Reviewerly/exHarmony huggingface dataset:
Fog Removal Algorithms for Real-Time Video Footage in Smart Cities for Safe Driving

In this chapter, different approaches are presented for removal of fog from video footage taken in moving cars. The methodology uses different approaches, namely dark channel prior, contrast limited adaptive histogram equalization (CLAHE), the combination of two approaches (dark channel prior and CLAHE), and RETINEX algorithm combined with DWT. The algorithms are implemented in MATLAB R2015a. Moreover, the algorithms are compared based on their computational complexity and a visibility metric which is used for computing the CNR of video frames before and after the application of the algorithm. The chapter discusses which algorithm would provide better performance during night fog and daylight fog. Finally, the safe speed of the driver is calculated based on the time complexity of the algorithm used.
Study of Scalability

A system having Scalability is highly desirable since it promises a proportional performance boost subject to the resource increase provided. In this chapter we try to analyze the extent of scalability various cryptographic workloads can offer. We try to optimally map two eSTREAM (ECRYPT (2012) “eSTREAM: The European Network of Excellence in Cryptology (ECRYPT) Stream Cipher Project.” [1]) finalists stream ciphers, i.e., HC-128 (and HC-256) and Salsa20 on modern Graphics Processor Units (GPUs). On NVIDIAs GPUs we used CUDA programming framework to exploit their many-core architecture on which parallel homogeneous threads are executed in a Single Instruction Multiple Thread (SIMT) fashion. Many cryptographic algorithms, especially block ciphers due to their block wise operations, have reportedly gained remarkable performance speedups on GPUs.
Security and Privacy Issues

The overall task of this paper is the contribution to the analysis of the relationship of privacy and security in various sectors. Security and privacy issues are an important paradox that has its adverse effects on the further development of the industries and all other things related to internet. Security and privacy issues apart from the personal ones are always linked to the personal data a person or an individual processes or stores online. Practically, no third person should have access to that potential data, but at times due to poor encrypting and holes in secure programming that data gets leaked and causes moral issues for the society. This paper high lights the issues and the possible causes that leads to such incidents and because of which the customers or the clients have to face discomfort. This paper highlights numerous fields which are open to such privacy leaks and what can be done to prevent and stop them from happening in near future.
Mentor Pattern Identification from Product Usage Logs

A typical software tool for solving complex problems tends to expose a rich set of features to its users. This creates challenges such as new users facing a steep onboarding experience and current users tending to use only a small fraction of the software's features. This paper describes and solves an unsupervised mentor pattern identification problem from product usage logs for softening both challenges. The problem is formulated as identifying a set of users (mentors) that satisfies three mentor qualification metrics: (a) the mentor set is small, (b) every user is close to some mentor as per usage pattern, and (c) every feature has been used by some mentor. The proposed solution models the task as a non-convex variant of an regularized logistic regression problem and develops an alternating minimization style algorithm to solve it. Numerical experiments validate the necessity and effectiveness of mentor identification towards improving the performance of a k-NN based product feature recommendation system for a real-world dataset. Further, t-SNE visuals demonstrate that the proposed algorithm achieves a trade-off that is both quantitatively and qualitatively distinct from alternative approaches to mentor identification such as Maximum Marginal Relevance and K-means.
Verifying Usefulness of Ant Colony Community for Solving Dynamic TSP

The paper describes Ant Colony Communities (ACC) and verifies their usefulness for Dynamic Travelling Salesman Problem (DTSP). DTSP is a version of the classical TSP in which the distance matrix change in time. The ACC consists of a set of separate ant colonies with a server that coordinates their work and sends them cargos of data for processing. The colonies could be distributed over many computers working in a LAN or even over Internet. Such a mode of operation is especially useful for dynamic tasks where solutions must catch up with the changing environment. The ACC is used for the regular ACO and its version designed for dynamic environments: PACO and Immigrant ant colonies. The experiments show that for all types Ant Colonies the introduction of the community boots the performance. The routes are far shorter than in the case of original colonies.
A Framework for Security Management in Cloud Based on Quantum Cryptography

Cloud Computing (CC) and Quantum Computing, both have been interesting areas of research, individually. However, integrating the two can come with mutual benefits for both the fields. Cloud platforms can offer Quantum Computing as a service, but more importantly, they are capable of offering the flexibility, inherent in architecture, to accommodate new developments in Quantum Computing. On the other hand, Quantum Computing in general and Quantum Cryptography (QC), in particular, can help in alleviating the security concerns associated with CC, which have prevented users from migrating to cloud. The paper proposes a model framework contemplating the use of Blind Quantum Computation (BQC) between cloud servers involved in multiparty computations during online phase and using authenticated Quantum Key Distribution (QKD) for secure distribution of keys (used for encrypting the secret files) when going into offline phase. Finally, a proof of the model has been presented, using Universal Composibility (UC) framework.
Latent Semantic Analysis (LSA): Reduction of Dimensions

After building the vector space model, we can represent and compare any type of objects of our study. Now we can discuss the question whether we can improve the vector space we have built. The importance of this question is related to the fact that the vector space model can have thousands of features, and possibly many of these features are redundant. Is there any way to get rid of the features that are not that important? Latent Semantic Analysis allows constructing new vector space model with smaller number of dimensions.
Semantic Description of the Organizational Knowledge Resources - Selected Aspects of Security

Abstract The paper proposes the use of semantic modeling to describe the organizational knowledge resources. Key concepts related to semantic representation of knowledge in the form of ontology were also presented. The study indicated opportunities for creating new business models based on the organizational knowledge resources formalized in ontologies (ontology providers, organizations that certify knowledge available in the form of ontologies and clients using paid knowledge resources in ontology in order to automate certain areas of their activity. The investigations were presented in light of safety mechanisms whose implementation is necessary when using a semantic approach in describing the organizational knowledge resources and creating new business models based on this approach, including mechanisms for protecting information and knowledge from unauthorized access, certificates that describe the level of trust and the design of a secure user interface. The focus was also on the fact that the formalization of organizational knowledge resources and its representation in an electronic form (ontologies) poses a major challenge for knowledge engineers and leads to the necessity to cooperate in research on the borderline of management and IT sciences.
Implementation of Web Browser Extension for Mitigating CSRF Attack

CSRF is one of the most serious cyber-attacks and has been recognized among the major threats and among the top ten worst vulnerabilities of web applications. CSRF attack occurs when the attacker takes the advantages of implicit authentication mechanisms of HTTP protocol and cached credentials in the browser to execute a sensitive action on a target website behalf of an authenticated user without his knowledge. In this paper, we present a CSRF protection mechanism that can be added to Google Chrome browser as an extension. Our tool “CSRF Detector” is purely implemented on the client-side to defeat the attacker attempt to perform CSRF attacks by analyzing web requests and web pages content to detect all the basic and advanced CSRF attacks. Our evaluation result shows that CSRF Detector extension successfully detects all the generated attacks and it has the ability to protect users and web applications against CSRF attacks with no false positive.
Semantic Web Languages: Expressivity of SWL

The paper tries to discuss from a slightly higher level a focus oriented towards general properties that a Semantic Web Language (SWL) must have. We state as a ground the following two points of view: to compare (1) Expressivity of the SWL, and (2) a possibility to infer new knowledge from an SWL knowledge base with corresponding properties of the classical First Order Logics (FOPL) as a measure of their basic quality (now prepared). From expressivity, the language for the semantic web must be a common communication tool for computers as well as for people fulfilling an easy-to-use condition by means of adding more semantics directly into the language's syntax. After a discussion of properties and critical recommendations two languages, OWL DL1 and RDF CFL have been proposed here to become the SWL both having the expressivity comparable with the FOPL.
Discovering Senile Dementia from Brain MRI Using Ra-DenseNet

With the rapid development of medical industry, there is a growing demand for disease diagnosis using machine learning technology. The recent success of deep learning brings it to a new height. This paper focuses on application of deep learning to discover senile dementia from brain magnetic resonance imaging (MRI) data. In this work, we propose a novel deep learning model based on Dense convolutional Network (DenseNet), denoted as ResNeXt Adam DenseNet (Ra-DenseNet), where each block of DenseNet is modified using ResNeXt and the adapter of DenseNet is optimized by Adam algorithm. It compresses the number of the layers in DenseNet from 121 to 40 by exploiting the key characters of ResNeXt, which reduces running complexity and inherits the advantages of Group Convolution technology. Experimental results on a real-world MRI data set show that our Ra-DenseNet achieves a classification accuracy with 97.1$$\%$$ and outperforms the existing state-of-the-art baselines (i.e., LeNet, AlexNet, VGGNet, ResNet and DenseNet) dramatically.
Analytical description of digital intersections: Minimal parameters and multiscale representation

The paper contributes to a multiscale theory of digital shapes by presenting novel methods for a multiscale representation of digital lines and their intersections according to the Stern-Brocot tree. We give a new definition of the intersection (main connected part) of two specific digital straight lines on the same quadrant (First quadrant). More precisely, we give some new results about the minimal set of parameters (i.e. slope (a, b), shift (μ), parity (even or odd), and the coordinates of the upper leaning points) for each line and their intersections.
การพัฒนาออนโทโลยีนิทานพื้นบ้านอีสานเพื่อการสืบค้นและเข้าถึง (THE DEVELOPMENT OF ISAN FOLKTALE ONTOLOGY FOR INFORMATION ACCESS AND RETRIEVAL)

บทความนเปนการวจยเกยวกบการพฒนาออนโทโลยนทานพนบานอสานโดยมวตถประสงคเพอวเคราะหขอบเขตและโครงสรางความรนทานพนบานอสาน และพฒนาออนโทโลยนทานพนบานอสานเพอการสบคนและการเขาถง ในการศกษาในครงนผวจยใชวธการวจยแบบการวจยและพฒนา (Research and Development Approach: RD knowledge about the contents of stories, beliefs, traditions, values, rituals, places, characters, and magical objects. The Isan folktale ontology developing process consists of 1) setting clear purposes for Isan folktale knowledge explanation to be used as a tool for Isan folktale knowledge access; 2) setting a concept model for ontology domain design and development; and 3) developing ontology for Isan folktales, which compiles of 8 main classes (contents of folktales, beliefs, traditions, values, rituals, places, characters, magical objects), 48 subclasses, and 58 object properties. The results of Isan folktale ontology evaluation by experts showed that the classification within the ontology are highly appropriate (X = 3.00). The classification within the ontology can adequately collect knowledge at a very high level (X = 3.00). The names of classes within the ontology are appropriate and can be understood at the highest level (X = 3.33). The classification of classes within the ontology is highly appropriate (X = 3.00). The class’s properties or the features can describe the class itself appropriately at the highest level (X = 3.67). Ontology has a very high level of relationship between classes at a high level (X = 3.00). The relationship names between classes within the ontology are appropriate and can be interpreted at the highest level (X = 3.33). The data type properties and data type details are consistent at a high level (X = 3.00). The ontology is well-designed and suitable for application at the highest level (X = 3.33). Keywords: Ontology, Isan Folktales, Content Analysis
Secure guest virtual machine support in apparition

Recent research utilizing Secure Virtual Architecture (SVA) has demonstrated that compiler-based virtual machines can protect applications from side-channel attacks launched by compromised operating system kernels. However, SVA provides no instructions for using hardware virtualization features such as Intel’s Virtual Machine Extensions (VMX) and AMD’s Secure Virtual Machine (SVM). Consequently, operating systems running on top of SVA cannot run guest operating systems using features such as Linux’s Kernel Virtual Machine (KVM) and FreeBSD’s bhyve.
GANs vs. good enough

Abstract General Adversarial Networks are hot. Given Murphy’s Law, it is prudent to be paranoid. Best not to design for the average case. There is a long tradition of designing for the hundred-year flood (and five 9s reliability). What is good enough? Historically, the market hasn’t been willing to pay for five 9s. Hard to justify upfront costs for future benefits that will only payoff under unlikely scenarios, and might not work when needed. If the market isn’t willing to pay for five 9s, can we afford to design for the worst case?
THE COURSE “FUNDAMENTALS OF INFORMATION CULTURE” AS A CONDITION FOR A PEDAGOGUE-PROFESSIONAL’S DEVELOPMENT

The article reveals the notion “teacher’s pedagogical culture”, considers its mandatory component - “information culture”, and presents the content components of a teacher’s information culture. The authors give the main characteristics of a teacher with developed pedagogical culture, and define the problems of developing the information culture of students - future teachers. The paper presents a review of various universities experience on introducing the disciplines developed on the basis of the course “Fundamentals of Information Culture” worked out by the creative team of Kemerovo State University of Culture and Arts under the supervision of N. I. Gendina in educational process. In turn, the paper presents a program of the educational course “Fundamentals of Information Culture” for students majoring in “Pedagogical Education”, specialization “Russian Language”, meant for four years of study.
Exploring Virtual Reality for Neural Rehabilitation and Phobia Treatment

The principal objective of neural rehabilitation therapies is helping affected people to recover their mobility and reduce their dependency to other people in personal and occupational life. The way neural rehabilitation therapies are applied used to be based on the experience of the therapists and the epidemiological data available. Meanwhile, computer games (serious games), specially, based on virtual reality, are already used to treat exclusively certain types of phobia considering that an effective therapy consists on exposing patients to the source of their pathological fear within a controlled and safe environment. At present, at National Autonomous University of Mexico we are developing a set of applications based on videogames technology, programming them by the Unity SDK. The idea is helping patients to recover their mobility, which was lost by a neurological accident, or to confront their phobia. In this work we present the corresponding advances. In the case of neural rehabilitation, we focus the applications for ocular, head and neck recovery, developing some 3D scenarios for the Oculus Rift device. Respect to phobia treatment we consider attending arachnophobia, acrophobia and aviophobia, developing some 3D scenarios for Card Boards and also the Oculus Rift.
Photovoltaic panels cost optimization with flexible polymer semiconductor cells using fuzzy logic

This paper presents the research undertaken by the authors to determine the parameters of electric power produced by a photovoltaic panel using flexible semiconductor polymer cells, aiming a comparative study between this panel and other types of conventional photovoltaic panels, with monocrystalline, polycrystalline and amorphous silicon, based on technical and economic indicators, established under uncertainty conditions. We will also present the variation of these dimensions according to the incidence angle of solar radiation. Thus, researches will show that for its value between 36-38 degrees, you get very good conversion yields. The economic study presented also reveals that under uncertainty there is a correspondence between the panel type and its physical and economic characteristics.
Robust framework of Delaunay triangulation matching based on feature saliency analysis

To reduce the matching ambiguities and explore the matching potential of repetitive features from the scenes with repetitive elements, we present a robust framework of Delaunay triangulation matching based on feature saliency analysis. The feature saliency is computed based on the Gaussian invariance model of the selected reliable features and used as guidance for the triangle-constraint region matching. Due to the seed-sensitive nature of the triangulation matching, the framework integrates the effectiveness validation steps to predict whether the extracted features and the found seeds are proper for matching the specific scenes. By suppressing the surround feature influence, we provide an opportunity for the repetitive features to enhance their feature saliency in the local regions and increase the discriminative power to identify their correspondences. We benchmark the matching performance on the tradeoff between the mean precision and recall. The promising results manifest its effectiveness on the ambiguity reduction.
Techniques Used for the Prediction of Number of Faults

PredictionPrediction ofTechniques number of faultsFaults refers to the process of estimating/predicting a potential number of faults that can occur in each given software module [41]. A software module can be a class for object-oriented software, file for traditional software or any other independent component having a bunch of code Prediction bundles together.
Design and Practice of College English Micro-course Based on Information Technology Background

With the development of information technology, education has gradually evolved towards individualization, diversification and fragmentation. As an innovative educational technology, micro-course has become an important teaching method for primary education, secondary education, higher education and vocational education. This paper focuses on the teaching status of college English, combines the characteristics of micro-course teaching, conducts a theoretical exploration of the micro-course teaching mode, makes a design proposal in the college English micro-course teaching, and discusses its practical operation, showing the necessity of the application of micro-course in college English teaching.
Recruiting Software Developers a Survey of Current Russian Practices

Software is mostly a “people” business: the single and most important asset of a software company is its developers. Finding an appropriate software developer is a problem that has created the whole area (and business) of IT recruiting, which is mostly an “art” involving a set of practical techniques and approaches. This paper discusses the typical practices of IT recruiting in Russia. Our aim is to describe its baseline from the point of view of its practitioners and to study ways to improve it. To achieve this aim we conducted a survey among more than 70 professional recruiters, we analysed the results, and we have identified mechanisms to improve it, also partially automating it. The results of our research appear to be applicable and beneficial for professionals and researchers living in several other parts of the world, given the evident similarity of the market structure.
Multiple-point variogram features for evolving of fractal image compression technique

The objective of this work is to reduce the time consuming that spent in the coding of the remote sensing image. The result shows a great improvement in the coding process with less processing time. Some efficiency tests are accomplished to prove the effective of the proposed method in comparing to other methods.
DEVELOPMENT OF THE PRINCIPAL EDUCATIONAL PROGRAMME WITHIN THE FIELD OF STUDY 44.03.05 PEDAGOGICAL EDUCATION (WITH TWO SPECIALISATIONS) TAKING INTO ACCOUNT REQUIREMENTS OF FEDERAL STATE EDUCATIONAL STANDARD OF HIGHER EDUCATION OF THE NEW GENERATION AND THE PROFESSIONAL STANDAR

In the article, the principle modular educational program within the field of study 44.03.05 Pedagogical education (with two specialisations) developed at Sevastopol State University according to the new Federal State Educational Standard of Higher Education and the requirements of the teacher’s professional standard is presented. It is noted that when developing such a programme, it is necessary to apply the competence based approach, to define clearly the goals and objectives of each module, and to work out a system of evaluation tools for universal, general professional and professional competencies that should be formed in future specialists in pedagogical education.
Differential Cryptanalysis of Symmetric Block Ciphers Using Memetic Algorithms

The paper presents a new differential cryptanalysis attack based on memetic algorithms. A prepared attack is directed against the ciphertext generated by one of the most popular ciphers named Data Encryption Standard (DES) reduced to six rounds of an encryption algorithm. The main purpose of the proposed MASA attack is to indicate the last encryption subkey, which allows the cryptanalyst to find 48 from 56 bits of decrypting key. With a simple comprehensive search, it's possible to get the remaining 8 bits. The memetic attack is based on the simulated annealing algorithm, used to improve the local search process, to achieve the best possible solution. The described algorithm will be compared with a genetic algorithm attack, named NGA, based on an additional heuristic operator.
Biometric-Based Linguistic Solutions for Data Encryption and Sharing

This paper will describe new hybrid classes of secret sharing protocols joining features of linguistic secret division procedures with biometric threshold schemes. Such advanced protocols will be defined with application of different classes of formal grammars with standard or non-standard biometric patterns. Evaluation of such method will be done, as well as possible application for data and services management will be presented.