Reviewerly/exHarmony huggingface dataset:
Features of Organization of the Educational Process in the Cluster of Pedagogical Education and Formation of Self-development Competencies at Students

A key resource of the modern education system is steadily becoming its personnel potential. It is the teacher who is called upon to become the main link that influences positive changes in education, which, in turn, presents him with significant professional and personal requirements: to be highly educated and cultural, competent not only in his subject area, but also in the field of education, psychology , pedagogical technologies, ready for innovative pedagogical activity. The article discusses the features of the organization of the educational process in the cluster of teacher education and the formation of self-development competencies among university students
Optimizing model and feature selection using evolutionary swarm intelligence for image classification

Model selection is the way towards choosing one machine learning model among an assortment of competitor models for a training dataset. The correct model selection isvital in academic machine learning research as well as in many industrial settings. Figuring out the relevant features from a set of features and removing the irrelevant or less vital features which no longer make contributions to the target variable so that wecan gain higher accuracy for our model is a common problem. Feature Selection is one of the main things which highly influences the performance of the model. The features that are used to train the models have a big effect on the performance one could gain. Irrelevant features can negatively impact model performance. Evolutionary algorithms are known for optimizing the process. In this paper we use an evolutionary algorithmcalled Ant Colony Optimization (ACO) to select an optimized model for given data and then use another algorithm called Particle Swarm Optimization (PSO) to select best features so that we get best of both model and features for the give data. We found thatthe combination of an optimal architecture selected by ACO and optimal features selected by PSO gives higher accuracy.
Variational Bayesian Group-Level Sparsification for Knowledge Distillation

Deep neural networks are capable of learning powerful representation, but often limited by heavy network architectures and high computational cost. Knowledge distillation (KD) is one of the effective ways to perform model compression and inference acceleration. But the final student models remain parameter redundancy. To tackle these issues, we propose a novel approach, called Variational Bayesian Group-level Sparsification for Knowledge Distillation (VBGS-KD), to distill a large teacher network into a small and sparse student network while preserving accuracy. We impose the sparsity-inducing prior on the groups of parameters in the student model, and introduce the variational Bayesian approximation to learn structural sparseness, which can effectively prune most part of weights. The prune threshold is learned during training without extra fine-tuning. The proposed method can learn the robust student networks that have achieved satisifying accuracy and compact sizes compared with the state-of-the-arts methods. We have validated our method on the MNIST and CIFAR-10 datasets, observing 90.3% sparsity with 0.19% accuracy boosting in MNIST. Extensive experiments on the CIFAR-10 dataset demonstrate the efficiency of the proposed approach.
SAVAŞ KAVRAMININ DÖNÜŞÜMÜ: 1. ve 2. KÖRFEZ SAVAŞI ÖRNEĞİNDE HİBRİT SAVAŞLARIN İNCELENMESİ

The concept of war is in constant transformation and change. As humanity evolved, the course of wars changed in line with the technology and environment of this age. Although the existence and causes of wars have not changed greatly since ancient times, war types, tactics and strategies have changed. The battles performed today differ significantly from traditional battles. Battles turn into a genre in which different tools and methods are used together, which is also referred to as hybrid warfare. Although this type of war has been used since antiquity, it has often started to find its place in the security literature, especially after the collapse of the Soviet Union. This study intends to present the basic principles of hybrid warfare which is frequently used and one most of the important methods of warfare of our time and to contribute to Turkey's defense and security policy, survivability strategy. For this purpose, firstly, the transformation of the concept of war and the hybrid warfare that took place in the period from the Ancient Age to the present day was examined. In the study, the 1st and 2nd Gulf Wars were taken as a sample. Here,the reason of selecting the First Gulf War was that it was at the beginning period of the unipolar world order, cyber attacks were used in the war, and it was an important war in the development of the hybrid warfare. The 2nd Gulf War, on the other hand, was preferred because it is one of the most important examples that express the transformation of the wars after the September 11 attacks. Cyber wars were prefered because they have been the ones in which psychological warfare methods were effectively used. Literature scanning and sampling method were used in the study. What is hybrid warfare? What is the reason and importance of using hybrid identification? How does hybrid warfare differ from traditional warfare methods? Can Gulf Wars be considered as hybrid warfare? What is the contribution of the definition of Gulf Wars as hybrid warfare to the literature? Answers to the questions are sought.
Efforts to Improve Reading Skills Through the Critical Reading Method for Students of Widya Dharma University on Academic Year 2018/2019

The ability to read can be interpreted as the will and ability, as well as the readiness of a person to understand the ideas and symbols or sounds of language in a reading text that is tailored to the intent and purpose of the reader to obtain the desired message or information.Reading requires a good understanding, because reading requires a good ability in order to understand the reading text and interpret the reading content well.The ability in the context of learning is an effort to obtain competent fast, fast, and appropriate in dealing with learning problems.Departing from these problems, this study aims: 1) to describe how the reading comprehension condition of the second semester students of Widya Dharma University Klaten in understanding a reading presented bya teacher (read: lecturer); 2) to find out what causes students to have difficulty in understanding a reading given by a teacher (lecturer).
MOTIVATING DELEGATION MODEL AND ITS RATIONALE

The model of motivating delegation has been proposed and its justification by the results of recent studies in educational psychology, neurobiology and pedagogy has been presented. The actualization of the employee’s personal effectiveness lies in his internal, inherent and characteristic motivational model only for him. To build the model, the theory of self-motivation and the phenomenon of self-determination, recent discoveries in neurobiology have been used, a sequence of communication interactions between the director and the employee, which makes it possible to include the motivation of aspiration in the employee’s own motivational model, has been formulated. The main elements of the model are unconscious and conscious desires, and regulatory motives of both the leader and subordinate. Their hierarchy and interaction provide effective employee`s self-motivation in terms of setting the task, developing criteria for assessing the performance of the task. Motivating delegation allows you guaranteed to activate both the emotional part of the performer’s brain, which provides energy for the execution of the task, and the prefrontal complex, which is responsible for the thoughtfulness, creativity and consistency of the result and the process of the performance of the task.
PENERAPAN METODE TALKING STICK BERBANTUAN MEDIA VISUAL UNTUK MENINGKATKAN KEMAMPUAN BERBICARA TEKS EKSPOSISI

This research aimed to describe the implementation of talking stick method assisted visual media to improve exposition text speaking ability on Senior High School Muhammadiyah 1 Denpasar students’ grade X natural science 1 year 2019/2020 and to know students’ response toward the implementation of talking stick method assisted visual media to improve exposition text speaking ability on Senior High School Muhammadiyah 1 Denpasar students’ grade X natural science 1 year 2019/2020. This research was classroom actionresearch with the implementation of three cycles. The subject of this research was Senior High School Muhammadiyah 1 Denpasar students’ grade X natural science 1 amount 30 students and Dra. DewiSetyowati as Indonesian teacher. The method of collecting data that used in this research was testing method to get the result of students’ exposition text speaking ability and questionnaire method to get students’ response toward the implementation of talking stick method assisted visual media to improve exposition text speaking ability. The average result of students’ exposition text speaking ability on the first cycle was 64 with lack category, second cycle was 77,33 with adequate category, and third cycle was 88 with good category. After that, the result of students’ response toward the implementation of talking stick method on the first cycle was amount 49,16 with lack of positivity category, second cycle amount 72,16 with positive category, and third cycle was 87 with very positive category. It can be concluded that the implementation of talking stick method assisted visual media is able to improve exposition text speaking ability on Senior High School Muhammadiyah 1 Denpasar students’ grade X natural science 1 year 2019/2020.
Fuzzy Genetic Algorithm for Solving Optimization Problems

Considered a fuzzy genetic algorithm in which fuzzy rules for creating genetic operators with various properties and fuzzy criteria for stopping the genetic search process are implemented using fuzzy logic tools. In this case, the mathematical apparatus of the theory of fuzzy systems is used to encode, select the optimal parameters of genetic algorithms, select the fitness function and stopping criterion, and create fuzzy genetic operators.
K-Nearest Neighbor Classification for Detection of The Effect of Game Addiction on Cognitive Activity in The Late Adolescent Phase based on Brainwave Signals

World Health Organization (WHO) has determined that Gaming disorder is included in the International Classification of Diseases (ICD-11). The behavior of playing digital games included in the Gaming disorder category is characterized by impaired control of the game, increasing the priority given to the game more than other activities insofar as the game takes precedence over other daily interests and activities, and the continuation or improvement of the game despite negative consequences. The influence of video games on children's development has always been a polemic because in adolescence not only adopts cognitive abilities in learning activities, but also various strategies related to managing activities in learning, playing and socializing to improve cognitive abilities. Therefore, this research was conducted to analyze the cognitive activity of late teens in learning and playing games based on brainwave signals and to find out the impact of games on cognitive activity in adolescents. Prediction of the effect of the game on cognitive activity will be done by applying Fast Fourier Transform for feature extraction and K-Nearest Neighbor for classification. The results of the expert assessment showed the percentage of respondents with superior cognitive category but game addiction was 63.3% and respondents with cognitive categorization were average but were addicted by 36.6%. The percentage of accuracy produced by the system shows 80% in games and cognitive by using k values of 1, 6, and 7. The correlation test results show a percentage of 0.089, so it is concluded that there is no influence of the game on cognitive activity in late adolescents.
STEGANOGRAFI DENGAN AES PADA MEDIA SUARA BERBASIS INTERNET

Information is an important part of the current era. Information has become a necessity so as not to be left behind by the times. By utilizing information, ideas and innovations will emerge. This information can be used for the benefit of many people. The more developed means of communication, the more the use of information is also developing. With the increasing number of ways to access this information, we need an application that can be used to secure information by storing information in containers such as sound, so that information can not be known by others. Steganography is a file hiding technique that becomes confidential so that other people do not understand the secret message that is in it. Cryptography is the science and art of secure messages. Utilizing sound as a media to insert secret messages, as well as adding cryptography as a security message secret before being inserted, so that the process of transferring information can be done safely. The results of this study steganography techniques can be used in sound. By inserting a text message that is first encrypted and then entered into sound by the Least Significant Bit method.
Implementation of Environmental Issues in Teaching the Subject of Technical Education at Primary Schools

Nowadays, environmental issues belong to frequently discussed topics. Our article focuses on the implementation of environmental issues in teaching the subject of Technical education at primary schools in the Slovak Republic. Our research sample consisted of 123 students, graduates of primary schools in Trnava, Trenčín and Bratislava regions after they started to study at secondary vocational schools. We wanted to find out more information about their experience related to working with tools, instruments and machines, to developing their creativity, designing and manufacturing of their hand-made products. Our main questions dealt with environmental issues and their acquisition in the subject of Technical education. Up to 55.5 % of respondents stated that they did not learn, or they did not remember the area of environmental issues within the given subject. 7.8 % of respondents remembered mainly the topic of waste sorting out of all environmental issues discussed at the lessons of Technical education. In general, environmental aspects as cross-cutting topics of the educational process can be adequately demonstrated and implemented in the subject of Technical education. However, this implementation also requires a new conceptual approach to the teachers` education and the lifelong education of the whole society, as well.
ERA: Evolution of Residual Architectures

This thesis investigates how well a neural architecture search can find competitive image classifiers on the CIFAR-10 data set with limited computational resources. Most work done on architecture search either uses vast computational resources or narrow and strongly informed space of possible solutions. The solution space proposed consists of residual convolutional networks with separable convolutions and is explored by a primitive evolutionary procedure. When regularizing the evolution it proceeds to find an architecture outperforming the ResNet-110 baseline. Further evolution is shown to find networks with significantly stronger average performance than random search. In comparison with Bayesian optimization and local search, evolution show competitive final performance. Bayesian optimization however gives unmatched sample efficiency.One pressing matter in the process of reducing computations is how extensive networks must be trained before evaluation. Small scale experiments shows a tolerable rank-correlation between early performance and final performance of residual networks but indicates a bias for shallow networks.
Implementasi Steganografi dengan Metode Ranked Positional Weight Untuk File Mp3

Abstract Protecting information including multimedia documents is a major requirement in the era of information disclosure as it is currently. One way to overcome the above situation is to use steganography techniques. Steganography is the science and art of inserting secret messages in other messages so that the existence of the secret message cannot be known. To implement steganography using the Randked Positional Weight method by modifying the least significant bit or the last bit in one byte of data by using MP3 files as a storage medium. The results showed that the application was 100% successful in inserting and recalling messages that had been inserted. The result of message extraction has a message character compatibility level of 100% to the original message content. The size of the Mp3 after inserting a message is 100% the same as the size of the original Mp3. Mp3 files from steganography have very good quality above 50dB. However, steganography with the RPW method is not resistant to compression attacks that will cause the contents of the message in the Mp3 file to be lost.
Philosophy, Requirements and Technologies of Artificial Intelligence

Artificial intelligence is a very wide topic to talk about. It is a mapping of the human brain into a computer, to make computers intelligent and predict things. For instance it is mainly used for data representation and data manipulation and pure computer logic to solve and reduce and upgrade the current problems that we are facing. Within the intersection of these issues lies mechanized intelligence. Already, robot expert systems are taking over many jobs in industries that are dangerous for or beyond human ability. I highlight that the potential applications of artificial Intelligence are abundant. In this paper we are going to discuss the pros and cons of AI (artificial intelligence) in the present and upcoming technologies. It will also give some information about technologies required in AI and the future of it.
A Splicing Technique for Image Tampering using Morphological Operations

Image tampering is one part of the field of image editing or manipulation that changes certain parts of the graphic content of a given image. There are several techniques commonly used for image tampering, such as splicing, copy-move, retouching, etc. Splicing is a type of image tampering technique that combines two different images, replacing particular objects, skewing, rotation, etc. This study applies the splicing technique to image tampering using morphological operations. Morphology is a collection of image processing operations that process images based on their shape. The aim of this study is to replace particular objects in an original image with other objects that are similar to another selected image. In this study, we try to replace the ball object in the original image with another ball object from another image
LibGuides: Business Resources: Case Study Research and Resources

This guide presents business and related resources at the James E. Shepard Memorial Library at North Carolina Central University. Keep in mind that some of the greatest resources are people and the Shepard Library staff are available to assist you.
Predicting the Determinants of Dynamic Geometry Software Acceptance: A Two-Staged Structural Equation Modeling — Neural Network Approach

This research examined the predictors of dynamic geometry software adoption by using GeoGebra as a case study.The proposed model incorporated basic predictors of the technology acceptance model such as perceived usefulness (PU), perceived ease of use (PEOU), and attitude toward usage (ATU), as well as predictors relating to students' mathematics attitudes, namely self-confidence in mathematics, perceived value of mathematics (VAL), and enjoyment of mathematics.Data were collected from 175 students who had applied GeoGebra for their mathematics learning, and a two-stage hybrid structural equation modeling (SEM)-neural network approach was employed to test the proposed research model.First, the variables significantly influencing GeoGebra usage intention were identified through SEM.Subsequently, the identified predictors were ranked in terms of their relative influence by using a neural network model.The results showed that PU, PEOU, ATU, and VAL had significant effects on students' behavioral intentions to use GeoGebra, and PU was the most significant predictor of students' intentions to use GeoGebra in mathematics learning, followed by PEOU, ATU, and VAL.The results of this study could be useful for teachers to formulate effective strategies of integrating dynamic geometry software into their mathematics teaching.
OBJECTS DETECTION TECHNIQUES FROM IMAGES A SYSTEMATIC COMPARATIVE STUDY

Object detection is a Computer technology identified with Computer vision and image processing that manages to detect the instances of semantic objects of a specific class, (for example, people, structures, or cars) in digital images and videos. It is a technologically challenging and practically useful problem in the field of computer vision which deals with identifying the presence of different individual objects in an image. In this paper, the study of different techniques and methods of detecting objects from images in the field of computer vision and pattern recognition will studied and focus will on understanding the issues or points which causes hurdles in detecting objects from images and videos.
Mobile Social Service User Identification Framework Based on Action-Characteristic Data Retention

Mobile social services are an indispensable part of our daily lives. These services are also favored by criminals because it is difficult to retrieve communication data from them. In the past, communication data provided by telecommunication carriers usually indicated when, from where, and with whom the communication occurred. Presently, it is difficult for law enforcement agencies and public security departments to obtain information regarding mobile social services. For this reason, these departments have requested Internet access service providers to store data that can be used to identify the user of a mobile social service at any given time. However, many non-government and civil society organizations claim that these practices violate privacy rights; hence, they strongly oppose the retention of the subscribers' data by the government. Currently, the European Union law does not allow “general and indiscriminate retention of traffic data and location data,” except for “targeted” use against “serious crimes.” Under this premise, ensuring the necessary data retention, while reducing the privacy violations and maintaining public security is a challenging task. In this study, a novel identification framework based on different types and action characteristics of mobile social services is proposed. Based on this framework, government agencies do not need to retain general and indiscriminate traffic data, but only data that aid in identification. Thus, this framework substantially reduces the volume of potential targets and improves the probability of correct target identification, ensuring a balance between privacy and public security.
La dottrina come “motore” del biodiritto

After having recalled the different forms of legal innovation and the function that the doctrine plays in fostering such innovation, the essay will focus on the emergence, in Italy, of the “biodiritto” label, on its ordering function as a category and on the role of doctrine as an engine of its evolution.