Reviewerly/exHarmony huggingface dataset:
An Effective Way to Enhance Classifications for the Semi-Structured Research Articles

Due to the drastic increase in the research publications, numerous research articles are available electronically on different online digital libraries. Some research articles or papers are not retrieved during online searches due to their classification issues. The adequately structured research articles are relatively easily approachable as compared to semi-structured and unstructured research articles, and sometimes the reader does not get accurate results on different digital libraries as the research articles are not classified properly. Neglecting the semi-structured and unstructured published research not only causes gap deficiency but also affects the results of the proposed techniques and citations for other articles. Usually, researchers missed semi-structured and unstructured research articles during their online search. Classification techniques have been applied to structured articles and no significant work has been performed towards the classification of semi-structured and unstructured research articles. Therefore, this research focuses on the classification of semi-structured research articles using different supervised classification techniques so that the most accurate and large amount of relevant research results will be achieved. For experimentation, a labeled dataset was used for the classification of semi-structured papers. The dataset we used for experimentation is comprised of manually gathered research articles from Santos repository dataset and labeling them accordingly. The current study used four different supervised classification techniques such as Support Vector Machine (SVM) classifier, Naive Based classifier, K Nearest Neighbor classifier, and Decision Tree classifier. The comparison was performed between these supervised classification techniques to see which classifier gives better accuracy. The unit of measures or parameters selected to compare these classifiers are: accuracy, recall, precision, and f-score. The evaluation was performed on the basis of results and comparison in the experimentation. Experimental results of classifiers K-neighbor are better than other classifiers SVM, Decision Trees and Naive Bayes
The Determinism of Professional Development Needs in Continuous Teacher Training

The need for professional development is a gap that could be bridged by a proper training that is meant to foster both demonstrated and expected competences of an individual or a group. Nowadays it is necessary to distinguish between the socially generated needs for professional development and the individually generated ones. Some of them include certain needs which are seemingly unrelated to professional competences, but which can influence the individual learning process: the need for self-training, the need to interact with other teachers, the need for leisure time, the need to study at a personal pace. It is obvious that a more thorough analysis is definitely required prior to courses in order to tailor them to each individual‘s professional development set of needs. Therefore, the aim of this paper is to provide a deeper and more realistic analysis of professional development needs, which can lead to a better insight into a more effective benchmarking of continuing professional training. The taxonomy featured in this paper is a tool that can be used by providers of continuing professional training to such an extent that they are enabled to optimise their course content and approach. Furthermore, this framework which relies on genuine professional needs empowers teachers to reflect on their own development priorities when they are supposed to select a suitable training programme provided by different educational suppliers.
The Internet in Crimea: a Case Study on Routing Interregnum

In 2014 the Russian Federation laid claim on Crimea, causing a change of regime and reportedly profound changes in Internet regulation and connectivity in the peninsula. The goal of this study is to introduce tools to monitor this, and similar situations, and to document changes that happened to the Internet in Crimea. This analysis aims at deconstructing a simplistic vision of a geopolitical controversy, by looking into technical arrangements between providers on the international and regional level, and in the context of international sanctions. We employ a multidisciplinary approach, combining sociological fieldwork with Internet measurements to cross-verify our findings. This paper sheds light on some transformations on Crimean networks through an analysis of AS dependencies and semi-structured in-depth interviews with ISPs from the region. We show that network measurements provide an impartial assessment of the effect of politically relevant changes, and allow us to monitor the impact of geopolitical and legal constraints on the networks, such as international sanctions. We believe this work lowers the barriers for interdisciplinary studies that covers Internet infrastructural changes and sets a first milestone to automate such studies in the future.
‘Like 9/11 on steroids’: AI in the age of coronavirus

The Covid-19 pandemic of 2020 is not the first such public health crisis we have faced, nor indeed the most lethal;however, it has occurred at the perfect time to foreground a number of key issues central to the role of AI in society at individual, national, and global levels This paper will examine the use of AI-driven systems to respond to the current situation, arguing that it marks a limit case for the employment of new technologies (most notably pervasive telecommunication) It will focus on three main concerns: UTILITY: what might AI systems offer as tools for risk/harm mitigation in situations such as these? A pandemic is the perfect domain for Big Data analysis, but there is also huge potential for transnational coordination of research, logistics, and necessary manufacture MORALITY: AI-supported contact tracking apps (as used in Singapore and Australia) enable rapid mapping of infection spread, and the possibility of identifying key vectors, but there is a vital debate to be had about surveillance, consent, and government control of citizens through the bulk collection of data Any discussion of AI is always an ethical conversation AUTHORITY: we have already seen a proliferation of misinformation concerning Covid-19 distributed online;much of this, it seems, comes from utterly unreliable sources, as deliberate acts of of Information Warfare by State actors AI offers the potential to generate highly specific messages designed to influence their targets, and distribute them further and faster than at any time in history ‘Fake News’ has become literally lethal;how can nations and individuals employ AI systems to inoculate themselves against highly infectious, harmful ideas? The paper discusses key components of a Code of Conduct for the use of AI balancing the need for effective and rapid threat mitigation with essential human rights The British Prime Minister has quoted Cicero’s ‘Salus populi suprema lex esto’ [the health of the people is the supreme law’];the severity of the current crisis must not blind us to the fact that the health of the body politic is a matter of morality as much as medicine © ECIAIR 2020 All right reserved
TO IMPROVE CYBER SECURITY OPERATION CENTRE PERFORMANCEIN THE USER CENTRIC MACHINE LEARNING FRAMEWORK

So as to guarantee an organization's Internet security, SIEM (Security Information and Occasion Management)framework is set up to streamline the different preventive advancements and banner alarms for security occasions.Overseers (SOC) examine alerts to decide whether this is valid or not. In any case, the quantity of alerts in general isn'tright with the dominant part and is more than the capacity of SCO to deal with all mindfulness. Along these lines,noxious probability. Assaults and bargained hosts might not be right. AI is a potential way to deal with improving thewrong positive rate and improving the profitability of SOC investigators. In this article, we make a client driven designerlearning system for the Internet Safety Useful Center in the genuine hierarchical setting. We talk about standardinformation sources in SOC, their work stream, and how to process this information andmake a compelling AIframework. This article is focused on two gatherings of perusers. The main gathering is smart specialists who have noinformation on information researchers or PC wellbeing fields however who specialist ought to create AI frameworks formachine wellbeing. The second gatherings of guests are Internet security specialists that have profound information andability in Digital Security, yet Machine learning encounters don't exist and I'd prefer to make one without anyone else.Toward the finish of the paper, we utilize the record for instance to exhibit full strides from information assortment, markcreation, include building, AI calculation furthermore, test execution assessments utilizing the PC worked in the SOCcreation of Seyondike.
Application of Steganography for Inserting Text Messages in Digital Images Using the Least Significant Bit Method

The development of digital media (Internet, electronic mail, and so on) gas data is already common, along with such developments, crimes in the field of information technology and telecommunication increasingly occur. Digital data commonly used is digital imagery, digital imagery that is transmitted through the media can be important data, so there is a problem arises how to secure digital imagery is confidential. One ofhis ways is steganography. The goal in this study inserts text messages using a steganography technique with the Least Significant Bit method on the digital Image media. The Least Significant Bit Method performs the insertion of a text message into a digital image by changing the value of the pixel to 8 bits then taking the leading 4 bits to be inserted at 4 the last bit at 8 bit pixels, the process of inserting a text message on digital imagery will be divided into three layers namely layer Red, layer Green, layer Blue . Once the digital image is saved, the extract process is aimed at retrieving text messages that are already stored in the digital image. In this test there are two images used that image size 325x325 pixels and image size 473x354 pixels each image is performed three times the insertion of text messages different number of characters ranging from three words to one paragraph. The image encryption process that becomes the container is not significantly different from the original, for image description results that have been inserted in a hidden text message can be returned with a change in the pixel value that does not alter the image Significant.Keywords : Digital imagery; Insertion; Least Significant Bit; Steganography; Text messages.
New Advances in Artificial Intelligence for the New Generation

Journal of Swarm Intelligence and Evolutionary Computation is a world forum for the publication of papers in Artificial Intelligence; Robotics; Modeling & Analysis of swarm particle optimization; Swarm Intelligence; Evolutionary programming and Evolutionary Genetics; Genetic Algorithm & Genetic Programming; Ant colony Optimization; Bacterial Forging; Artificial Life & Digital Organisms; Bioinformatics; Evolutionary Computation; Artificial Immune System; Computing; Nano computing; Computational intelligence, etc. Swarm Intelligence journals are at higher echelons that enhance the intelligence and knowledge dissemination on topics closely associated with Swarm Intelligence. Computational methods in synthetic biology plays a major role in this journal.
Novel INS/GPS/Fisheye-Camera Loosely/Tightly Coupled Enhancing Robust Navigation in Dense Urban Environment

This paper addresses an original problem of integrated navigation system INS/GPS in urban environment when LOS/NLOS measurement could be mixed and sequentially available. To solve this problem, multiple Kalman filtering algorithms were investigated and tested on a real designed platform called: nanoiBB, which is an integrated navigation and recording system developed by LASSENA laboratory in ETS-Montreal. With IMU 9DOF and GPS receiver, Loosely and Tightly coupled approach were implemented and compared for long duration navigation in the city of Montreal, in Obstructed and Unobstructed areas, when experimental data collected from four (04) iBB systems were used to analyze and validate loosely/tightly coupled Information Fusion method for INS/GPS integrated system. To achieve that, different scenarios and observability conditions were assumed and then implemented in different Kalman filtering frameworks in post processing; to achieve the best NLOS detection, Fisheye camera view was selected to detect NLOS regions and select the best adaptive or robust nonlinear filters for loosely/tightly integration. It is important to mention that there is no rejection of satellites, instead, adaptive fading factors and Hinfinity versions of Gauss quadrature Kalman filters was designed and applied. During the tests, micro-iBB integrated navigation systems and recorders have demonstrated good performances using EKF/UKF, then with much higher efficiency when using High degree Cubature Kalman filters. It was found that it is a good candidate for driving assessment and data recording systems, in real time and post processing data analysis for event emergency detection even in dense urban environment.
DEVELOPMENT OF ADVANCED HUMAN ACTIVITY RECOGNITION SYSTEM USING WEARABLESENSORS

ABSTRACT: In the field of medical science and automation, human activity recognition system is used widely.This paper discusses about the development of advanced human activity recognition system using wearablesensors. In this first MEMS sensor will detect the motion whenever there will be change in temperature andautomatically AC it will be turned on. In the same way whenever the vibration sensor will detect the motion bothfan and light will be turned on. The alert message is send to the corresponding number using globalcommunication system. The main intent of RS-232 is to provide communication. Hence this system giveseffective results compared to others.
한국어 교재의 변천사 연구

This paper aims at describing the historical changes of the textbooks to explain the history of the textbooks and find a plan for development of the Korean textbooks as a part of the study on the theory of Korean textbooks. For the purpose, the Korean textbooks as a foreign language developed at a Korean language institutes attached to a domestic university that took lead from the beginning of the development course of the Korean language education became the subject of this study. The transition process of the Korean textbooks was divided into five periods to examine the development situation and internal and external composition of the textbooks from the late 19th century to the present. It has been found with this analysis that the Korean textbooks have been developed reflecting the teaching theories of each period fully in the field of the type of the textbook, visual design, translations, relevant contents, entire composition, development purpose, unit composition, unit name, study content, and study activity. For the continuous development of the Korean textbooks and Korean language education, however, the following study and development are required. Firstly, a teacher tutorial which includes the principle of textbook development, the intent of writing, and the proper way of use should be developed. Secondly, a study on the development of the teaching materials which reflect the changes in digital technology is required. Thirdly, a consideration on making a textbook with a variable system which takes selective learning, the selection of the educational content, and the use of various programs into account. Finally, there should be a compilation of “A Series of Korean Teaching Materials Data,“ named tentatively, in the form of a book or digital data to implement the first role of data for the development of the Korean language education as study.
“Jag trodde att det kunde vara ok”. Polisens rättsmedvetande i relation till dess brott.

This bachelor thesis, regarding Swedish police officers' legal consciousness, in relation to their convictions, is a content analysis. It includes the convictions and/or interrogation protocols of 26 charges. The documents have been coded, analysed and reduced into pronouncements and explanations as to why the police officer has chosen to commit a crime, in relation to their service as a police officer. The hypothesis has been that these pronouncements are reflections of legal consciousness, and that they can be a guidance, in understanding and interpreting it. The notion legal consciousness has been based on three aspects: knowledge and interpretation of as well as attitude towards the law. The pronouncements have been analysed with a starting point in Gresham Sykes and David Matza's five techniques of neutralization (1957), that are generally used to explain why individuals commit criminal acts, and an indication on how they justify their crime. The analysis has shown that the officers’ pronouncements reflect parts of their legal consciousnesses, particularly by descriptions of their interpretation(s) of the situation. Most of the officers expressed that there were, by their judgment, extenuating circumstances in their case. The aspects of legal consciousness that were identified, were found to be partly related to the kind of circumstance and the type of neutralization technique that the officer had been using when justifying his action. Above all, the officers’ legal consciousness consisted of significant margins of interpretation. (Less)
Intelligent Management System of Computer Room Based on Internet of Things Technology in Big Data Center

In recent years, with the advancement of campus information construction in colleges and universities, Internet of things technology provides solutions for the intelligent management of big data room. The administrator of the computer room can monitor the status of the computer room environment, power and cloud operating system in real time without the limitation of time and place. It can receive various fault warning information in real time, and carry out intelligent processing through various mobile terminals timely as well. Based on the Internet of things technology, this paper proposes to develop an intelligent management system of big data center computer room using HTML5. In a variety of intelligent mobile terminal systems, it receives real-time early warning information such as temperature and humidity environment in the machine room of the big data center, power, server cloud operating system and so on, and realizes the intelligent management function of the power system such as suction fan, anti-theft, air conditioning, power distribution cabinet and UPS power supply. Through the practical application of the system, the management level of the machine room of the big data center is improved effectively with the advantages of the unattended intelligent management and reducing the workload of the machine room administrators. It provides strong security for the computer room of big data center.
Interactive Mathematics Learning Media Development Problem in the form of Android Application on The Material Building Students Class VIII Junior High School.

This research is supported by the non-availability of media that can add students understanding to the material taught by the teacher to junior class VIII students. It is clear that students are struggling in understanding material from a flat side chamber that teachers teach to make students less self-reliant and active in learning. To overcome this, one of the efforts done is to make learning media mathematics based interactive problems in the form of Android applications on the material building space. It is supported with mobile phone advances which give some advantages to the production of audio visuals, in addition the phone is no longer foreign to students, all students already have it and take it to school. The research is used research and development. The method of developing a Plomp model consisting of an initial investigation phase, planning phase, realization stage, test phase, evaluation and, revision and final stage of implementation. But this research only phases the test, evaluation and revision only. Validation is done by 1 mathematics lecturer and 1 PTIK lecturer. Practicality check is done to 28 students of class VIII SMPN 27 Padang and 1 person mathematics teachers of SMPN 27 Padang. Based on the validation results of the expert acquired the results that this interactive learning Media is valid with an average of 87%. Based on the practical poll of the teacher, the results of the average practicality of 86.67% by criteria are practically practicable. The student's practicality results from an average of 82.05% with practical criteria. From the results of this research researchers suggested that further research can develop interactive mathematics learning media in the form of Android applications with other models of learning because interactive mathematics learning Media In this form of Android application can be used as a companion media in the learning process. In addition it is expected that researchers can also develop interactive mathematics learning media in the form of this problem-based mathematical Android application with language that is easier to understand by students of grade VIII SMPN. Key Words : Development, android, media, smartphone app.
Analysis of RF Device Fingerprinting using Convolutional Neural Network

The authentication of devices and identification of unauthorised signals has been difficult in many scenarios.In this paper, a method for identifying a specific device among a range of similar devices is discussed using the techniques of convolutional neural network.The approach is to use radio fingerprints as samples for the identification process.The variability caused in the manufacture of these wireless transmitters serves as a unique feature, creating repeatable signatures for a particular device.These signatures are used as fingerprints for identification and verification.A framework is then developed for training the convolutional neural network using complex baseband error signals in time domain for varying signal-to-noise ratios (SNRs).
THE IMPLEMENTATION OF COOPERATIVE LEARNING AND PROBLEM BASED LEARNING IN TEACHING WRITING NARRATIVE TEXT AT SECOND GRADE OF JUNIOR HIGH SCHOOL

This research entitled “The Implementation of Cooperative Learning and Problem Based Learning in Teaching Writing Narrative Text at Second Grade of Junior High School” was aimed to know the differences of cooperative learning and problem based learning in teaching writing narrative text, to know the implementation of cooperative learning (think-pair-share) and problem based learning in learning process, and to know the difficulties that faced by students in writing narrative text. This particular research was categorized as quasi experimental research. The treatment were implemented in experimental class and control class. This research involved 60 students of class VIII at MTs Negeri 1 KBB. The data of this research was in the form of quantitative data acquired through pre-test and post-test and was analyzed by using SPSS. The data also supported by observation and interview. The research finding showed that the result of the test has a sig 0.0015 < 0.05, so hypothesis H1 was accepted. It can be concluded there was differences of cooperative learning (think-pair-share) and problem based learning in teaching writing narrative text. The result of observation showed that initially students had difficulties in writing narrative text but after the treatment was done the students showed significant changes, they began to be able to develop ideas to create stories and share advise with their friends in other groups. The result of interview showed that students faced the difficulties in grammar and mechanic aspect.