Advances in Intelligent Systems and Computing

Online ISSN: 2194-5357
Publications
Article
With exponential increase in the volumes of video traffic in cellular net-works, there is an increasing need for optimizing the quality of video delivery. 4G networks (Long Term Evolution Advanced or LTE A) are being introduced in many countries worldwide, which allow a downlink speed of upto 1 Gbps and uplink of 100 Mbps over a single base station. In this paper, we characterize the performance of LTE A physical layer in terms of transmitted video quality when the channel condi-tions and LTE settings are varied. We test the performance achieved as the channel quality is changed and HARQ features are enabled in physical layer. Blocking and blurring metrics were used to model image quality.
 
Article
The paper introduces a propositional linguistic logic that serves as the basis for automated uncertain reasoning with linguistic information. First, we build a linguistic logic system with truth value domain based on a linear symmetrical hedge algebra. Then, we consider G\"{o}del's t-norm and t-conorm to define the logical connectives for our logic. Next, we present a resolution inference rule, in which two clauses having contradictory linguistic truth values can be resolved. We also give the concept of reliability in order to capture the approximative nature of the resolution inference rule. Finally, we propose a resolution procedure with the maximal reliability.
 
2 True Positives Rates 
1 Detection Rates 
3 True Negatives Rates 
Article
Network security is a growing issue, with the evolution of computer systems and expansion of attacks. Biological systems have been inspiring scientists and designs for new adaptive solutions, such as genetic algorithms. In this paper, we present an approach that uses the genetic algorithm to generate anomaly net- work intrusion detectors. In this paper, an algorithm propose use a discretization method for the continuous features selected for the intrusion detection, to create some homogeneity between values, which have different data types. Then,the intrusion detection system is tested against the NSL-KDD data set using different distance methods. A comparison is held amongst the results, and it is shown by the end that this proposed approach has good results, and recommendations is given for future experiments.
 
Article
The Quality of Service in security networks systems is constantly improved. The current paper propose a newly defense mechanism, based on ant system, for different jamming attack on Wireless Sensor Network (WSN). The sensitive ants react on attacks based on several reliable parameters including their level of sensitivity. The information in network is re-directed from the attacked node to its appropriate destination node. The paper analyzes how are detected and isolated the jamming attacks using mobile agents, ant systems in general and with the newly ant-based sensitive approach in particular.
 
An example for a two stage supply chain network [10] 
Results of unpaired t-test results, based on HNN- DY10 results
Article
In order to keep a green planet, in particular its important to limiting the pollution with gas emissions. In a specific capacitated fixed-charge transportation problem with fixed capacities for distribution centers and customers with particular demands, the objective is to keep the pollution factor in a given range while the total cost of the transportation is as low as possible. In order to solve this problem, we developed several hybrid variants of the nearest neighbor classical approach. The proposed models are analyzed on a set of instances used in the literature. The preliminary results shows that the newly approaches are attractive and appropriate for solving the described transportation problem.
 
E, S, and C of physiochemical variables of the Arctic lake model and daily variations of homeostasis H during a simulated year.  
Physiochemical variables considered in the Arctic lake model.
Variables and organisms used for calculating autopoiesis.
Article
We apply formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity to an aquatic ecosystem; in particular to the physiochemical component of an Arctic lake. These measures are based on information theory. Variables with an homogeneous distribution have higher values of emergence, while variables with a more heterogeneous distribution have a higher self-organization. Variables with a high complexity reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values coincide with the variation of the winter and summer seasons. Autopoiesis values show a higher degree of independence of biological components over their environment. Our approach shows how the ecological dynamics can be described in terms of information.
 
Article
In the paper different roles of users in social media, taking into consideration their strength of influence and different degrees of cooperativeness, are introduced. Such identified roles are used for the analysis of characteristics of groups of strongly connected entities. The different classes of groups, considering the distribution of roles of users belonging to them, are presented and discussed.
 
Article
Data mining techniques have been used by researchers for analyzing protein sequences. In protein analysis, especially in protein sequence classification, selection of feature is most important. Popular protein sequence classification techniques involve extraction of specific features from the sequences. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP, Rough Set Classifier etc for accurate classification. This paper presents a review is with three different classification models such as neural network model, fuzzy ARTMAP model and Rough set classifier model. A new technique for classifying protein sequences have been proposed in the end. The proposed technique tries to reduce the computational overheads encountered by earlier approaches and increase the accuracy of classification.
 
Article
As the size of a multiprocessor system increases, processor failure is inevitable, and fault identification in such a system is crucial for reliable computing. The fault diagnosis is the process of identifying faulty processors in a multiprocessor system through testing. For the practical fault diagnosis systems, the probability that all neighboring processors of a processor are faulty simultaneously is very small, and the conditional diagnosability, which is a new metric for evaluating fault tolerance of such systems, assumes that every faulty set does not contain all neighbors of any processor in the systems. This paper shows that the conditional diagnosability of bubble sort graphs $B_n$ under the PMC model is $4n-11$ for $n \geq 4$, which is about four times its ordinary diagnosability under the PMC model.
 
Block scheme presents the MG in the configuration of prediction.
The time evolution of Ψ (t) for λ-GCMG with N = 1 and S = 16 pairwise different strategies from RSS. Red dashed line corresponds to λ = 0.7, solid blue line corresponds to λ = 0.97 , green dotted line corresponds to λ = 1.
The Ψ ( t ) at time t = 3000 for Fig. 4. The time evolution of Ψ ( t ) for 
The Ψ (t) at time t = 3000 for λ-GCMG with N = 1, S = 16 pairwise different strategies from RSS and λ = 0.97. Error bars correspond to one standard deviation and curves are drawn to guide ones eye. Statistics are calculated over 10 realizations of nonstationary AR(3) process.
Article
In this paper the extended model of Minority game (MG), incorporating variable number of agents and therefore called Grand Canonical, is used for prediction. We proved that the best MG-based predictor is constituted by a tremendously degenerated system, when only one agent is involved. The prediction is the most efficient if the agent is equipped with all strategies from the Full Strategy Space. Each of these filters is evaluated and, in each step, the best one is chosen. Despite the casual simplicity of the method its usefulness is invaluable in many cases including real problems. The significant power of the method lies in its ability to fast adaptation if \lambda-GCMG modification is used. The success rate of prediction is sensitive to the properly set memory length. We considered the feasibility of prediction for the Minority and Majority games. These two games are driven by different dynamics when self-generated time series are considered. Both dynamics tend to be the same when a feedback effect is removed and an exogenous signal is applied.
 
Article
The quality of human capital is crucial for software companies to maintain competitive advantages in knowledge economy era. Software companies recognize superior talent as a business advantage. They increasingly recognize the critical linkage between effective talent and business success. However, software companies suffering from high turnover rates often find it hard to recruit the right talents. There is an urgent need to develop a personnel selection mechanism to find the talents who are the most suitable for their software projects. Data mining techniques assures exploring the information from the historical projects depending on which the project manager can make decisions for producing high quality software. This study aims to fill the gap by developing a data mining framework based on decision tree and association rules to refocus on criteria for personnel selection. An empirical study was conducted in a software company to support their hiring decision for project members. The results demonstrated that there is a need to refocus on selection criteria for quality objectives. Better selection criteria was identified by patterns obtained from data mining models by integrating knowledge from software project database and authors research techniques.
 
Article
It has been shown recently that the use of two pairs of resistors with enhanced Johnson-noise and a Kirchhoff-loop-i.e., a Kirchhoff-Law-Johnson-Noise (KLJN) protocol-for secure key distribution leads to information theoretic security levels superior to those of a quantum key distribution, including a natural immunity against a man-in-the-middle attack. This issue is becoming particularly timely because of the recent full cracks of practical quantum communicators, as shown in numerous peer-reviewed publications. This presentation first briefly surveys the KLJN system and then discusses related, essential questions such as: what are perfect and imperfect security characteristics of key distribution, and how can these two types of securities be unconditional (or information theoretical)? Finally the presentation contains a live demonstration.
 
A random forest model for the dataset from Table 1. The set LD in the root node contains a local training set for the tree. The sets LD in the child nodes correspond to the split of the above set according to the value of selected feature. In each node, Y n mean denotes the fraction of instances in the LD set in this node belonging to class 1, whilst LI n f shows non-zero local increments. 
The workflow for assessing the reliability of the prediction made by a random forest (RF) model. 
Percentage of trees that vote for each class in RF model for a selection of instances from the BCW Dataset. 
The box-plot for feature contributions within a core cluster for a hypothetical random forest model. 
Medians of feature contributions for each class for the UCI Iris Dataset. 
Article
Model interpretation is one of the key aspects of the model evaluation process. The explanation of the relationship between model variables and outputs is relatively easy for statistical models, such as linear regressions, thanks to the availability of model parameters and their statistical significance . For “black box” models, such as random forest, this information is hidden inside the model structure. This work presents an approach for computing feature contributions for random forest classification models. It allows for the determination of the influence of each variable on the model prediction for an individual instance. By analysing feature contributions for a training dataset, the most significant variables can be determined and their typical contribution towards predictions made for individual classes, i.e., class-specific feature contribution “patterns”, are discovered. These patterns represent a standard behaviour of the model and allow for an additional assessment of the model reliability for new data. Interpretation of feature contributions for two UCI benchmark datasets shows the potential of the proposed methodology. The robustness of results is demonstrated through an extensive analysis of feature contributions calculated for a large number of generated random forest models.
 
Knowledge-based view to e-Science tasks 
Article
Presented paper describes the development of comprehensive approach for knowledge processing within e-Sceince tasks. Considering the task solving within a simulation-driven approach a set of knowledge-based procedures for task definition and composite application processing can be identified. This procedures could be supported by the use of domain-specific knowledge being formalized and used for automation purpose. Within this work the developed conceptual and technological knowledge-based toolbox for complex multidisciplinary task solv-ing support is proposed. Using CLAVIRE cloud computing environment as a core platform a set of interconnected expressive technologies were developed.
 
Conference Paper
In this paper with the aid of genetic algorithm and fuzzy theory, we present a hybrid job scheduling approach, which considers the load balancing of the system and reduces total execution time and execution cost. We try to modify the standard Genetic algorithm and to reduce the iteration of creating population with the aid of fuzzy theory. The main goal of this research is to assign the jobs to the resources with considering the VM MIPS and length of jobs. The new algorithm assigns the jobs to the resources with considering thejob length and resources capacities. We evaluate the performance of our approach with some famous cloud scheduling models. The results of the experiments show the efficiency of the proposed approach in term of execution time, execution cost and average Degree of Imbalance (DI).
 
An illustration of the relation between the Fuzzy Biometric Menagerie and the Fuzzy 3-Valent Disambiguated Model of biometric security. 
Article
This paper analyses the set of iris codes stored or used in an iris recognition system as an f-granular space. The f-granulation is given by identifying in the iris code space the extensions of the fuzzy concepts wolves, goats, lambs and sheep (previously introduced by Doddington as ‘animals’ of the biometric menagerie) – which together form a partitioning of the iris code space. The main question here is how objective (stable / stationary) this partitioning is when the iris segments are subject to noisy acquisition. In order to prove that the f granulation of iris code space with respect to the fuzzy concepts that define the biometric menagerie is unstable in noisy conditions (is sensitive to noise), three types of noise (localvar, motion blur, salt and pepper) have been alternatively added to the iris segments extracted from University of Bath Iris Image Database. The results of 180 exhaustive (all-to-all) iris recognition tests are presented and commented here.
 
Detailed Flow Sequence of the Proposed Method : (a) Flow Chart for Obtaining New Fine Scale (Resolution of 128 × 128 pixels) of Enhanced image (b) Flow Chart for Obtaining New Normal Scale (Resolution of 256 × 256 pixels) of Enhanced image 
Article
This paper presents a new color image enhancement technique based on modified MultiScale Retinex(MSR) algorithm and visual quality of the enhanced images are evaluated using a new metric, namely, wavelet energy. The color image enhancement is achieved by down sampling the value component of HSV color space converted image into three scales (normal, medium and fine) following the contrast stretching operation. These down sampled value components are enhanced using the MSR algorithm. The value component is reconstructed by averaging each pixels of the lower scale image with that of the upper scale image subsequent to up sampling the lower scale image. This process replaces dark pixel by the average pixels of both the lower scale and upper scale, while retaining the bright pixels. The quality of the reconstructed images in the proposed method is found to be good and far better then the other researchers method. The performance of the proposed scheme is evaluated using new wavelet domain based assessment criterion, referred as wavelet energy. This scheme computes the energy of both original and enhanced image in wavelet domain. The number of edge details as well as wavelet energy is less in a poor quality image compared with naturally enhanced image. Experimental results presented confirms that the proposed wavelet energy based color image quality assessment technique efficiently characterizes both the local and global details of enhanced image.
 
Article
Survival of IT industries depends much upon the development of high quality and customer satisfied software products. Quality however can be viewed from various perspectives such as deployment of the products within estimated resources, constrains and also being defect free. Testing is one of the promising techniques ever since the inception of software in the global market. Though there are several testing techniques existing, the most widely accepted is the conventional scripted testing. Despite of advancement in the technology, achieving defect free deliverables is yet a challenge. This paper therefore aims to enhance the existing testing techniques in order to achieve nearly zero defect products through the combined approach of scripted and exploratory testing. This approach thus enables the testing team to capture maximum defects and thereby reduce the expensive nature of overheads. Further, it leads towards generation of high quality products and assures the continued customer satisfaction.
 
“Political books” network displayed with a force directed placement algorithm. The nodes are labeled according to their political orientation and are colored according to a gradient that aims at emphasizing the distance between clusters on the grid, as represented at the top the figure. 
Left: Simplified representation of the graph on the grid: each node represents a cluster whose area is proportional to the number of nodes included in it and the edges width represents the number of edges between the nodes of the corresponding cluster. Right: Distribution of the node labels for each neuron of the grid for the clustering obtained with the dissimilarity based on the length of the shortest paths. Red is for liberal books, blue for conservative books and green for neutral books. 
Article
In some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilarities only. Several variants of the Self Organizing Map algorithm were introduced to generalize the original algorithm to this framework. Whereas median SOM is based on a rough representation of the prototypes, relational SOM allows representing these prototypes by a virtual combination of all elements in the data set. However, this latter approach suffers from two main drawbacks. First, its complexity can be large. Second, only a batch version of this algorithm has been studied so far and it often provides results having a bad topographic organization. In this article, an on-line version of relational SOM is described and justified. The algorithm is tested on several datasets, including categorical data and graphs, and compared with the batch version and with other SOM algorithms for non vector data.
 
Article
In numerous applicative contexts, data are too rich and too complex to be represented by numerical vectors. A general approach to extend machine learning and data mining techniques to such data is to really on a dissimilarity or on a kernel that measures how different or similar two objects are. This approach has been used to define several variants of the Self Organizing Map (SOM). This paper reviews those variants in using a common set of notations in order to outline differences and similarities between them. It discusses the advantages and drawbacks of the variants, as well as the actual relevance of the dissimilarity/kernel SOM for practical applications.
 
Article
In recent years videogame companies have recognized the role of player engagement as a major factor in user experience and enjoyment. This encouraged a greater investment in new types of game controllers such as the WiiMote, Rock Band instruments and the Kinect. However, the native software of these controllers was not originally designed to be used in other game applications. This work addresses this issue by building a middleware framework, which maps body poses or voice commands to actions in any game. This not only warrants a more natural and customized user-experience but it also defines an interoperable virtual controller. In this version of the framework, body poses and voice commands are respectively recognized through the Kinect's built-in cameras and microphones. The acquired data is then translated into the native interaction scheme in real time using a lightweight method based on spatial restrictions. The system is also prepared to use Nintendo's Wiimote as an auxiliary and unobtrusive gamepad for physically or verbally impractical commands. System validation was performed by analyzing the performance of certain tasks and examining user reports. Both confirmed this approach as a practical and alluring alternative to the game's native interaction scheme. In sum, this framework provides a game-controlling tool that is totally customizable and very flexible, thus expanding the market of game consumers.
 
Article
We present a graph-based variational algorithm for classification of high-dimensional data, generalizing the binary diffuse interface model to the case of multiple classes. Motivated by total variation techniques, the method involves minimizing an energy functional made up of three terms. The first two terms promote a stepwise continuous classification function with sharp transitions between classes, while preserving symmetry among the class labels. The third term is a data fidelity term, allowing us to incorporate prior information into the model in a semi-supervised framework. The performance of the algorithm on synthetic data, as well as on the COIL and MNIST benchmark datasets, is competitive with state-of-the-art graph-based multiclass segmentation methods.
 
Conference Paper
We live on an era of awareness where the uneducated end-user from the past, gives place to an informed and demanding consumer in the present, who seeks for a product that meets the ever-changing needs of his day-to-day life. If yesterday we were slaves to the dictatorship created by international fashion brands, today we seek to break free from the fashion cycle that enslaves us with its impositions of time and contemporaneity. The fashion system is failing. Fashion trends are weakened with the constant flow of information powered by the internet. Consumers can now define their personal styles, creating their own “micro-trends”. With this resurgence of clothes, concepts like uniqueness and quality will arise, reviving the cult of exclusive garments. Customization of fashion products emerges as a way to reinforce self-identity, allowing the end-user to control in a more intrinsic way the image he shares to the world. This article aims to identify the potentialities of customized surface design in the fashion industry, trying to understand the strategies to use in the management of human factors in user-based designs. This study is part of a Ph.D. investigation on the role of textile surfaces in fashion.
 
Conference Paper
Regardless of the field of activity, managers work with people. Not only those, who are called managers by their title, belong to the category of managers. Business owners and plant foremen, supervisors and heads of departments, commanders of military units and coaches of athletic teams, and many others - all fall into the category of managers by their functions. In our work, we will describe the most important managerial functions of the psychological nature and make an attempt to shed light on a new understanding of these functions from the activity theory (AT) perspective.
 
Conference Paper
Acute and chronic syndromes account for ~50% of the estimated 500,000 cardiovascular deaths annually in the United States and similarly in densely populated countries as India. More than 100 years after its invention, surface electrocardiogram introduced by William Einthoven is still the most common fundamental technique and the gold standard for diagnosis, prognosis, screening and evaluating heart disease for many clinical conditions. Progress in wearable diagnostic devices have made possible low-cost, convenient and 24 × 7 point-of-care healthcare; however, their use is still limited to clinical diagnostic measurements. The main gap is the electrode placement at the correct intended location to realize high sensitivity with accurate waveform reconstruction. To achieve a precision of less than 1cm placement accuracy in precordial electrodes placement and to obtain consistent intra- and inter-observer results for avoiding wrong diagnosis, an interactive image-processing software has been developed in this work. We aim to provide a self-operable solution for placing non-contact wearable sensors without any medical assistance and generate repeatable and reproducible interpretations to get the best results.
 
Book
This book contains works on mathematical and simulation modeling of processes in various domains: ecology and geographic information systems, IT, industry, and project management. The development of complex multicomponent systems requires an increase in accuracy, efficiency, and adequacy while reducing the cost of their creation. The studies presented in the book are useful to specialists who are involved in the development of real events models: analog, management and decision-making models, production models, and software products. Scientists can get acquainted with the latest research in various decisions proposed by leading scholars and identify promising directions for solving complex scientific and practical problems. The chapters of this book contain the contributions presented on the 15th International Scientific-Practical Conference, MODS, June 29–July 01, 2020, Chernihiv, Ukraine.
 
Book
World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.
 
Conference Paper
The paper contains results of statistical and chemometric analysis for 15 thiourea derivatives containing the 3-amino-1,2,4-triazole moiety and characterized by antimicrobial activity against Staphylococcus aureus (NCTC 4163, ATCC 25923, ATCC 6538, ATCC 29213), Staphylococcus epidermidis (ATCC 12228) bacteria, as well as by low cytotoxicity (or lack thereof) against infected MT-4 cells. Multiple regression and cluster analysis were employed to perform the study. The research enabled obtaining linear relationships connected with three molecular descriptors SA, η, logP. The conducted chemometric analyses indicate that the increase in activity against the studied strains is closely related to the type and position of substituent in a phenyl ring.
 
Conference Paper
The Tangible User Interfaces (TUIs) and in particular, the RFID/NFC technologies are natural candidates to enhance some well-known psycho-pedagogical practices in a Technology Enhanced Learning (TEL) approach. The paper shows the prototype named Activity Board 1.0: an RFID prototype developed for the educational and rehabilitation aims. The innovative and strong assets of the prototype are: the Wi-Fi connection with the main device; and the multi-tags nature allowing more smart-objects at the same time. These two features are decisive for the educative and rehabilitative environments recovering practices based on the manipulation and multisensoriality (e.g. Montessori an pedagogy, exercises for cognitive diseases, etc.). In addition, in the article, the authors show some application where the Activity Board is already applied with success.
 
Chapter
The purpose of present thesis was to simulate real trajectory of the industrial robot Fanuc ARC Mate 100iB in LabVIEW. For this purpose the simulation of kinematic and dynamic modules were used. The planer generated the trajectory and the robot moved along it. The ending point was made by a human. The program saved the real trajectory, which was compared to the actual trajectory and the comparison was presented in the charts.
 
Chapter
This paper proposes an effective fast Fourier transform (FFT) processor for 1024-point computation based on the radix-2 of decimation-in-frequency (R2DIF) and uses the pipelined feedback (PF) technique via shift registers to efficiently share the same storage between the inputs and outputs during computation. The large memory footprint of the complex twiddle factor multipliers, and hence, area on a chip, of the proposed design is reduced by employing the coordinate rotation digital computer (CoRDiC), which replaces the complex multipliers and does not require memory blocks to store the twiddle factors. To enhance the efficient usage of the hardware resources, the proposed design only uses distributed logic. This can eliminate the use of dedicated functional blocks, which are usually limited to the target chip. The entire proposed system is mapped on a Virtex-7 field-programmable gate array (FPGA) for functional verification and synthesis. The achieved result is the proposed FFT processor more effective in terms of the speed, precision, and resource, as shown in experimental results.
 
Article
Since FFT algorithm is extremely demanding task and has several applications in the areas of signal processing and communication systems, it must be precisely designed to induce an efficient implementation of the parameters involving area and performance. To fulfill this requirement an optimized architecture is demonstrated in this paper for computing 1024-point, Radix-4 FFT using FPGA and is majorly compared with Xilinx LogiCore™ FFT IP and found that proposed design is more efficient and effective in terms of area and performance. A novel architecture referred to as 2-D Vector Rotation and Complex Math Processor has been proposed in this paper. This single structure rotation helps in effectively carrying out the complex multiplications. The algorithm implements multiplexor hardware for computing the complex multipliers, thus consuming the minimal hardware resources. The entire RTL design is described using Verilog HDL and simulated using Xilinx ISim[™]. This experimental result is tested on Spartan-6 XC6SLX150T. The result shows 557 LUT's, 837 Flip Flops, 3 DSP Slices, Maximum Frequency of 215 MHz. This is about 52% improvement in resource usage and 5% upgrade in the performance.
 
Article
This paper is the extended part of "A PROSPECTIVE APPROACH ON SECURITY WITH RSA ALGORITHM AND CLOUD SQL IN CLOUD COMPUTING" in this paper research work in done on RSA Security with cloud Oracle 10g it helps organizations protect private information and manage the identities of people and applications accessing and exchanging that information. cloud Oracle 10g Identity Management solution consists of the Oracle Internet Directory as well as additional security components and services provided by Oracle Application Server 10g, including provisioning, authentication and single sign-on (SSO) to Oracle and RSA are designed to provide the most seamless e-security experience in the market, To satisfy the customer needs from anywhere the information posted by the customer is not maintained in a single site or computer, rather maintained in number of trusted nodes. Simultaneous and faster access by different users from different places is also supported. To get high reliability and availability the data processed by the customer is stored and updated in multiple machines. If any one node gets failed, the other one provides the service. It reduce the costs associated with computing, dynamic resource pools, virtualization, increases the efficiency of computing and high availability.
 
Book
Recent years have seen remarkable progress on both advanced multimedia data processing and intelligent network information systems. The objective of this book is to contribute to the development of multimedia processing and the intelligent information systems and to provide the researches with the essentials of current knowledge, experience and know-how. Although many aspects of such systems have already been under investigation, but there are many new that wait to be discovered and defined. The book contains a selection of 36 papers based on original research presented during the 10th International Conference on Multimedia & Network Information Systems (MISSI 2016) held on 14–16 September 2016 in Wrocław, Poland. The papers provide an overview the achievements of researches from several countries in three continents. The volume is divided into five parts: (a) Images and Videos - Virtual and Augmented Reality, (b) Voice Interactions in Multimedia Systems, (c) Tools and Applications, (d) Natural Language in Information Systems, and (e) Internet and Network Technologies. The book is an excellent resource for researchers, those working in multimedia, Internet, and Natural Language technologies, as well as for students interested in computer science and other related fields.
 
Book
Presenting a collection of high-quality research papers on image processing and communications, this book not only discusses emerging applications of the currently available solutions, but also outlines potential future techniques and research directions in these areas. Gathering the proceedings of the 10th International Conference on Image Processing and Communications (IP&C 2018), held in Bydgoszcz, Poland in November 2018, it is divided into two parts. Part I focuses on image processing, offering a comprehensive survey of available methods and discussing current trends in computer vision. In turn, Part II presents novel results on networks, communications and a diverse range of applications, including cybersecurity and cloud computing.
 
Book
This book presents the main scientific results of the 10th International Symposium of Computer Science in Sport (IACSS/ISCSS 2015), sponsored by the International Association of Computer Science in Sport in collaboration with the International Society of Sport Psychology (ISSP), which took place between September 9-11, 2015 at Loughborough, UK. This proceedings aims to build a link between computer science and sport, and reports on results from applying computer science techniques to address a wide number of problems in sport and exercise sciences. It provides a good platform and opportunity for researchers in both computer science and sport to understand and discuss ideas and promote cross-disciplinary research. The strictly reviewed and carefully revised papers cover the following topics: Modelling and Analysis, Artificial Intelligence in Sport, Virtual Reality in Sport, Neural Cognitive Training, IT Systems for Sport, Sensing Technologies and Image Processing.
 
Book
This volume contains selected papers presented at the 10th International Conference on Advanced Computing and Communication Technologies (10th ICACCT 2016), technically sponsored by Institution of Electronics and Telecommunication Engineers (India), held during 18 – 20 November 2016 at Asia Pacific Institute of Information Technology, Panipat, India. The volume reports latest research on a wide range of topics spanning theory, system, applications and case studies in the fields of computing and communication technologies. Topics covered are robotics, computational intelligence encompassing fuzzy logic, neural networks, GA and evolutionary computing, applications, knowledge representation, data encryption, distributed computing, data analytics and visualization, knowledge representation, wireless sensor networks, MEM sensor design, analog circuit, statistical machine translation, cellular automata and antenna design. The volume has 31 chapters, including an invited paper on swarm robotics, grouped into three parts, viz., Advanced Computing, Communication Technologies, and Micro Electronics and Antenna Design. The volume is directed to researchers and practitioners aspiring to solve practical issues, particularly applications of the theories of computational intelligence, using recent advances in computing and communication technologies.
 
Book
This book highlights recent research on bio-inspired computing and its various innovative applications in information and communication technologies. It presents 38 high-quality papers from the 10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2019) and 9th World Congress on Information and Communication Technologies (WICT 2019), which was held at GIET University, Gunupur, India, on December 16–18, 2019. As a premier conference, IBICA–WICT brings together researchers, engineers and practitioners whose work involves bio-inspired computing, computational intelligence and their applications in information security, real-world contexts, etc. Including contributions by authors from 18 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
 
Book
Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘16 hopes to contribute to this effort promoting this fruitful interaction. PACBB'16 technical program included 21 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly promote the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work being developed by each of the participants.
 
Book
This book contains a collection of the papers accepted by the CENet2020 – the 10th International Conference on Computer Engineering and Networks held on October 16-18, 2020 in Xi’an, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.
 
Book
This book intends to bring together researchers and developers from industry, the education field, and the academic world to report on the latest scientific research, technical advances, and methodologies. The 10th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning is hosted by the University of L’Aquila and is going to be held in L’Aquila (Italy). Initially planned on the 17th to the 19th of June 2020, it was postponed to the 7th to the 9th of October 2020, due to the COVID-19 outbreak. The 10th edition of this conference and its related workshops expand the topics of the evidence-based TEL workshops series in order to provide an open forum for discussing intelligent systems for TEL, their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone solutions, or web-based ones. This bridge has been realized also thanks to the sponsor of this edition of MIS4TEL: the Armundia Group https://www.armundia.com, the support from national associations (AEPIA, APPIA, CINI, and EurAI), and organizers (UNIVAQ, UNIROMA1, UNIBZ, UCV, UFSC, USAL, AIR institute, UNC, and UNIBA)
 
Book
This book features contributions to the XVIIth International Conference “Linguistic and Cultural Studies: Traditions and Innovations” (LKTI 2017), providing insights into theory, research, scientific achievements, and best practices in the fields of pedagogics, linguistics, and language teaching and learning with a particular focus on Siberian perspectives and collaborations between academics from other Russian regions. Covering topics including curriculum development, designing and delivering courses and vocational training, the book is intended for academics working at all levels of education striving to improve educational environments in their context – school, tertiary education and continuous professional development.
 
Book
The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
 
Chapter
In the age of dynamic development of information and communication technologies, students get bored quickly and easily lose their interest and motivation for learning when the taught material gets presented in the traditional ways. The purpose of the following study is to determine the level of impact of gamification on the process of studying Mathematics, and on the emotional condition of students with certain motivation and learning styles. The results of the study show that the evaluation and implementation of the gamification, achieved with the usage of Kahoot! in the process of studying Mathematics, do not affect the academic achievements of students with low intrinsic motivation in terms of studying mathematics, however, positively affect their emotional state, stimulate their interest and promote active learning.
 
Book
This book highlights recent research results in Bio-Inspired Computing and Applications. It presents 33 selected papers from the 8th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2017), which was held in Marrakesh, Morocco from December 11 to 13, 2017. A premier conference in the nature-inspired computing field, IBICA is intended to bring together the world’s leading researchers and practitioners interested in advancing the state of the art in biologically inspired computing, allowing them to exchange notes on a broad range of disciplines. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
 
Book
This volume contains the papers presented at the Eleventh Flexible Query Answering Systems 2015 (FQAS-2015) held on October 26-28, 2015 in Cracow, Poland. The international conferences on Flexible Query Answering Systems (FQAS) are a series of premier conferences focusing on the key issue in the information society of providing easy, flexible, and intuitive access to information and knowledge to everybody, even people with a very limited computer literacy. In targeting this issue, the Conference draws on several research areas, such as information retrieval, database management, information filtering, knowledge representation, soft computing, management of multimedia information, and human-computer interaction. The Conference provides a unique opportunity for researchers, developers and practitioners to explore new ideas and approaches in a multidisciplinary forum.
 
Top-cited authors
Aboul Ella Hassanien
  • Cairo University
Aafaf Ouaddah
  • Institut National des Postes et Télécommunications
Juan Manuel Corchado Rodríguez
  • Universidad de Salamanca - AIR Institure
Aleksei Bogoviz
  • independent researcher
Hasmat Malik
  • BEARS Singapore