Reviewerly/exHarmony huggingface dataset:
Religiosity and Credibility of the Bids and Awards Committee (BAC) of the Civil Aviation Authority of The Philippines (CAAP)

This study aimed to establish the significant influence of religiosity on the credibility of the Bids and Awards Committee of the Civil Aviation Authority of the Philippines. There were 300 respondents in this study chosen through the random sampling technique. Respondents were the members of the Bids and Awards committees, office personnel, suppliers, and bidders of the Civil Aviation of the Philippines, excluding the rest of the aviation employees not involved in the procurement system of CAAP. A non-experimental quantitative design utilized a descriptive correlational technique to gather data. Statistics used in data analysis were the mean and standard deviation, Pearson r, and regression analysis. Results showed a very high level of religiosity and a high level of credibility among the respondents. In addition, the correlation test revealed a significant positive relationship between religiosity and credibility. Furthermore, the regression analysis revealed the overall influence of religiosion to credibility. When regressed individually, it was found that responsibility best predicts credibility.
Penerapan Metode Visualisasi Kolaborasi Aksi (ViKA) pada Pembelajaran Menyimak Teks Berita Kelas VIII

The learning method is an important part of the learning component. The selection of the right learning method can support the maximum achievement of learning objectives. Learning methods must continue to innovate so that it is not monotonous and boring for students. The Action Collaboration Visualization Method (ViKA) is one of the innovative and creative Indonesian language learning methods. The ViKA method is used in learning to listen to news texts for class VIII. The aims of this study are (1) to describe the Visualization of Collaborative Action (ViKA) method, (2) to describe the preparation for the application of the ViKA method in learning to listen to news texts for class VIII, (3) to describe the steps in applying the ViKA method in learning to listen to news texts for class VIII, (4) describe the advantages and disadvantages of the ViKA method. The method used in this research is descriptive qualitative. The main data source in this research is the ViKA learning method. The research instrument used was student worksheets related to news text elements. Data collection techniques using documentation techniques. This study uses descriptive data analysis techniques in the form of an explanation of the ViKA learning method. The subjects in this study were 15 grade VIII students. The results of this study indicate that there are differences in the results of student worksheets before and after the ViKA method is applied. Student worksheet results have increased after the ViKA method was applied. An abstract must be in English, consists of 150-250 words length, and contains at least: general theme of the article, focus, question, method, and general argument or main finding. Use this document as a template if you are using Microsoft Word 7.0 or later. Otherwise, use this document as an instruction set.
EFFECTIVENESS OF COMMUNICATIVE LANGUAGE TEACHING (CLT) METHOD TO IMPROVE STUDENTS SPEAKING SKILL

Students in Indonesia may understand theories in learning English but struggle to put them into practice.This research was conducted at SMAN 7 SIDRAP and the researcher wants to use Communicative Language Teaching (CLT) method which emphasizes language as a tool for communication, the researcher wanted to compare the CLT method with the conventional method that teachers usually use at school, so the formulation of the problem in this study was to find out whether there were differences in learning outcomes between the CLT method and the conventional method.This study aimed to assess the effectiveness of the Communicative Language Teaching (CLT) method in improving the speaking ability of students at SMAN 7 SIDRAP. This research used experiment design with Quasi experimental, the total sample was 40 students that devided in 2 class that is 20 students’ was from 10 MIPA 1 as an Experiment class and another 20 was from 10 MIPA 2 as an Control Class, the result showed that the independent sample t-test revealed a significant difference between the two methods, with the CLT method being more effective in improving students' speaking abilities.
Preface

Organized by Beijing University of Technology, the 2023 Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC2023) was successfully held both face to face &amp; virtually in Dalian, China during April 14-16, 2023. Part of participants who were unable to actually attend due to travel and their schedules also delivered their speeches online through VooV Meeting. During the conference, the keynote speakers were each allocated 30 – 45 minutes to hold their speeches. After speech, there was a Q&amp;A discussion between the speakers and participants. We believe that this conference is an important forum for the exchange of information and research results among us, who come from different countries, different educational and research institutes, and different research interests. All of the papers included in the proceedings were subjected to peer-review by conference committee members and international reviewers. 86 papers were accepted as full papers for presentation on the conference and publication in IPEC2023 Proceedings. These papers provide excellent advances of current research on the topics covering Image processing, computer vision, electronic technology, machine learning, signal and information processing, applied computer science and so on. The conference cannot be successful without the efforts of all conference committees, organizers, participants. We would like to express our deep gratitude and appreciation to all involved. Many thanks go as well to all of the reviewers who have helped us to maintain the high quality of manuscripts included in the Proceedings published by IOP Publishing. Finally, we sincerely hope you enjoy the scientific and technical contents of the conference and find a good opportunity to discuss ideas and future collaborations with other researchers and practitioners from institutions around the world. Ljiljana Trajković, Simon Fraser University, Canada Xuesong Xu, Hunan University of Technology and Business &amp; Brandeis University, USA IPEC2023 General Chairs List of Conference Committees are available in this pdf.
Preface

2023 7 th International Conference on Data Mining, Communications and Information Technology (DMCIT 2023), was successfully held on May 27, 2023, which was organized by Asia Pacific Institute of Science and Engineering (APISE), and sponsored by Jiangnan University. DMCIT conference has been held for six years since 2017 after successful onsite conferences or virtual conferences. DMCIT 2023 continued its tradition of providing a unique and excellent forum for exchanging research methodologies, exploring practical applications, and fostering innovative ideas. DMCIT 2023 strives to offer networking opportunities to meet and interact with the world-leading scientists, engineers and researchers as well as industrial partners in Core Data Mining, Communication Engineering, Information Technology Applications Topics. The conference was originally scheduled in Chongqing, China from May 26 to 28, 2023. Most authors cannot attend offline with personal reasons, but they can only attend online. As a result of small number of offline participants, it had to be turned into a fully virtual conference via Tencent meeting on May 27, 2023. The proceedings of this year’s edition comprised four main categories: “1. Image Processing and Computer Vision”; “2. Machine Learning and Data Analysis”; “3. Information Technology and Communication Systems”; “4. Optimization and Modeling”. All these submissions were rigorously reviewed by the Program Committee. The research tracks attracted 42 submissions in total, and out of 27 papers were accepted, including countries like Pakistan, Japan, Philippines and China, etc. On the conference day, 9 oral presentations and 18 posters presentation were arranged according to the participants’ choices. Two awards, one best oral presentation award and one best poster presentation award were selected by the end of conference. Four distinguished keynote speakers, including Prof. Shahram Latifi from University of Nevada, Las Vegas (USA); Prof. Yudong Zhang from The University of Leicester (UK) and Prof. João Alexandre Lôbo Marques from University of Saint Joseph, Macau SAR; and Prof. Miaowen Wen from South China University of Technology, delivered excellent speeches, sharing their latest and insightful research ideas. We extend our sincere gratitude to all the authors who submitted their papers to the DMCIT conference. We also like to express our great appreciation to the invited speakers, PC members, supporting staff, and all the organizing committee members for their great efforts in making the conference a sucess. Simon Fong, University of Macau, Macau S.A.R, China Conference Committee Chair, DMCIT 2023 Lis of Committees are available in this pdf.
AN ANALYSIS OF STUDENTS’ DIFFICULTIES IN SPEAKING ENGLISH

The purpose of this study is to find out the causes of students' difficulties in speaking English. This research uses descriptive quantitative method. In collecting data, the researcher used a closed questionnaire and also a Liker scale to determine the factors that cause students' difficulties in speaking. Data collection was carried out by distributing questionnaires to 30 students of class XI IPS. The results of this study indicate that the inhibiting factors, having nothing to say, the lack of participants and the use of the mother tongue can be a source of student difficulties. From these four aspects, the results showed that 72.40% of students experienced inhibition, 60% could nothing to say, 60.93% low participations and 64.4% used their mother tongue. It can be concluded that of the four factors there is one factor that shows high presentation value, namely the obstacle where most students have obstacles in speaking English so they find it difficult to speak.
FACE RECOGNITION MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER DAN LOCAL BINARY PATTERN HISTOGRAM

Increasing threats to data security is a consequence of technological advances that continue to develop, especially with the existence of technology that allows data access remotely. It is important to always maintain data security and take preventive measures to prevent data theft. The author proposes the use of facial recognition biometric technology. Face Recognition is one of several biometric technologies that can be used for identity verification systems. The data used amounted to 5 classes, classes with each class having 250 facial images, the total data used amounted to 1250 facial images, consisting of 1000 training data (train) and 250 test data ( tests). The shooting process is done automatically, the system automatically takes 250 faces per class. The next stage is feature extraction using the Local Binary Patterns Histograms (LBPH) method. Furthermore, the system will recognize the detected faces with those in the dataset. The use of the Haar Cascade Classifier and Local Binary Pattern Histogram (LBPH) methods to detect faces using 250 test data obtains an accuracy value of 92%. Testing in real time was carried out 75 times with a distance of 30 cm, 50 cm and 100 cm. The use of the Haar Cascade Classifier and Local Binary Pattern Histogram (LBPH) methods to detect faces in real time obtains an accuracy of 90%.
PELAYANAN INTENSIF “ENGLISH FOR CHILDREN” DARI PROGRAM BAKTI PADAMU NEGERI PROGRAM STUDI SASTRA INGGRIS DI KOMUNITAS BELAJAR MAN JADDA WA JADDA RUMBIA LAMPUNG TENGAH

Education is the most effective social elevator to improve the quality of life.During the pandemic, education at every level experienced distraction, so a counter was needed to overcome this situation.The learning community is a place to help children learn more comfortably during the absence of teaching and learning activities in formal education.High student interest and limited volunteers make a difference in the achievement of learning objectives.In this regard, the English Literature Study Program is here to bridge the gap in accordance with the vision and mission of the study program.This community service activity is carried out using a participatory method by observing several stages: coordination with administrators, field surveys, and program implementation.The results and implementation are increasing the knowledge and abilities of students and volunteers on English material.
Pengaruh Variasi Serat Fiberglass Terhadap Kekuatan Tarik Komposit High Density Polyethylene

This research was aimed to determine the effect of fiberglass fibers in increasing the tensile strength of HDPE composites and their advantages over PVC materials. The specimens were printed using a hot press by pressing and heating at a temperature of 140°C, mixing the materials was carried out by mixing in a measuring cup, then cutting was carried out for tensile testing with the ASTM D3039 standard on the specimen. The results of the study obtained tensile strength with a fraction of 70% vol HDPE resin, 30% vol fiber fiberglass average of 13.774 Mpa with short fiber type and fraction 75% vol HDPE resin, 25% vol fiber fiberglass average of 24,334 Mpa for this type of fiber the length and tensile strength of PVC material has a value of 7 25 Mpa, the tensile strength of HDPE fiberglass composite of 24,334 Mpa is sufficient to replace PVC.&#x0D;
Analysis on serialized expressions of rational numbers

Rational numbers can be serialized, in other words, rational numbers can be expressed in a regular, ordered way. This paper discusses the background, reasons and methods of rational number serialization, and also identifies the rules of rational number serialization, derives a unique sequence of rational numbers, identifies the expressions for rational number serialization, and lays the foundation for the use of rational number sequences in mathematics. The purpose of serializing rational number in this paper is to make transmitting and storing data more easily, and gives a better way for researchers to do further Mathmetics studies.
Take a close look at deep learning applications from loss view

Deep learning is an intrinsic learning style and representation through which knowledge acquired helps interpret data such as words, images and sounds. The ultimate aim is to enable computers to analyse and recognize data, such as words, images and sounds, in the same way as humans. In artificial intelligence, loss function is a very effective method. In the deep study, the loss function is used to determine the relationship between the target and the prediction. This paper analyzes and summarizes the loss functions in face recognition, object detection and face recognition, and focuses on some key loss functions.
An introduction to continuous functions, metric space, manifolds, topological spaces and its properties

A n-dimensional topological manifold is defined as an n-dimensional local Euclidean space M that is also a second countable space and a Hausdorff space. If a topological space has a countable base, it is referred to as a second countable space. At the same time, continuous function and metric space can help people to understand topological space better. This article will express some basic ideas about continuous functions, metric space, topological space and its properties, and topological manifolds. Moreover, the paper shows some basic ideas of how topological manifolds, topological space and function could be recognized and proved. Through analysis, this paper demonstrates the connection between them, such as using properties of continuous function to prove the definition and properties of topological manifolds and spaces.
Latent space manipulation of stable diffusion model for image generation

The creation of the diffusion model was a piece of exciting news in the deep learning community. Millions of people are excited to try the new DALLE 2 AI artist and the state-of-the-art stable diffusion model. One of the greatest advantages of these AI artists is that they can apply many distinct artistic styles to the same image. Nonetheless, the image created using a specific artistic style sometimes seems too strong or too weak. The ability of adjusting the strength of artistic styles of the generated images enables users of this algorithm greater degrees of freedom in terms of creating images of their wishes. Moreover, the ability of adjusting the strength of artistic styles of the generated images can also serve an educational purpose from which users can understand artistic styles in concreate terms. This paper proposed a novel method of adjusting the level of artistic styles of the generated image which utilized the continuity of the latent space of the Contrastive Language-Image Pretraining (CLIP) encoding and calculate the augmenting latent vector. This novel method provides a greater level of tailored manipulability of the generated image.
Game theory--optimum strategy for drawing cards in 21 points

Blackjack is a popular casino poker game in which players make drawing decisions based on rules other than the size of their points. We found that despite the randomness of the card draw, blackjack is actually very mathematical and logical. By calculating probabilities and using game theory, we can allow players to make relatively "rational" decisions that maximize their expectations of winning, rather than relying solely on guesswork and vague feelings. Therefore, in this article, we built several models to simulate a blackjack game with different numbers of people. For players in each model, we give them a code that outputs the optimal decision, which helps them figure out the winning percentage (more specifically, the expectation, since once stakes are involved in multiplayer games, the winning percentage doesn't necessarily represent the expectation of winning money) for each decision, thus helping the player make a better decision.
A review of statistical analysis related to information theory and machine learning

With the collection and use of large amounts of data in various disciplines, it has become a necessity to analyze these data that people cannot handle by means of mathematics and information theory. A review of statistical analysis on previous work like data analysis, data mining, and machine learning are conducted in this paper. Specifically information theory in conjunction with machine learning based on basic statistical evaluation are focused on. Many mathematical instruments are used in this area, including evaluating the performance, loss functions, and activation functions. In this paperall these methods from previous work are concluded and the future potential development in this area is discussed. Finally, this paper broadly summarizes the development history about machine learning and information theory, and discusses the pros and cons of both of them and their future development.
Analysis on the relation between the vertex angle of a tube airplane and its flying time

The tube is a type of airplane that is shaped as a hollow cylinder. In common sense, it seems impossible that an airplane has no wings, however, the tube airplane can fly even longer in the sky comparing with normal airplanes. In this paper, the practical experiment related to Bernoullis theorem and Magnus Force will be introduced. In order to understand those equations more deeply with logic, a paper airplane model called the tube is going to be studied. The author makes the models with different shapes and angles so as to figure out the relationship between the angle of the index and the flying time of the airplane. Results show that the angle of the index has an impact on the time of the airplane staying in the sky, and the angle affects the angular and linear rotating speed of the airplane so that the time required for the airplanes varies.
BLOCKCHAIN IMPLEMENTATION IN THE FINANCIAL INDUSTRY TO ENHANCE SCALABILITY

The implementation of blockchain technology in the financial sector with a focus on improving scalability.Blockchain has received a great deal of attention for its ability to transform financial systems, but challenges such as scalability remain.It takes an insightful approach to the strategies and responses that enterprise players use to address scalability issues, from sharding from second-tier solutions to conceptualizing regulatory improvements following real international applications, this one-stage study shed light on how the the scalability of blockchain can improve the financial landscape, and pave the way for greater adoption and adoption within the industry.
A New Efficient Forgery Detection Method using Scaling, Binning, Noise Measuring Techniques and Artificial Intelligence (Ai)

In the market new updated editing tools and technologies are available to edit images and with help of these tools images are easily forged. In this research paper we proposed new forgery detection technique with estimation of noise on various scale of input image affect of noise in input image, frequency of images are also changed due to noise, noise signal correlated with original input images and in compressed images quantization level frequency also changed due to noise.We partition input image into M X N blocks, resized blocks are proceed further, image colors are also taken into consideration, each block noise value is evaluated at local level and global level. For each color channel of input image estimate local and global noise levels are estimated and compared using binning method. Also measured heat map of each block and each color channel of input image and all these values are stored in bins. Finally from all noise values calculate average mean value of noise, with these values decide whether input image is forgery or not, and performance of proposed method is compared with existing methods.
Operational Knowledge and Context

The chapter shows that context is intertwined with operational knowledge and reasoning in real-world applications (and more particularly in domains where knowledge occurs in an operational form that is different of knowledge in formal models).
Better Real-Life Space Utilization in VR Through a Multimodal Guardian Alternative

Space utilization and better exploration are important parts when building VR experiences that can be used by people with different play styles, requirements, and needs. A key factor in achieving this is a flexible guardian system that informs users about their position and potential hazards. We propose an alternative guardian solution that incorporates various modalities, notification types, diegetic and non-diegetic interfaces, which demonstrated improved space utilization and mobility compared to a standard system. However, this alternative solution may come with a higher cognitive load. We believe this system demonstrates that a better more immersive alternative to the Guardian solution is possible, which would maximize the utilized real-world space while adding better immersion. We plan to use this initial research as a basis for developing more robust versions, utilizing different combinations of the proposed features.