Search results for: Prior knowledge

Authors: Sawsan J. Al-Husseini

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Transformational leadership (TL) has been found to have an important influence on knowledge and knowledge management (KM). It can contribute to organizational learning, employees’ creativity, encourage followers to participate in educational programs and develop the skills needed to achieve exceptional performance. This research sought to examine the impact of TL on knowledge donating and collecting and the differences between these impacts in public and private higher education institutes (HEIs) in Iraq. A mixed method approach was taken and 580 valid responses were collected to test the causal relationships between the factors, then 12 interviews were conducted with the leaders of HEIs to give more insight of the findings from quantitative stage. Employing structural equation modelling with AMOS v.24, the research found that TL would be ideal in an educational context, promoting knowledge sharing activities in both sectors. The interviews revealed differences between public and private HEIs in terms of the effects relationships. Guidelines are developed for academics as well as leaders and provided evidence to support the use of TL to encourage knowledge sharing activities within higher education in developing countries particularly Iraq.

Keywords: Transformational leadership, knowledge sharing, higher education, multi-groups.

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Authors: S. Minhas, C. Juzek, U. Berger

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The planning in manufacturing system is becoming complicated day by day due to the expanding networks and shortage of skilled people to manage change. Consequently, faster lead time and rising demands for eco-efficient evaluation of manufacturing products and processes need exploitation of new and intelligent knowledge management concepts for manufacturing planning. This paper highlights motivation for incorporation of new features in the manufacturing planning system. Furthermore, it elaborates requirements for the development of intelligent knowledge management concept to support planning related decisions. Afterwards, the derived concept is presented in this paper considering two case studies. The first case study is concerned with the automotive ramp-up planning. The second case study specifies requirements for knowledge management system to support decisions in eco-efficient evaluation of manufacturing products and processes

Keywords: Ramp-up, Environmental impact, Knowledge management.

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Authors: Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaa, Basel Solaiman, Henda Ben Ghezala

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This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.

Keywords: Knowledge discovery in satellite databases, knowledge fusion, data imperfection, data mining, spatiotemporal change detection.

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Authors: Turan Erman Erkan

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Business Process Reengineering (BPR) is an essential tool before an information system project implementation. Enterprise Resource Planning (ERP) projects definitely require the standardization and fixation of business processes from customer order to shipment. Therefore, ERP implementations are well proven to be coupled with BPR, although the extend and timing of BPR with respect to ERP implementation differ. This study aims at analyzing the effects of BPR on ERP implementation success. Basing on two Turkish ERP implementations in pharmaceutical sector, a comparative study is performed. One of the ERP implementations took place after a BPR implementation, whereas the other implementation was without a prior BPR application. Both implementations have been realized with the same consultant team, the case with prior BPR implementation going live first. The results of the case study reveal that if business processes are not optimized and improved before an ERP implementation, ERP live system would face with disharmony problems of processes and processes automated by ERP. This suggests a definite precedence relationship between BPR and ERP applications

Keywords: Business Process Reengineering, Enterprise Resource Planning

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Authors: Alan C. Lin, Dean K. Sheu

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This paper aims to study the methodology of building the knowledge of planning adequate punches in order to complete the task of strip layout for shearing processes, using progressive dies. The proposed methodology uses die design rules and characteristics of different types of punches to classify them into five groups: prior use (the punches must be used first), posterior use (must be used last), compatible use (may be used together), sequential use (certain punches must precede some others) and simultaneous use (must be used together). With these five groups of punches, the searching space of feasible designs will be greatly reduced, and superimposition becomes a more effective method of punch layout. The superimposition scheme will generate many feasible solutions, an evaluation function based on number of stages, moment balancing and strip stability is developed for helping designers to find better solutions.

Keywords: Manufacturing systems, advances in metal forming, computer-aided design, progressive die.

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Authors: Harleen Kaur

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Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.

Keywords: Data Mining Community, Knowledge Discovery inDatabases (KDD), Interestingness, Subjective Measures, Actionability.

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Authors: Matthew P. Mancini, Vincent Ribiere

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Today’s workers face more numerous and complex challenges and are required to be increasingly interdependent and faster learners. Knowledge sharing activities between people have been understood as a significant element affecting organizational innovation performance. While they do have the potential to spark cognitive conflict, disagreement is important from an organizational perspective because it can stimulate the development of new ideas and perhaps pave the way for creativity, innovation, and competitive advantage. How teams cope with the cognitive conflict dimension of knowledge sharing and the associated interpersonal risk is what captures our attention. Specifically, assertive conflict management strategies have a positive influence on knowledge sharing behaviors, and team psychological safety has a positive influence on knowledge sharing intention. This paper focuses on explaining the impact that these factors have on the shaping of an individual’s decision to engage or not in knowledge sharing activities. To accomplish this, we performed an empirical analysis on the results of our questionnaire about knowledge-sharing related conflict management and team psychological safety in pharmaceutical enterprises located in North America, Europe, and Asia. First, univariate analysis is used to characterize behavior regarding conflict management strategy into two groups. Group 1 presents assertive conflict management strategies and group 2 shows unassertive ones. Then, by using SEM methodology, we evaluated the relationships between them and the team psychological safety construct with the knowledge sharing process. The results of the SEM analysis show that assertive conflict management strategies affect the knowledge sharing process the most with a small, but significant effect from team psychological safety. The findings suggest that assertive conflict management strategies are just as important as knowledge sharing intentions for encouraging knowledge sharing behavior. This paper provides clear insights into how employees manage the sharing of their knowledge in the face of conflict and interpersonal risk and the relative importance of these factors in sustaining productive knowledge sharing activities.

Keywords: Cognitive dissonance, conflict management, knowledge sharing, organizational behavior, psychological safety.

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Authors: Ines Hamdi, Mohamed Ben Ahmed

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The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower

Keywords: Ontological model, spatio-temporal modeling, Genetic Regulatory Networks (GRNs), knowledge representation.

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Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.

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Authors: Rabi W. Yousif, Mohd Asri Hj Mansor

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In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.

Keywords: Expert system, knowledge base, mobile robot, visual basic.

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Authors: Rachelle Bosua, Nina Evans

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The resource-based view of the firm regards knowledge as one of the most important organizational assets and a key strategic resource that contributes unique value to organizations. The acquisition, absorption and internalization of external knowledge are central to an organization-s innovative capabilities. This ability to evaluate, acquire and integrate new knowledge from its environment is referred to as a firm-s absorptive capacity (AC). This research in progress paper explores the link between interorganizational Social Networks (SNs) and a firm-s Absorptive Capacity (AC). Based on an in-depth literature survey of both concepts, four propositions are proposed that explain the link between AC and SNs. These propositions suggest that SNs are key to a firm-s AC. A qualitative research method is proposed to test the set of propositions in the next stage of this research.

Keywords: Knowledge, Innovation, Absorptive Capacity, Social Networks

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Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

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In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: Game-based learning, knowledge based engineering, product modelling, design automation.

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Authors: Ahmed Alaoui

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This paper contributes to the ongoing debate as to the relevance of translation studies to professional practitioners. It exposes the various misconceptions permeating the links between theory and practice in the translation landscape in the Arab World. It is a thesis of this paper that specialization in translation should be redefined; taking account of the fact, that specialized knowledge alone is neither crucial nor sufficient in technical translation. It should be tested against the readability of the translated text, the appropriateness of its style and the usability of its content by endusers to carry out their intended tasks. The paper also proposes a preliminary model to establish a working link between theory and practice from the perspective of professional trainers and practitioners, calling for the latter to participate in the production of knowledge in a systematic fashion. While this proposal is driven by a rather intuitive conviction, a research line is needed to specify the methodological moves to establish the mediation strategies that would relate the components in the model of knowledge transfer proposed in this paper. 

Keywords: Knowledge transfer, misconceptions, specialized texts, translation theory, translation practice.

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Authors: A. Johannet, B. Vayssade, D. Bertin

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Neural networks are well known for their ability to model non linear functions, but as statistical methods usually does, they use a no parametric approach thus, a priori knowledge is not obvious to be taken into account no more than the a posteriori knowledge. In order to deal with these problematics, an original way to encode the knowledge inside the architecture is proposed. This method is applied to the problem of the evapotranspiration inside karstic aquifer which is a problem of huge utility in order to deal with water resource.

Keywords: Neural-Networks, Hydrology, Evapotranpiration, Hidden Function Modeling.

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Authors: M. V. Sudhamani, C. R. Venugopal

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This paper deals with the application for contentbased image retrieval to extract color feature from natural images stored in the image database by segmenting the image through clustering. We employ a class of nonparametric techniques in which the data points are regarded as samples from an unknown probability density. Explicit computation of the density is avoided by using the mean shift procedure, a robust clustering technique, which does not require prior knowledge of the number of clusters, and does not constrain the shape of the clusters. A non-parametric technique for the recovery of significant image features is presented and segmentation module is developed using the mean shift algorithm to segment each image. In these algorithms, the only user set parameter is the resolution of the analysis and either gray level or color images are accepted as inputs. Extensive experimental results illustrate excellent performance.

Keywords: Segmentation, Clustering, Image Retrieval, Features.

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Authors: A. Ahmed Haza’a, M. Ali Odhah, S. Ahmed Al-Ahdal, A. Saleh Al-Jaradi, G. Ghaleb Alrubaiee

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Patient safety in hospitals is an essential professional indicator that should be noticed. The threat of fires is potentially the most dangerous risk that could harm patients and personnel. The aim of the study is to assess the knowledge of operating room (OR) staff toward prevention and control sources of fires. Data collection was done between March 1 and March 30, 2022. A descriptive cross-sectional study was conducted. The sample of the study consisted of 89 OR staff from different governmental hospitals. Convenient sampling was applied to select the sample size. Official approvals were obtained from selected settings for start collection data. Data were collected using a close-ended questionnaire and tested for knowledge. This study was conducted in four governmental hospitals in Sana'a, Yemen. Most of the OR staff were male. Of these, 50.6% of them were operation technician professionals. More than two-thirds of OR staff have less than ten years of experience; 93% of OR staff had inadequate knowledge of sources of fires, and inadequate knowledge toward control and prevention of fires (73%, 79.8%), respectively; 77.5% of OR staff had inadequate knowledge of prevention and control sources of fires. The study concluded that most of OR staff had inadequate knowledge of sources, controls, and prevention of fires, while 22.5% of them had adequate knowledge of prevention and control sources of fires. We recommended the implementation of training programs toward sources, controls, and prevention of fires or related workshops in their educational planning for OR staff of hospitals.

Keywords: Staff, fire source, operation room safety.

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Authors: Khababa Abdallah, Touahria Mohamed, Frécon Louis

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The school / university orientation interests a broad and often badly informed public. Technically, it is an important multicriterion decision problem, which supposes the combination of much academic professional and/or lawful knowledge, which in turn justifies software resorting to the techniques of Artificial Intelligence. CORUS is an expert system of the "Conseil et ORientation Universitaire et Scolaire", based on a knowledge representation language (KRL) with rules and objects, called/ known as Ibn Rochd. CORUS was developed thanks to DéGSE, a workshop of cognitive engineering which supports this LRC. CORUS works out many acceptable solutions for the case considered, and retains the most satisfactory among them. Several versions of CORUS have extended its services gradually.

Keywords: Kknowledge Engineering, Multicriterion Decision, Knowledge-Based Systems.

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Authors: Sandeep Chandana, Rene V. Mayorga, Christine W. Chan

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This article outlines conceptualization and implementation of an intelligent system capable of extracting knowledge from databases. Use of hybridized features of both the Rough and Fuzzy Set theory render the developed system flexibility in dealing with discreet as well as continuous datasets. A raw data set provided to the system, is initially transformed in a computer legible format followed by pruning of the data set. The refined data set is then processed through various Rough Set operators which enable discovery of parameter relationships and interdependencies. The discovered knowledge is automatically transformed into a rule base expressed in Fuzzy terms. Two exemplary cancer repository datasets (for Breast and Lung Cancer) have been used to test and implement the proposed framework.

Keywords: Knowledge Extraction, Fuzzy Sets, Rough Sets, Neuro–Fuzzy Systems, Databases

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Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: Effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating.

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Authors: Siti Waringin Oon, Rashidah Shuib, Siti Hawa Ali, Nik Hazlina Nik Hussain, Juwita Shaaban, Harmy Mohd Yusoff

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This paper explores the knowledge and attitude of women and men in decision making on pap smear screening. This qualitative study recruited 52 respondents with 44 women and 8 men, using the purposive sampling with snowballing technique through indepth interviews. This study demonstrates several key findings: Female respondents have better knowledge compared to male. Most of the women perceived that pap smear screening is beneficial and important, but to proceed with the test is still doubtful. Male respondents were supportive in terms of sending their spouses to the health facilities or give more freedom to their wives to choose and making decision on their own health due to prominent reason that women know best on their own health. It is expected that the results from this study will provide useful guideline for healthcare providers to prepare any action/intervention to provide an extensive education to improve people-s knowledge and attitude towards pap smear.

Keywords: Attitude, decision making, knowledge, pap smearscreening..

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Authors: Regine W. Vroom, Lysanne E. Vossen, Anoek M. Geers

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Industrial design engineering is an information and knowledge intensive job. Although Wikipedia offers a lot of this information, design engineers are better served with a wiki tailored to their job, offering information in a compact manner and functioning as a design tool. For that reason WikID has been developed. However for the viability of a wiki, an active user community is essential. The main subject of this paper is a study to the influence of the communication and the contents of WikID on the user-s willingness to contribute. At first the theory about a website-s first impression, general usability guidelines and user motivation in an online community is studied. Using this theory, the aspects of the current site are analyzed on their suitability. These results have been verified with a questionnaire amongst 66 industrial design engineers (or students industrial design engineering). The main conclusion is that design engineers are enchanted with the existence of WikID and its knowledge structure (taxonomy) but this structure has not become clear without any guidance. In other words, the knowledge structure is very helpful for inspiring and guiding design engineers through their tailored knowledge domain in WikID but this taxonomy has to be better communicated on the main page. Thereby the main page needs to be fitted more to the target group preferences.

Keywords: Industrial Design Engineering Knowledge, SemanticWiki, User Willingness to Contribute Knowledge to a Wiki, Influence of Website Content to User Activation.

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Authors: Norsiah Abdul Hamid, Halimah Badioze Zaman

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This paper outlines the research conducted to propose na framework of 'Knowledge Society' (KS) in the Malaysian context. It is important to highlight that the emergence of KS is a result of the rapid growth in knowledge and information. However, the discussion of KS should not only be limited to the importance of knowledge, but a holistic KS is also determined by other imperative dimensions. This article discusses the results of a study conducted previously in Malaysia in order to identify the essential dimensions of KS, and consequently propose a KS framework in the Malaysian context. Two methods were employed, namely the Delphi technique and semi-structured interviews. The modified Delphi involved five rounds with ten experts, while the interviews were conducted with two prominent figures in Malaysia. The results support the proposed framework which contains seven major dimensions in order for Malaysia to become a KS in the future. The dimensions which are crucial for a holistic Malaysian KS are human capital, spirituality, economy, social, institutional, sustainability, and driven by the ICT.

Keywords: Malaysia, Knowledge Society, Framework, Delphi Technique, Interview.

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Authors: María Jesús Luengo-Valderrey, Mónica Moso-Díez

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In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Keywords: High and medium technology sector, innovation, knowledge management, Spanish companies.

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Authors: Ahmed Tawfik, Fausto Giunchiglia, Vincenzo Maltese

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Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper, we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features.

Keywords: Knowledge Diversity, Knowledge Representation, Ontology Development.

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Authors: F. Rashno Seydari, M. Nikafrooz

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This paper intends to study needs analysis of hearing-impaired students’ teachers in elementary schools all over Iran. The subjects of this study were 275 teachers who were teaching hearing-impaired students in elementary schools. The participants were selected by a quota sampling method. To collect the data, questionnaires of training needs consisting of 41 knowledge items and 31 performance items were used. The collected data were analyzed by using SPSS software in the form of descriptive analyses (frequency and mean) and inferential analyses (one sample t-test, paired t-test, independent t-test, and Pearson correlation coefficient). The findings of the study indicated that teachers generally have considerable needs in knowledge and performance domains. In 32 items out of the total 41 knowledge domain items and in the 27 items out of the total 31 performance domain items, the teachers had considerable needs. From the quantitative point of view, the needs of the performance domain were more than those of the knowledge domain, so they have to be considered as the first priority in training these teachers. There was no difference between the level of the needs of male and female teachers. There was a significant difference between the knowledge and performance domain needs and the teachers’ teaching experience, 0.354 and 0.322 respectively. The teachers who had been trained in working with hearing-impaired students expressed more training needs (both knowledge and performance).

Keywords: Needs analysis, hearing impaired students, hearing impaired students’ teachers, knowledge domain, performance domain.

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Authors: U. Sakthi, R. Hemalatha, R. S. Bhuvaneswaran

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In Virtual organization, Knowledge Discovery (KD) service contains distributed data resources and computing grid nodes. Computational grid is integrated with data grid to form Knowledge Grid, which implements Apriori algorithm for mining association rule on grid network. This paper describes development of parallel and distributed version of Apriori algorithm on Globus Toolkit using Message Passing Interface extended with Grid Services (MPICHG2). The creation of Knowledge Grid on top of data and computational grid is to support decision making in real time applications. In this paper, the case study describes design and implementation of local and global mining of frequent item sets. The experiments were conducted on different configurations of grid network and computation time was recorded for each operation. We analyzed our result with various grid configurations and it shows speedup of computation time is almost superlinear.

Keywords: Association rule, Grid computing, Knowledge grid, Mobility prediction.

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Authors: Zhanna Mingaleva, Irina Mirskikh

Abstract:

Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.

Keywords: knowledge economy, innovational development, transfer of knowledge, institutional preconditions, innovation andknowledge capacity.

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Authors: Tarek Mohammad

Abstract:

The amplitude response of infrared (IR) sensors depends on the reflectance properties of the target. Therefore, in order to use IR sensor for measuring distances accurately, prior knowledge of the surface must be known. This paper describes the Phong Illumination Model for determining the properties of a surface and subsequently calculating the distance to the surface. The angular position of the IR sensor is computed as normal to the surface for simplifying the calculation. Ultrasonic (US) sensor can provide the initial information on distance to obtain the parameters for this method. In addition, the experimental results obtained by using LabView are discussed. More care should be taken when placing the objects from the sensors during acquiring data since the small change in angle could show very different distance than the actual one. Since stereo camera vision systems do not perform well under some environmental conditions such as plain wall, glass surfaces, or poor lighting conditions, the IR and US sensors can be used additionally to improve the overall vision systems of mobile robots.

Keywords: Distance Measurement, Infrared sensor, Surface properties, Ultrasonic sensor.

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Authors: M. Nashriyah, T. Salmah, M.Y. NurAtiqah, O. Siti Nor Indah, A.W. MuhamadAzhar, S. Munirah, Y. Nornasuha, A. Abdul Manaf

Abstract:

Dioscorea species or commonly named as yam is reported to be one of the major food sources worldwide. This ethnobotanical study was conducted to document local knowledge and potentials of DioscoreahispidaDennst. and to investigate and record its distribution in three districts of Terengganu. Information was gathered from 23 villagers from three districts of Besut, Marang and Setiu by using semi-structured questionnaire. The villagers were randomly selected and no appointment was made prior to the visits. For distribution, the location of Dioscoreahispida was recorded by using the Global Positioning System (GPS). The villagers identified Dioscoreahispida or locally named ubigadong by looking at the physical characteristics that include its leaf shape, stem and the color of the tuber-s flesh. The villagers used Dioscoreahispida in many ways in their life such as for food, medicinal purposes and fish poison.

Keywords: Dioscoreahispida, ethnobotany, intoxicating yam, ubigadong, Terengganu.

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Authors: Reza Sigari Tabrizi, Yeap Peik Foong, Nazli Ebrahimi

Abstract:

This paper is concerned with the establishment of relationships among knowledge management (KM) criteria that will ensure an essential foundation to evaluate KM outcomes. The major issue under investigation is to assess the popularity of criteria within organizations and to establish a structure of criteria for measuring KM results. An empirical survey was conducted among Malaysian organizations to investigate KM criteria for measuring success of KM initiatives. Therefore, knowledge workers as the respondents were targeted to establish a structure of criteria for evaluating KM outcomes. An established structure of criteria based on the Interpretive Structural Modeling (ISM) is used to map criteria relationships inside organizations. This structure is portrayed to identify that how these set of criteria are related. This network schema should be investigated and implemented to promote innovation and improve enterprise performance. To the researchers, this survey has significant insights into relationship between KM programs and business success.

Keywords: Knowledge Management, Knowledge ManagementOutcomes, KM Criteria, Innovation, Interpretive Structural Modeling

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