Search results for: iron based catalyst
27358 A Comparative Study of Virus Detection Techniques
Authors: Sulaiman Al amro, Ali Alkhalifah
Abstract:
The growing number of computer viruses and the detection of zero day malware have been the concern for security researchers for a large period of time. Existing antivirus products (AVs) rely on detecting virus signatures which do not provide a full solution to the problems associated with these viruses. The use of logic formulae to model the behaviour of viruses is one of the most encouraging recent developments in virus research, which provides alternatives to classic virus detection methods. In this paper, we proposed a comparative study about different virus detection techniques. This paper provides the advantages and drawbacks of different detection techniques. Different techniques will be used in this paper to provide a discussion about what technique is more effective to detect computer viruses.Keywords: computer viruses, virus detection, signature-based, behaviour-based, heuristic-based
Procedia PDF Downloads 48427357 Development of an Intelligent Decision Support System for Smart Viticulture
Authors: C. M. Balaceanu, G. Suciu, C. S. Bosoc, O. Orza, C. Fernandez, Z. Viniczay
Abstract:
The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.Keywords: blockchain, IoT, smart agriculture, vineyard
Procedia PDF Downloads 20027356 Modeling and Simulation of a CMOS-Based Analog Function Generator
Authors: Madina Hamiane
Abstract:
Modelling and simulation of an analogy function generator is presented based on a polynomial expansion model. The proposed function generator model is based on a 10th order polynomial approximation of any of the required functions. The polynomial approximations of these functions can then be implemented using basic CMOS circuit blocks. In this paper, a circuit model is proposed that can simultaneously generate many different mathematical functions. The circuit model is designed and simulated with HSPICE and its performance is demonstrated through the simulation of a number of non-linear functions.Keywords: modelling and simulation, analog function generator, polynomial approximation, CMOS transistors
Procedia PDF Downloads 45927355 Robust Variogram Fitting Using Non-Linear Rank-Based Estimators
Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean
Abstract:
In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.Keywords: asymptotic relative efficiency, non-linear rank-based, rank estimates, variogram
Procedia PDF Downloads 43127354 Activity-Based Costing in the Hospitality Industry: A Case Study in a Hotel
Authors: Bita Mashayekhi, Mohammad Ara
Abstract:
The purpose of this study is to provide some empirical evidence about implementing Activity-Based Costing (ABC) in the hospitality industry in Iran. For this purpose, we consider the Tabriz International Hotel as our sample hotel and then gather the relevant data from its cost accounting system in 2012. Then, we use ABC as our costing method and compare the cost of each service unit with that cost which had been extracted for the traditional costing method. The results show a different cost per unit for two methods. Also, because of its more precise and detailed provided information, an ABC system facilitates the decision-making process for managers on decisions related to profitability analysis, budgeting, pricing, and so on.Keywords: Activity-Based Costing (ABC), activity, cost driver, hospitality industry
Procedia PDF Downloads 29827353 Ambiguity Resolution for Ground-based Pulse Doppler Radars Using Multiple Medium Pulse Repetition Frequency
Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu
Abstract:
In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal
Procedia PDF Downloads 15227352 Towards a Measurement-Based E-Government Portals Maturity Model
Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri
Abstract:
The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.Keywords: best practices, e-government portal, maturity model, quality model
Procedia PDF Downloads 33827351 Fault Detection and Isolation of a Three-Tank System using Analytical Temporal Redundancy, Parity Space/Relation Based Residual Generation
Authors: A. T. Kuda, J. J. Dayya, A. Jimoh
Abstract:
This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations
Procedia PDF Downloads 30227350 Case Analysis of Bamboo Based Social Enterprises in India-Improving Profitability and Sustainability
Authors: Priyal Motwani
Abstract:
The current market for bamboo products in India is about Rs. 21000 crores and is highly unorganised and fragmented. In this study, we have closely analysed the structure and functions of a major bamboo craft based organisation in Kerela, India and elaborated about its value chain, product mix, pricing strategy and supply chain, collaborations and competitive landscape. We have identified six major bottlenecks that are prevalent in such organisations, based on the Indian context, in relation to their product mix, asset management, and supply chain- corresponding waste management and retail network. The study has identified that the target customers for the bamboo based products and alternative revenue streams (eco-tourism, microenterprises, training), by carrying out secondary and primary research (5000 sample space), that can boost the existing revenue by 150%. We have then recommended an optimum product mix-covering premium, medium and low valued processing, for medium sized bamboo based organisations, in accordance with their capacity to maximize their revenue potential. After studying such organisations and their counter parts, the study has established an optimum retail network, considering B2B, B2C physical and online retail, to maximize their sales to their target groups. On the basis of the results obtained from the analysis of the future and present trends, our study gives recommendations to improve the revenue potential of bamboo based organisation in India and promote sustainability.Keywords: bamboo, bottlenecks, optimization, product mix, retail network, value chain
Procedia PDF Downloads 21727349 Curriculum Based Measurement and Precision Teaching in Writing Empowerment Enhancement: Results from an Italian Learning Center
Authors: I. Pelizzoni, C. Cavallini, I. Salvaderi, F. Cavallini
Abstract:
We present the improvement in writing skills obtained by 94 participants (aged between six and 10 years) with special educational needs through a writing enhancement program based on fluency principles. The study was planned and conducted with a single-subject experimental plan for each of the participants, in order to confirm the results in the literature. These results were obtained using precision teaching (PT) methodology to increase the number of written graphemes per minute in the pre- and post-test, by curriculum based measurement (CBM). Results indicated an increase in the number of written graphemes for all participants. The average overall duration of the intervention is 144 minutes in five months of treatment. These considerations have been analyzed taking account of the complexity of the implementation of measurement systems in real operational contexts (an Italian learning center) and important aspects of replicability and cost-effectiveness of such interventions.Keywords: curriculum based measurement, precision teaching, writing skill, Italian learning center
Procedia PDF Downloads 12927348 Holistic Risk Assessment Based on Continuous Data from the User’s Behavior and Environment
Authors: Cinzia Carrodano, Dimitri Konstantas
Abstract:
Risk is part of our lives. In today’s society risk is connected to our safety and safety has become a major priority in our life. Each person lives his/her life based on the evaluation of the risk he/she is ready to accept and sustain, and the level of safety he/she wishes to reach, based on highly personal criteria. The assessment of risk a person takes in a complex environment and the impact of actions of other people’actions and events on our perception of risk are alements to be considered. The concept of Holistic Risk Assessment (HRA) aims in developing a methodology and a model that will allow us to take into account elements outside the direct influence of the individual, and provide a personalized risk assessment. The concept is based on the fact that in the near future, we will be able to gather and process extremely large amounts of data about an individual and his/her environment in real time. The interaction and correlation of these data is the key element of the holistic risk assessment. In this paper, we present the HRA concept and describe the most important elements and considerations.Keywords: continuous data, dynamic risk, holistic risk assessment, risk concept
Procedia PDF Downloads 12727347 Management of Nutrition Education in Spa Resorts in Poland
Authors: Joanna Wozniak-Holecka, Sylwia Jaruga-Sekowska
Abstract:
There are 45 statutory spa and treatment areas in Poland, and the demand for spa and treatment services increases year by year. Within each type of spa treatment facilities, nutritional education services are provided. During spa treatment, the patient learns the principles of rational nutrition and applied diet therapy. It should help him develop proper eating habits, which will also follow at home. However, the nutrition education system of spa resort patients should be considered as very imperfect and requiring a definite systemic correction. It has, at the same time, a wide human and infrastructure base, which guarantees to obtain positive reinforcement in the scope of undertaken activities and management. Unfortunately, this advantage is not fully used. The aim of the project was to assess the quality of implemented nutritional education and to assess the diet of patients in spa treatment entities from a nationwide perspective. The material for the study was data obtained as part of an in-depth interview conducted among nutrition department managers (25 interviews) and a survey addressed to patients (600 questionnaires) of a selected group of spa resorts from across the country about the implementation of nutritional education in institutions. Also, decade menus for the basic diet, easily digestible diet and diet with limitation of easily digestible carbohydrates (a total of 1,120 menus) were obtained for the study. Almost 2/3 of respondents (73.2%) were overweight or obese, but only 32.8% decided on an easily digestible or low-energy diet during the treatment. Most of the surveyed patients rated the nutrition in spa resorts as satisfactory. Classes on nutrition education were carried out mainly by a dietitian (65% of meetings), the other educators were doctors and nurses. The meetings (95%) were of a group nature and lasted only 30 minutes on average. The subjects of the classes concerned the principles of proper nutrition and composition of meals, a nutrition pyramid and a diet adapted to a given disease. The assessed menus did not meet the nutrition standards and, therefore, did not provide patients with the correct quality of nutrition. The norm of protein, fat, vitamin A, B12, phosphorus, iron and sodium was exceeded, while vitamin D, folic acid, magnesium and zinc were not enough than recommended. The study allowed to conclude that there is a large discrepancy between the recommendations presented during the nutrition education classes and the quality of diet implemented in the examined institutions. The project may contribute to the development of effective educational tools in nutrition, especially about a specific group of chronically ill patients.Keywords: diet, management, nutritional education, spa resort
Procedia PDF Downloads 14427346 Unsupervised Text Mining Approach to Early Warning System
Authors: Ichihan Tai, Bill Olson, Paul Blessner
Abstract:
Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.Keywords: early warning system, knowledge management, market prediction, topic modeling.
Procedia PDF Downloads 33827345 Live Music Promotion in Burundi Country
Authors: Aster Anderson Rugamba
Abstract:
Context: Live music in Burundi is currently facing neglect and a decline in popularity, resulting in artists struggling to generate income from this field. Additionally, live music from Burundi has not been able to gain traction in the international market. It is essential to establish various structures and organizations to promote cultural events and support artistic endeavors in music and performing arts. Research Aim: The aim of this research is to seek new knowledge and understanding in the field of live music and its content in Burundi. Furthermore, it aims to connect with other professionals in the industry, make new discoveries, and explore potential collaborations and investments. Methodology: The research will utilize both quantitative and qualitative research methodologies. The quantitative approach will involve a sample size of 57 musician artists in Burundi. It will employ closed-ended questions and gather quantitative data to ensure a large sample size and high external validity. The qualitative approach will provide deeper insights and understanding through open-ended questions and in-depth interviews with selected participants. Findings: The research expects to find new theories, methodologies, empirical findings, and applications of existing knowledge that can contribute to the development of live music in Burundi. By exploring the challenges faced by artists and identifying potential solutions, the study aims to establish live music as a catalyst for development and generate a positive impact on both the Burundian and international community. Theoretical Importance: Theoretical contributions of this research will expand the current understanding of the live music industry in Burundi. It will propose new theories and models to address the issues faced by artists and highlight the potential of live music as a lucrative and influential industry. By bridging the gap between theory and practice, the research aims to provide valuable insights for academics, professionals, and policymakers. Data Collection and Analysis Procedures: Data will be collected through surveys, interviews, and archival research. Surveys will be administered to the sample of 57 musician artists, while interviews will be conducted to gain in-depth insights from selected participants. The collected data will be analyzed using both quantitative and qualitative methods, including statistical analysis and thematic analysis, respectively. This mixed-method approach will ensure a comprehensive and rigorous examination of the research questions addressed.Keywords: business music in burundi, music in burundi, promotion of art, burundi music culture
Procedia PDF Downloads 6127344 Non-Convex Multi Objective Economic Dispatch Using Ramp Rate Biogeography Based Optimization
Authors: Susanta Kumar Gachhayat, S. K. Dash
Abstract:
Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.Keywords: economic load dispatch, ELD, biogeography-based optimization, BBO, ramp rate biogeography-based optimization, RRBBO, valve-point loading, VPL
Procedia PDF Downloads 37927343 Multi-Linear Regression Based Prediction of Mass Transfer by Multiple Plunging Jets
Abstract:
The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90O; whereas, multiple inclined plunging jets have jet impact angle of θ = 600. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (KLa) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modelling mass transfer by multiple plunging jets.Keywords: mass transfer, multiple plunging jets, multi-linear regression, earth sciences
Procedia PDF Downloads 46227342 Entropy Risk Factor Model of Exchange Rate Prediction
Authors: Darrol Stanley, Levan Efremidze, Jannie Rossouw
Abstract:
We investigate the predictability of the USD/ZAR (South African Rand) exchange rate with sample entropy analytics for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. These results are preliminary and do not yet account for reasonable transactions costs, although these are very small in currency markets.Keywords: currency trading, entropy, market timing, risk factor model
Procedia PDF Downloads 27127341 Predicting Global Solar Radiation Using Recurrent Neural Networks and Climatological Parameters
Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar
Abstract:
Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error
Procedia PDF Downloads 44427340 A Review on Water Models of Surface Water Environment
Authors: Shahbaz G. Hassan
Abstract:
Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.Keywords: empirical models, mathematical, statistical, water quality
Procedia PDF Downloads 26527339 Fabrication of ZnO Nanorods Based Biosensor via Hydrothermal Method
Authors: Muhammad Tariq, Jafar Khan Kasi, Samiullah, Ajab Khan Kasi
Abstract:
Biosensors are playing vital role in industrial, clinical, and chemical analysis applications. Among other techniques, ZnO based biosensor is an easy approach due to its exceptional chemical and electrical properties. ZnO nanorods have positively charged isoelectric point which helps immobilize the negative charge glucose oxides (GOx). Here, we report ZnO nanorods based biosensors for the immobilization of GOx. The ZnO nanorods were grown by hydrothermal method on indium tin oxide substrate (ITO). The fabrication of biosensors was carried through batch processing using conventional photolithography. The buffer solutions of GOx were prepared in phosphate with a pH value of around 7.3. The biosensors effectively immobilized the GOx and result was analyzed by calculation of voltage and current on nanostructures.Keywords: hydrothermal growth, sol-gel, zinc dioxide, biosensors
Procedia PDF Downloads 30127338 Reframing Service Sector Privatisation Quality Conception with the Theory of Deferred Action
Authors: Mukunda Bastola, Frank Nyame-Asiamah
Abstract:
Economics explanation for privatisation, drawing on neo-liberal market structures and technical efficiency principles has failed to address social imbalance and, distribute the efficiency benefits accrued from privatisation equitably among service users and different classes of people in society. Stakeholders’ interest, which cover ethical values and changing human needs are ignored due to shareholders’ profit maximising strategy with higher service charges. The consequence of these is that, the existing justifications for privatisation have fallen short of customer quality expectations because the underlying plan-based models fail to account for the nuances of customer expectations. We draw on the theory of deferred action to develop a context-based privatisation model, the deferred-based privatisation model, to explain how privatisation could be strategised for the emergent reality of the wider stakeholders’ interests and everyday quality demands of customers which are unpredictable.Keywords: privatisation, service quality, shareholders, deferred action, deferred-based privatisation model
Procedia PDF Downloads 27427337 A Convolutional Neural Network-Based Model for Lassa fever Virus Prediction Using Patient Blood Smear Image
Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa
Abstract:
A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever
Procedia PDF Downloads 12027336 Spherical Harmonic Based Monostatic Anisotropic Point Scatterer Model for RADAR Applications
Authors: Eric Huang, Coleman DeLude, Justin Romberg, Saibal Mukhopadhyay, Madhavan Swaminathan
Abstract:
High performance computing (HPC) based emulators can be used to model the scattering from multiple stationary and moving targets for RADAR applications. These emulators rely on the RADAR Cross Section (RCS) of the targets being available in complex scenarios. Representing the RCS using tables generated from electromagnetic (EM) simulations is often times cumbersome leading to large storage requirement. This paper proposed a spherical harmonic based anisotropic scatterer model to represent the RCS of complex targets. The problem of finding the locations and reflection profiles of all scatterers can be formulated as a linear least square problem with a special sparsity constraint. This paper solves this problem using a modified Orthogonal Matching Pursuit algorithm. The results show that the spherical harmonic based scatterer model can effectively represent the RCS data of complex targets.Keywords: RADAR, RCS, high performance computing, point scatterer model
Procedia PDF Downloads 19127335 Scheduling of Cross-Docking Center: An Auction-Based Algorithm
Authors: Eldho Paul, Brijesh Paul
Abstract:
This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks
Procedia PDF Downloads 41227334 The Impact of International Human Rights Law on Local Efforts to Address Women’s Realities of Violence: Lessons from Jamaica
Authors: Ramona Georgeta Biholar
Abstract:
Gender-based violence against women plagues societies around the world. The work to eliminate it is an ongoing battle. At the international level, Article 5 (a) CEDAW establishes an agenda for social and cultural transformation: it imposes on States parties to CEDAW an obligation to modify sex roles and stereotypical social and cultural patterns of conduct. Also, it provides for the protection of women from violence stemming from such gender norms. Yet, the lived realities of women are frequently disconnected from this agenda. Nonetheless, it is the reality of the local that is crucial for the articulation, implementation and realization of women’s rights in general, and for the elimination of gender-based violence against women in particular. In this paper we discuss the transformation of sex roles and gender stereotyping with a view to realize women’s right to be free from gender-based violence. This paper is anchored in qualitative data collection undertaken in Jamaica and socio-legal research. Based on this research, 1) We explain the process of vernacularisation as a strategy that enables women’s human rights to hit the ground and benefit rights holders, and 2) We present a synergistic model for the implementation of Article 5 (a) CEDAW so that women’s right to be free from gender-based violence can be realized in a concrete national jurisdiction. This model is grounded in context-based demands and recommendations for social and cultural transformation as a remedy for the incidence of gender-based violence against women. Moreover, the synergistic model offers directions that have a general application for the implementation of CEDAW and Article 5 (a) CEDAW in particular, with a view to realize women’s right to be free from gender-based violence. The model is thus not only a conceptual tool of analysis, but also a prescriptive tool for action. It contributes to the work of both academics and practitioners, such as Governmental officials, and national and local civil society representatives. Overall, this paper contributes to understanding the process necessary to bridge that gap between women’s human rights norms and women’s life realities of discrimination and violence.Keywords: CEDAW, gender-based violence against women, international human rights law, women’s rights implementation, the Caribbean
Procedia PDF Downloads 33227333 Benefits of Monitoring Acid Sulfate Potential of Coffee Rock (Indurated Sand) across Entire Dredge Cycle in South East Queensland
Authors: S. Albert, R. Cossu, A. Grinham, C. Heatherington, C. Wilson
Abstract:
Shipping trends suggest increasing vessel size and draught visiting Australian ports highlighting potential challenges to port infrastructure and requiring optimization of shipping channels to ensure safe passage for vessels. The Port of Brisbane in Queensland, Australia has an 80 km long access shipping channel which vessels must transit 15 km of relatively shallow coffee rock (generic class of indurated sands where sand grains are bound within an organic clay matrix) outcrops towards the northern passage in Moreton Bay. This represents a risk to shipping channel deepening and maintenance programs as the dredgeability of this material is more challenging due to its high cohesive strength compared with the surrounding marine sands and potential higher acid sulfate risk. In situ assessment of acid sulfate sediment for dredge spoil control is an important tool in mitigating ecological harm. The coffee rock in an anoxic undisturbed state does not pose any acid sulfate risk, however when disturbed via dredging it’s vital to ensure that any present iron sulfides are either insignificant or neutralized. To better understand the potential risk we examined the reduction potential of coffee rock across the entire dredge cycle in order to accurately portray the true outcome of disturbed acid sulfate sediment in dredging operations in Moreton Bay. In December 2014 a dredge trial was undertaken with a trailing suction hopper dredger. In situ samples were collected prior to dredging revealed acid sulfate potential above threshold guidelines which could lead to expensive dredge spoil management. However, potential acid sulfate risk was then monitored in the hopper and subsequent discharge, both showing a significant reduction in acid sulfate potential had occurred. Additionally, the acid neutralizing capacity significantly increased due to the inclusion of shell fragments (calcium carbonate) from the dredge target areas. This clearly demonstrates the importance of assessing potential acid sulfate risk across the entire dredging cycle and highlights the need to carefully evaluate sources of acidity.Keywords: acid sulfate, coffee rock, indurated sand, dredging, maintenance dredging
Procedia PDF Downloads 36827332 Performance Evaluation of Content Based Image Retrieval Using Indexed Views
Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris
Abstract:
Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.Keywords: content based image retrieval (CBIR), indexed view, color, image retrieval, cross correlation
Procedia PDF Downloads 47027331 Development of Application Architecture for RFID Based Indoor Tracking Using Passive RFID Tag
Authors: Sumaya Ismail, Aijaz Ahmad Rehi
Abstract:
Abstract The location tracking and positioning systems have technologically grown exponentially in recent decade. In particular, Global Position system (GPS) has become a universal norm to be a part of almost every software application directly or indirectly for the location based modules. However major drawback of GPS based system is their inability of working in indoor environments. Researchers are thus focused on the alternative technologies which can be used in indoor environments for a vast range of application domains which require indoor location tracking. One of the most popular technology used for indoor tracking is radio frequency identification (RFID). Due to its numerous advantages, including its cost effectiveness, it is considered as a technology of choice in indoor location tracking systems. To contribute to the emerging trend of the research, this paper proposes an application architecture of passive RFID tag based indoor location tracking system. For the proof of concept, a test bed will be developed to in this study. In addition, various indoor location tracking algorithms will be used to assess their appropriateness in the proposed application architecture.Keywords: RFID, GPS, indoor location tracking, application architecture, passive RFID tag
Procedia PDF Downloads 11727330 Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models
Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh
Abstract:
In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals
Procedia PDF Downloads 30227329 A Lagrangian Hamiltonian Computational Method for Hyper-Elastic Structural Dynamics
Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer
Abstract:
Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.Keywords: Hamilton's principle of least action, particle-based method, hyper-elasticity, analysis of stability
Procedia PDF Downloads 341