Reviewerly/exHarmony huggingface dataset:
Multilevel holographic encryption based on the Tiger Amulet concept

Optical holographic encryption (OHE) has been extensively researched in the field of information security due to its parallel and multi-dimensional characteristics. However, although some progress in OHE has been made in recent years, inherent security flaws resulting from the robust nature of holograms persist. In this study, we propose a multilevel holographic encryption method based on the Tiger Amulet (TA) concept. Compared with the normal OHE, our method employs two ciphertexts. It strategically utilizes the low-level plaintext as intentional deceptive content to confound the potential eavesdroppers. Furthermore, we ingeniously exploit the hologram’s robustness in reverse, thereby establishing an additional protection mechanism to enhance the security of the middle-level plaintext. Leveraging the TA concept, the high-level plaintext can only be decrypted when two matched ciphertexts are combined and collimated. The TA based decryption mechanism enhances the security and sensitivity deciphering high-level plaintext. Benefiting from the security mechanisms above, our proposed method demonstrates promising applicability across diverse scenarios and holds the potential to redefine the landscape of multilevel OHE design.
PELATIHAN PENGOLAHAN LIMBAH KAIN PERCA MENJADI PRODUK AKSESORIS DESAIN INTERIOR DI BANK SAMPAH GULON ASRI, JEBRES, SURAKARTA

&#x0D; &#x0D; &#x0D; &#x0D; Basically, the cloth is indispensable in the interior design sector, especially in the manufacture of interior accessories products made from textiles or upholstery. The problem of fabric waste that is abundant and difficult to decompose should be a solution for interior design products. Interior Design can utilize patchwork waste into products that have beauty, function, and economic value. Therefore, this community service activity at the Gulon Asri Waste Bank focuses on processing patchwork into interior accessory products, such as blankets, carpets, pillows, and others. Then the product is packaged and marketed online.&#x0D; &#x0D; &#x0D; &#x0D;
Analisis Sentimen Terhadap Pengaruh Minat Belanja Berdasarkan Komentar di Marketplace Menggunakan Metode Recurrent Neural Network (RNN)

Product reviews on the marketplace can provide useful information if they are properly processed. Product review analysis can be performed by merchants to obtain information that can be used to evaluate products and services. It is not enough to look at the number of stars in product review analysis activities; it is also necessary to look at the entire contents of the review comments to determine the intent of the review. This can be done manually in small quantities, but in large quantities, the system is more efficient. In order to understand the intent of the reviews, a system that can effectively analyze many reviews is required. Using the Recurrent Neural Network (RNN) method, this study aims to analyze sentiment on the influence of shopping interest based on comments in the marketplace. The RNN model is trained to recognize positive and negative sentiments using data from the marketplace. The sentiment analysis results will be used to assess the impact on user shopping interest in the marketplace. Sentiment analysis was performed in this study using the RNN method in the GRU/LSTM training model with epochs. The researcher determined the epoch to achieve high accuracy. The data used for model training and testing is separated into training and testing data before it is used. A comparison of 80% of training data and 20% of test data is used to split data. This study uses a training model with 77 epochs and a batch size of 128 to create a system that automatically calculates comment sentiment in the marketplace with a 100% accuracy value and determines positive and negative sentiments.
Efficient Malaria Parasite Detection From Diverse Images of Thick Blood Smears for Cross-Regional Model Accuracy

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Goal</i> : The purpose of this work is to improve malaria diagnosis efficiency by integrating smartphones with microscopes. This integration involves image acquisition and algorithmic detection of malaria parasites in various thick blood smear (TBS) datasets sourced from different global regions, including low-quality images from Sub-Saharan Africa. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methods:</i> This approach combines image segmentation and a convolutional neural network (CNN) to distinguish between white blood cells, artifacts, and malaria parasites. A portable system integrates a microscope with a graphical user interface to facilitate rapid malaria detection from smartphone images. We trained the CNN model using open-source data from the Chittagong Medical College Hospital, Bangladesh. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results:</i> The validation process, using microscopic TBS from both the training dataset and an additional dataset from Sub-Saharan Africa, demonstrated that the proposed model achieved an accuracy of 97.74% ± 0.05% and an F1-score of 97.75% ± 0.04%. Remarkably, our proposed model with AlexNet surpasses the reported literature performance of 96.32%. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusions:</i> This algorithm shows promise in aiding malaria-stricken regions, especially those with limited resources.
An Entropy-based Adaptive DBSCAN Clustering Algorithm and Its Application in THz Wireless Channels

Terahertz (THz) communication has emerged as a highly promising technology in the field of sixth-generation (6G) communication systems. The understanding of propagation behavior, channel characteristics, and the development of a realistic channel model are essential prerequisites for THz communications. Notably, THz channels exhibit the distinctive feature of sparse clustering, which is a characteristic unique to THz channels. In this paper, we propose an entropy-based adaptive density-based spatial clustering of applications with noise (EBA-DBSCAN) algorithm for efficient cluster analysis in THz communication channels. The EBA-DBSCAN algorithm combines the entropy method (EM) and the median absolute deviation method (MAD) to determine the clustering order and obtain an adaptive neighborhood radius for each multipath component (MPC). Extensive measurement campaigns are conducted in an indoor L-shaped hallway, covering the frequency range from 215 GHz to 225 GHz. The clustering performance and time complexity of the proposed algorithm are comprehensively evaluated. Furthermore, we analyze the cluster parameters by considering the distribution characteristics of the surrounding environment. The clustering characteristics presented in this study significantly contribute to a better understanding of radio propagation and serve as a foundation for the development of efficient and accurate cluster-based channel models for 6G THz communication systems.
Forum shopping in regulatory sandboxes and the perils of experimental law-making

The gradual emergence of regulatory sandboxes in various jurisdictions has already triggered considerable attention of legal academia. Thus, academicians have addressed various legal frameworks, providing for regulatory sandboxes in the field of financial and energy technologies, artificial intelligence, medical products etc. In all these fields, regulatory sandboxes do currently serve as a tool for facilitating these new technologies, which could hardly emerge successfully under the rules of conventional legal frameworks. Beside identifying the advantages of regulatory sandboxes, various risks were also identified with respect to the prospective introduction of regulatory sandboxes in various fields of governance. This article aims to address the feature of ‘forum shopping’, that the spontaneous emergence of regulatory sandboxes might imply. The authors argue, that while such forum shopping will represent an inevitable implication of legal pluralism, one may also expect various attempts for the “passportisation” of regulatory sandboxes. At the same time, the authors aim to address a more theoretical question, to which extent are classical tenets of legal jurisprudence applicable to the experimental legislation?
Development of a Service Quality Analysis Information System with the Importance Performance Analysis Method

Service is an activity where a company helps customers solve their problems. Good service quality can make customers loyal to the company. To maintain service quality, service performance is measured. The Importance Performance Analysis (IPA) method is one method that can be used to measure service performance from a customer perspective. Qanaah Carpet Shop is a business that operates in the field of goods and services. By using the IPA method, Toko Qanaah Karpet measures its service performance manually using paper media, which makes analysis ineffective and inefficient. This research aims to build an information system that can analyze service quality using the IPA method. The analysis was carried out by measuring 30 service attributes which were divided into 5 dimensions, namely: Tangible (Physical evidence), Reliability (Reliability), Responsiveness (Responsiveness), Assurance (Guarantee), and Empathy (Empathy). Data collected through a questionnaire involved 50 respondents. The results of this research show that there are 6 attributes in quadrant A, 10 attributes in quadrant B, 8 attributes in quadrant C, and 6 attributes in quadrant D. Companies can take action to maintain and improve service attributes in accordance with the recommendations from the results of this research.
A Deixis Analysis in Joko Widodo’s Speech on the Closing G20 Summit

Deixis become an important function in oral communication. They can resolve confusion, ambiguity, and misunderstanding on meaning of utterances. Among the many formal communication forms, the speech of President Joko Widodo in G20 Summit closing event can become interesting to research in term of deixis study. This article investigates the type of deixis and what deixis is the most dominantly used in the speech of Joko Widodo at the G20 Summit closing. The data were described qualitatively by referring to Levinson. Using Miles and Huberman's interactive mode, the finding shows that among 47 of deixis used, person deixis was 25, temporal deixis 3, social deixis 14, and discourse deixis 5. Person deixis “I” was found to be the most dominant in the speech, which indeed conclude that President Joko Widodo showed himself the the holder of the mandate for holding the G20 Summit in Indonesia.&#x0D; Keywords: Deixis, Types of Deixis, Joko Widodo, G20 Summit
The Students’ Vocabulary Learning Strategies and Vocabulary Size of the English Study Program of UIN Fatmawati Soekarno Bengkulu

The objectives of this research are to analyze information about students' vocabulary learning strategies and vocabulary size. This research is mixt-methods; there were descriptive quantitative and qualitative method. The sample of this research is students’ English Study Program of UIN Fatmawati Bengkulu. The data were gathered by using questionnaires, test and interview, and were analyzed by descriptive quantitative and qualitative analysis.The results showed that there was no difference which is significant in terms of frequency of using among each student of English education at UIN FAS Bengkulu. So the dominant strategies were used by students that were determination strategies (M=3.3), metacognitive strategies and memory strategies (M=3,2), cognitive strategies (M=3.1), and the last social strategies (M=3). It meant that determination strategies most frequency used by the students English Study Program of UIN FAS Bengkulu. Result for students’ vocabulary size showed that average vocabulary sizes below 8000 word families. Meanwhile from interview data, the students used metacognitive, memory, determination and social strategies for their vocabulary learning. In conclusion, each strategy is a good vocabulary learning strategies to students for improving vocabulary size andmay help lecturers and students to facilitate English vocabulary learning by English Study Program students and other students.&#x0D; &#x0D;
Analisis Unsur STEAM dan Literasi Sains dalam Buku Tematik Siswa Kelas IV pada Tema 3 Peduli Terhadap Makhluk Hidup Muatan Pelajaran IPA SD

The study is intended to describe principles of STEAM and science literacy in the thematic book (the fourth student book on the 3rd theme concerned with living creatures' stuffed science ds lessons). This type of research is descriptive research. The objects in this study are the STEAM and science literacy elements that were analyzed and appearing in the fourth-grade student thematic book. Research instruments are STEAM element analysis sheets and science literacy. The data analysis techniques used are descriptive. The percentage category of growing up Used the rater percentage formula of the deal. Research shows that: 1) the STEAM element in the fourth-grade elementary student's thematic book the percentage of the biggest indicator growing is the science element by 40%, mathematics by 26,67%, technology by 10%, art by 10%, and engineering by 6.66%; (2) the science literacy in the fourth-grade elementary student book the most indicator percentage for ever showing up is 100% attitude, competence by 55.56%, context by 26.66%, and knowledge by 38.88%.
Improving Uncertainty Sampling with Bell Curve Weight Function

Typically, a supervised learning model is trained using passive learning by randomly selecting unlabelled instances to annotate. This approach is effective for learning a model, but can be costly in cases where acquiring labelled instances is expensive. For example, it can be time-consuming to manually identify spam mails (labelled instances) from thousands of emails (unlabelled instances) flooding an inbox during initial data collection. Generally, we answer the above scenario with uncertainty sampling, an active learning method that improves the efficiency of supervised learning by using fewer labelled instances than passive learning. Given an unlabelled data pool, uncertainty sampling queries the labels of instances where the predicted probabilities, p, fall into the uncertainty region, i.e., $p \approx 0.5$. The newly acquired labels are then added to the existing labelled data pool to learn a new model. Nonetheless, the performance of uncertainty sampling is susceptible to the area of unpredictable responses (AUR) and the nature of the dataset. It is difficult to determine whether to use passive learning or uncertainty sampling without prior knowledge of a new dataset. To address this issue, we propose bell curve sampling, which employs a bell curve weight function to acquire new labels. With the bell curve centred at p=0.5, bell curve sampling selects instances whose predicted values are in the uncertainty area most of the time without neglecting the rest. Simulation results show that, most of the time bell curve sampling outperforms uncertainty sampling and passive learning in datasets of different natures and with AUR.
SOME IDEAS FOR DIGITAL SUPPORT OF STUDENTS’ ACTIONS IN PRESCHOOL AND FIRST-GRADE COUNTING

The use of digital support for preschool and fi rst-grade education is an urgent and disputable question. It is thus even more important to analyse the content of actions, which we expect students to acquire. In this case it is possible to assign the appropriate functions to the software. In our study we used Davydov’s analysis of the action of counting as a prerequisite for the wholesome Maths curriculum design. Our research aim is to study the psychological conditions for preschool and fi rst grade students to acquire and appropriately perform a possible procedure of counting, required for the number-concept formation. We exploit the context of adding or removing some tokens to the “hidden” amount, signed with the corresponding number - so that the students cannot count each object directly. We have devised the general comprehensive view of the necessary support for mediated “counting up” and “counting down” and the series of tasks, varied according to modifi - cations suggested in Galperin’s theory of planned step-by-step formation. We have conducted two cycles of experimental teaching (over  hours each,  participants in total,  years of age). The data collected (video-taped classroom discussions, students’ drawings, pre- and post-tests) showed signifi - cant progress and allowed us to consider our hypothesis on the content of students’ actions as a feasible perspective for future research. Moreover, the analysis of the action content, which will presumably provide children with a solid basis for number-concept development, defi nes particular requirements for the digital support design. The computer is to provide the place to work with suitable tokens and special modelling means, as well as the “unbiased” feedback on whether the calculated answers suffi ce, and the opportunity for teachers to vary task conditions as planned.
TRANSITION TO SECONDARY EDUCATION: RE-THINKING THE BACKGROUND OF THE PLACE-VALUE COUNTING

The diffi cult period of transition between primary and secondary school demands deep “re-thinking” of the content of school curricula, mathematics in particular. In order for the principles of place-value computations (our current study subject), not only to conclude the elementary school, but also to make a solid foundation for students’ further promotion. The mistakes students make, while using the “well-learned” decimal system, stem from their miscomprehension of the structure and the arrangement of “positional” counting. Thus, following Davydov, we suggest reconstructing the place-value origin by organising and scaffolding students’ own learning actions in other-base counting systems. Our research goal is to discover and describe the psychological conditions for students’ acquisition and appropriate application of the place-value concept in various critical computational tasks. For this purpose, we have devised a wide range of task conditions, which were modifi ed according to the principles suggested by Galperin, in order to keep the orientation procedure in demand and thus achieve the desired consciousness in thinking. These tasks were embedded into the “intergalactic” storyline, so that students would join the “cosmic voyagers” on their expedition, as they have to calculate the exact amounts of “cosmo-fuel” for different-base counting systems. We have conducted several cycles of experimental teaching (about  hours each) according to the materials and instruction, which we have designed: a total of  students (- years of age, th-th grade) comprised our sample. In our investigation we followed the “planned formation” method of Galperin and the traditions of the developmental instruction design (according to El’konin and Davydov). The results of the teaching series proved the potential of the content and the computer support, which we have developed, for the promotion of mathematical literacy and for overcoming the formalism of calculation procedures, adopted in primary school.
An Optimized Deep Learning Method for Video Summarization Based on the User Object of Interest

Surveillance video is now able to play a vital role in maintaining security and protection thanks to the advancement of digital video technology. Businesses, both private and public, employ surveillance systems to monitor and track their daily operations. As a result, video generates a significant volume of data that needs to be further processed to satisfy security protocol requirements. Analyzing video requires a lot of effort and time, as well as quick equipment. The concept of a video summary was developed in order to overcome these limitations. To work past these limitations, the concept of video summarization has emerged. In this study, a deep learning-based method for customized video summarization is presented. This research enables users to produce a video summary in accordance with the User Object of Interest (UOoI), such as a car, airplane, person, bicycle, automobile, etc. Several experiments have been conducted on the two datasets, SumMe and self-created, to assess the efficiency of the proposed method. On SumMe and the self-created dataset, the overall accuracy is 98.7% and 97.5%, respectively, with a summarization rate of 93.5% and 67.3%. Furthermore, a comparison study is done to demonstrate that our proposed method is superior to other existing methods in terms of video summarization accuracy and robustness. Additionally, a graphic user interface is created to assist the user with summarizing the video using the UOoI.
Using Topic in Summarization for Vietnamese Paragraph

This article delves into the realm of refining the precision of automated text summarization tasks by harnessing the underlying themes within the documents. Our training data draws upon the VNDS dataset (A_Vietnamese_Dataset_for_Summarization), encompassing a total of 150,704 samples aggregated from diverse online news sources like vnexpress.net, tuoitre.vn, and more. These articles have been meticulously processed to ensure they align with our training objectives and criteria. This paper presents an approach to text summarization that is theme-oriented, utilizing Latent Dirichlet Allocation to delineate the document's subject matter. The data subsequently have been fed into the BERT model, which constitutes one of the subtasks within the broader domain of abstractive summarization—summarizing content based on pivotal concepts. The results attained, although modest, underscore the challenges we've confronted. Consequently, our model necessitates further development and refinement to unlock its full potential.
The Effect Of Reader’s Theater Strategy On Students’ Skills In Writing Recount Text

Writing is an effective tool de develop communication for students. By writing, students can explore everything to deliver to others. As a result, the purpose of this study was to look into the effect of the reader's theater strategy on improving students' writing skills when writing recount text. This was a pre-experimental study. This study's sample consisted of eighth-grade students from MTs Pidua Meranjat. The information was gathered using a written test and analyzed using a paired sample t-test. The findings revealed that the t-obtained (5.228) was higher than the t-table (0.692) at a significant level of p-value below 0.5. It meant that there was a significant improvement in writing recount text after having taught using the reader’s theater strategy. In conclusion, the Reader’s Theater strategy affected students in writing recount text because it offers a fun way of learning where students must complete a story by recreating the script by characterizing the text that was guided by its strategy.