Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis in Facebook using Machine Learning Techniques

Sentiment analysis is the process of computationally identifying and categorizing opinions expressed in text to determine the users' attitude towards a particular product is positive, negative or neutral. In today's world, opinions and reviews accessible to us are one of the most critical factors in formulating our views and influencing the success of a brand, product or service. With the advent and growth of social media in the world, stakeholders often take to expressing their opinions on popular social media, namely facebook. While Facebook data is extremely informative, it presents a challenge for analysis because of its humongous and disorganized nature. This paper is a thorough effort to dive into the novel domain of performing sentiment analysis about people's opinion about Google and apple productions. For performance analysis machine learning approaches such as n-gram technique is used. Hybrid approach is implemented by combining lexicon-based and machine learning algorithms. The result obtained through this approach is feasible to perform sentiment analysis in facebook with high accuracy.
Vehicle Accident Detection and Emergency Alert System

In recent years' injuries due to accidents are among the leading causes of hospitalization in humans, often resulting in a rapid decline in functionality and death. Rapid response can improve the patient's outcome, but this is often lacking when the injured person meets with a huge accident and the nature of the injury complicates calling for help. The lack of efficient accident detection and help management system that will help in times of need. One common scenario during accidents is that the activity of rescue and relief is not well-coordinated. For this reason, there is a need for a system that will help in the efficient provision of rescue and relief to accident affected people after increasing the chances of life. So in our project we are going to develop a system which will try to prevent and manage accidents with various sensors and an Arduino kit. The data will continuously have transmitted to the Android Phone of the driver. The phone will give instructions to avoid accidents. If then also an accident occurs the kit will send an alert to Android application of driver which in return will send location updates of the accident to concerned authorities for rescue work and to the nearest hospital. The Concerned authority will then track the rescue work. The location and alert system will be sent to the cloud at real time which will help monitor the accident at real time with the help of a desktop application and Google Maps. The data on the cloud will be secured by encryption and decryption base AES algorithm.
Higher Education and the National System of Research and Innovation: The Case of the Republic Of Benin

The link between theory and practice is the key of development of the country and explain the copetitivness in the international market. In the context of republic of Benin; a lot of the result of researchers are not valorized because of the weakness of system of extension. This study try to identify the problem. The diagnostic analysis show that we have research institutions without linkage, weak financng in the research sector, without leadership actors. So; Benin's ability to be part of international economic competition will rely more and more on its capacity for innovation and research and the quality of education and training.
Results of the 2019 Wiley Open Research Survey

Wiley has published the results of its Open Research Survey 2019. Earlier this year, over 2,600 researchers worldwide shared their thoughts and experiences of open research practices including: open access publication, data sharing, open peer review and open collaboration. For each of these areas we’ll present what motivates researchers to adopt these practices and the ways in which they do so, looking at how this varies by geography, subject area and career level. We’ll also look at the reasons why researchers might not be adopting these practices.
Personality Traits and Industry 4.0

The paper aims to understand the relationship between personality traits and its compatibility with the Industry 4.0 paradigm. It proposes modelling through big five personality traits and academic achievement of engineering students in Industry 4.0 courses. The study adopted an exploratory path through structured questionnaire on personality traits with 44 items and administered it on students undergoing courses in Industry 4.0 in an autonomous engineering college. The results suggest that personality traits influence significantly in the success of the courses in Industry 4.0. The academic results have also reflected in the success of a student in Industry 4.0 course and its influence on the traits. However, the study results have practical implications as the results can be applied for determining career choice of engineering students and providing directions to enhance academic achievement in Industry 4.0 course which is the future of engineering education.
Using Kotobee Author Software to Design Integrated Topic E-books and Using them in Teaching Chemisitry

At present, with the development of computer science and in the context of the fourth industrial revolution, technology products are used in all fields. In the field of education, more and more pieces of software and applications that support teaching are created, and one of them is e-books. E-books are documents which can flexibly and efficiently provide students with information and instructions in the form of multimedia and therefore can support and improve learning. The article presents the process of using Kotobee Author software to build e-book contents and using e-books to teach integrated topics in teaching chemistry with a view to developing self-learning ability for students.
Predictive Models on Early Detection of Mental Health Problems using Big Data and Artifical Intelligence

In the modern world, due to the increase in mental health disorders and its grave consequences throughout the world, it is of utmost importance that we pay greater attention to mental health and thus find out more about its various disorders and their treatment. As the traditional database management tools cannot handle large datasets, thus using big data analytics tools and techniques is advisable by accumulating the mental health data and further processing it. This paper is putting forward the ideas and strategy of using data mining and prediction models that can be used to efficiently predict the state of the mental health of an individual and thus give out proper remedies for treatment. We put forward a framework that classifies into five kinds of model and discusses predictive modelling in the domain of mental health. We have also proposed a BP Neural Network model for early detection of deteriorating mental health.
Designing a Midterm Reading Test for Junior High School Students in Semarang: A Practical Experience of a Master Student in TESOL

Designing a test is an uneasy task. It is proven by the fact that many teachers find difficulties in designing a good test. The present article attempts to review the English school exam in Indonesia and present an example of the test design of a midterm reading test for junior high school students in Semarang. To this end, firstly, a sample of test script of the school exam for JHS students in Semarang in the academic year 2017/2018 was reviewed. The review of the test shows that creating a good quality of test items still become a concern for English teachers as they made some grammatical errors. Consecutively, a midterm reading test was also designed and administered in a junior high school in Semarang, Central Java. Then, the test designed was evaluated by considering the validity, reliability, and practicality as suggested by (Brown Abeywickrama, 2010). The administration of the test and evaluation show some weaknesses; therefore, the suggestions for the betterment of the test design are also made, such as revising some test items with a very low facility index and negative discrimination index. This study implicates pedagogically the teachers to train students on how to summarize and paraphrase since these skills underrepresented.
Study of Convergence in Metaheuristics Algorithms

Artificial intelligence (AI) system purpose is to help humans solve problems.This branch of science became famous less than a hundred years ago.Since then, it has gained momentum and scale.This area is currently associated with many methodologies, some of which are called metaheuristics algorithms.In this work, we will look at several metaheuristics algorithms.Comparison of algorithm solutions will be performed.We compare the accuracy of the results, the speed of the solution, and other parameters.They will solve one of the classic NP problems.This problem is named a scheduling problem.This paper presents an approach for enhancement of this balance in single solution metaheuristics applied to solve two processors scheduling problem generated during metaheuristic search.We compare Simulated Annealing (SA) algorithm with our develop modification amongst to other well-known metaheuristics like a genetic algorithm (GA) and artificial ant colonies algorithm (ACA) taken from the source of literature.
Chatbot: A User Service for College

A chatbot is a software that is used to interact between a computer and a human in natural language. The chatbot application provided in this paper helps the users to access the college related information along with the functionality of college map from any location with internet connection. This system reduces the work of college administration and the staff in case of answering all the basic queries of the students. The proposed system makes use of AIML along with NLP in order to provide responses to the user. It has made the use of client-server communication for providing faster responses to the users.
Age-Invariant Face Recognition Using Trigonometric Central Features

Many facial recognition systems must fail because of many influences such as lighting, changes in composition, expression and aging in the face.But the effects of facial aging are the main problem that many algorithms face with precision.Accordingly, this work provides a model based on the extraction of a number of trigonometric features.The proposed model includes three areas connecting and surrounding the main facial features.In addition, aging is recognized by calculating the trigonometric zones extracted.The system compares the query face with the database.Then, the query image is extracted from the original face image.Next, the performance of the proposed model is compared with some of the latest facial recognition techniques.Facial recognition systems in different stages of life prove that the proposed facial recognition system gives enhanced accuracy of 99.80% with very low FAR level of 0.0001.
S6CRISPR GENOME EDITING BASED ISOGENIC INDUCED PLURIPOTENT STEM CELL SYSTEM FOR SCHIZOPHRENIA DISEASE MODELING

Among the solutions to improve the integration of intermittent solar system, solar irradiation prediction is an essential process. This kind of prediction is a highly complex problem and requires highly robust and reliable statistical models for its simulation. The current research is devoted on the implementation of time series formalism which is based on the periodic autoregressive model (PAR) coupled with a power transform (Box–Cox; BC) of data to stabilize variance. A new and robust functional model is proposed based on the prediction intervals approach whose results in term of efficiency (prediction interval coverage probability) and interest (normalized mean interval length) are similar or better than classical prediction tools based on bootstrap utilization. In the deterministic case, the PAR coupled with BC transform gives more mixed results, but for most cases, the classical tools, like persistence, smart persistence, auto-regression, and artificial neural network fail to compete with PAR or PAR-BC models.
AN ELEMENTARY PROOF OF FISHER-COCHRAN THEOREM USING A GEOMETRICAL APPROACH

The classical Fisher-Cochran theorem is a fundamental result in many areas of statistics as analysis of variance and hypothesis tests. In general this theorem is proved with linear algebraic arguments. An elementary proof is present, based strongly on geometrical concepts as linear subspaces and orthogonal projections, which may improve our intuition about the result.
Risk Management of Mobile Commerce Using Social Networks in Jordan

IntroductionMobile commerce, commonly regarded as m-commerce is currently becoming important for individuals and companies alike.Indeed, according to Rana, Barnard, Baabdullah, Rees & Roderick (2019), 75% of smartphone users often check product and service prices, while 42% made purchases using their phones through social networks.This has led to a different move by organizations who currently desire to increase their advertising budgets using different social media networks to reach the increasing number of users.Mobile retailing coupled with other wireless business operations is providing another revolution in the world of business.This growth has been fueled by the rapid development of smart phones around the globe.Technological advancements have led to new business markets, and this has changed the traditional way of marketing.Today, online marketing and advertising have become paramount for most business operations whether they are small or large.With the advent of social networking sites, the relationships between the customer and their business providers have changed drastically.Businesses are now forced to deal with their customers' needs and demands in a different unique way while ensuring convenience and overall satisfaction.Businesses can easily use their customer behaviors through such sites to provide suitable services and products to other potential clients.This is done by collecting individual data which is later analyzed to provide relevant information on customer demographics, needs, and requirements.Research indicates that individuals currently take more time on different social networks when compared to other activities like e-mail.The popularity of different social networks and the increased usage of such networks by users and business owners indicate a positive correlation that leads to better business operations between the two groups.Social networks usage is estimated to be around 900 billion and 1.3 trillion dollars (Hsu & Yeh, 2018).Despite the increased use of social networks through mobile commerce by individuals and organizations the technology carries various risks, and these are often greater when compared to environments that allow physical shopping.
Tuning of Acoustic Modeling and Adaptation Technique for a Real Speech Recognition Task

At the beginning, we had started to develop a Czech telephone acoustic model by evaluating various Kaldi recipes. We had a 500-h Czech telephone Switchboard-like corpus. We had selected the Time-Delay Neural Network (TDNN) model variant "d" with the i-vector adaptation as the best performing model on the held-out set from the corpus. The TDNN architecture with an asymmetric time-delay window also fulfilled our real-time application constrain. However, we were wondering why the model totally failed on a real call center task. The main problem was in the i-vector estimation procedure. The training data are split into short utterances. In the recipe, 2-utterance pseudospeakers are made and i-vectors are evaluated for them. However, the real call center utterances are much longer, in order of several minutes or even more. The TDNN model was trained from i-vectors that did not match the test ones. We propose two ways how to normalize statistics used for the i-vector estimation. The test data i-vectors with the normalization are better compatible with the training data i-vectors. In the paper, we also discuss various additional ways of improving the model accuracy on the out-of-domain real task including using LSTM based models.
Organic Characterization of the “TÉGulines Clay Formation”, East Paris-Basin, France: Bulk and Molecular Investigations

Preview this conference paper: Organic Characterization of the “TÉGulines Clay Formation”, East Paris-Basin, France: Bulk and Molecular Investigations, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/2214-4609/2019/P82-1.gif
The problem of Professional Growth of a Specialist in a Paradigm of Ratio-Humanistic Psychology of George Ball

In this article the features of the research on the process of professional growth of a specialist were specified according to the analysis of contemporary psychological and pedagogical works. The phenomenon of professional development in the paradigm of ratiohumanistic psychology of George Ball
Robust Hybrid Intelligent Based Motion Control of Industrial Robot Manipulators for Unstructured Dynamic Environment

The intelligent robot system is credited with a commendable task of moving in an unstructured dynamic environment with a little period information without a chance of being collided.This interesting capability is apparently the subject of research for more scholars then researchers in robotics.This study investigates moving of a robotic arm in the presence of any obstacle.The robots that are capable of working in unpredictable and changing environment will be suitable and effectively used in wide range of applications.Moving a robot arm around obstacle needs a special skill which is akil to intuitive skill for human beings.Intuitive skill is translated in to instructions for a robotic arm is a Himalayan task.Neuro fuzzy systems are excellent in determining the input and output relationships using a simple data.The traditional fuzzy logic system is replaced with the back propagation neural network.A robotic arm could be trained to plan its movements averting collision with obstacle in its area.This is possible only with neuro fuzzy techniques since several of its controllers are trained using simple data received from human control of robotic arm and this study quantifies and compares their performance.The suggestions for possible avenues for future work are also explained.
Forget the future: Our time is now

The text of a 2017 address at the RUSA President’s program talks about the need for librarians to be centered on active learning. Aspects of continuous learning for librarians should be participatory, happening everywhere, and occurs in a social context. The author argues that librarians must be advocates and must advocate for everyone in the community regardless of race, religion, education level, or country of origin. This is a job that cannot be delayed until tomorrow. It is a duty outlined in the values of our profession and enabled by technology. The article ends with a call for personal action in supporting communities of all types.
PENGGUNAAN PERANGKAT MOBILE TERHADAP SUATU TINDAK KEJAHATAN (STUDI KASUS PADA TEMUAN BUKTI DIGITAL SHORT MESSAGE SERVICE (SMS) DI UNALLOCATED DATA)

Mobile devices usage has become a part of daily life modern humans today. And one of mobile devices that is almost owned by mobile devices users is mobile phone, including a smartphones. As an electronic devices that can store data, even various kinds of data types, that information stored from data on mobile phone can reflect the user’s activity. So the information can be described as a chronologically if needed. In this study, there are case studies about findings and handlings of digital evidence form of Short Message Services (SMS) that obtained on unallocated data in an android smartphone. By practically testing the procedures, the results show that steps and stages used for handling mobile devices evidence could be run dynamically, in the sense that, there are several procedural steps can be run as simultaneously, but the activity stages could be run regularly too. So the artefacts has a forensically sound elements and can be proven as a scientific with the clear stages.
Neural Machine Translation with Bilingual History Involved Attention

The using of attention in neural machine translation (NMT) has greatly improved translation performance, but NMT models usually calculate attention vectors independently at different time steps and consequently suffer from over-translation and under-translation. To mitigate the problem, in this paper we propose a method to consider the translated source and target information up to now related to each source word when calculating attentions. The main idea is to keep track of the translated source and target information assigned to each source word at each time step and then accumulate these information to get the completion degree for each source word. In this way, in the later calculation of the attention, the model can adjust the attention weights to give a reasonable final completion degree for each source word. Experimental results show that our method can outperform the strong baseline systems significantly both on the Chinese-English and English-German translation tasks and produce better alignment on the human aligned data set.
Enhancing Speaking Skills in the Material of Remedial Learning Through Community Language Learning in SMP Multazam Semarang

This paper highlighted how extremely English language learning that sometimes seemed threatening pupils in the classroom where they were unable to express much attention and confidence. They quantitatively got the worst score for this subject due to several aspects that must be comprehended by students: pronunciation, grammatical structure, vocabulary, and intonation. As long as, students participated in the teaching-learning process, they had standardly done all of the assessment. Therefore, teachers here as the facilitator or counselor should redesign the classroom’s atmosphere and its method; instead, it would invite students to show their best performance. Community Language Learning (CLL) displayed how effectively and efficiently English should be taught. Thus, this research is qualitatively reported to observe how CLL was able to increase the students’ speaking skill in the Material of Remedial Learning for students’ eight grade in SMP Multazam with the total number of 26 students. An observation sheet and the score ranking sheet were as data collection to consider the names. A fluency, a pronunciation, an expression, a vocabulary, and content were the instrument to analysis their performance. This study was Classroom Action Research which revealed that the students are comfortable in joining learning’s experience, and its effects to their competence in speaking skill with the amount of enhancement through 2 cycles; post-test 1 and post-test 2. CLL was considered to be an effective method since it contributed to the prominent effect of speaking skill.