Reviewerly/exHarmony huggingface dataset:
swAFL: A Library of High-Performance Activation Function for the Sunway Architecture

The Sunway supercomputers have recently attracted considerable attention to execute neural networks. Meanwhile, activation functions help extend the applicability of neural networks to nonlinear models by introducing nonlinear factors. Despite the numerous activation function-supported AI frameworks, only PyTorch and TensorFlow were ported to the Sunway platforms. Although these libraries can meet the minimum functional requirements to deploy a neural network on the Sunway machines, there still exist some drawbacks including the limited number of usable functions and unsatisfactory performances remaining unresolved. Therefore, two activation function algorithms with different computing accuracies were developed in this study, and an efficient implementation scheme was designed using the single instruction/multiple data extension and multiply–add instructions of the platform. Finally, an efficient library-swAFL-composed of 48 function interfaces was designed and implemented on the Sunway platforms. Experimental results indicate that swAFL outperformed PyTorch and TensorFlow by 19.5 and 23 times, respectively, on average.
Students' Learning Difficulties And Their Relationship With Biology Learning Outcomes Of Class XI Students at SMA N 8 Padang During Online Learning

his research is motivated by students who have difficulty in the online learning process is the low learning outcomes obtained from students. This study aims to analyze what factors influence the biology learning difficulties of students in class XI IPA at SMA Negeri 8 Padang during online learning and to determine the relationship between students' learning difficulties in biology through online learning and student biology learning outcomes. This research is descriptive research. The population of this research is class XI IPA which consists of 3 classes totaling 110 students. The research sample amounted to 33 students. The sampling technique is a random sampling technique with a sample proportion of 30%. The research data were analyzed using descriptive analysis and then a t-test to determine the correlation. The results showed that the highest score of the student learning difficulty factor was 2.81, namely the motivation and interest in student learning factors, and the lowest difficulty factor obtained a score of 2.44, namely social interaction. There is a relationship between students' learning difficulties in biology through online learning with biology learning outcomes with a value of r = 0.520; the coefficient of tcount value of 4.642 is greater than ttable of 2.040, so it can be concluded that there is a positive and significant relationship between learning difficulties in biology through online learning and student learning outcomes and there are suggestions for schools to be positive inputs in efforts to build and improve models. online/online learning and is also able to improve student learning and it is hoped that teachers and parents can recognize and observe online learning difficulties experienced by these students.
Supervised Regularized Multidimensional Scaling Using Weighted Stress Measure

Supervised Regularized Multidimensional Scaling (SRMDS), a non-linear variant of classical Multi-Dimensional Scaling (cMDS) is proposed recently which involves Radial basis function.The method is focused on the effective selection of centers of the radial basis functions in transforming data from a higher dimensional space to a lower dimension.The transformation matrix is determined by minimizing stress.Weights of components of the stress that are of great importance for classification of data got less focus in Supervised Regularized Multidimensional Scaling.In this article, we have investigated several forms of non-linear functions which may be used as weights of the stress measure.A new form of Z-shape weight function dependent on intraclass information of the dataset is introduced which prefers to preserve global structure of the dataset.The efficiency of the proposed approach is illustrated on several benchmarking datasets which shows that the weighted Supervised Regularized Multidimensional Scaling (WSRMDS) outperforms the base method and some other state of the art approaches such as Linear Discriminant Analysis (LDA), and Supervised Principal Component Analysis (SPCA).Observing the finding of this research, among different weight functions, Z-shape weight function is recommended to use since it works better then any other weight functions for most of the data sets.
Reception of Vl.S. Solovyov’s philosophical conceptions in A. Beliy’s epistolar heritage

The article presents results of research of Vl.S. Solovyov’s sophiological and theurgic concepts reception in the epistolary heritage of A. Beliy – first of all, the early period of philosopher and symbolist poet until 1905. It is argued, that of all the Young Symbolists, it was Beliy who was the closest to understanding Solovyov's sophiology and creating his own integral system of theurgic symbolism on its basis. It is substantiated, that the starting point in the construction of this system is the direction to synthesis of eschatology, World Soul doctrine and theurgic role of the life-creator artist. The purpose of this research is to trace the origin of Beliy's doctrine of symbolism as a worldview, a self-conscious soul and a collective personality, presented in detail much later, but rooted in the original reading of Solovyov. An appeal to the correspondence between Beliy and A.A. Blok, E.K. Metner, N.I. Petrovskaya, A.S. Petrovskiy and others, is justified by the fact that it is in these letters that the general ideological contours of his concepts are outlined. Later, they turned out to be eclectically complicated in many ways, which makes it difficult for modern researchers to fully understand them, but the epistolary material is a kind of compass in the confused area of Beliy's metaphysics. The epistolary material analysis provides the method of understanding Beliy's metaphysics, taken into account, that later his system concepts turned out to be complicated by the thinker himself, which makes it difficult for modern researchers to understand them holistically.
A graph-based knowledge representation for intelligent fault diagnosis and early-warning knowledge base

This paper aims to effectively utilize the vast amounts of data generated by data centers, which are used to support fault diagnosis and early warning functions. Due to the large volume and complexity of data, as well as the semantic relationship among data, in this paper, we adopt knowledge graph technology to extract, fuse, process, and update the knowledge in data centers. Then, we provide a feasible method for constructing a knowledge graph for fault diagnosis and early warning in a data center by describing the correlation of data, reasoning and analyzing the data on a reasonable basis. In addition, we also discuss how knowledge is represented.
The use of interactive game simulators for the development of algorithmic thinking of students in Russian language and literature lessons

Problem and goal . The model of formation of competitive qualities of a graduate of a modern digital school assumes that he has a culture of thinking, the ability to generalize, analyze, perceive information, set goals and choose ways to achieve it. The development of relevant skills is actively taking place in the lessons of computer science, mathematics, physics, chemistry. However, the Russian language and literature have a certain didactic potential for the formation of the ability to perform mental operations, choosing the optimal way to achieve the goal, etc. The expediency of using interactive simulators to support the communicative activity of students in the study of the Russian language and literature in order to form algorithmic thinking is substantiated. Metodology. The possibilities of designers of interactive simulators for various purposes are analyzed: for the development of online games (Lingo Play, Kid Mama), quests (Learnis), mobile phones (Alice's Resort, Kotovasia), for creating puzzles, charades, crosswords, metagrams and puzzles with riddles, quizzes. To evaluate the input conditions, testing was used, including blocks on the Russian language, literature, and computer science. The experimental study was conducted in the MOE Secondary School No. 25 of Sochi named after Hero of the Soviet Union S.E. Voitenko at the lessons of Russian language, literature, computer science. The participants of the experiment were 46 schoolchildren from the sixth grades. To create interactive game simulators in the classroom, the online designer of “eTrenics” is used (services “Kokla,” “Krypton,” “Morphanki,” “UFO,” “Potato”). Statistical processing of the results was performed using Pearson's chi-square test. Results. Students study services for creating interactive game simulators, use them to process new words, memorize spelling rules, and the plot of works of art. Statistically significant differences in the qualitative changes that occurred in the system according to the levels of development of algorithmic thinking were revealed. Conclusion. Described the features of the presented version of the use of interactive game simulators for the development of algorithmic thinking of schoolchildren in Russian language and literature lessons: inter-network interaction, the design of simulators according to the rules of the Russian language or the plot of the work, the intensification of learning, taking into account the specifics of the “clip” thinking of adolescents.
Optimal Design of a Novel Leg-Based Stair-Climbing Wheelchair Based on the Kinematic Analysis of the Stair Climbing States

This work presents a method to find the optimal configuration of a leg-based stair-climbing wheelchair. This optimization begins with the definition of a high-level control architecture, in which the kinematics restrictions related to the specific obstacles are considered. Then, the reference trajectories for all the actuators are generated as a function of the physical parameters of the mechanism, the dynamic restrictions of the actuators (velocity and acceleration) and the sensor errors. This work illustrates, based on a set of configurations, how the total time to climb up and climb down a defined stair depends on all these parameters, also reporting the best set of parameters that reduces the time and makes the mechanism more stable for a given scenario. The optimization in this work is performed with a brute-force search within a grid of parameters with a resolution of 1 mm. Thus, as the local minima is located, the complexity of the problem is revealed.
Customer experience dimensions and e-government success in United Arab Emirates

This systematic research study examined the connection between customer experience dimensions and e- government success in Abu Dhabi in United Arab Emirates (UAE). The organized study utilized a descriptive and cross-sectional survey research design with a positivism philosophy. A sample of 382 participants out of 108,825 target population was chosen employing a table developed by Morgan &amp; Krejcie (1970). Facts were gathered utilizing a questionnaire, simple random sampling and examined applying Descriptive Statistics and Structural Equation Modeling using the Smart Partial Least Squares (SPLS) Version 3.3.3 software to test the hypotheses. The inquiry study findings came up with a significant correlation between customer experience dimensions (comfort, security and usability) and e- government success at significant level of 0.05. It was thus concluded that the customer experience dimensions significantly affect e- government success. The logical investigation study recommended that the UAE government should augment the budget for e-government successful implementation programs.
ANALISIS KOMPARTEMEN DESAIN TAS PERLENGKAPAN KAMERA UNTUK VIDEO BLOGGER

Increasing video content on social media has led to more people doing video blogging or referred as video bloggers (vloggers). It affects the number of vloggers in Indonesia, reaching half the total number in the world. Vloggers need a bag to carry equipment so that the equipment is stored correctly and undamaged when creating content outdoors. The specific bags for camera equipment on the market still do not fulfill their requirement. These conditions require vloggers to provide various bags, while vlogger activities and equipment always change according to content needs. This study aims to answer the problems experienced by vloggers by increasing the effectiveness of the bag through concepts, systems, access, and compartment layouts. The method used in developing the compartment starts from collecting data such as questionnaires and interviews to identify problems, observation of existing products and product references, activities studies, continued analysis data, design concepts to production, and product testing.
Maker-based Serious 3D Game Authoring Tool for Cultural Heritage Education

As globalization and internationalization are taking place, it has become necessary to preserve one’s cultural heritage. In an individual’s personality, culture plays a substantial role and by educating each other about one’s culture, better cultural inclusion and respect are achieved. For better equality and inclusion within communities as mentioned by United Nations 17 Sustainable Development Goals, an engaging yet effective way of cultural awareness should be focused on. However, as younger generations are the future of a community, proper digital technologies should be utilized to make them engagedand entertained including benefiting the main objective of cultural heritage preservation. This research gathers appropriate design guidelines by letting users play a serious cultural Internet of Things (IoT) game focusing on a UNESCO Heritage Site in Malaysia and then validating a serious 3D game authoring tool by interviewing experts. The aim of this research is to design and develop an effective and innovative serious 3D game authoring tool with which anybody i.e., even non-experts can make their own game to share their cultural heritage story with others while playing a game themselves. Furthermore, this research also attempts to integrate interactive technologies such as IoT and haptic feedback technology such as Leap Motion, and UltraLeap 3Di into the game authoring tool. Finally, this research will do a case study with a school and a museum to validate the serious 3D game authoring tool and how it was perceived and accepted by the required stakeholders.
Real-time Face Tracking for Service-Robot

Real-time human face tracking is suggested in this paper for use while interacting with robots. The system consists of two main parts, the first works to discover the human face, determine its location in relation to the original image, and find the dimensions of the face to be used in the second part of this system. The second part receives the location and dimension of the face and tracks it by controlling the movement of the camera according to the offset between the interval. In order to detect human faces for the earlier job, the Haar cascade method is used, whereas the Kanade-Lucas-Tomasi (KLT) algorithm is used for face tracking under various circumstances. As a trace output from the prior stage, the camera is offset by its offset between image frames. The findings of the experiments demonstrate that real-time tracking of human faces was successful even when the participants were donning glasses, hats, or face-side positions. At a maximum frame rate of 26 fps, experiments were conducted.
Opportunities and Challenges of Bamboo Based Entrepreneurship in Badikhel Area of Lalitpur District, Nepal

This study opportunities and challenges of bamboo based entrepreneurship was carried out in Badikhel area of Lalitpur district, Nepal. This paper is a descriptive study focused to assess the opportunities and challenges of bamboo based entrepreneurship. Both primary and secondary data were used. Questionnaire, key informants interview, focus group discussion were used to coined the required information. The quantitative data are presented in tabulator form and qualitative data are interpreted as a narrative form. The study showed traditional marketing strategy, lack of resources, traditional skills, and transportations, lack of opportunities, lack of financial knowledge and lack to access to financial institutions are major challenges while promoting the bamboo based enterprises. However, this study proved that these entrepreneur, identified good opportunities, practice on equal wage for same work, initiate their ventures and they have formulated plan. The study indicated that financial access, training facilities, government subsidy, etc. are opportunities in this regard. Pahari were socialized in farming, husbandry, bamboo winning, bamboo crafting and now some people are shifting others. There are some recommendations that could uplift the micro enterprises in Nepal. Without entrepreneurship rural area cannot be developed, thus, good policies and plan must formulate and implement as well with sufficient financial and technical support by local government and development stakeholders. The verbal consent was taken while collecting the data.
UoLMM'22: 2nd International Workshop on Robust Understanding of Low-quality Multimedia Data: Unitive Enhancement, Analysis and Evaluation

Low-quality multimedia data (including low resolution, low illumination, defects, blurriness, etc.) often pose a challenge for content understanding, as algorithms are typically developed under ideal conditions (high resolution and good visibility). To alleviate this problem, data enhancement techniques (e.g., super-resolution, low-light enhancement, derain, and inpainting) have been proposed to restore low-quality multimedia data. Efforts are also being made to develop robust content understanding algorithms in adverse weather and lighting conditions. Some quality assessment techniques aiming at evaluating the analytical quality of data have also emerged. Even though these topics are mostly studied independently, they are tightly related in terms of ensuring a robust understanding of multimedia content. For example, enhancement should maintain the semantic consistency of the analysis, while quality assessment should consider the comprehensibility of the multimedia data. The purpose of this workshop is to bring together individuals in three areas: enhancement, analysis, and evaluation, for sharing ideas and discussion on current developments and future directions.
The alternative irregularity reduction algorithm built on 2-stage identification with AMF on FMIO

Built on neighborhood correlation, a 2-stage identification technique was offered to incorporate on the irregularity reduction algorithm for random magnitude impulse outlier (RMIO). As a result, this algorithm has an ultimate efficacy thereby a 2-stage identification technique becomes to be one of the high efficacy identification technique. Accordingly, this paper attempts to propose an alternative irregularity reduction algorithm built on a 2-stage identification and adaptive median filter (AMF) with under fix magnitude impulsive outlier (FMIO) at little, mild and immense massiveness. First, by examining great number of depictions, the optimized window dimension for 2-stage scheme from computation and performance is disposed. Second, comprehensive examinations represent that the 2-stage identification technique is disposed to identify between regular and irregular pixels at all massiveness, especially little and mild massiveness. Third, the identification efficacy on great depictions at all massiveness is examined on regular, irregular, regular-irregular efficacy perspective to estimate the optimal window size and optimal 2-stage constant value. Finally, the overall outlier reduction efficacy of an outlier reduction built on 2-stage technique and AMF is examined on great depictions at all massiveness related with other up-to-the-minute outlier reductions. From these results, the outlier reduction has remarkable efficacy than other up-to-the-minute outlier reductions.
Close-range Hot Spot Detection based on K-neighbor Algorithm and Experiment on Hot Spot Effect

Abstract Abnormalities caused by the hot spot effect are very common in the application of photovoltaic modules, which seriously affect the life and power generation efficiency of photovoltaic modules. Therefore, the study of hot spot effect is of great significance to the development of photovoltaic industry in the future. By analyzing the hot spot effect and its causes, this paper lists possible factors that may affect the hot spot effect, uses the K-proximity algorithm for hot spot detection to classify the near-field infrared images obtained in photovoltaic power plants, and designs experiments to explore the influence of several factors on the hot spot effect, the influence characteristics of the shading area and the types of shading objects are deeply explored, and finally a certain summary is made.
ICNet: Joint Alignment and Reconstruction via Iterative Collaboration for Video Super-Resolution

Most previous frameworks either cost too much time or adopt some fixed modules resulting in alignment error in video super-resolution (VSR). In this paper, we propose a novel many-to-many VSR framework with Iterative Collaboration (ICNet), which employs the concurrent operation by iterative collaboration between alignment and reconstruction proving to be more efficient and effective than existing recurrent and sliding-window frameworks. With the proposed iterative collaboration, alignment can be conducted on super-resolved features from reconstruction while accurate alignment boosts reconstruction in return. In each iteration, the features of low-resolution video frames are first fed into the alignment and reconstruction subnetworks, which can generate temporal aligned features and spatial super-resolved features. Then, both outputs are fed into the proposed Tidy Two-stream Fusion (TTF) subnetwork that shares inter-frame temporal information and intra-frame spatial information without redundancy. Moreover, we design the Frequency Separation Reconstruction (FSR) subnetwork to not only model high-frequency and low-frequency information separately but also take benefit of each other for better reconstruction. Extensive experiments on benchmark datasets demonstrate that the proposed ICNet outperforms state-of-the-art VSR methods in terms of PSNR/SSIM values and visual quality, respectively.
CRITICAL ANALYSIS USING TECHNOLOGIES AT AUTOMOTIVE REMANUFACTURING OPERATION

As part of the circular economy, remanufacturing plays an important role in the economic and sustainable development of automotive industries.In this way, this article, through a systematic literature review, presents the main challenges faced by remanufacturing companies in their operations and how technologies towards Industry 4.0 can help to mitigate some of these problems.A case-study in an automotive company was carried out and compared with the results from the literature.It can be seen that even remanufacturing operation being done manually, and all parts replaced in case of uncertainties the cost saving from material recovered is still significant, which opens opportunities for future studies to consider the application of current used manufacturing technologies in the remanufacturing operation.