Reviewerly/exHarmony huggingface dataset:
Multi-objective optimal decision making for autonomous driving based on multi-modal predicted trajectories

Authors:
raw_author_name: Chao Wei
raw_affiliation_string: Beijing Institute of Technology (China); National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology (China)

Abstract: With the advancement of science and technology, the rapid development of the autonomous driving industry has put forward higher requirements for related algorithms. To improve the reliability and intelligence of autonomous vehicles, it is necessary to have robust and reliable decision-making module, which depends on accurate trajectory prediction. In this paper, research on multi-modal trajectory prediction and decision-making for autonomous driving based on deep learning is carried out. Firstly, a multi-modal trajectory prediction model is constructed based on graph neural network to obtain the predicted trajectories of vehicles around the autonomous vehicle. Based on the prediction results, a decision-making network model of the autonomous vehicle is constructed, and the optimal decision-making results satisfying the multi-objective requirements are obtained by combining the multi-objective optimization method. The experimental results verified the feasibility of the method and its good performance.
Feature selection algorithm for ant colony clustering optimization for target tracking

Authors:
raw_author_name: Qi Yang
raw_affiliation_string: Shenyang Ligong University (China)
raw_author_name: Xunyang Liang
raw_affiliation_string: Shenyang Ligong University (China)
raw_author_name: Shida Wang
raw_affiliation_string: Shenyang Ligong University (China)

Abstract: Aiming at the texture processing and noise disturbance problems of simultaneous localization and mapping algorithm for dynamic scenes under the strong static assumption theory, Improved dynamic object tracking based on ant colony clustering (IACDOT) was proposed. The algorithm combines fractional differential and sparse optical flow algorithm to make full use of the weak texture gradient of the image. A dynamic feature search and selection strategy is designed to obtain ant colony clustering, which reduces motion interference and mismatching of dynamic and static features. The experimental results show that the algorithm not only realizes the adaptive selection of pixel gradient order, but also has a better ability to distinguish dynamic disturbance through the clustering of feature selection. It can effectively distinguish motion and static information while retaining more details of weak gradient feature optical flow. The algorithm has a good application prospect in simultaneous localization and mapping system.
Penggunaan Media Pop Up Book untuk Meningkatkan Minat Baca Siswa Kelas II SD Negeri Malaka

Authors:
raw_author_name: None Patri Janson Silaban
raw_affiliation_string: Universitas Katolik Santo Thomas

Abstract: This research aims to increase interest in reading by using pop up book media in class II students at SD Negeri Malaka. This research is collaborative classroom action research. The subjects of this research were class II students at SD Negeri Malaka for the 2023/2024 academic year, totaling 20 students. The research design used is the Kemmis and Mc model. Taggart. The data collection techniques used in this research are: 1) scale, 2) observation, and 3) documentation. Data analysis techniques use quantitative and qualitative descriptive analysis. The results of the research show that class II students' interest in reading at SD Negeri Malaka can be increased by using pop up book media through the steps of observing pop up book media, listening to and reading poetry, asking and answering questions and directing attention to learning. In pre-action, the percentage of students who had a minimum interest in reading had reached a good predicate of 0%. In the first cycle, the percentage increase in the number of students who had a minimum interest in reading reached a good predicate of 45%. In cycle II, the percentage increase in the number of students who had a minimum interest in reading reached a good predicate of 85%.
Pengaruh Pendidikan Karakter terhadap Hasil Belajar PAI kelas V di SD N 34 VII Koto Sungai Sarik

Authors:
raw_author_name: None Wedra Aprison
raw_affiliation_string: Universitas Islam Negeri (UIN) Sjech M. Djamil Djambek Bukittinggi
raw_author_name: None Arman Husni
raw_affiliation_string: Universitas Islam Negeri (UIN) Sjech M. Djamil Djambek Bukittinggi
raw_author_name: None Salmi Wati
raw_affiliation_string: Universitas Islam Negeri (UIN) Sjech M. Djamil Djambek Bukittinggi

Abstract: This research is motivated by the results of research on November 24, 2021 at SD N 34 VII Koto Sungai Sarik. The researcher observed that students' bad character greatly affected students' learning outcomes. The problems identified include absenteeism, lack of attention in lessons, noisy behavior in class, and lack of motivation to do assignments. This study aims to determine the effect of character education on the learning outcomes of fifth grade Islamic religious education at SD N 34 VII Koto Sungai Sarik. The type of research used is quantitative with a correlational approach. The population is all fifth grade students (120 people), with a sample of 30 people selected using random sampling technique. The results of the analysis showed a significant influence between student character and Islamic religious education learning outcomes. The coefficient of determination shows that 50.2681% of student learning outcomes are influenced by student character, while the rest is influenced by other factors. This finding confirms that student character has an important role in learning outcomes, especially in Islamic religious education subjects at SD N 34 VII Koto Sungai Sarik.
Pengaruh Model Pembelajaran Numbered Head Together dan Jigsaw untuk Meningkatkan Hasil Belajar Siswa Mata Pelajaran Ekonomi Kelas X IPS di SMA Negeri 5 Kota Serang

Authors:
raw_author_name: Yusina Fadla Ilmi
raw_affiliation_string: Universitas Banten Jaya

Abstract: This research aims to determine the effect of the Numbered Head Together (NHT) learning model and the Jigsaw learning model on student learning outcomes in economics class X IPS at SMA Negeri 5 Serang City, as well as to determine the differences using the Numbered Head Together (NHT) learning model and Jigsaw on student learning outcomes in economics subjects for class X IPS at SMA Negeri 5 Serang City. This type of research is a quasi-experimental quantitative research (Quasi experimental design) with a nonequivalent pretest-posttest control group design, the population used for this research data is the entire class X IPS. The samples taken were classes X IPS 1 and X IPS 3. The instruments used were tests (pretest-posttest), interviews and non-tests in the form of documentation. Based on the results of the analysis of the Numbered Head Together (NHT) learning model on learning outcomes with the t test Tcount &lt; Ttable, namely 0.000 &lt; 2.306. So the Numbered Head Together (NHT) learning model influences student learning outcomes. Based on the results of the analysis of the Jigsaw learning model with the t test Tcount &lt; Ttable, namely 0.001 &lt; 2.306. So the Jigsaw learning model influences student learning outcomes. The Numbered Head Together (NHT) and Jigsaw learning models have significant differences in learning outcomes. This can be seen from Tcount &lt; Ttable, namely that the Jigsaw learning model is -2.928 &lt; 2.306 and the learning model is -2.928 &lt; 2.306. So it can be concluded that there is a significant difference in learning outcomes between the Numbered Head Together (NHT) and jigsaw learning models on the learning outcomes of class X IPS students at SMA Negeri 5 Serang City.
Exploring Health Science Students' Experiences of Learning Management Systems: Through the Lens of the Community of Inquiry Framework

Authors:
raw_author_name: Untoro Dwi Raharjo
raw_affiliation_string: Universitas Jenderal Achmad Yani Yogyakarta
raw_author_name: Praptana Praptana
raw_affiliation_string: Universitas Jenderal Achmad Yani Yogyakarta
raw_author_name: Suryo Nugroho Markus
raw_affiliation_string: Universitas Jenderal Achmad Yani Yogyakarta

Abstract: &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; The digital revolution in education, particularly in higher education, has led to the widespread adoption of online learning platforms like Learning Management Systems (LMS). The Faculty of Health at Universitas Jenderal Achmad Yani Yogyakarta has embraced this trend, employing Moodle for blended learning. However, there has been a lack of formal evaluation of students' experiences with the LMS. This research aims to fill this gap by comprehensively evaluating the user experience and learning experience of students within the Faculty of Health using the Community of Inquiry (CoI) framework. The study collected data from 201 respondents and analyzed their experiences across various CoI domains. Results indicated positive perceptions of teaching presence, social presence, and cognitive presence, with teaching presence scoring the highest. However, social presence remained the lowest aspect, highlighting the need for more personalized engagement on the LMS. While the study identified areas for improvement, it also underscored the LMS's potential in modern learning and its role in enhancing the flexibility of higher education. Further research was recommended to address the study's limitations and continue improving online learning experiences on the LMS.&#x0D; &#x0D; &#x0D; &#x0D;
Application of the fractional Fourier transform for decryption in experimental optical cryptosystems

Authors:
raw_author_name: Alejandro Velez-Zea
raw_affiliation_string: Grupo de Óptica y Fotónica, Instituto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia, Cra 53 #61-30, Laboratorio de optica, Medellin, 050010, COLOMBIA
raw_author_name: John Fredy Barrera-Ramírez
raw_affiliation_string: Grupo de Óptica y Fotónica, Instituto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia, Calle 53 #61-30, Laboratorio de óptica, Medellin, Antioquia, 050010, COLOMBIA

Abstract: Abstract In this contribution, we introduce a new practical approach to apply the fractional Fourier transform in the modelling of two optical systems: free space propagation and a single lens processor. This formulation presents a simple way to stablish a direct relationship between physical parameters of the two optical systems and a real-valued fractional order. Furthermore, we employ and compare two numerical methods for evaluating the fractional Fourier transform: the convolution and the Fresnel transform. Consequently, we apply this innovative approach to the digital decryption process in an opto-digital joint transform correlator cryptosystem, considering both the free space propagation and the single lens processor variants. We analyse both numerically and experimentally encrypted data to support our proposed method and to investigate the sensitivity of the decryption process with the fractional order. Notably, we obtain similar decryption results for both numerically and experimentally encrypted objects, demonstrating excellent agreement between the theoretical model, the numerical test, and the experiment.
Postcumulus processes recorded in whole-rock geochemistry: a case study from the Mirabela layered intrusion, Brazil

Authors:
raw_author_name: Stephen J Barnes
raw_affiliation_string: CSIRO Mineral Resources, Kensington , Perth, Australia
raw_author_name: Morgan Williams
raw_affiliation_string: CSIRO Mineral Resources, Kensington , Perth, Australia

Abstract: Abstract According to the “trapped liquid” paradigm, whole-rock chemical compositions of cumulate rocks in layered intrusions can be represented as closed-system multicomponent mixtures of the cumulus phases and the liquids from which they crystallised. Alternative open-system models for cumulate solidification assert that intercumulus liquid is continuously mobile as a result of compaction of crystal mushes. In the closed-system models, all excluded elements, i.e. those incompatible in the cumulus phases, should be correlated with one another, whereas in open systems the more incompatible elements should be decoupled from the more compatible ones and correlations should be poor. These alternative hypotheses are tested using a database of more than 63,000 whole-rock analyses of mostly ultramafic cumulates from a single package of layers across the entire width of the Mirabela layered intrusion, a 2.5 km wide by &amp;gt;2 km thick intrusion with Great Dyke-like stratigraphy. Variably compatible elements Al, Na, Ti and P are found to show strong correlations with one other in olivine-pyroxene cumulates across the spectrum from mesocumulate to orthocumulate rocks, where drill-core sample intervals are composited over 3m; weaker correlations are found over 1m sample intervals. The closed-system trapped liquid model is robust for this suite of rocks at the scale of 3m lengths of drill core (approx. 1 kg of sample). Furthermore, a very smooth and symmetrical variation is observed from dominantly ad- to mesocumulate rocks in the geometrical centre of the intrusion towards orthocumulates at both margins, attributable to increase in cooling rate towards the margins. The most adcumulate rocks are gabbronorites at the base of the mafic sequence in the centre of the intrusion. There is no corresponding decrease in layer thickness towards the centre that would be predicted by a compaction model. The only incompatible element showing partial decoupling is K, which appears to have been mobile at a very late stage, probably in an aqueous fluid phase. There is no evidence for mobilisation of PGEs or other chalcophile elements by this fluid despite the presence of disseminated sulfide throughout the sampled interval.
Multi-Modal Deep Learning based Metadata Extensions for Video Clipping

Authors:
raw_author_name: Geon-Woo Kim
raw_affiliation_string: Department of Computer Science, Kyonggi University, Suwon 16227, Republic of Korea
raw_author_name: Joo-Chang Kim
raw_affiliation_string: Division of AI Computer Science and Engineering, Kyonggi University, Suwon 16227, Republic of Korea

Abstract: General video search and recommendation systems primarily rely on metadata and personal information. Metadata includes file names, keywords, tags, and genres, among others, and is used to describe the video's content. The video platform assesses the relevance of user search queries to the video metadata and presents search results in order of highest relevance. Recommendations are based on videos with metadata judged to be similar to the one the user is currently watching. Most platforms offer search and recommendation services by employing separate algorithms for metadata and personal information. Therefore, metadata plays a vital role in video search. Video service platforms develop various algorithms to provide users with more accurate search results and recommendations. Quantifying video similarity is essential to enhance the accuracy of search results and recommendations. Since content producers primarily provide basic metadata, it can be abused. Additionally, the resemblance between similar video segments may diminish depending on its duration. This paper proposes a metadata expansion model that utilizes object recognition and Speech-to-Text (STT) technology. The model selects key objects by analyzing the frequency of their appearance in the video, extracts audio separately, transcribes it into text, and extracts the script. Scripts are quantified by tokenizing them into words using text-mining techniques. By augmenting metadata with key objects and script tokens, various video content search and recommendation platforms are expected to deliver results closer to user search terms and recommend related content.
Advancements in Artificial Intelligence for Games

Authors:
raw_author_name: Ibrahim Khan

Abstract: Abstract: Interactive entertainments using AI have become possible due to merging AI with games. The paper explores in-depth multi-dimensional relations among AI in gaming, including Game AI, Adaptive Gameplay, and ML in VE. The study intends to investigate how the current AI in games landscape impacts gameplay dynamics and customer experience. The paper discusses the latest approaches such as AI-driven NPCs and procedural generation of content that transforms gameplay experience. Secondly, it analyzes how machine-learning can help in designing adaptable gaming situations to satisfy different tastes and skills players. Further, this study identifies trends and envisages future breakthroughs in AI in gaming. This work aims at addressing challenges and ethical issues associated with artificial intelligence and virtual environment domain in order to understand where is future heading for gaming experience.
Actor-network interpretation of phenomena and current issues of education: The historicist grounds and specificity

Authors:
raw_author_name: Olga Alexandrovna Vlasova

Abstract: Introduction. The research analyzes the changes of ontological and methodological grounds of the philosophy of education in the modern world. The aim of the research is to identify the historicist grounds and specificity of the actor-network interpretation of phenomena and current problems in education. Materials and Methods. The study employs complex and interdisciplinary approaches. The data sources for this problematic research include the latest scholarly publications, tending to apply actor-network theory in the field of pedagogy and philosophy of education and published in academic journals between 2000 and 2023. The typologisation and comparative methods, along with contextual and textual analysis are used in order to analyze contemporary discussions in this field. Results. Based on the most recent studies, this work reveals the grounds and identifies the specificity of actor-network interpretation of some educational phenomena and problems. During the research the basis of actor-network pedagogy is revealed as historicist ontology, which overcomes the opposition between classical historicism and relativism. The article demonstrates how the reconsideration of ontological and methodological foundations influences the building of terminological glossary of the philosophy of education. The concept of ‘educational spatiality’ is contextualized, which in its turn, makes it possible to analyze a network of educational practices as a complex. Apart from that, the potential of using the tools of the actor-network theory is characterized in a context of research of different educational models from a historical perspective, in materially and contextually heterogeneous networks. It is also claimed that due to its multidisciplinary nature, the actor-network theory can be successfully used to problematize educational phenomena and develop specific teaching strategies. Conclusions. It is demonstrated that actor-network theory, due to its reliance on a new model of historicism, can provide a multidisciplinary orientation of pedagogy and its lability in relation to the modern situation.
Dynamic Range Compression of Infrared Images Based on Histogram Equalization with Edge Inversion

Authors:
raw_author_name: V. Yu. Tsviatkou
raw_affiliation_string: Belarusian State University of Informatics and Radioelectronics

Abstract: The problem of compression of the dynamic range of infrared images is considered. To improve the quality of tone mapping of infrared images when their dynamic range is compressed and to simplify the control over the reproduction characteristics of infrared images, a dynamic range conversion algorithm based on adaptive histogram equalization with edge inversion is proposed. The essence of the algorithm consists in double reduction of the dynamic range of the infrared image with intermediate stretching, compression and overlapping of edges with inversion. To select the brightness interval and the degree of its stretching, the proposed algorithm uses the asymmetry coefficient. The algorithm makes it possible to improve some global and interval indicators of image reproduction quality by superimposing the edges of the histogram.
COMPARISON OF GRAMMAR INTERVENTION PBLAND PBL IN JUNIOR MIDDLE SCHOOL ENGLISH READING

Authors:
raw_author_name: None Xu Ke
raw_affiliation_string: Faculty of Education and Liberal Studies, City University Malaysia
raw_author_name: Mohd Ridzuan Darun
raw_affiliation_string: Faculty of Education and Liberal Studies, City University Malaysia

Abstract: &#x0D; &#x0D; &#x0D; &#x0D; This paper compares the effectiveness of grammar intervention problem-based learning (GIPBL) and problem-based learning (PBL). PBLis a constructivism-based popular teaching pedagogy previously used in medical education, then widely applied in other fields of education, including junior high school English reading teaching. However, researchers of Scaffolding learning theory argue that grammar intervention PBL (GIPBL) is more suitable for Junior high students in English reading courses. To compare the effect of GIPBL and PBL on satisfaction and learning process in junior high school Grade 3 students, this study does a quasi-experimental study in Jiangyou Foreign Language Experimental School in Sichuan Province, China. The participants include 120 students of grade 8 in two different classes in Junior High School. Experimental and control groups are designed.The practical class is taught in GIPBL,and the control class is taught in PBL. Both classes are about learning English reading, an integral part of the English course.Pretest and post-test were applied. The instruments were a demographic questionnaire,reading test and satisfaction questionnaire. The result shows that students' reading comprehension scores in GIPBL are better than those of the control group. GIPBL broadens the implementation of PBL in practice. There was more satisfaction with GIPBL. 82% of students thought GIPBL was a more acceptable and effective teaching method. The result shows that Grammar Intervention PBL suits junior and middle school students in English reading courses.&#x0D; &#x0D; &#x0D; &#x0D;
Innovative Stripe Noise Image Correction Method for Remote Sensing

Authors:
raw_author_name: Ayoub Boutemedjet
raw_author_name: Azzedine Bouaraba

Abstract: Unmanned SystemsAccepted Papers No AccessInnovative Stripe Noise Image Correction Method for Remote SensingSid Ahmed Hamadouche, MasterAyoub Boutemedjet, and Azzedine BouarabaSid Ahmed Hamadouche, Ayoub Boutemedjet Search for more papers by this author , and Azzedine Bouaraba Search for more papers by this author https://doi.org/10.1142/S2301385025500335Cited by:0 (Source: Crossref) Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetails Recommended Accepted Papers Metrics History Received 12 October 2023 Accepted 27 February 2024 PDF download