Reviewerly/exHarmony huggingface dataset:
At your service: how can blockchain be used to address societal challenges

This chapter explores the contributions that blockchain may offer to the societal challenges of realising sustainable development and a circular economy. More specifically, we address the question on how blockchain can be used to develop a hybrid, transactional values-system using multiple values (e.g., electricity, mobility, assets, etc.) simultaneously between various actors. We do so by conceptually exploring the concept of circularity and sustainability in addition to typifying the characteristics of blockchain technology. To frame this exploration, we first specify three distinct, yet coherent levels of development: accounting, contractual, and community. Each of these levels will be illustrated by examples. Next, we confront these developmental levels of blockchain with three levels of societal challenges, namely (i) servitisation and dematerialisation, (ii) life-cycle extension, and (iii) recycling, conversion, and substitution. Confronting blockchain levels with the levels of societal challenges leads to a possible conceptualisation of the application of blockchain technology in relationship to the societal challenges. In conclusion, we state that this debate is still in its infancy and that we have only superficially investigated this intriguing issue.
Self-determined Lighting Control by Surveillance Camera in Smart Building

A recent smart building can realize energy-saving while providing a comfortable environment for users. However, it still remains an open question that unilateral users' control or time-based loop operating in a fixed pattern. It would be ideal for a smart building to think for itself and give the users a suitable environment: that is a self-determined control system. Thus, as a first step of the self-determined control of the smart building, the lighting and surveillance camera have been selected in this paper. Moreover, to communicate with users, we used a smart speaker to let users know the information about the device being controlled. The method which is one-side communication from building has a higher score (5.38) than the approach without using the smart speaker (4.08). This study, thus, may contribute to getting closer to the final goal of smart buildings.
E-AGRICULTURE MANAGEMENT SYSTEM SUPPORTING FARMERS ACTIVITY

Technological importance have been a great support for making decisions in various fields especially in farming. The growth of agriculture has been on under development for the past few years due to lack of Agriculture knowledge and ecological changes. The main aim of this paper is to accomplish farmers for their wakefulness, usage and observation in e-Agriculture. The study used numerical investigation design technique to collect data from farmers for their awareness in e-Commerce. The results obtained indicate the level of awareness is less such that there is a need for e-agriculture for their support. E-Agriculture is a stage for supporting marketing of agricultural products.
Improving Students’ Writing Skills through Collaborative Learning: A Case Study of Senior High School Veteran 1 of Sukoharjo

The research aims at improving students’ writing skills using collaborative learning at 10th-grade students of the Senior High School 1 of Veteran Sukoharjo. This research was a classroom action research. The technique used in this research consisted of planning, implementing, observing and reflecting. The research was applied in two cycles. Every cycle consisted of three meetings. In the technique of collecting data, the researcher used qualitative and quantitative techniques. The qualitative data were collected from documentation, observation and interview with teachers and some students. The quantitative data were collected from the score of the students’ pre-test ad post-test, validity and reliability. The result of the research showed that collaborative learning could improve students’ writing skills. By using collaborative learning, the students showed active and have self-confidence in the teaching-learning process. This method brought positive result. The progress of the students’ writing skills also can be seen from the result of the tests score. In the multiple-choice pre-test, the mean score of the pre-test was 59,7and improved to be 68,1in post-test 1 of cycle 1. In cycle 2, the mean score of post-tests 2 was 79,7. In the essay pre-test, the mean score of the pre-test was 61,3and improved to be 69,1in post-test 1 of cycle 1. In cycle 2, the mean score of post-tests 2 was 78,4. It could be concluded that there was a significant improvement in the students writing skills after using collaborative learning.
SUCCESS FACTORS OF ACCOUNTING INFORMATION SYSTEM IN PT. KUNCIMAS NIAGATAMA BANYUWANGI

This study aims to analyze the factors that influence the success of the accountinginformation system at PT. Kuncimas Niagatama Banyuwangi. The success of accountinginformation systems is influenced by Human Behavior in Organizations, ManagementSupport, Motivation and Training, Data Processing in the System, and Management andImplementation Process. This study used the primary data by total sample of thirty-fiveemployees and used the purposive sampling technique. The quality of the questionnaire wastested using the validity test and reliability test. Data analysis used multiple regressionanalysis, which includes the classic assumption test, t test and the coefficient of determinationThe results showed that Human Behavior in Organizations, Motivation and Training,Management and Implementation Process significantly influence the Success of AISImplementation. Only Management Support variable and Data Processing in the System haveno significant effect on the Success of AIS Implementation.
Hybrid Deep Network for Anomaly Detection.

In this paper, we propose a deep convolutional neural network (CNN) for anomaly detection in surveillance videos. The model is adapted from a typical auto-encoder working on video patches under the perspective of sparse combination learning. Our CNN focuses on (unsupervisedly) learning common characteristics of normal events with the emphasis of their spatial locations (by supervised losses). To our knowledge, this is the first work that directly adapts the patch position as the target of a classification sub-network. The model is capable to provide a score of anomaly assessment for each video frame. Our experiments were performed on 4 benchmark datasets with various anomalous events and the obtained results were competitive with state-of-the-art studies.
Exploring Modified Symmetric Hellinger's Measures for the Generation of Association Rules

데이터 마이닝 기법 가운데 현업에서 많이 활용되고 있는 연관성 규칙은 데이터베이스에 있는 항목들 간에 관련성을 찾아내는 기법이므로 많은 연구자들에 의해 연관성 평가 기준들이 개발되고 있다. 본 논문에서는 여러 가지 연관성 평가 기준인 흥미도 측도 중에서 헬링거 함수를 응용한 측도를 제안하고자 한다. 헬링거 측도는 현재까지 개발된 연관성 측도들에 비해 여러 가지 장점은 있으나 연관성의 한쪽 방향만을 고려함으로써 연관성 평가 결과가 왜곡되게 나타날 수 있다. 본 논문에서는 이러한 문제를 해결하고자 대칭적 헬링거 측도를 변형하여 여러 종류의 대칭적 헬링거 측도를 고안하여 제시하고, 예제를 이용하여 동시 발생 빈도와 불일치 빈도 등에 따른 변화를 비교해봄으로써 유용성을 탐색해보았다. 동시 발생 빈도가 증가하면 양의 연관성의 크기는 증가해야 하고, 불일치 빈도가 증가하게 되면 양의 연관성의 크기가 증가해야 한다. 예제를 통한 실험 결과, 대칭적 부호 헬링거 측도, 조정된 대칭적 헬링거 측도, 그리고 조정된 대칭적 부호 헬링거 측도 중에서 조정된 대칭적 부호 헬링거 측도가 연관성의 정도와 방향을 가장 잘 표현해주므로 연관성 측도로서는 가장 바람직한 것으로 나타났다.The association rule mining that is widely used in the field of data mining is a method of finding the degree of association among the items in the database, so that many researchers have developed association thresholds. In this paper, we propose some measures applying the Hellinger function among interestingness measures. The Hellinger measure has several advantages over the association mesures developed so far, but the association evaluation result may be distorted by considering only one direction of the association. We have devised various modified symmetric Hellinger measures such as symmetric sign Hellinger measure, adjusted symmetric Hellinger measure, and adjusted symmetric sign Hellinger measure to solve this problem, and tried to explore the usefulness by comparing them with examples. As a result, the adjusted symmetric sign Hellinger measure showed the best association threshold because it showed the degree and direction of the association.
ГОТОВНОСТЬ ПЕДАГОГОВ ДОШКОЛЬНОЙ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ К РАБОТЕ С ДЕТЬМИ С ОГРАНИЧЕННЫМИ ВОЗМОЖНОСТЯМИ ЗДОРОВЬЯ

The article is devoted to one of the main requirements for the implementation of support of participants of the inclusive process - the readiness of teachers of preschool organizations to work in an inclusive education of children with disabilities. The results of sociological research of information, psychological and professional readiness of teachers to include special children in the educational process are presented.
SIGCSE organizational updates

On behalf of the SIGCSE Board, I hope that everyone is adjusting to these unprecedented times. From emergency remote teaching, to isolating in our homes, to taking care of ourselves and families, and adjusting to this new existence, the current world situation has touched all of us in numerous ways. As a SIGCSE community, there has been much discussion of how these changes will impact our courses and students on the SIGCSE-members listserv. If you are not already a member of this wonderful community resource, feel free to see this page (https://sigcse.org/sigcse/membership/ mailing-lists.html) for information for how to join us in that discussion.
Optimisation of a Checkers Player Using Neural and Metaheuristic Approaches

Within this paper we evaluate the components used to build a checkers playing system with no embedded expert knowledge. We found that Particle Swarm Optimisation (PSO) and Evolutionary Algorithms (EA) are suitable training methods for Artificial Neural Networks (ANN) acting as evaluation functions within minimax, when training on 2 and 4 plies. By playing the trained networks against one other the single best network was found, which was produced by 3000 iterations of PSO playing on 2 plies. We show that this network outperformed a piece differential evaluation function, both on a fixed number of plies, and when using iterative deepening search. We also show that the higher the amount of plies the better a system will perform, however it is the relative difference between the amount of plies that impacts the performance. External validation of the system shows it winning all 44 games it played against non-expert human players. It was also able to solve the hardest tasks on a checkers problem website. The system was also able to draw against Chinook, a checkers playing system with expert knowledge and state-of-the-art in the field.
Pelatihan Automatic Pipe Gas Cutter Bagi Pekerja Bengkel Las di Meunasah Mesjid Kecamatan Blang Mangat Kota Lhokseumawe

The cutting process is one of the engineering work that is very often done by welding workshop workers everywhere. Plates and pipes have become fabrication components for all construction needs in the community. In the field, in general welding workshops still use a fully manual method in which the results of cutting are highly dependent on the operator's hand line alignment. Many shortcomings / weaknesses of the cutting process that are carried out completely manually include the precision value of the cut is very low, the straightness of the cut tends to deviate from the size, greater cut gas consumption, and higher operational costs. Based on the description above and observing the cutting process in the fabrication process carried out in the Adek Abang welding workshop, it still fully uses the hands. Automatic Pipe Gas Cutter Training for Welding Workshop Workers in Meunasah Mosque, Blang Mangat Subdistrict, Lhokseumawe City, aims to introduce the welding workshop practitioners to cutting technology that makes it easier to cut the process with high productivity so that it can increase the level of competition with the optimum low price of fabrication. This training is also a form of transfer of science and technology to welding workshop workers with the aim of increasing their income and welfare. This training method includes 30% theory and 70% practice, participants are able to understand all the material correctly and are able to practice independently of the object of training correctly and on time. The number of participants who took part in the training program totaled 6 people. From the results of the evaluation conducted, it was apparent that all participants understood correctly all the evaluation material which included the principle of cutting pipes with automatic machinery as well as the safety of working with tools. Overall participants can be categorized as graduated by obtaining an average grade of 85. This value can be used as an indicator of the success of this training in achieving training objectives.
РАЗВИТИЕ ПОЗНАВАТЕЛЬНОГО ИНТЕРЕСА ШКОЛЬНИКОВ НА УРОКАХ ФИЗИКИ

The article presents the study of the development of cognitive interest of students in physics lessons. Special attention is focused on the importance of the development of cognitive interest. One of the factors of formation of cognitive interest - entertaining-is considered. Created a collection of Interesting control works, which presents the tasks: related to the life experience of people, task drawings, tasks with fairy-tale heroes.
Learning Aids and Japanese Teaching

Cards and other means are used to assist teaching in traditional foreign language teaching.However, with the rapid development of science and technology, the teaching efficiency of such learning aids is low and cannot be suitable for modern teaching.In particular, the 50 picture cards used in Japanese teaching are relatively rigid and cannot play a role in deepening memory.In view of this, this study intends to design a Japanese language learning aid device, on the one hand, to increase the entertainment and interaction of Japanese language learning, on the other hand, strengthen the learning and memory of Japanese Hiragana, katakana and pronunciation, and improve the efficiency of Japanese learning. Pros and cons of modern learning aidsWith the development of society and the advancement of science and technology, although the learning aids in traditional teaching can still play a certain role in teaching, it can no longer adapt to modern teaching.Especially with the development of the Internet, modern technologies such as mobile phones and computers Products are gradually used in teaching, which not only improves the efficiency of "teaching", but also promotes the effect of "learning".For example, a foreign language learning website not only has a large amount of learning resources, but also learners can learn autonomously at any time and place.In addition, it can meet the learning of foreign language learners at different stages and levels from elementary to advanced levels.Moreover, there is no limit to languages and categories, covering all aspects from simple letters and intonation to high difficulty in listening, speaking, reading and writing.It can be said that foreign language learning website has the characteristics of specialization and systematization, and it is a good helper for foreign language learners to learn foreign languages.As another example, the popularity of mobile phones has greatly facilitated people's lives.Using mobile phones to assist teaching in teaching, such as learning apps, flipping classrooms, Mobile phone check-in, etc., can be implemented on mobile phones.It can be said that mobile phones are a modern learning Means can play a role in improving learning effects.However, no matter which modern learning method is based on the network, it cannot be achieved without the "support" of the network.Moreover, there are many and complex contents of
Knowledge Economy as a Cross Cultural Aspect in the Training of Engineering and Humanitarian Students

The global economy and national industries have faced the time of far-reaching continuous innovation that is to substantially increase the quality of life of local population. In doing this, extensive process of innovative reproduction leads to an objective need to trigger creativity potential of both faculty and students within universities, which means generating new ideas, diffusing knowledge and designing innovative products. Thus, the conditions of the modern educational activities bring about a necessity to develop and adopt educational competence practices in the field of knowledge economy including skills and abilities to boost intelligence level and mature economic mentality, as well as change academic and cross-disciplinary profiles in their professional fields.The text focuses on laying grounds for the necessity to design a strategy for social and economic breakthrough. This strategy is to form a new economic system type based on knowledge. Knowledge here is viewed as an economic category. The authors also propose the model of an integrated economic field and the principle of spiritual production development in the frame of knowledge economy. The basic condition for effective progress in knowledge economy is the implementation of the capital return mechanism in the production patterns where aggregate product surplus value is produced.
The Demos in a Pandemic: Staging Elections in a Health Emergency

(2300 words) Canvasses current and potential legal responses to holding elections during a time of prolonged contagion, including surveying current and forthcoming elections in Australia and elsewhere and practical, constitutional and participatory challenges.
The Stochastic Complexity of Spin Models: Are Pairwise Models Really Simple?

Models can be simple for different reasons: because they yield a simple and computationally efficient interpretation of a generic dataset (e.g. in terms of pairwise dependences) - as in statistical learning - or because they capture the essential ingredients of a specific phenomenon - as e.g. in physics - leading to non-trivial falsifiable predictions. In information theory and Bayesian inference, the simplicity of a model is precisely quantified in the stochastic complexity, which measures the number of bits needed to encode its parameters. In order to understand how simple models look like, we study the stochastic complexity of spin models with interactions of arbitrary order. We highlight the existence of invariances with respect to bijections within the space of operators, which allow us to partition the space of all models into equivalence classes, in which models share the same complexity. We thus found that the complexity (or simplicity) of a model is not determined by the order of the interactions, but rather by their mutual arrangements. Models where statistical dependencies are localized on non-overlapping groups of few variables (and that afford predictions on independencies that are easy to falsify) are simple. On the contrary, fully connected pairwise models, which are often used in statistical learning, appear to be highly complex, because of their extended set of interactions.
A Meta-Heuristic Algorithm Approximating Optimized Recommendations for E-Commerce Business Promotions

To provide personalized services such as online-product recommendations, it is usually necessary to model clickstream behavior of users if implicit preferences are taken into account. To accomplish this, web log mining is a promising approach that mines clickstream sessions and depicts frequent sequential paths that a customer follows while browsing e-commerce websites. Strong attributes are identified from the navigation behavior of users. These attributes reflect absolute preference (AP) of the customer towards a product viewed. The preferences are obtained only for the products clicked. These preferences are further refined by calculating the sequential preference (SP) of the user for the products. This paper proposes an intelligent recommender system known as SAPRS (sequential absolute preference-based recommender system) that embed these two approaches that are integrated to improve the quality of recommendation. The performance is evaluated using information retrieval methods. Extensive experiments were carried out to evaluate the proposed approach against state-of-the-art methods.
Implementation of ROS in Drones for Animate and Inanimate Object Detection

The purpose is to create elementary drone surveillance system for safety and security. They become predominant in the time of wars. The aerial surveillance proves to be very promising when wide areas are considered. It provides visual imagery or video of the site. These unmanned aerial vehicles (UAVs) help in safety and security of site and people at public places and military bases. Most drones just provide live video feed through cameras attached to them. It is unable to identify the objects present at the site. Drones also need to be automatic in conditions where remotely controlling the drone is not possible. The drone needs to reach the starting position in these conditions using the shortest path while avoiding obstacles. The drone needs to have an OS of its own during these conditions. It needs to maneuver itself to a safe location. The You Only Look Once—version 3 (YOLOv3) algorithm helps in fast processing of video frames and hence is being widely used for real-time purposes.
Transfer Learning for Seismic Phase Picking on Different Geographic Regions

Machine learning algorithms have become a powerful tool in different areas of seismology, such as phase picking/earthquake detection, earthquake early warning and focal mechanism determination. Previously convolutional neural networks (CNN) have been applied to continuous seismic waveform recordings to perform efficient phase picking and event detection with good accuracy [Zhu et al., 2018]. However, the off-line training of current CNN requires at least a few thousands of accurately picked seismic phases, which makes it difficult to be applied to regions without sufficient picked phases. In this work, we will validate the transfer learning among different geographic regions. Our tests show that the phase picker trained on manually-labeled data acquired from Sichuan, China following the 2008 M7.9 Wenchuan earthquake [Zhu et al., 2018] works equally well on the continuous waveform acquired from Oklahoma, US [Zhu et al., 2018]. Specifically, using the CNN trained on the Wenchuan dataset, together with 895 local/regional catalog events recorded in central Oklahoma, we refine part of the networks to pick the arrival times of the local seismicity in Oklahoma. The refined CNN results are compatible with the matched filter results using the same catalog events as templates. Our next step is to extend our test to waveforms from different tectonic regions to demonstrate the generality of CNN-based phase picker. We plan to further use a New Zealand seismic dataset that includes more than 20 GeoNet stations in the North Island, where the matched-filter detected results are available to be compared with (Yao et al., 2018). Alternatively dataset include a subset of events in the waveform relocated catalog in Southern California. Updated results will be presented at the meeting.
Study on oceanic big data clustering based on incremental K-means algorithm

With the increase of marine industry in the Beibu Gulf, data clustering has become an important task of intelligent ocean. Partition clustering methods are suitable for marine data. However, traditional K-means algorithm is not suitable for large scale data. Focusing on the characteristics of oceanic big data, we propose a clustering method based on incremental K-means (IKM) algorithm. First, a vector model is adopted to represent data sets, and the calculation model for mean values and centres is used to initialise arbitrary numbers of data points. Second, the input data vectors are iteratively calculated in an incremental vector form. Finally, by applying incremental vector and distance model, the large-scale data are clustered according to convergence condition. Experiments show that the algorithm can increase the clustering efficiency, reduce time and space complexity, and lower the missing data rate.