Reviewerly/exHarmony huggingface dataset:
Training in a virtual environment for high risk work at heights

Falls from a height are a common reason for workplace fatalities in the construction industry. Such high-risk work is likely to remain inherent in construction tasks requiring further efforts to reduce the risk of falling. As an underlying instability in balance may promote the development of height phobia, the current study investigated the role of fear of heights, and individual's postural response (PR) to the perturbation of an elevated work platform while exposed to simulated heights scenarios in virtual reality (VR). Postural responses were measured during the VR training experiment and the Acrophobia questionnaire and motion sickness susceptibility questionnaire were administered. Results indicated that the height anxiety (a sub-scale of the acrophobia questionnaire) was reduced after the 50-minute VR session comprising five trials. Postural response improvement also correlated with decreases in fear of heights. Findings indicate that construction workers may benefit from inclusion of VR exposure to heights as part of preparation to work at heights.
Human Behaviour Classification for Video Surveillance Using CNN

The surveillance systems were introduced to assist the security officers to prevent crimes. The addition of deep learning technologies to such systems has led to a revolution, converting them into smart video surveillance, which could do automatic human behaviour classification. This paper presents a transfer learning approach by using VGG16 as a feature extractor and convolutional neural network as a classifier. The report mainly focuses on strategies for reducing the input features and training the model to classify three human behaviours, namely, run, walk and wave and comparing the results based on those approaches. The experimental results show that the proposed algorithm of removing the irrelevant features, allows the model to focus only on the essential details and gives better results as compared to earlier methods. An increase in accuracy can be seen with the removal of each irrelevant input feature.
제한적 합리성 위상공간에서 가치-비용 합리성 매핑의 비적용성

The decision of human cognition always accompanies by wavering behavior. It is why a decision bears the ICP (indeterminate, coincidental, path-dependent) property. If the suspicion of mechanical problem holds Akerlof’s used car in check, there is wavering in a purchase decision. The premise CMVCI (consistent measuring of the value-cost indices) severs the behavioral approach from the rationality approach. It is nothing but Hume’s PUN (the principle of the uniformity of nature). The VCR (value-cost rationality) mapping is unfit for modeling the ICP phenomena.
Visualizing Rule Sets: Exploration and Validation of a Design Space

Rule sets are often used in Machine Learning (ML) as a way to communicate the model logic in settings where transparency and intelligibility are necessary. Rule sets are typically presented as a text-based list of logical statements (rules). Surprisingly, to date there has been limited work on exploring visual alternatives for presenting rules. In this paper, we explore the idea of designing alternative representations of rules, focusing on a number of visual factors we believe have a positive impact on rule readability and understanding. The paper presents an initial design space for visualizing rule sets and a user study exploring their impact. The results show that some design factors have a strong impact on how efficiently readers can process the rules while having minimal impact on accuracy. This work can help practitioners employ more effective solutions when using rules as a communication strategy to understand ML models.
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization

Federated learning (FL) has become a prevalent distributed machine learning paradigm with improved privacy. After learning, the resulting federated model should be further personalized to each different client. While several methods have been proposed to achieve personalization, they are typically limited to a single local device, which may incur bias or overfitting since data in a single device is extremely limited. In this paper, we attempt to realize personalization beyond a single client. The motivation is that during FL, there may exist many clients with similar data distribution, and thus the personalization performance could be significantly boosted if these similar clients can cooperate with each other. Inspired by this, this paper introduces a new concept called federated adaptation, targeting at adapting the trained model in a federated manner to achieve better personalization results. However, the key challenge for federated adaptation is that we could not outsource any raw data from the client during adaptation, due to privacy concerns. In this paper, we propose PFA, a framework to accomplish Privacy-preserving Federated Adaptation. PFA leverages the sparsity property of neural networks to generate privacy-preserving representations and uses them to efficiently identify clients with similar data distributions. Based on the grouping results, PFA conducts an FL process in a group-wise way on the federated model to accomplish the adaptation. For evaluation, we manually construct several practical FL datasets based on public datasets in order to simulate both the class-imbalance and background-difference conditions. Extensive experiments on these datasets and popular model architectures demonstrate the effectiveness of PFA, outperforming other state-of-the-art methods by a large margin while ensuring user privacy. We will release our code at: https://github.com/lebyni/PFA.
Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification

Generative Adversarial Networks can learn the mapping of random noise to realistic images in a semi-supervised framework. This mapping ability can be used for semi-supervised image classification to detect images of an unknown class where there is no training data to be used for supervised classification. However, if the unknown class shares similar characteristics to the known class(es), GANs can learn to generalize and generate images that look like both classes. This generalization ability can hinder the classification performance. In this work, we propose the Vanishing Twin GAN. By training a weak GAN and using its generated output image parallel to the regular GAN, the Vanishing Twin training improves semi-supervised image classification where image similarity can hurt classification tasks.
Aesthetic dimension of technology: dynamo as technological Sublime at the turn of the XIX and XX centuries

In the second half of the XIX century technology saturated urban space and transformed fac­tory production around the world. Reception of technologies in everyday life was connected with aesthetic comprehension. Besides, perception of new technologies was a complex emo­tional experience that fostered reflections on possibilities of human mind and of man-made power, on historical role of technology and its future development. This article is devoted to the aesthetic characteristics of interaction with technology as an affective aesthetic expe­rience of the technological sublime. As an example, the representation and reception of the dynamo in the public discourse at the turn XX century will be considered. The concept of the technological sublime develops the classical category of the sublime, which was inter­preted as an extreme degree of tension of the senses when meeting objects and phenomena that exceed the possibilities of human perception. In the XVIII century, the aesthetics of the sublime was discovered in nature, and in the XIX century new machines and technolo­gies began to claim the role of objects of the sublime aesthetic experience. Technological sublime can be regarded as a transgressive experience (collision with the limits of human perception and limits of possibilities) and as existential experience (human awareness of the finitude of being).
Quantum secret sharing with twisted light

Quantum secret sharing is the procedure of securely distributing information between multiple parties by exploiting the features of quantum mechanics. Many variants exist, but in this work, we report a high-dimensional realization of a single-photon secret sharing scheme for distributing classical keys amongst many nodes. The implementation, which makes use of twisted light, is realized for as high as 11 dimensions and for as many as 10 participants: the highest reported to date and which is easily extendable to even higher dimensions and many participants. Such a result is an important first step towards a future quantum network.
Perancangan Sistem Informasi dan Sarana Pelaporan Kasus Bullying Berbasis Web Menggunakan Teknologi Pemograman PHP dengan Framework Laravel

Bullying is still a troubling social problem. Bullying cases that occur in high school students have caused many problems both physically and psychologically. Bullying is a phenomenon that is very much, rooted, passed down from generation to generation. The seriousness of bullying is a big problem for all of us. The level of knowledge and concern for teachers, parents, health service teams, and the Indonesian people towards bullying is still low. Information systems are needed for management in making decisions to overcome bullying problems. Researchers in this study created a system that can be used as a means of delivering information from students to schools. The creation of this system is based on a system that is easily accessible, secure, and guarantees the confidentiality of the complainants. So that this product can help schools identify cases of bullying in schools, who are the perpetrators of bullying, and victims of bullying, with the hope that schools can stop the chain of bullying events and prevent bullying at schools. The scheme in this study is to design a website that reports bullying and provides information. The system design model used in this study is a prototype model and data was collected through observation, interviews and literature study. The programming language used is PHP and software for designing interfaces using the laravel framework. Making a database using MySQL with the XAMMP application.&#x0D;
Fully Decentralized Application Model by Peer to Peer Smart Contract of Blockchain

&lt;div&gt;Currently, the P2P method is that its software runs on a P2P hardware environment. However, the software is not a P2P one. It is difficult to match the scenarios in which the users' requirements change often. Meanwhile, if the software is out of service, all participants are affected. Thus, in this paper, we propose the fully decentralized application model, in which a P2P software runs in a P2P hardware environment. It is based on the blockchain, as a blockchain provides a secured P2P hardware environment. We focus on its P2P software (the P2P smart contract). A P2P smart contract is formed by smart contracts from its participants instead of a third party. It allows each participant to specify its requirement in a turning-complete way and the failure of one smart contract does not affect other smart contracts. We first describe the requirement of the P2P smart contract and the dependence among them. Then, we propose different ways to pair associated smart contracts. At last, we verify the proposed P2P smart contract model, and it shows more flexibility and robustness than the centralized software method.&lt;/div&gt;
Image/Video Deep Anomaly Detection: A Survey

The considerable significance of Anomaly Detection (AD) problem has recently drawn the attention of many researchers. Consequently, the number of proposed methods in this research field has been increased steadily. AD strongly correlates with the important computer vision and image processing tasks such as image/video anomaly, irregularity and sudden event detection. More recently, Deep Neural Networks (DNNs) offer a high performance set of solutions, but at the expense of a heavy computational cost. However, there is a noticeable gap between the previously proposed methods and an applicable real-word approach. Regarding the raised concerns about AD as an ongoing challenging problem, notably in images and videos, the time has come to argue over the pitfalls and prospects of methods have attempted to deal with visual AD tasks. Hereupon, in this survey we intend to conduct an in-depth investigation into the images/videos deep learning based AD methods. We also discuss current challenges and future research directions thoroughly.
Software Development with Scrum: A Bibliometric Analysis and Profile

Introduction of the Scrum approach into software engineering has changed the way software is being developed. The Scrum approach emphasizes the active end-user involvement, embracing of change, and /iterative delivery of products. Our study showed that Scrum has different variants or is used in combination with different methods. Some tools not normally used in the conventional software approaches, like gamification, content analysis and grounded theory are also employed. However, Scrum like other software development approach focuses on improvement of software process, software quality, business value, performance, usability and efficiency and at the same time to reduce cost, risk and uncertainty. Contrary to some conventional approaches it also strives to boost soft factors like agility, trust, motivation, responsibility and transparency. The bibliometric synthetic scoping study revealed seven main research themes concerned with the Scrum research.
The Error Analysis and Teaching Strategies of the Synonymous Monosyllabic and Disyllabic Verbs in Chinese Language for Korean Learners

“Monosyllabic and Disyllabic Word” is a kind of word that morphemes which construct the disyllabic verb have the similar meaning with each other, and each of them also has the similar meaning with disyllabic word combined by them. Monosyllabic and Disyllabic Word is a one of the synonym types that second language learners often feel confused when they acquire Chinese Vocabulary. In this paper, I extracted 78sets of Synonymous Monosyllabic and Disyllabic Verbs from the <HSK vocabulary> in A,B two levels of vocabulary, and through the extraction of the error examples from the <HSK writing corpus>, this paper tried to analyzed the types of Errors and the effective teaching method for the Synonymous Monosyllabic and Disyllabic Verbal Morpheme to the Korean Learners.
Decay of Entanglement of Correlated Qubits Through Bosonic Fields

Distribution of entangled parties with the longest time possible is of importance to quantum communication. Therefore, analyzing the decay character of entanglement of correlated qubits in the presence of reservoir effects is of significance to the quantum-based technologies. This study covers the analysis of the temporal entanglement decay of two maximally entangled qubits against different reservoir types and system parameters. It is shown how varying the coupling type of the system to the environment affects the lifetime of entanglement. In the presence of quantum interaction between entangled qubits, it is possible to enlarge the entanglement lifetime depending on the initialization of entanglement. Model parameters used in the numerical calculations and the results are general enough to be applied in any specific quantum-based experimental task.
The Teaching System of IT Support Course Group of Economics and Management Majors Based on Big Data Technology

In the context of big data, adding data analysis and processing to the teaching system of IT-supported courses of economics and management majors is of great significance to improving the comprehensive quality of students. This article aims to study the teaching system of IT supporting courses based on big data technology. This article adopts the method of experimental investigation to randomly survey the students’ performance of economics and management majors in a certain college that offers big data technology and application majors, and conducts research on this. Experimental data shows that from the perspective of student feedback and test results, students’ interest in learning and learning effects have been greatly improved. The results of the experiment show that the student’s score in the IT-supported course teaching system for economics and management based on big data is 89.89 ± 5.45, which is higher than the traditional learning score of 79.51 ± 5.99. Both in basic knowledge mastery and practical teaching are better than the control group. In the process of exploring the construction of IT supporting teaching system for economics and management majors in the era of big data, there is still a lot of work to be done. In the next teaching and research, we will study the teaching mode and assessment mode of IT supporting courses for economics and management majors under the background of big data. Design, etc. to be discussed.
SISTEM DETEKSI QR CODE PADA MOBIL BERGERAK DENGAN METODE FASTER R-CNN

AbstrakPada tugas akhir ini dirancang sebuah sistem yang dapat membaca QR Code pada mobil yang bergerak. Metode yang digunakan pada penelitian tugas akhir ini yaitu menggunakan metode Faster R-CNN dan pretrained model ResNet50 sebagai model object detection yaitu QR Code. Penelitian ini menggunakan 400 data latih berupa citra QR Code dan 15 data uji berupa video dengan frame rate sebesar 60 fps. Analisis performasistem dilakukan dengan dua buah parameter pengujian sistem yaitu loss training dan akurasi sistem. Pada penelitian tugas akhir ini dapat diketahui bahwa konfigurasi model terbaik terdapat pada model dengan jumlah step training 20K dan batch size 1. Variasi kecepatan terbaik untuk membaca QR Code yaitu pada kecepatan 20 km/jam dan 40 km/jam dengan akurasi sebesar 80%. Sistem ini mendapatkan frame rate sebesar 4,9-5,3 fps.Kata Kunci: QR Code, Object Detection, Faster R-CNNAbstractIn this final project, a system that can read QR Code on a moving car is designed. The method used in this research is using the Faster R-CNN method and the pre-trained model ResNet50 as the object detection model, namely QR Code. This research use 400 training data in the form of QR Code images and 15 testing data in the form of video with a frame rate of 60 fps. System performance analysis is carried out by using two system test parameters, namely loss training and system accuracy. In this final project research, it can be seen that the best model configuration is in a model with a number of training steps 20K and a batch size 1. The best speedvariation for reading QR Code is at a speed of 20 km/hour and 40 km/hour with an accuracy of 80%. This system gets a frame rate of 4.9-5.3 fps.Keyword: QR Code, Object Detection, Faster R-CNN
Activities of Pedagogical Educational Institutions of the Krasnoyarsk Region on Preparing Teachers for National Schools in the 1930s

The relevance of the study is determined by the modernization of education, the surge of national self-awareness in the regions of the country and insufficient knowledge of the historical experience of training teachers for national schools in the Krasnoyarsk Territory in the 1930s. In this regard, the historical experience of the Soviet period of training teachers as carriers of the culture of the peoples of Khakassia and the Krasnoyarsk North for national schools is of great interest. The purpose of the article is to characterize the experience of training teachers for national schools in the Krasnoyarsk Territory in the 1930s. Methodology and research methods. To solve the set research tasks, the following were used: historical-retrospective, historical-reconstructive, historical-typological, comparative-historical, systemic-structural, chronological, historical-genetic methods, analysis and generalization. Results. The results of the study consist in identifying the historical experience of several educational institutions of professional pedagogical education in the region in training teachers for national schools in Khakassia and the Krasnoyarsk North, identifying problems and obstacles in the training of pedagogical personnel. In the 1930s, in the Krasnoyarsk Territory, the task of training pedagogues for national schools was solved in 3 pedagogical colleges and a pedagogical institute at special departments and in the form of additional classes. By the 1940s, this activity was discontinued for a number of reasons: lack of funding, the remoteness of educational institutions from national schools, lack of methodological experience for governing structures, and the policy of Russification of the population in the second half of the 1930s.
AN ANALYSIS OF STUDENTS’ VOCABULARY ABILITY IN FINDING VERB THROUGH SONG LYRICS IN SMP MARISI MEDAN.

This research was aimed to find out the students’ vocabulary ability in finding verb through song lyrics. And this study have done in SMP MARISI Medan. Speaking is one of the language skills in English. That’s why mastery vocabulary is needed by every people. Vocabulary is a set of similar words within a person’s language. A vocabulary, usually developed with age, serves as as useful and fundamental tool for communication and acquiring knowledge. Teaching vocabulary through song is not only sing or reading lyric of song and fun so that is make the students passive but also process of teaching these vocabulary to be applied in activities in a form of communication.&#x0D; The result of analysis showed that finding verb through song lyrics answered by students’. The students’ who got excellent is 18 (60%), the students’ who got good is 10 (33,3%) . so after the writer got there are score, the writer concluded that students’ who got excellent and good categorized able. The students’ who got categorized Bad2 (6,6%) students’. So, after the writer got there are score, the writer conclude that students’ who got enough and bad categorized unable in finding verb.&#x0D; The researcher hopes that the students’ should be active in learning especially on vocabulary . because vocabulary is one of important skills in learning English. The students’ must develop their vocabulary so they can speak well in English. Moreover, the students’ may get more knowledge to improve their vocabulary in English.&#x0D; Keywords : vocabulary, verb, song lyrics.
Infrastructure Assisted Constrained Connected Automated Vehicle Trajectory Optimization on Curved Roads: A Spatial Formulation on a Curvilinear Coordinate

Vehicle trajectory optimization is essential to ensure vehicles travel efficiently and safely. This paper presents an infrastructure assisted constrained connected automated vehicles (CAVs) trajectory optimization method on curved roads. This paper systematically formulates the problem based on a curvilinear coordinate which is flexible to model complex road geometries. Further, to deal with the spatial varying road obstacles, traffic regulations, and geometric characteristics, two-dimensional vehicle kinematics is given in a spatial formulation with exact road information provided by the infrastructure. Consequently, we applied a multi-objective model predictive control (MPC) approach to optimize the trajectories in a rolling horizon while satisfying the collision avoidances and vehicle kinematics constraints. To verify the efficiency of our method, a numerical simulation is conducted. As the results suggest, the proposed method can provide smooth vehicular trajectories, avoid road obstacles, and simultaneously follow traffic regulations, which is robust to road geometries and disturbances.