Search results for: non-linear programming
460 Stochastic Optimization of a Vendor-Managed Inventory Problem in a Two-Echelon Supply Chain
Authors: Bita Payami-Shabestari, Dariush Eslami
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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory
Procedia PDF Downloads 122459 Distributed Cost-Based Scheduling in Cloud Computing Environment
Authors: Rupali, Anil Kumar Jaiswal
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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc. Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively. Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.Keywords: physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model
Procedia PDF Downloads 162458 Development of a Matlab® Program for the Bi-Dimensional Truss Analysis Using the Stiffness Matrix Method
Authors: Angel G. De Leon Hernandez
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A structure is defined as a physical system or, in certain cases, an arrangement of connected elements, capable of bearing certain loads. The structures are presented in every part of the daily life, e.g., in the designing of buildings, vehicles and mechanisms. The main goal of a structure designer is to develop a secure, aesthetic and maintainable system, considering the constraint imposed to every case. With the advances in the technology during the last decades, the capabilities of solving engineering problems have increased enormously. Nowadays the computers, play a critical roll in the structural analysis, pitifully, for university students the vast majority of these software are inaccessible due to the high complexity and cost they represent, even when the software manufacturers offer student versions. This is exactly the reason why the idea of developing a more reachable and easy-to-use computing tool. This program is designed as a tool for the university students enrolled in courser related to the structures analysis and designs, as a complementary instrument to achieve a better understanding of this area and to avoid all the tedious calculations. Also, the program can be useful for graduated engineers in the field of structural design and analysis. A graphical user interphase is included in the program to make it even simpler to operate it and understand the information requested and the obtained results. In the present document are included the theoretical basics in which the program is based to solve the structural analysis, the logical path followed in order to develop the program, the theoretical results, a discussion about the results and the validation of those results.Keywords: stiffness matrix method, structural analysis, Matlab® applications, programming
Procedia PDF Downloads 114457 Statistical Data Analysis of Migration Impact on the Spread of HIV Epidemic Model Using Markov Monte Carlo Method
Authors: Ofosuhene O. Apenteng, Noor Azina Ismail
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Over the last several years, concern has developed over how to minimize the spread of HIV/AIDS epidemic in many countries. AIDS epidemic has tremendously stimulated the development of mathematical models of infectious diseases. The transmission dynamics of HIV infection that eventually developed AIDS has taken a pivotal role of much on building mathematical models. From the initial HIV and AIDS models introduced in the 80s, various improvements have been taken into account as how to model HIV/AIDS frameworks. In this paper, we present the impact of migration on the spread of HIV/AIDS. Epidemic model is considered by a system of nonlinear differential equations to supplement the statistical method approach. The model is calibrated using HIV incidence data from Malaysia between 1986 and 2011. Bayesian inference based on Markov Chain Monte Carlo is used to validate the model by fitting it to the data and to estimate the unknown parameters for the model. The results suggest that the migrants stay for a long time contributes to the spread of HIV. The model also indicates that susceptible individual becomes infected and moved to HIV compartment at a rate that is more significant than the removal rate from HIV compartment to AIDS compartment. The disease-free steady state is unstable since the basic reproduction number is 1.627309. This is a big concern and not a good indicator from the public heath point of view since the aim is to stabilize the epidemic at the disease equilibrium.Keywords: epidemic model, HIV, MCMC, parameter estimation
Procedia PDF Downloads 592456 DLtrace: Toward Understanding and Testing Deep Learning Information Flow in Deep Learning-Based Android Apps
Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li
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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.Keywords: mobile computing, deep learning apps, sensitive information, static analysis
Procedia PDF Downloads 163455 The Impact of Vertical Product Differentiation on Exchange Rate Pass-Through: An Empirical Investigation of IRON and Steel Industry between Thailand and Vietnam
Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya
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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation
Procedia PDF Downloads 137454 Simulation of Mid Infrared Supercontinuum Generation in Silicon Germanium Photonic Waveguides for Gas Spectroscopy
Authors: Proficiency Munsaka, Peter Baricholo, Erich Rohwer
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Pulse evolutions along the 5 cm long, 6.0 ×4.2 μm² cross-section silicon germanium (SiGe) photonic waveguides were simulated and compared with experiments. Simulations were carried out by solving a generalized nonlinear Schrodinger equation (GNLSE) for an optical pulse evolution along the length of the SiGe photonic waveguides by the split-step Fourier method (SSFM). The solution obtained from the SSFM gave the pulse envelope in both time and spectral domain calculated at each distance step along the propagation direction. The SiGe photonic waveguides were pumped in an anomalous group velocity dispersion (GVD) regime using a 4.7 μm, 210 fs femtosecond laser to produce a significant supercontinuum (SC). The simulated propagation of ultrafast pulse along the SiGe photonic waveguides produced an SC covering the atmospheric window (2.5-8.5 μm) containing the molecular fingerprints for important gases. Thus, the mid-infrared supercontinuum generation in SiGe photonic waveguides system can be commercialized for gas spectroscopy for detecting gases that include CO₂, CH₄, H₂O, SO₂, SO₃, NO₂, H₂S, CO, and NO at trace level using absorption spectroscopy technique. The simulated profile evolutions are spectrally and temporally similar to those obtained by other researchers. Obtained evolution profiles are characterized by pulse compression, Soliton fission, dispersive wave generation, stimulated Raman Scattering, and Four Wave mixing.Keywords: silicon germanium photonic waveguide, supercontinuum generation, spectroscopy, mid infrared
Procedia PDF Downloads 122453 A Fuzzy Hybrıd Decısıon Support System for Naval Base Place Selectıon in a Foreıgn Country
Authors: Latif Yanar, Muharrem Kaçan
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In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making
Procedia PDF Downloads 389452 Rising STI Prevalence among MSM Clients in Calabar, Nigeria: A Call to Action
Authors: Ugoh Kelechi Melford, Anene O.
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Introduction: Evidence has shown that there are increasing rates of new HIV and other STI infections occurring among Men who have Sex with Men (MSM) in Nigeria, with the prevalence 3 times higher than the general population as reported by the 2011 National Integrated Bio Behavioral Surveillance Survey. The poor state of health care and support services hinders our effort to control the high rates of these new infections among MSM. Methods: The Initiative for Improved Male Health (IMH-Initiative) works to provide a safe space for young MSM living with HIV to access comprehensive palliative care and support, as well as referrals for other services through drama and dance competitions. An STI assessment was conducted in IMH-Initiative’s Community Center in Calabar, for gay men and other MSM. An STI history was conducted for all clients who visited the community clinic specifically for HCT and STI counseling and referrals within a 5 month period, and their data were collated. Results: 61 MSM were diagnosed, and reported the following in the last 6 months. 49 where living with HIV. 46 had previous histories of untreated anal warts. 20 had previous histories of treated Gonorrhea by self-medication and herbs. 21 had untreated boils and rashes around the genitals. 10 clients where living with HIV, and reported untreated penile and rectal gonorrhea. All clients indicated that there were not comfortable discussing STI infections with staff of public hospitals. Conclusion: It is evident that a reasonable number of STI infections among MSM are not completely treated or ignored. This thereby increases the individual’s risk of HIV infection, and cripples HIV prevention programming in Nigeria. HIV programs targeting MSM must incorporate STI syndromic management, so as to increase access to non-stigmatized diagnosis and treatment of STIs. Also, access to STI drugs for clients cannot be overemphasized.Keywords: MSM, IBBSS, STI, IMH
Procedia PDF Downloads 326451 Nine-Level Shunt Active Power Filter Associated with a Photovoltaic Array Coupled to the Electrical Distribution Network
Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir
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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control
Procedia PDF Downloads 332450 Taleb's Complexity Theory Concept of 'Antifragility' Has a Significant Contribution to Make to Positive Psychology as Applied to Wellbeing
Authors: Claudius Peter Van Wyk
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Given the increasingly manifest phenomena, as described in complexity theory, of volatility, uncertainty, complexity and ambiguity (VUCA), Taleb's notion of 'antifragility, has a significant contribution to make to positive psychology applied to wellbeing. Antifragility is argued to be fundamentally different from the concepts of resiliency; as the ability to recover from failure, and robustness; as the ability to resist failure. Rather it describes the capacity to reorganise in the face of stress in such a way as to cope more effectively with systemic challenges. The concept, which has been applied in disciplines ranging from physics, molecular biology, planning, engineering, and computer science, can now be considered for its application in individual human and social wellbeing. There are strong correlations to Antonovsky's model of 'salutogenesis' in which an attitude and competencies are developed of transforming burdening factors into greater resourcefulness. We demonstrate, from the perspective of neuroscience, how technology measuring nervous system coherence can be coupled to acquired psychodynamic approaches to not only identify contextual stressors, utilise biofeedback instruments for facilitating greater coherence, but apply these insights to specific life stressors that compromise well-being. Employing an on-going case study with BMW South Africa, the neurological mapping is demonstrated together with 'reframing' and emotional anchoring techniques from neurolinguistic programming. The argument is contextualised in the discipline of psychoneuroimmunology which describes the stress pathways from the CNS and endocrine systems and their impact on immune function and the capacity to restore homeostasis.Keywords: antifragility, complexity, neuroscience, psychoneuroimmunology, salutogenesis, volatility
Procedia PDF Downloads 371449 Design and Implementation of Low-code Model-building Methods
Authors: Zhilin Wang, Zhihao Zheng, Linxin Liu
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This study proposes a low-code model-building approach that aims to simplify the development and deployment of artificial intelligence (AI) models. With an intuitive way to drag and drop and connect components, users can easily build complex models and integrate multiple algorithms for training. After the training is completed, the system automatically generates a callable model service API. This method not only lowers the technical threshold of AI development and improves development efficiency but also enhances the flexibility of algorithm integration and simplifies the deployment process of models. The core strength of this method lies in its ease of use and efficiency. Users do not need to have a deep programming background and can complete the design and implementation of complex models with a simple drag-and-drop operation. This feature greatly expands the scope of AI technology, allowing more non-technical people to participate in the development of AI models. At the same time, the method performs well in algorithm integration, supporting many different types of algorithms to work together, which further improves the performance and applicability of the model. In the experimental part, we performed several performance tests on the method. The results show that compared with traditional model construction methods, this method can make more efficient use, save computing resources, and greatly shorten the model training time. In addition, the system-generated model service interface has been optimized for high availability and scalability, which can adapt to the needs of different application scenarios.Keywords: low-code, model building, artificial intelligence, algorithm integration, model deployment
Procedia PDF Downloads 15448 Solution-Processed Threshold Switching Selectors Based on Highly Flexible, Transparent and Scratchable Silver Nanowires Conductive Films
Authors: Peiyuan Guan, Tao Wan, Dewei Chu
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With the flash memory approaching its physical limit, the emerging resistive random-access memory (RRAM) has been considered as one of the most promising candidates for the next-generation non-volatile memory. One selector-one resistor configuration has shown the most promising way to resolve the crosstalk issue without affecting the scalability and high-density integration of the RRAM array. By comparison with other candidates of selectors (such as diodes and nonlinear devices), threshold switching selectors dominated by formation/spontaneous rupture of fragile conductive filaments have been proved to possess low voltages, high selectivity, and ultra-low current leakage. However, the flexibility and transparency of selectors are barely mentioned. Therefore, it is a matter of urgency to develop a selector with highly flexible and transparent properties to assist the application of RRAM for a diversity of memory devices. In this work, threshold switching selectors were designed using a facilely solution-processed fabrication on AgNWs@PDMS composite films, which show high flexibility, transparency and scratch resistance. As-fabricated threshold switching selectors also have revealed relatively high selectivity (~107), low operating voltages (Vth < 1 V) and good switching performance.Keywords: flexible and transparent, resistive random-access memory, silver nanowires, threshold switching selector
Procedia PDF Downloads 125447 Optimization of Multi Commodities Consumer Supply Chain: Part 1-Modelling
Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong
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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system
Procedia PDF Downloads 307446 Tribocorrosion Behavior of Austempered Ductile Iron Microalloyed with Boron
Authors: S. Gvazava, N. Khidasheli, G. Gordeziani, A. DL. Batako
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The work presented in this paper studied the tribological characteristics (wear resistance, friction coefficient) of austempered ductile iron (ADI) with different combinations of structural composition (upper bainite, lower bainite, retained austenite) in dry sliding friction. A range of structural states of the metal matrix was obtained by changing the regimes of isothermal quenching of high-strength cast iron. The tribological tests were carried out using two sets of isothermal quenched cast irons. After austenitization at 900°С for 60 minutes, the specimens from the first group were isothermally quenched at the 300°С temperature and the specimens from the second set – at 400°С. The investigations showed that the isothermal quenching increases the friction coefficient of high-strength cast irons. The friction coefficient was found to be in the range from 0.4 to 0.55 for cast irons, depending on the structures of the metal matrix. The quenched cast irons having lower bainite demonstrate higher wear resistance in dry friction conditions. The dependence of wear resistance on the amount of retained austenite in isothermal quenched cast irons has a nonlinear characteristic and reaches its maximum value when the content of retained austenite is about 15-22%. The boron micro-additives allowed to reduce the friction coefficient of ADI and increase their wear resistance by 1.5-1.7 times.Keywords: wear resistance, dry sliding, austempering, ADI, friction coefficient, retained austenite, isothermal quenching
Procedia PDF Downloads 174445 Optimization Technique for the Contractor’s Portfolio in the Bidding Process
Authors: Taha Anjamrooz, Sareh Rajabi, Salwa Bheiry
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Selection between the available projects in bidding processes for the contractor is one of the essential areas to concentrate on. It is important for the contractor to choose the right projects within its portfolio during the tendering stage based on certain criteria. It should align the bidding process with its origination strategies and goals as a screening process to have the right portfolio pool to start with. Secondly, it should set the proper framework and use a suitable technique in order to optimize its selection process for concertation purpose and higher efforts during the tender stage with goals of success and winning. In this research paper, a two steps framework proposed to increase the efficiency of the contractor’s bidding process and the winning chance of getting the new projects awarded. In this framework, initially, all the projects pass through the first stage screening process, in which the portfolio basket will be evaluated and adjusted in accordance with the organization strategies to the reduced version of the portfolio pool, which is in line with organization activities. In the second stage, the contractor uses linear programming to optimize the portfolio pool based on available resources such as manpower, light equipment, heavy equipment, financial capability, return on investment, and success rate of winning the bid. Therefore, this optimization model will assist the contractor in utilizing its internal resource to its maximum and increase its winning chance for the new project considering past experience with clients, built-relation between two parties, and complexity in the exertion of the projects. The objective of this research will be to increase the contractor's winning chance in the bidding process based on the success rate and expected return on investment.Keywords: bidding process, internal resources, optimization, contracting portfolio management
Procedia PDF Downloads 138444 Maximizing Profit Using Optimal Control by Exploiting the Flexibility in Thermal Power Plants
Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey
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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model
Procedia PDF Downloads 132443 Oil Demand Forecasting in China: A Structural Time Series Analysis
Authors: Tehreem Fatima, Enjun Xia
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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)
Procedia PDF Downloads 279442 Web-Based Learning in Nursing: The Sample of Delivery Lesson Program
Authors: Merve Kadioğlu, Nevin H. Şahin
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Purpose: This research is organized to determine the influence of the web-based learning program. The program has been developed to gain information about normal delivery skill that is one of the topics of nursing students who take the woman health and illness. Material and Methods: The methodology of this study was applied as pre-test post-test single-group quasi-experimental. The pilot study consisted of 28 nursing student study groups who agreed to participate in the study. The findings were gathered via web-based technologies: student information form, information evaluation tests, Web Based Training Material Evaluation Scale and web-based learning environment feedback form. In the analysis of the data, the percentage, frequency and Wilcoxon Signed Ranks Test were used. The Web Based Instruction Program was developed in the light of full learning model, Mayer's research-based multimedia development principles and Gagne's Instructional Activities Model. Findings: The average scores of it was determined in accordance with the web-based educational material evaluation scale: ‘Instructional Suitability’ 4.45, ‘Suitability to Educational Program’ 4.48, ‘Visual Adequacy’ 4.53, ‘Programming Eligibility / Technical Adequacy’ 4.00. Also, the participants mentioned that the program is successful and useful. A significant difference was found between the pre-test and post-test results of the seven modules (p < 0.05). Results: According to pilot study data, the program was rated ‘very good’ by the study group. It was also found to be effective in increasing knowledge about normal labor.Keywords: normal delivery, web-based learning, nursing students, e-learning
Procedia PDF Downloads 173441 Estimation of Consolidating Settlement Based on a Time-Dependent Skin Friction Model Considering Column Surface Roughness
Authors: Jiang Zhenbo, Ishikura Ryohei, Yasufuku Noriyuki
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Improvement of soft clay deposits by the combination of surface stabilization and floating type cement-treated columns is one of the most popular techniques worldwide. On the basis of one dimensional consolidation model, a time-dependent skin friction model for the column-soil interaction is proposed. The nonlinear relationship between column shaft shear stresses and effective vertical pressure of the surrounding soil can be described in this model. The influence of column-soil surface roughness can be represented using a roughness coefficient R, which plays an important role in the design of column length. Based on the homogenization method, a part of floating type improved ground will be treated as an unimproved portion, which with a length of αH1 is defined as a time-dependent equivalent skin friction length. The compression settlement of this unimproved portion can be predicted only using the soft clay parameters. Apart from calculating the settlement of this composited ground, the load transfer mechanism is discussed utilizing model tests. The proposed model is validated by comparing with calculations and laboratory results of model and ring shear tests, which indicate the suitability and accuracy of the solutions in this paper.Keywords: floating type improved foundation, time-dependent skin friction, roughness, consolidation
Procedia PDF Downloads 462440 Efficiency of Robust Heuristic Gradient Based Enumerative and Tunneling Algorithms for Constrained Integer Programming Problems
Authors: Vijaya K. Srivastava, Davide Spinello
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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3n enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3n integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm
Procedia PDF Downloads 320439 Designing of Content Management Systems (CMS) for Web Development
Authors: Abdul Basit Kiani, Maryam Kiani
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Content Management Systems (CMS) have transformed the landscape of web development by providing an accessible and efficient platform for creating and managing digital content. This abstract explores the key features and benefits of CMS in web development, highlighting its impact on website creation and maintenance. CMS offers a user-friendly interface that empowers individuals to create, edit, and publish content without requiring extensive technical knowledge. With customizable templates and themes, users can personalize the design and layout of their websites, ensuring a visually appealing online presence. Furthermore, CMS facilitates efficient content organization through categorization and tagging, enabling visitors to navigate and search for information effortlessly. It also supports version control, allowing users to track and manage revisions effectively. Scalability is a notable advantage of CMS, as it offers a wide range of plugins and extensions to integrate additional features into websites. From e-commerce functionality to social media integration, CMS adapts to evolving business needs. Additionally, CMS enhances collaborative workflows by allowing multiple user roles and permissions. This enables teams to collaborate effectively on content creation and management, streamlining processes and ensuring smooth coordination. In conclusion, CMS serves as a powerful tool in web development, simplifying content creation, customization, organization, scalability, and collaboration. With CMS, individuals and businesses can create dynamic and engaging websites, establishing a strong online presence with ease.Keywords: web development, content management systems, information technology, programming
Procedia PDF Downloads 77438 Dynamic Behavior of Brain Tissue under Transient Loading
Authors: Y. J. Zhou, G. Lu
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In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury
Procedia PDF Downloads 263437 Optimal Geothermal Borehole Design Guided By Dynamic Modeling
Authors: Hongshan Guo
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Ground-source heat pumps provide stable and reliable heating and cooling when designed properly. The confounding effect of the borehole depth for a GSHP system, however, is rarely taken into account for any optimization: the determination of the borehole depth usually comes prior to the selection of corresponding system components and thereafter any optimization of the GSHP system. The depth of the borehole is important to any GSHP system because the shallower the borehole, the larger the fluctuation of temperature of the near-borehole soil temperature. This could lead to fluctuations of the coefficient of performance (COP) for the GSHP system in the long term when the heating/cooling demand is large. Yet the deeper the boreholes are drilled, the more the drilling cost and the operational expenses for the circulation. A controller that reads different building load profiles, optimizing for the smallest costs and temperature fluctuation at the borehole wall, eventually providing borehole depth as the output is developed. Due to the nature of the nonlinear dynamic nature of the GSHP system, it was found that between conventional optimal controller problem and model predictive control problem, the latter was found to be more feasible due to a possible history of both the trajectory during the iteration as well as the final output could be computed and compared against. Aside from a few scenarios of different weighting factors, the resulting system costs were verified with literature and reports and were found to be relatively accurate, while the temperature fluctuation at the borehole wall was also found to be within acceptable range. It was therefore determined that the MPC is adequate to optimize for the investment as well as the system performance for various outputs.Keywords: geothermal borehole, MPC, dynamic modeling, simulation
Procedia PDF Downloads 282436 Control System Design for a Simulated Microbial Electrolysis Cell
Authors: Pujari Muruga, T. K. Radhakrishnan, N. Samsudeen
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Hydrogen is considered as the most important energy carrier and fuel of the future because of its high energy density and zero emission properties. Microbial Electrolysis Cell (MEC) is a new and promising approach for hydrogen production from organic matter, including wastewater and other renewable resources. By utilizing anode microorganism activity, MEC can produce hydrogen gas with smaller voltages (as low as 0.2 V) than those required for electrolytic hydrogen production ( ≥ 1.23 V). The hydrogen production processes of the MEC reactor are very nonlinear and highly complex because of the presence of microbial interactions and highly complex phenomena in the system. Increasing the hydrogen production rate and lowering the energy input are two important challenges of MEC technology. The mathematical model of the MEC is based on material balance with the integration of bioelectrochemical reactions. The main objective of the research is to produce biohydrogen by selecting the optimum current and controlling applied voltage to the MEC. Precise control is required for the MEC reactor, so that the amount of current required to produce hydrogen gas can be controlled according to the composition of the substrate in the reactor. Various simulation tests involving multiple set-point changes disturbance and noise rejection were performed to evaluate the performance using PID controller tuned with Ziegler Nichols settings. Simulation results shows that other good controller can provide better control effect on the MEC system, so that higher hydrogen production can be obtained.Keywords: microbial electrolysis cell, hydrogen production, applied voltage, PID controller
Procedia PDF Downloads 239435 Contribution of Spatial Teledetection to the Geological Mapping of the Imiter Buttonhole: Application to the Mineralized Structures of the Principal Corps B3 (CPB3) of the Imiter Mine (Anti-atlas, Morocco)
Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad
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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments
Procedia PDF Downloads 91434 Optimal Energy Management and Environmental Index Optimization of a Microgrid Operating by Renewable and Sustainable Generation Systems
Authors: Nabil Mezhoud
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The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm
Procedia PDF Downloads 64433 Design and Implementation of the Embedded Control System for the Electrical Motor Based Cargo Vehicle
Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki
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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)
Procedia PDF Downloads 202432 Using the SMT Solver to Minimize the Latency and to Optimize the Number of Cores in an NoC-DSP Architectures
Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui
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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.Keywords: multi-cores DSP, scheduling, SMT solver, workflow
Procedia PDF Downloads 280431 Reservoir Inflow Prediction for Pump Station Using Upstream Sewer Depth Data
Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim
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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth
Procedia PDF Downloads 309