Reviewerly/exHarmony huggingface dataset:
Fuzzy Logic Based Contrast Enhancement

A novel improved fuzzy logic based image enhancement method using local information from the sub-images has been proposed in this work. The proposed methodology enhances only the V component of HSV colour space model of the sub-images, which carries the achromatic information of the image, retaining the hue and saturation components. For effectively extracting the local information, the number of sub-images has been optimized using bacterial foraging optimization algorithm. The enhancement process employs the fuzzy logic which computes the enhanced intensity values of the sub-image pixels depending on the average intensity value of the sub-images and a contrast intensification parameter. The performance of the enhancementprocess has been judged in terms of performance measures like Tenengrad and contrast improvement index. The combination of all the enhanced sub-images shows 35-45% improvement over the fuzzy based and histogram equalization based other techniques in the literature.
Transfer Learning for Cross-Domain Sequence Tagging Tasks

Neural network has been proved to be effective in sequence annotation task. Since it does not require task-specific knowledge, the same network structure can be easily applied to a wide range of applications. However, domain sequence tagging tasks still suffer from lack of available data. First, there is fewer available domain annotated data to train the recurrent neural network adequately. Second, the corpus maybe not available for domain-specific word embedding training. In this paper, we explore the problem of transfer learning of domain name entity recognition task. We proposed a modified skip-gram model for training cross-domain word embeddings, and we use source task with a large number of annotations (e.g. NER on CoNLL2003) to improve the performance on target task with fewer available annotations (e.g. NER on biomedical dataset). We evaluate our approach on a range of sequence tagging benchmarks, and the results show that significant improvement can be achieved using our approach.
Path tracking mobile robot using steppers

In control of mobile robots, precision plays a key role in path tracking. In this paper we have intended to use hybrid stepper motors for precise control of the two wheeled robot. A control algorithm was developed to control the robot along different trajectories. We have found that stepper motors are more accurate for path tracking than normal DC motors with wheel encoders and one can obtain the implicit coordinates of the robot in runtime more precisely. Getting the precise coordinates of the robot at runtime can be used in various SLAM and VSLAM techniques for more accurate 3D mapping of the environment.
Linked Data Live Exploration with Complete Results

Linked Data is one of the emerging ways to publish and link structured and machine-processable data on the Web, however, the existing techniques to perform live query Linked Data are based on recursive URI look-up process. These techniques contain a limitation for the query patterns having subject unbound and object containing a foreign URI. In such cases, the live query does not produce any answers to the query as the querying process could not be initiated due to unavailability of subject field in the triple pattern. In this paper, we make use of backlinking to extract and store foreign URIs and using this information for executing the queries live where the subject is unbound.
Improved Differential Fault Analysis on Authenticated Encryption of PAEQ-128

PAEQ is an AES-based authenticated encryption proposed by Biryukov and Khovratovich in 2014, which stays in the CAESAR competition until the second round. In CHES 2016, Dhiman Saha and Dipanwita Roy Chowdhury first discussed the differential fault analysis to PAEQ. Their work shows that the nonce used in PAEQ that is usually considered as a natural DFA countermeasure can be overcome by carefully constructing the encryption message and injecting two faults. This work presents a fully optimized DFA attack on PAEQ-128 with regard to the key recovery process. We apply the information theoretical analysis and the DFA techniques for AES into the DFA key recovery on PAEQ-128. As a result, without changing the attack assumption, the key recovery complexity is reduced from $$2^{50}$$ to $$2^{24}$$ for PAEQ-128. The successful key recovery together with its computational complexity have been verified with the key recovery simulations.
NIDES as an IS Audit Tool

The aim of this paper is to present the role of the IDS system in the process of information system audit. The paper introduces the IDS systems, their organization and architecture, and the accent is placed on IDS systems of a network type that have in their architecture an associated expert system with the task of predicting malicious activities in the system in order to take protective or protective measures in a timely manner. The paper provides basic definitions, architecture and partially describes the functioning of these systems, the usefulness and need of consulting the IDS system in the process of information system audit. When auditing the information systems, a large part refers to the security or safety aspects of the functioning of the system, and therefore IDS systems are the ideal partner in the audit process, which can provide the auditor with very important data. These data can range from recognizing the established ways of using the system, specific actions in a system that can be considered potentially harmful to the data that definitely confirm malicious actions in the system.
Developing an Open Social Scholarship Collaboration: Lessons from INKE

Many academic teams and granting agencies undergo a process of reflection at the completion of research projects to understand lessons learned and develop best practice guidelines. Generally completed at the project’s end, these reviews focus on the actual research work accomplished with little discussion of the work relationships and process involved. As a result, some hard-earned lessons are forgotten or minimized through the passage of time. Additional learning about the nature of collaboration may be gained if this type of reflection occurs during the project’s life. Building on earlier examinations of INKE, this paper contributes to that discussion with an exploration of seventh and final year of a large-scale research project.Implementing New Knowledge Environment (INKE) serves as a case study for this research. Members of the administrative team, researchers, postdoctoral fellows, graduate research assistants, and others are asked about their experiences collaborating within INKE on an annual basis in order to understand the nature of collaboration and ways that it may change over the life of a long-term grant. Interviewees continue to outline benefits for collaboration within INKE while admitting that there continue to be challenges. They also outline several lessons learned which will be applied to the next project.
Investigation on the efficiency of Tikhonov regularized approximation algorithm

An inductive algorithm is presented for smooth approximation of functions based on the Tikhonov regularization method. The discrepancy principle is used for estimating the optimal value of the smoothing parameter. The principle of heuristic self-organization is applied for assessment of some parameters and the optimal complexity of the approximating function. In this paper the efficiency of this algorithm was investigated for different kind of the Tikhonov parametric functional using model functions distorted by additive Gaussian noise simulated by a random numbers generator.
A Semantic-Based Metadata Schema to Handle System and Software Configuration

Configuration management is a key process in the system and software engineering. Product integrity is a key requirement in the development of software-based solutions, and Configuration Management defines the set of practices aimed to ensure the consistency and coherence of the product during its full life cycle. Although there are different standards that establish the principles of Configuration Management, in complex projects that require the interaction of several entities and companies, a more precise, detailed specification about how to report, compare and handle configuration data is needed. This constitutes an interesting opportunity for metadata management professionals. This contribution presents the development of a tool for managing configuration management data. The case study - developed in the context of a system engineering company – makes use of semantic web languages (RDF, OWL) and technologies to support engineers in the registration, analysis, reporting and auditing of products’ configuration. The solution defines different metadata used to handle configuration status, and a technical solution to handle them.
On properties of output sequence of multi-cyclic generator over direct sum of residue groups modulo 2

Abstract The formula for the frequencies of symbols in the output sequence of multi-cyclic generator over the direct sum of residue groups modulo 2 is obtained. In the case when cells of registers contain independent random values with the uniform distribution the limit joint distribution of the frequencies (as lengths of the registers tend to infinity) is obtained.
Design of Multi-dimensional Electronic Channel Unified Identity Authentication Method for Power Information System

At present, State Grid Corporation has established a wealth of electronic service channels, including 95598 website, electric E-power, hand-held power, national network mall, E-charging, WeChat, with the rich application of various electronic channels, while gradually facilitating user use. There has been a problem of poor user experience such as registration and query service sharing, lack of unified management of multiple electronic service channels, and lack of service supervision for various electronic channels. Therefore, it is urgent to start from the source to conduct specific research on unified identity authentication system among various electronic channels. So in this paper, we proposed a multi-dimensional electronic channel unified authentication method based PKI certificate for power information system. By the proposed method, users can directly access each application system and perform fast and secure switching between application systems without multiple authentication process, providing users with the convenience and security of engaging in complex business management activities.
A Multi-chaotic Fibonacci Algorithm for Digital Image Encryption

Actually, images are widely used in various real applications, such as Internet communication, multimedia systems, medical imaging, telemedicine, monitoring, and military communication, so their security is becoming very important. Basically, encryption is one of the best alternative way to ensure information security. In this research work, we propose a hybrid encryption algorithm for the digital grayscale image. The developed approach is based on the combination of Fibonacci sequence with the chaotic logistic map to create the secret key in order to improve encryption quality. Numerical results using a set of image benchmarks have shown the capability of the proposed encryption model to produce a better image security compared to results given by some other recently literature works.
Motivation for Wavelets and Some Simple Examples

In the first part of the book the focus was on approximating functions or vectors with trigonometric counterparts. We saw that Fourier series and the Discrete Fourier transform could be used to obtain such approximations, and that the FFT provided an efficient algorithm. This approach was useful for analyzing and filtering data, but had some limitations. Firstly, the frequency content is fixed over time in a trigonometric representation. This is in contrast to most sound, where the characteristics change over time. Secondly, we have seen that even if a sound has a simple trigonometric representation on two different time intervals, the representation as a whole may not be simple. In particular this is the case if the function is nonzero only on a very small time interval.
POLYNOMIAL METHOD FOR THE SYNTHESIS OF MULTICHANNEL SYSTEMS BY TRANSITION TO MATRIX POLYNOMIAL REPRESENTATION

Polynomial methods for synthesizing linear regulators for automatic control systems with linear objects, proposed by a number of authors, including Chen, Kailath, Gaiduk, and others, along with methods of synthesis in the state space, are becoming increasingly widespread. The synthesis of multichannel regulators caused by the need to use the matrix polynomial calculus is of a special difficulty, which is aggravated by a significant increase in the dimension of the matrices during the transition from polynomial matrices to numeric ones, in which Sylvester matrices are used. Herewith, it is necessary to take into account the requirements of controllability and observability, leading to the need to check for the presence of identical roots in polynomial matrices corresponding to the numerator and denominator of the object. This leads to the requirement of a relatively prime matrix polynomial fraction, which can be significantly weakened if it is possible to include in the desired characteristic matrix of the system some zeros and poles of the object located far to the left of the imaginary axis. In calculations using numerical matrices and, consequently, using Sylvester matrices, the latter degenerate due to the lowering of the rank, which complicates the calculations. The research continues to study polynomial synthesis of multichannel regulators based on the results obtained by Chen and other researchers and presents an algorithm for the synthesis of regulators, the feature of which is the possibility of introducing additional so-called free parameters that allow additional requirements for the automatic control system. The free parameters allow to obtain strictly proper regulators, along with the proper regulators.
Document Based RDF Storage Method for Efficient Parallel Query Processing

In this paper, we investigate the problem of efficiently evaluating SPARQL queries, over large amount of linked data utilizing distributed NoSQL system. We propose an efficient approach for partitioning large linked data graphs using distributed frameworks (MapReduce), as well as an effective data model for storing linked data in a document database using a maximum replication factor of 2 (i.e., in the worst case scenario, the data graph will be doubled in storage size). The model proposed and the partitioning approach ensure high-performance query evaluation and horizontal scaling for the type of queries called generalized star queries (i.e., queries allowing both subject-object and object-subject edges from a central node), due to the fact that no joining operations over multiple datasets are required to evaluate the queries. Furthermore, we present an implementation of our approach using MongoDB and an algorithm for translating generalized star queries into MongoDB query language, based on the proposed data model.
Proactive Information Security Strategy for a Secure Business Environment

Taking into consideration the competitive market, the protection of information infrastructure for a company means competitive advantage. The protected information along with risk analysis are the underlying decision making in the company: either development, positioning on new markets, expansion on emerging markets, exit markets, or acquisitions. At the same time, the protection of information together with operational business intelligence systems are the keys for the decisions of CEOs. Implementing appropriate security measures to counter threats such as attacks can be blocked, or its effects can be mitigated. In this context, this chapter intends to be a thorough reflection on the awareness of potential threats and vulnerabilities, as well as a preoccupation towards cooperation in countering them with well-established rules and mechanisms created at a national and organizational level. The results are relevant to better understand how the actors involved in information and communication technologies could develop new models of information systems and risk management strategies.
Finite Strain Analysis Using Shape and Point Data

Understanding the finite strain state of a rock or its spatial variation is an important component of structural geology. In this chapter the problem of calculating finite strain using shape data and point data is considered in detail. The first step in strain analysis is data acquisition, and the first section is concerned with semiautomatic extraction of data for strain analysis from digital images. Two methods for strain analysis are considered: the first method (MRL, mean radial length) uses the shapes of strain markers, and the second method (Delaunay triangulation nearest neighbor method) uses the relative positions of strain marker centroids. In each case, relevant image files, data, and C++ code are provided. Background theory is discussed, and an example application is considered emphasizing that finite strain analysis is best used in conjunction with a range of structural observations.
Metadata for Large-Scale Research Instruments

The work outlines diverse effort of a few initiatives for metadata and attribution mechanisms that can be used for large-scale instruments hosted by shared research facilities. Specifically, the role of persistent identifiers and associated metadata is considered, in relation to cases where the use of references to large-scale instruments can support research impact studies and Open Science agenda. A few routes for the adoption of large-scale instruments metadata are outlined, with indication of their advantages and limitations.
An Enhanced Hybrid Model for Solving Multiple Sequence Alignment Problem

In this work, we aim to develop a novel hybrid system (VNPSO) for solving multiple sequence alignment (MSA) problem. The presented procedure is a hybridization of particle swam optimization (PSO) algorithm and variable neighborhood descent (VND) method. When the first metaheuristic is used to discover the search space, the VND procedure is exploited to improve the swarm leader (gbest) solution quality and to overcome the local optimum problem. Experimental studies on BaliBASE benchmark have shown the effectiveness of the proposed method and its ability to obtain good quality solutions comparing to those given by some literature published works.
Microseeps as pathfinder and regional filtering tool in petroleum exploration

Microseeps are the nonvisual forms of macroseeps that are detected by use of radiometric, chemical, and magnetic methods in the soil substrate. These methods are typically referred to as surface geochemical surveys that are typically limited to the upper 20 feet (6 m) of the soil or bedrock section. Offshore surface geochemistry has been used by detecting hydrocarbon microseeps in the water column or analyzing cores from the upper 3 to 10 ft (1–3 m) of the sea floor substrate. Surface geochemistry can be an integral part in finding petroleum reservoirs when used in conjunction with subsurface and seismic data. Surface geochemical methods are based on the concept that vertically migrating hydrocarbons move from a reservoir to the surface along micropores, microfractures, and microunconformities. These fluids migrate as the result of simple physics of a liquid or gas under pressure moving towards an area of ever decreasing pressure. The petroleum fluids and gases eventually enter the soil substrate and react with existing oxides, carbonates, metals, plants, bacteria, water, and clays. The migrating hydrocarbons cause changes in Eh, pH, deposition of or removal or deposition of radioactive, halogen, and carbonate minerals. Petroleum compounds such as methane and ethane will escape into the atmosphere, and heavier ones may stay in the oil substrate unit and be degraded by bacteria. Both the mining and environmental industries use surface geochemical methods to detect buried ore deposits or areas of contamination. The mining industry is using soil gas methods to define ore deposits affiliated with organic material whether organic shales, bitumen, or “live” petroleum. The environmental industry uses various forms of soil gas methods as well as analyzing for halogenated hydrocarbons, specifically iodine, to delineate and define contaminated areas. One of the pressing questions for an explorationist is whether a target defined by subsurface geology or 3D or 2D seismic contains hydrocarbons. The only direct method of determining the presence or absence of hydrocarbons prior to drilling is detecting the presence of macro or microseeps.
Topology of Merges/Crossovers

The topology of the solutions when two classes of cubic Bézier solutions meet is described. The solutions obtained by fitting curvature at the endpoints do not adequately describe this juncture. A better description is proposed based on the behavior of the center of mass of the object, plus the extrema of the center of mass function. This is shown to be topologically correct, but too restrictive an explanation. A more detailed inspection of the ODF data shows that two types of event can occur: a merge of two solutions, plus a crossover of two other solutions. The merge event is an example of a fold catastrophe, and is associated with a zero in the determinant of the response matrix. The crossover event is much less common, and is associated with a simultaneous zero in the determinants of both this matrix and an augmented matrix containing additional information on how the spline responds to changes in the shape of the hypoTrochoid.
Discrete honey bees mating optimization (DHBMO) for solving environmental optimization problem using single and multi-objectives optimization

One of the recently proposed algorithms in the field of nature-inspired algorithm is the Honey Bees Mating Optimization (HBMO) algorithm by Haddad and Afshar. The HBMO algorithm simulates the marriage behaviour of bees. The solutions are incrementally constructed by the HBMO algorithm. Therefore, the HBMO algorithm is a swarm-based constructive optimization algorithm. However, no study has reported the modification of HBMO for feature selection. Therefore, we try to develop a discrete honey bees mating optimization (DHBMO) as the modification of HBMO for solving discrete optimization problem especially feature selection to improve the performance of machine vision for predicting water stress in plants. We test the algorithm to solve feature selection problem using single and multi-objectives optimization to optimize water usage in plants for environmental sustainability. The results showed DHBMO has better performance compared to the existed nature-inspired optimization algorithms such as genetic algorithms (GA), simulated annealing (SA) and discrete-particle swarm optimization (discrete-PSO).
Anomaly Detection for Environmental Data Using Machine Learning Regression

Environmental data exhibits as huge amount and complex dependency. Utilizing these data to detect anomaly is beneficial to the disaster prevention. Big data approach using the machine learning method has the advantage not requiring the geophysical and geochemical knowledge to detect anomaly. This paper using the popular support vector regression (SVR ) to model the correlation between factors. From the residual of the regression, it develops a statistical method to quantify the extremity of some abnormal observed data. A case study is proposed to demonstrate the developed methods.