Search results for: knowledge discovery from databases
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8245

Search results for: knowledge discovery from databases

8185 Extracting the Coupled Dynamics in Thin-Walled Beams from Numerical Data Bases

Authors: Mohammad A. Bani-Khaled

Abstract:

In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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8184 A Framework for Customer Knowledge Management (CKM) as a Key Role in Relationship

Authors: Mehrnoosh Askarizadeh

Abstract:

The customer’s value has become obvious for the leading companies in today’s competitive environment. Therefore they are constantly trying to improve their relationship with customers. Customer Knowledge has been recognized as a strategic resource and a key to the success of any company. Talking about the Customer Knowledge Management is closely associated with Knowledge Management and Customer Relationship Management (CRM). Recent studies conducted in the fields of Knowledge Management (KM) and Customer Relationship Management (CRM) has explained that the two approaches can have great synergies. In this paper, our aim is to provide an understanding of Customer Knowledge Management (CKM) as an integrated management approach and competence it requires. We describe CKM as an ongoing process of generating, disseminating and using customer knowledge within an organization and between an organization and its customers. In addition, we propose a comprehensive framework of CKM, the ability to integrate customer knowledge into customer relationship management processes.

Keywords: e-commerce, knowledge management (KM), customer relationship management (CRM), customer knowledge management (CKM)

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8183 Artificial Intelligence in Bioscience: The Next Frontier

Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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8182 Role of Medicinal Plants in Treatment of Diseases and Drug Discovery in Azad Kashmir, Pakistan

Authors: Neelam Rashid, Muhammad Zafar, Mushtaq Ahmad, Khafsa Malik, Syed Nasar Shah

Abstract:

The present study was conducted to study the role of medicinal plants used to cure different ailments in Azad Kashmir. Various ethno medicinal surveys were carried out during 2016 to enlist the uses of plants against various ailments by rural communities of the area. Information was obtained from 60 local people including 45 males (10 traditional health practitioners) and 15 females by semi structured interviews and group discussions. 65 plant species belonging to 45 families were reported. The dominant plant habit was herbaceous (56%) while decoction was the most common method of utilization (40%). The most cited turmoil was the gastrointestinal disorders. The data obtained were analyzed using ethno medicinal indices such as FL, UV, ICF, FC, and RFC. Results revealed that various species had numerous uses in curing of diseases. So conservation of biodiversity of these medicinal plants and traditional knowledge can play important role in improving the local health conditions of rural people and modern drug discovery and development.

Keywords: medicinal plants, ailments, drug, health, traditional

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8181 Enhancing Students’ Achievement, Interest and Retention in Chemistry through an Integrated Teaching/Learning Approach

Authors: K. V. F. Fatokun, P. A. Eniayeju

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This study concerns the effects of concept mapping-guided discovery integrated teaching approach on the learning style and achievement of chemistry students. The sample comprised 162 senior secondary school (SS 2) students drawn from two science schools in Nasarawa State which have equivalent mean scores of 9.68 and 9.49 in their pre-test. Five instruments were developed and validated while the sixth was purely adopted by the investigator for the study, Four null hypotheses were tested at α = 0.05 level of significance. Chi square analysis showed that there is a significant shift in students’ learning style from accommodating and diverging to converging and assimilating when exposed to concept mapping- guided discovery approach. Also t-test and ANOVA that those in experimental group achieve and retain content learnt better. Results of the Scheffe’s test for multiple comparisons showed that boys in the experimental group performed better than girls. It is therefore concluded that the concept mapping-guided discovery integrated approach should be used in secondary schools to successfully teach electrochemistry. It is strongly recommended that chemistry teachers should be encouraged to adopt this method for teaching difficult concepts.

Keywords: integrated teaching approach, concept mapping-guided discovery, achievement, retention, learning styles and interest

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8180 Understanding Tacit Knowledge and Its Role in Military Organizations: Methods of Managing Tacit Knowledge

Authors: M. Erhan Orhan, Onur Ozdemir

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Expansion of area of operation and increasing diversity of threats forced the military organizations to change in many ways. However, tacit knowledge still is the most fundamental component of organizational knowledge. Since it is human oriented and in warfare human stands at the core of the organization. Therefore, military organizations should find effective ways of systematically utilizing tacit knowledge. In this context, this article suggest some methods for turning tacit knowledge into explicit in military organizations.

Keywords: tacit knowledge, military, knowledge management, warfare, technology

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8179 Pharmaceutical Innovation in Jordan: KAP Analysis

Authors: Abdel Qader Al Bawab, Mohannad Odeh, Rami Amer

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Recently, there has been an increasing interest in innovative business development. Nevertheless, in the pharmacy practice field, there seems to be a gap in perceptions, attitudes, and knowledge about innovation between practicing pharmacists and academia. This study explores this gap and aspects of pharmaceutical innovation in Jordan, comparing pharmacists and last-year pharmacy students. A validated (r2 = 0.74) and reliable (Pearson’s r = 0.88) online questionnaire was designed to assess and compare knowledge, attitude, and perceptions about pharmaceutical innovation. A total of 397 participants (215 pharmacy students and 182 pharmaceutical professionals) responded. Compared with 50% of the pharmacists, only 32.1% of the students claimed that they knew the differences between pharmaceutical innovation, discovery, invention, and entrepreneurship [x2 (2) = 14.238, p = 0.001; Cramer’s V = 0.189]. Pharmacists demonstrated a higher level of trust in the innovative website design for their institution compared with students (25.3% vs. 16.3%, p < 0.001, Cramer’s V = 0.327). However, 60% of the students did not know the innovative design standards for websites, while the corresponding percentage was 37% for the pharmacists (p < 0.001; Cramer’s V = 0.327). The majority of the students were interested in pharmaceutical innovation (81.9%). Unfortunately, 76.3% never studied innovation in their pharmacy curricula. Similarly, most pharmacists (76.4%) considered adopting innovation, but only 30% had a concrete plan. For the field where pharmacists aim to innovate in the next 5 years, new pharmaceutical services were the dominant field (34.6%). Despite a positive attitude and perception, pharmacists and pharmacy students expressed poor knowledge about innovation. Policies to enhance awareness about innovation and professional educational tools should be implemented.

Keywords: pharmacy, innovation, knowledge, attitude, practice

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8178 Effect of Incentives on Knowledge Sharing and Learning: Evidence from the Indian IT Sector

Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

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The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) program, thanks to their in-house technological abilities. This paper tries to study the various knowledge-based incentive programs and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM incentives, knowledge sharing, and learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: knowledge management, knowledge management incentives, knowledge sharing, learning

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8177 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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8176 The Work System Method for Designing Knowledge Mobilization Projects

Authors: Chihab Benmoussa

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Could the Work System Approach (WSA) function as a framework for designing high-impact knowledge mobilization systems? This paper put forward arguments in favor of the applicability of WSA for knowledge mobilization design based on evidences from a practical research. Normative approaches for practitioners are highly needed especially in the field of knowledge management (KM), given the abysmal rate of disappointment and failure of KM projects. The paper contrasts knowledge management and knowledge mobilization, presents the WSA and showed how the WSA’s concepts and ideas fit with the approach adopted by a multinational company in designing a successful knowledge mobilization initiative.

Keywords: knowledge management, knowledge mobilizations, work system method

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8175 Management of Indigenous Knowledge: Expectations of Library and Information Professionals in Developing Countries

Authors: Desmond Chinedu Oparaku, Pearl C. Akanwa, Oyemike Victor Benson

Abstract:

This paper examines the challenges facing library and information centers (LICs) in managing indigenous knowledge in academic libraries in developing countries. The need for managing an indigenous knowledge in library and information centers in developing nations is becoming more critical. There is an ever increasing output of indigenous knowledge; effective management of indigenous knowledge becomes necessary to enable the next generation benefit from them. This paper thus explores the concept of indigenous knowledge (IK), nature of indigenous knowledge (IK), the various forms of indigenous knowledge (IK), sources of indigenous knowledge (IK), and relevance of indigenous knowledge (IK). The expectations of library and information professionals towards effective management of indigenous knowledge and the challenges to effective management of indigenous knowledge were highlighted. Recommendations were made based on the identified challenges.

Keywords: library, indigenous knowledge, information centres, information professionals

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8174 Identifying Enablers and Barriers of Healthcare Knowledge Transfer: A Systematic Review

Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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8173 Knowledge Graph Development to Connect Earth Metadata and Standard English Queries

Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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8172 Anomaly Detection with ANN and SVM for Telemedicine Networks

Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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8171 Self-Directed-Car on GT Road: Grand Trunk Road

Authors: Rameez Ahmad, Aqib Mehmood, Imran Khan

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Self-directed car (SDC) that can drive itself from one fact to another without support from a driver. Certain trust that self-directed car obligate the probable to transform the transportation manufacturing while essentially removing coincidences, and cleaning up the environment. This study realizes the effects that SDC (also called a self-driving, driver or robotic) vehicle travel demands and ride scheme is likely to have. Without the typical obstacles that allows detection of a audio vision based hardware and software construction (It (SDC) and cost benefits, the vehicle technologies, Gold (Generic Obstacle and Lane Detection) to a knowledge-based system to predict their potential and consider the shape, color, or balance) and an organized environment with colored lane patterns, lane position ban. Discovery the problematic consequence of (SDC) on GT (grand trunk road) road and brand the car further effectual.

Keywords: SDC, gold, GT, knowledge-based system

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8170 Knowledge, Attitudes, and Practices regarding Anthrax among Community Members, Health and Veterinary Workers in Maragua, Kenya

Authors: Isaiah Chacha, Samuel Arimi, Andrew Thaiya

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Background: This study was conducted to assess knowledge, attitudes and practices regarding anthrax in Maragua, Kenya to provide baseline information to design interventions. Methods: A cross sectional survey was conducted among head of households, health and veterinary workers in Maragua Sub-county in August and September 2014. Administered questionnaires were used to collect data from household members and a key informant interview held with health and veterinary workers. Multi stage sampling was used to obtain participants’ knowledge, attitudes and practices. Questions were scored and descriptively analyzed using Excel spreadsheet then exported to GenStat Discovery Edition 4. Results: A total of 293 community members were recruited in this study. The overall level of knowledge was 77.9% of all community members regarding cause, transmission, symptoms and prevention of the disease in both humans and animals. Majority of the participants (96.3%) had heard about anthrax. A total of 99 (33.8%) correspondents had seen a person with anthrax and 75.1% think that anthrax is a very serious disease in the area. Of the interviewed correspondents, 14.3% of them have had their animals (mostly cattle) suffer from anthrax while 15.7% had either suffered from anthrax or have had their family member who suffered from anthrax. Conclusion: The study findings indicate above average knowledge on cause, symptoms, transmission and prevention of anthrax among community members in humans and animals. Practices in this study were still risk among community members. Veterinary and Medical health planners should design anthrax awareness interventions as a team targeting to reach these communities and the public through barazas, radio, CHW and other communication channel on a regular basis.

Keywords: anthrax, attitudes, Kenya, knowledge, Maragua, practices

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8169 Zika Virus NS5 Protein Potential Inhibitors: An Enhanced in silico Approach in Drug Discovery

Authors: Pritika Ramharack, Mahmoud E. S. Soliman

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The re-emerging Zika virus is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus already been linked to irreversible chronic central nervous system (CNS) conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA-approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of Zika virus Methyltransferase and RNA-dependent RNA polymerase. This in silico “per-residue energy decomposition pharmacophore” virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Keywords: NS5 protein inhibitors, per-residue decomposition, pharmacophore model, virtual screening, Zika virus

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8168 Modeling Optimal Lipophilicity and Drug Performance in Ligand-Receptor Interactions: A Machine Learning Approach to Drug Discovery

Authors: Jay Ananth

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The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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8167 Valorization, Conservation and Sustainable Production of Medicinal Plants in Morocco

Authors: Elachouri Mostafa, Fakchich Jamila, Lazaar Jamila, Elmadmad Mohammed, Marhom Mostafa

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Of course, there has been a great growth in scientific information about medicinal plants in recent decades, but in many ways this has proved poor compensation, because such information is accessible, in practice, only to a very few people and anyway, rather little of it is relevant to problems of management and utilization, as encountered in the field. Active compounds are used in most traditional medicines and play an important role in advancing sustainable rural livelihoods through their conservation, cultivation, propagation, marketing and commercialization. Medicinal herbs are great resources for various pharmaceutical compounds and urgent measures are required to protect these plant species from their natural destruction and disappearance. Indeed, there is a real danger of indigenous Arab medicinal practices and knowledge disappearing altogether, further weakening traditional Arab culture and creating more insecurity, as well as forsaking a resource of inestimable economic and health care importance. As scientific approach, the ethnopharmacological investigation remains the principal way to improve, evaluate, and increase the odds of finding of biologically active compounds derived from medicinal plants. As developing country, belonging to the Mediterranean basin, Morocco country is endowed with resources of medicinal and aromatic plants. These plants have been used over the millennia for human welfare, even today. Besides, Morocco has a large plant biodiversity, in fact, its medicinal flora account more than 4200 species growing on various bioclimatic zones from subhumide to arid and Saharan. Nevertheless, the human and animal pressure resulting from the increase of rural population needs has led to degradation of this patrimony. In this paper, we focus our attention on ethnopharmacological studies carried out in Morocco. The goal of this work is to clarify the importance of herbs as platform for drugs discovery and further development, to highlight the importance of ethnopharmacological study as approach on discovery of natural products in the health care field, and to discuss the limit of ethnopharmacological investigation of drug discovery in Morocco.

Keywords: Morocco, medicinal plants, ethnopharmacology, natural products, drug-discovery

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8166 Using Data Mining in Automotive Safety

Authors: Carine Cridelich, Pablo Juesas Cano, Emmanuel Ramasso, Noureddine Zerhouni, Bernd Weiler

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Safety is one of the most important considerations when buying a new car. While active safety aims at avoiding accidents, passive safety systems such as airbags and seat belts protect the occupant in case of an accident. In addition to legal regulations, organizations like Euro NCAP provide consumers with an independent assessment of the safety performance of cars and drive the development of safety systems in automobile industry. Those ratings are mainly based on injury assessment reference values derived from physical parameters measured in dummies during a car crash test. The components and sub-systems of a safety system are designed to achieve the required restraint performance. Sled tests and other types of tests are then carried out by car makers and their suppliers to confirm the protection level of the safety system. A Knowledge Discovery in Databases (KDD) process is proposed in order to minimize the number of tests. The KDD process is based on the data emerging from sled tests according to Euro NCAP specifications. About 30 parameters of the passive safety systems from different data sources (crash data, dummy protocol) are first analysed together with experts opinions. A procedure is proposed to manage missing data and validated on real data sets. Finally, a procedure is developed to estimate a set of rough initial parameters of the passive system before testing aiming at reducing the number of tests.

Keywords: KDD process, passive safety systems, sled test, dummy injury assessment reference values, frontal impact

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8165 Building a Hierarchical, Granular Knowledge Cube

Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

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A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: granular computing, granular knowledge, hierarchical structuring, knowledge bases

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8164 Presenting a Knowledge Mapping Model According to a Comparative Study on Applied Models and Approaches to Map Organizational Knowledge

Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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8163 Contestation of Local and Non-Local Knowledge in Developing Bali Cattle at Barru Regency, Province of South Sulawesi, Indonesia

Authors: A. Amidah Amrawaty, M. Saleh S. Ali, Darmawan Salman

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The aim of this study was to identify local and non local knowledge in Bali cattle development, to analyze the contestation between local and non-local knowledge. The paradigm used was constructivism paradigm with a qualitative approach. descriptive type of research using case study method. The study was conducted in four villages subjected to Agropolitan Program, i.e. Palakka, Tompo, Galung and Anabanua in Barru District, province of South Sulawesi. The results indicated that the local knowledge of the farmers were: a) knowledge of animal housing, b) knowledge of the prevention and control disease, c) knowledge of the feed, d) knowledge of breed selection, e) knowledge of sharing arrangement, f) knowledge of marketing, Generally, there are three patterns of knowledge contestation namely coexistence, ‘zero sum game’ and hybridization but in this research only coexistence and zero sum game patterns took place, while the pattern of hybridization did not occur.

Keywords: contestation, local knowledge, non-local knowledge, developing of Bali cattle

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8162 In silico Subtractive Genomics Approach for Identification of Strain-Specific Putative Drug Targets among Hypothetical Proteins of Drug-Resistant Klebsiella pneumoniae Strain 825795-1

Authors: Umairah Natasya Binti Mohd Omeershffudin, Suresh Kumar

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Klebsiella pneumoniae, a Gram-negative enteric bacterium that causes nosocomial and urinary tract infections. Particular concern is the global emergence of multidrug-resistant (MDR) strains of Klebsiella pneumoniae. Characterization of antibiotic resistance determinants at the genomic level plays a critical role in understanding, and potentially controlling, the spread of multidrug-resistant (MDR) pathogens. In this study, drug-resistant Klebsiella pneumoniae strain 825795-1 was investigated with extensive computational approaches aimed at identifying novel drug targets among hypothetical proteins. We have analyzed 1099 hypothetical proteins available in genome. We have used in-silico genome subtraction methodology to design potential and pathogen-specific drug targets against Klebsiella pneumoniae. We employed bioinformatics tools to subtract the strain-specific paralogous and host-specific homologous sequences from the bacterial proteome. The sorted 645 proteins were further refined to identify the essential genes in the pathogenic bacterium using the database of essential genes (DEG). We found 135 unique essential proteins in the target proteome that could be utilized as novel targets to design newer drugs. Further, we identified 49 cytoplasmic protein as potential drug targets through sub-cellular localization prediction. Further, we investigated these proteins in the DrugBank databases, and 11 of the unique essential proteins showed druggability according to the FDA approved drug bank databases with diverse broad-spectrum property. The results of this study will facilitate discovery of new drugs against Klebsiella pneumoniae.

Keywords: pneumonia, drug target, hypothetical protein, subtractive genomics

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8161 Creation and Management of Knowledge for Organization Sustainability and Learning

Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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8160 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns

Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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8159 Management of Cultural Heritage: Bologna Gates

Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

Procedia PDF Downloads 386
8158 Towards an Environmental Knowledge System in Water Management

Authors: Mareike Dornhoefer, Madjid Fathi

Abstract:

Water supply and water quality are key problems of mankind at the moment and - due to increasing population - in the future. Management disciplines like water, environment and quality management therefore need to closely interact, to establish a high level of water quality and to guarantee water supply in all parts of the world. Groundwater remediation is one aspect in this process. From a knowledge management perspective it is only possible to solve complex ecological or environmental problems if different factors, expert knowledge of various stakeholders and formal regulations regarding water, waste or chemical management are interconnected in form of a knowledge base. In general knowledge management focuses the processes of gathering and representing existing and new knowledge in a way, which allows for inference or deduction of knowledge for e.g. a situation where a problem solution or decision support are required. A knowledge base is no sole data repository, but a key element in a knowledge based system, thus providing or allowing for inference mechanisms to deduct further knowledge from existing facts. In consequence this knowledge provides decision support. The given paper introduces an environmental knowledge system in water management. The proposed environmental knowledge system is part of a research concept called Green Knowledge Management. It applies semantic technologies or concepts such as ontology or linked open data to interconnect different data and information sources about environmental aspects, in this case, water quality, as well as background material enriching an established knowledge base. Examples for the aforementioned ecological or environmental factors threatening water quality are among others industrial pollution (e.g. leakage of chemicals), environmental changes (e.g. rise in temperature) or floods, where all kinds of waste are merged and transferred into natural water environments. Water quality is usually determined with the help of measuring different indicators (e.g. chemical or biological), which are gathered with the help of laboratory testing, continuous monitoring equipment or other measuring processes. During all of these processes data are gathered and stored in different databases. Meanwhile the knowledge base needs to be established through interconnecting data of these different data sources and enriching its semantics. Experts may add their knowledge or experiences of previous incidents or influencing factors. In consequence querying or inference mechanisms are applied for the deduction of coherence between indicators, predictive developments or environmental threats. Relevant processes or steps of action may be modeled in form of a rule based approach. Overall the environmental knowledge system supports the interconnection of information and adding semantics to create environmental knowledge about water environment, supply chain as well as quality. The proposed concept itself is a holistic approach, which links to associated disciplines like environmental and quality management. Quality indicators and quality management steps need to be considered e.g. for the process and inference layers of the environmental knowledge system, thus integrating the aforementioned management disciplines in one water management application.

Keywords: water quality, environmental knowledge system, green knowledge management, semantic technologies, quality management

Procedia PDF Downloads 192
8157 Complexity Leadership and Knowledge Management in Higher Education

Authors: Prabhakar Venugopal G.

Abstract:

Complex environments triggered by globalization have necessitated new paradigms of leadership – complexity leadership that encompasses multiple roles that leaders need to take upon. The success of higher education institutions depends on how well leaders can provide adaptive, administrative and enabling leadership. Complexity leadership seems all the more relevant for institutions that are knowledge-driven and thrive on knowledge creation, knowledge storage and retrieval, knowledge sharing and knowledge applications. In this paper are the elements of globalization, the opportunities and challenges that are brought forth by globalization are discussed. The complexity leadership paradigm in a knowledge-based economy and the need for such a paradigm shift for higher education institutions is presented. Further, the paper also discusses the support the leader requires in a knowledge-driven economy through knowledge management initiatives.

Keywords: globalization, complexity leadership, knowledge management

Procedia PDF Downloads 459
8156 Information Literacy Skills of Legal Practitioners in Khyber Pakhtunkhwa-Pakistan: An Empirical Study

Authors: Saeed Ullah Jan, Shaukat Ullah

Abstract:

Purpose of the study: The main theme of this study is to explore the information literacy skills of the law practitioners in Khyber Pakhtunkhwa-Pakistan under the heading "Information Literacy Skills of Legal Practitioners in Khyber Pakhtunkhwa-Pakistan: An Empirical Study." Research Method and Procedure: To conduct this quantitative study, the simple random sample approach is used. An adapted questionnaire is distributed among 254 lawyers of Dera Ismail Khan through personal visits and electronic means. The data collected is analyzed through SPSS (Statistical Package for Social Sciences) software. Delimitations of the study: The study is delimited to the southern district of Khyber Pakhtunkhwa: Dera Ismael Khan. Key Findings: Most of the lawyers of District Dera Ismail Khan of Khyber Pakhtunkhwa can recognize and understand the needed information. A large number of lawyers are capable of presenting information in both written and electronic forms. They are not comfortable with different legal databases and using various searching and keyword techniques. They have less knowledge of Boolean operators for locating online information. Conclusion and Recommendations: Efforts should be made to arrange refresher courses and training workshops on the utilization of different legal databases and different search techniques for retrieval of information sources. This practice will enhance the information literacy skills of lawyers, which will ultimately result in a better legal system in Pakistan. Practical implication(s): The findings of the study will motivate the policymakers and authorities of legal forums to restructure the information literacy programs to fulfill the lawyers' information needs. Contribution to the knowledge: No significant work has been done on the lawyers' information literacy skills in Khyber Pakhtunkhwa-Pakistan. It will bring a clear picture of the information literacy skills of law practitioners and address the problems faced by them during the seeking process.

Keywords: information literacy-Pakistan, infromation literacy-lawyers, information literacy-lawyers-KP, law practitioners-Pakistan

Procedia PDF Downloads 114