Reviewerly/exHarmony huggingface dataset:
IMPROVING STUDENTS’ READING SKILL USING COMMUNICATIVE LANGUAGE TEACHING (A case study at tenth grade of SMAN 10 Depok)

The aims of this study are to analyze the materials and activities used in teaching reading and the result is to describe the process of improving students’ reading skill using communicative language teaching (CLT) used by the teacher at tenth grade of SMAN 10 Depok. The approach used in this study is qualitative, that is by doing observation, interviewing, and giving questionnaire. Through descriptive qualitative approach, the data of observation, interview and questionnaire are analyzed in description. Based on finding of the study,the reading material in class X MIA 1 at SMAN 10 Depok using English book 2013 curriculum. The activities in the class the teacher divided the students into groups to discussing the reading material and give conclusion or suggestion for students, it can be concluded that teaching reading using communicative language teaching can improve the student English reading skill in an English class, because the class activities were communicative. As show by the score the highest score is 95 and the lowest score 65, the average of students score in class X MIA 1 at SMAN 10 Depok is 82,2. The result from questionnaire, most students enjoy in reading class using CLT because, the teacher clearly and always gives opportunity to the students to ask the question it make students easier for understanding the text reading.
Construction Monitoring Platform with BIM+IoT+GIS for Xintian Yangtze River Bridge

In view of the low degree of informatization and long feedback period of traditional long-span suspension bridge construction monitoring, relying on Xintian Yangtze River Bridge, using BIM model as the information carrier, while integrating GIS and IOT technology, combined with monitoring business needs, build construction monitoring visualization The software platform provides various environmental structure status information in the process of suspension bridge construction monitoring in an intuitive and three-dimensional form to all participants, providing a reference for the realization of intelligent monitoring and the application of BIM in suspension bridge construction monitoring.
3D Key Frame Animation Generation Method Based on Deep Learning

In order to improve the generation and recognition ability of 3D key frame animation, a 3D key frame animation generation method based on deep learning is proposed. Build the 3D key frame animation detection and frame stability control model, realize the dynamic parameter identification of 3D key frame animation through multi-dimensional space parameter detection technology, and establish the grey parameter analysis model of 3D key frame animation by using deep learning image stabilization control technology. According to the parameter detection results under deep learning control, combined with adaptive animation feature location and block detection technology, a 3D animation feature point fusion matching filter model is established, which can realize the detection and automatic reconstruction of 3D key frame animation. The test results show that this method has high accuracy and good block matching effect for the automatic reconstruction of 3D key frame animation, and improves the fidelity and fidelity of 3D key frame animation.
Google Translate’s Rendition of Verb-Subject Structures in Arabic News Reports

The present paper attempts to shed light on one of the issues of Arabic-English translation by the Google Translate service. The renditions provided for verb-subject structures in several news reports are compared and contrasted with the originals in order to come up with some rules which could assist in regulating the translation of the basic elements of the Arabic sentence in the above genre. A number of factors are taken into consideration, such as the length of the subject NP and the verb form and function. GT’s rendition of news reports may be improved by introducing certain rules associated with number and articles as well as a limited number of reporting verbs..
Local Style Tokens: Fine-Grained Prosodic Representations For TTS Expressive Control

Neural Text-To-Speech (TTS) models achieve great performances regarding naturalness, but modeling expressivity remains an ongoing challenge.Some success was found through implicit approaches like Global Style Tokens (GST), but these methods model speech style at utterance-level.In this paper, we propose to add an auxiliary module called Local Style Tokens (LST) in the encoder-decoder pipeline to model local variations in prosody.This module can implement various scales of representations; we chose Word-level and Phoneme-level prosodic representations to assess the capabilities of the proposed module to better model sub-utterance style variations.Objective evaluation of the synthetic speech shows that LST modules better capture prosodic variations on 12 common styles compared to a GST baseline.These results were validated by participants during listening tests.
Avoidance Navigation Based on Offline Pre-Training Reinforcement Learning

This paper presents a Pre-Training Deep Reinforcement Learning(DRL) for avoidance navigation without map for mobile robots which map raw sensor data to control variable and navigate in an unknown environment. The efficient offline training strategy is proposed to speed up the inefficient random explorations in early stage and we also collect a universal dataset including expert experience for offline training, which is of some significance for other navigation training work. The pre-training and prioritized expert experience are proposed to reduce 80\% training time and has been verified to improve the 2 times reward of DRL. The advanced simulation gazebo with real physical modelling and dynamic equations reduce the gap between sim-to-real. We train our model a corridor environment, and evaluate the model in different environment getting the same effect. Compared to traditional method navigation, we can confirm the trained model can be directly applied into different scenarios and have the ability to no collision navigate. It was demonstrated that our DRL model have universal general capacity in different environment.
The Use of Global English Pare Platform as A Mobile Learning Resource to Learn English Vocabulary

The use of Instagram nowadays has been widely expanded as a source to learn English by the huge number of EFL students. The most popular use of Instagram these days is to learn vocabulary. The account facilitated the English learners the materials for learning. The object of the study was to investigate the Students Perception upon the Use of English Learning Account on Instagram which in this case of study was the account of Global English Pare as a Mobile Learning Resource to Learn English Vocabulary, employed using a descriptive qualitative method with online questionnaire, interview, and documentation as the instruments. The data were collected from second semester English students of E2D class at University of Mataram. The participants in this study were chosen using the cluster sampling technique which resulted in selecting 30 members of English second semester students of University of Mataram. It can be inferred that the student's perception towards Global English Pare account was varied and they dominantly presented positive opinions about the platform which indicated the good reflection upon their experience of using the platform as media to learn vocabulary. The majority of students found the account was very effective to develop their vocabulary mastery by portraying several personal positive reasons recorded in the interview section. Meanwhile, it was also found by the students the few numbers of difficulties during their activities using the platform.
HERDING BEHAVIOR IN VOLATILE MARKET REGIMES: AN IN-DEPTH ANALYSIS OF COINS, TOKENS, PANDEMIC, PENNY, AND PRICEY CRYPTOCURRENCIES

This study comprehensively analyzes herding behavior in the cryptocurrency market. First, we conduct an in-depth investigation of herding behavior in the overall cryptocurrency market. Second, we form several groups of cryptocurrencies according to their characteristics and analyze whether each group behaves similarly in volatile market regimes. Third, we investigate whether herding existed in each cryptocurrency group before and during the COVID-19 pandemic. Using a sample of 227 cryptocurrencies constituting nearly 95% of market capitalization, we reveal that herding behavior was absent in the overall sample and sub-samples comprising cryptocurrency groups. Further, the anti-herding behavior implies a contrarian response to the crowd. This anti-herding can be explained from two views: rational behavior of taking profit from market irrationality and irrational behavior due to fear or recency bias.
Heterogeneous Ensemble Models for In-Hospital Mortality Prediction

Electronic Health Records data are rich and contain different types of variables, including structured data (e.g., demographics), free text (e.g., medical notes), and time series data. In this work, we explore the use of these different types of data for the task of in-hospital mortality prediction, which seeks to predict the outcome of death for patients admitted to the hospital. We build base learning models for the different data types and combine them in a heterogeneous ensemble model. In these models, we apply state-of-the-art classification algorithms based on deep learning. Our experiments on a set of 20K ICU patients from the MIMIC-III dataset showed that the ensemble method brings improvements of 3 percentage points, achieving an AUROC of 0.853.
PERANCANGAN PROGRAM KEDATANGAN DAN KEBERANGKATAN KAPAL PERIKANAN DI PELABUHAN PERIKANAN NUSANTARA KARANGANTU

The purpose of this study is to further ease in accessing the data - the data and preparing reports required by the parties - those in need . The method used in this study is the waterfall method ( waterfall model) that begins with research on a running system , design , coding , and maintenance of records management system that archives information management and records management report generation can run fast , precise and accurate . The results obtained from this study is the management information system that is integrated with the database records to support records management process easily , quickly , and accurately .The conclusion that can be drawn from this information system that records management can be well documented because it is equipped databases , storage has become a single entity , can reduce redundancy or duplicate data, it can display the file management information is needed so as to facilitate officers in preparing reports of record-keeping . For this reason , the authors take the title of real practice ( PKN ) is as follows: "RECORDS MANAGEMENT SYSTEM ANALYSIS OF FINANCIAL MANAGEMENT DEPARTMENT OF REVENUE AND PROVINCIAL BANTEN "
Evaluating the Impact of Color Normalization on Kidney Image Segmentation

The role of deep learning in the recognition of morphological structures in histopathological data has progressed significantly. But, less intensive preprocessing stages and their contribution to deep learning pipelines is often overlooked. Color normalization (CN) algorithms are among the most prominent methods in this stage, and they work by standardizing the staining pattern of a dataset. However, the impact of various color normalization algorithms on the detection of glomeruli functional tissue units (FTUs) in kidney tissue data has not been explored before. An advanced deep learning architecture was built with the U-NET segmentation model. The U-NET model is an architecture that specializes in the segmentation of biomedical data. A dataset of 15 kidney whole slide images (WSIs), each annotated with locations of glomeruli FTUs were processed and subsequently normalized according to three 3 different conventional color normalization techniques (Reinhard, Vahadane, Macenko), and fed into a U-NET model. The dice score coefficient (DSC) was used to compare the results of each run. It was determined that color normalization algorithms significantly impact the segmentation results of deep learning algorithms, with the Reinhard algorithm being the best technique. The implications of this work are immense, as it could contribute to the proliferation of color normalization techniques in preprocessing deep learning workflows, which could improve general segmentation accuracies.
A Review of Cybersecurity as an Effective Tool for Fighting Identity Theft across United States

The study is focused on identity theft and cybersecurity in United States. Hence, the study is aimed at examining the impact of cybersecurity on identity theft in United States using a time series data which covers the period between 2001 and 2021. Trend analysis of complaints of identity theft and cybersecurity over the years was conducted; also, the nature of relationship between the two variables was established. Chi-Square analysis was used to examine the impact of cybersecurity on identity theft in United States. Line graphs were used to analyze the trend in the variable. Time series data was used in the study and the data was obtained from secondary sources; Statista.com, US Federal Trade Commission, Insurance Information Institute and Identitytheft.org. Result from the study revealed that consumers’ complaints on identity theft were on the increase every year. Total spending of the economy (both private and public sector) on cybersecurity was on continuous increase over the years. More than 100% of spending in 2010 was incurred in 2018. The Chi-Square analysis revealed that cybersecurity does not have significant impact on identity theft. The study recommended that the government increase the level of public awareness to ensure that members of the public protect their personal and other information to ensure that they are not compromised for fraud or identity theft. Organizations also need to invest more in the security system and develop policies that will support the security system. At the country level, international treaties and collaboration should be encouraged to prosecute the fraudsters hiding behind national borders.
Pelatihan Literasi Media Bagi Siswa SMA Muhammadiyah 16 Jakarta

The presence of digital media and its convenience in searching for information and data has made today's young people born and grow to be digital natives. Media literacy is a person's basic ability to access digital media. These capabilities include identifying, accessing, managing, integrating, evaluating, analyzing and synthesizing digital resources. The problem faced by Muhammadiyah 16 Jakarta high school students is that there is no learning related to media literacy that is given specifically at school. The training provided by the government to the community has not yet reached students at the high school level. Even though most of the students at the school are active users of various social media platforms. training is carried out using Zoomeeting with methods, material presentation, discussion and evaluation. Training participants are given an understanding of media literacy and how to filter information, how to distinguish information that includes facts or hoaxes.
Achievement and Aspiration of Local Colleges and Universities on the Research Agenda of Funding Institutions: Basis for Research Capability Building

This study was conducted for a specific purpose: to assess the research culture in the local colleges and universities and to propose an enhanced research capacity-building program. There were sixteen informants of this study; four administrators and twelve faculty members in the local colleges and universities in the CAMANAVA area namely: The University of Caloocan City, City of Malabon University, Navotas Polytechnic College and Valenzuela City Polytechnic College. A Purposive sampling technique was used to identify the informants. The study made use of a qualitative research approach. The data were collected from individual interviews with the administrators and faculty members. Using open coding, six (6) themes were emerged from the interviews and analysis of the document: philosophical research perspective, impact on institution’s growth and development, motivational components in research engagement, promoting the research culture, managing challenges and impediments and enhancing research capability. The informants identified the challenges in the development of the intensified research culture in the local colleges and universities which includes the scarcity of funds, research skills and expertise, network resources, and time constraint. These can be resolved through the enhancement of research capabalities and development programs. Generally, the study concluded that the research is indeed a powerful tool in addressing institutional problems and the utmost contribution of faculty members of the local colleges and universities in the academic and curricular programs and institutional growth and development. The institutional support will address the compelling need of the local colleges and universities to improve their research capability and research output.
Combination of Course Teaching and Scientific Research for Particle Physics at Guizhou Minzu University

Particle physics as an important branch of modern physics, its important research object is the microcosmic elementary particles and their interactions.The fundamentals of the particle physics course provide students with the necessary tools to explore particle physics research in depth.By studying particle physics courses, students can better understand the nature of particle physics theory and the design and results of related experiments, and communicate with the international physics community more smoothly.Today's particle science research is devoted to the exploration of higher energy particles and deeper physical phenomena.Combining particle physics courses with particle physics science research can help students gain an in-depth understanding of the current frontiers of physics research and cultivate their innovative ability in this field.At the same time, it helps students to deeply understand and participate in the forefront of particle physics research.Through such learning, students can not only master basic physics knowledge and experimental skills but also develop the ability of thinking, innovation, and teamwork.The deep integration of the two can enhance students' innovative consciousness and teamwork ability.Through course design and practical activities, students will be exposed to the latest scientific developments and cutting-edge technologies, and cultivate their scientific research interests and innovative thinking.Based on this, this paper systematically sorts out the objectives, key difficulties, and theoretical framework of particle physics courses, and introduces the basic situation of the research team of particle physics at Guizhou Minzu University and some recent research progress of myself.Combining the course of particle physics with some current scientific research, this paper puts forward some suggestions for improving course teaching for readers' reference.
Investigation of the Earth’s Albedo using Meteorological Parameters over Nguru, Nigeria

Estimation and investigation of an earth’s albedo is significant in the evaluation and design of solar energy collectors, atmospheric radiative transfer and studies that relates to atmospheric thermal balance. This study employed the shortwave solar energy balancing at the edge of the Earth’s atmosphere to estimate and compare the variation of albedo for Nguru situated in the Sahelian region of Nigeria, using measured monthly mean daily meteorological parameter of global solar radiation obtained from the National Aeronautics and Space Administration (NASA) during the period of thirty-eight years (1984 – 2021). The variation of albedo with surface temperature, maximum wavelength, clearness index, global solar radiation, relative humidity and mean temperature for this location was investigated. The results in this study show that the estimated surface albedo depicts a direct opposite relationship with the clearness index, an inverse relationship with the emitting Earth’s surface temperature and a direct relationship with the wavelength for the studied location. The highest and lowest values of albedo for the location was in the months of August and January with 0.4628 and 0.3403 respectively. The emitting Earth surface temperature ranged between 238.5837 K in August and 251.1607 K in January. These values agreed closely to the standard emitting Earth surface temperature value (255.0000 K). The maximum emitting wavelength values for the location revealed that the radiation is longwave and is found within the infrared region of the electromagnetic spectrum.
Motion Planning Strategies for Autonomous Robotic Systems

Motion Planning Strategies for AutonomousRobotic Systems
Machine Learning Empowerment in Fluid Mechanics: Unveiling Insights and Elevating Predictive Proficiency

Machine Learning Empowerment in Fluid Mechanics: Unveiling Insightsand Elevating Predictive Proficiency
The Importance of Students’ Perception of Online Learning During Pandemic

The Covid-19 epidemic has affected both traditional and online classrooms and the Indonesian government, including education. The world of education is one of the fields that has been badly affected by the pandemic. This research is descriptive research with a questionnaire in a survey via Google Forms to gather information about how they feel about their online course. The subject of this research were students of English Education Department. The data were the usage of applications in online learning, student participation, accessibility, distribution of materials and assignments, and material delivery. Tables and narrative summaries of the findings are provided. This study highlighted three key barriers to online learning, and nearly half of the respondents did not have a favorable opinion of it. Even though over 50% of students claimed to have encountered challenges with online learning, including poor signal, boredom, being unable to meet friends, losing focus while studying, not understanding the subject, and improper settings. Because they reside in villages and rural areas, please encourage their online learning activities. This research is expected to aid in advancing related studies and serve as a foundation for future considerations regarding the development and sustainability of the teaching and learning process without endangering kids, teachers, or parents.
Construction of Curriculum Ideological and Political Model Curriculum based on the Background of Engineering Education Certification

The professional certification of engineering education is an important educational quality assurance system recognized internationally in the field of engineering education at present. The ideological and political construction of curriculum can cultivate students' craftsman spirit of great country for excellence. Engineering materials and machinery manufacturing is based on the process equipment and control engineering, mechanical engineering, an important professional course, in this paper, combining with the characteristics of curriculum and syllabus, fully excavate ideological elements of curriculum knowledge and build "people-oriented" of "s ix integration” ideological system, implements the concept of engineering education accreditation with course education accurately. This course can stimulate students' patriotism enthusiasm, cultivate students' practical ability and grasp the law of development of things.