Search results for: knowledge extraction

Authors: G. Schuh, S. Aghassi

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In order to bridge the gap between research and industry, promoting technology and knowledge transfer becomes increasingly important. Especially small- and medium-sized enterprises, having only little R&D resources themselves, depend on external technology development activities for remaining innovative. Academia research on the other hand needs potential industrial partners, who are capable and willing to commercialize their technologies as most public funding programs require some sort of technology transfer or dissemination activities. Modern web technologies offer more and more “social” functionalities and open up new ways of user interaction. In the past years several technology transfer platforms were developed, making use of modern web technologies in order to enable and support technology transfer. In this paper we report on the results of a state-of-the art analyses of existing technology transfer platforms, point out their advantages and deficits and give a perspective to the development of an improved technology transfer platform.

Keywords: Knowledge transfer, social software, technology management, technology transfer.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

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Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.

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Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

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Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm^-1 - 500 cm^-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm^-1), C-H absorption ranging from 2851 to 2924 cm^-1, C=C absorbance (1628 - 1655 cm^-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm^-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia lineari-bracteolata, Ruellia prostrata, Saponins.

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Authors: Wen-Yen Wu, Tsung-Cheng Hsieh, Ching-Sung Lai

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In this paper, we propose a method to extract the road signs. Firstly, the grabbed image is converted into the HSV color space to detect the road signs. Secondly, the morphological operations are used to reduce noise. Finally, extract the road sign using the geometric property. The feature extraction of road sign is done by using the color information. The proposed method has been tested for the real situations. From the experimental results, it is seen that the proposed method can extract the road sign features effectively.

Keywords: Color information, image processing, road sign.

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Authors: Michele V. Carbinatto, Wagner Wey Moreira, Myrian Nunomura; Mariana H. C. Tsukamoto, VilmaLeni Nista-Piccolo

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Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.

Keywords: Sport science, body, complexity theory, corporeity.

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Authors: Turgay Temel, John Hallam

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A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.

Keywords: Classification, neuro-spike coding, non-parametricmodel, parametric model, Gaussian mixture, EM algorithm.

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Authors: Hassan El Maia, Ahmed Hammouch, Driss Aboutajdine

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This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.

Keywords: Color, texture, laws filter, mutual information, SVM, hybrid space.

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Authors: Shuib Rambat, Ruzsyahriman Jenal, John Elgy

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This paper presented the potential of smart phone to provide support on mapping the indoor asset. The advantage of using the smart phone to generate the indoor map is that it has the ability to capture, store and reproduces still or video images; indeed most of us do have this powerful gadget. The captured images usually used by maintenance team to save a record for future reference. Here, these images are used to generate 3D models of an object precisely and accurately for efficient and effective solution in data gathering. Thus, it could be a resource for an informative database in asset management.

Keywords: 3D modeling, Asset Management, Object Extraction, Smart Device

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Authors: Päivi Aarreniemi-Jokipelto, Merja Alanko-Turunen

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The possibilities of mobile technology generate new demands for vocational teacher trainers to transform their approach to work and to incorporate its usage into their ordinary educational practice. This paper presents findings of a focus discussion group (FDG) session on the usage of iPads within a school of vocational teacher education (SoVTE). It aims to clarify how the teacher trainers are using iPads and what has changed in their work during the usage of iPads. The analytical framework bases on content analysis and expansive learning cycle. It was not only found what kind of a role iPads played in their daily practices but it brought also into attention how a cultural change regarding the usage of social media and mobile technology was desperately needed in the whole work community. Thus, the FGD was abducted for developing the knowledge practices of the community of the SoVTE.

Keywords: iPad, mobile learning, vocational teacher education.

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Authors: Mohammadsadegh Zanganehfar

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Since the introduction of fractal geometry in 1970, numerous efforts have been made by architects and researchers to transfer this area of mathematical knowledge in the discipline of architecture and postmodernist discourse. The discourse of complexity and architecture is one of the most significant ongoing discourses in the discipline of architecture from the 70's until today and has generated significant styles such as deconstructivism and parametricism in architecture. During these years, several projects were designed and presented by designers and architects using fractal geometry, but due to the lack of sufficient knowledge and appropriate comprehension of the features and characteristics of this nonlinear geometry, none of the fractal-based designs have been successful and satisfying. Fractal geometry as a geometric technology has a long presence in the history of architecture. The current research attempts to identify and discover the characteristics, features, potentials and functionality of fractals despite their aesthetic aspect by examining case studies of pre-modern architecture in Asia and investigating the function of fractals. 

Keywords: Asian architecture, fractal geometry, fractal technique, geometric properties

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Authors: H. Zainuddin, F. Hanafi, M. H. Hairi, A. Aman, M.H.N. Talib

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This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.

Keywords: Knowledge-based Supplementary Control, Acceleration Feedback, Load Frequency Control, Automatic Generation Control.

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Authors: Sakthi Priya Balaji R., Vijayendar G.

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This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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Authors: Zuzana Dideková, Beata Mikovičová

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Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications

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Authors: Isabel Díez Vial, Marta Fernández Olmoss

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This research tries to analyze the role that knowledge about foreign markets has in increasing firms- exports in clustered spaces. We consider two interrelated sources of knowledge: firms- direct experience and indirect experience from other clustered firms – export externalities. In particular, it is proposed that firms would improve their export performance by accessing to export externalities if they have some previous direct experience that allows them to identify, understand and exploit them. Also, we propose that this positive influence of previous direct experience on export externalities keeps only up to a point, where it becomes negative, creating an inverted “U" shape. Empirical evidence gathered among wine producers located in La Rioja tends to confirm that firms enjoy of export externalities if they have export experience along several years and countries increase their export performance. While this relationship becomes less relevant as they develop a higher experience, we could not confirm the existence of a curvilinear relationship in their influence on export externalities and export performance.

Keywords: Clusters, curvilinear relationship, absorptive capacity

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Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil

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Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.

Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari

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Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Eigen Face, Multidimensional, Matching, PCA.

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Authors: Sam, Ng, Lewis Leighton, Sam Atkinson, Carson Yan, Landan Hu, Leslie Cheung, Brian Yap, Kent Lung, Ketat Sarakune

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This paper presents a method for verifying cryptocurrency reserves that balances the need for both transparency and data confidentiality. Our methodology employs cryptographic techniques, including Merkle Trees, Bulletproof, and zkSnark, to verify that total assets equal or exceed total liabilities, represented by customer funds. Notably, this verification is achieved without disclosing sensitive information such as the total asset value, customer count, or cold wallet addresses. We delve into the construction and implementation of this methodology. While the system is robust and scalable, we also identify areas for potential enhancements to improve its efficiency and versatility. As the digital asset landscape continues to evolve, our approach provides a solid foundation for ensuring continued trust and security in digital asset platforms.

Keywords: Cryptocurrency, crypto-currency, proof-of-reserve, por, zero-knowledge, zkpor.

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Authors: Nobuhiko Hishinuma, Jun Igari, Rentaro Yoshioka

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When programming in languages such as C, Java, etc., it is difficult to reconstruct the programmer's ideas only from the program code. This occurs mainly because, much of the programmer's ideas behind the implementation are not recorded in the code during implementation. For example, physical aspects of computation such as spatial structures, activities, and meaning of variables are not required as instructions to the computer and are often excluded. This makes the future reconstruction of the original ideas difficult. AIDA, which is a multimedia programming language based on the cyberFilm model, can solve these problems allowing to describe ideas behind programs using advanced annotation methods as a natural extension to programming. In this paper, a development environment that implements the AIDA language is presented with a focus on the annotation methods. In particular, an actual scientific numerical computation code is created and the effects of the annotation methods are analyzed.

Keywords: cyberFilm, development environment, knowledge engineering, multimedia programming language

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Authors: Sanpachai Huvanandana

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A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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Authors: Irfan N. Umar, Yong Su-Lyn

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The purpose of this research is to determine the knowledge and skills possessed by instructional design (ID) practitioners in Malaysia. As ID is a relatively new field in the country and there seems to be an absence of any studies on its community of practice, the main objective of this research is to discover the tasks and activities performed by ID practitioners in educational and corporate organizations as suggested by the International Board of Standards for Training, Performance and Instruction. This includes finding out the ID models applied in the course of their work. This research also attempts to identify the barriers and issues as to why some ID tasks and activities are rarely or never conducted. The methodology employed in this descriptive study was a survey questionnaire sent to 30 instructional designers nationwide. The results showed that majority of the tasks and activities are carried out frequently enough but omissions do occur due to reasons such as it being out of job scope, the decision was already made at a higher level, and the lack of knowledge and skills. Further investigations of a qualitative manner should be conducted to achieve a more in-depth understanding of ID practices in Malaysia

Keywords: instructional design, ID competencies, ID models, IBSTPI

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Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

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Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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Authors: Do Thi Ha, Khanitta Nuntaboot

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Background: Competency of nurses is vital to safe nursing practice as well as essential component to drive quality of nursing services. There exists little up to date information concerning actual competency among Vietnamese nurses. Purposes: The purpose of this study is to identify the actual nursing competency among nurses in clinical settings in Vietnam. Methods: A qualitative study, ethnographic method, comprised of the participant-observation, in-depth interview, and focus group discussion with multidisciplinary groups of nurses employing in Cho Ray hospital, Vietnam, managers/administrators, nurse teachers, medical doctors, other health care providers, patients and family members which derived from purposeful sampling technique. Content analysis was used for data analysis. Results: Five essential themes of nursing competencies among nurses were identified include (1) knowledge, (2) skills, (3) attitude and value-based nursing practice, (4) legal and ethical competencies, and (5) transcultural competencies. Basic and advanced knowledge were identified as further two dimensions of knowledge. There were five sub themes identified as further dimensions of skills include technical skills, communication skills, organizing and management skills, teamwork and interrelationship, and critical thinking skills. Conclusions: The findings from this study provide valuable information and understanding of the actual competency among nurses in clinical settings in Vietnam. It is expected that this understanding would assist in developing a guide to nursing education and training, nursing practice and relevant policy regulation used for promoting nursing competency among nurses.

Keywords: Nursing competency, qualitative design, ethnographic method, Vietnam.

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Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam

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The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.

Keywords: Speech Recognition, MFCC, Neural Network, classifier.

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Authors: Madihah Mohd Saudi, Zul Hilmi Abdullah

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This research paper presents a framework on how to build up malware dataset.Many researchers took longer time to clean the dataset from any noise or to transform the dataset into a format that can be used straight away for testing. Therefore, this research is proposing a framework to help researchers to speed up the malware dataset cleaningprocesses which later can be used for testing. It is believed, an efficient malware dataset cleaning processes, can improved the quality of the data, thus help to improve the accuracy and the efficiency of the subsequent analysis. Apart from that, an in-depth understanding of the malware taxonomy is also important prior and during the dataset cleaning processes. A new Trojan classification has been proposed to complement this framework.This experiment has been conducted in a controlled lab environment and using the dataset from VxHeavens dataset. This framework is built based on the integration of static and dynamic analyses, incident response method and knowledge database discovery (KDD) processes.This framework can be used as the basis guideline for malware researchers in building malware dataset.

Keywords: Dataset, knowledge database discovery (KDD), malware, static and dynamic analyses.

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Authors: Shafiq R. Qureshi, Syed Noman Danish, Muhammad Saeed Khalid

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Fossil fuels are the major source to meet the world energy requirements but its rapidly diminishing rate and adverse effects on our ecological system are of major concern. Renewable energy utilization is the need of time to meet the future challenges. Ocean energy is the one of these promising energy resources. Threefourths of the earth-s surface is covered by the oceans. This enormous energy resource is contained in the oceans- waters, the air above the oceans, and the land beneath them. The renewable energy source of ocean mainly is contained in waves, ocean current and offshore solar energy. Very fewer efforts have been made to harness this reliable and predictable resource. Harnessing of ocean energy needs detail knowledge of underlying mathematical governing equation and their analysis. With the advent of extra ordinary computational resources it is now possible to predict the wave climatology in lab simulation. Several techniques have been developed mostly stem from numerical analysis of Navier Stokes equations. This paper presents a brief over view of such mathematical model and tools to understand and analyze the wave climatology. Models of 1st, 2nd and 3rd generations have been developed to estimate the wave characteristics to assess the power potential. A brief overview of available wave energy technologies is also given. A novel concept of on-shore wave energy extraction method is also presented at the end. The concept is based upon total energy conservation, where energy of wave is transferred to the flexible converter to increase its kinetic energy. Squeezing action by the external pressure on the converter body results in increase velocities at discharge section. High velocity head then can be used for energy storage or for direct utility of power generation. This converter utilizes the both potential and kinetic energy of the waves and designed for on-shore or near-shore application. Increased wave height at the shore due to shoaling effects increases the potential energy of the waves which is converted to renewable energy. This approach will result in economic wave energy converter due to near shore installation and more dense waves due to shoaling. Method will be more efficient because of tapping both potential and kinetic energy of the waves.

Keywords: Energy Utilizing, Wave Shoaling Phenomenon

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Authors: Mi Sook Lee

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The number of the companies accepting RFID in Korea has been increased continuously due to the domestic development of information technology. The acceptance of RFID by companies in Korea enabled them to do business with many global enterprises in a much more efficient and effective way. According to a survey[33, p76], many companies in Korea have used RFID for inventory or distribution manages. But, the use of RFID in the companies in Korea is in the early stages and its potential value hasn-t fully been realized yet. At this time, it would be very important to investigate the factors that affect RFID acceptance. For this study, many previous studies were referenced and some RFID experts were interviewed. Through the pilot test, four factors were selected - Security Trust, Employee Knowledge, Partner Influence, Service Provider Trust - affecting RFID acceptance and an extended technology acceptance model(e-TAM) was presented with those factors. The proposed model was empirically tested using data collected from employees in companies or public enterprises. In order to analyze some relationships between exogenous variables and four variables in TAM, structural equation modeling(SEM) was developed and SPSS12.0 and AMOS 7.0 were used for analyses. The results are summarized as follows: 1) security trust perceived by employees positively influences on perceived usefulness and perceived ease of use; 2) employee-s knowledge on RFID positively influences on only perceived ease of use; 3) a partner-s influence for RFID acceptance positively influences on only perceived usefulness; 4) service provider trust very positively influences on perceived usefulness and perceived ease of use 5) the relationships between TAM variables are the same as the previous studies.

Keywords: RFID, TAM, Security Trust, Employee Knowledge, Partner Influence, Service Provider Trust.

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Authors: Bilal Alatas, Ahmet Arslan

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The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

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Authors: Ivana Tadić, Željana Aljinović Barać, Nikolina Plazonić

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Living today in turbulent business environment forces companies to distinguish from each other, securing sustainable competitive growth and competitive advantage. The best possible solution is to invest (effort and financial resources) within companies’ different practices of human resource management (HRM), more specifically in employees’ knowledge, skills and abilities. Applying this approach companies will create enviable level of human capital securing its economic growth. Employees become human capital for their employers at the moment when they contribute with their own knowledge and abilities in creating material and non-material value of the company. The main aim of this research is to explore the relations between human capital investments and business excellence of Croatian companies. Furthermore, the differences in the level of human capital investments with regard to several companies’ characteristics (e.g. size of the company, ownership and type of the industry) are investigated.

Keywords:

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Authors: Jaqueline M. R. Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.

Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.

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Authors: Mpho A. Mbeo, Patient Rambe

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The 13th year of the Central University of Technology, Free State’s (CUT) transition from a vocational and professional training orientation institution (i.e. a technikon) into a university with a strong research focus has neither been a smooth nor an easy one. At the heart of this transition was the need to transform the psychological faculties of academic and research staffs compliment who were accustomed to training graduates for industrial placement. The lack of a research culture that fully embraces the strong solid ethos of conducting cutting-edge research needs to be addressed. The induction and socialisation of academic staff into the development and execution of cutting-edge research also required the provision of research support and the creation of a conducive academic environment for research, both for emerging and non-research active academics. Drawing on ten cases, consisting of four heads of departments, three seasoned researchers, and three novice researchers, this study explores the challenges faced in establishing a strong research culture at the university. Furthermore, it gives an account of the extent to which the current research interventions have addressed the perceivably “missing research culture”, and the implications of these interventions for knowledge management. Evidence suggests that the capability of an ideal institutional research environment, consisting of mentorship of novice researchers by seasoned researchers, balanced effort into teaching and research responsibilities, should be supported by strong research-oriented leadership. Furthermore, recruitment of research passionate staff, adoption of a salary structure that encourages the retention of excellent scholars should be matched by a coherent research incentive culture to growth research publication outputs. This is critical for building new knowledge and entrenching knowledge management founded on communities of practice and scholarly networking through the documentation and communication of research findings. The study concludes that the multiple policy documents set for the different domains of research may be creating pressure on researchers to engage research activities and increase output at the expense of research quality.

Keywords: Central University of Technology, performance, publication, research culture, university.

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