Search results for: corporate memory

Authors: M. Tarafdar Haque, A. Taheri

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Application of neural networks in execution of programmed pulse width modulation (PPWM) of a voltage source inverter (VSI) is studied in this paper. Using the proposed method it is possible to cancel out the desired harmonics in output of VSI in addition to control the magnitude of fundamental harmonic, contineously. By checking the non-trained values and a performance index, the most appropriate neural network is proposed. It is shown that neural networks may solve the custom difficulties of practical utilization of PPWM such as large size of memory, complex digital circuits and controlling the magnitude of output voltage in a discrete manner.

Keywords: Neural Network, Inverter, PPWM.

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Authors: Hanh Huu Hoang, Tho Manh Nguyen

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Ever increasing capacities of contemporary storage devices inspire the vision to accumulate (personal) information without the need of deleting old data over a long time-span. Hence the target of SemanticLIFE project is to create a Personal Information Management system for a human lifetime data. One of the most important characteristics of the system is its dedication to retrieve information in a very efficient way. By adopting user demands regarding the reduction of ambiguities, our approach aims at a user-oriented and yet powerful enough system with a satisfactory query performance. We introduce the query system of SemanticLIFE, the Virtual Query System, which uses emerging Semantic Web technologies to fulfill users- requirements.

Keywords: Ontology-based Information Retrieval, Digital Memories, SemanticLIFE.

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Authors: Varun Gupta, Ankit Pandey

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Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.

Keywords: Crude oil price prediction, deep learning, LSTM, recurrent neural networks.

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Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mohamad Teshnelab, Ehsan Shahamatnia

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The anti-lock braking systems installed on vehicles for safe and effective braking, are high-order nonlinear and timevariant. Using fuzzy logic controllers increase efficiency of such systems, but impose a high computational complexity as well. The main concept introduced by this paper is reducing computational complexity of fuzzy controllers by deploying problem-solution data structure. Unlike conventional methods that are based on calculations, this approach is based on data oriented modeling.

Keywords: ABS, Fuzzy controller, PSDS, Time-Memory tradeoff, Data oriented modeling.

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Authors: J.H. Park, S. Lakshmanan, H.Y. Jung, S.M. Lee

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This paper is concerned with the delay-distributiondependent stability criteria for bidirectional associative memory (BAM) neural networks with time-varying delays. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, a delay-probability-distribution-dependent sufficient condition is derived to achieve the globally asymptotically mean square stable of the considered BAM neural networks. The criteria are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Finally, a numerical example and its simulation is given to demonstrate the usefulness and effectiveness of the proposed results.

Keywords: BAM neural networks, Probabilistic time-varying delays, Stability criteria.

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Authors: Shigeaki Sakurai, Ryohei Orihara

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This paper proposes an improvement method of classification efficiency in a classification model. The model is used in a risk search system and extracts specific labels from articles posted at bulletin board sites. The system can analyze the important discussions composed of the articles. The improvement method introduces ensemble learning methods that use multiple classification models. Also, it introduces expressions related to the specific labels into generation of word vectors. The paper applies the improvement method to articles collected from three bulletin board sites selected by users and verifies the effectiveness of the improvement method.

Keywords: Text mining, Risk search system, Corporate reputation, Bulletin board site, Ensemble learning

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Authors: Pavol Molnar, Martin Dolinsky

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Paper deals with environmental metrics and assessment systems devoted to Small and Medium Sized Enterprises. Authors are presenting proposed assessment model which has an ability to discover current environmental strengths and weaknesses of Small and Middle Sized Enterprise. Suggested model has also an ambition to become a Sustainability Decision Tool. Model is able to identify "best environmental devision" in the company, and to quantify how this decision contributed into overall environmental improvement. Authors understand environmental improvements as environmental innovations (product, process and organizational). Suggested model is based on its own concept; however, authors are also utilizing already existing environmental assessment tools.

Keywords: Corporate Social Responsibility, (e)IMPACT model, Environmental metrics, , Small and Middle Sized Enterprises

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Authors: S.Aranganayagi, K.Thangavel

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Clustering categorical data is more complicated than the numerical clustering because of its special properties. Scalability and memory constraint is the challenging problem in clustering large data set. This paper presents an incremental algorithm to cluster the categorical data. Frequencies of attribute values contribute much in clustering similar categorical objects. In this paper we propose new similarity measures based on the frequencies of attribute values and its cardinalities. The proposed measures and the algorithm are experimented with the data sets from UCI data repository. Results prove that the proposed method generates better clusters than the existing one.

Keywords: Clustering, Categorical, Incremental, Frequency, Domain

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Authors: Anjali Sadanand, R. V. Nagarajan

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Architecture morphs with advances in technology and the roof, wall, and floor as basic elements of a building, follow in redefining themselves over time. Their contribution is bound by time and held by design principles that deal with function, sturdiness, and beauty. Architecture engages with people to give joy through its form, material, design structure, and spatial qualities. This paper attempts to re-interpret John Ruskin’s “Seven lamps of Architecture” in the context of the architecture of the modern and present period. The paper focuses on the “wall” as an element of study in this context. Four of Ruskin’s seven lamps will be discussed, namely beauty, truth, life, and memory, through examples of architecture ranging from modernism to contemporary architecture of today. The study will focus on the relevance of Ruskin’s principles to the “wall” in specific, in buildings of different materials and over a range of typologies from all parts of the world. Two examples will be analyzed for each lamp. It will be shown that in each case, there is relevance to the significance of Ruskin’s lamps in modern and contemporary architecture. Nature to which Ruskin alludes to for his lamp of “beauty” is found in the different expressions of interpretation used by Corbusier in his Villa Stein façade based on proportion found in nature and in the direct expression of Toyo Ito in his translation of an understanding of the structure of trees into his façade design of the showroom for a Japanese bag boutique. “Truth” is shown in Mies van der Rohe’s Crown Hall building with its clarity of material and structure and Studio Mumbai’s Palmyra House, which celebrates the use of natural materials and local craftsmanship. “Life” is reviewed with a sustainable house in Kerala by Ashrams Ravi and Alvar Aalto’s summer house, which illustrate walls as repositories of intellectual thought and craft. “Memory” is discussed with Charles Correa’s Jawahar Kala Kendra and Venturi’s Vana Venturi house and discloses facades as text in the context of its materiality and iconography. Beauty is reviewed in Villa Stein and Toyo Ito’s Branded Retail building in Tokyo. The paper thus concludes that Ruskin’s Lamps can be interpreted in today’s context and add richness to meaning to the understanding of architecture.

Keywords: Beauty, design, façade, modernism.

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Authors: Mehdi Shami Zanjani, Roshanak Rouzbehani, Hosein Dabbagh

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Although current competitive challenges induced by today-s digital economy place their main emphasis on organizational knowledge, customer knowledge has been overlooked. On the other hand, the business community has finally begun to realize the important role customer knowledge can play in the organizational boundaries of the corporate arena. As a result, there is an emerging market for the tools and utilities whose objective is to provide the intelligence for knowledge sharing between the businesses and their customers. In this paper, we present a conceptual model of customer knowledge management by identifying and analyzing the existing tools in the market. The focus will be upon the emerging British dotcom industry whose customer based B2C behavior has been an influential part of the knowledge based intelligence tools in existence today.

Keywords: Customer knowledge, customer knowledge management, knowledge management, B2C E-commerce.

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Authors: Y. Bentoutou

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On-board Error Detection and Correction (EDAC) devices aim to secure data transmitted between the central processing unit (CPU) of a satellite onboard computer and its local memory. This paper presents a comparison of the performance of four low complexity EDAC techniques for application in Random Access Memories (RAMs) on-board small satellites. The performance of a newly proposed EDAC architecture is measured and compared with three different EDAC strategies, using the same FPGA technology. A statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard Alsat-1 is given for a period of 8 years

Keywords: Error Detection and Correction; On-board computer; small satellite missions

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Authors: Mario Spremić

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Despite the financial crisis and ongoing need for cost cutting, companies all around the world heavily invest in Information Systems (IS) and underlying Information Technology (IT). Proliferation of governance of enterprise IT helps companies manage, or rather, governs IS as a primary business function with executive management involved in making decision about IS and IT. The business value of IT is raising with the involvement of the executive management in IT decision making process and quality IT governance mechanisms in place. In this paper the practice of governing the enterprise IT will be investigated on a sample of the largest 100 Croatian companies. Research questions posed here will reveal if there are some formal IT governance mechanisms, are there any differences in perceived role of IS and IT between CIOs (Chief Information Officers) and CEOs (Chief Executive Officers) of the sampled companies and what are the mechanisms to govern massive investment in enterprise IT.

Keywords: IT governance, governance of enterprise IT, information system auditing, IT maturity.

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Authors: Heesung Lee, Joonkyung Sung, Euntai Kim

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This paper proposes a method which reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory error correction code. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting codes. The genetic algorithm is employed to solve the non linear power optimization problem. The method is applied to two commonly used SEC-DED codes: standard Hamming and odd column weight Hsiao codes. Experiments were performed to show the performance of the proposed method.

Keywords: Error correcting codes, genetic algorithm, non-linearpower optimization, Hamming code, Hsiao code.

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Authors: Aytunc Durlanik, Ibrahim Sogukpinar

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SIP (Session Initiation Protocol), using HTML based call control messaging which is quite simple and efficient, is being replaced for VoIP networks recently. As for authentication and authorization purposes there are many approaches and considerations for securing SIP to eliminate forgery on the integrity of SIP messages. On the other hand Elliptic Curve Cryptography has significant advantages like smaller key sizes, faster computations on behalf of other Public Key Cryptography (PKC) systems that obtain data transmission more secure and efficient. In this work a new approach is proposed for secure SIP authentication by using a public key exchange mechanism using ECC. Total execution times and memory requirements of proposed scheme have been improved in comparison with non-elliptic approaches by adopting elliptic-based key exchange mechanism.

Keywords: SIP, Elliptic Curve Cryptography, voice over IP.

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Authors: Wen-Bao Qiao, Jean-Charles Créput

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To accelerate the solution for large scale traveling salesman problems (TSP), a parallel 2-opt local search algorithm with simple implementation based on Graphics Processing Unit (GPU) is presented and tested in this paper. The parallel scheme is based on technique of data decomposition by dynamically assigning multiple K processors on the integral tour to treat K edges’ 2-opt local optimization simultaneously on independent sub-tours, where K can be user-defined or have a function relationship with input size N. We implement this algorithm with doubly linked list on GPU. The implementation only requires O(N) memory. We compare this parallel 2-opt local optimization against sequential exhaustive 2-opt search along integral tour on TSP instances from TSPLIB with more than 10000 cities.

Keywords: Doubly linked list, parallel 2-opt, tour division, GPU.

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Authors: Earleen Jane Fuentes, Regeene Melarese Lim, Franklin Benjamin Tapia, Alexis Pantola

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Mobile Ad-hoc Network (MANET) is an infrastructure-less network of mobile devices, also known as nodes. These nodes heavily rely on each other’s resources such as memory, computing power, and energy. Thus, some nodes may become selective in forwarding packets so as to conserve their resources. These nodes are called misleading nodes. Several reputation-based techniques (e.g. CORE, CONFIDANT, LARS, SORI, OCEAN) and acknowledgment-based techniques (e.g. TWOACK, S-TWOACK, EAACK) have been proposed to detect such nodes. These techniques do not appropriately punish misleading nodes. Hence, this paper addresses the limitations of these techniques using a system called MINDRA.

Keywords: Mobile ad-hoc network, selfish nodes, reputation-based techniques, acknowledgment-based techniques.

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Authors: Zhang Xiuping, Yang Guowu, Zheng Desheng

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Embedded hardware simulator is a valuable computeraided tool for embedded application development. This paper focuses on the ARM926EJ-S MMU, builds state transition models and formally verifies critical properties for the models. The state transition models include loading instruction model, reading data model, and writing data model. The properties of the models are described by CTL specification language, and they are verified in VIS. The results obtained in VIS demonstrate that the critical properties of MMU are satisfied in the state transition models. The correct models can be used to implement the MMU component in our simulator. In the end of this paper, the experimental results show that the MMU can successfully accomplish memory access requests from CPU.

Keywords: MMU, State transition, Model, Simulation.

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Authors: Mario Mastriani

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In this work, we developed the concept of supercompression, i.e., compression above the compression standard used. In this context, both compression rates are multiplied. In fact, supercompression is based on super-resolution. That is to say, supercompression is a data compression technique that superpose spatial image compression on top of bit-per-pixel compression to achieve very high compression ratios. If the compression ratio is very high, then we use a convolutive mask inside decoder that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. Specifically, the mentio-ned mask is coded inside texture memory of a GPGPU.

Keywords: General-Purpose computation on Graphics Processing Units, Image Compression, Interpolation, Super-resolution.

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Authors: A. Evans, M. McKinley

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Knowledge management (KM) is generally considered to be a positive process in an organisation, facilitating opportunities to achieve competitive advantage via better quality information handling, compilation of expert know-how and rapid response to fluctuations in the business environment. The KM paradigm as portrayed in the literature informs the processes that can increase intangible assets so that corporate knowledge is preserved. However, in some instances, knowledge management exists in a universe of dynamic tension among the conflicting needs to respect privacy and intellectual property (IP), to guard against data theft, to protect national security and to stay within the laws. While the Knowledge Management literature focuses on the bright side of the paradigm, there is also a different side in which knowledge is distorted, suppressed or misappropriated due to personal or organisational motives (the paradox). This paper describes the ethical paradoxes that occur within the taxonomy and deontology of knowledge management and suggests that recognising both the promises and pitfalls of KM requires wisdom.

Keywords: business ethics, data, knowledge, knowledgemanagement, privacy, protection.

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Authors: Chengxuan Geng, Haitao E, Yijie Jiang

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According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.

Keywords: private listed companies, debt financing, business performance

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Authors: Blandina Šramová, Gabriela Kučeráková

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The paper is intended to declare and apply ethics, i. e. moral principles, rules in marketing environment. Ethical behavior of selected pharmaceutical companies in the Slovak Republic is the object of our research. The aim of our research is to determine perception of ethical behavior of the pharmaceutical industry in Slovakia by the medicine representatives in comparison with the assessment of doctors and patients. The experimental sample included 90 participants who were divided into three groups: medicine representatives of the pharmaceutical companies (N=30), doctors (N=30) and patients (N=30). The research method was a Questionnaire of ethical behavior, created by us, that describes individual areas included in the Code of ethics of the pharmaceutical industry in Slovakia. The results showed influence of professional status on ethical behavior perception, not gender. Higher perception was indicated at patients rather than doctors and medicine representatives.

Keywords: Ethics, corporate social responsibility, marketing, pharmaceutical industry.

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Authors: Isaias Ramirez, Jose Luis Silva, Carlos Gonzalez, Gustavo Candelaria, Jose Pepe Rasgado, Carlos Carrillo

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This paper presents the experience in an eLearning training project that is being implemented for electrical planning engineers from the national Mexican utility Comision Federal de Electricidad (CFE) Distribution. This modality is implemented and will be used in the utility for training purposes to help personnel in their daily technical activities. One important advantage of this training project is that once it is implemented and applied, financial resources will be saved by CFE Distribution Company because online training will be used in all the country; the infrastructure for the eLearning training will be uploaded in computational servers installed in the National CFE Distribution Training Department, in Ciudad de Mexico, and can be used in workplaces of 16 Distribution Divisions and 150 Zones of CFE Distribution. In this way, workers will not need to travel to the National Training Department, saving enormous efforts, financial, and human resources.

Keywords: Moodle, eLearning, corporate training, electrical planning engineer.

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Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. Noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: Chaotic behavior, wavelet, noise reduction, river flow.

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Authors: L. N. A. C. Jayawardena, Ales Gregar

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Emotional Intelligence (EI) has been identified as an important factor for corporate success. However, there are few empirical findings on the impact of Strategic EI per se. The ooverall objective of the study was to empirically examine the relationship between the Strategic EI and Transformational Leadership style of managers. Sixty four managers were selected from the banking industry in Czech Republic. Genos EI Inventory, and the Multifactor Leadership Questionnaire – Form 5X-Short were employed as the major research instruments of the study. Descriptive and inferential analyses of survey data were conducted using SPSS software. Variations were observed among the components of Strategic EI between males, and females. Study concludes positive a relationship between Strategic EI of Czech managers and their transformational leadership style. Improving awareness and usage of EI, will contribute to facilitate career success through enhanced levels of transformational leadership of managers.

Keywords: Strategic Emotional Intelligence, Transformational leadership, Socio-demographic factors.

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Authors: Anayochukwu Leonard Okoli

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The nexus between language and culture is so intertwined and very significant that language is largely seen as a vehicle for cultural transmission. Culture itself refers to the aggregate belief system of a people, embellishing its corporate national image or brand. If we conceive national rebranding as a campaign to rekindle the patriotic flame in the consciousness of a people towards its sociocultural imperatives and values, then, Nigerian indigenous linguistic flame has not been ignited. Consequently, the paper contends that the current national rebranding policy remains a myth in the confines of the elitists' intellectual squabble. It however recommends that the use of our indigenous languages should be supported by adequate legislation and also propagated by Nollywood in order to revamp and sustain the people’s interest in their local languages. Finally, the use of the indigenous Nigerian languages demonstrates patriotism, an important ingredient for actualizing a genuine national rebranding.

Keywords: Appraisal, Indigenous Languages, Policy, Rebranding.

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Authors: Muazzam A. Khan, Ghalib A. Shah, Muhammad Sher

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Wireless sensor network is formed with the combination of sensor nodes and sink nodes. Recently Wireless sensor network has attracted attention of the research community. The main application of wireless sensor network is security from different attacks both for mass public and military. However securing these networks, by itself is a critical issue due to many constraints like limited energy, computational power and lower memory. Researchers working in this area have proposed a number of security techniques for this purpose. Still, more work needs to be done.In this paper we provide a detailed discussion on security in wireless sensor networks. This paper will help to identify different obstacles and requirements for security of wireless sensor networks as well as highlight weaknesses of existing techniques.

Keywords: Wireless senor networks (WSNs), security, denial of service, black hole, cryptography, stenography.

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Authors: Ju-Chun Chien

Abstract:

The validity of Herzberg-s Two-Factor Theory of Motivation was tested empirically by surveying 2372 chemical fiber employees in 2012. In the valid sample of 1875 respondents, the degree of overall job satisfaction was more than moderate. The most highly valued components of job satisfaction were: “corporate image," “collaborative working atmosphere," and “supervisor-s expertise"; whereas the lowest mean score was 34.65 for “job rotation and promotion." The top three job retention options rated by the participants were “good image of the enterprise," “good compensation," and “workplace is close to my residence." The overall evaluation of the level of thriving facilitation workplace reached almost to “mostly agree." For those participants who chose at least one motivator as their job retention options had significantly greater job satisfaction than those who chose only hygiene factors as their retention options. Therefore, Herzberg-s Two-Factor Theory of Motivation was proven valid in this study.

Keywords: Employee job satisfaction, Job retention, Traditional business, Two-factor theory of motivation.

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Authors: Zhenhuan Zhu, David Mulvaney, Vassilios Chouliaras

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This paper presents a novel genetic algorithm, termed the Optimum Individual Monogenetic Algorithm (OIMGA) and describes its hardware implementation. As the monogenetic strategy retains only the optimum individual, the memory requirement is dramatically reduced and no crossover circuitry is needed, thereby ensuring the requisite silicon area is kept to a minimum. Consequently, depending on application requirements, OIMGA allows the investigation of solutions that warrant either larger GA populations or individuals of greater length. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of existing hardware GA implementations. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space.

Keywords: Genetic algorithms, hardware-based machinelearning.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Constantin Pehoiu, Cristian Savu, Silviu Badea, Cristian Borida

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The physiological effects of physical exercise on human body are relatively well known in literature, which describes in detail the changes that occur in the cardiovascular system, the respiratory one, in bones and other systems, both during exercise and after its delivery. However, the effects of exercise on mental processes are less treated. From the literature reviews discussed in this study, it can be detached the idea that we can not exactly say that physical exercise has beneficial effects on mental processes, but neither that it would have potentially negative effects. This uncertainty, reflected in the inability to indicate precise and unequivocal meaning, favorable-unfavorable physical effort in acting on mental processes, is a prime reason to undertake a study of the phenomenon influence effort administered physical education classes on the dynamics of mental processes like attention and memory.

Keywords: management, exercise, mental process, lesson.

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