Search results for: sign language recognition

Authors: A. K. Al-Othman, K. M. EL-Nagger

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Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: Juliana Panova

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Severe symptoms, such as dissociation, depersonalization, self-mutilation, suicidal ideations and gestures, are the main reasons for a person to be diagnosed with Borderline Personality Disorder (BPD) and admitted to an inpatient Psychiatric Hospital. However, these symptoms are also indicators of a severe traumatic history as indicated by the extensive research on the topic. Unfortunately patients with such clinical presentation often are treated repeatedly only for their symptomatic behavior, while the main cause for their suffering, the trauma itself, is usually left unaddressed therapeutically. All of the highly structured, replicable, and manualized treatments lack the recognition of the uniqueness of the person and fail to respect his/her rights to experience and react in an idiosyncratic manner. Thus the communicative and adaptive meaning of such symptomatic behavior is missed. Only its pathological side is recognized and subjected to correction and stigmatization, and the message that the person is damaged goods that needs fixing is conveyed once again. However, this time the message would be even more convincing for the victim, because it is sent by mental health providers, who have the credibility to make such a judgment. The result is a revolving door of very expensive hospitalizations for only a temporary and patchy fix. In this way the patients, once victims of abuse and hardship are left invalidated and thus their re-victimization is perpetuated in their search for understanding and help. Keywordsborderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

Keywords: borderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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Authors: Akie Nimiya, Tomoyuki Yokogawa, Hisashi Miyazaki, Sousuke Amasaki, Yoichiro Sato, Michiyoshi Hayase

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In this paper, we proposed a method for detecting consistency violation between UML state machine diagrams and communication diagrams using Alloy. Using input language of Alloy, the proposed method expresses system behaviors described by state machine diagrams, message sequences described by communication diagrams, and a consistency property. As a result of application for an example system, we confirmed that consistency violation could be detected using Alloy correctly.

Keywords: Model checking, UML, state machine diagrams, communication diagram, alloy.

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: Artificial neural networks, digital image processing, pattern recognition.

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel. The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. Message Passing Interface (MPI) and Open Computing Language (OpenCL) is used to achieve task and pixel level parallelism respectively.

Keywords: Edge detection, multicore, GPU, openCL, MPI.

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Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny

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Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Keywords: Cancer, metabolites, metabolic pathway, signaling pathway.

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Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: Corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism.

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Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

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Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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Authors: Rodrigo Chandia, Mauricio Papa

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Efforts to secure supervisory control and data acquisition (SCADA) systems must be supported under the guidance of sound security policies and mechanisms to enforce them. Critical elements of the policy must be systematically translated into a format that can be used by policy enforcement components. Ideally, the goal is to ensure that the enforced policy is a close reflection of the specified policy. However, security controls commonly used to enforce policies in the IT environment were not designed to satisfy the specific needs of the SCADA environment. This paper presents a language, based on the well-known XACML framework, for the expression of authorization policies for SCADA systems.

Keywords: Access policy specification, process control systems, network security.

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Authors: Antonio Di Leva, Roberto Berchi, Gianpiero Pescarmona, Michele Sonnessa

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The aim of a biological model is to understand the integrated structure and behavior of complex biological systems as a function of the underlying molecular networks to achieve simulation and forecast of their operation. Although several approaches have been introduced to take into account structural and environment related features, relatively little attention has been given to represent the behavior of biological systems. The Abstract Biological Process (ABP) model illustrated in this paper is an object-oriented model based on UML (the standard object-oriented language). Its main objective is to bring into focus the functional aspects of the biological system under analysis.

Keywords: Biological processes, system dynamics, systemmodeling, UML.

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Authors: Dyah Iswantini, Trivadila, Novik Nurhidayat, Waras Nurcholis

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The antioxidant compounds are needed for the food, beverages, and pharmaceuticals industry. For this purpose, an appropriate method is required to measure the antioxidant properties in various types of samples. Spectrophotometric method usually used has some weaknesses, including the high price, long sample preparation time, and less sensitivity. Among the alternative methods developed to overcome these weaknesses is antioxidant biosensor based on superoxide dismutase (SOD) enzyme. Therefore, this study was carried out to measure the SOD activity originating from Deinococcus radiodurans and to determine its kinetics properties. Carbon paste electrode modified with ferrocene and immobilized SOD exhibited anode and cathode current peak at potential of +400 and +300mv respectively, in both pure SOD and SOD of D. radiodurans. This indicated that the current generated was from superoxide catalytic dismutation reaction by SOD. Optimum conditions for SOD activity was at pH 9 and temperature of 27.50C for D. radiodurans SOD, and pH 11 and temperature of 200C for pure SOD. Dismutation reaction kinetics of superoxide catalyzed by SOD followed the Lineweaver-Burk kinetics with D. radiodurans SOD KMapp value was smaller than pure SOD. The result showed that D. radiodurans SOD had higher enzyme-substrate affinity and specificity than pure SOD. It concluded that D. radiodurans SOD had a great potential as biological recognition component for antioxidant biosensor.

Keywords: Antioxidant biosensor, Deinococcus radiodurans, enzyme kinetic, superoxide dismutase (SOD).

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Authors: Solehah Yaacob

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The study focuses on revisiting the effectiveness of Critical Thinking in human mind capability as a major faculty in human life. The tool used as a measurement of this knowledge ability consists of several processes including experience and education background. To emphasize the `Overview` concept, the researcher highlights two major aspects of philosophical approach, they are; Divine Revelation Concept and Modern Scientific Theory. The research compares between the both parties to introduce the Divine Revelation into Modern Scientific theory. An analytical and critical study of the both concepts become the methodology of the discussion.

Keywords: Critical thinking, knowledge, intellectual, language.

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Authors: Pavel Adámek

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This study examines perception of environmental approach in small and medium-sized enterprises (SMEs) – the process by which firms integrate environmental concern into business. Based on a review of the literature, the paper synthesizes focus on environmental issues with the reflection in a case study in the Czech Republic. Two themes of corporate environmentalism are discussed – corporate environmental orientation and corporate stances toward environmental concerns. It provides theoretical material on greening organizational culture that is helpful in understanding the response of contemporary business to environmental problems. We integrate theoretical predictions with empirical findings confronted with reality. Scales to measure these themes are tested in a survey of managers in 229 Czech firms. We used the process of in-depth questioning. The research question was derived and answered in the context of the corresponding literature and conducted research. A case study showed us that environmental approach is variety different (depending on the size of the firm) in SMEs sector. The results of the empirical mapping demonstrate Czech company’s approach to environment and define the problem areas and pinpoint the main limitation in the expansion of environmental aspects. We contribute to the debate for recognition of the particular role of environmental issues in business reality.

Keywords: Corporate environmentalism, Czech Republic, empirical mapping, environmental performance.

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

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Authors: Atena Sajedin, Shokoufeh Zakernejad, Soheil Faridi, Mehrdad Javadi, Reza Ebrahimpour

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This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then feature extraction module extracts 10 ECG morphological features and one timing interval feature. Then a number of multilayer perceptrons (MLPs) neural networks with different topologies are designed. The performance of the different combination methods as well as the efficiency of the whole system is presented. Among them, Stacked Generalization as a proposed trainable combined neural network model possesses the highest recognition rate of around 95%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems. ECG samples attributing to the different ECG beat types were extracted from the MIT-BIH arrhythmia database for the study.

Keywords: ECG beat Classification; Combining Classifiers;Premature Ventricular Contraction (PVC); Multi Layer Perceptrons;Wavelet Transform

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

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LABVIEW is a graphical programming language that has its roots in automation control and data acquisition. In this paper we have utilized this platform to provide a powerful toolset for process identification and control of nonlinear systems based on artificial neural networks (ANN). This tool has been applied to the monitoring and control of a lab-scale distillation column DELTALAB DC-SP. The proposed control scheme offers high speed of response for changes in set points and null stationary error for dual composition control and shows robustness in presence of externally imposed disturbance.

Keywords: Distillation, neural networks, LABVIEW, monitoring, identification, control.

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Authors: Baharak Mousapour

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Creating public spaces which are tailored for the specific demands of the individuals is one of the challenges for the contemporary interior designers. Improving the general knowledge as well as providing a forum for all walks of life to exploit is one of the objectives of a public library. In this regard, interior design in consistent with the demands of the individuals is of paramount importance. Seemingly, study spaces, in particular, those in close relation to the personalized sector, have proven to be challenging, according to the literature. To address this challenge, attributes of individuals, namely, perception of people from public spaces and their interactions with the so-called spaces, should be analyzed to provide interior designers with something to work on. This paper follows the analytic-descriptive research methodology by outlining case study libraries which have personalized public libraries with the investigation of the type of personalization as its primary objective and (I) recognition of physical schedule and the know-how of the spatial connection in indoor design of a library and (II) analysis of each personalized space in relation to other spaces of the library as its secondary objectives. The significance of the current research lies in the concept of personalization as one of the most recent methods of attracting people to libraries. Previous research exists in this regard, but the lack of data concerning personalization makes this topic worth investigating. Hence, this study aims to put forward approaches through real-case studies for the designers to deal with this concept.

Keywords: interior design, library, library design, personalization

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Authors: Mohd Kamir Yusof, Suhailan Dato' Safei

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Images are important in disease research, education, and clinical medicine. This paper presents a Web Service Platform (WSP) for support multiple programming languages to access image from biomedical databases. The main function WSP is to allow web users access image from biomedical databases. The WSP will receive web user-s queries. After that, it will send to Querying Server (QS) and the QS will search and retrieve data from biomedical databases. Finally, the information will display to the web users. Simple application is developed and tested for experiment purpose. Result from experiment indicated WSP can be used in biomedical environment.

Keywords: Biomedical, Image, Web Service Platform

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Authors: Tae in Seol, Sun-Tae Chung, Seongwon Cho

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Realistic 3D face model is desired in various applications such as face recognition, games, avatars, animations, and etc. Construction of 3D face model is composed of 1) building a face shape model and 2) rendering the face shape model. Thus, building a realistic 3D face shape model is an essential step for realistic 3D face model. Recently, 3D morphable model is successfully introduced to deal with the various human face shapes. 3D dense correspondence problem should be precedently resolved for constructing a realistic 3D dense morphable face shape model. Several approaches to 3D dense correspondence problem in 3D face modeling have been proposed previously, and among them optical flow based algorithms and TPS (Thin Plate Spline) based algorithms are representative. Optical flow based algorithms require texture information of faces, which is sensitive to variation of illumination. In TPS based algorithms proposed so far, TPS process is performed on the 2D projection representation in cylindrical coordinates of the 3D face data, not directly on the 3D face data and thus errors due to distortion in data during 2D TPS process may be inevitable. In this paper, we propose a new 3D dense correspondence algorithm for 3D dense morphable face shape modeling. The proposed algorithm does not need texture information and applies TPS directly on 3D face data. Through construction procedures, it is observed that the proposed algorithm constructs realistic 3D face morphable model reliably and fast.

Keywords: 3D Dense Correspondence, 3D Morphable Face Shape Model, 3D Face Modeling.

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Authors: N. Mantalay, N. Chakpitak, W. Janchai, P. Sureepong

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Work-life balance has been acknowledged and promoted for the sake of employee retention. It is essential for a manager to realize the human resources situation within a company to help employees work happily and perform at their best. This paper suggests knowledge management and critical thinking are useful to motivate employees to think about their work-life balance. A qualitative case study is presented, which aimed to discover the meaning of work-life balance-s meaning from the perspective of Thai knowledge workers and how it affects their decision-making towards work resignation. Results found three types of work-life balance dimensions; a work- life balance including a workplace and a private life setting, an organizational working life balance only, and a worklife balance only in a private life setting. These aspects all influenced the decision-making of the employees. Factors within a theme of an organizational work-life balance were involved with systematic administration, fair treatment, employee recognition, challenging assignments to gain working experience, assignment engagement, teamwork, relationship with superiors, and working environment, while factors concerning private life settings were about personal demands such as an increasing their salary or starting their own business.

Keywords: knowledge management, work-life balance, knowledge workers, decision-making, critical thinking, diverse workforce

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Authors: Paris Kitsos

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In this paper the FPGA implementations for four stream ciphers are presented. The two stream ciphers, MUGI and SNOW 2.0 are recently adopted by the International Organization for Standardization ISO/IEC 18033-4:2005 standard. The other two stream ciphers, MICKEY 128 and TRIVIUM have been submitted and are under consideration for the eSTREAM, the ECRYPT (European Network of Excellence for Cryptology) Stream Cipher project. All ciphers were coded using VHDL language. For the hardware implementation, an FPGA device was used. The proposed implementations achieve throughputs range from 166 Mbps for MICKEY 128 to 6080 Mbps for MUGI.

Keywords: Cryptography, ISO/IEC 18033-4:2005 standard, Hardware implementation, Stream ciphers

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Authors: Jolanta Brodowska-Szewczuk

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The article includes the results and conclusions from empirical researches that had been done. The research focuses on the impact of investments made in small and medium-sized enterprises financed from EU funds on the competitiveness of these companies. The researches includes financial results in sales revenue and net income, expenses, and many other new products/services on offer, higher quality products and services, more modern methods of production, innovation in management processes, increase in the number of customers, increase in market share, increase in profitability of production and provision of services. The main conclusions are that, companies with direct investments under this measure shall apply the modern methods of production. The consequence of this is to increase the quality of our products and services. Furthermore, both small and medium-sized enterprises have introduced new products and services. Investments were carried out, thus enabling better work organization in enterprises. Entrepreneurs would guarantee higher quality of service, which would result in better relationships with their customers, what is more, noting the rise in number of clients. More than half of the companies indicated that the investments contributed to the increase in market share. Same thing as for market reach and brand recognition of particular company. An interesting finding is that, investments in small enterprises were more effective than medium-sized enterprises.

Keywords: Competitiveness, efficiency, EU funds, small and medium-sized enterprises.

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: Curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering.

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Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

Abstract:

A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: Brain activity, dense EEG, evoked responses, spatiotemporal analysis, SVM, perception.

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Authors: Sapfo A. Mortaki

Abstract:

This article examines the presence of Greek immigrant artists (painters and sculptors) in Paris during 1970-2010. The aim is to highlight their presence in the French capital through archival research in the daily and periodical press as well as present the impact of their artistic activity on the French intellectual life and society. At the same time, their contribution to the development of cultural life in Greece becomes apparent. The integration of those migrant artists into an environment of cultural coexistence and the understanding of the social phenomenon of their migration, in the context of postmodernity, are being investigated. The cultural relations between the two countries are studied in the context of support mechanisms, such as the Greek community, cultural institutions, museums and galleries. The recognition of the Greek artists by the French society and the social dimension in the context of their activity in Paris, are discussed in terms of the assimilation theory. Since the 1970s, and especially since the fall of the dictatorship in Greece, in opposition to the prior situation, artists' contacts with their homeland have been significantly enhanced, with most of them now travelling to Paris, while others work in parallel in both countries. As a result, not only do the stages of the development of their work through their pursuits become visible, but, most importantly, the artistic world becomes informed about the multifaceted expression of art through the succession of various contemporary currents. Thus, the participation of Greek artists in the international cultural landscape is demonstrated.

Keywords: Artistic migration, cultural impact, Greek artists, postmodernity, theory of assimilation.

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Authors: Christhu Raj, Rajeev Sukumaran

Abstract:

In this research article of modeling Underwater Wireless Sensor Network Simulators, we provide a comprehensive overview of the various currently available simulators used in UWSN modeling. In this work, we compare their working environment, software platform, simulation language, key features, limitations and corresponding applications. Based on extensive experimentation and performance analysis, we provide their efficiency for specific applications. We have also provided guidelines for developing protocols in different layers of the protocol stack, and finally these parameters are also compared and tabulated. This analysis is significant for researchers and designers to find the right simulator for their research activities.

Keywords: Underwater Wireless Sensor networks (UWSN), SUNSET, NS2, OPNET, WOSS, DESERT, RECORDS, Aqua- Sim, Aqua- Net Mate.

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