Reviewerly/exHarmony huggingface dataset:
A Multi-agent Design of a Computer Player for Nine Men's Morris Board Game using Deep Reinforcement Learning

Deep Reinforcement Learning (DRL) has been recently deployed in many artificial intelligence applications, and game players are not an exception. Nine Men's Morris is a board game that has been addressed and implemented using different AI techniques. In this paper, a multi-agent design of a computer player is introduced that represents the placing, moving, and capturing phases of the Nine Men's Morris. This design is a self-play one that knows nothing about the game other than the rules. Monte Carlo Tree Search (MCTS) is combined with Convolutional Neural Network (CNN) in each agent to provide the DNN with the training data. This combination allows the DNN to play against itself and tune its weights to predict actions. This computer player design ensures a proper training of NN without any human dataset and can compete with expert humans in the board games.
Shape Description and Retrieval in a Fused Scale Space

In this work, a scale-space shape descriptor is proposed for shape retrieval, which is motivated by the multiscale mechanism of our human visual perception. First, morphological operations and the Gaussian smoothing are jointly used to produce a fused scale-space description of the input shape, which is able to handle strong noise, intra-class shape variation and irregular deformation simultaneously. Then, the height-function features of the shape are extracted across scales. Finally, shape retrieval is conducted by an integration of the retrieval results individually yielded at multiple scales. Experimental results on benchmark datasets validate the accuracy, efficiency and robustness of our proposed method.
General Characteristics of Related Rights of the Publisher in Russian Civil Law

The paper has analyzed the grounds for emergence and termination, as well as the validity period and features of the content of intellectual rights of the publisher under the current civil legislation. The possibility of its early termination in court is considered as one of the features of the exclusive right of the publisher. The author has determined the range of actors authorized to reguest early termination of the exclusive right of the publisher The influence of the will of the author on the range of actors entitled to reguest the early termination has been identified. The author has substantiated the researchers' standing that permits the application of the rules regulating the application of the sign of legal protection of related rights to the exclusive right of the publisher by analogy. The personal intangible right of the publisher to indicate his name is characterized as perpetual. The paper has established the independence of the emergence of this right from the acquisition of the exclusive right of the publisher. The authors have supported the opinion concerning the possibility for the publisher to use a pseudonym on the basis of application of the rules concerning the right of the author to the right of the publisher to indicate his name by analogy. The power of the publisher to permit the introduction of changes, abbreviations or additions to the published work is considered as forming a non-personal urgent intangible right of the publisher to inviolability of the work of another author. The authors have highlighted the dependence of the emergence and content of the right under consideration upon the will of the work's author expressed in writing. The authors have also investigated the termination of the right under consideration in case of transfer of exclusive right of the publisher to another person. The authors have revealed the inconsistency of the existing legislative regulation. Thus, the publisher is not entitled to supplement the work with illustrations and explanations. The authors have expressed their opinion on the inexpediency of interpretation of civil legislation as excluding the possibility for the publisher to independently make changes, abbreviations or additions to the work when it is being used.
Avoid Shortcomings of Cashless Transaction System using Blockchain

Technology is backbone of every system in today/s era. But as it is known that every coin has two faces. Technology is invented for betterment of society and humanity but it is necessary to ponder on security issues of digital system. Cashless Economy is a debatable issue of current days. This Paper addresses Errors and Loopholes in Cashless Transaction System (CTS), Mathematical Model to Illustrate loopholes, Difference between Cash and Cashless economy, Electronic Pickpocketing types, Security essentials of online shopping and how to avoid it using hash function, Soft Targets of intruders in cashless economy and some illustration for the same. Lastly this paper discusses the future of cashless economy and Online Shopping using blockchain technology.
Keynote presentations

The work demonstrates that brain might reflect the external world causal relationships in the form of a logically consistent and prognostic model of reality, which shows up as consciousness. The paper analyses and solves the problem of statistical ambiguity and provides a formal model of causal relationships as probabilistic maximally specific rules. We suppose that brain makes all possible inferences from causal relationships. We prove that the suggested formal model has a property of an unambiguous inference: from consistent premises we infer a consistent conclusion. It enables a set of all inferences to form a consistent model of the perceived world. Causal relationships may create fixed points of cyclic inter-predictable properties. We consider the “natural” classification introduced by John St. Mill and demonstrate that a variety of fixed points of the objects’ attributes forms a “natural” classification of the external world. Then we consider notions of “natural” categories and causal models of categories, introduced by Eleanor Rosch and Bob Rehder and demonstrate that fixed points of causal relationships between objects attributes, which we perceive, formalize these notions. If the “natural” classification describes the objects of the external world, and “natural” concepts the perception of these objects, then the theory of integrated information, introduced by G. Tononi, describes the information processes of the brain for “natural” concepts formation that reflects the “natural” classification. We argue that integrated information provides high accuracy of the objects identification. A computer-based experiment is provided that illustrates fixed points formation for coded digits.
Capacity and performance evaluation of the drainage system Jati Pinggir - Petamburan Central Jakarta

Abstract Flood problems become a crucial problem in the city of Jakarta. Jati Pinggir - Petamburan area is one of the affected floods. The density of the population and the narrower open land for water absorption causes the accumulation of standing water. The increased flow of water inundation affects channel capacity. For this reason, it is necessary to examine the ability to exist flood control buildings such as drainage canals, reservoirs and pump houses to deal with flooding with a 10-year return flood discharge in Jati Pinggir - Petamburan. Analysis of regional rainfall data, 10-year return period flood discharge, existing channel dimensions, the capacity of the pond and pump needs were used in this study.
Russian Language Proficiency is the Basis of the National Self-Identification of Russian Citizens

The article discusses the problem of teaching the Russian language in modern conditions of the functioning of educational organizations. The reasons for the decline in literacy of the younger generation and Russian citizens are described, among which are population migration, insufficient attention to teaching methods, etc. The requirements for primary school graduates in terms of mastering the Russian language are outlined in the draft new version of the Federal State Educational Standard for Primary General Education. Approaches to their implementation are being outlined, which will make it possible to positively affect literacy in our country. The article evaluates the discussion on the support and development of the Russian language, which took place at a meeting of the Russian Language Council under the President of the Russian Federation in September 2019.
An Electro-Acoustic Devices Recognition Detection System Based on Machine Vision

Abstract Aiming at a series of problems, such as low efficiency, low quality and high error detection rate, in the manufacturing process of various electro-acoustic devices, a recognition and detection system based on machine vision technology is proposed.Electroacoustic device were collected to patch the image threshold segmentation, feature points of the special points and electroacoustic device noise in image segmentation, and then to get the edge detection and binarization image set according to the characteristics of characteristics of electro-acoustic device patch contour recognition and extraction, realize the automatic recognition and detection of electroacoustic device.The system has successfully carried out the identification and detection test of electro-acoustic devices, and has high identification and detection efficiency and accuracy, high stability of the system, which has great practical application and promotion value.
Programs for optimization of communicative capacity of specialists of socio-common profile as a factor of their professional readaptation

The article presents an innovative approach to developing programs for developing the communication potential of sales specialists, which is based on the principle of amplification of semantic structures of communication and is built in opposition to the established industrial methods of training sales managers. The fundamental difference of this approach to training, as a form of training, lies in the goals and processes of the curriculum. Amplification, as a technique for enriching the semantic content of a concept through its integration with meanings that correlate with it in the context of objective activity, provides a new resource for the development of communicative potential. The article demonstrates a consistent chain of application of technology on the example of one factor of communication efficiency: the factor of communication efficiency is highlighted; amplification of the value of this factor; learning tasks aimed at correcting the semantic structure; elements of a training program designed to implement the selected tasks have been developed. The article analyzes the results of the training program. Based on the results of participation in the study of the experimental and control groups, the hypothesis about the possibility of increasing the effectiveness of communication by correcting the semantic structures of the seller by amplifying the range of values-factors of the effectiveness of interpersonal communication in a sales situation is confirmed.
Developing a New Haptic Passcode for User Authentication with a Personal ID Tag to Prevent Copying Attacks

We designed a haptic authentication system with a personal identification (ID) tag equipped with an embedded acceleration sensor and a radio frequency identification (RFID) tag that can be used in automated security systems. In the suggested system, users generate a passcode by haptic manipulation of an ID tag instead of typing in passwords using a keypad. An ID tag may be an ideal personalized gadget for ID authentication in many circumstances. The core of the proposed haptic authentication system is the activity-recognizable process that can be manipulated by the probabilistic model we developed and generate a much more secure passcode for authentication. With the system learning a total of 250 trials by 50 users for each haptic gesture, the average successful classification rate for the four-digit haptic passcode authentication was 88.9% using the probabilistic model we developed. Some haptic gestures, such as vertical upward flipping of the ID tag, showed lower accuracy than others due to the difficulty in haptic manipulation of the ID tag. From a copying attack experiment to examine the reliability of our haptic passcode scheme, it was proved that the haptic gestures with enough digits, apparently at least 6, were difficult enough to resist being copied by attackers. The same authentication scheme can also be applied for other personal devices that can be manipulated by hands for making haptic gestures, such as a mobile phone.
Multi-signal detection and parameter estimation fusion with an improved utility function

Joint detection and parameter estimation problems arise in a wide range of practical applications. For the multi-signal case, one needs to not only determine the presence of signals or not, but also to estimate the number of signals and the corresponding parameters. In this paper, we focus on modeling and solving the multi-signal joint detection and estimation fusion problem. Firstly, we present an extension of the original multi-signal joint detection and estimation model to the multi-sensor fusion scenarios. Secondly, an improved utility function is developed based on the optimal assignment, avoiding the possible many-to-one mapping when evaluating the difference between the true and estimated parameters. Moreover, the multi-sensor measurement likelihood function under clutter environments is evaluated by the Total Probability Formula, and the weighting probabilities are computed as done in the Joint Probability Data Association (JPDA) algorithm. To obtain the practical decision rule when given the constraint on the probability of false-positive (FP) events, the original constrained optimization model is solved efficiently by utilizing a series of model transformations. Simulation results demonstrate the efficiency of the proposed algorithm in the presence of an unknown number of signals, when compared with other competing algorithms.
Enhancement of OTP stream cipher algorithm based on bit separation

Abstract Along with the increasing development of cryptography and computer science, It is appropriate that we try to prepare and improve the ability of cryptographic algorithms To counteract and prevent threats. Generally This algorithm encrypt the text with combined using key. The original message must be the same length of the key used. Actually in this study, a new method for improve OTP was successfully carried out. first, key will be generated using PRNG algorithm then bits of Plaintext will be separate each into 2 bits then rotating it key using matrix table, further key will be inserted into separated Plaintext and re-separate each it into 1 byte, hereinafter the new Plaintext will be XORed with a rotated key. To produce more advanced cipher.
Strengthening character education with the implementation of machine learning in the millennial era industrial revolution 4.0

Abstract Education is a part that cannot be separated from human life. There is a relationship between education and prosperity and patterns of human life. In the context of human life, education has a significant role in aspects of social, economic, environmental, political and security safeguards. In terms of welfare, education has a large influence. One education actor who plays a very important role is the teacher, who will teach and become an example for his students. And things that should not be eroded by the development of the age are the cultivation of good character in educating students, including those that must be prevented are acts of violence against students maybe it can happen in the world of education, either by the teacher or fellow students. In this study a web-based Expert System will be designed using the Forward Chaining method. Forward Chaining is a search method or a forward tracking technique with information and merging rules to produce conclusions. With this system the teachers can conduct online consultations that will be applied in machine learning in the learning process, so that the teachers can find out whether their actions in the teaching and learning process are in accordance with the ethics of an educator.
Initial Weights Optimization using Enhanced Step Size Firefly Algorithm for Feed Forward Neural Network applied to Spam Detection

Spams are unsolicited and unnecessary messages which may contain harmful codes or links for activation of malicious viruses and spywares. Increasing popularity of social networks attracts the spammers to perform malicious activities in social networks. So an efficient spam detection method is necessary for social networks. In this paper, feed forward neural network with back propagation based spam detection model is proposed. The quality of the learning process is improved by tuning initial weights of feed forward neural network using proposed enhanced step size firefly algorithm which reduces the time for finding optimal weights during the learning process. The model is applied for twitter dataset and the experimental results show that, the proposed model performs well in terms of accuracy and detection rate and has lower false positive rate.
Evaluating Cybersecurity-Related Competences through Serious Games

This thesis looks at ways how to use serious games to evaluate cybersecurity-related competences. Various case studies show how competency-driven design of technical exercises can help to target specific competencies in a scalable manner.
Monthly Rainfall Prediction Using Statistical Downscaling with Combination of Grid Boxes and Adaptive Neuro Fuzzy and Inference System in Lombok

Abstract Lombok is an island in Indonesia that has more people live in this area. Flood is a natural disaster that cause severe impact on society. To manage the risk of natural disaster, seasonal prediction of rainfall for early warning system are needed. However, prediction is difficult to predict due to El Niño and La Niña. Seasonal prediction of rainfall using Global Circulation Model (GCM) is useful to capture rainfall variability, but has a lack information because it has coarse of grid resolution (more than 200 kilometers). This model cannot provide in the local area so statistical downscaling model is used to get detail information. To optimize the result of prediction from global model, a method to capture the extreme condition is needed. Taking a best predictor that will be used to predict the rainfall is done to get the high performance of model used Singular Value Decomposition (SVD). ANFIS (Adaptive Neuro Fuzzy and Inference System) is a model prediction to capture the rainfall variability. Predictor is chosen based on the physical condition of atmosphere and ocean that have impact on Lombok Region. Selected area of predictor (atmospheric variable) are grid boxes in the Maritime Continent (80°E - 150°E and 12.5°N – 12.5°S) and Nusa Tenggara (105°E - 120°E, 10°S - 0). Eight variable predictors are used for prediction, they are air temperature at 2 m (T2M), geopotential height at 500 mb (Z500), zonal and meridional wind at 850 mb (U850 and V850) and at 200 mb (U200 and V200), sea level pressure (SLP), and air temperature at 850 millibar (T850). Both predictor variables (grid box combination) are used to predict for lead time one month. The result of research shows that rainfall prediction can capture the rainfall variability (correlation 0.70) with RMSE (Root Mean Square Error) is 69.
Prediction of surface tension of branched alkanes using ANN-MLP and ANN-RBF: application to bitumen recovery

The viscosity of bitumen is extremely high at ambient temperature and in order to produce and transport the bitumen, it is necessary to reduce its viscosity. In this regard various n-alkane with different surface tension dilutes bitumen. This study features the application of artificial neural network for prediction of surface tension of branched alkanes. Modeling results showed that the both models are accurate and effective in prediction of surface tension of branched alkanes. However, the results were compared with experimental data and it was found that the estimated surface tension by ANN-MLP is more accurate than radial basis function network.
The Formation of the Ability to Work with Information in the Study of Elementary Mathematics

The article substantiates the possibility of forming universal educational actions that characterize the information literacy of a primary schoolchild. The following actions are considered: data search in a mathematical task, presentation of information in a given or independently selected form, interpretation of information obtained during the solution in the form of an answer, conclusion or explanation. The pedagogical conditions for the successful development of a primary school student’s ability to work with information using the means of the subject “Mathematics” are described: highlighting common skills and actions for mathematical and informational literacy, using group work to motivate children to learn, maximize inclusion in it, etc.
A Dynamic Risk Assessment (DRA) Methodology for High Impact Low Probability (HILP) Security Risks

This paper proposes a Dynamic Risk Assessment (DRA) methodology applicable to the so-called High Impact Low Probability (HILP) security risks which, by their very nature, are difficult to identify or occur only infrequently. DRA is based on the processing of Weak Signals (WSs) to protect critical infrastructures and soft targets against HILP security risks before they materialise. DRA allows to rank WSs according to the reliability and credibility of the sources and to correlate them to obtain threat precursors. Experimental results have shown that DRA is effective and helps suppressing irrelevant alerts.
SO-CCA Secure PKE in the Quantum Random Oracle Model or the Quantum Ideal Cipher Model

Selective opening (SO) security is one of the most important securities of public key encryption (PKE) in a multi-user setting. Even though messages and random coins used in some ciphertexts are leaked, SO security guarantees the confidentiality of the other ciphertexts. Actually, it is shown that there exist PKE schemes which meet the standard security such as indistinguishability against chosen ciphertext attacks (IND-CCA security) but do not meet SO security against chosen ciphertext attacks. Hence, it is important to consider SO security in the multi-user setting. On the other hand, many researchers have studied cryptosystems in the security model where adversaries can submit quantum superposition queries (i.e., quantum queries) to oracles. In particular, IND-CCA secure PKE and KEM schemes in the quantum random oracle model have been intensively studied so far. In this paper, we show that two kinds of constructions of hybrid encryption schemes meet simulation-based SO security against chosen ciphertext attacks (SIM-SO-CCA security) in the quantum random oracle model or the quantum ideal cipher model. The first scheme is constructed from any IND-CCA secure KEM and any simulatable data encapsulation mechanism (DEM). The second one is constructed from any IND-CCA secure KEM based on Fujisaki-Okamoto transformation and any strongly unforgetable message authentication code (MAC). We can apply any IND-CCA secure KEM scheme to the first one if the underlying DEM scheme meets simulatability, whereas we can apply any DEM scheme meeting integrity to the second one if the underlying KEM is based on Fujisaki-Okamoto transformation.