Search results for: automatic knowledge discovery
2537 Ontology Population via NLP Techniques in Risk Management
Authors: Jawad Makki, Anne-Marie Alquier, Violaine Prince
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In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.Keywords: Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15362536 Automatic Moment-Based Texture Segmentation
Authors: Tudor Barbu
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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Then, an automatic pixel classification approach is proposed. The feature vectors are clustered using an unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.
Keywords: Image segmentation, moment-based texture analysis, automatic classification, validity indexes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23802535 Personalisation of SOA Registry Query Results: Implementation, Performance Analysis and Scalability Evaluation
Authors: Kee-Leong Tan, Karyn Wei-Ju Khoo, Hui-Na Chua
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Service discovery is a very important component of Service Oriented Architectures (SOA). This paper presents two alternative approaches to customise the query results of private service registry such as Universal Description, Discovery and Integration (UDDI). The customisation is performed based on some pre-defined and/or real-time changing parameters. This work identifies the requirements, designs and additional mechanisms that must be applied to UDDI in order to support this customisation capability. We also detail the implements of the approaches and examine its performance and scalability. Based on our experimental results, we conclude that both approaches can be used to customise registry query results, but by storing personalization parameters in external resource will yield better performance and but less scalable when size of query results increases. We believe these approaches when combined with semantics enabled service registry will enhance the service discovery methods within a private UDDI registry environment.
Keywords: Service Oriented Architecture (SOA), Web service, Service discovery, registry, UDDI
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14032534 Design of an Augmented Automatic Choosing Control with Constrained Input by Lyapunov Functions Using Gradient Optimization Automatic Choosing Functions
Authors: Toshinori Nawata
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In this paper a nonlinear feedback control called augmented automatic choosing control (AACC) for a class of nonlinear systems with constrained input is presented. When designed the control, a constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.
Keywords: Augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17342533 Fortification for P2P Grid Computing Used for Resource Discovery
Authors: Bhawneet Singh Marwah, Rishabh Rastogi, Shinon Kochar
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Grid computing provides an effective infrastructure for massive computation among flexible and dynamic collection of individual system for resource discovery. The major challenge for grid computing is to prevent breaches and secure the data from trespassers. To overcome such conflicts a semantic approach can be designed which will filter the access requests of peers by checking the resource description specifying the data and the metadata as factual statements. Between every node in the grid a semantic firewall as a middleware will be present The intruder will be required to present an application specifying there needs to the firewall and hence accordingly the system will grant or deny the application request.
Keywords: Grid Computing, Metadata, Semantic, Peers, Resource Discovery, Firewall.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15672532 Personal Information Classification Based on Deep Learning in Automatic Form Filling System
Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao
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Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.Keywords: Personal information, deep learning, auto fill, NLP, document analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8652531 Performance of Laboratory Experiments over the Internet: Towards an Intelligent Tutoring System on Automatic Control
Authors: Kleanthis Prekas, Maria Rangoussi, Savvas Vassiliadis, George Prekas
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Intelligent tutoring systems constitute an evolution of computer-aided educational software. We present here the modules of an intelligent tutoring system for Automatic Control, developed in our department. Through the software application developed,students can perform complete automatic control laboratory experiments, either over the departmental local area network or over the Internet. Monitoring of access to the system (local as well as international), along with student performance statistics, has yielded strongly encouraging results (as of fall 2004), despite the advanced technical content of the presented paradigm, thus showing the potential of the system developed for education and for training.
Keywords: Automatic control, tutoring system, Internet access, laboratory experiments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16562530 Automatic Extraction of Water Bodies Using Whole-R Method
Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao
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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.
Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33712529 Proffering a Brand New Methodology to Resource Discovery in Grid based on Economic Criteria Using Learning Automata
Authors: Ali Sarhadi, Mohammad Reza Meybodi, Ali Yousefi
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Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.
Keywords: Resource discovery, learning automata, neural network, economic policy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14562528 Using Textual Pre-Processing and Text Mining to Create Semantic Links
Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo
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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.Keywords: Semantic links, data mining, linked data, SKOS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10652527 Classifier Based Text Mining for Neural Network
Authors: M. Govindarajan, R. M. Chandrasekaran
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Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.Keywords: Back propagation, classification accuracy, textmining, time complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42182526 Knowledge Representation and Inconsistency Reasoning of Class Diagram Maintenance in Big Data
Authors: Chi-Lun Liu
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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.
Keywords: Knowledge representation, reasoning, ontology, class diagram, software engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10442525 Approaches to Developing Semantic Web Services
Authors: Jorge Cardoso
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It has been recognized that due to the autonomy and heterogeneity, of Web services and the Web itself, new approaches should be developed to describe and advertise Web services. The most notable approaches rely on the description of Web services using semantics. This new breed of Web services, termed semantic Web services, will enable the automatic annotation, advertisement, discovery, selection, composition, and execution of interorganization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the semantic Web. It describes how semantic Web services extend Web services as the semantic Web improves the current Web, and presents three different conceptual approaches to deploying semantic Web services, namely, WSDL-S, OWL-S, and WSMO.Keywords: Semantic Web, Web service, Web process, WWW
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14382524 Automatic Microaneurysm Quantification for Diabetic Retinopathy Screening
Authors: A. Sopharak, B. Uyyanonvara, S. Barman
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Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.
Keywords: Diabetic retinopathy, microaneurysm, naive Bayes classifier
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21942523 Knowledge Representation Based On Interval Type-2 CFCM Clustering
Authors: Myung-Won Lee, Keun-Chang Kwak
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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.
Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26192522 A Comparison of YOLO Family for Apple Detection and Counting in Orchards
Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long
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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.
Keywords: Agricultural object detection, Deep learning, machine vision, YOLO family.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11012521 Towards an Automatic Translation of Colored Petri Nets to Maude Language
Authors: Noura Boudiaf, Abdelhamid Djebbar
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Colored Petri Nets (CPN) are very known kind of high level Petri nets. With sound and complete semantics, rewriting logic is one of very powerful logics in description and verification of non-deterministic concurrent systems. Recently, CPN semantics are defined in terms of rewriting logic, allowing us to built models by formal reasoning. In this paper, we propose an automatic translation of CPN to the rewriting logic language Maude. This tool allows graphical editing and simulating CPN. The tool allows the user drawing a CPN graphically and automatic translating the graphical representation of the drawn CPN to Maude specification. Then, Maude language is used to perform the simulation of the resulted Maude specification. It is the first rewriting logic based environment for this category of Petri Nets.Keywords: Colored Petri Nets, Rewriting Logic, Maude, Graphical Edition, Automatic Translation, Simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15982520 Manufacturing of Full Automatic Carwash Using with Intelligent Control Algorithms
Authors: Amir Hossein Daei Sorkhabi, Bita Khazini
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In this paper the intelligent control of full automatic car wash using a programmable logic controller (PLC) has been investigated and designed to do all steps of carwashing. The Intelligent control of full automatic carwash has the ability to identify and profile the geometrical dimensions of the vehicle chassis. Vehicle dimension identification is an important point in this control system to adjust the washing brushes position and time duration. The study also tries to design a control set for simulating and building the automatic carwash. The main purpose of the simulation is to develop criteria for designing and building this type of carwash in actual size to overcome challenges of automation. The results of this research indicate that the proposed method in process control not only increases productivity, speed, accuracy and safety but also reduce the time and cost of washing based on dynamic model of the vehicle. A laboratory prototype based on an advanced intelligent control has been built to study the validity of the design and simulation which it’s appropriate performance confirms the validity of this study.
Keywords: Automatic Carwash, Dimension, PLC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 68252519 A New Automatic System of Cell Colony Counting
Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva
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The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.Keywords: Automatic cell counting, neural network, region growing, Sanger net.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14622518 Causal Relation Identification Using Convolutional Neural Networks and Knowledge Based Features
Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi
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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.
Keywords: Causal relation identification, convolutional neural networks, natural Language Processing, Machine Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22582517 CASTE: a Cloud-Based Automatic Software Test Environment
Authors: Fuyang Peng, Bo Deng, Chao Qi
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This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Keywords: Software testing, test environment, test script, cloud computing, IaaS, test automation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21842516 Effective Keyword and Similarity Thresholds for the Discovery of Themes from the User Web Access Patterns
Authors: Haider A Ramadhan, Khalil Shihab
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Clustering techniques have been used by many intelligent software agents to group similar access patterns of the Web users into high level themes which express users intentions and interests. However, such techniques have been mostly focusing on one salient feature of the Web document visited by the user, namely the extracted keywords. The major aim of these techniques is to come up with an optimal threshold for the number of keywords needed to produce more focused themes. In this paper we focus on both keyword and similarity thresholds to generate themes with concentrated themes, and hence build a more sound model of the user behavior. The purpose of this paper is two fold: use distance based clustering methods to recognize overall themes from the Proxy log file, and suggest an efficient cut off levels for the keyword and similarity thresholds which tend to produce more optimal clusters with better focus and efficient size.
Keywords: Data mining, knowledge discovery, clustering, dataanalysis, Web log analysis, theme based searching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14552515 Development of Automatic Guided Mobile Robot Using Magnetic Position Meter
Authors: Geun-Mo Kim, Young-Jae Ryoo
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In this paper, an automatic guided mobile robot using a new magnetic position meter is described. In order to measure the lateral position of a mobile robot, a new magnetic position meter is developed. The magnetic position meter can detect the position of a magnetic wire on the center of road. A mobile robot in designed with a sensing system, a steering system and a driving system. The designed mobile robot is tested to verify the performance of automatic guidance.
Keywords: Autonomous vehicle, magnetic position meter, steering, magnet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16542514 Knowledge Relationship Model among User in Virtual Community
Authors: Fariba Haghbin, Othman Bin Ibrahim, Mohammad Reza Attarzadeh Niaki
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With the development of virtual communities, there is an increase in the number of members in Virtual Communities (VCs). Many join VCs with the objective of sharing their knowledge and seeking knowledge from others. Despite the eagerness of sharing knowledge and receiving knowledge through VCs, there is no standard of assessing ones knowledge sharing capabilities and prospects of knowledge sharing. This paper developed a vector space model to assess the knowledge sharing prospect of VC users.Keywords: Knowledge sharing network, Virtual community, knowledge relationship, Vector Space Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13432513 Automatic Camera Calibration for Images of Soccer Match
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Camera calibration plays an important role in the domain of the analysis of sports video. Considering soccer video, in most cases, the cross-points can be used for calibration at the center of the soccer field are not sufficient, so this paper introduces a new automatic camera calibration algorithm focus on solving this problem by using the properties of images of the center circle, halfway line and a touch line. After the theoretical analysis, a practicable automatic algorithm is proposed. Very little information used though, results of experiments with both synthetic data and real data show that the algorithm is applicable.
Keywords: Absolute conic, camera calibration, circular points, line at infinity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23672512 Analysis of Investment in Knowledge inside OECD Countries
Authors: JunSeok Hwang, Mohsen Gerami
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Knowledge is the foundation for growth and development. Investment in knowledge improves new method for originate knowledge society and knowledge economy. Investment in knowledge embraces expenditure on education and R&D and software. Measuring of investment in knowledge is characteristically complicated. We examine the influence of investment in knowledge in multifactor productivity growth and numbers of patent. We analyze the annual growth of investment in knowledge and we estimate portion of each country intended for produce total investment in knowledge on the whole OECD. We determine the relative efficiency of average patent numbers with average investment in knowledge and we compare GDP growth rates and growth of knowledge investment. The main purpose in this paper is to study to evaluate different aspect, influence and output of investment in knowledge in OECD countries.Keywords: Knowledge, GDP, Multifactor productivity, Investment, efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16762511 Intrapreneurship Discovery: Standard Strategy to Boost Innovation inside Companies
Authors: Chiara Mansanta, Daniela Sani
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This paper studies the concept of intrapreneurship discovery for innovation and technology development related to the manufacturing industries set up in the center of Italy, in Marche Region. The study underlined the key drivers of the innovation process and the main factors that influence innovation. Starting from a literature study on open innovation, this paper examines the role of human capital to support company’s development. The empirical part of the study is based on a survey to 151 manufacturing companies that represent the 34% of that universe at the regional level. The survey underlined the main KPI’s that influence companies in their decision processes; then tools for these decision processes are presented.
Keywords: Business model, decision making, intrapreneurship discovery, open innovation, standard methodology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9552510 Effect of Manual Compacting and Semi-Automatic Compacting on Behavior of Stabilized Earth Concrete
Authors: Sihem Chaibeddra, Fattoum Kharchi, Fahim Kahlouche, Youcef Benna
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In the recent years, a considerable level of interest has been developed on the use of earth in construction, led by its rediscovery as an environmentally building material. The Stabilized Earth Concrete (SEC) is a good alternative to the cement concrete, thanks to its thermal and moisture regulating features. Many parameters affect the behavior of stabilized earth concrete. This article presents research results related to the influence of the compacting nature on some SEC properties namely: The mechanical behavior, capillary absorption, shrinkage and sustainability to water erosion, and this, basing on two types of compacting: Manual and semi-automatic.Keywords: Behavior, compacting, manual, SEC, semi-automatic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21112509 An Owl Ontology for Commonkads Template Knowledge Models
Authors: B. A. Gobin, R. K. Subramanian
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This paper gives an overview of how an OWL ontology has been created to represent template knowledge models defined in CML that are provided by CommonKADS. CommonKADS is a mature knowledge engineering methodology which proposes the use of template knowledge model for knowledge modelling. The aim of developing this ontology is to present the template knowledge model in a knowledge representation language that can be easily understood and shared in the knowledge engineering community. Hence OWL is used as it has become a standard for ontology and also it already has user friendly tools for viewing and editing.Keywords: Ontology, OWL, Template Knowledge Models, CommonKADS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17952508 Minimizing the Broadcast Traffic in the Jordanian Discovery Schools Network using PPPoE
Authors: Sameh H. Ghwanmeh
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Discovery schools in Jordan are connected in one flat ATM bridge network. All Schools connected to the network will hear broadcast traffic. High percentage of unwanted traffic such as broadcast, consumes the bandwidth between schools and QRC. Routers in QRC have high CPU utilization. The number of connections on the router is very high, and may exceed recommend manufacturing specifications. One way to minimize number of connections to the routers in QRC, and minimize broadcast traffic is to use PPPoE. In this study, a PPPoE solution has been presented which shows high performance for the clients when accessing the school server resources. Despite the large number of the discovery schools at MoE, the experimental results show that the PPPoE solution is able to yield a satisfactory performance for each client at the school and noticeably reduce the traffic broadcast to the QRC.Keywords: Education, networking, performance, e-content.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1642