Reviewerly/exHarmony huggingface dataset:
감정분석의 시각화를 통한 셰익스피어 4대 비극작품 주요 등장인물의 막간 감정 추이와 감정 관계 연구

The purpose of this study is to investigate emotional changes in an Act and across Acts and the emotion relationship between major characters in Shakespeare's four great tragedies through visualization of sentiment analysis using dialogue corpora, a VADER sentiment word-list, Python 3.5, and Netminer 4.4. We use both bar graphs and line charts as time visualization. The bar charts show how emotional changes between major characters are compared within an Act and across Acts in the normalized positive and negative sentiment valence sum. The line charts show who has emotional ups and downs throughout the whole play in the average sentiment valence. This study also attempts to visualize network structures connecting major characters and discuss sentiment intensity to tell us how much positive or negative sentiment there is in their detailed emotion relationship, representing relation visualization.
IMPLEMENTASI LOGIKA FUZZY DALAM MENENTUKAN JURUSAN SISWA BARU: (STUDI KASUS : SMK TAMAN SISWA RANCAEKEK)

Education plays a very important role in the process of improving the quality of human resources. The process of selecting a course for prospective students by SMK Taman Siswa Rancaekek is done in a way that is still manual. The research aims to analyse new students in determining the majors that match their talents, interests and abilities. Therefore, the results of this research built the Fuzzy logic implementation system using Tsukamoto method, from the research results get that Tsukamoto method is able to provide recommendations according to subjects that have value High.
USING DYNAMIC CONTENT TO INCREASE RELEVANCE

This article explores the process of using dynamic content to increase the relevance and conversion rate of a web resource. The main advantage of this approach is that it does not require the creation of additional pages of the site, increases the relevance of the content and, consequently, the likelihood of obtaining the effect of conversion.
인공지능의 군사적 활용 가능성과 과제

The era of the Fourth Industrial Revolution, which is characterized by the development of artificial intelligence(AI), big data, robot technology, object recognition, virtual reality, and life science, is known as the era of convergence. The new technologies are fused with one another, and they are rapidly changing our daily lives. In fact, aside from the impact on normal life, the unprecedented development of science and technology is also accelerating the pace of change of the battlefields of the future. Many scholars predict that AI will give rise to smart battlefields based on hyper-intelligent and hyper-connective technologies. Many states are now rapidly and actively implementing the basic and applied technologies associated with AI in the military field, although there is a lack of research concerning such technologies in Korea. Therefore, this paper aims to understand the concept of AI and its military applicability in the Korean context rather than to engage in a detailed technical discussion. First, the definition and current level of AI were evaluated. Second, this paper discusses in detail how AI is used in military activities at the tactical and operational levels to implement the key concepts of future warfare, including swarming tactics and multi-domain operations. Finally, the paper examines the limitations and potential problems regarding the application of AI to the battlefields and also discusses the possible measures and strategies to overcome the challenges associated with AI-based warfare.
MATHEMATICAL TASKS FOR THE PRESCHOOL EDUCATION BASED ON CHILDREN'S DAILY LIFE

Today, more than ever, school is expected to provide students with a solid mathematical knowledge and experience that will enable them, throughout their education, to integrate and mobilize them in diverse contexts, as well as in their future lives at a personal, professional, or social level. Being aware of this situation, we think that these skills in students should be developed in the early years, and in this sense it is up to the teacher to provide children with challenging and enriching experiences so that they feel motivated to study mathematics. These learning situations involve the use of different methodologies based on non-routine tasks of a diversified nature, contextualized in the students’ daily lives and that help them to build new mathematical knowledge, developed logical-mathematical reasoning, problem solving, as well as creativity and critical thinking. In this way, students will acquire a taste for mathematics and will certainly be able to appreciate this science, allowing them to develop a proper vision and positive outlook on its role and use in the current world. In this article we present a proposal of tasks that were implemented with a group of Pre-school children, in the context of Supervised Teaching Practice, related to the area of mathematics, in interdisciplinarity with the other areas of knowledge, taking into account the learning to be promoted according to the Curriculum Guidelines for Pre-school Education. These tasks allow us to work mathematics in a concrete context, close to the students’ daily lives, such as commemorative days of various annual events, based on means and didactics resources familiar to children, as well as others specifically built for this purpose, as playful and dynamic as possible. This way of promoting the learning of concepts, appealing, whenever possible, to concrete realities of everyday life will allow students to more easily understand and accept them, thus promoting learning with an understanding of these contents. We believe that these task proposals can also be used as inspiration for the adaptation or creation of other possibilities of use not only in the Portuguese context, but also in other foreign contexts.
Computation of Verb Similarity

In this paper, we focus on verb similarity where the noun similarity is taken as a benchmark. The calculation of similarity between verbs is not an easy task as initially there is no standard dataset available for the calculation of verb similarity. Secondly, there is no exact idea that the Wordnet Verb hierarchy is capable to calculate the verb similarity. The Calculation of similarity considers three parameters such as path, link, and depth. But in this paper, in addition to the previous parameters, we also considered parameters such as stem-similarity weighting, derivation nouns weighting, and gloss similarity weighting. Moreover, we implemented two algorithms namely Rich Hierarchy Exploration and Shallow Hierarchy Exploration, and found that there is no significant difference in its performance.
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs

Graph Neural Networks (GNNs) have shown excellent performance on graphs that exhibit strong homophily with respect to the node labels i.e. connected nodes have same labels. However, they perform poorly on heterophilic graphs. Recent approaches have typically modified aggregation schemes, designed adaptive graph filters, etc. to address this limitation. In spite of this, the performance on heterophilic graphs can still be poor. We propose a simple alternative method that exploits Truncated Singular Value Decomposition (TSVD) of topological structure and node features. Our approach achieves up to ~30% improvement in performance over state-of-the-art methods on heterophilic graphs. This work is an early investigation into methods that differ from aggregation based approaches. Our experimental results suggest that it might be important to explore other alternatives to aggregation methods for heterophilic setting.
ANALYSIS OF THE MAIN GENERATOR DUAL FUEL DIESEL ELECTRIC (DFDE) 12V50DF SUDDEN TRIP

In the 20th century, the growth of marine transportation has grown rapidly in line with technological advances. Given that the marine transportation sector is one of the pollutants that exist today, the use of energy sources with better thermal efficiency and combustion that does not have a negative impact on the environment is needed in the modern era. In accordance with the regulations stipulated by IMO in the Marine Polution (Marpol) Annex VI Regulation 14 which regulates the prohibition of ships from using fuels with sulfur content higher than 0.5%. The need for alternative fuels in the shipping industry is an important thought to support the efficiency of the shipping industry. Liquid Natural Gas (LNG) is currently being developed by the government as a fuel for vehicles and environmentally friendly industries. In addition to its availability, natural gas is also considered effective for combustion. Methane / LNG gas is one of the most dominant alternative fuels at this time. This fuel can also save company expenses, namely reducing the cost of providing fuel for energy needs as a source of propulsion on board the ship. For the above, ships, especially LNG carriers, have used a lot of diesel engines to propel their ships using LNG fuel with the concept of the engine being Two Fuel Diesel Electric (DFDE) where the engine can use Marine Diesel Oil (MDO) and LNG. The DFDE engine drives the Generator and the Generator generates electricity to drive the Electric Motor and the Electric motor moves the propeller shaft, this DFDE engine in the future will replace conventional diesel engines because it is more cost efficient, but requires Engineers who understand DFDE engine technology.
IDENTIFIKASI SAMPAH ANORGANIK PADA EKOSISTEM MANGROVE DI DESA LESAH KECAMATAN TAGULANDANG KABUPATEN SITARO

Based on the material content, waste is grouped into two types, namely organic waste (waste derived from animal, plant and human parts) and inorganic waste (waste derived from materials such as metal, glass, styrofoam, plastic and rubber). Inorganic waste is one of the coastal pollution problems, yet information about inorganic waste in mangrove ecosystem was relatively low, especially at Lesah Village, Tagulandang Sub district, Sitaro Regency. This study aims to determine the distribution of inorganic waste by type and to analyze the characteristic of inorganic waste based on the amount of size and weight found. The method used in this research is the line transects method at 3 different stations. The results showed that the types of marine debris that found were plastic, rubber, metal, and glass waste and there were 2 characteristics, namely mega-debris and macro-debris. Of the various types of debris obtained, plastic is the most commonly found, 161 items/23.329m2 (69.099 Items/ha) with a total weight of 1357.75 gram/ha and a total size of 1938.93 cm/ha. Followed by rubber debris as many as 5 items/23.329m2 (2.146 items/ha) with a total weight of 159.309 gram/ha and a total size of 59.871 cm/ha. Then, glass debris as many as 4 items/23.329m2 (1.717 items/ha) with a total weight of 402,159 grams/ha a total size of 31.030 cm/ha. Whereas, metal debris is the lowest value found as many as 3 item/23.329m2 (1.288 items/ha) with a total weight of 67.622 gram/ha and a total size of 19.528 cm/ha.Keywords: Inorganic waste, Mangrove Ecosystem, Desa Lesah
Real-time Malicious URL Detection Using Machine Learning

In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. This paper proposes machine learning based mostly on the approach to scrutinizing universal resource locator instead of linear approaching of saving information and examination 33,1622 URLs with 62 options were collected to validate the planned feature engineering strategies.
Fuzzy Topsis System Untuk Pemilihan Karyawan Terbaik Pada PT. Delta Dunia Textile

This research implements a fuzzy topsis based system for selecting the best employees at PT. Delta World Textil. One of the matters, especially in the management of Human Energy Resources (HR) is the selection of the best employees periodically, so that those who are elected will be given an award in the form of a bonus in order to motivate employees to improve their service and performance. The best and quality employees are the legacy of the industry that wants to make the industry grow rapidly. Several methods have been proposed for selecting the best employees. However, the method used is inaccurate because it only uses one method with few criteria. This study aims to select the best employees by looking at several criteria in the form of discipline, teamwork, attitudes, presence, skills, loyalty, tenure, and productivity for initial processing using fuzzy logic. Initial values are obtained in the form of membership function values which are used as input into the topsis method. The first stage of the topsis method is carried out in the normalized decision metric stage, the results of this stage are used to find a weighted normalized decision matrix according to the weight of the criteria for each criterion, the results of this stage are used to ensure positive ideal solving and negative perfect solutions after that the distance between the values is determined. each alternative with a positive perfect solution matrix and a negative perfect solution matrix. In the last session, the highest preference value was sought so that the best employees were obtained. The results show that the system established is very feasible in ensuring the best employees in performance evaluation. Keywords : Fuzzy Logic, Topsis, Best Employees, Decision Support System
THE TECHNOLOGICAL ASPECTS OF THE DIGITAL TRANSFORMATION EXPERIENCE OF UNIVERSITY EDUCATION DURING THE COVID-19 PANDEMIC

THE TECHNOLOGICAL ASPECTS OF THE DIGITAL TRANSFORMATION EXPERIENCE OF UNIVERSITY EDUCATION DURING THE COVID-19 PANDEMIC
Effective video retrieval system using Adaptive Shot Detection and Feature Vector Algorithm

In the current situation, around 150 million hours of video are uploaded to the Internet (i.e., YouTube, Netflix, Dailymotion, Vimeo, etc.). It becomes very difficult to extract the required relevant videos from such a large data set. Semantic / context-based matching is fast but highly dependent on the correct tags assigned to the video. On the other hand, due to the large number of frames involved in the video, it is difficult to apply a context-based search to the video. We have developed a novel video retrieval system that can extract the required videos from large sets of video data. The algorithm consists of content-based adaptive shot detection and feature vector extraction from each video from the dataset. The user only needs to provide an image similar to the system input to search for any video in the dataset.
The Use of Guided–Questions Combined with Buzz Group Technique to Increase Students’ Writing Skill of SMP Muhammadiyah Pagaralam

Buzz Group Tehcnique are a technique in teaching which divide students into a group activity in which groups of students have a brief discussion (for example, five minutes) to generate ideas or answer specific questions. Buzz group can be used in many different ways and are most often used in combination with other techniques”. In this research the writer will combined two kinds of technique, Guided-question Combined with Buzz Group Technique. Guided-question Combined with Buzz Group Technique means combine two kinds of technique in teaching learning process those are Guided-question with Buzz Group Technique to enhance both techniques. The research design used in this study was one-group pre test-post test design. The study employed both quantitative and qualitative data analyses from pre-and post-tests, a questionnaire, and an interview. The participants of the study were 35 first-year students enrolling in a compulsory reading course called Communication and Reading Skills at Darussalam Polytechnic of Palembang. It is shown shown by a significant difference in quality of students’ in-class written experimental designs between the treatment and control groups (19.943 versus 17.943; p &gt;0.0489). However, draft (22.337 versus 18.929; p &gt;0.0760) and paper grades (27.186 versus 27.971; p &gt;0.6726) did not vary significantly whether or not students were provided with the guided questions. There were several intervening and potentially confounding factors, due to the nature of the paper writing process in our labs, which included peer review of paper drafts that were not limited to students within the treatment and control groups.. The results suggested that 1) The English writing ability post test mean score of students was higher than the pre test mean score at the 0.05 level of significance; 2) most students were satisfied with their own writing ability; 3) they enjoyed working in group and agreed that mind mapping technique was a useful technique and can be applied to non- English subjects. Findings and implications for further research are discussion.
Improved CLARA-High-Dimensional Data Clustering Using Improved Clustering Large Applications

High-dimensional data clustering mechanisms are appearing, based on information clamorous and low-quality difficulties. Many of the current clustering algorithms become implicitly ineffective if the algorithms' essential similarity measure is calculated between data points in the high-dimensional space. To this end, various projected based clustering algorithms have been proposed. But, most of them faced problems when clusters cover in subspaces with very less dimensionality. To this end, the partition based Improved Clustering Large Applications (ICLARA) mechanism is employed. It is an expansion to approach to trade with data comprising many objects to reduce computing time and RAM storage problems. The proposed describes various representations and provides the most suitable clustering as the result to work with large datasets. The proposed approach is compared with previous hierarchal based CURE (Clustering Using REpresentatives), BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies), and Partitional Distance-Based Projected Clustering (PDBPC) approaches.Also, we calculated the accuracy of all clustering techniques about their parameters configuration. The experimental results show the proposed Improved CLARA algorithm provides better accuracy compared with previous methods.
Personalized Response Generation with Tensor Factorization

Personalized response generation is essential for more human-like conversations.However, how to model user personalization information with no explicit user persona descriptions or demographics still remains underinvestigated.To tackle the data sparsity problem and the huge number of users, we utilize tensor factorization to model users' personalization information with their posting histories.Specifically, we introduce the personalized response embedding for all questionuser pairs and form them into a three-mode tensor, decomposed by Tucker decomposition.The personalized response embedding is fed to either the decoder of an LSTM-based Seq2Seq model or a transformer language model to help generate more personalized responses.To evaluate how personalized the generated responses are, we further propose a novel ranking-based metric called Per-Hits@k which measures how likely are the generated responses come from the corresponding users.Results on a large-scale English conversation dataset show that our proposed tensor factorization based models generate more personalized and higher quality responses compared to baselines.We have publicly released our code at
The Effectiveness of Arranging Word Game In Teaching Grammar: An Evidence From VIII Grade Students of SMPN 2 Simpang Alahan Mati, Indonesia

The aim of this research was to know how the students’ ability in arranging word into a sentence of simple present tense and effectiveness of Arranging Word Game in teaching simple present tense at VIII Grade Students of SMPN 2 Simpang Alahan Mati. The researcher found some problems that related to arranging word game which was used by English teacher. The first problem was English teacher has been applied and used Arranging Word Game in teaching simple present tense, but some students still had difficulties in arranging word into a sentence. The second problem was some students often forgot with the structure of the sentence which was taught before such as the structure of simple present tense and the students’ mark was somewhat varied which 65% of the students were considered to have poor achievement. The third problem was some students still could not make sentence such as arranging word into a good sentence and could not understand the material well. This research used a descriptive quantitative research. The population of this research was all students at VIII Grade of SMP N 2 Simpang Alahan Mati where it consisted of two classes which were VIII.1 and VIII.2. In this research, the researcher used total sampling as a sampling technique and the total of sample was 65 students of VIII Grade students. The instruments that were used in this research were test and questionnaire. Based the result of this research, it was concluded that students’ ability in mastering simple present tense at VIII Grade Students of SMPN 2 Simpang Alahan Mati was very good category where the mean of students’ test result was 88,06 on the rating scale 80-100 which was on the very good category. Furthermore, Arranging Word game was effective to be used in teaching simple present tense at VIII Grade Student of SMPN 2 Simpang Alahan Mati where it was gotten from the mean data percentage of students’ questionnaire result which was 77,06% on the percentage of rating scale on 72-89% which it was effective on rating quality.
One-dimensional Block Matching Algorithm in Video Image Motion Estimation

<p indent=0mm>Motion estimation is a basic problem in the fields of video image compression and video image restoration. The traditional block matching methods have good search quality, but the search speed is not fast enough. Aiming at the shortcomings of the search speed in the traditional block matching methods, we proposed a fast one-dimensional block matching motion estimation algorithm. Firstly, the motion vector is orthogonally decomposed, and the two-dimensional matching block is reduced by a special weight coefficient matrix to obtain two sets of one-dimensional feature matrices. Then the one-dimensional three step search method is selected as the search strategy. The sum of absolute differences criterion is used as the matching criterion. The two sets of one-dimensional feature matrices are used to search for the two components of the matching motion vector. Finally the two components are formed into a complete motion vector. The results of multiple sets of comparative experiments show that the search speed of motion estimation is significantly improved while the algorithm is guaranteed to quantitatively evaluate the PSNR. The higher the video definition and the larger the pixel size of the matching block, the better the algorithm can improve the search speed of motion estimation.