الضمير والتفتح بينما أقل من المتو سط في سمة العصابية، وکذلک أظهرت أن قيمة (ت) للفروق في سمات الشخصية لدى مستخدمي شبکات الإعلام الاجتماعي جاءت دالة في السما: المقبولية في اتجاه الذکور، ويقظة الضمير في اتجاه الذکور، والعصابية في اتجاه الإناث، بينما لم تکن قيمة اختبار (ت) دالة للسمات الانبساطية والتفتح. The differences in the five major personality factors of University students who use  social media networks Abstract The present study aims to identify the differences between the average scores of the personality traits of users of social media networks, and to identify the differences between the average scores of the personality traits according to the gender variable of the users of social media networks. The study sample consisted of 680 male and female preparatory year students in Saudi universities, in the second semester of the 2019/2020 academic year, and for the purposes of the current study, a scale was applied: a list of the five major factors of personality. The results of the study indicated: that the users of social media networks are above average in the characteristics of extroversion, acceptability, alertness of conscience and openness, while less than the average in the trait of neuroticism, and also showed that the value of (t) for differences in personality traits among users of social media networks was a function of the traits: Acceptability In the direction of males, awakening of conscience towards males, and neuroticism in the direction of females, while the value of (t) test was not a function of extroversion and openness traits.
Breast cancer analysis using Machine Learning algorithms

Breast cancer (BC) is one of the most common types of cancer and one of the leading causes of death for women around the world. Breast cancer occurs when cells in the breast cells mutate and form a malignant tumor. State-of-the-art technologies can detect BC at an early stage, which helps in treatment and reduces the risk of death. Medical doctors commonly use breast tissue biopsy when diagnosing breast cancer, enabling them to take a microscopic look for breast tissue and determine whether the tissue is benign or malignant. To improve biopsy results, many researchers have studied the feasibility of using artificial intelligence (AI) to help doctors detect any harmful changes that may lead to cancer. In this research work detail analysis of Breast Cancer using support vector machine (SVM) and convolutional neural networks (CNN) algorithms is performed and the results show CNN has more superior results in comparison to SVM in the recognition of images affected by Breast Cancer.
Analisis Proses Software Testing pada PT. Signify Commercial Indonesia

In this final project, what has been done is analyzing the implementation of Software Quality Assurance at Pt. Signify Commercial Indonesia by PT. Axelsen Marvel Studio uses the User Acceptance Test method. The goal is to find out what steps must be taken so that the system testing runs smoothly. The system is a monitoring system on the products of PT. Signify Commercial Indonesia. Before the system is actually applied by the user, the system must pass several testing stages based on the Software Testing Life Cycle (STLC). If the system satisfies the user and meets the desired standards, the system is ready to be published.
Voice interface for semi-automatic generation of annotated surgical reports of paranasal sinus surgeries

Background The aim of our project is the development of an annotation tool that uses speech recognition during a paranasal sinus operation to create a surgical report. This is intended to save time in documentation and improve its quality. We consider this speech interface to be the base technology for the development of future collaborative assistance functions.
УЧЕТ ВОЗРАСТНЫХ И ИНДИВИДУАЛЬНЫХ ОСОБЕННОСТЕЙ УЧАЩИХСЯ НАЧАЛЬНЫХ КЛАССОВ В РАЗВИТИИ ЛИЧНОСТИ

In this article authors talks about the importance of accounting the age and individual feature characteristics of primary school students on educational process. One of the most important factors of personal development is the consideration of the age and individual features of pupil. Author reveal the psycho-physiological development of primary school pupils and analyze the works of famous teachers and psychologists of Kazakhstan and foreign countries. It is mentioned that the importance of taking into account the pupil's age and individual features on educational process was noted in the works of such Kazakh educators as Zh.Aymautov, A.Baitursynov, M.Zhumabaev, Sh. Kudaiberdiev, M.Dulatov, K. Zharykbaeyv.
ИНТЕГРАТИВНЫЕ МЕТОДЫ В ОБУЧЕНИИ КОМПОЗИЦИИ

The article discusses integrative methods in teaching composition. The complex possibilities of teaching composition are shown, providing the application of various techniques and techniques of artistic activities and their integration. Integrative methods of teaching composition provide for an integrated approach to the creative process in compositional activities. By means of interconnection and integration of tools and techniques of various types of arts and various types of artistic activity. Comprehensive integrative methods of teaching composition contributes to a more dynamic and fruitful integration of materials, tools, techniques and methods of types of art and artistic activity, and thereby contributes to the feasible creation of an artistic image. The subject of study is the artistic and creative development of students on the basis of the principles and methods of integrative learning composition. The objectives of this study are the study of integrative methods in teaching composition as an interactive toolkit of an integrated system of artistic and creative process.
Un estudio de la generalización en la clasificación de peatones

Since the surge in popularity of Histogram of Oriented Gradients (HOG) in 2005 as the de facto feature vector for pedestrian detection, there have been many improvements in the detection pipeline that enable state of the art performance to be applicable to many real world problems. Nonetheless, the datasets available for training models have many biases, making it hard to use to detect pedestrians from videos and images obtained from other sources than the datasets.This article presents a protocol to evaluate how pedestrian models generalize between different datasets. The protocol roughly consists of training a model with each dataset or dataset combination, and evaluating with the remaining dataset in each case.We use the protocol to evaluate the performance of a typical pedestrian classification model based on HOG and/or LBP features and a SVM classifier. Alternatively, we also use a modern ConvNets model, to verify that the results of the protocol are due to the datasets and not the model.We evaluate the models with the three most used datasets for pedestrian classification: INRIA, Daimler and TUD-Brussels. Our results show that while each dataset presents real world scenes, there are significant biases in each dataset that prevent models trained on one dataset to generalize to other datasets. Models trained on two fused datasets perform only marginally better on the third dataset than models trained on individual datasets, both for SVM and ConvNet classifiers.
The Effect of Foreign Direct Investment on Economic Growth in Ethiopia: A Granger Causality Analysis

The objective of this study is to investigate the relationship between foreign direct investment and economic growth in Ethiopia by employing an Autoregressive Distributed Lag (ARDL) model.For the purpose of examining the relationship between FDI and economic growth a time series data was collected for the period 1992/93-2018/19.According to the findings of this study, foreign direct investment is found to influence economic growth positively and significantly both in the short run and long run.Moreover, in order to identify the direction of causality between economic growth and foreign direct investment a Granger Causality test were undertaken.The result from the causality test shows that there is a unidirectional causality running from economic growth to FDI.Thus, policies that aim to expand infrastructural facilities and good management skill have to be implemented to attract more foreign direct investment in Ethiopia.
MANAJEMEN SISTEM INFORMASI AKADEMIK DALAM MENINGKATKAN KUALITAS PELAYANAN PERGURUAN TINGGI

In the world of education today the application of information and communication technology is very necessary, because along with the increasingly fierce competition of information that starts from the role of efficiency, effectiveness to the strategic role, making many parties of educational institutions in Indonesia use technology as a supporter to improve the quality of education from institutions These, both in terms of the quality of learning, the quality of lecturers, the quality of graduates and so forth. Various Education Information Systems continue to be developed both in terms of student management, academics, lecturers, finance, libraries, question banks and reporting, but have not been able to give meaning to improving the quality of higher education services so that they have a negative impact on college performance. This happens because the technology, curriculum, facilities / infrastructure, cost and human resources are not yet optimal and are exacerbated by the not yet optimal public awareness, stakeholders and commitment of all parties involved in the management of education in tertiary institutions. This study aims to uncover the analysis of the role of the Academic Information system (SIAKAD) in improving the quality of higher education services in the West Java Province Region. This research uses a field research method (Field Research), which is an in-depth investigation conducted with a field research procedure. This study also uses descriptive qualitative data, namely research aimed at describing or describing the phenomena that exist, both natural phenomena or human engineering. Based on descriptive research that has been done, it can be concluded that: 1) There are several obstacles that must be overcome to achieve these goals. Managers and institutions have not yet identified the needs as a whole, so that the detailed needs of stakeholders have not been met properly. 2) Not conducting a needs survey directly, so that what is really needed by stakeholders is not clearly known by the institution and the management of quality management, so that the basic needs of students are not met
Word sense disambiguation based on stretchable matching of the semantic template

<p style='text-indent:20px;'>It is evident that the traditional hard matching of a fixed-length template cannot satisfy the nearly indefinite variations in natural language. This issue mainly results from three major problems of the traditional matching mode: 1) in matching with a short template, the context of natural language cannot be effectively captured; 2) in matching with a long template, serious data sparsity will lead to a low success rate of template matching (i.e., low recall); and 3) due to a lack of flexible matching ability, traditional hard matching is more prone to failure. Therefore, this paper proposed a novel method of stretchable matching of the semantic template (SMOST) to deal with the above problems. We have applied this method to word sense disambiguation in the natural language processing field. In the same case of using only the SemCor corpus, the result of our system is very close to the best result of existing systems, which shows the effectiveness of new proposed method.
Autoencoding Under Normalization Constraints

Likelihood is a standard estimate for outlier detection. The specific role of the normalization constraint is to ensure that the out-of-distribution (OOD) regime has a small likelihood when samples are learned using maximum likelihood. Because autoencoders do not possess such a process of normalization, they often fail to recognize outliers even when they are obviously OOD. We propose the Normalized Autoencoder (NAE), a normalized probabilistic model constructed from an autoencoder. The probability density of NAE is defined using the reconstruction error of an autoencoder, which is differently defined in the conventional energy-based model. In our model, normalization is enforced by suppressing the reconstruction of negative samples, significantly improving the outlier detection performance. Our experimental results confirm the efficacy of NAE, both in detecting outliers and in generating in-distribution samples.
Formation of Professional Culture in Higher Education: Experience and Problems

The subject of the article is the formation of professional culture of students; it is considered in order to improve the work on its formation in the educational process at the University, in particular-in RIPB-on the material of training economists, lawyers and customs officers. The authors describe professional culture as a set of special knowledge and practical skills of a person as an “employeeˮ, implemented in a specific type of socially significant work, emphasize that it is based on the universal values of a professional as a «person». Therefore, the formation of professional culture is inseparable from the socio-humanitarian development of students, carried out in the course of studying the relevant disciplines. According to the authors, any professional culture has its own organization (in our case - University), which is based on a particular professional activity (in particular, University training), while it embodies a Form that is subject to “fillingˮ with the specific Content of various activities as socially institutionalized pro-fessions. As conclusions, the following problems are substantiated: introduction of a special course “Professional cultureˮ; overcoming “departmentalˮ disciplinarity in the study of socio-humanitarian and professional dis-ciplines; improving the quality of “formalˮ training of students in the conditions of digitalization and comput-erization; development of a culture of extracurricular forms of professional work.
Corpus Analysis on one of the Philosophical Works of Acharya AbinavaGupta and Acharya Sri Adi Sankaracharya

This research paper documents a Philosophical corpus study on the work of Acharya AbinavaGupta and Acharya Sri Adi Sankaracharya. The document in the corpus is prepared using Sanskrit to English translated verses in ‘Tantraloka’ a work of AbhinavaGupta and English translated verses of ‘Vivekachudamani’ a work of Adi Sankaracharya. As a result, the corpus reflects some of the most significant texts on the magnificent work of Acharya AbhinavaGupta and Acharya Sri Adi Sankaracharya The data or verses are manually copied into excel. Data is prepared by removing the special characters, numbers, and stop words using python modules like Stop words and regular expression. The data is then lemmatized and the frequency of the words are studied The paper provides: (1) the spread of the corpus (2) the Jupyter notebook interface that helps in coding and analyzing the corpus using the NLTK (Natural Language Toolkit), spacy module, and word cloud (3) Graphical representation of words using word cloud and (4) a set of HTML visualizations using scattertext to navigate the corpus Scattertext visual basically gives an idea of what are the most discussed text in the verses of Acharya AbhinavaGupta on the Y-axis and Acharya Sri Adi Sankaracharya on the X-axis and the diagonal overlap is something that are common texts across 2 Philosophical verses.