Reviewerly/exHarmony huggingface dataset:
Untraceability of Partial Blind and Blind Signature Schemes

Blind Signature is employed in privacy related protocols, where signer signs on a blinded message. It provides anonymity in various cryptographic applications such as electronic voting, digital cash system etc. Concerning the need for quantum resistant scheme, Ruckert and Tian et al. proposed the lattice based blind signature and partial blind signature schemes respectively. But, both the schemes left out one of the security requirement of a blind i.e. Untraceability, where the signer can’t link the blinded signature with a valid message-signature pair even when it is revealed in public. In this article, we propose an attack on the untracebility property of both the schemes. The proposed attack opens the door for researchers to work on quantum resistant untraceable blind signature.
Research on Temperature Control System of Desktop 3D Printer Based on Fuzzy Adaptive

In the printing process of desktop 3D printer, the printing consumables is to be heated and melted, and the layers of the extrusion layer are stacked. The heating temperature control system has the characteristics of nonlinearity, large inertia and large hysteresis, which it is some disadvantages for making the heating process take more time and inaccurating temperature control. Aiming at the above problems, a fuzzy adaptive desktop 3D printer temperature control strategy is proposed in this paper. The ARM LPC1768 high-performance microcontroller is combined with the fuzzy adaptive feature to implement temperature control fastly and precisly, and the temperature simulation model of the control system is established by Matlab/Simulink. The experimental results show that the fuzzy adaptive PID controller has the advantages of small overshoot, good temperature tracking performance, fast dynamic response and high reliability compared with the conventional PID control method. It is optimal for the temperature control of the desktop 3D printer.
Author Identification for Marathi Language

This is era of new technology; most of information is collected from internet, web sites
Technical Aspects of Web Design

The quality of a website application reflects not only what is seen by the user (the front-end) but also the technical processes responsible for the functioning of a website (the back-end). HTML represents a language that is used to specify the structure and form of information on a website. The important aspect of HTML is that all the changes made in the code are subsequently interpreted by a browser and displayed on the user’s screen. Nowadays, websites can be viewed on a variety of portable devices with different levels of Internet access which may affect the ways information is represented. In addition, automatic personalization may alter the website features according to user preferences. Moreover, technical aspects such as the structure of the HTML code, loading speed or the use of keywords contribute to the visibility of the website and its placement in the search results displayed by search engines. In this chapter, we demonstrate the impacts of keyword and traffic analysis using a dataset about website traffic prior and after a search engine optimization. The effects of automatic personalization of the website features are assessed by comparing the user behavior and revenues generated by tailored and non-tailored content.
Consolidating Hash Power in Blockchain Shards with a Forest

Sharding has been a highly expected solution for the blockchain scalability problem. But with computation power of honest miners (or stakes in PoS based systems) distributed in shards, it becomes easier for attackers to attack a single shard. In this research, we propose a new consensus algorithm, Greedy Observed Largest Forest (GOLF), aiming to consolidate distributed hash power in all shards to make attacking a single shard as hard as attacking the entire system.
Evaluating the Cache Side Channel Attacks Against ECDSA

Various attacks are proposed against different ECDSA implementations: the key-related data are acquired through cache side channels, and then processed to recover the private key. For each cache side channel attack, the requirements of the data qualified for sequent processing vary greatly, and the success probability of private key recovery relies on both the acquired data and the parameters of data processing. So it is difficult to tell, for a certain ECDSA implementation, (a) how many signatures does a cache side channel attack need to recover the private key? or which attack performs the best? and (b) what kind of threat level exists due to potential side channel attacks, if the ECDSA implementation runs for a number of signatures on an unprotected system with cache side channels? Currently, there is no quantitative metric to fairly answer the questions. Such a metric to evaluate cache side channel attacks, will provide a reference for the adversaries to choose the suitable attack, and also for the defenders to set up protections for the certain ECDSA implementation (e.g., updating the private key after it has been used for a certain number of signatures). In this paper, we design an evaluation approach to quantitatively compare the cache side channel attacks against ECDSA. The expected minimum number of signatures needed for at least one successful private key recovery, is proposed as the metric, and this metric considers both the data requirements and the success probability. We apply the approach to evaluate various cache side channel attacks against ECDSA. By calculating the metric, we obtain (a) for each attack, the optimal parameters with the minimum number of signatures needed, and (b) for each ECDSA implementation, the minimum number of signatures that will be enough for at least one successful private key recovery of some cache side channel attacks.
Problems of Humanizing Higher Education in Today's Russian Society: Factors, Main Directions and Methods

The article examines the factors, main directions, problems and methods of humanizing education in its various subsystems. The study allows us to outline ways to further organize and flesh out a very important, complex and necessary process of humanizing higher education in our country, rationalizing it and improving efficiency.
Study on Fault Diagnosis for Bearing Based on Hierarchical Extreme Learning Machine

Rolling bearings are widely used in mechanical systems but have a high damage rate. Its running state is related to the production safety and stable operation of various industries. Nowadays, scholars have applied so many signal processing methods such as differential entropy, energy entropy, and empirical mode decomposition methods in conjunction with various algorithms which likes particle swarms and neural networks to implement pattern classification in the process of the vibration signals of rolling bearings (Qin et al. in Mech Des Manuf 08:11–14, 2018 [1]). On this basis of it, this paper presents the variational mode decomposition–singular value decomposition (VMD-SVD) method based on the previous studies by other scholars with good verification effect that is developed and used to extract the characteristics of different IMF components under different operating conditions in order to establish the characteristic matrix. The latest and better effect of hierarchical extreme learning machine (H-ELM) is applied for training and verification. Besides, by comparing with the traditional ELM method, it verifies its superiority in rolling bearing fault diagnosis.
Research of Turnout Fault Diagnosis Method Based on Qualitative Trend Analysis

The turnout is connected to different tracks and usually installed between two or more strands, not only is responsible for switching track line but also ensures operation safety. It is of great practical significance to study the fault diagnosis methods. The fault diagnosis method based on qualitative trend analysis is to use the interval semi-division method to extract the trend of different state signals, and match the diagnostic signal with it to obtain the result. The experimental results show that the presented method has good accuracy.
Long Live the IEEE Transactions on Artificial Intelligence

Presents the President’s message for this issue of the publication.
Special Issue: Selected Papers from IEEE ICASI 2019

The fifth IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019 [...]
ANALISIS FAKTOR-FAKTOR YANG DIPERTIMBANGKAN SISWA DALAM PENGAMBILAN KEPUTUSAN SEKOLAH DI SMK NASIONAL MOJOSARI

The purpose of this study was to determine what factors influenced students choosing schools at the National Vocational School in Mojosari. With the limitation of the problem in this study, the students who attend the Mojosari National Vocational Schools in grades 2 and 3. Vocational High Schools (Vocational High Schools) are a formal educational institution that organizes vocational education from secondary/junior high school. The method in this research uses quantitative methods. The population in this study was all students in grade 2 and 3 who attended the National Vocational School in Mojosari. To determine the sample using an opinion (Maholtra, 2006:291) that is 4 or 5 times the number of variables known in this study the variables are 42 x 4 = 168, so the number of samples from this study amounted to 168 respondents. The technique used is proportionate stratified random sampling, this technique is used for populations that have proportional and non-homogeneous stratified members/elements (Sugiyono, 2016:82). Sources of data in this study are primary, secondary and documentation data. For the results of factor analysis, the KMO (Kaisser-Meyer-Olkin) measure of sampling adequacy of 0.706 is greater than 0.5 and there are 42 variables whose values are above 0.5. For the factors formed there are 15 factors out of 42 variables. Of the 15 factors formed, the most influential were school product factors with a variance value of 15,885.
Principle-to-Program: Neural Methods for Similar Question Retrieval in Online Communities

Similar question retrieval is a challenge due to lexical gap between query and candidates in archive and is very different from traditional IR methods for duplicate detection, paraphrase identification and semantic equivalence. This tutorial covers recent deep learning techniques which overcome feature engineering issues with existing approaches based on translation models and latent topics. Hands-on proposal thus will introduce each concept from end user (e.g., question-answer pairs) and technique (e.g., attention) perspectives, present state of the art methods and a walkthrough of programs executed on Jupyter notebook using real-world datasets demonstrating principles introduced.
Issues related to personal and social self-development of academic staff members of higher education institutions in today's Russia

The issues addressed in the article are of particular relevance due to the growing role of teachers of higher education institutions in the modern society. The article is dedicated to the current issues of self-development of teachers and is aimed to identify the main reasons for their poor social and personal self-development. The most important research method used by the authors was the pedagogic experiment, including such particular empirical methods as monitoring, tests, surveys, questionnaires, interviews, self-assessment and psychological diagnostics. As a result of the study, it was found out that teachers' leisure time is not properly organised, therefore they have no opportunities for rehabilitation and recreation in their free time, which considerably reduces effectiveness of their personal self-development. The article describes a set of measures aimed to enhance the effectiveness of teachers' self-development through the organization of cultural and creative associations in higher education institutions, including four stages and six spheres of activity that can be implemented in such cultural and creative associations. Materials of this article may be useful for the management of higher education institutions and department heads, advanced training centres for higher education professionals and for all academic staff members.
Penerapan Metode ELECTRE II Dalam Menentukan Faktor Yang Mempengaruhi Prestasi Belajar Mahasiswa Untuk Meningkatkan Nilai IPK

One of the goals of the teaching and learning process is changes in behavior both aspects of knowledge (cognitive), attitude (effective),and psychomotor aspects. Learning achievement achieved by students is essentialy a reflection of learning efforts. In general,the better the learning effort, the better the achievement will be,of course this is inseparable from the factor that influnce it, among others, motivation of parents’ level of education, ways of learning taught by lecturers, concentration. Hower most students lack learning achievement so the IPK value decreases. Whereas if the IPK is high the it will be very easy to determine the job. Student learning achievement and to increase the IPK is strongly influenced by a factor for that it requires a study to increase the value of I. Realizedby making a decision support system in determining the factors that influence student achievement to increase the IPK score.
Adaptive multilayer T-S fuzzy controller for nonlinear SISO system optimized by differential evolution algorithm

In this paper, the authors propose a novel adaptive multilayer T-S fuzzy controller (AMTFC) with an optimized soft computing algorithm for a class of robust control uncertain nonlinear SISO systems. First, a new multilayer T-S fuzzy was created by combined multiple simple T-S fuzzy models with a sum function in the output. The multi-layer fuzzy model used in nonlinear identification has many advantages over conventional fuzzy models, but it cannot be created by the writer's experience or the trial and error method. It can only be created using an optimization algorithm. Then the parameters of the multilayer fuzzy model are optimized by the differential evolution DE algorithm is used to offline identify the nonlinear inverse system with uncertain parameters. The trained model was validated by a different dataset from the training dataset to guarantee the convergence of the training algorithm. Second, for robustly and adaptive purposes, the authors have proposed an additional adaptive fuzzy model based on Lyapunov stability theory combined with the optimized multilayer fuzzy. The adaptive fuzzy based on the sliding mode surface is designed to guarantee that the closed-loop system is asymptotically stable has been proved base on a Lyapunov stability theory. Furthermore, simulation tests are performed in the Matlab/Simulink environment that controlling a water level of a coupled tank with uncertain parameters are given to illustrate the effectiveness of the proposed control scheme. The proposed control algorithm is implemented in simulation with many different control parameters, and it is also compared with the conventional adaptive control algorithm and inverse controller. The simulation results also show the superior of the proposed controller than an adaptive fuzzy control or inverse controller when using the least mean square error standard.
Web-Based Learning: A Strategy of Teaching Gender Violence

Gender-based violence has been widely recognized as a cross-cutting issue impacting the lives of victims of diverse dimensions, spreading to culture, economy, education, health, livelihood, psychology and political participation. Thus, there arises a need to raise capacity and commitment to build programmes and to take random use of Internet to target the eradication of gender-based violence by developing a new movement of gender equality. Web-based learning techniques have served immense help in educating the womenfolk regarding gender-based violence. Social media has taken up many connotations in the present day as it has opened up many online platforms for people where they not only interact but also actively participate in larger discussions of general or social issues. It is noteworthy that the widened social circle of people has made access to interaction with diversely opinionated people and discussion in online spaces. But all the social platforms are not bereft of its pitfalls. With juxtaposition of different kinds of people with one another, there is a considerable reduction of space of tolerance for opposing opinions. The gender-based abuse, violence in online spaces ranging from heckling to harassment to stalking and threats (specially trolling, body shaming, cyberbullying, etc.) are the common forms of abuse that the online portal throws at the users. The paper specially highlights the support services and the constructive aid of the online social networking services in terms of educating and eradicating the gender-based violence.
METHODOLOGICAL APPROACHES TO PROFESSIONAL TRAINING OF FUTURE PRACTICAL PSYCHOLOGISTS

The article argues that the professional training of future practical psychologists involves taking into account different methodological approaches to the organization of the educational process in institutions of higher education, which enrich the methodological consciousness of the specialist by knowledge of professionally oriented sciences and contribute to its adaptation to the specifics of higher education. The justification of methodological approaches has allowed to establish causal relationships between pedagogical phenomena and processes and to determine the most important of them for effective solution of problems that take place in the training of practical psychologists.&#x0D; The main methodological approaches, which are followed in the professional training of students-psychologists, include system-scientific, synergistic, thesaurus, complex, humanistic, competent, personally oriented, activity, praxeological, axiological, acmeological and others. It is proved that approaches, structured in this way, enabled the researcher-teacher to understand mentally in the organization of their own professional activity and to practically realize the educational actions and pedagogical actions in teaching the students; contributed to the definition of the professional training of practical psychologists and the most holistic acquisition of objectively impartial, professionally relevant knowledge, skills and competences by students. Within these approaches, the focuses are accented on the importance of reconstitution in the contest of the education of holistic image of human as biopsychological system and active-creative possibilities of student with his desire to realize himself on the principles of love to the person and in the public interests.
Random distributions via Sequential Quantile Array

We propose a method to generate random distributions with known quantile distribution, or, more generally, with known distribution for some form of generalized quantile.The method takes inspiration from the random Sequential Barycenter Array distributions (SBA) proposed by Hill and Monticino (1998) which generates a Random Probability Measure (RPM) with known expected value.We define the Sequential Quantile Array (SQA) and show how to generate a random SQA from which we can derive RPMs.The distribution of the generated SQA-RPM can have full support and the RPMs can be both discrete, continuous and differentiable.We face also the problem of the efficient implementation of the procedure that ensures that the approximation of the SQA-RPM by a finite number of steps stays close to the SQA-RPM obtained theoretically by the procedure.Finally, we compare SQA-RPMs with similar approaches as Polya Tree.
CHARACTERISTIC OF A STUDENT IN EXPERIMENTAL PEDAGOGY BY O. NECHAEV AND G. ROSSOLIMO

In the article, based on the analysis of the works of scientists – the representatives of experimental pedagogy Olexandr Nechaev (1870–1947) and Grigory Rossolimo (1860–1928), their contribution to the development of the problem of the pupil’s profile is highlighted. It has been proved that both scientists paid special attention to this issue, developing it in the following aspects: substantiation of the necessity of studying a pupil by the teacher and improvement of psychological knowledge of the teacher (O. Nechaev); creation of plans for studying the pupil in the form of special questionnaires with detailed recommendations on their use (O. Nechaev, G. Rossolimo), filling out the results of studying the pupil in the form of «psychological profile», which was a graphic representation of the profile (G. Rossolimo). It has been substantiated that, developing a problem of the pupil’s profile, O. Nechaev proceeded from the need to take into account the individual abilities and inclinations of the pupil in the educational process, which could be effectively carried out on the basis of studying the pupil with the subsequent compilation of the pupil’s profile. It has been well-reasoned that relations between scientists were significant in the development of scientific ideas: G. Rossolimo linked the emergence of his method of «psychological profile» directly with the ideas of O. Nechaev. It has been emphasized that the psychological characteristics of various types given by Rossolimo were his contribution to the typology of childhood, along with the typology of P. Lesgaft. These typologies are a significant help to the teacher in the process of learning the pupil and compilation of his profile. It has been emphasized that experimental pedagogy is a scientific phenomenon, the name of which reflects the main method of obtaining empirical knowledge — an experiment that was supposed to guarantee the objectivity of the data obtained, bringing pedagogy to the level of exact sciences; the concept of «experimental pedagogy» is established within the limits of historical–pedagogical discourse as a definition of the scientific phenomenon, characteristic only for the beginning of the XX century.
Data Aggregation for Reducing Training Data in Symbolic Regression

The growing volume of data makes the use of computationally intense machine learning techniques such as symbolic regression with genetic programming more and more impractical. This work discusses methods to reduce the training data and thereby also the runtime of genetic programming. The data is aggregated in a preprocessing step before running the actual machine learning algorithm. K-means clustering and data binning is used for data aggregation and compared with random sampling as the simplest data reduction method. We analyze the achieved speed-up in training and the effects on the trained models’ test accuracy for every method on four real-world data sets. The performance of genetic programming is compared with random forests and linear regression. It is shown, that k-means and random sampling lead to very small loss in test accuracy when the data is reduced down to only 30% of the original data, while the speed-up is proportional to the size of the data set. Binning on the contrary, leads to models with very high test error.
Mytho-Plastics as a Relevant Design Technique

The article analyses mytho-plastics as a design technique appealing to the deepest layers of the human’s psyche: myth, archetype and symbol. The research objective includes developing conceptions by L. B. Pereverzev, the author of this methodology. The paper shows relevance of mytho-plastics, identifies its origins, justifies its efficiency as an educational technology and design technique. The study covers both theoretical and methodological aspects.