Reviewerly/exHarmony huggingface dataset:
Unsupervised Descriptive Text Mining for Knowledge Graph Learning

The use of knowledge graphs (KGs) in advanced applications is constantly growing, as a consequence of their ability to model large collections of semantically interconnected data.The extraction of relational facts from plain text is currently one of the main approaches for the construction and expansion of KGs.In this paper, we introduce a novel unsupervised and automatic technique of KG learning from corpora of short unstructured and unlabeled texts.Our approach is unique in that it starts from raw textual data and comes to: i) identify a set of relevant domain-dependent terms; ii) extract aggregate and statistically significant semantic relationships between terms, documents and classes; iii) represent the accurate probabilistic knowledge as a KG; iv) extend and integrate the KG according to the Linked Open Data vision.The proposed solution is easily transferable to many domains and languages as long as the data are available.As a case study, we demonstrate how it is possible to automatically learn a KG representing the knowledge contained within the conversational messages shared on social networks such as Facebook by patients with rare diseases, and the impact this can have on creating resources aimed to capture the "voice of patients".
APPLICATION OF INFORMATION SESSION INFORMATION SYSTEM AS MEDIA SUBMISSION OF FINAL RESULTS COMPREHENSIVE SESSION

Good information that is based on data that has been processed properly so as to generate useful communication. The trial assessment system has 3 parts, but the system is not mutually integrated because 2 of them can already be accessed online while the examiner's assessment system still uses the local network. In the grading system, the examiner has a session news information system that is useful for conveying the final results of the session to the trial participants. This is because as technology advances are utilized as well as possible by educational institutions in this case namely universities to be used in a comprehensive session of thesis students or final assignments. Therefore, development is carried out on the examiner's assessment system so that it can be accessed online, where there is a trial news information system. The research was conducted using the method of observation, interviews and literature to maximize this research. The trial news information system is a very important system when a comprehensive trial process takes place. This is because the news information system of the hearing has information about the grades, grades and status obtained by the trial participants. This certainly becomes very vital in the trial assessment system. The display that will be developed in the examiner's rating system will be user friendly, making it easier for the board of examiners to use it. Even though the system was developed but did not change the original flow of the examiner's assessment system so that the board of examiners could adjust well to the new system, along with the news information system of the trial. With the existence of a hearing news information system, it makes the comprehensive trial process perfect and the trial assessment system becomes integrated again as before.
Proactive and reactive context reasoning architecture for smart web services

The web of things (WoT) uses web technologies to connect embedded objects to each other and to deliver services to stakeholders.The context of these interactions (situation) is a key source of information which can be sometimes uncertain.In this paper, we focus on the development of intelligent web services.The main requirements for intelligent service are to deal with context diversity, semantic context representation and the capacity to reason with uncertain information.From this perspective, we propose a framework for intelligent services to deal with various contexts, to reactively respond to real-time situations and proactively predict future situations.For the N. Sekkal et al. semantic representation of context, we use PR-OWL, a probabilistic ontology based on multi-entity Bayesian networks.PR-OWL is flexible enough to represent complex and uncertain contexts.We validate our framework with an intelligent plant watering use case to show its reasoning capabilities.
An Openness Of Government Website Content Using Text Analysis Method

Website as the most common media in use for the implementation of Public Information Openness. Content presented on the website has a major impact on public perception on government performance. In the text analysis of this research website, Indonesia Act. No.14/2008 on public information openness becomes the benchmark. The text analysis of the content starts by listing the content of the information on the website, then categorizing the information, in each category there are parameters in the parameters that the information starts at the value, and get the measurement value of the website content. The validation of website content information measurement in this research is Kutai Kartanegara (Kukar) District Government, Kukar has 110 units of Local Government Work Unit and 76 has website to disseminate information. The results of measurement of content with text analysis on all websites that are active in Kukar, indicating the presentation of content in the categories below is enough because only two public bodies have complete information and as mandated by the Act.
Corpus-Based Methods for Recognizing the Gender of Anthroponyms

This paper presents a series of methods for automatically determining the gender of proper names, based on their co-occurrence with words and grammatical features in a large corpus. Although the results obtained were for Spanish given names, the method presented here can be easily replicated and used for names in other languages. Most methods reported in the literature use pre-existing lists of first names that require costly manual processing and tend to become quickly outdated. Instead, we propose using corpora. Doing so offers the possibility of obtaining real and up-to-date name-gender links. To test the effectiveness of our method, we explored various machine-learning methods as well as another method based on simple frequency of co-occurrence. The latter produced the best results: 93% precision and 88% recall on a database of ca. 10,000 mixed names. Our method can be applied to a variety of natural language processing tasks such as information extraction, machine translation, anaphora resolution or large-scale delivery or email correspondence, among others.
Genetic Evolutionary Learning Fitness Function (GELFF) for Feature Diagnosis to Software Fault Prediction

Nowadays, proper feature selection f+orFault prediction is very perplexing task. Improper feature selection may lead to bad result. To avoid this, there is a need to find the aridity of software fault. This is achieved by finding the fitness of the evolutionaryAlgorithmic function. In this paper, we finalize the Genetic evolutionarynature of our Feature set with the help of Fitness Function. Feature Selection is the objective of the prediction model tocreate the underlying process of generalized data. The wide range of data like fault dataset, need the better objective function is obtained by feature selection, ranking, elimination and construction. In this paper, we focus on finding the fitness of the machine learning function which is used in the diagnostics of fault in the software for the better classification.
South Korea

This chapter offers an analysis of distance education in Korea as a model for developing countries to catch up with advanced countries in meeting the demand for higher education. First, we analyze the functions and roles of distance education in the higher and lifelong education sectors in Korea. Second, we present a brief review of the history of distance education in Korea, followed by the characteristics of distance education offered by the Korea National Open University (KNOU), cyber universities and traditional universities that offer distance and online learning. Third, we examine major legislation and policies, including the Higher Education Act, to highlight efforts that have been made to ensure the quality of distance education. Lastly, we make closing remarks about future directions and challenges of distance education in the higher and lifelong education sectors in Korea.
Researchon Classification Techniques in Data Mining

Data Mining means a procedure to extracting the information out of large data. Data miningapproaches includes classification, association rule, clustering, etc. Data mining is applied in four stages such as data sources, data extrapolation / gathering, modeling and deploying modules. Classification is a method in data mining to predict the group membership of data instances. It’s an method useful in data mining with vast applications for classifying the different types of data used in almost every fields. Classification is giving a class label to in determine set of cases. In this survey, we would like discuss Bayesian classification, rules based classification, Decision trees &amp;neural network.
Supervised learning

In supervised classification, we search criteria allowing us to decide whether a sample belongs to a certain class of patterns. The identification of such decision functions is based on examples where we know a priori to which class they belong. The distinction of seismic signals, produced from earthquakes and nuclear explosions, is a classical problem of discrimination using classification with supervision. We move on from observed data—signals originating from known earthquakes and nuclear tests—and search for criteria on how to assign a class to a signal of unknown origin. We begin with Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (FLDA), identifying a linear element separating groups at best. PCA, FLDA, and likelihood-based approaches make use of statistical properties of the groups. Considering only the number of misclassified samples as a cost, we may prefer alternatives, such as the Multilayer Perceptrons (MLPs). The Support Vector Machines (SVMs) use a modified cost function, combining the criterion of the minimum number of misclassified samples with a request of separating the hulls of the groups with a margin as wide as possible. Both SVMs and MLPs overcome the limits of linear discrimination. A famous example for the advantages of the two techniques is the eXclusive OR (XOR) problem, where we wish to form classes of objects having the same parity—even, e.g., (0,0), (1,1) or odd, e.g., (0,1), (1,0). MLPs and SVMs offer effective methods for the identification of nonlinear decision functions, allowing us to resolve classification problems of any complexity provided the data set used during earning is sufficiently large. In Hidden Markov Models (HMMs), we consider observations where their meaning depends on their context. Observations form a causal chain generated by a hidden process. In Bayesian Networks (BNs) we represent conditional (in)dependencies between a set of random variables by a graphical model. In both HMMs and BNs, we aim at identifying models and parameters that explain observations with a highest possible degree of probability.
CBIR System for Lung Nodule Retrieval in CT Scans

Lung cancer remains one of the fatal diseases with very high mortality rate in both men and women. Computer aided diagnostic systems have been contributing towards the enhancement of survival rate to a maximum extent. Most of such systems yield binary results, i.e. they classify whether a nodule is benign or malignant and they are computationally expensive. This paper proposes a methodology to build a Content Based Image Retrieval (CBIR) system that provides additional provision to the domain experts. Since the CBIR systems retrieve most similar images, this visual dimension will assist the budding and experience radiologist to assess the nodule information to greater detail. Nine visual and shape features are extracted for each nodule image collected from LIDC database and Minkowski distance measure is used for computing similarity. Experiments are conducted on 750 nodules out of which 375 are benign and 375 are malignant as identified by domain experts. Precision, recall and F measure metrics are considered to evaluate the methodology with achieved average values of 0.92, 0.82 and 0.86 respectively.
Data Science and Artificial Intelligence for Communications

The six papers in this special section address the application of artificial intelligence, machine learning, and data analytics at different layers and different applications of different types of communications networks. The objective of using these tools is the optimal design and improved operation of networks. These articles feature new opportunities to develop and advance various areas of communications through the use and applications of AI/ML/ deep learning technologies.
Impact of Classification Algorithms on Census Dataset

Data mining is a method by which valuable information can be obtained from large databases. A supervised method of classification assigns data samples to target groups. In this system, it uses various classification algorithms namely decision trees, SVM, random forest and neural network. This system will classify and analyses the best suited algorithm which gives maximum accuracy among the other algorithms. The accuracy in these algorithms has been calculated by sensitivity and specificity. Evaluation of these models has been calculated by the error rate with respect to the classes. It uses census dataset and finds whether the income above 50k or below 50k. Matrix of error consists of true positive, neutral, true negative and false negative values. Based on true positive and false negative values, specificity is determined. Based on true negative and false positive values, sensitivity is determined. The algorithm analysis which finds the better algorithm with respect to the accuracy, error rate and efficiency.
A Decentralized Data Privacy for Mobile Payment using Blockchain Technology

Mobile payments today have become the most preferred method of transaction for an increasing number of customers. To provide robust security mechanism for mobile payment in public network is challenging task for device manufacturing companies and network service companies. Most of the mobile payment apps make payment easy and fast, but users have to face new security challenges. Because users have to do payment transaction in an open network this makes users sensitive data put at risk, where advisories launch attack and theft of user’s identity information. Resent payment apps like Google-pay and phone-pay successfully address the security issues, but these apps might suffer from internal attacks, because data is centralized where apps should accept permission from bank server to do the transaction. In the proposed system we introduce a protected transaction pattern using blockchain technology which overcomes the limitation from the existing system. Our money transformed in the form of cryptocurrencies and it stored in the separate wallet. The particular wallet is installed in the mobile devices. Payment or transaction through two consumers lacking any prior permission. The proposed System uses decentralized data server to preserve data privacy from adversaries. While transaction we directly transfer through the blockchain wallet without any interference from the Bank. The proposed system proven to be secure and efficient for online payment transaction. It secured from cyber attackers or intruders hence data can be stored in separate blocks and its difficult to find out exact data. This overcomes the negative aspect of usual mobile payments.
An Insight of Information Security: A Skeleton

In this age of growing and developing information and technology, data security, integrity and confidentiality are essential aspects related to shared data over some network or medium. Many techniques over the years have been developed for securing the messages from attack or theft or breach of very sensible and essential data when shared over a network. The security threats to data have been ascending, so are the data hiding or securing techniques. This is where Information Security has a role to play. Development of techniques and methods that prevents the essential and secret data being stolen and thus providing security to the data. This paper discusses the significance of Information Security, its evolution since its infant stage and study about various subdomains of the same. This paper also shows a comparative study of various Information Security Techniques, their pros and cons and the applications in various domains. This paper analyses various Information Security methods or techniques based on their various characteristics and effectiveness on securing the data from any adversaries. This includes a study of some benchmark techniques and their subsidiaries along with it. The techniques under focus for analyzing were Watermarking, Digital Signatures, Fingerprinting, Cryptography, Steganography and latest being CryptoSteganography Information Security Technique. The characteristics focused were security-related properties, data or message-related properties, their objectives, drawbacks, applications and algorithms.
Bridging the digital divide

A century ago, when pandemic influenza struck a war-torn world, few multilateral institutions existed. Countries fought their common microbial enemy alone. Today, an array of multilateral mechanisms exists to confront global public health emergencies and address their economic, social, and political effects. The global nature of the current pandemic requires a global response. Let us make sure we leverage existing multilateral mechanisms to help fight the virus and overcome the current crisis.
Wireless Gesture Control Wheelchair

Wheelchairs have been used by patients who suffer from various physical disabilities to help them with locomotion and cater their day to day needs with ease. But there are some cases where the movement of a wheelchair is dependent on another individual as is the case with patients who lack the required arm strength and movement to properly push the wheels forward such as quadriplegics, paraplegics, stroke patients, elders etc. Joystick oriented wheelchairs, thought to be a solution to those kinds of patients, can pose different problems as it requires basic shoulder movement. It is not always possible for the aforementioned types of patients. In addition, our solution doesn’t have the positional constraints that a joystick wheelchair might have as it is wireless and can be worn on either hand which allows the patient to sit in their preferred position for minimum discomfort. This project is an attempt to help the disabled move around independently. Thus, in this research work, we present a prototype of a wireless gesture-based wheelchair which can be controlled via hand gestures. The framework consists of a transmitter and a receiver that communicate with each other wirelessly. For wireless transmission, 433Mhz RF Transmitter and Receiver Unit has been used as it transmits data through an antenna at the speed of 1Kbps – 10Kbps and the range can be adjusted as required. The transmitter unit consists of an Arduino LilyPad microcontroller and an accelerometer that has been attached to a hand glove. The accelerometer sensor has been used to register the position of the hand while creating a gesture. This glove is supposed to be worn by the patient allowing them to move their hand conveniently, sending signals to the receiver unit connected to the wheelchair leading to the movement of the wheels in the desired direction. The receiver unit consist of motor drivers that convert the voltage as needed by the wheels. This paper presents an alternative to the commercial wheelchairs as it is cost effective, easy to control and efficient. The working and assembly of the system has been explained in the paper.
Development of restaurant serving robot using line following approach

As the era of industrial revolution 4.0 is coming, most of robots are developed to replace the human works and services. However, in Vietnam, putting robots in service industry such as waiter robot serving in restaurants is still very limited. This study presents the initial development of restaurant serving robot using line following approach. The robot is designed by referring to the survey on the size and appearance requirements at a restaurant. Robot is programmed to come to a specific table by mapping data. Based on the line reading algorithm implemented on microcontroller PIC18F4550, the robot follows the line marked on the floor to move to the desired table position and returns to the service counter after completing the task. There are ultrasonic sensors on the robot that can detect the obstacle to help the robot stop and output warning signal. The robot also can output some simple voices to customers in English, Korean and Vietnamese such as "Welcome", “Please enjoy your food"...
Differentiated Learning Model For Student with Reading Difficulties

This research is an analytical-descriptive study which focuses on the characteristics of students with difficulties in reading and the needs for differentiated learning instruction. The result of this study reveals that the prevalence of Students with Difficulties in Reading reaches 9,15% of the total population of students from each elementary school in Tomohon. The most excellent ability in reading comprehension which students have achieved is the level of literal reading. Students who have this level of reading skill can only be found in two elementary schools. Of 10 elementary schools, only students from 4 elementary schools whose reading ability lies on the lowest level, that is understanding vocabulary. In general, students face the difficulties in understanding inference and applying vocabularies. Learning process which has recently used is inadequate to accommodate students’ ability and solve their difficulties. The methods used in class include lectures and assignments. There are two methods, those are Rumpang Method and Glass analysis. The recent condition which students with difficulties in reading face requires immediate and meticulous problem solving. Therefore, teachers need to apply differentiated learning instruction in order to facilitate adaptive learning process suitable for the abilities of students with difficulties in reading.
Hardware implementation of a new chaotic secured transmission system

In this paper, a novel secured transmission scheme implemented in Arduino-Uno boards is proposed. The transmission scheme is composed of two coupled discrete-time chaotic systems and two combined observers. In the first observer, some sufficient conditions on varying equal impulsive distance are established in order to guarantee the impulsive synchronisation method. In the second observer, an exact discrete-time observer is designed in order to reconstruct all states and the message information. Simulation results are presented to highlight the performances of the proposed method. One of the main contributions is to show that the proposed scheme, which is based on impulsive synchronisation of discrete-time chaotic systems is experimentally feasible with digital devices using the Arduino-Uno boards. The obtained experimental results validate the proposed approach.