Reviewerly/exHarmony huggingface dataset:
Natural Reweighted Wake–Sleep

Helmholtz Machines (HMs) are a class of generative models composed of two Sigmoid Belief Networks (SBNs), acting respectively as an encoder and a decoder. These models are commonly trained using a two-step optimization algorithm called Wake-Sleep (WS) and more recently by improved versions, such as Reweighted Wake-Sleep (RWS) and Bidirectional Helmholtz Machines (BiHM). The locality of the connections in an SBN induces sparsity in the Fisher Information Matrices associated to the probabilistic models, in the form of a finely-grained block-diagonal structure. In this paper we exploit this property to efficiently train SBNs and HMs using the natural gradient. We present a novel algorithm, called Natural Reweighted Wake-Sleep (NRWS), that corresponds to the geometric adaptation of its standard version. In a similar manner, we also introduce Natural Bidirectional Helmholtz Machine (NBiHM). Differently from previous work, we will show how for HMs the natural gradient can be efficiently computed without the need of introducing any approximation in the structure of the Fisher information matrix. The experiments performed on standard datasets from the literature show a consistent improvement of NRWS and NBiHM not only with respect to their non-geometric baselines but also with respect to state-of-the-art training algorithms for HMs. The improvement is quantified both in terms of speed of convergence as well as value of the log-likelihood reached after training.
Project activities of bachelor students of a pedagogical university as a condition for preparing schoolchildren’s research activities

The paper discusses current issues of training a professional teacher, a successful organizer of schoolchildrens research activities. The material is presented in terms of new standards. The author discusses innovative forms of educational process organization at university and school the creation of a single educational space based on the principles of science and education integration. The main condition for schoolchildrens research potential development and successful teachers development is the project activity of students and schoolchildren in the framework of cooperation. A structural model of network interaction between the Minin Nizhny Novgorod State Pedagogical University, schools № 151, 129, 173 of Nizhny Novgorod, the Immanuel Kant Baltic Federal University (Kaliningrad) and the A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences (Moscow) has been developed. This model is a key factor contributing to the solution of the problem of high-quality training of a prospective teacher majoring in Biology who will be able to organize students research activities and develop their creative activity. The experience of the development and testing of various joint scientific, social and creative projects is shown. The data of the experiment are presented, which speak about the success of the events held as part of the implementation of the project technology.
IMPLEMENTASI KEBIJAKAN PENGELOLAAN ARSIP DINAMIS DI PT. KONSTRINDO PUTRA PERKASA PALU PROVINSI SULAWESI TENGAH

This research aims to find out the Implementation of Dynamic Archieve Management Policies at PT. Konstrindo Putra Perkasa in Palu City, Central Sulawesi. The usefulnes of this research is theoretical and practical. In the Literate review explains the concept of Public Policy and the Concept Archive Management Policy. The flow of thought by the theory of policy implementation Edward III which includes the factors of communication, disposition, resources and bureaucratic structure. Research white qualitative method, PT. Konstrindo Putra Perkasa Research Location in Palu City Central Sulawesi, Research time for the three month, Informants are elements of Leadership and staff. Definition Operational Concept related to the implementation model of the policy. Qualitative data type, and data sources namely Secondary data and Primary Data. The Discussion explained,explicity about the Implementation of Dynamic Archive Management Policy at PT. Konstrindo Putra Perkasa at PT. Konstrindo Putra Perkasa in Palu city, Central Sulawesi and concluded that the Dynamic Archive Management Policy at PT. Konstrindo Putra Perkasa In Palu Central Sulawesi not maximal was caused lack of human resources manager archives, facilities that have not been in accordance with aplicable standars and archival rules, and lack of socialization from the relevant goverment.
‘Uh-oh Spaghetti-oh’: When Successful Genetic and Evolutionary Feature Selection Makes You More Susceptible to Adversarial Authorship Attacks

Feature selection is a technique used to reduce an original set of features to a subset containing the most salient features. Reducing the feature set to the most significant subset of features typically results in an increase in the overall accuracy of a system. It has been shown that in some cases, the use of feature selection can make an underlying system susceptible to adversarial attacks. In this paper, we investigate the susceptibility of a feature selection-based Authorship Attribution System (AAS) to adversarial authorship attacks. The AAS studied is an instance of a Linear Support Vector Machine (LSVM). The feature selection algorithm used is an instance of Genetic & Evolutionary Feature Selection (GEFeS)In order to evaluate the GEFeS+LSVM-based AAS, we use three adversarial authorship masking techniques to generate adversarial texts to attack the AAS. Our results show that in some cases the GEFeS+LSVM-based AAS is more susceptible to adversarial authorship attacks. We provide a simple measurement to determine whether the use of GEFeS is beneficial or detrimental to a LSVM-based AAS.
BOOSTING ENTREPRENEURSHIP IN NIGERIA: THE NEED FOR A NEW MANAGEMENT APPROACH

Developing nations obviously need ever-improving entrepreneurial activities to keep afloat given the dynamics of the global environment. This study examined the need for a new approach to entrepreneurship In Nigeria if its related activities must receive the necessary boost. Data was obtained from secondary sources including books, journals magazines, newspaper internet, etc. The theory of entrepreneurial growth by Mahajan (1970) was adopted as its theoretical framework while data analysis was by the mode of content analysis. Result revealed that a dynamic approach which is capable of evolving changes in line with the global business trends is required in Nigeria if entrepreneurship must be given the necessary boost. The paper recommended that government should give serious consideration to such an approach.
Facial Expression Generating Method to Express Suppressed Positive Emotion Considering Involuntary of Facial Actions – A Case Study on Tsundere –

In order to convey user’s feeling through his/her avatar on remote communication, not only verbal information but also non-verbal information such as tone of voice, facial expression, and gesture are important. Although some studies propose methods to express basic emotions on avatar, no method has been established to create facial animation that expresses complicated emotional states like “happy but embarrassed” yet. This paper proposes a method to create facial animation expressing complicated emotional state by combining involuntary facial actions of suppressed real emotion and voluntary facial actions of suppressing fake emotion. The proposed method is explained in a case of “Tsundere” that consists of real happiness and fake calm/anger. 18 facial animations were created and evaluated by Sheffé’s method. The experimental results revealed that blushing, an involuntary action for happy, enhanced impression that the avatar sincerely felt happy. On the contrary, smiling faces without involuntary blushing gave impression that the avatar pretended to be happy with fake smile. It indicates that the proposed method that expresses real emotion by involuntary action unit can express real emotion selectively.
Challenges in Adoption of Secure Digitization of Graduate Assessments: Scope for Blockchain Technologies

Blockchain technology finds variety of applications in everyday life. It is also capable of disrupting the implications on activities which were founded on time-stamped record keeping of titles of ownership. In education, blockchain technology shall disrupt activities such as the qualifications, licensing and accreditation, management of student records, IPR management and payments. Hence, blockchain technology-based products or services are significantly different from previous Internet-based commercial developments. Also blockchain is catching up interest in the education sector. However, the stakeholders within education are largely unaware of the social advantages and potential of blockchain technology. Within the educational sphere, the adoption of blockchain technology in the replacement of paper-based assessments has both advantages and challenges. This paper attempts to explore the challenges faced by faculty and graduate students in the adoption of digitized assessments and technical issues in achieving secured system. By identifying the challenges in implementation, it will be easy to achieve successful adoption of digitized assessments in a large scale.
PETA: Privacy Enabled Task Allocation

Service organizations need to comply with numerous data regulations to protect and preserve their customers' privacy. Any misuse of data and privacy breach can affect the organizations' reputation and brand image. In service delivery scenarios, such as IT support help desk, agents need to access customer data to serve them effectively. This data often includes sensitive and personally identifiable information of the customer. While some amount of data exposure is needed to serve a customer, however, exposure to more data than required could be a threat to an individual's privacy. Hence, organizations need to design methodologies to ensure customer privacy while achieving minimal cost of operations.In this paper, we propose the Privacy Enabled Task Allocation (PETA) model for assigning customer requests to agents so that the overall cost of operations and data exposure is minimal. Data exposure is minimized by restricting the amount of data exposure per agent and by regulating the assignment of tasks. The PETA problem is modelled as an integer linear program, which is NP-hard. To solve this combinatorial hard problem, we have designed an allocation algorithm based on the linear programming relaxation for finding a quick feasible solution.
Thesaurus tool for analysing the semantic compatibility of educational texts

Abstract The developed software is designed to analyze the semantic compatibility of educational text materials. This need is due to the existing negative trends noted by scientists (didactics, psychologists, neuroscientists) in the mechanism of information perception in the learning process of the modern generation of students. The way to level this tendency in the educational process is to take into account the unconscious patterns of information perception, associated with a gradual increase in its complexity. Semantic compatibility in the developed program is assessed by comparing the thesauri of educational materials, which allows in the future to influence the required degree of increase in their novelty (and, as a consequence, complexity). The work algorithm is formed taking into account the specific variable features of the Russian language. The proposed analytical tool is intended for didactic use, but due to the flexibility of the action algorithms provided by the program, it allows the use of the software product for the analysis of texts for other purposes, for which compatibility is of practical importance.
Regulation of the Institute of Higher Education in Modern Conditions: Risks of Personalization

The paper reveals the features of the functioning of the institution of education in the context of transformation, instability and risks of personalization. Modern circumstances confirm the inevitability of planned and coordinated innovative activities of participants in the educational process at all stages in the higher education system. The student must clearly understand the purpose of educational activities, analyze and assess their abilities in obtaining education, understand the degree of individual responsibility to themselves, relatives and society for the learning outcomes. However, the mass character of education and the diversity of levels of basic training, intellectual capabilities, and personality traits create additional difficulties in organizing a personalized educational process. An attempt made in this work to generalize and evaluate such experience will allow us to identify the positive components and identify the risks of personalization in order to minimize them in the future to increase the effectiveness of professional training.
Comparison of three artificial neural networks for predict the electrodeposition of nano-silver film

The back-propagation neural network (BP), genetic algorithm based on BP (GA-BP), and extreme learning machine (ELM) were established to predict the glossiness of silver film and current efficiency for the electrodeposition of nano-silver film in this paper. The artificial neural networks (ANNs) were built to predict the results and contrast with experimental results. The prediction results demonstrated that GA-BP exhibited a relatively higher accuracy than simple BP. ELM demonstrated an efficient rate and the time required was far less than BP and GA-BP, which also had a high accuracy if the sample data were sufficient. GA-BP only needs a few sample data as the basis to obtain high accuracy, which has a low demand for sample data. In conclusion, for the electrodeposition of nano-silver film, the order of the accuracy of learning process is ELM > GA-BP > BP, the order of analogical ability is GA-BP ≈ BP > ELM and the order of time required is GA-BP > BP > ELM. Mean impact value (MIV) analysis was utilized to explore the impact of each parameter for three kinds of ANNs. The results display that glossiness, and current efficiency are mainly controlled by current density and substrate glossiness, but which parameter plays the crucial role is not manifest.
Parallel Image Scaling Density-based Clustering

Clustering is one of the most important methods to discover the intrinsic grouping in a set of unlabeled data. As ways of getting data are more various and easier, the amount of data processed is increasing exponentially and the data is more likely to be located at different clients. Traditional clustering methods cannot process the large dataset one time due to the limit of memories. In this paper, an Image Scaling Density-based Clustering (ISDC) algorithm is proposed. ISDC can process data by a client alone as well as process in parallel by several clients to deal with data located at different clients. The ISDC algorithm does not need any parameters to be designated manually. The parameters are determined by the algorithm based on the statistical features of dataset. In Parallel ISDC or PISDC, each data block located at different client is clustered alone to form intermediate clusters. By border detection algorithm, representative clusters are formed by the points that are at the edge of intermediate clusters. Then, in global clustering, representative clusters from all clients are merged by the server. The border detection algorithm reduces the communication cost between clients and the server, as well as increases the efficiency of global clustering. At last, the server feeds back the clustering information to clients to complete clustering. Our experimental results verified the effectiveness and efficiency of PISDC and ISDC.
System of Collection and Analysis Event Log from Sources under Control of Windows Operating System

The purpose of this work is to implement a universal system for collecting and analyzing event logs from sources that use the Windows operating system. The authors use event-forwarding technology to collect data from logs. Security information and event management detects incidents from received events. The authors analyze existing methods for transmitting event log entries from sources running the Windows operating system. This article describes in detail how to connect event sources running on the Windows operating system to the event collector without connecting to a domain controller. Event sources are authenticated using certificates created by the event collector. The authors suggest a scheme for connecting the event collector to security information and event management. Security information and event management must meet the requirements for use in conjunction with event forwarding technology. The authors of the article demonstrate the scheme of the test stand and the result of testing the event forwarding technology.
Engineering Or Not Engineering? That Is Still The Question

In this paper, we present the results of an inquiry on security vulnerabilities in software, aiming also to contribute to a critical reflection about Software Engineering and, as consequence, to System Engineering as well. Data was gathered from a sample of security analysis done between January/ 2013 and June/ 2018 with the aid of penetration tests (pentests), by a cyberintelligence company that operates in a dozen countries (Tempest Security Intelligence). This sample was analyzed from a quantitative and qualitative perspective. Results in the sample suggest that: a) security vulnerabilities in software are found in the three layers of an information system (infrastructure, communications and application); b) a determined vulnerability may appear more than once in a system, resulting in points of vulnerabilities; c) it is huge the amount of points of vulnerabilities found in the period (23721 points of vulnerabilities in 1046 security analysis done with pentests); d) although absolute numbers indicate discrepancies in the distribution of points of security vulnerabilities in systems from different economic segments (Traditional Commerce, E-commerce, Industry, Energy, Finances, Services and others), normalized data reveal the opposite; e) there is no huge difference in normalized quantities of points of vulnerabilities found in the economic segments considered, even Energy and Industry stand out in this criterion; f) isolated numbers of points of vulnerabilities were elevated in Finances because, as a consequence of a natural concern in this segment, more pentests were done in it; g) the more pentests are done, the more points of vulnerabilities are identified; h) in the application layer (web application), the top 9 vulnerabilities found according to their severity and frequency are Cross-Site Scripting (XSS), Failures in Access Control, Failures in Authentication, Sensitive Data Exposure, Failures in Session Management, Remote Script Inclusion, Missing HTTPS, SQL Injection and Failure in the Upload Mechanism; i) the picture exposed by the data related to vulnerabilities in applications is compatible with the OWASP Top 10 Application Security Risks; j) the amount of security vulnerabilities and the insecurity of softwares are independent of niche, being, probably, linked to the Engineering involved in the construction of information systems; k) considered the 23721 points of security vulnerabilities identified in this study and, consequently, the evident failure in the development of the softwares analyzed, it may be inappropriate saying that there is, today, a “Software Engineering”; l) even, since the first time the term “Software Engineering” was used (1968), development methods had been created, new languages were conceived and new paradigms emerged, there is, in fact, no real Engineering related to software; m) if isolated efforts have not resulted in a mature new Engineering, the key for a change may involve integration and reuniting efforts, as well as thinking globally and not about isolated disciplines in Computer Science, after all Science is simply one.
Real-time Object Tracking Based on Improved Adversarial Learning

With the development of deep learning and the emergence of massive video data, object tracking has great application prospects in many fields. However, most tracking algorithms can hardly get top performance with real-time speed. In this paper, we improved tracking model based on adversarial learning and to accelerate feature extraction we proposed an efficient and accurate method. We also present a Precise ROI Pooling (PrROIPooling) based algorithm for extracting more accurate representations of targets. Furthermore, a novel regularization term is defined to ensure the similarity between the generated features and the real features. Finally, the improved objective function with modulating factors is designed to handle the problem of imbalance in the number of positive and negative samples. Extensive experiments on three datasets have demonstrated our effectiveness and achieved competitive results compared with state-of-the-art methods.
Information Security Policies Based on the Behavior of IT Users in the Microfinance Sector of Lambayeque-Peru

Financial institutions in Peru are obliged to protect information through security systems that are generally not effective in identifying, evaluating and treating the risks resulting from internal threats, defined as an employee who intentionally or not, accesses the information to negatively affect its confidentiality, integrity or availability. The study developed a conceptual model identifies and evaluates the main factors that influence the behaviors, intentional or not, of IT users in organizations of the microfinance sector of Lambayeque Peru. The evaluated factors are related to the behavior, the influence of the environment and the perception of the control established, to identify in advance the possible risk scenarios that later become an internal threat. This work is based on the theories of planned behavior, reasoned action and deterrence. A survey prepared by the researchers and validated using the Conbach alpha statistic was applied to a sample of 110 IT users, belonging to eight microfinance entities. Through the correlation analysis, it was obtained that the factors related to the intentional behavior obtain a correlation coefficient of 0.695 with respect to the compliance of the information security policies, while the factors related to the non-intentional behavior obtain a coefficient of correlation of 0.564. The model explains 63.9% of the behavior with the identified factors.
Artificial Intelligence in the Game to Respond Emotion Using Fuzzy Text and Logic

Emotions play an important role in everyday life when it comes to human communication. Forms of emotion such as pleasure, sadness, anger, fear, etc. have long been recognized and are important features of human behavior, but the application of emotions has not been commonly used in human and computer interactions. Because research about emotions is a complicated process because it can change dynamically. Therefore, research related to text-based emotions is made in the form of text which is relatively simple compared to other forms such as visuals or sounds and compared to images or views on the video. The game as entertainment media has developed rapidly along with technological developments. Artificial intelligence is one element that plays an important role in a game. For artificial intelligence, game elements can act as natural as possible as manifestations of human behavior. This study will be built in the implementation of artificial intelligence in games where one of the elements of the game, NPC (Non-Playable Character) will recognize the emotions of the Indonesian text while at the same time reacting to actions by emotional characters. The approach used in this study is to identify the text as a determinant of the emotional character in the text and fuzzy logic as a determinant of NPC actions according to the type of emotion.