Reviewerly/exHarmony huggingface dataset:
Analysis of Job Interest Type and Academic Achievement of Automobile Major Students

This study was conducted to identify the suitability of majors and jobs through an analysis of the career interest types and academic achievements of automotive students in the engineering department of Y University, and to use them as basic data for learning guidance, career guidance, and curriculum development. The STRONGTM Occupational Interest Test, a standardization tool for occupational interest tests, was conducted in May of the 2022 academic year, the first semester, and in September of the 2022 academic year, the second semester. The analysis tool used SPSS 14.0 to analyze GOT, BIS, PSS, and academic achievement by performing frequency analysis, mean analysis, correlation analysis, and variance analysis. First, the type of career interest of automotive students is 86% R when examined with the 1st code, R is 46.8% when considering the 2nd code, and R is 36.4% when considering both 3rd codes, so the proportion of R type is high. Therefore, it is necessary to prepare a study guidance and career guidance plan at the department level that takes into account the characteristics of the field type presented in the previous research. Second, in the correlation analysis of GOT and the Basic Interest Scale (BIS), it was analyzed that among the BIS scales of R and R, the mechanical field had the highest correlation (0.963). This results suggest that students have a very high interest in jobs and activities that work with machines. Third, in the analysis of GET and academic achievement, as mentioned in the previous study, the field type was analyzed as having the lowest academic achievement, and there was no significant difference in learning level for each type. In the future, academic achievement needs to be analyzed by subjects of liberal arts and majors, and detailed analysis is required considering values, learning attitudes, and learning methods in addition to interests. Fourth, in the Analysis of the Personal Characteristics Scale (PSS), they tend to prefer to work alone, preferring practical qualifications, short-term learning, and carrying out what they are directed to do with participatory leadership. In addition, it is analyzed that people prefer to challenge themselves towards adventure, so it is necessary to design lessons so that they can present or challenge themselves in class at school sites, and participate in certificates, competitions, and competitions.
Educational Needs in Reading and Writing across Different Age Groups with Dyslexia: Elementary, Secondary, and College Students

본 연구는 난독현상을 보이는 초등학교, 중고등학교 학생들과 대학생 성인의 읽기, 쓰기 능력을 비교하였다. 초등학교 10명, 중고등학교 9명, 대학생 성인 10명을 대상으로 읽기, 쓰기 및 관련 영역의 검사를 실시하였다. 검사결과 세 집단은 읽기이해, 듣기이해, 철자 검사 결과에서 유의한 차이가 없었으며 단어읽기, 읽기유창성, 음운처리속도, 문장 따라 말하기 검사에서는 대학생 난독성인이 다른 연령그룹의 난독학생들보다 높은 수행 수준을 보여주었다. 검사결과를 종합해 보면 대학생이 된 난독 성인들에서는 일부 향상된 능력이 관찰되었지만 전반적으로 초등학교 6학년부터 성인기 초기에 이르기까지 읽기 및 쓰기 능력에서 난독현상은 지속성이 높다고 볼 수 있었다. 특히 상위인지를 필요로 하는 읽기나 듣기이해능력과 철자 영역에서 지속적인 어려움이 관찰되었다. 연구자들은 국내에서는 처음으로 다양한 연령대에서 난독현상의 지속성을 데이터를 통해 증명하였다. 국내에서도 난독현상이 초등 이후에 사라지거나 저절로 나아지는 것이 아니라는 근거를 제시함으로써 난독 지원 체계가 중등학년과 대학으로 확대될 필요성이 있음을 시사하였다.Korean research initiatives and educational policies related to dyslexia currently tend to cater to elementary school children. However, the impact of dyslexia is lifelong; that is, individuals with dyslexia experience constant difficulties regarding literacy-related skills throughout their school-going age and adulthood. This study compares literacy-related skills in three age groups of students with dyslexia: sixth graders at elementary school, secondary school students, and college students. Herein, participants were administered word reading, reading fluency, reading comprehension, and spelling tasks along with letter knowledge, working memory, and listening comprehension tests. Surprisingly, the study results revealed that scores in reading comprehension, listening comprehension, and spelling were similar in all three age groups. College students presented superior word recognition, reading fluency, phonological processing speed, and working memory compared with sixth graders and/or secondary school students. These results imply that literacy-related skills, especially those relatively more cognitively demanding, do not improve easily in students with dyslexia in the absence of systematic intervention to support their learning. To our knowledge, this investigation is the first to observe differences in the educational needs of Korean dyslexic students across age groups. Future studies should investigate the educational needs of secondary and postsecondary students with dyslexia to properly support them in overcoming their lifelong struggles with dyslexia.
Microstructures Mimic Meso-Scale Structures

The chapter deals with the imitation of meso-scale as microstructures in photomicrographs from a complexly deformed Precambrian terrane of the Aravalli craton from northwest India. These structures are mostly seen in low to medium-grade metamorphosed metasediments e.g., calc-silicates, schists, and gneisses.
Challenges of globalization and quality of education: legal aspect

The article explores the issues of higher education quality in the context of global changes, taking into account the legal framework, which emphasizes the relevance of research. The approach to study the impact of international trends on the quality of higher education institutions, the level of educational services and the demand for graduates in the labor market is of scientific interest.&nbsp; The purpose of the study is to validate the interaction of global trends on the quality of academic services, to identify the problems of quality of higher education, the specific features of the transformation of education and to determine the main guidelines to improve their competitiveness. Ongoing monitoring and comparative analysis have indicated that in order to improve the quality of education in higher education institutions it is essential to continue further targeted work in accord with international quality standards, which will facilitate the entry into the world educational space. The study is descriptive and sequential, from simple to complex, which examines the essence of the quality education concept, presents development stages of this category, examines legislative support, formation of independent evaluation of HEIs and study programmes, which allows to determine the critical role and particular importance of promoting quality culture in higher education institutions. The study proposes to develop an annual Action Plan for the implementation of the University Development Strategy, taking into account risk management, which will allow universities to improve the quality of educational programmes and increase the competitiveness of graduates. The study advances knowledge in the area of international accreditation and provides insight to management, faculty, students and stakeholders on the challenges of implementing international standards and external quality assurance in education. Key words: globalisation, quality of education, legal assurance, accreditation.
Food Menu Recommendations Based on Recommended Dietary Allowances using Genetic Algorithm

Nowadays, there are still often unbalanced nutritional problems such as overnutrition or malnutrition. Many factors can affect it, one of which is an unbalanced diet. One solution that can be done is a system for optimizing nutritional needs. In this study, the method used for optimization is genetic algorithms. Genetic algorithms are one of the metaheuristic methods that are often used for optimization problems. A particular chromosome representation is designed to provide suitable solutions. The system can provide food recommendations with nutrients close to a person's nutritional needs by using the genetic algorithm. Based on the test results obtained, the difference in nutrition from food recommendations with nutritional needs is below 5 percent.
Manufacturing of Medical Devices Using Artificial Intelligence-Based Troubleshooters

To make a process independent of human skills, an artificial intelligent (AI) agent is required which would learn the tricks of trade in exactly the same fashion as a human would do. This work showcases an AI agent which gains knowledge of the manufacturing process exactly the same way as an operator learns on the production floor. The AI agent incrementally learns the process when presented with positive and negative events on the floor. No supervision is provided for the leaning activity of the agent, rather it is exposed to the same set of events as an operator on the floor. The AI agent makes use of these events and the device history record (DHR) to learn and then come up with solutions for the problems presented to it. The unsupervised learning is modeled here to understand how an AI agent behaves against the systemic learning in certain other scenarios.
Content-Based Image Retrieval Techniques and Their Applications in Medical Science

Introduction: Content-based image retrieval (CBIR) retrieves the images from the vast image repositories. Research in the CBIR domain gets attention due to the massive number of images generated by the mobiles and various image-capturing machines. Objectives: Any image retrieval system’s primary goal is to reduce the semantic gap between low-level features and high-level perception. Methods: The CBIR techniques are classified into multiple categories based on the feature extraction and retrieval mechanism. These categories are feature-based, machine-learning-based, and deep-learning-based methods. The pioneer techniques for each category are explained in detail in this chapter. Results: The comparative analysis has been done to highlight the advantages of techniques over others. Conclusion: The various application area of the CBIR has been described. The most evolving application is the content-based medical image retrieval (CBMIR) system. The applicability of the CBMIR system in different medical science domains is explained in detail.
Histopathology Whole Slide Image Analysis for Breast Cancer Detection

In this work, we propose a novel method for weakly supervised histopathology whole slide image (WSI) classification for addressing the breast cancer detection task. Some of the salient aspects of our approach include extracting embeddings from a pretrained CNN network, using a cosine loss and training schedule for the classification network, and suggesting an overall decision making criteria for the WSI based on intermediate decisions on local random selection. We also provide an extensive review of closely related methods with an elaborate compression analysis of the embeddings used in these. Finally, we validate our approach on two well-known datasets, Camelyon16 and Camelyon17 with a variety of results and comparisons related weakly supervised methods.
Blijken: een evidentieel-miratieve outsider

Dutch has three seem-type verbs (schijnen, lijken, blijken), which behave in clearly different ways, although they can all be regarded as epistemicevidential markers in some of their uses. This paper addresses the semantic contribution of blijken, its morpho-syntactic variability and the possible link between both. The analysis is based on data taken from the Corpus of Spoken Dutch (CGN). One of the main findings of this paper pertains to the fact that blijken not only has (typically intersubjective) epistemic-evidential meaning, but also expresses mirativity, especially in those constructional patterns in which the qualification expressed by the verb is non-focal (and hence has only secondary information status). The corpus data show that such non-focal uses of blijken can occur in every construction type the verb occurs in, but clearly favour inherently non-focalizing syntactic patterns like the auxiliary use of blijken with a te-infinitive.
VEŠTAČKA INTELIGENCIJA I AUTORSKO PRAVO

Nowadays, artificial intelligence is no longer science fiction, but is present all around us. Just as artificial intelligence is increasingly affecting our daily lives, it has also gained importance in the field of intellectual property. Since innovative companies are interested in protecting their ideas in a technical environment, the question arises as to how the results generated by artificial intelligence can be protected. The issue of such protection has also become relevant in the field of copyright. For example, the Nanshan District Court in Shenzhen (China) ruled that an article written by an intelligent writing assistance system was protected by copyright. The company that developed the software for this system has accused another company of copyright infringement, which is said to have made this article available to the public on its website. The court ruled in favor of the plaintiff. On the other hand, Christie's is the first auction house to offer a work of art created by an algorithm. It is a portrait of Edmond Bellamy that was sold for 432,500 US dollars. This sale is actually a signal that works of art that are the product of artificial intelligence are slowly entering the world auction stage. Artificial intelligence is therefore able to create works of art and literature that are just as original and creative as human creations. In the paper, the author dealt with the question of whether the results generated by artificial intelligence de lege lata are protected by copyright, as well as whether de lege ferenda new legal solutions will be developed in the field of creative artificial intelligence.
MEDIJSKE USLUGE I SEKSIZAM

Media services are provided in the circumstances of the development of technology and the emergence of a large number of media that are not media in the legal sense of the word. Digitalization and development of the Internet as a platform for communication through which information is exchanged at high speed has brought many advantages but also challenges due to the inability to pre-check content in terms of its truthfulness and accuracy. It is noticeable that the lack of editorial cyontrola has led to an increase in hate speech, discrimination, sexism and other forms of violation of freedom of expression. Sexism as a form of discriminatory perception of gender roles and gender identity is recognized as a particularly dangerous way of creating media content because it is based on stereotypes and generalizations about the roles of women and men in society, which in the long run intensifies inequality and prevents the functioning of democracy as a form of government and organization of state power, at the base of which is the equality of all citizens regardless of their special characteristics. Since the role of the media in society is defined as the role of the "guardian dog" of democratic institutions, it is very important to understand and identify what exactly sexism is, how it is related to the concept of gender equality and how much through media content (non)contributes to the development of a society based on mutual respect and respect for diversity in all its manifestations. In 2021, the Law on Gender Equality was adopted in Serbia, which clearly defines the concepts of gender, gender, equal opportunities of both sexes and defines discrimination on the basis of gender, gender characteristics and gender, which further achieved the positive obligation of the state in the direction of improving the human rights situation in this area. The paper starts from the thesis that in addition to the improved legal regulations in the field of gender equality, and measures to combat and prevent all forms of gender-based violence, violence against women and domestic violence, in practice there has been an increase in this form of discrimination both through the actions of certain institutions of the system and the political establishment, as well as through the actions of the media. That is why it is necessary to improve regulations in the field of media in the direction of defining social media as a media in the legal sense with all the responsibilities that this entails, especially since at the level of the European Union such regulations are adopted. In addition to the provision prohibiting discrimination and hate speech, media laws should also include a provision prohibiting sexism. Of great importance would be preventive action towards the education of media workers and media service providers, as much as the placement of sexist content in the long run is harmful to the state of democratic institutions and human rights of a society.
Fault Detection in Inertial Measurement Unit and Global Navigation Satellite System of an Unmanned surface vehicle

This paper presents a method which detects faults in the measurement required for navigation of an unmanned surface vehicle. The measurement includes acceleration and angular rate by an inertial measurement unit (IMU), and the location by global navigation satellite system (GNSS). The method uses Kalman filter to estimate the state variables which represent the amount of faulty measurements. The method is tested by the experiment in which a boat equipped by commercial IMU and GNSS navigates in a sea trial. The result verifies that faults in acceleration and angular rate measurements are detected robustly and the GNSS position fault is detected when there is considerable location error.
Iterative LQR with Discrete Barrier States for Efficient Collision Avoidance of Autonomous Vehicle

Ensuring safe motion planning of autonomous vehicles, especially on collision avoidance in an emergency, is challenging. Many optimal control methods have been proposed for safe and efficient nonlinear motion planning. It is well known that iterative linear quadratic regulator (iLQR) is particularly suitable for nonlinear optimization. Although many methods have been developed to solve the inequality constrained differential dynamic programming (DDP), this paper proposes a method for efficient vehicle motion planning by using discrete barrier states to iLQR. In the proposed method, multiple inequality constraints such as obstacle avoidance and road boundaries are reflected in a single barrier state in the collision avoidance scenario and applied to the iLQR/DDP framework. For comparison, both the unconstrained iLQR using the potential field method and the barrier state iLQR proposed in this study were simulated in the collision avoidance scenario. We tested on a real-time software-in-the-loop simulation using CarMaker and ROS. Compared with the unconstrained iLQR, our proposed method generated a safe and efficient optimized trajectory for autonomous vehicles in emergency situations such as fishhook tests.
Promoting a Hybrid Cryptosystem System’s Security based on Fresnel lens and RSA Algorithm

with the growing concerns of the current network security, development of hybrid cryptosystem based on the combination of optical symmetric cryptography and public key cryptography has aroused considerable research interest. In optical symmetry system, a new method for encrypting optical information using Fresnel lenses is proposed. The symmetry system’s keys include the focal length (f) and propagation wavelength ($\lambda$). Then, in public key cryptography, the key ($\lambda$,J) is encrypted by the RSA algorithm. Finally, we have implemented and result have been obtained using 12-level digital Fresnel lens by COMSOL Multiphysics to study of how the optical image deciphered the information using encryption keys. In addition, the main challenges and future prospects for the further development of hybrid cryptosystem system are discussed.
Research on Algorithms of Positive and Negative Co-occurrence in Spatio-temporal Datasets

Discovering spatio-temporal co-occurrence patterns is a significant issue in many fields. Previous algorithms simply looked for positive patterns when mining spatial co-occurrence patterns. However, patterns with strong negative associations are ignored. This paper proposed a novel algorithm for mining both positive and negative co-occurrence patterns. We introduced the notions of positive and negative co-occurrence patterns, and positive and negative co-occurrence patterns are mined by using an effective pruning strategy. This paper analyzed the completeness and correctness of the algorithm. We conducted experiments using both real and synthetic data sets to validate the effectiveness and efficiency of the suggested method.
A Path Planning and Coordination Algorithm for Heterogeneous Tasks of Multi-UGV in Smart Farm: Work in Progress

We propose a path planning and coordination algorithm for the heterogeneous tasks of multiple unmanned ground vehicles in a smart farm. The proposed algorithm considers the priorities of each of the tasks to maximize the productivity of smart farms. The algorithm can solve a scenario in which the robot operations are stopped unnecessarily. The proposed algorithm will be verified in a field evaluation. In this paper, we describe our experimental scenarios and list the performance metrics used in the field experiments. For evaluation, situations in which multiple UGVs are required to be coordinated in a smart farm were assumed as the experimental scenarios. The following performance metrics were used: (1) utilization rate, (2) success rate, (3) number of collisions, and (4) localization errors. The experimental results will be statistically analyzed. We hope that the analysis results will help determine whether the proposed path planning and coordination algorithm is effective when used in smart farms.
A Sensor-Based Study for Security Events Detection Systems On Board Autonomous Trains

The Human wish for autonomy in vehicles goes back to the 15 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> century and has been the subject of numerous research. In the past decade in particular, the rise of Artificial Intelligence & Deep Learning has provided new efficient tools for self-driving transportation systems. Most of existing works focus on cars, while trains have attracted less attention. However, railway is the most interesting transportation mode in the optic of sustainability. Given the high number of passengers it may carry, an autonomous train must analyze even more accurately its environment. It must also recognize everything happening in its cars to ensure passengers security. The total absence of railway agents on-board fully autonomous trains brings requirements for a monitoring system. It would include sets of sensors for the acquisition, algorithms for analysis and telecommunication network to transfer either the data or its extracted information. Cameras are the first sensor that comes in mind as they would furnish images of the scenes, copying human vision. In addition, other signals such as sound and air composition may supply complementary or new information. The paper offers a review of sensors and their use through the scope of event detection, in the context of public transportation.
Application of Visual Inertial Odometry for Pose Estimation of a Mobile Robot

In this paper, an application of visual inertial odometry is described. Details of the implementation including the calibration are also described. The method uses visual data from two cameras and the measurements from inertial measurement unit. Previous researches usually used only front view image, whereas this study uses three different visual data from different view angles: front view, floor view, and ceiling view. The results are compared and the effect according to different view angles is analyzed. The comparison shows that the number of detectable features affects the performance of the visual odometry.