Reviewerly/exHarmony huggingface dataset:
Design of 3D Display System for Intangible Cultural Heritage Based on Generative Adversarial Network

This paper designs a three-dimensional display system for intangible cultural heritage based on generative adversarial networks. The system function is realized through four modules: input module, data processing module, 3D model generation module, and model output module. Two 3D model reconstruction methods are used to realize the transformation from 2D images to 3D models. In the low-resolution Nuo surface 3D construction, multiresidual dense blocks are introduced and applied to the deep image super-resolution network. The experimental comparison results show that the quadratic optimization multifusion 3D construction model proposed in this paper can achieve considerable improvement and can improve the reconstruction accuracy by about 6.3%. In the high-resolution 3D construction of the Nuo surface, a generative adversarial network model is used to improve the generator, discriminator, and loss function of the original SRGAN model. Experimental results show that this method can generate super-resolution images with more realistic and natural depth maps. In addition, when it is used for high-resolution 3D Nuo surface sculpting, it can also generate 3D voxel Nuo surfaces with more details.
Defending against Adversarial Attacks in Deep Learning with Robust Auxiliary Classifiers Utilizing Bit-plane Slicing

Deep Neural Networks (DNNs) have been widely used in variety of fields with great success. However, recent research indicates that DNNs are susceptible to adversarial attacks, which can easily fool the well-trained DNN-based classifiers without being detected by human eyes. In this article, we propose to integrate the target DNN model with our robust bit-plane classifiers to defend against adversarial attacks. The bit-plane classifiers take bit-planes of input images for convolution, which is motivated by our observation that successful attacks aim to generate imperceptible perturbations, and they mainly affect the low-order bits of pixels in clean images when adding the perturbations. We also propose two metrics, bit-plane perturbation rate and channel modification rate, to further explain the robustness of bit-plane classifiers. We discuss potential adaptive attack and find that our defense can be effective as long as the adversarial examples are qualified. We conduct experiments on dataset CIFAR-10 and GTSRB under white-box attack and black-box attack. The results show that our defense method can effectively increase the average model accuracy from 16.23% to 83.53% under white-box attack and from 40.65% to 88.14% under black-box attack on CIFAR-10 without sacrificing the accuracy of clean images.
Building empirical knowledge on the relationship between code smells and design patterns: An exploratory study

Abstract Code smell is a concept describing potential problems in software design. In opposition, design pattern describes good design solutions in terms of maintainability and reusability. Code smell and design pattern might be perceived as metaphors supporting software design activity in terms of understanding and communication. However, empirical evaluation is needed to investigate their effect in terms of programming activity. Our objective is to build empirical knowledge on the relationship between code smells and design patterns. We carried out an exploratory study based on mining software repositories and in a baseline study addressing software evolution. In total, we analyzed 61 software. Their classes were identified as linked to both code smells and design patterns metaphors. Then, we analyzed the co‐occurrence of these metaphors. Our findings indicate that the relationship between smells and design patterns is software dependent. Some software present many smells linked to design patterns while for other software, smelly classes are not linked to design patterns. We also found that the instability metric weakly reflects this idea. Our study supports better understanding of the topic. It presents results in the opposite direction of expectations that the presence of smells is correlated with the absence of design patterns and vice versa.
Cross-Lingual Embeddings Using a Temporally Aligned Comparable Corpus: A Case Study For Manipuri–English

Cross-lingual embeddings facilitate cross-language learning, bridging the gap between rich-resource and low-resource languages. This study provides and assesses unsupervised cross-lingual embeddings generation methods for the low-resource Manipuri–English language pair. Manipuri is a resource-poor language spoken in India’s northeastern regions. The embeddings are evaluated on the language pair bilingual dictionary induction task. Furthermore, we propose a method to improve the cross-lingual embeddings by exploiting a temporally aligned comparable corpus. Lack of supervision has always been an issue for learning models, especially in low-resource settings. The proposed method takes advantage of the temporal alignments and provides the much-needed supervision to improve the alignment between Manipuri and English language pair. We observe that the proposed model consistently outperforms all the corresponding baselines from various experimental results.
Investigation and Research on the Use of the App of the National Anti Fraud Center

China's telecommunications fraud crime continues to occur at a high rate, coupled with the changing means of fraud, and an increasing number of people are being defrauded. In the face of such oppression, the Ministry of Public Security launched the national anti fraud center App in June 2021, which aims to help users maintain the security of telecommunications networks, establish channels for users to report cases related to telecommunications networks, and enhance the purpose of prevention and publicity. However, with the strong support of the state for anti fraud Apps and the requirement of all people to download them, a series of problems came one after another. Different voices were transmitted on major platforms, which also proved that there were some defects in Apps. The project studies the problems existing in the anti fraud App since its launch, such as the imprecise mode setting, the lack of in-depth publicity and education, and the low download rate, and puts forward corresponding solutions to these problems, so as to help the App serve people better.
An Intelligent Face Recognition Technology for IoT-Based Smart City Application Using Condition-CNN with Foraging Learning PSO Model

The internet of things (IoT) is a rapidly expanding network of smart digital devices that can communicate with one another and be controlled remotely over the internet. Moreover, IoT devices are cheap and can be used to control and monitor activities remotely. Due to this reason, IoT is widely used in the applications of a smart city. Moreover, the smart devices that are used in IoT-based smart city applications are used to gather information from devices, humans, and other sources for analyzing purposes. Hence, it is crucial to conduct the face recognition process to ensure the safety of the city. Several works were conducted by the researchers to recognize the face accurately. Typically, the effectiveness of achieving face recognition is still an intricate one. To tackle those issues, we have proposed a novel condition convolutional neural network (condition-CNN)-based bee foraging learning (BFL)-based particle swarm optimization (PSO) algorithm (CCNNBFLPSO). To recognize the facial images from the face image datasets, the proposed CCNNBFLPSO model is used. To ensure the prediction accuracy condition, CNN uses the conditional probability weight matrix (CPWM) to estimate the higher and lower class level of image features. Meanwhile, the learning of CPWM can be performed by utilizing the adopted BPL-PSO approach. For experimental purposes, we have taken three datasets namely the CVL face database, the MUCT database, and the CMU multi-PIE face database. The training time and the training accuracy are analyzed for all the three datasets, and comparative studies are performed with state-of-art works such as LBPH, FoL TDL, and TPS approaches. The training and validation loss functions are analyzed with baseline CNNs, B-CNN, and condition-CNN. The proposed approach accomplishes better face recognition accuracy and F1-score of about 99.9% and 99.9%, respectively.
Brief Announcement: How to Tame Multiple Spending in Decentralized Cryptocurrencies

The last decade has seen a variety of Asset-Transfer systems designed for decentralized environments. To address the problem of double-spending, these systems inherently make strong model assumptions and spend a lot of resources. In this paper, we take a non-orthodox approach to the double-spending problem that might suit better realistic environments in which these systems are to be deployed. We consider the decentralized trust setting, where each user may independently choose who to trust by forming its local quorums. In this setting, we define k-Spending Asset Transfer, a relaxed version of asset transfer which bounds the number of times the same asset can be spent. We establish a precise relationship between the decentralized trust assumptions and k, the optimal spending number of the system.
PENGUATAN STANDAR KOMPETENSI LULUSAN MEMBACA SASTRA MELALUI STRATEGI META-ANALISIS BAGI MAHASISWA JURUSAN BAHASA DAN SASTRA INDONESIA

At first, students' low literary reading experience became a thought to find effective strategies so that students were interested in reading and got the concept of learning experience by thinking critically. To achieve this kind of condition, students' familiarity with literary works accompanied by an understanding of critical reviews is absolutely necessary. Meta-analysis provides a strategy that can be used by lecturers to strengthen the Literature Reading Competency Standards (SKL). This study aims to reveal the use of meta-analysis strategies in strengthening SKL Reading Literature for students majoring in Language. This research uses descriptive analysis method. The data collection stage was carried out through literature study (critical review), interviews, and observations. The results showed that there was a correlation that could be correlated between the achievement of SKL Reading Literature through meta-analysis strategies. Furthermore, the meta-analysis learning design in Literature Reading SKL Achievement is carried out in four stages, namely determining the literary period (problem formulation), determining and selecting literary reading results, reading literary works, and presenting the literary reading meta-analysis report
The Relationship of Literature Culture And Student's Learning Motivation with School Library Readiness in Sma Negeri 1 East Suwawa

The results showed that: (1) The relationship between literacy culture and school library readiness at SMA Negeri 1 Suwawa Timur. From the results of the research above, it is known that the test is carried out by comparing the alpha value with a significant value (0.006) &gt; (0.05), then H 0 is rejected and H 1 is accepted. That is, partially there is a relationship between literacy culture with school library readiness. It can be concluded that literacy culture has a relationship with the readiness of school libraries at SMA Negeri 1 Suwawa Timur. (2) The relationship between students' learning motivation and the readiness of the school library at SMA Negeri 1 Suwawa Timur The test is done by comparing the alpha value with a significant value (0.000) &gt; (0.05) then H 0 is rejected and H 1 is accepted. That is, partially there is a relationship between student learning motivation and school library readiness. It can be concluded that partially there is a relationship between school library readiness and student learning motivation at SMA Negeri 1 Suwawa Timur. (3) The Relationship between Literacy Culture, learning motivation and school library readiness for students at SMA Negeri 1 Suwawa Timur. count (496.29) &gt; F table value (2.70) with a significant value (0.000) &gt; (0.05) then H 0 is rejected and H 1 is accepted. That is, there is a relationship between Literacy culture of learning motivation with school library readiness can be concluded that simultaneously the literacy culture of student learning motivation with school library readiness at SMA Negeri 1 Suwawa Timur.
Autonomous Update of a Dataset for Anomaly Detection Services in Elderly Care Smart House

This work proposes a smart system that could be useful in the delivery of elderly care services. Elderly care is a set of services that are provided to senior citizens to help them have a more comfortable and independent life which would not be possible without these services. This proposed system is unique in that it combines the detection algorithm with the automatic update of the dataset. It also uses a heuristic mechanism to reduce false detections. This is on the premise that the AI effort is good, but it could be made better with the inclusion of heuristics. Fall detection accuracy is initially solved by the first classifier, then another classifier evaluates the result with inferences before evoking an alarm. It checks the location of the subject to use in its inferences. Hence the smart house design consists of two machine learning systems. One system performs human activity classification while the other performs fall occurrence detection. Of the eight different classification methods utilized, XGBoost was most accurate with an average of 97.65% during training. A customized dataset is then generated with newly labeled data hence improving system performance.
A Comprehensive Study on Artificial Intelligence and Blockchain Driven Beyond 5G Networks

Swift evolution of novel computing and communication technologies in beyond 5G networks (B5G) opens up the possibilities for advanced techniques to tackle various issues, which can not be solved by the existing frameworks. As the number of devices continuously increases, blockchain can provide a secure platform for communication among all the users in the network. Moreover, along with the security, blockchain requires low computation and also provides fast network response. Furthermore, artificial intelligence enhances the ability of devices to learn and construct knowledge about dynamic wireless environments. Recently, many researchers have shown interest in integration of both the platforms to solve the complex problems of B5G networks. This work reviews the application of both the technologies in various networks related problems recently completed by the authors. Moreover, it also discusses various possible research issues that can be handled by the integration of both platforms.
Development of technology-embedded solar energy STEM (SESTEM) module among Universiti Pendidikan Sultan Idris (UPSI) diploma science students

Abstract The purpose of this study is to design and develop a Solar Energy STEM module (SESTEM) among a class of 80 diploma science students in the Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris (UPSI). This module was developed to create an enjoyable technology-embedded learning process for solar energy education. The students’ perceptions evaluations of the complete SESTEM module were based on questionnaires and open-ended questions. The module implements fully hands-on activities using smartphones, QR codes, images, and videos. This work was based on the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) instructional model. The findings showed that students gave positive feedback regarding the contents and the activities implemented in the module. In conclusion, SESTEM can be considered a modern teaching tool, enhancing more value-added skills and being accustomed in the future
Medical genetic technologies in the biosafety system: a risk-based approach

The subject of the research is the legal mechanisms of regulation of public relations in the field of medical genetic technologies as an element of the biological security system of Russia. The purpose of the reasearch is to analyze the legal regulation of medical genetic technologies as an integral part of biosafety, taking into account their inherent features, to identify an assessment of the effectiveness of existing rationing mechanisms and to propose new more effective legal mechanisms. The methodological basis of the research consists of general scientific and special methods. The general scientific methods include system, structural-functional, formal-logical (deduction, induction, analysis, synthesis) methods. To achieve the purpose of the research work, special methods of legal science are also used: formal legal, legal modeling and others. The result of the research was the identification of a low-effective legal mechanism for regulating medical genetic technologies as an integral part of biosafety existing in domestic legislation. In this regard, we have proposed some directions for improving the current regulatory framework in the field of public relations under consideration. The results obtained can be used in educational activities in the courses "Social law", "Medical law". The novelty of the research work lies in the fact that for the first time medical genetic technologies are considered as an element of the biological security system of Russia, taking into account the characteristic features and social significance inherent in this type of genetic technologies, which were also highlighted for the first time. Also, the novelty is expressed in the parameters developed by the author for attributing medical genetic technologies to technologies of low, medium or high probability of occurrence of risks, which we have also identified. Based on the results of the study, we came to the conclusion that it is necessary to design truly effective legal mechanisms for regulating medical genetic technologies based on the proposals we have put forward to ensure the legally permissible level of biosafety in Russia when using medical genetic technologies.
The Development E-Learning Assisted by Flashcard to Improve Students Scientific Literacy in High School on the Kinetic Theory of Gases Materials

Abstract Since the outbreak of the pandemic, it requires educators and students at all levels of education to be able to adapt to virtual learning. Based on the needs analysis that the researchers conducted through an online questionnaire for science class of XI students, their obstacle during distance learning was that 64% of students still had difficulty understanding physics material. Students have difficulty analyzing problems in physics problems because there are too many formulas that must be understood, as well as learning factors for students who are less effective. Most of them are interested in interactive learning methods by emphasizing audiovisual, as well as animations and learning videos. Therefore, the study aims to develop e-learning assisted by flashcards to improve the scientific literacy in high school students, because it is easily accessible on any device, can be via a laptop or smartphone. The average validation results by media experts are 89.58%, material experts are 90.65%, learning experts are 94.15% and by class XI physics teachers are 96.00%. The average value of the overall validation test by experts is 92.6% with the interpretation of “very feasible” as a learning medium with an N-Gain of 0.44 on a medium increase interpretation.
Development and usability of JUQUANJI game in quantum theory of light among pre-service physics teacher

Abstract This study aimed to develop a teaching aid namely ‘JUQUANJI’ and evaluate its usability among physics trainee teachers at Sultan Idris Education University. ‘JUQUANJI’ is adapted from the JUMANJI board game and developed by using Genialy website tool. This study uses a development research design by applying the ADDIE model, which has five phases: analysis, design, development, implementation and evaluation. The research samples consisted of 32 trainee physics teachers from semesters seven and eight selected using a simple random sampling technique. Two research instruments were used, namely the expert validation form and usability questionnaires adapted from the USE Questionnaire. Data from the usability questionnaire were analyzed descriptively using Statistical Package for Social Science (SPSS) version 26.0 to obtain the mean and standard deviation (s.d). The data analyses from two experts showed that the developed game had a very satisfactory validity with 99.48% of agreement. The usability data analyses showed that the ‘JUQUANJI’ game was at a good level with a mean score of 3.79 (s.d = 0.353). The three constructs that represent usability namely usefulness, ease of use, ease of learning and satisfaction are at a good level with the mean score of 3.71 (s.d = 0.385), 3.73 (s.d = 0.391), 3.83 (s.d = 0.333) and 3.89 (s.d = 0.304) respectively. In conclusion, ‘JUQUANJI’ game has achieved the research objectives which is proven through the findings from the validity of experts and usability. This game suitable to help teachers to assess students while the student can make a revision related to the subtopic of Quantum Theory of Light.
Effect of composition CaCO<sub>3</sub>/polyurethane (PU) on contact angle of the surface and compressive strength of mortar

Abstract Infrastructure development, especially in the field of construction material technology, one of them is mortar. The water content greatly determines the energy performance and durability of the mortar. Water can enter building materials or mortar through rain. Damage caused by moisture is common, especially in areas with high moisture content. To solve this problems, a hydrophobic or water-repellent mortar was created, one of which was by using a hydrophobic additive, namely CaCO3/PU. The purpose of this research was to determine the effect of the composition of CaCO3/PU on the surface contact angle and mortar strength. This research uses spray coating method. The hydrophobic layer was made with various compositions of 5%, 10% and 15% and the carbonation temperature used was 60°C using an oven. This research resulted in optimum contact angle at 15% PU variation of 120.8936° and optimum compressive strength of 187,68 kg/cm 2 at 10% CaCO3 immersion.