Reviewerly/exHarmony huggingface dataset:
Text Mining with Apache Hadoop over different Hadoop Clusters Architectures

Big data is very much practical for real time applicational systems. One of the mostly used real time application worldwide are on unstructured documents. Large number of documents are managed and maintained through popular leadingBig Data platform is Hadoop. It maintains all the information at Hadoop Distributed File System in Blocks. Irrespective of datasize, BigData has opened its path to store and analyze the data which has consumed time. To overcome this, Hadoophas designed cluster process for large volumes of unstructured data computations. Three different cluster architectures like Standalone, Single node cluster and multi node clusters are considered. In this paper, Big Data allows Hadoop platform to boost the processing speed overlarge datasets through cluster architectures, which are studied and analyzed through text documents from newsgroup20 dataset.It identifies the challenges on text mining and its applications using ApacheHadoop.
Feature Selection with Centre of Gravity Method using Ant Colony Optimization

The high dimensional dataset with irrelevant, redundant and noisy features has much influence on the performance of machine learning problems. In this work, an existing Ant Colony Optimization (ACO) based feature selection algorithm is modified by attaching a dimensionality reduction method as a data pre-processing step. This is achieved by introducing the concept of Centre of Gravity (CoG) of a set of points. After reducing the dimension, the ACO algorithm is used to generate the optimal subset of features. The performance of the proposed algorithm is evaluated using Artificial Neural Network (ANN) classifier. The performance comparison using various dataset shows that the proposed method outperforms the existing ACO based feature selection methods.
Image Map: Alternative for Password Based Authentication

In the world today there are millions of websites and other web applications which operate with customizations to the user using the user account registration. This naturally requires a user name or a unique ID like email address and a password. This kind of authentication is being employed from days past to invention of authentication systems. But today with many such websites it has become a herculean task to remember the passwords of each and every sites. There are solutions like writing down or noting on any electronic device but these has equal physical chances of being revealed. So there is a need for a brand new authentication techniques which are better than existing ones and are easy to implement. Image map is one such an alternative that can replace traditional systems. This technique makes use of images taken from users during registration and certain number of points on one exclusive image from taken set of images.
Knowledge Retention Strategy Evaluation &amp; Knowledge Management System Design at Plastic Injection Company in Indonesia

The potential of knowledge loss when an employee retires or resigns is high at PT. XYZ a plastic injection company in Indonesia. Therefore, it is required to evaluate their knowledge retention strategy (KRS) and developing a knowledge management system (KMS). The evaluation of KRS using Organizational Knowledge Retention Framework developed by David DeLong and for designing KMS model using the 10-Step KM Roadmap method developed by Amrit Tiwana. Through a well-developed KRS and KMS design model, PT. XYZ can overcome the problem of losing the knowledge that occurs because employees retire or resign.
Pelatihan Dan Bimbingan Teknis Pembuatan Peta Tanah Di Sekolah Menengah Atas Di Kota Kendari

Knowledge about the land and the skills in making land maps provided is one of the efforts made to create appropriate resources. Efforts to increase knowledge and skills that can be done are introduction of soil descriptions and profiles along with training in making land maps. The purpose of this training and technical guidance activity is to provide students with an understanding of the soil at the high school level, knowing about soil resources in detail to students, knowing the procedures for making a land map using Geographic Information Systems (GIS) and knowing how to conduct soil investigations in the field. The problem solving framework of this activity is carried out in several stages, namely preparation, preparation of training materials, presentation of material by resource persons, discussions and questions and answers, practice of making land maps, and practice of making soil profiles by dividing student groups, evaluating the results of activities and preparing reports. This training was held in SMA Neg. 4 Kendari and SMA Neg. 6 Kendari. The result of this training and technical guidance is that the trainees have added knowledge and skills in making land descriptions and profiles, as well as making land maps using the geogarfi information system application. Keywords:. Training Students, Land, Geographic Information Systems
Tiffin Ordering System

Tiffin Delivery System facilitates the customers and small scale Homemade food businesses/mess to manage and control their business through online platforms. Tiffin Delivery System is introduced to overcome the dis-advantages of the traditional mess food delivery system. This system improves the procedure of taking the order from customers with the use of technology. The application sets up a food menu online and customers can easily view this menu online and place the order according to their food choices. This system also provides the feature on vendor side that once the order is arrived on vendor side from customer, vendor can accept or cancel that order as per the resource availability. For more secured ordering specificand private accounts are maintained for each user by providing them an unique Users ID and Password which is generated after successfully registering into the application.
Serials Spoken Here - Reports of Conferences, Institutes, and Seminars

This column includes reports on sessions from the American Library Association Midwinter Conference 2019, with a report on how libraries can be part of a shared community with developers and users through the use of future of libraries, is open (FOLIO) library services platform and a report reflecting on future technological developments. Additionally, conference reports from the 14th Annual Electronic Resources & Libraries Conference, which includes reports on implementing troubleshooting training programs for public services staff and using budget cuts as an opportunity to generate goodwill. The remaining reports are from American Library Association Annual Conference 2019, which includes a report about the parallels between managing campaigns and managing an integrated library system (ILS) migration, how to improve a collection development plan with resources about Cheyenne and Arapaho people, and an exploration of the challenges of hosting student and faculty journals.
Homogeneous Image Compression Techniques with the Shannon-Fano Algorithm

Compression is a field that needed at this time where increasingly high-tech digital and computing makes it possible to process data in a size that is large enough like multimedia. Compression needed to keep pressing the storage media consumption of data and information stored on computer media. The Shannon-Fano compression algorithm is one of the well-known compression algorithms and is useful in saving data storage space. Shannon-Fano compression algorithms can be performed on text and digital images. In this study applying the Shannon-Fano method to homogeneous digital images using applications created with the MATLAB Program. The product of this research will be tested using several images taken using a webcam. The product tested to find out whether the coding used is correct or has errors. The product will be successful if it can reduce the size of the compressed image from the original image. Homogeneous images that have tested using the Shannon-Fano image compression application have an average compression ratio value of 52%. The size of the compression results reaches half of the original image. The Shannon-Fano compression algorithm detects the number of times that characters appear in each experiment, then the coding of the frequency of characters appearing in binary numbers.
Transfer learning using AlexNet Convolutional Neural Network for Face Recognition

This research is aimed to achieve high-precision accuracy and for face recognition system. Convolution Neural Network is one of the Deep Learning approaches and has demonstrated excellent performance in many fields, including image recognition of a large amount of training data (such as ImageNet). In fact, hardware limitations and insufficient training data-sets are the challenges of getting high performance. Therefore, in this work the Deep Transfer Learning method using AlexNet pre-trained CNN is proposed to improve the performance of the face-recognition system even for a smaller number of images. The transfer learning method is used to fine-tuning on the last layer of AlexNet CNN model for new classification tasks. The data augmentation (DA) technique also proposed to minimize the over-fitting problem during Deep transfer learning training and to improve accuracy. The results proved the improvement in over-fitting and in performance after using the data augmentation technique. All the experiments were tested on UTeMFD, GTFD, and CASIA-Face V5 small data-sets. As a result, the proposed system achieved a high accuracy as 100% on UTeMFD, 96.67% on GTFD, and 95.60% on CASIA-Face V5 in less than 0.05 seconds of recognition time.
AN ANALYSIS OF ENGLISH WORD FORMATION PROCESSES IN BEATS APART NOVEL BY ALANDA KARIZA AND KEVIN ADITYA

This research discusses word formation process used in Beats Aparts novel By Alanda Kariza And Kevin Aditya. The aims to describe how are English word created and found out types of word formation processes. To analyze the data found the researchers applied English word formation in English morphology.This is qualitative descriptive research. The data were taken from Beats A parts novel By Alanda Kariza And Kevin Aditya. The main theory which was used in this research is taken from the book under the titleThe Study of Language,Third Edition byYule (2006). The result of this research showed that the process of borrowing from other language, there were Spain, China, French, Italy and Germany. The process of compounding, found out some category, there wereAdv + N, Adv + Adv, Adv + Adj, Adv + V, Adj + N, Adj + Adv, Adj + V, V + N, V + Adj, N + N, N + Adv, N + Adj, N + V. The process of clipping found out two category, there are foreclipped and backclipped. The process of conversion only found word from noun became adverb. The process of derivation consist from adding prefix such us un-, re-, dis-, im-. Adding suffix such us –ly, -ish, -er, -ness, -ion / tion, -able, -ful, -ship, -ment, -ate, -r, -en, -ity, -tic, -ism, -al, -ar. Adding infix such us –s-, -ly-, -bor-. The process of multiple processes is all words including multiple processes in this research have a word that covers the processes of back formation and derivation. This research found out types of English word formation processes such as borrowing, compounding, blending, clipping, back formation, conversion, acronyms,derivation and multiple processes. The researcher hopes that this research can improve the knowledge about morphology, especially in word formation. Key words: Morphology, Word formation, Novel
Reversible Data Hiding in Encrypting Images - An System

In today’s technology data hiding has become an essential need due to the availability of the internet all over the world. Nowadays, it has become necessary task for the people to communicate through networks and share contents with each other. In the meanwhile, transferring the data in a secured manner has become a challenge and also a paradigm. Still there exists many ways for hiding the data in an encrypted images. Hiding information at the back end of the image should not affect the original data or image pixels. It is one type of steganographical method where the data can be hidden inside the images and original data can be losslessly retrieved after extracting the embedded text.The proposed work discusses encryption using reversible data hiding and produces an outlineof various reversible data hiding techniques which includes quantization technique, histogram shifting, expansion technique, compression technique anddual image technique
On the Deployment of Web Browsers

The examination of rasterization is a persuading request. Here, we confirm the examination of Scheme. In order to surmount this issue, we manufacture an assessment of compilers (DIVES), which we use to fight that DNS and wide-district frameworks can synchronize to address this trap.
SHA_1 Enhancement Based on Resilent Boolean Function

SHA_1 is a one way hash function which is used in cryptographic systems to provide message authentication and integrity. In recent year this algorithm faced new type of attacks. These attacks make use of the simplicity of message expansion step to leak some information used to build a matching patterns or build differential path according to local collision. In this paper an enhanced version of SHA_1 was proposed depend on using resilent Boolean function which is a Boolean function that offers properties of balancedness, algebraic degree, correlation immunity and nonlinearity. This enhancement tends to countermeasures these attacks. Enhancement was made in two places for the original algorithm, first enhanced message expansion process, second change the value of 32 variable inputs to Boolean function in the algorithm.
Predicting Severity Level of Road Traffic Accidents in Oromiya East Shewa Zone using Iterative Dichotomiser3

Abstract: - Highway traffic accidents are a main community health problem unease ensuing millions fatalities and million serious injuries in the world each year. In the developing country like Ethiopia, is also the victim of road traffic accident or crush causing deaths, property damage and serious injuries. In order to analyses severity level of road traffic accidents, data is important to find out factors that are related to fatal, grievous, minor and non- injuries to gauge a fixed variables that contributes towards forecast the severity level of road traffic crashes. A lane traffic stream pound or impact happens when a vehicle slams into another vehicle, passerby, creature, or geological or building obstruction and result in injury, property harm, and lethal/demise. Path traffic control framework is, where basic information about the squash is recorded and saved for looming use. Expending that information the proposed examination have been extricated the contributing elements of street auto collision and create prescient model to foresee seriousness level for street car crash, wounds and fatalities utilizing information mining methods.. The main task of research is to make known the applicability of data mining techniques in emerging a model to support road traffic accident brutality analysis in preventing and extracting patterns that are corresponding with road accident in different ways of presentation methods. The road traffic accident historical data ,obtained from traffic Oromia police commission of East Shewa Zone, Oromia and police commission of Federal government of Ethiopia.
Happy new year? Biometrics is top target for hackers in 2019

Biometric hacking will be one of the biggest cyber-threats in 2019, according to global information services company Experian.
REIMAGINING RELATIVITY Transitioning the physical body into a virtual inhabitant

This paper explores the ideas and mechanics through a case study which generated a reimagined means of inhabiting a speculative immersive environment. Currently, many users reside within virtual environments for their own leisure, work, or any other reason desired from short amounts of time to extreme lengths. This paper shows the generation directly relative to the inhabitant, where gravity, orientation, scale, and locomotion is completely dynamic. Details within this paper experiment with the laws and bounds of the virtual space within a real-time game engine where reimagining the way one inhabits space compared to current norms of real-world inhabitation is possible with creativity and applied knowledge. Escherâs lithograph of Relativity is the driving concept explored within this paper beginning with creating gravitational pulls in multiple directions within the immersive virtual reality environment to accommodate various sources of gravity. The result of the case study demonstrated the generation of new virtual relativity laws reimagining how the virtual space is inhabited, in short, omnidirectional flying, gravitation defined by the inhabitant to geometry relationship, controlled local scaling, and populating space with multiple inhabitants in a unique manner.
TECHNOLOGY-ENHANCED LANGUAGE TEACHING WITH MUSIC IN CHINESE KINDERGARTEN: INVESTIGATING IMPLEMENTATION AND EFFICACY

TECHNOLOGY-ENHANCED LANGUAGE TEACHING WITH MUSIC IN CHINESE KINDERGARTEN: INVESTIGATING IMPLEMENTATION AND EFFICACY
The inclusion of students of a technical university in research as a pedagogical condition for the formation of their mathematical orientation

О. В. Лешер, И. А. Вахрушева, Е
How to Reduce Supply Chain Risk: Lessons from Efforts to Block Huawei

Supply chain security is a vital component of American national security. United State officials have continued to warn that 5G infrastructure equipment built by Huawei could be subverted by China to conduct espionage. There has been an intense investigation on Huawei, ranging from their software development processes to allegations of back doors. While it may be debated if Huawei is a pawn in a trade war or national security risks, it reinforces the importance of knowing one’s ecosystem. This article summarizes a panel discussion at the RSA2020 cybersecurity conference in San Francisco, titled "How to Reduce Supply Chain Risk: Lessons from Efforts to Block Huawei" was moderated by Craig Spiezle, founder of Agelight Advisory and Research Group, with panelists Katie Arrington, cyber information security officer of acquisitions for the U.S. Department of Defense; Donald Andy Purdy, chief security officer of Huawei Technologies USA; Bruce Schneier, security researcher and lecturer at the Harvard Kennedy School; and Kathryn Waldron, a fellow at R Street Institute. This session uses Huawei as a case study for best practices to assess risk and provide transparency to all stakeholders.
International scientific associations of the History of Science and Technology: formation and development (part III)

The activity of international organizations on the history and philosophy of science and technology is a remarkable phenomenon in the world scientific and sociocultural sphere. Such centers influence and contribute to the scientific communication of scientists from different countries and the comprehensive development of numerous aspects of the history and phylosiphy of science and technology, carry out scientific congresses. That is why the analysis of the acquired experience and the obtained results of these groups are important.&#x0D; The history of the formation and development, task, structure, background and directions of the activities of some international organizations in the field of history and philosophy of science and technology, including The European Philosophy of Science Association (EPSA), The International Society for the History of Philosophy of Science (HOPOS), The International Federation of Philosophical Societies (FISP) and The International council for philosophy and human sciences (ICPHS) have been shown.&#x0D; The European Philosophy of Science Association (EPSA) was established in 2007 to promote and advance the investigations and teaching the philosophy of science in Europe. EPSA edits the European Journal for Philosophy of Science (EJPS), which publishes articles in all areas of philosophy of science. The International Society for the History of Philosophy of Science (HOPOS) promotes serious, scholarly research on the history of the philosophy of science and gathers scholars who share an interest in promoting research on the history of the philosophy of science and related topics in the history of the natural and social sciences, logic, philosophy and mathematics. The scholarly journal HOPOS is published by University of Chicago Press.&#x0D; The International Federation of Philosophical Societies (FISP) is the highest nongovernmental world organization for philosophy, whose members-societies represent every country where there is significant academic philosophy. It was established in Amsterdam in 1948. FISP’s first seat was located at the the Sorbonne in Paris. FISP includes approximately one hundred members. It does not include individual members, but only «societies» in a broad sense, that is, philosophical institutions of different kinds, such as associations, societies, institutes, centres and academies at national, regional and international levels. The International council for philosophy and human sciences (ICPHS) is a non-governmental organisation within UNESCO, which federates hundreds of different learned societies in the field of philosophy, human sciences and related subjects. It was conceived as the intermediary between UNESCO on one hand, and learned societies and national academies on the other. Its aim was to extend UNESCO's action in the domain of humanistic studies.
Parallel Computation Performingkernel-Based Clustering Algorithm using Particle Swarm Optimization for the Big Data Analytics

Digital data has been accelerating day by day with a bulk of dimensions. Analysis of such an immense quantity of data popularly termed as big data, which requires tremendous data analysis scalable techniques. Clustering is an appropriate tool for data analysis to observe hidden similar groups inside the data. Clustering distinct datasets involve both Linear Separable and Non-Linear Separable clustering algorithms by defining and measuring their inter-point similarities as well as non-linear similarity measures. Problem Statement: Yet there are many productive clustering algorithms to cluster linearly; they do not maintain quality clusters.Kernel-based algorithms make use of non-linear similarity measures to define similarity while forming clusters specifically with arbitrary shapes and frequencies. Existing System:Current Kernel-based clustering algorithms have few restraints concerning complexity, memory, and performance. Time and Memory will increase equally when the size of the dataset increase. It is challenging to elect kernel similarity function for different datasets. We have classical random sampling and low-rank matrix approximation linear clustering algorithms with high cluster quality and low memory essentials. Proposed work: in our research, we have introduced a parallel computation performing Kernel-based clustering algorithm using Particle Swarm Optimization approach. This methodology can cluster large datasets having maximum dimensional values accurately and overcomes the issues of high dimensional datasets.