Search results for: Risk identification
1376 A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data
Authors: N. Borjalilu, P. Rabiei, A. Enjoo
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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.Keywords: F-TOPSIS, fuzzy set, FDM, flight safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8891375 Impact of Liquidity Crunch on Interbank Network
Authors: I. Lucas, N. Schomberg, F-A. Couturier
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Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced.
Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.
Keywords: Systemic Risk, Financial Contagion, Liquidity Risk, Interbank Market, Network Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20281374 Identification of Anaerobic Microorganisms for Converting Kitchen Waste to Biogas
Authors: A. Malakahmad, S.M. Zain, N.E. Ahmad Basri, S. R. Mohamed Kutty, M. H. Isa
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Anaerobic digestion process is one of the alternative methods to convert organic waste into methane gas which is a fuel and energy source. Activities of various kinds of microorganisms are the main factor for anaerobic digestion which produces methane gas. Therefore, in this study a modified Anaerobic Baffled Reactor (ABR) with working volume of 50 liters was designed to identify the microorganisms through biogas production. The mixture of 75% kitchen waste and 25% sewage sludge was used as substrate. Observations on microorganisms in the ABR showed that there exists a small amount of protozoa (5%) and fungi (2%) in the system, but almost 93% of the microorganism population consists of bacteria. It is definitely clear that bacteria are responsible for anaerobic biodegradation of kitchen waste. Results show that in the acidification zone of the ABR (front compartments of reactor) fast growing bacteria capable of growth at high substrate levels and reduced pH was dominant. A shift to slower growing scavenging bacteria that grow better at higher pH was occurring towards the end of the reactor. Due to the ability of activity in acetate environment the percentages of Methanococcus, Methanosarcina and Methanotrix were higher than other kinds of methane former in the system.Keywords: Anaerobic microorganism identification, Kitchenwaste, Biogas.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25641373 A Real-Time Specific Weed Recognition System Using Statistical Methods
Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan
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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22661372 Health Risk Assessment for Sewer Workers using Bayesian Belief Networks
Authors: Kevin Fong-Rey Liu, Ken Yeh, Cheng-Wu Chen, Han-Hsi Liang
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The sanitary sewerage connection rate becomes an important indicator of advanced cities. Following the construction of sanitary sewerages, the maintenance and management systems are required for keeping pipelines and facilities functioning well. These maintenance tasks often require sewer workers to enter the manholes and the pipelines, which are confined spaces short of natural ventilation and full of hazardous substances. Working in sewers could be easily exposed to a risk of adverse health effects. This paper proposes the use of Bayesian belief networks (BBN) as a higher level of noncarcinogenic health risk assessment of sewer workers. On the basis of the epidemiological studies, the actual hospital attendance records and expert experiences, the BBN is capable of capturing the probabilistic relationships between the hazardous substances in sewers and their adverse health effects, and accordingly inferring the morbidity and mortality of the adverse health effects. The provision of the morbidity and mortality rates of the related diseases is more informative and can alleviate the drawbacks of conventional methods.Keywords: Bayesian belief networks, sanitary sewerage, healthrisk assessment, hazard quotient, target organ-specific hazard index.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17071371 OCR for Script Identification of Hindi (Devnagari) Numerals using Error Diffusion Halftoning Algorithm with Neural Classifier
Authors: Banashree N. P., Andhe Dharani, R. Vasanta, P. S. Satyanarayana
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The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).
Keywords: OCR, Halftoning, Neural classifier, 16-segmentdisplay concept.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17161370 Gene Expression Signature for Classification of Metastasis Positive and Negative Oral Cancer in Homosapiens
Authors: A. Shukla, A. Tarsauliya, R. Tiwari, S. Sharma
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Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.
Keywords: Cancer, Gene Signature, SAM, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20771369 Kinematic Hardening Parameters Identification with Respect to Objective Function
Authors: Marina Franulovic, Robert Basan, Bozidar Krizan
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Constitutive modeling of material behavior is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behavior of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behavior modeling.
Keywords: Genetic algorithm, kinematic hardening, material model, objective function
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38011368 Safety Climate Assessment and Its Impact on the Productivity of Construction Enterprises
Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska
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Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.
Keywords: Civil engineering, occupational health, productivity, safety climate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11221367 Pension Plan Member’s Investment Strategies with Transaction Cost and Couple Risky Assets Modelled by the O-U Process
Authors: Udeme O. Ini, Edikan E. Akpanibah
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This paper studies the optimal investment strategies for a plan member (PM) in a defined contribution (DC) pension scheme with transaction cost, taxes on invested funds and couple risky assets (stocks) under the Ornstein-Uhlenbeck (O-U) process. The PM’s portfolio is assumed to consist of a risk-free asset and two risky assets where the two risky assets are driven by the O-U process. The Legendre transformation and dual theory is use to transform the resultant optimal control problem which is a nonlinear partial differential equation (PDE) into linear PDE and the resultant linear PDE is then solved for the explicit solutions of the optimal investment strategies for PM exhibiting constant absolute risk aversion (CARA) using change of variable technique. Furthermore, theoretical analysis is used to study the influences of some sensitive parameters on the optimal investment strategies with observations that the optimal investment strategies for the two risky assets increase with increase in the dividend and decreases with increase in tax on the invested funds, risk averse coefficient, initial fund size and the transaction cost.
Keywords: Ornstein-Uhlenbeck process, portfolio management, Legendre transforms, CARA utility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4841366 Structured Phospholipids from Commercial Soybean Lecithin Containing Omega-3 Fatty Acids Reduces Atherosclerosis Risk in Male Sprague dawley Rats which Fed with an Atherogenic Diet
Authors: Jaya Mahar Maligan, Teti Estiasih, Joni Kusnadi
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Structured phospholipids from commercial soybean lecithin with oil enriched omega-3 fatty acid form by product of tuna canning is alternative procedure to provides the stability of omega-3 fatty acid structure and increase these bioactive function in metabolism. Best treatment condition was obtain in 18 hours acidolysis reaction with 30% enzyme concentration, which EPADHA incorporation level was 127,47 mg/g and incorporation percentage of EPA-DHA was 51,04% at phospholipids structure. This structured phospolipids could reduce atherosclerosis risk in male Sprague dawley rat. Provision of structured phospholipids has significant effect (α = 0.05) on changes in lipid profile, intima-media thickness of aorta rats (male Sprague dawley) fed atherogenic diet. Structured phospholipids intake can lower total cholesterol 78.36 mg/dL, total triglycerides 94,57 mg/dL, LDL levels 87.08 mg/dL and increased HDL level as much as 12,64 mg/dL in 10 weeks cares. Structured phospholipids intake also can prevent the thickening of the intima-media layer of the aorta.Keywords: Structured phospholipids, commercial soybean lecithin, omega-3 fatty acid, atherosclerosis risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25641365 Capacities of Early Childhood Education Professionals for the Prevention of Social Exclusion of Children
Authors: Dejana Bouillet, Vlatka Domović
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Both policymakers and researchers recognize that participating in early childhood education and care (ECEC) is useful for all children, especially for those who are exposed to the high risk of social exclusion. Social exclusion of children is understood as a multidimensional construct including economic, social, cultural, health, and other aspects of disadvantage and deprivation, which individually or combined can have an unfavorable effect on the current life and development of a child, as well as on the child’s development and on disadvantaged life chances in adult life. ECEC institutions should be able to promote educational approaches that portray developmental, cultural, language, and other diversity amongst children. However, little is known about the ways in which Croatian ECEC institutions recognize and respect the diversity of children and their families and how they respond to their educational needs. That is why this paper is dedicated to the analysis of the capacities of ECEC professionals to respond to the demands of educational needs of this very diverse group of children and their families. The results obtained in the frame of the project “Models of response to educational needs of children at risk of social exclusion in ECEC institutions,” funded by the Croatian Science Foundation, will be presented. The research methodology arises from explanations of educational processes and risks of social exclusion as a complex and heterogeneous phenomenon. The preliminary results of the qualitative data analysis of educational practices regarding capacities to identify and appropriately respond to the requirements of children at risk of social exclusion will be presented. The data have been collected by interviewing educational staff in 10 Croatian ECEC institutions (n = 10). The questions in the interviews were related to various aspects of inclusive institutional policy, culture, and practices. According to the analysis, it is possible to conclude that Croatian ECEC professionals are still faced with great challenges in the process of implementation of inclusive policies, culture, and practices. There are several baselines of this conclusion. The interviewed educational professionals are not familiar enough with the whole complexity and diversity of needs of children at risk of social exclusion, and the ECEC institutions do not have enough resources to provide all interventions that these children and their families need.
Keywords: children at risk of social exclusion, ECEC professionals, inclusive policies, culture and practices, interpretative phenomenological analysis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6311364 Building an Inferential Model between Caregivers and Patients by using RFID
Authors: Yung-Ting Chang, Chung-You Tsai, Yu-Chuan Li
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Nosocomial (i.e., hospital-acquired) infections (NI) is a major cause of morbidity and mortality in hospitals. NI rate is higher in intensive care units (ICU) than in the general ward due to patients with severe symptoms, poor immunity, and accepted many invasive therapies. Contact behaviors between health caregivers and patients is one of the infect factors. It is difficult to obtain complete contact records by traditional method of retrospective analysis of medical records. This paper establishes a contact history inferential model (CHIM) intended to extend the use of Proximity Sensing of rapid frequency identification (RFID) technology to transferring all proximity events between health caregivers and patients into clinical events (close-in events, contact events and invasive events).The results of the study indicated that the CHIM can infer proximity care activities into close-in events and contact events. The infection control team could redesign and build optimal workflow in the ICU according to the patient-specific contact history which provided by our automatic tracing system.Keywords: Active Radio Frequency Identification, Intensive Care Unit, Nosocomial Infections
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16261363 The Capacity Building in the Natural Disaster Management of Thailand
Authors: Eakarat Boonreang
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The past two decades, Thailand faced the natural disasters, for instance, Gay typhoon in 1989, tsunami in 2004, and huge flood in 2011. The disaster management in Thailand was improved both structure and mechanism for cope with the natural disaster since 2007. However, the natural disaster management in Thailand has various problems, for examples, cooperation between related an organizations have not unity, inadequate resources, the natural disaster management of public sectors not proactive, people has not awareness the risk of the natural disaster, and communities did not participate in the natural disaster management. Objective of this study is to find the methods for capacity building in the natural disaster management of Thailand. The concept and information about the capacity building and the natural disaster management of Thailand were reviewed and analyzed by classifying and organizing data. The result found that the methods for capacity building in the natural disaster management of Thailand should be consist of 1) link operation and information in the natural disaster management between nation, province, local and community levels, 2) enhance competency and resources of public sectors which relate to the natural disaster management, 3) establish proactive natural disaster management both planning and implementation, 4) decentralize the natural disaster management to local government organizations, 5) construct public awareness in the natural disaster management to community, 6) support Community Based Disaster Risk Management (CBDRM) seriously, and 7) emphasis on participation in the natural disaster management of all stakeholders.
Keywords: Capacity Building, Community Based Disaster Risk Management, Natural Disaster Management, Thailand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32491362 Pattern Recognition Techniques Applied to Biomedical Patterns
Authors: Giovanni Luca Masala
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Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Keywords: Computer Aided Detection, mammary tumor, pattern recognition, dissimilarity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23631361 Artificial Neural Networks Application to Improve Shunt Active Power Filter
Authors: Rachid.Dehini, Abdesselam.Bassou, Brahim.Ferdi
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Active Power Filters (APFs) are today the most widely used systems to eliminate harmonics compensate power factor and correct unbalanced problems in industrial power plants. We propose to improve the performances of conventional APFs by using artificial neural networks (ANNs) for harmonics estimation. This new method combines both the strategies for extracting the three-phase reference currents for active power filters and DC link voltage control method. The ANNs learning capabilities to adaptively choose the power system parameters for both to compute the reference currents and to recharge the capacitor value requested by VDC voltage in order to ensure suitable transit of powers to supply the inverter. To investigate the performance of this identification method, the study has been accomplished using simulation with the MATLAB Simulink Power System Toolbox. The simulation study results of the new (SAPF) identification technique compared to other similar methods are found quite satisfactory by assuring good filtering characteristics and high system stability.Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total Harmonic Distortion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20361360 A Third Drop Level For TCP-RED Congestion Control Strategy
Authors: Nabhan Hamadneh, Michael Dixon, Peter Cole, David Murray
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This work presents the Risk Threshold RED (RTRED) congestion control strategy for TCP networks. In addition to the maximum and minimum thresholds in existing RED-based strategies, we add a third dropping level. This new dropping level is the risk threshold which works with the actual and average queue sizes to detect the immediate congestion in gateways. Congestion reaction by RTRED is on time. The reaction to congestion is neither too early, to avoid unfair packet losses, nor too late to avoid packet dropping from time-outs. We compared our novel strategy with RED and ARED strategies for TCP congestion handling using a NS-2 simulation script. We found that the RTRED strategy outperformed RED and ARED.Keywords: AQM, congestion control, RED, TCP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14941359 Issues Problems of Sedimentation in Reservoir Siazakh Dam Case Study
Authors: Reza Gharehkhani
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Sedimentation in reservoirs lowers the quality of consumed water, reduce the volume of reservoir, lowers the controllable amount of flood, increases the risk of water overflow during possible floods and the risk of reversal and reduction of dam's useful life. So in all stages of dam establishment such as cognitive studies, phase-1 studies of design, control, construction and maintenance, the problem of sedimentation in reservoir should be considered. What engineers need to do is examine and develop the methods to keep effective capacity of a reservoir, however engineers should also consider the influences of the methods on the flood disaster, functions of water use facilities and environmental issues.This article first examines the sedimentation in reservoirs and shows how to control it and then discusses the studies about the sedimens in Siazakh Dam.Keywords: Sedimentation, Reservoir, Sediment Control, Dam
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26551358 Artificial Intelligence Techniques applied to Biomedical Patterns
Authors: Giovanni Luca Masala
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Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.Keywords: Computer Aided Detection, mammary tumor, pattern recognition, thalassemia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14251357 Public Private Partnership for Infrastructure Projects: Mapping the Key Risks
Authors: Julinda Keçi
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In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and useroriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework, this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: construction, design, economic, legal, market, natural, operation, political, project finance, project selection and relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.
Keywords: Construction, infrastructure, public private partnerships, risks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35261356 Vehicle Risk Evaluation in Low Speed Accidents: Consequences for Relevant Test Scenarios
Authors: Philip Feig, Klaus Gschwendtner, Julian Schatz, Frank Diermeyer
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Projects of accident research analysis are mostly focused on accidents involving personal damage. Property damage only has a high frequency of occurrence combined with high economic impact. This paper describes main influencing parameters for the extent of damage and presents a repair cost model. For a prospective evaluation method of the monetary effect of advanced driver assistance systems (ADAS), it is necessary to be aware of and quantify all influencing parameters. Furthermore, this method allows the evaluation of vehicle concepts in combination with an ADAS at an early point in time of the product development process. In combination with a property damage database and the introduced repair cost model relevant test scenarios for specific vehicle configurations and their individual property damage risk may be determined. Currently, equipment rates of ADAS are low and a purchase incentive for customers would be beneficial. The next ADAS generation will prevent property damage to a large extent or at least reduce damage severity. Both effects may be a purchasing incentive for the customer and furthermore contribute to increased traffic safety.Keywords: Property damage analysis, effectiveness, ADAS, damage risk, accident research, accident scenarios.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13891355 Identification of Seat Belt Wearing Compliance Associate Factors in Malaysia: Evidence-based Approach
Authors: L. Fauziana, M. F. Siti Atiqah, Z. A. Ahmad Noor Syukri
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The aim of the study was to identify seat belt wearing factor among road users in Malaysia. Evidence-based approach through in-depth crash investigation was utilised to determine the intended objectives. The objective was scoped into crashes investigated by Malaysian Institute of Road Safety Research (MIROS) involving passenger vehicles within 2007 and 2010. Crash information of a total of 99 crash cases involving 240 vehicles and 864 occupants were obtained during the study period. Statistical test and logistic regression analysis have been performed. Results of the analysis revealed that gender, seat position and age were associated with seat belt wearing compliance in Malaysia. Males are 97.6% more likely to wear seat belt compared to females (95% CI 1.317 to 2.964). By seat position, the finding indicates that frontal occupants were 82 times more likely to be wearing seat belt (95% CI 30.199 to 225.342) as compared to rear occupants. It is also important to note that the odds of seat belt wearing increased by about 2.64% (95% CI 1.0176 to 1.0353) for every one year increase in age. This study is essential in understanding the Malaysian tendency in belting up while being occupied in a vehicle. The factors highlighted in this study should be emphasized in road safety education in order to increase seat belt wearing rate in this country and ultimately in preventing deaths due to road crashes.Keywords: crash investigation, risk compensation, road safety, seat belt wearing, statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19661354 Sexual Behaviors and Condom Attitude among Injecting Drug Users in Hai Phong, Vietnam: Qualitative Findings
Authors: Tanvir Ahmed, Thanh N. Long, Phan T. Huong, Donald E. Stewart
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This paper presents views on condom use and the contexts of safe and unsafe sexual practices with different sexual partners and their relationships among Injecting Drug Users (IDUs) in Hai Phong, Vietnam. Fifteen IDUs participated and two local interviewers conducted qualitative semi-structured face-to-face interviews in September-October, 2012 in Vietnamese language. Data were analyzed thematically. Non-protective condom attitudes include negotiate or convince Female Sex Workers (FSW); not realizing risk, importance or necessity; partner doesn’t like, and having extra money/drug from clients. On the other hand, self-awareness, family-consciousness, suspicion of STI presence, fear of getting HIV, and client negotiation sometimes resulted in a safe-sex practice. A thematic diagram was developed to present the relationship (strong/weak) between condom attitude and sexual practice (safe/unsafe) by partner types. The experiences and views reflected in the qualitative information emphasize the heightened need for safe-sex education especially among young IDUs (male/female) highlighting sexual transmission risk.
Keywords: AIDS, HIV, injecting drug user, risk behaviors, Vietnam.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18691353 Canada Deuterium Uranium Updated Fire Probabilistic Risk Assessment Model for Canadian Nuclear Plants
Authors: Hossam Shalabi, George Hadjisophocleous
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The Canadian Nuclear Power Plants (NPPs) use some portions of NUREG/CR-6850 in carrying out Fire Probabilistic Risk Assessment (PRA). An assessment for the applicability of NUREG/CR-6850 to CANDU reactors was performed and a CANDU Fire PRA was introduced. There are 19 operating CANDU reactors in Canada at five sites (Bruce A, Bruce B, Darlington, Pickering and Point Lepreau). A fire load density survey was done for all Fire Safe Shutdown Analysis (FSSA) fire zones in all CANDU sites in Canada. National Fire Protection Association (NFPA) Standard 557 proposes that a fire load survey must be conducted by either the weighing method or the inventory method or a combination of both. The combination method results in the most accurate values for fire loads. An updated CANDU Fire PRA model is demonstrated in this paper that includes the fuel survey in all Canadian CANDU stations. A qualitative screening step for the CANDU fire PRA is illustrated in this paper to include any fire events that can damage any part of the emergency power supply in addition to FSSA cables.
Keywords: Fire safety, CANDU, nuclear, fuel densities, FDS, qualitative analysis, fire probabilistic risk assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7421352 Risk Assessment of Acrylamide Intake from Roasted Potatoes in Latvia
Authors: Irisa Murniece, Daina Karklina, Ruta Galoburda
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From food consumption surveys has been found that potato consumption comparing to other European countries is one of the highest. Hence acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine acrylamide content and estimate intake of acrylamide from roasted potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile, and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. Time and temperature (210 ± 5°C) was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. estimated intake of acrylamide ranges from 0.012 to 0.496μgkg-1 BW per day.
Keywords: potato, roasting, variety, acrylamide, Latvia, risk assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20641351 Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette
Authors: M.K. Bhuyan, Aragala Jagan.
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Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19131350 A Method for Iris Recognition Based on 1D Coiflet Wavelet
Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa
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There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.Keywords: Biometric, iris recognition, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19061349 Improved Text-Independent Speaker Identification using Fused MFCC and IMFCC Feature Sets based on Gaussian Filter
Authors: Sandipan Chakroborty, Goutam Saha
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A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel- Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.Keywords: Gaussian Filter, Triangular Filter, Subbands, Correlation, MFCC, IMFCC, GMM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24541348 A New Fuzzy DSS/ES for Stock Portfolio Selection using Technical and Fundamental Approaches in Parallel
Authors: H. Zarei, M. H. Fazel Zarandi, M. Karbasian
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A Decision Support System/Expert System for stock portfolio selection presented where at first step, both technical and fundamental data used to estimate technical and fundamental return and risk (1st phase); Then, the estimated values are aggregated with the investor preferences (2nd phase) to produce convenient stock portfolio. In the 1st phase, there are two expert systems, each of which is responsible for technical or fundamental estimation. In the technical expert system, for each stock, twenty seven candidates are identified and with using rough sets-based clustering method (RC) the effective variables have been selected. Next, for each stock two fuzzy rulebases are developed with fuzzy C-Mean method and Takai-Sugeno- Kang (TSK) approach; one for return estimation and the other for risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation method. In parallel, for fundamental expert systems, fuzzy rule-bases have been identified in the form of “IF-THEN" rules through brainstorming with the stock market experts and the input data have been derived from financial statements; as a result two fuzzy rule-bases have been generated for all the stocks, one for return and the other for risk. In the 2nd phase, user preferences represented by four criteria and are obtained by questionnaire. Using an expert system, four estimated values of return and risk have been aggregated with the respective values of user preference. At last, a fuzzy rule base having four rules, treats these values and produce a ranking score for each stock which will lead to a satisfactory portfolio for the user. The stocks of six manufacturing companies and the period of 2003-2006 selected for data gathering.Keywords: Stock Portfolio Selection, Fuzzy Rule-Base ExpertSystems, Financial Decision Support Systems, Technical Analysis, Fundamental Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18421347 Design and Simulation of Portable Telemedicine System for High Risk Cardiac Patients
Authors: V. Thulasi Bai, Srivatsa S. K.
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Deaths from cardiovascular diseases have decreased substantially over the past two decades, largely as a result of advances in acute care and cardiac surgery. These developments have produced a growing population of patients who have survived a myocardial infarction. These patients need to be continuously monitored so that the initiation of treatment can be given within the crucial golden hour. The available conventional methods of monitoring mostly perform offline analysis and restrict the mobility of these patients within a hospital or room. Hence the aim of this paper is to design a Portable Cardiac Telemedicine System to aid the patients to regain their independence and return to an active work schedule, there by improving the psychological well being. The portable telemedicine system consists of a Wearable ECG Transmitter (WET) and a slightly modified mobile phone, which has an inbuilt ECG analyzer. The WET is placed on the body of the patient that continuously acquires the ECG signals from the high-risk cardiac patients who can move around anywhere. This WET transmits the ECG to the patient-s Bluetooth enabled mobile phone using blue tooth technology. The ECG analyzer inbuilt in the mobile phone continuously analyzes the heartbeats derived from the received ECG signals. In case of any panic condition, the mobile phone alerts the patients care taker by an SMS and initiates the transmission of a sample ECG signal to the doctor, via the mobile network.
Keywords: WET, ECG analyzer, Bluetooth, mobilecellular network, high risk cardiac patients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2107