Search results for: Activity Learning

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 884

Authors: María Teresa García-Álvarez, Isabel Soares, Rosa María Mariz-Pérez

Abstract:

Directive 2009/28/CE establishes, as obligatory objective, a share of renewable energies on energetic consumption of 20%, in European Union, in 2020 However, such European normative gives freedom to member states in the selection of the renewable promotion mechanism that allows them to obtain that objective. In this paper, we analyze the main characteristics of the promotion mechanisms of renewable energy used in the countries that shape the Electricity Iberian Market (Spain and Portugal) and the results in employment. The importance of these countries is given by the great increasing of the renewable energies which suppose a share higher than 30% of the overall generation in 2010. Therefore, this research paper can serve as the basis for the learning of other countries with regard to the main advantages that entail the use of a feed-in tariff system.

Keywords: Employment, Energy policy, Professional profiles, Renewable energies, Professional profiles.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1925

Authors: Sajjad Farashi

Abstract:

Neurons in the nervous system communicate with each other by producing electrical signals called spikes. To investigate the physiological function of nervous system it is essential to study the activity of neurons by detecting and sorting spikes in the recorded signal. In this paper a method is proposed for considering the spike sorting problem which is based on the nonlinear modeling of spikes using exponential autoregressive model. The genetic algorithm is utilized for model parameter estimation. In this regard some selected model coefficients are used as features for sorting purposes. For optimal selection of model coefficients, self-organizing feature map is used. The results show that modeling of spikes with nonlinear autoregressive model outperforms its linear counterpart. Also the extracted features based on the coefficients of exponential autoregressive model are better than wavelet based extracted features and get more compact and well-separated clusters. In the case of spikes different in small-scale structures where principal component analysis fails to get separated clouds in the feature space, the proposed method can obtain well-separated cluster which removes the necessity of applying complex classifiers.

Keywords: Exponential autoregressive model, Neural data, spike sorting, time series modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1757

Authors: Ali Nouri

Abstract:

Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: Neuroeducation studies, neuroeducational theory, theory building, neuroeducation research.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432

Authors: Sukir Maryanto, Didik R. Santosa, Iyan Mulyana, Muhammad Hendrasto

Abstract:

Successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were analyzed to investigate the dynamical system regarding to their eruptive mechanism. The eruptive activity at Semeru volcano East Java, Indonesia is intermittent emission of ash and bombs with Strombolian style which occurred at interval of 15 to 45 minutes. The explosive eruptions accompanied by explosion earthquakes and followed by volcanic tremor which generated by continuous emission of volcanic ash. The spectral and Lyapunov exponent of successive event of explosion and harmonic tremor were analyzed. Peak frequencies of explosion earthquakes range 1.2 to 1.9 Hz and those of the harmonic tremor have peak frequency range 1.5 — 2.2 Hz. The phase space is reconstructed and evaluated based on the Lyapunov exponents. Harmonic tremors have smaller Lyapunov exponent than explosion earthquakes. It can be considerably as correlated complexity of the mechanism from the variance of spectral and fractal dimension and can be concluded that the successive event of harmonic tremor and explosions are chaotic.

Keywords: Semeru volcano, explosion earthquakes, harmonic tremor, lyapunov exponent, chaotic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1564

Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

Abstract:

Data in IT systems in enterprises have been growing at phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several Artificial Intelligence/Machine Learning (AI/ML) and Business Intelligence (BI) tools and technologies available in marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information and intelligence components and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: Architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1282

Authors: Ljubomir Nikolic, Larisa Trichtchenko

Abstract:

The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation. 

Keywords: Space weather, numerical modeling, coronal field, solar wind.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2121

Authors: M.A. Lazim, M.T.Abu Osman

Abstract:

This paper deals with the application of a fuzzy set in measuring teachers- beliefs about mathematics. The vagueness of beliefs was transformed into standard mathematical values using a fuzzy preferences model. The study employed a fuzzy approach questionnaire which consists of six attributes for measuring mathematics teachers- beliefs about mathematics. The fuzzy conjoint analysis approach based on fuzzy set theory was used to analyze the data from twenty three mathematics teachers from four secondary schools in Terengganu, Malaysia. Teachers- beliefs were recorded in form of degrees of similarity and its levels of agreement. The attribute 'Drills and practice is one of the best ways of learning mathematics' scored the highest degree of similarity at 0. 79860 with level of 'strongly agree'. The results showed that the teachers- beliefs about mathematics were varied. This is shown by different levels of agreement and degrees of similarity of the measured attributes.

Keywords: belief, membership function, degree of similarity, conjoint analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2329

Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

Abstract:

The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: Demand forecasting, machine learning, risk management, supply chain design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 136

Authors: K. Ben Khalifa, M.H. Bédoui, M. Dogui, F. Alexandre

Abstract:

Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.

Keywords: Electroencephalogram interpretation, artificialneural networks, vigilance states, hardware implementation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1467

Authors: Clarissa L. de Araujo, Kátia N. Suzuki, Wilson T. V. Machado, Luis F. Bellido, Alfredo V.B. Bellido

Abstract:

This study aims at contributing to the characterization of the process of biological incorporation of chromium by two benthonic species, the macroalgae Ulva sp. and the aquatic macrophyte Ruppia maritima, to subsidize future activities of monitoring the contamination of aquatic biota. This study is based on laboratory experiments to characterize the incorporation kinetics of the radiotracer ⁵¹Cr in two oxidation states (III and VI), under different salinities (7, 15, and 21 ‰). Samples of two benthonic species were collected on the margins of Rodrigo de Freitas Lagoon (Rio de Janeiro, Brazil), acclimated in the laboratory and subsequently subjected to experiments. In tests with 51Cr (III and IV), it was observed that accumulation of the metal in Ulva sp. has inverse relationship with salinity, while for R. maritima, the maximum accumulation occurs in salinity 21‰. In experiments with Cr(III), increases in the uptake of ion by both species were verified. The activity of Cr(III) was up to 19 times greater than the Cr(VI). As regards the potential for accumulation of metals, a better sensitivity of Ulva sp. for any chromium tri or hexavalent forms was verified, while for the Cr(VI) it will require low salinities and longer exposure (>24h). For R. maritima, the results showed the uptake of Cr(VI) increase along with time (>20h), because this species is more resistant for the hexavalent form and useful for any salinity as well.

Keywords: Chromium, Cr-51, macroalgae, macrophyte, uptake.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 994

Authors: Kadio Valere R. Angaman, Birahim Bouna Niang

Abstract:

Land degradation is a serious problem in developing countries including Cote d’Ivoire, which has its economy focused on agriculture. It occurs in all kinds of ecosystems over the world. However, the drivers of land degradation vary from one region to another, and from one ecosystem to another. Thus, identifying these drivers is an essential prerequisite to develop and implement appropriate policies to reverse the trend of land degradation in the country, especially in the trays ecosystem. Using the binary logistic model with primary data obtained through 780 farmers surveyed, we analyze and identify the drivers of land degradation in the trays ecosystem. The descriptive statistics show that 52% of farmers interviewed have stated facing land degradation in their farmland. This high rate shows the extent of land degradation in this ecosystem. Also, the results obtained from the binary logit regression reveal that land degradation is significantly influenced by a set of variables such as sex, education, slope, erosion, pesticide, agricultural activity, deforestation, and temperature. The drivers identified are mostly local, as a result, the government must implement some policies and strategies that facilitate and incentive the adoption of sustainable land management practices by farmers to reverse the negative trend of land degradation.

Keywords: Drivers, land degradation, trays ecosystem, sustainable land management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 376

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: Finance, machine learning, opening price, stock market.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 482

Authors: Maia Margvelashvili, Kakhaber Cheishvili, Ineza Vatsadze

Abstract:

In Capitalism all economic activity rests upon a set of core institutional foundations, main from which are privately owned capital assets and profit. How these core institutional foundations are working in former soviet countries, in particular in Travel and Tourism Industry of Georgia? The role of Travel and Tourism as a key pillar of economic growth is being increasingly recognized by governments in all regions of the world. For the last few years Georgia succeeded in the World Bank and IFC “Doing Business” rankings. Despite of that, during decades totally different statistical data of the tourism sector were provided by the different State bodies; economic parameters were published few, or not published at all. The frequency and extent of property rights violation in Georgia has repeatedly been the subject of concern for the last decade. Total value of abrogated by the former Georgian Government private property is estimated approximately in US$4-5 billion. Thus, if economic profitability is unknown and property rights are not protected – that means that the main institutional foundations of capitalism in Georgia, are not working properly yet, that cause management problems at all levels of the national Travel and Tourism industry of Georgia.

Keywords: Institutional foundations of capitalism, Tourism management, Transition stage.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1633

Authors: Sayed Amir Hamzeh Mirkheshti

Abstract:

Offshore wind energy as a strategic renewable energy, has been growing rapidly due to availability, abundance and clean nature of it. On the other hand, budget of this project is incredibly higher in comparison with other renewable energies and it takes more duration. Accordingly, precise estimation of time and cost is needed in order to promote awareness in the developers and society and to convince them to develop this kind of energy despite its difficulties. Occurrence risks during on project would cause its duration and cost constantly changed. Therefore, to develop offshore wind power, it is critical to consider all potential risks which impacted project and to simulate their impact. Hence, knowing about these risks could be useful for the selection of most influencing strategies such as avoidance, transition, and act in order to decrease their probability and impact. This paper presents an evaluation of the feasibility of 500 MV offshore wind project in the Persian Gulf and compares its situation with uncertainty resources and risk. The purpose of this study is to evaluate time and cost of offshore wind project under risk circumstances and uncertain resources by using Monte Carlo simulation. We analyzed each risk and activity along with their distribution function and their effect on the project.

Keywords: Wind energy project; uncertain resources; risks; Monte Carlo simulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 783

Authors: E. A. Makky

Abstract:

Studies were carried out on the comparative study of the production of Avicelase enzyme using sugarcane bagasse-SCB in two different statuses (i.e. treated and untreated SCB) by thermophilic Geobacillus stearothermophilus at 50ºC. Only four thermophilic bacterial isolates were isolated and assayed for Avicelase production using UntSCB and TSCB. Only one isolate selected as most potent and identified as G. stearothermophilus used in this study. A specific endo-β-1,4-D-glucanase (Avicelase EC 3.2.1.91) was partially purified from a thermophilic bacterial strain was isolated from different soil samples when grown on cellulose enrichment SCB substrate as the sole carbon source. Results shown that G. stearothermophilus was the better Avicelase producer strain. Avicelase had an optimum pH and temperature 7.0 and 50ºC for both UntSCB and TSCB and exhibited good pH stability between "5-8" and "4-9", however, good temperature stability between (30-80ºC) for UntSCB and TSCB, respectively. Other factors affecting the production of Avicelase were compared (i.e. SCB concentration, inoculum size and different incubation periods), all results observed and obtained were revealed that the TSCB was exhibited maximal enzyme activity in comparison with the results obtained from UntSCB, so, the TSCB was enhancing the Avicelase production.

Keywords: Geobacillus stearothermophilus, Avicelase, Sugarcane bagasse

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2795

Authors: Manpreet Singh, Parvinder Singh, Suman

Abstract:

The data is available in abundance in any business organization. It includes the records for finance, maintenance, inventory, progress reports etc. As the time progresses, the data keep on accumulating and the challenge is to extract the information from this data bank. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of business. For the development of accurate and required information for particular problem, business analyst needs to develop multidimensional models which give the reliable information so that they can take right decision for particular problem. If the multidimensional model does not possess the advance features, the accuracy cannot be expected. The present work involves the development of a Multidimensional data model incorporating advance features. The criterion of computation is based on the data precision and to include slowly change time dimension. The final results are displayed in graphical form.

Keywords: Multidimensional, data precision.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1440

Authors: Honghao Ren, Mariko Kondo

Abstract:

This study investigates the perceptual features of Japanese obstruent geminates among Chinese learners of Japanese, focusing on the dialectal effect of the checked-tone, a syllable that ends in a stop consonant or a glottal stop, which is similar to Japanese obstruent geminates phonetically. In this study, 41 native speakers of Cantonese are divided into two groups based on their proficiency as well as learning period of Japanese. All stimuli employed in this study are made into C[p,k,s]+V[a,e,i] structure such as /apa/, /eke/, /isi/. Both original sounds and synthesized sounds are used in three different parts of this study. The results of the present study show that the checked-tone does have the positive effect on the perception of Japanese gemination. Furthermore, the proportion of closure duration in the entire word would be a more reliable and appropriate criterion in testing this kind of task.

Keywords: Dialectal differences, Cantonese learners of Japanese, acoustic experiment, closure duration.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 626

Authors: W. Wanmolee, W. Sornlake, N. Laosiripojana, V. Champreda

Abstract:

Conversion of lignocellulosic biomass is the basis process for production of fuels, chemicals and materials in the sustainable biorefinery industry. Saccharification of lignocellulosic biomass is an essential step which produces sugars for further conversion to target value-added products e.g. bio-ethanol, bio-plastic, g-valerolactone (GVL), 5-hydroxymethylfuroic acid (HMF), levulinic acid, etc. The goal of this work was to develop an efficient enzyme for conversion of biomass to reducing sugar based on crude fungal enzyme from Chaetomium globosum BCC5776 produced by submerged fermentation and evaluate its activity comparing to a commercial Acremonium cellulase. Five local biomasses in Thailand: rice straw, sugarcane bagasse, corncobs, corn stovers, and palm empty fruit bunches were pretreated and hydrolyzed with varying enzyme loadings. Saccharification of the biomass led to different reducing sugar levels from 115 mg/g to 720 mg/g from different types of biomass using cellulase dosage of 9 FPU/g. The reducing sugar will be further employed as sugar feedstock for production of ethanol or commodity chemicals. This work demonstrated the use of promising enzyme candidate for conversion of local lignocellulosic biomass in biorefinery industry.

Keywords: Biomass, Cellulase, Chaetomiun glubosum, Saccharification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2365

Authors: César Camisón-Zornoza, Beatriz Forés-Julián, Alba Puig-Denia

Abstract:

The literature has argued that firms based in industrial districts enjoy advantages for creating internal knowledge and absorbing external knowledge as a consequence of to the knowledge flows and spillovers that exist in the district. However, empirical evidence to show how belonging to an industrial district affects the business processes of creation and absorption of knowledge is scarce and, moreover, empirical research has not taken into account the influence of variations in the flows of knowledge circulating in each cluster. This study aims to extend empirical evidence on the effect that the stock of shared competencies in industrial districts has on the business processes of creation and absorption of knowledge, through data from an initial study on 952 firms and 35 industrial districts in Spain.

Keywords: Absorptive capacity, industrial district, knowledge creation, organisational learning

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1618

Authors: P. Cermak

Abstract:

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Keywords: Mind, Multi-agent system, Cognitive analysis, Fuzzy system, Neural network, Genetic algorithm, Rule base.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1236

Authors: Dennys Robson Girardi, Hugo Bulegon, Claudia Maria Moro Barra

Abstract:

Leprosy is an infectious disease caused by Mycobacterium Leprae, this disease, generally, compromises the neural fibers, leading to the development of disability. Disabilities are changes that limit daily activities or social life of a normal individual. When comes to leprosy, the study of disability considered the functional limitation (physical disabilities), the limitation of activity and social participation, which are measured respectively by the scales: EHF, SALSA and PARTICIPATION SCALE. The objective of this work is to propose an on-line monitoring of leprosy patients, which is based on information scales EHF, SALSA and PARTICIPATION SCALE. It is expected that the proposed system is applied in monitoring the patient during treatment and after healing therapy of the disease. The correlations that the system is between the scales create a variety of information, presented the state of the patient and full of changes or reductions in disability. The system provides reports with information from each of the scales and the relationships that exist between them. This way, health professionals, with access to patient information, can intervene with techniques for the Prevention of Disability. Through the automated scale, the system shows the level of the patient and allows the patient, or the responsible, to take a preventive measure. With an online system, it is possible take the assessments and monitor patients from anywhere.

Keywords: Leprosy, Medical Informatics, Decision SupportSystem, Disability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2034

Authors: Quratulain N. Rajput, Sajjad Haider, Nasir Touheed

Abstract:

The internet has become an attractive avenue for global e-business, e-learning, knowledge sharing, etc. Due to continuous increase in the volume of web content, it is not practically possible for a user to extract information by browsing and integrating data from a huge amount of web sources retrieved by the existing search engines. The semantic web technology enables advancement in information extraction by providing a suite of tools to integrate data from different sources. To take full advantage of semantic web, it is necessary to annotate existing web pages into semantic web pages. This research develops a tool, named OWIE (Ontology-based Web Information Extraction), for semantic web annotation using domain specific ontologies. The tool automatically extracts information from html pages with the help of pre-defined ontologies and gives them semantic representation. Two case studies have been conducted to analyze the accuracy of OWIE.

Keywords: Ontology, Semantic Annotation, Wrapper, Information Extraction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2098

Authors: Joanna M. Dulińska, Maria Fabijańska

Abstract:

In the paper the results of calculations of the dynamic response of a multi-storey reinforced concrete building to a strong mining shock originated from the main region of mining activity in Poland (i.e. the Legnica-Glogow Copper District) are presented. The representative time histories of accelerations registered in three directions were used as ground motion data in calculations of the dynamic response of the structure. Two variants of a numerical model were applied: the model including only structural elements of the building and the model including both structural and non-structural elements (i.e. partition walls and ventilation ducts made of brick). It turned out that non-structural elements of multi-storey RC buildings have a small impact of about 10 % on natural frequencies of these structures. It was also proved that the dynamic response of building to mining shock obtained in case of inclusion of all non-structural elements in the numerical model is about 20 % smaller than in case of consideration of structural elements only. The principal stresses obtained in calculations of dynamic response of multi-storey building to strong mining shock are situated on the level of about 30% of values obtained from static analysis (dead load).

Keywords: Dynamic characteristics of buildings, mining shocks, dynamic response of buildings, non-structural elements

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1867

Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

Abstract:

Knowledge management is considered as an important factor in improving health care services. KM facilitates the transfer of existing knowledge and the development of new knowledge in hospitals. This paper reviews practices adopted by doctors in Kuwait for capturing, sharing, and generating knowledge. It also discusses the perceived impact of KM practices on performance of hospitals. Based on a survey of 277 doctors, the study found that KM practices among doctors in the sampled hospitals were not very effective. Little attention was paid to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, good km practices were perceived by doctors to have a positive impact on performance of hospitals. It was concluded that through effective KM practices hospitals could improve the services they provide. Documentation of best practices and capturing of lessons learnt for re-use of knowledge could help transform the hospitals into learning organizations.

Keywords: Health Sector, Hospitals, Knowledge Management, Kuwait, Tools and Practices.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3506

Authors: Ayu S. Muhamad, Michael Gleeson

Abstract:

Immunomodulators are substances that alter immune system via dynamic regulation of messenger molecules. It can be divided into immunostimulant and immunosuppressant. It can help to increase immunity of people with a low immune system, and also can help to normalize an overactive immune system. Aim of this study is to investigate the effects of in vitro exposure to low and high doses of several immunomodulators which include caffeine, kaloba and quercetin on antigen-stimulated whole blood culture cytokine production. Whole blood samples were taken from 5 healthy males (age: 32 ± 12 years; weight: 75.7 ± 6.1 kg; BMI: 24.3 ± 1.5 kg/m2) following an overnight fast with no vigorous activity during the preceding 24 h. The whole blood was then stimulated with 50 μl of 100 x diluted Pediacel vaccine and low or high dose of immunomodulators in the culture plate. After 20 h incubation (5% CO2, 37°C), it was analysed using the Evidence Investigator to determine the production of cytokines including IL-2, IL-4, IL-10, IFN-γ, and IL-1α. Caffeine and quercetin showed a tendency towards decrease cytokine production as the doses were increased. On the other hand, an upward trend was evident with kaloba, where a high dose of kaloba seemed to increase the cytokine production. In conclusion, we found that caffeine and quercetin have potential as immunosuppressant and kaloba as immunostimulant.

Keywords: Caffeine, cytokine, immunomodulators, kaloba, quercetin.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2290

Authors: Elin Cahyaningsih, Dana Indra Sensuse, Wahyu Catur Wibowo, Sofiyanti Indriasari

Abstract:

Bureaucracy reform program drives Indonesian government to change their management to enhance their organizational performance. Information technology became one of strategic plan that organization tried to improve. Knowledge management system is one of information system that supporting knowledge management implementation in government which categorized as people perspective, because this system has high dependency in human interaction and participation. Strategic plan for developing knowledge management system can be determine using some of information system strategic methods. This research conducted to define type of strategic method of information system, stage of activity each method, strength and weakness. Literature review methods used to identify and classify strategic methods of information system, differentiate method type, categorize common activities, strength and weakness. Result of this research are determine and compare six strategic information system methods, Balanced Scorecard and Risk Analysis believe as common strategic method that usually used and have the highest excellence strength.

Keywords: Knowledge management system, balanced scorecard, five force, risk analysis, gap analysis, value chain analysis, SWOT analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2632

Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

Abstract:

Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: BERT, chatbot, cryptocurrency, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 948

Authors: J. C. Moctezuma, V. Breña-Medina, Jose Luis Nunez-Yanez, Joseph P. McGeehan

Abstract:

In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focus in two principal parameters: current and leakage conductance. Study of stable and unstable solutions are explored; also Hop-bifurcation and frequency interpretation when current varies is examined. This study allows having control of neuron dynamics and neuron response when these parameters change. Analysis like this is particularly important for several applications such as: tuning parameters in learning process, neuron excitability tests, measure bursting properties of the neuron, etc. Finally, a hardware implementation results were developed to corroborate these results.

Keywords: Traub model, Pinsky-Rinzel model, Hopf bifurcation, single-compartment models, Bifurcation analysis, neuron modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1196

Authors: Hadi Veisi, Mansour Jamzad

Abstract:

In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2203