Search results for: multi agent system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21715

Search results for: multi agent system

21145 Efficient Chiller Plant Control Using Modern Reinforcement Learning

Authors: Jingwei Du

Abstract:

The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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21144 Green Thumb Engineering - Explainable Artificial Intelligence for Managing IoT Enabled Houseplants

Authors: Antti Nurminen, Avleen Malhi

Abstract:

Significant progress in intelligent systems in combination with exceedingly wide application domains having machine learning as the core technology are usually opaque, non-intuitive, and commonly complex for human users. We use innovative IoT technology which monitors and analyzes moisture, humidity, luminosity and temperature levels to assist end users for optimization of environmental conditions for their houseplants. For plant health monitoring, we construct a system yielding the Normalized Difference Vegetation Index (NDVI), supported by visual validation by users. We run the system for a selected plant, basil, in varying environmental conditions to cater for typical home conditions, and bootstrap our AI with the acquired data. For end users, we implement a web based user interface which provides both instructions and explanations.

Keywords: explainable artificial intelligence, intelligent agent, IoT, NDVI

Procedia PDF Downloads 166
21143 Genetic Algorithms Multi-Objective Model for Project Scheduling

Authors: Elsheikh Asser

Abstract:

Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multi-objective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: genetic algorithms, time-cost trade-off, multi-objective model, project scheduling

Procedia PDF Downloads 414
21142 Personnel Selection Based on Step-Wise Weight Assessment Ratio Analysis and Multi-Objective Optimization on the Basis of Ratio Analysis Methods

Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

Abstract:

Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: accommodation establishments, human resource management, multi-objective optimization on the basis of ratio analysis, multi-criteria decision making, step-wise weight assessment ratio analysis

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21141 Investigations into Effect of Neural Network Predictive Control of UPFC for Improving Transient Stability Performance of Multimachine Power System

Authors: Sheela Tiwari, R. Naresh, R. Jha

Abstract:

The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

Procedia PDF Downloads 377
21140 A Study of Transferable Strategies in Multilanguage Learning

Authors: Zixi You

Abstract:

With the demand of multilingual speakers increasing in the job market, multi-language learning programs have become more and more popular among undergraduate students. A study on multi-language learning strategies is therefore highly demanded on both practical and theoretical levels. Based on previous classification of learning strategies in SLA, and an investigation of BA Modern Language program students (with post-A level L2 and ab initio L3 learning experience from year one), this study explores and compares different types of learning strategies used by multi-language speakers and learners, transferable learning strategies between L2 and L3, and factors affecting the transfer. The results indicate that all the 23 types of learning strategies of L2 are employed when learning L3 from ab initio level, yet with different tendencies. Learning strategy transfer from L2 to L3 (i.e., the learners attribute the applying of these L3 learning strategies to be a direct result of their L2 learning experience) are observed in all 23 types of learning strategies. Comparatively, six types of “cognitive strategies” have higher transfer tendency than others. With regard to the failure of the transfer of some particular L2 strategies and the development of independent L3 strategies of individual learners, factors such as language proficiency, language typology and learning environment have played important roles among others. The presentation of this study will provide audiences with detailed data, insightful analysis and discussion on both theoretical and practical aspects of multi-language learning that will benefit both students and educators.

Keywords: learning strategy, multi-language acquisition, second language acquisition, strategy transfer

Procedia PDF Downloads 578
21139 A Review on Intelligent Systems for Geoscience

Authors: R Palson Kennedy, P.Kiran Sai

Abstract:

This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

Procedia PDF Downloads 138
21138 Creating a Professional Knowledge Base for Multi-Grade Teaching: Case Studies

Authors: Matshidiso Joyce Taole, Linley Cornish

Abstract:

Teacher’s professional knowledge has become the focus of interest over decades and the interest has intensified in the 21st century. Teachers are expected to develop their professional academic expertise continually, on an ongoing basis. Such professional development may relate to acquiring enhanced expertise in terms of leadership, curriculum development, teaching and learning, assessment of/for learning and feedback for enhanced learning. The paper focuses on professional knowledge base required for teachers in multi-grade contexts. This paper argues that although teacher knowledge is strongly related to individual experiences and contexts, there are elements of teacher knowledge that are particular to multi-grade context. The study employed qualitative design using interviews and observations. The participants were multi-grade teachers and teaching principals. The study revealed that teachers need to develop skills such as learner grouping, differentiating the curriculum, planning, time management and be life-long learners so that they stay relevant and up to date with developments not only in the education sector but globally. This will help teachers to learn increasingly sophisticated methods for engaging the diverse needs of students in their classrooms.

Keywords: curriculum differentiation, multi-grade, planning, teacher knowledge

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21137 Urea Amperometric Biosensor Based on Entrapment Immobilization of Urease onto a Nanostructured Polypyrrol and Multi-Walled Carbon Nanotube

Authors: Hamide Amani, Afshin FarahBakhsh, Iman Farahbakhsh

Abstract:

In this paper, an amprometric biosensor based on surface modified polypyrrole (PPy) has been developed for the quantitative estimation of urea in aqueous solutions. The incorporation of urease (Urs) into a bipolymeric substrate consisting of PPy was performed by entrapment to the polymeric matrix, PPy acts as amperometric transducer in these biosensors. To increase the membrane conductivity, multi-walled carbon nanotubes (MWCNT) were added to the PPy solution. The entrapped MWCNT in PPy film and the bipolymer layers were prepared for construction of Pt/PPy/MWCNT/Urs. Two different configurations of working electrodes were evaluated to investigate the potential use of the modified membranes in biosensors. The evaluation of two different configurations of working electrodes suggested that the second configuration, which was composed of an electrode-mediator-(pyrrole and multi-walled carbon nanotube) structure and enzyme, is the best candidate for biosensor applications.

Keywords: urea biosensor, polypyrrole, multi-walled carbon nanotube, urease

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21136 Multi-Temporal Cloud Detection and Removal in Satellite Imagery for Land Resources Investigation

Authors: Feng Yin

Abstract:

Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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21135 Using the Dokeos Platform for Industrial E-Learning Solution

Authors: Kherafa Abdennasser

Abstract:

The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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21134 Assessment of ATC with Shunt FACTS Devices

Authors: Ashwani Kumar, Jitender Kumar

Abstract:

In this paper, an optimal power flow based approach has been applied for multi-transactions deregulated environment for ATC determination with SVC and STATCOM. The main contribution of the paper is (i) OPF based approach for evaluation of ATC with multi-transactions, (ii) ATC enhancement with FACTS devices viz. SVC and STATCOM for intact and line contingency cases, (iii) impact of ZIP load on ATC determination and comparison of ATC obtained with SVC and STATCOM. The results have been determined for intact and line contingency cases taking simultaneous as well as single transaction cases for IEEE 24 bus RTS.

Keywords: available transfer capability, FACTS devices, line contingency, multi-transactions, ZIP load model

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21133 Finding Optimal Operation Condition in a Biological Nutrient Removal Process with Balancing Effluent Quality, Economic Cost and GHG Emissions

Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

Abstract:

It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.

Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant

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21132 Multivariate Output-Associative RVM for Multi-Dimensional Affect Predictions

Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

Abstract:

The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

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21131 The Three-Zone Composite Productivity Model of Multi-Fractured Horizontal Wells under Different Diffusion Coefficients in a Shale Gas Reservoir

Authors: Weiyao Zhu, Qian Qi, Ming Yue, Dongxu Ma

Abstract:

Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interference of the fractures. In regard to the fractured horizontal wells, the free gas was found to majorly contribute to the productivity, while the contribution of the desorption increased with the increased pressure differences.

Keywords: multi-scale, fracture network, composite model, productivity

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21130 Digital Homeostasis: Tangible Computing as a Multi-Sensory Installation

Authors: Andrea Macruz

Abstract:

This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience

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21129 High Order Block Implicit Multi-Step (Hobim) Methods for the Solution of Stiff Ordinary Differential Equations

Authors: J. P. Chollom, G. M. Kumleng, S. Longwap

Abstract:

The search for higher order A-stable linear multi-step methods has been the interest of many numerical analysts and has been realized through either higher derivatives of the solution or by inserting additional off step points, supper future points and the likes. These methods are suitable for the solution of stiff differential equations which exhibit characteristics that place a severe restriction on the choice of step size. It becomes necessary that only methods with large regions of absolute stability remain suitable for such equations. In this paper, high order block implicit multi-step methods of the hybrid form up to order twelve have been constructed using the multi-step collocation approach by inserting one or more off step points in the multi-step method. The accuracy and stability properties of the new methods are investigated and are shown to yield A-stable methods, a property desirable of methods suitable for the solution of stiff ODE’s. The new High Order Block Implicit Multistep methods used as block integrators are tested on stiff differential systems and the results reveal that the new methods are efficient and compete favourably with the state of the art Matlab ode23 code.

Keywords: block linear multistep methods, high order, implicit, stiff differential equations

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21128 A Multi-Modal Virtual Walkthrough of the Virtual Past and Present Based on Panoramic View, Crowd Simulation and Acoustic Heritage on Mobile Platform

Authors: Lim Chen Kim, Tan Kian Lam, Chan Yi Chee

Abstract:

This research presents a multi-modal simulation in the reconstruction of the past and the construction of present in digital cultural heritage on mobile platform. In bringing the present life, the virtual environment is generated through a presented scheme for rapid and efficient construction of 360° panoramic view. Then, acoustical heritage model and crowd model are presented and improvised into the 360° panoramic view. For the reconstruction of past life, the crowd is simulated and rendered in an old trading port. However, the keystone of this research is in a virtual walkthrough that shows the virtual present life in 2D and virtual past life in 3D, both in an environment of virtual heritage sites in George Town through mobile device. Firstly, the 2D crowd is modelled and simulated using OpenGL ES 1.1 on mobile platform. The 2D crowd is used to portray the present life in 360° panoramic view of a virtual heritage environment based on the extension of Newtonian Laws. Secondly, the 2D crowd is animated and rendered into 3D with improved variety and incorporated into the virtual past life using Unity3D Game Engine. The behaviours of the 3D models are then simulated based on the enhancement of the classical model of Boid algorithm. Finally, a demonstration system is developed and integrated with the models, techniques and algorithms of this research. The virtual walkthrough is demonstrated to a group of respondents and is evaluated through the user-centred evaluation by navigating around the demonstration system. The results of the evaluation based on the questionnaires have shown that the presented virtual walkthrough has been successfully deployed through a multi-modal simulation and such a virtual walkthrough would be particularly useful in a virtual tour and virtual museum applications.

Keywords: Boid Algorithm, Crowd Simulation, Mobile Platform, Newtonian Laws, Virtual Heritage

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21127 A Novel Multi-Attribute Green Decision Making Model for Environmental Supply Chain Sustainability

Authors: Amirhossein Mahlouji

Abstract:

In current business market, the concept of integrating environmental sustainability into long-term as well as routine operations is becoming a prevailing trend. Therefore, several stimuli are helping organization to move toward environmental sustainability. The concept of green supply chain management can help provide a strategic framework to develop a customized sustainability roadmap for each organization. In this regard, this paper is mainly focused on presenting a strategic decision making framework that will assist top level decision-making issues. This decision-making tool is based on literature and practice in the area of environmentally conscious business practices. The goal of this paper will be on the components and parameters of green supply chain management and how they serve as a baseline for the decision framework. Later, the applicability of a multi-input multi-output decision model (MIMO), will be analyzed as the analytical network process, within the green supply chain.

Keywords: Multi-attribute, Green Supply Chain, Environmental, Sustainability

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21126 Developing the Morphological Field of Problem Context to Assist Multi-Methodology in Operations Research

Authors: Mahnaz Hosseinzadeh, Mohammad Reza Mehregan

Abstract:

In this paper, we have developed a morphological field to assist multi- methodology (combining methodologies together in whole or part) in Operations Research (OR) for the problem contexts in Iranian organizations. So, we have attempted to identify some dimensions for problem context according to Iranian organizational problems. Then, a general morphological program is designed which helps the OR practitioner to determine the suitable OR methodology as output for any configuration of conditions in a problem context as input and to reveal the fields necessary to be improved in OR. Applying such a program would have interesting results for OR practitioners.

Keywords: hard, soft and emancipatory operations research, General Morphological Analysis (GMA), multi-methodology, problem context

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21125 Analytical Modeling of Equivalent Magnetic Circuit in Multi-segment and Multi-barrier Synchronous Reluctance Motor

Authors: Huai-Cong Liu,Tae Chul Jeong,Ju Lee

Abstract:

This paper describes characteristic analysis of a synchronous reluctance motor (SynRM)’s rotor with the Multi-segment and Multi-layer structure. The magnetic-saturation phenomenon in SynRM is often appeared. Therefore, when modeling analysis of SynRM the calculation of nonlinear magnetic field needs to be considered. An important influence factor on the convergence process is how to determine the relative permeability. An improved method, which ensures the calculation, is convergence by linear iterative method for saturated magnetic field. If there are inflection points on the magnetic curve,an optimum convergence method of solution for nonlinear magnetic field was provided. Then the equivalent magnetic circuit is calculated, and d,q-axis inductance can be got. At last, this process is applied to design a 7.5Kw SynRM and its validity is verified by comparing with the result of finite element method (FEM) and experimental test data.

Keywords: SynRM, magnetic-saturation, magnetic circuit, analytical modeling

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21124 Natural Honey and Effect on the Activity of the Cells

Authors: Abujnah Dukali

Abstract:

Natural honey was assessed in cell culture system for its anticancer activity. Human leukemic cell line HL 60 was treated with honey and cultured for 5 days and cytotoxicity was calculated by MTT assay. Honey showed cytotoxicity with CC50 value of 174.20 µg/ml. Radical modulation activities was assessed by lipid peroxidation assay using egg lecithin. Honey showed antioxidant activity with EC50 value of 159.73 µg/ml. In addition, treatment with HL60 cells also resulted in nuclear DNA fragmentation, as seen in agarose gel electrophoresis. This is a hallmark of cells undergoing apoptosis. Confirmation of apoptosis was performed by staining the cells with Annexin V and FACS analysis. Apoptosis is an active, genetically regulated disassembly of the cell form within. Disassembly creates changes in the phospholipid content of the cytoplasmic membrane outer leaflet. Phosphatidylserine (PS) is translocated from the inner to the outer surface of the cell for phagocytic cell recognition. The human anticoagulant, annexin V, is a Ca2+-dependent phospholipid protein with a high affinity for PS. Annexin V labeled with fluorescein can identify apoptotic cells in the population It is a confirmatory test for apoptosis. Annexin V-positive cells were defined as apoptotic cells. Since honey shows both antioxidant activity and cytotoxicity at almost the same concentration, it can prevent the free radical induced cancer as prophylactic agent and kill the cancer cells by apoptotic process as a chemotherapeutic agent. Everyday intake of honey can prevent the cancer induction.

Keywords: anticancer, cells, DNA, honey

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21123 Optimum Dispatching Rule in Solar Ingot-Wafer Manufacturing System

Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

Abstract:

In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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21122 Multi-Objective Optimization of Electric Discharge Machining for Inconel 718

Authors: Pushpendra S. Bharti, S. Maheshwari

Abstract:

Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: electric discharge machining, material removal rate, surface roughness, too wear rate, multi-response signal-to-noise ratio, multi response signal-to-noise ratio, optimization

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21121 The Influence of Gossip on the Absorption Probabilities in Moran Process

Authors: Jurica Hižak

Abstract:

Getting to know the agents, i.e., identifying the free riders in a population, can be considered one of the main challenges in establishing cooperation. An ordinary memory-one agent such as Tit-for-tat may learn “who is who” in the population through direct interactions. Past experiences serve them as a landmark to know with whom to cooperate and against whom to retaliate in the next encounter. However, this kind of learning is risky and expensive. A cheaper and less painful way to detect free riders may be achieved by gossiping. For this reason, as part of this research, a special type of Tit-for-tat agent was designed – a “Gossip-Tit-for-tat” agent that can share data with other agents of its kind. The performances of both strategies, ordinary Tit-for-tat and Gossip-Tit-for-tat, against Always-defect have been compared in the finite-game framework of the Iterated Prisoner’s Dilemma via the Moran process. Agents were able to move in a random-walk fashion, and they were programmed to play Prisoner’s Dilemma each time they met. Moreover, at each step, one randomly selected individual was eliminated, and one individual was reproduced in accordance with the Moran process of selection. In this way, the size of the population always remained the same. Agents were selected for reproduction via the roulette wheel rule, i.e., proportionally to the relative fitness of the strategy. The absorption probability was calculated after the population had been absorbed completely by cooperators, which means that all the states have been occupied and all of the transition probabilities have been determined. It was shown that gossip increases absorption probabilities and therefore enhances the evolution of cooperation in the population.

Keywords: cooperation, gossip, indirect reciprocity, Moran process, prisoner’s dilemma, tit-for-tat

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21120 Geographical Information System and Multi-Criteria Based Approach to Locate Suitable Sites for Industries to Minimize Agriculture Land Use Changes in Bangladesh

Authors: Nazia Muhsin, Tofael Ahamed, Ryozo Noguchi, Tomohiro Takigawa

Abstract:

One of the most challenging issues to achieve sustainable development on food security is land use changes. The crisis of lands for agricultural production mainly arises from the unplanned transformation of agricultural lands to infrastructure development i.e. urbanization and industrialization. Land use without sustainability assessment could have impact on the food security and environmental protections. Bangladesh, as the densely populated country with limited arable lands is now facing challenges to meet sustainable food security. Agricultural lands are using for economic growth by establishing industries. The industries are spreading from urban areas to the suburban areas and using the agricultural lands. To minimize the agricultural land losses for unplanned industrialization, compact economic zones should be find out in a scientific approach. Therefore, the purpose of the study was to find out suitable sites for industrial growth by land suitability analysis (LSA) by using Geographical Information System (GIS) and multi-criteria analysis (MCA). The goal of the study was to emphases both agricultural lands and industries for sustainable development in land use. The study also attempted to analysis the agricultural land use changes in a suburban area by statistical data of agricultural lands and primary data of the existing industries of the study place. The criteria were selected as proximity to major roads, and proximity to local roads, distant to rivers, waterbodies, settlements, flood-flow zones, agricultural lands for the LSA. The spatial dataset for the criteria were collected from the respective departments of Bangladesh. In addition, the elevation spatial dataset were used from the SRTM (Shuttle Radar Topography Mission) data source. The criteria were further analyzed with factors and constraints in ArcGIS®. Expert’s opinion were applied for weighting the criteria according to the analytical hierarchy process (AHP), a multi-criteria technique. The decision rule was set by using ‘weighted overlay’ tool to aggregate the factors and constraints with the weights of the criteria. The LSA found only 5% of land was most suitable for industrial sites and few compact lands for industrial zones. The developed LSA are expected to help policy makers of land use and urban developers to ensure the sustainability of land uses and agricultural production.

Keywords: AHP (analytical hierarchy process), GIS (geographic information system), LSA (land suitability analysis), MCA (multi-criteria analysis)

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21119 A Gyro-stabilized Autonomous Multi-terrain Quadrupedal-wheeled Robot: Towards Edge-enabled Self-balancing, Autonomy, and Terramechanical Efficiency of Unmanned Off-road Vehicles

Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

Abstract:

For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

Procedia PDF Downloads 158
21118 Evaluation of the Radiolabelled 68GA-DOTATOC Complex in Adenocarcinoma Breast Cancer

Authors: S. Zolghadri, M. Naderi, H. Yousefnia, B. Alirzapour, A. R. Jalilian, A. Ramazani

Abstract:

Nowadays, 68Ga-DOTATOC has been known as a potential agent for the detection of neuroendocrine tumours and it has indicated higher sensitivity compared with the 111In-Octeroetide. The aim of this study was to evaluate the effectiveness of this new agent in the diagnosis of adenocarcinoma breast cancer. 68Ga-DOTATOC was prepared with the radiochemical purity of higher than 98% and by the specific activity of 39.6 TBq/mmol. 37 MBq of the complex was injected intravenously into the BULB/c mice with adenocarcinoma breast cancer. PET/CT images were acquired after 30, 60 and 90 min post injection demonstrated significant accumulation in the tumour sites. Also, considerable activity was observed in the kidney and bladder as the main routs of excretion. Generally, the results showed that 68Ga-DOTATOC can be considered as a suitable complex for diagnosis of the adenocarcinoma breast cancer using PET procedure.

Keywords: adenocarcinoma breast cancer, 68Ga, octreotide, imaging

Procedia PDF Downloads 342
21117 Multi-Focus Image Fusion Using SFM and Wavelet Packet

Authors: Somkait Udomhunsakul

Abstract:

In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: multi-focus image fusion, wavelet packet, spatial frequency measurement

Procedia PDF Downloads 476
21116 Off-Policy Q-learning Technique for Intrusion Response in Network Security

Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

Abstract:

With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

Procedia PDF Downloads 243