The Journal of Institute of Information and Communication Technologies of Bulgarian Academy of Sciences

Cybernetics and Information Technologies

Cybernet. & Inform. Techn.ONL

<article-title>Preface</article-title>

{"article-title":"Preface"}

<abstract><title style='display:none'>Abstract</title><p>The existing cloud data models cannot meet the management requirements of structured data very well including a great deal of relational data, therefore a two-layer cloud data model is proposed. The composite object is defined to model the nested data in the representation layer, while a 4-tuple is defined to model the non-nested data in the storage layer. Referring the relational algebra, the concept of SNO (Simple Nested Object) is defined as basic operational unit of the algebraic operations; the formal definitions of the algebraic operations consisting of the set operations and the query operations on the representation layer are proposed. The algorithm of extracting all SNOs from a CAO (Component-Attribute-Object) set of a composite object is proposed firstly as the foundation, and then as the idea; the pseudo code implementation of algorithms of the algebraic operations on the storage layer are proposed. Logic proof and example proof indicate that the definition and the algorithms of the algebraic operations are correct.</p></abstract>

Abstract

Guangxi Colleges and Universities Key Laboratory of Scientific Computing & Intelligent Information Processing, Guangxi Teachers Education University, Nanning 530001,

School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044,

Keywords

<article-title>The Algebraic Operations and Their Implementation Based on a Two-Layer Cloud Data Model</article-title>

The Algebraic Operations and Their Implementation Based on a Two-Layer Cloud Data Model

<abstract><title style='display:none'>Abstract</title><p>Although Clustering Algorithm Based on Sparse Feature Vector (CABOSFV) and its related algorithms are efficient for high dimensional sparse data clustering, there exist several imperfections. Such imperfections as subjective parameter designation and order sensibility of clustering process would eventually aggravate the time complexity and quality of the algorithm. This paper proposes a parameter adjustment method of Bidirectional CABOSFV for optimization purpose. By optimizing Parameter Vector (PV) and Parameter Selection Vector (PSV) with the objective function of clustering validity, an improved Bidirectional CABOSFV algorithm using simulated annealing is proposed, which circumvents the requirement of initial parameter determination. The experiments on UCI data sets show that the proposed algorithm, which can perform multi-adjustment clustering, has a higher accurateness than single adjustment clustering, along with a decreased time complexity through iterations.</p></abstract>

Donlinks School of Economics and Management, University of Science and Technology Beijing (USTB), Beijing,

School of Business, Anhui University, Hefei,

<article-title>Improved Bidirectional CABOSFV Based on Multi-Adjustment Clustering and Simulated Annealing</article-title>

Improved Bidirectional CABOSFV Based on Multi-Adjustment Clustering and Simulated Annealing

<abstract><title style='display:none'>Abstract</title><p>The development of internet public opinion presents a certain ecological characteristics. According to the different characteristics, this paper divides internet public opinion into five stages. This paper focuses on the first stage in internet public opinion, from the perspective of qualitative and quantitative analysis, to have a definition of embryonic stage, characteristics, as well as composition. Then this paper analyzes the causes of the formation mechanism in internet public opinion’s embryonic stage with the method of game theory. After that, the concepts of hot source factors are introduced to construct the conceptual model of embryonic stage in internet public opinion. Finally, aiming at different types of hot source factors (internet public opinion events), we put forward the effective means to guide and control the development of embryonic stage.</p></abstract>

School of Traffic and Transportation, Beijing Jiaotong University, Beijing,

Beijing Institute of Graphic Communication, Beijing,

<article-title>A Game Theory Based Model for Internet Public Opinion’s Embryonic Stage</article-title>

A Game Theory Based Model for Internet Public Opinion’s Embryonic Stage

{"article-title":"A Game Theory Based Model for Internet Public Opinion\u2019s Embryonic Stage"}

<abstract><title style='display:none'>Abstract</title><p>An ECG baseline shift correction method is presented on the base of the adaptive bionic wavelet transform. After modifying the bionic wavelet transform according to the characteristics of the ECG signal, we propose a novel adaptive BWT algorithm. Using the contaminated and actual data in the MIT-BIH database, the method of fast and simple adaptive bionic wavelet transform can effectively correct the baseline shift under the premise of maintaining the geometric characteristics of the ECG signal. Evaluation of the proposed method shows that the average improvement SNR of FABWT is 2.187 dB more than the CWT-based best case result.</p></abstract>

Automation School, Beijing University of Post and Telecommunications, Beijing 100876,

<article-title>A Fast and Simple Adaptive Bionic Wavelet Transform: ECG Baseline Shift Correction</article-title>

A Fast and Simple Adaptive Bionic Wavelet Transform: ECG Baseline Shift Correction

<abstract><title style='display:none'>Abstract</title><p>There is a huge growth in the amount of documents of corporations in recent years. With this paper we aim to improve classification performance and to support the effective management of massive technical material in the domain-specific field. Taking the field of petro-chemical process as a case, we study in detail the influence of parameters on classification accuracy when using Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) Text auto-classification algorithm. Advantages and disadvantages of the two text classification algorithms are presented in the field of petro-chemical processes. Our tests also show that more attention to the professional vocabulary can significantly improve the F1 value of the two algorithms. These results have reference value for the future information classification in related industry fields.</p></abstract>

School of Economics & Management, Beijing Institute of Petrochemical Technology, 102617 Beijing,

MES Department, PCITC Information Technology Co., Ltd., 100007 Beijing,

<article-title>Chinese Text Auto-Categorization on Petro-Chemical Industrial Processes</article-title>

Chinese Text Auto-Categorization on Petro-Chemical Industrial Processes

{"article-title":"Chinese Text Auto-Categorization on Petro-Chemical Industrial Processes"}

<abstract><title style='display:none'>Abstract</title><p>Energy consumption forecasting is a kind of fundamental work of the energy management in equipment-manufacturing enterprises, and an important way to reduce energy consumption. Therefore, this paper proposes an intellectualized, short-term distributed energy consumption forecasting model for equipment-manufacturing enterprises based on cloud computing and extreme learning machine considering the practical enterprise situation of massive and high-dimension data. The analysis of the real energy consumption data provided by LB Enterprise was undertaken and corresponding calculating experiments were completed using a 32-node cloud computing cluster. The experimental results show that the energy consumption forecasting accuracy of the proposed model is higher than the traditional support vector regression and the generalized neural network algorithm. Furthermore, the proposed forecasting algorithm possesses excellent parallel performance, overcomes the shortcoming of a single computer’s insufficient computing power when facing massive and high-dimensional data without increasing the cost.</p></abstract>

Department of Mathematics, Tianjin University of Technology, Tianjin 300384,

ZhongHuan Information College, Tianjin University of Technology, Tianjin 300380,

Economics and Management School, Yanshan University, Qinhuangdao, Hebei 066004,

<article-title>Cloud Computing and Extreme Learning Machine for a Distributed Energy Consumption Forecasting in Equipment-Manufacturing Enterprises</article-title>

Cloud Computing and Extreme Learning Machine for a Distributed Energy Consumption Forecasting in Equipment-Manufacturing Enterprises

<abstract><title style='display:none'>Abstract</title><p>The traditional time series studies consider the time series as a whole while carrying on the trend detection; therefore not enough attention is paid to the stage characteristic. On the other hand, the piecewise linear fitting type methods for trend detection are lacking consideration of the possibility that the same node belongs to multiple trends. The above two methods are affected by the start position of the sequence. In this paper, the concept of overlapping trend is proposed, and the definition of milestone nodes is given on its base; these way not only the recognition of overlapping trend is realized, but also the negative influence of the starting point of sequence is effectively reduced. The experimental results show that the computational accuracy is not affected by the improved algorithm and the time cost is greatly reduced when dealing with the processing tasks on dynamic growing data sequence.</p></abstract>

Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing,

<article-title>Determination of the Starting Point in Time Series for Trend Detection Based on Overlapping Trend</article-title>

Determination of the Starting Point in Time Series for Trend Detection Based on Overlapping Trend

<abstract><title style='display:none'>Abstract</title><p>The conventional Chirp Scaling Algorithm is mainly used in side looking or small squint angle mode of synthetic aperture imaging. In application of synthetic sonar, the large squint angle imaging is often required and the range-azimuth coupling is serious. On the basis of studying the principle of the conventional Chirp Scaling Algorithm, we improved the imaging algorithm in large squint mode. We analysed the structure of the echo frequency spectrum and the compensation of phase factor. The improved imaging algorithm designs a more precision of phase compensation factor, and eliminates the high order degree of range and azimuth coupling in the specific mapping band. Any target point is simulated in imaging region by using the improved algorithm. The simulation conclusion showed that the improved Chirp Scaling Algorithm is able to meet the imaging focus and is more suitable to slant imaging as compared with the traditional algorithm.</p></abstract>

Engineering Practice Training Center, Northwestern Ploytechnical University, Xi’an,

School of Marine Science And Technology, Northwestern Ploytechnical University, Xi’an,

Northwestern Ploytechnical University Ming De College, Xi’an,

<article-title>Improved Chirp Scaling Algorithm for Processing Squinted Mode Synthetic Aperture Sonar Data</article-title>

Improved Chirp Scaling Algorithm for Processing Squinted Mode Synthetic Aperture Sonar Data

<abstract><title style='display:none'>Abstract</title><p>The wireless sensor network covers more scale with more sensor nodes for larger scale agriculture. The article describes improvement of DV-Hop Algorithm to locate the nodes with quadrilateral range positioning method, so that the difficulty of dilatation method in agriculture actual application to be solved. The analog test for the algorithm is conducted and is mainly developed for the average locating error with illustration and discussion on the proportion relations of average error, average connectivity and anchor nodes. According to the analog results, the algorithm obtains better effect on the average locating error, which improves the accuracy of the algorithm.</p></abstract>

<article-title>Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture</article-title>

Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture

{"article-title":"Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture"}

<abstract><title style='display:none'>Abstract</title><p>Head pose estimation plays an important role in face recognition. However, it faces vast challenges on account of the initialization, facial feature points’ location accuracy and so on. Inspired by the observation that head pose angles change smoothly and continuously, we present a method based on a robust convolutional neural network for head pose estimation. The proposed network architecture consists of three levels and each level has three convolutional neural networks. The first level is a global one; it predicts the head pose quickly as a preliminary estimation. The following two levels are local ones; they refine the estimation achieved from the previous level step by step. Higher and higher resolution image with different input regions are taken as input in our network. At last, a multi-level regression is employed to combine the estimations from each level. The whole process is conducted in a cascade way to improve the head pose estimation performance directly with three angles together. We perform large experiments on nine challenging benchmark datasets. The experimental results demonstrate that our method performs better than the compared methods.</p></abstract>

<article-title>Head Pose Estimation Based on Robust Convolutional Neural Network</article-title>

Head Pose Estimation Based on Robust Convolutional Neural Network

{"article-title":"Head Pose Estimation Based on Robust Convolutional Neural Network"}

<abstract><title style='display:none'>Abstract</title><p>With the rapid development of social networks, location based social network gradually rises. In order to retrieve user’s most preferred attractions from a large number of tourism information, personalized recommendation algorithm based on the geographic location has been widely concerned in academic and industry. Aiming at the problem of low accuracy in personalized tourism recommendation system, this paper presents a personalized algorithm for tourist attraction recommendation – RecUFG Algorithm, which combines user collaborative filtering technology with friends trust relationships and geographic context. This algorithm fully exploits social relations and trust friendship between users, and by means of the geographic information between user and attraction location, recommends users most interesting attractions. Experimental results on real data sets demonstrate the feasibility and effectiveness of the algorithm. Compared with the existing recommendation algorithm, it has a higher prediction accuracy and customer satisfaction.</p></abstract>

School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101,

Business School, Shandong Normal University, Jinan 250014,

<article-title>A Context-Awareness Personalized Tourist Attraction Recommendation Algorithm</article-title>

A Context-Awareness Personalized Tourist Attraction Recommendation Algorithm

{"article-title":"A Context-Awareness Personalized Tourist Attraction Recommendation Algorithm"}

<abstract><title style='display:none'>Abstract</title><p>In this paper, the generation method of the medial axis in the arbitrary quadrilateral surface is proposed. It can provide a solution for the simplification of the complex fillet feature and the generation of the mesh in the model. By using the locus method associated with moving Frenet frame, we realize the simple and fast algorithm for generating the medial axis. As for the engineering problem, B-rep 3D solid models with clear boundary definition are mostly applied; the information of vertex, side and surface of the model, which is clearly stored in the model file, can be used to simplify the traditional locus method for generating the medial axis, in order to reduce the amount of data required by the generation. In this paper, we use the clear boundary information in the B-rep model as the condition for generating the medial axis and the characteristics of the bisector to eliminate the calculation of the branch points, reducing the factors affecting the accuracy of the medial axis. In order to ensure the accuracy of the medial axis, the density of the insertion points can be used for control.</p></abstract>

School of Information Science and Engineering, Dalian Polytechnic University, Liaoning Dalian 116034,

College of Mathematics and Informatics, South China Agricultural University, Guangzhou Guangdong 510642,

School of Computer and Information Technology, Liaoning Normal University, Dalian 116029,

<article-title>Generation Method and Application of Product-Oriented Medial Axis</article-title>

Generation Method and Application of Product-Oriented Medial Axis

{"article-title":"Generation Method and Application of Product-Oriented Medial Axis"}

<abstract><title style='display:none'>Abstract</title><p>Current works have been focused on the robustness of single network and interdependent networks. However, to be more correct, the dependence of many real systems should be described as unidirectional. To study the structural robustness of networks with unidirectional dependence, the dependent networks named UDN are proposed, the description of the propagation of failures in them is given, as well as the introduction of the attack strategies that the probability of a node being attacked depends on the degree (DP attack) or on the betweenness (BP attack) of this node. The simulated results show that UDN is more vulnerable to BP attack when is first attacked a node with high betweenness. Compared with the Interacting Networks (IN), the UDN is more fragile under the two attack’s strategies.</p></abstract>

Simulation Training Center, Logistical Engineering University, Chongqing 401311,

Training Department, Logistical Engineering University, Chongqing 401311,

<article-title>Structural Robustness of Unidirectional Dependent Networks Based on Attack Strategies</article-title>

Structural Robustness of Unidirectional Dependent Networks Based on Attack Strategies

<abstract><title style='display:none'>Abstract</title><p>In view of the defects and deficiencies of existing detection methods of rotor position for Switched Reluctance Motor (SRM), an indirect Detection Method (DM) based on DE-SVM for Support Vector Machine (SVM) rotor position is proposed. This method uses the three-phase current and flux linkage within the full angle domain of SRM as input and rotor position angle as output, and utilizes the strong nonlinear mapping capability of SVM to create a predication model for these three parameters offline. The strong global optimization capability of Differential Evolution (DE) Algorithm is then employed based on the deviation between actual rotor position and model output to optimize the prediction model online, thereby realizing sensorless detection of SRM rotor position. The simulation result shows that this method can accurately predict the position of SRM rotor.</p></abstract>

School of Electrical and Information Engineering, Jiangsu University, Zhenjing 212003,

School of Electrical and Photoeletronic Engineering, Changzhou Institute of Technology, Changzhou 213022,

<article-title>Indirect Detection Method of Rotor Position Based on DE-SVM</article-title>

Indirect Detection Method of Rotor Position Based on DE-SVM

{"article-title":"Indirect Detection Method of Rotor Position Based on DE-SVM"}

<abstract><title style='display:none'>Abstract</title><p>Clustering on multiple manifolds serves as an analysis of the data lying on multiple manifolds. The smoothness and local linearity of data samples are utilized to define the local linear degree which is motivated by Principal Component Analysis (PCA) and Depth First Search (DFS). Then, Multiple Manifolds Clustering (LMMC) is proposed on the base of the Local Linear Analysis (LLA) via this definition and neighbor-growing algorithm, which are especially effective under the condition of interactions. Instead of addressing problems of complex optimization and K-means operation, LMMC is simple and efficient compared with traditional manifold clustering. The algorithm can achieve superior performance on complex subspace and manifolds clustering datasets. Meanwhile, comparative experiments are given to show the effectiveness and efficiency of this algorithm.</p></abstract>

School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169,

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094,

<article-title>Multiple Manifolds Clustering via Local Linear Analysis</article-title>

Multiple Manifolds Clustering via Local Linear Analysis

{"article-title":"Multiple Manifolds Clustering via Local Linear Analysis"}

<abstract><title style='display:none'>Abstract</title><p>Depth data is an effective tool to locate the intelligent agent in space because it accurately records the 3D geometry information on the surface of the scanned object, and is not affected by factors like shadow and light. However, if there are many planes in the work scene, it is difficult to identify objects and process the resulting huge amount of data. In view of this problem and targeted at object calibration, this paper puts forward a depth data calibration method based on Gauss mixture model. The method converts the depth data to point cloud, filters the noise and collects samples, which effectively reduces the computational load in the following steps. Besides, the authors cluster the point cloud vector with the Gaussian mixture model, and obtain the target and background planes by using the random sampling consensus algorithm to fit the planes. The combination of target Region Of Intelligent agent (ROI) and point cloud significantly reduces the computational load and improves the computing speed. The effect and accuracy of the algorithm is verified by the test of the actual object.</p></abstract>

College of Technology, Hubei Engineering University, Xiao Gan 432000, China, Department of Automatic Control, Northwestern Polytechnical University, Xi’an 710072,

University of Victoria, Victoria BC V8P 5C2,

<article-title>Depth Data Reconstruction Based on Gaussian Mixture Model</article-title>

Depth Data Reconstruction Based on Gaussian Mixture Model

{"article-title":"Depth Data Reconstruction Based on Gaussian Mixture Model"}

<abstract><title style='display:none'>Abstract</title><p>With the formation of China’s large power grid, the security of the network is particularly important. The contaminant flashover of insulators has a serious impact on the operation safety of a high voltage power network. In this paper, the acoustic signals’ characteristics of the contaminant insulators flashover are analyzed, and, as a result, the correlation between the acoustic signal and the contaminant insulator flashover is established. To experiment with contaminant insulator for three different Equivalent Salt Deposit Densities (ESDD), acoustic signals were collected separately. Then, the contaminant insulators’ acoustic signals of flashover were analyzed by wavelet packet. The characteristics of the signals were obtained, and they can be judged for contaminant flashover warning.</p></abstract>

School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072,

The Mechanical and Electrical Institute, Shihezi University, Shihezi 832003,

<article-title>Analysis of Various ESDD of Contaminant Insulator Flashover Acoustic Signal by Wavelet Packet</article-title>

Analysis of Various ESDD of Contaminant Insulator Flashover Acoustic Signal by Wavelet Packet

<abstract><title style='display:none'>Abstract</title><p>Internal clustering validation is recognized as one of the vital issues essential to clustering applications, especially when external information is not available. Existing measures have their limitations in different application circumstances. There are still some deficiencies for Internal Validation of Boolean clustering. This paper proposes a new Clustering Validation index based on Type of Attributes for Boolean data (CVTAB). It evaluates the clustering quality in the light of Dissimilarity of two clusters for Boolean Data (DBD). The attributes in the Boolean Data are categorized into three types: Type A, Type O and Type E representing respectively the attribute values 1,0 and not the same for all the objects in the set. When two clusters are composed into one, DBD applies the numbers of attributes with the types changed and the numbers of objects changed to measure dissimilarity of two clusters. CVTAB evaluates the clustering quality without respect to external information</p></abstract>

<article-title>An Internal Clustering Validation Index for Boolean Data</article-title>

An Internal Clustering Validation Index for Boolean Data

{"article-title":"An Internal Clustering Validation Index for Boolean Data"}

<abstract><title style='display:none'>Abstract</title><p>In the era of big data, people have to face information filtration problem. For those cases when users do not or cannot express their demands clearly, recommender system can analyse user’s information more proactive and intelligent to filter out something users want. This property makes recommender system play a very important role in the field of e-commerce, social network and so on. The collaborative filtering recommendation algorithm based on Alternating Least Squares (ALS) is one of common algorithms using matrix factorization technique of recommendation system. In this paper, we design the parallel implementation process of the recommendation algorithm based on Spark platform and the related technology research of recommendation systems. Because of the shortcomings of the recommendation algorithm based on ALS model, a new loss function is designed. Before the model is trained, the similarity information of users and items is fused. The experimental results show that the performance of the proposed algorithm is better than that of algorithm based on ALS.</p></abstract>

Institute of Disaster Prevention, Yanjiao Town 065201,

<article-title>Application of Improved Recommendation System Based on Spark Platform in Big Data Analysis</article-title>

Application of Improved Recommendation System Based on Spark Platform in Big Data Analysis

<abstract><title style='display:none'>Abstract</title><p>Aiming at the golf tournament technical requirements in International Humanoid robot Olympic Game (IHOG), two-freedom-degrees “head &amp; eye” system based on monocular vision robot MF-AI is developed. The new robot equipped with the “head &amp; eye” system can identify the location of the golf ball and the hole, and can measure the distance of the two objects. Experiments show that the two-freedom-degrees “head &amp; eye” system improves the accuracy of hitting the golf ball into the hole. Moreover, the system can identify the target, can calibrate distances, can measure robot’s moving and look for the hole, can adjust the position of the robot and hit the ball effectively.</p></abstract>

Beijing Information Science & Technology University, 100192,

<article-title>Realization of Humanoid Robot Playing Golf</article-title>

Realization of Humanoid Robot Playing Golf

{"article-title":"Realization of Humanoid Robot Playing Golf"}

<p> <em>Cybernetics and Information Technologies</em> is covered by the following services: </p> <ul> <li> ACM Digital Library </li> <li> Baidu Scholar </li> <li> Cabell's Whitelist </li> <li> CNKI Scholar (China National Knowledge Infrastructure) </li> <li> CNPIEC - cnpLINKer </li> <li> Dimensions </li> <li> DOAJ (Directory of Open Access Journals) </li> <li> EBSCO </li> <li> Engineering Village </li> <li> ExLibris </li> <li> Genamics JournalSeek </li> <li> GoOA </li> <li> Google Scholar </li> <li> Inspec </li> <li> Japan Science and Technology Agency (JST) </li> <li> J-Gate </li> <li> JournalGuide </li> <li> JournalTOCs </li> <li> KESLI-NDSL (Korean National Discovery for Science Leaders) </li> <li> Mathematical Reviews (MathSciNet) </li> <li> MyScienceWork </li> <li> Naver Academic </li> <li> Naviga (Softweco) </li> <li> Publons </li> <li> QOAM (Quality Open Access Market) </li> <li> ReadCube </li> <li> SCImago (SJR) </li> <li> SCOPUS </li> <li> Semantic Scholar </li> <li> Sherpa/RoMEO </li> <li> TDNet </li> <li> Ulrich's Periodicals Directory/ulrichsweb </li> <li> WanFang Data </li> <li> Web of Science - Emerging Sources Citation Index </li> <li> WorldCat (OCLC) </li> <li> X-MOL </li> </ul>

<p> <em>Cybernetics and Information Technologies</em> ist in den folgenden Services indiziert: </p> <ul> <li> ACM Digital Library </li> <li> Baidu Scholar </li> <li> Cabell's Whitelist </li> <li> CNKI Scholar (China National Knowledge Infrastructure) </li> <li> CNPIEC - cnpLINKer </li> <li> Dimensions </li> <li> DOAJ (Directory of Open Access Journals) </li> <li> EBSCO </li> <li> Engineering Village </li> <li> ExLibris </li> <li> Genamics JournalSeek </li> <li> GoOA </li> <li> Google Scholar </li> <li> Inspec </li> <li> Japan Science and Technology Agency (JST) </li> <li> J-Gate </li> <li> JournalGuide </li> <li> JournalTOCs </li> <li> KESLI-NDSL (Korean National Discovery for Science Leaders) </li> <li> Mathematical Reviews (MathSciNet) </li> <li> MyScienceWork </li> <li> Naver Academic </li> <li> Naviga (Softweco) </li> <li> Publons </li> <li> QOAM (Quality Open Access Market) </li> <li> ReadCube </li> <li> SCImago (SJR) </li> <li> SCOPUS </li> <li> Semantic Scholar </li> <li> Sherpa/RoMEO </li> <li> TDNet </li> <li> Ulrich's Periodicals Directory/ulrichsweb </li> <li> WanFang Data </li> <li> Web of Science - Emerging Sources Citation Index </li> <li> WorldCat (OCLC) </li> <li> X-MOL </li> </ul>

<DIV align=left> <P><STRONG><U>Call for papers</U></STRONG> </P> <P><STRONG>Submission</STRONG> </P> <P>Please submit your manuscripts to "Cybernetics and Information Technologies" via email to: <A href="mailto:cit@bas.bg">cit@bas.bg</A>. </P> <P>All the requirements for paper formatting are described in the document <A href="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/CAIT/Instructions_for_authors.pdf">Instructions for Authors</A>. </P> <P>Submission of a manuscript to the journal signifies that work has not been previously published and that it has not been submitted or accepted for publication elsewhere. </P> <P><STRONG>Selection</STRONG> </P> <P>Submitted manuscripts are subject to a peer-review procedure. The reviewing is made by the Editorial Board, substantially supported by a pool of additional reviewers (announcedin the journal). The decision on whether or not to accept the paper is made by the Editorial board. </P> <P><STRONG>Publication</STRONG> </P> <P>The author(s) of accepted papers will receive a LICENSE TO PUBLISH to sign and send it to the Editorial office. </P> <P>The journal publishes 4 regular issues and some additional special thematic issues (no more than two) per annum. </P> <P>The normal review period is about 6 months. The accepted papers are published in the next 1-2 months after the reviewing period. </P> <P><STRONG>Page charges</STRONG> </P> <P>The regular papers do not have article processing charges. </P> <P>A limited number of papers (up to 2-3 in an issue) are processed by paid fast-track mode in order to publish the paper in the next journal issue (if submitted at least 1 month before publication date). The fee for fast-track processing is 450 EURO per paper; it is paid only if a submitted paper is positively reviewed. </P> <P><STRONG>Special thematic issues</STRONG> </P> <P>The additional thematic issues are intended to present extended variants of selected papers presented at international scientific events. The event organizers send to CIT Editor-in-Chief (<A href="mailto:dochev@iinf.bas.bg">dochev@iinf.bas.bg</A>) a proposal for publishing a thematic special issue that contains the proposed title of the issue, the event description (link), names and detailed CV’s of proposed guest editors and expected numbers of papers in the issue. The special issues must contain 8-20 papers with the paper length of 10-15 pages (up to 200-250 pages in total). The selected papers should be written by authors from different countries and no more than two papers with the same author(s) are allowed to be included into the special issue. </P> <P>The cost for publishing a special thematic issue is: 300 EURO per paper (including a preface) for up to 12 papers and 250 EURO per paper (including a preface) for more than 12 papers. The cost should be covered by the event organizers. </P> <P>The guest editors are responsible for reviewing and selecting high quality papers to be published in the thematic issue and for writing a preface of the issue. The selected papers must provide a minimum of 50% new content and not exceed 30% copy/paste from the proceedings paper. All reviews (at least two per paper) should be sent to CIT Editor-in-Chief for approval. </P> <P>After both sides agree on all the details a contract with the organizing university/institution is signed for publishing the special issue. The special issue will be published up to 2 months after receiving the final texts in the required journal format and the Licenses to publish from the authors. </P> <P></P> <P><STRONG>Open Access Statement</STRONG> </P> <P>The journal is an Open Access journal that allows a free unlimited access to all its contents without any restrictions upon publication to all users. </P> <P><STRONG><A href="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/CAIT/Open_Access_License.pdf">Open Access License</A></STRONG> </P></DIV>

<DIV align=left> <P><STRONG>Editor-in-Chief<BR></STRONG>Danail Dochev, IICT - BAS, Bulgaria </P> <P>Institute of Information and Communication Technologies of Bulgarian Academy of Sciences - <A href="http://www.iict.bas.bg/index.html">www.iict.bas.bg/index.html</A> </P><BR> <P><STRONG>Aims &amp; Scope</STRONG> </P> <P>The Cybernetics and Information Technologies presents scientific papers including original theoretical as well as application contributions to the subject areas: information processes and systems, operational research, pattern recognition, signal and image processing, artificial intelligence, linguistic modelling, control theory and applications, high performance computing, scientific computations, computer communication technologies, software technologies, information technologies in education (the list is not exhausting). </P> <P>This is an open access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access. </P> <P>The journal acknowledges and adheres to the Core Practices of the Committee on Publication Ethics (COPE) (see details in ‘<A href="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/CAIT/Editorial_policy.pdf">Editorial Policy</A>'). </P> <P>The journal publishes 4 regular issues per annum (March, June, September, December) and some additional special thematic issues with selection of extended papers from international scientific events. </P> <P>Cybernetics and Information Technologies is a single-blind peer-reviewed journal. </P> <P>All the information for paper submission is available on the page <STRONG><EM>Submit</EM></STRONG>. </P> <P>The requirements for paper submission are described in the document '<A href="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/CAIT/Instructions_for_authors.pdf">Instructions for Authors</A>'. </P> <P><STRONG>Archiving</STRONG> </P> <P>Sciendo archives the contents of this journal in <A href="https://www.portico.org/">Portico</A> - digital long-term preservation service of scholarly books, journals and collections. </P> <P><STRONG>Plagiarism Policy</STRONG> </P> <P>The editorial board is participating in a growing community of <A href="https://www.crossref.org/services/similarity-check/">Similarity Check System's</A> users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. </P></DIV>

<P><STRONG>Editor-in-Chief<BR></STRONG>Danail Dochev, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria </P> <P><STRONG>Managing Editor<BR></STRONG>Gennady Agre, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria </P> <P><STRONG>Editorial Board<BR></STRONG></P> <P>Costin Badica, University of Craiova, Romania<BR>Farshad Badie, Berlin School of Business and Innovation, Germany<BR>Christo Dichev, Winston-Salem State University, North Carolina, USA<BR>Stefka Fidanova, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria<BR>Nagamalai Jeyanthi, Vellore Inst. of Technology, Tamil Nadu, India<BR>Christo Kabakchiev, University of Sofia, Bulgaria<BR>Aneta Karaivanova, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria<BR>Petia Koprinkova-Hristova, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria<BR>Aswani Kumar, Vellore Inst. of Technology, Tamil Nadu, India<BR>Andrea De Lorenzo, University of Trieste, Italy<BR>Gabriel Luque, University of Malaga, Spain<BR>Yannis Manolopoulos, Aristotle University, Thessaloniki, Greece<BR>Vladimir Monov, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria<BR>Petya Osenova, University of Sofia / Inst. of ICT – BAS, Sofia, Bulgaria<BR>Maciej Piasecki, Wroclaw University of Science and Technology, Poland<BR>Ivan Tanev, Doshisha University, Kyoto, Japan<BR>Dalin Zhang, Beijing Jiaotong University, China </P><STRONG></STRONG> <P><STRONG>Advisory Board</STRONG><BR>Acad. Janos Demetrovics, Hungarian Acad. of Sciences, Budapest, Hungary<BR>Acad. Ivan Popchev, Bulgarian Acad. of Sciences, Sofia, Bulgaria<BR>Acad. Vassil Sgurev, Bulgarian Acad. of Sciences, Sofia, Bulgaria<BR>Corr.-mem. Svetozar Margenov, Bulgarian Acad. of Sciences, Sofia, Bulgaria </P> <P><STRONG>Language Editor<BR></STRONG>Stanislav Drangajov, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria </P> <P><STRONG>Technical Editor<BR></STRONG>Sasha Spasova, Inst. of ICT – Bulg. Acad. of Sciences, Sofia, Bulgaria </P> <P><STRONG>Additional Reviewers<BR></STRONG><BR>Kiril Alexiev, Vera Angelova, Ognian Bumbarov, Praveen Kumar Donta, Lyubka Doukovska, Svetozar Ilchev, Nikolay Manev, Ivo Marinchev, Ioannis Mavridis, Atanas Ouzounov, S. P. Raja, Nageswara Rao, Todor Stoilov, Pencho Venkov </P> <P><STRONG>Contact email:</STRONG> <A href="mailto:cit@bas.bg">cit@bas.bg</A> </P> <P></P> <P><STRONG>Publisher</STRONG><BR>De Gruyter Poland<BR>Bogumiła Zuga 32A Str.<BR>01-811 Warsaw, Poland </P>

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Volume 16 (2016): Issue 6 (December 2016)<br/>Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

Volume 16 (2016): Issue 6 (December 2016)

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Volume 16 (2016): Issue 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

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Volume 16 (2016): Issue 6 (December 2016)Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

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Volume 16 (2016): Issue 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016