Search results for: optimization tool

Authors: Kwok Tak Kit

Abstract:

With the increase of demand and popularity of ecotourism development to address the concern of carbon emission, the acceleration of development of the concept of net zero carbon ecotourism can increase international competitiveness, sustainability and productivity. This paper aims to outline the major key components and considerations in ecotourism development with integration of net zero strategy and provide recommendation and reference to government agents, Architecture, Engineering and Construction (AEC) industry and stakeholders to contribute to the target of net zero and environmentally friendly ecotourism development project. This paper explores the alternative to the reliance on local regulation and ecotourism certification programs as a base tool to achieve the higher standard of the reduction of the use of energy and natural resources in ecotourism development and to enhance their sustainability.

Keywords: Net zero ecotourism, sustainability, embodied carbon, Paris Agreement.

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Authors: Maha Sharkas, Dahlia R. ElShafie, Nadder Hamdy

Abstract:

Image watermarking has proven to be quite an efficient tool for the purpose of copyright protection and authentication over the last few years. In this paper, a novel image watermarking technique in the wavelet domain is suggested and tested. To achieve more security and robustness, the proposed techniques relies on using two nested watermarks that are embedded into the image to be watermarked. A primary watermark in form of a PN sequence is first embedded into an image (the secondary watermark) before being embedded into the host image. The technique is implemented using Daubechies mother wavelets where an arbitrary embedding factor α is introduced to improve the invisibility and robustness. The proposed technique has been applied on several gray scale images where a PSNR of about 60 dB was achieved.

Keywords: Image watermarking, Multimedia Security, Wavelets, Image Processing.

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Authors: Nor Azuana Ramli, Mohd Tahir Ismail, Hooy Chee Wooi

Abstract:

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we take the Euclidean distance and the Manhattan as a consideration. For the comparison, we employ three other methods which are logistic regression analysis (logit), back-propagation neural network (NN) and sequential minimal optimization (SMO). The analysis using datasets from 8 countries and 13 macro-economic indicators for each country shows that the proposed k-NN method with k = 4 and Manhattan distance performs better than the other methods.

Keywords: Currency crisis, k-nearest neighbour method, logit, neural network.

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Authors: K. Aloui, M. S. Naceur

Abstract:

The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images and set up compression-transmit schemes to distribute result to the remote doctor. To achieve this goal, we use basically a level-sets approach to delineating brain tumors in threedimensional. Then introduce a new compression and transmission plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by wireless network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.

Keywords: Medical imaging, level-sets, compression, meshessimplification, telemedicine, wireless transmission.

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Authors: I. A. Farhat

Abstract:

The The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: Artificial Immune System (AIS), Dynamic Economic Dispatch (DED).

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Authors: Michal Martinovič, Jaroslav Polec, Kvetoslava Kotuliaková

Abstract:

In this paper we proposed multistage adaptive ARQ/HARQ/HARQ scheme. This method combines pure ARQ (Automatic Repeat reQuest) mode in low channel bit error rate and hybrid ARQ method using two different Reed-Solomon codes in middle and high error rate conditions. It follows, that our scheme has three stages. The main goal is to increase number of states in adaptive HARQ methods and be able to achieve maximum throughput for every channel bit error rate. We will prove the proposal by calculation and then with simulations in land mobile satellite channel environment. Optimization of scheme system parameters is described in order to maximize the throughput in the whole defined Signal-to- Noise Ratio (SNR) range in selected channel environment.

Keywords: Signal-to-noise ratio, throughput, forward error correction (FEC), pure and hybrid automatic repeat request (ARQ).

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Authors: Felix Dobslaw

Abstract:

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Keywords: Parameter-Tuning, Metaheuristics, Design of Experiments, Artificial Neural Networks.

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Authors: V. K. Banga, R. Kumar, Y. Singh

Abstract:

In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuzzy logic and Genetic Algorithms. The development of a fuzzy genetic optimization algorithm is presented and discussed. The result are compared only GA and Fuzzy GA. This paper describes genetic algorithms, which is designed to optimize robot movement and trajectory. Though the model represents is a general model for redundant structures and could represent any n-link structures. The result is a complete trajectory planning with Fuzzy logic and Genetic algorithms demonstrating the flexibility of this technique of artificial intelligence.

Keywords: Inverse kinematics, Genetic algorithms (GAs), Fuzzy logic (FL), Trajectory planning.

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Authors: Badr M. Alshammari, T. Guesmi

Abstract:

This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: Economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones.

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Authors: H.S. Kim

Abstract:

In this study, control performance of a smart base isolation system consisting of a friction pendulum system (FPS) and a magnetorheological (MR) damper has been investigated. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

Keywords: Fuzzy logic controller, genetic algorithm, MR damper, smart base isolation system

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Authors: Amit Kumar, Pushpinder Singh, Parampreet Kaur, Amarpreet Kaur

Abstract:

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Systems with Applications 36 (2009) 6833-6842) is incorrect. The main aim of this paper is to propose a new approach for the ranking of generalized trapezoidal fuzzy numbers. The main advantage of the proposed approach is that the proposed approach provide the correct ordering of generalized and normal trapezoidal fuzzy numbers and also the proposed approach is very simple and easy to apply in the real life problems. It is shown that proposed ranking function satisfies all the reasonable properties of fuzzy quantities proposed by Wang and Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).

Keywords: Ranking function, Generalized trapezoidal fuzzy numbers

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Authors: Yu Li, Jingwu He, Yuexi Xiong

Abstract:

The spar layout will affect the wing’s stiffness characteristics, and irrational spar arrangement will reduce the overall bending and twisting resistance capacity of the wing. In this paper, the active structural stiffness design theory is used to match the stiffness-center axis position and load-cases under the corresponding multiple flight conditions, in order to achieve better stiffness properties of the wing. The combination of active stiffness method and principle of stiffness distribution is proved to be reasonable supplying an initial reference for wing designing. The optimized layout of spars is eventually obtained, and the high-aspect-ratio wing will have better stiffness characteristics.

Keywords: Active structural stiffness design theory, high-aspect-ratio wing, flight load cases, layout of spars.

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Authors: Wen-Lung Huang, Shih-Pin Chen

Abstract:

This paper investigates the optimization problem of multi-product aggregate production planning (APP) with fuzzy data. From a comprehensive viewpoint of conserving the fuzziness of input information, this paper proposes a method that can completely describe the membership function of the performance measure. The idea is based on the well-known Zadeh-s extension principle which plays an important role in fuzzy theory. In the proposed solution procedure, a pair of mathematical programs parameterized by possibility level a is formulated to calculate the bounds of the optimal performance measure at a . Then the membership function of the optimal performance measure is constructed by enumerating different values of a . Solutions obtained from the proposed method contain more information, and can offer more chance to achieve the feasible disaggregate plan. This is helpful to the decision-maker in practical applications.

Keywords: fuzzy data, aggregate production planning, membership function, parametric programming

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Authors: Xie Kefeng, Zhang He

Abstract:

For the stability and control demand of offshore small floating platform, a 2-HUS/U parallel mechanism was presented as offshore platform. Inverse kinematics was obtained by institutional constraint equation, and the dynamic model of offshore 2-HUS/U parallel platform was derived based on rigid body’s Lagrangian method. The equivalent moment of inertia, damping and driving force/torque variation of offshore 2-HUS/U parallel platform were analyzed. A numerical example shows that, for parallel platform of given motion, system’s equivalent inertia changes 1.25 times maximally. During the movement of platform, they change dramatically with the system configuration and have coupling characteristics. The maximum equivalent drive torque is 800 N. At the same time, the curve of platform’s driving force/torque is smooth and has good sine features. The control system needs to be adjusted according to kinetic equation during stability and control and it provides a basis for the optimization of control system.

Keywords: 2-HUS/U platform, Dynamics, Lagrange, Parallel platform.

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Authors: Mohammad Reza Ghanbari, Parham Azimi, Farrokh Abdollahi

Abstract:

Since the last two decades, container transportation system has been faced under increasing development. This fact shows the importance of container transportation system as a key role of container terminals to link between sea and land. Therefore, there is a continuous need for the optimal use of equipment and facilities in the ports. Regarding the complex structure of container ports, this paper presents a simulation model that compares tow storage strategies for storing containers in the yard. For this purpose, we considered loading and unloading norm as an important criterion to evaluate the performance of Shahid Rajaee container port. By analysing the results of the model, it will be shown that using marshalling yard policy instead of current storage system has a significant effect on the performance level of the port and can increase the loading and unloading norm up to 14%.

Keywords: Simulation Modeling, Container Port, Marshaling Yard, Storage Policy

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Authors: V. K. Bansal

Abstract:

Geographic Information System (GIS) is a computerbased tool used extensively to solve various engineering problems related to spatial data. In spite of growing popularity of GIS, its complete potential to construction industry has not been realized. In this paper, the summary of up-to-date work on spatial applications of GIS technologies in construction industry is presented. GIS technologies have the potential to solve space related problems of construction industry involving complex visualization, integration of information, route planning, E-commerce, cost estimation, etc. GISbased methodology to handle time and space issues of construction projects scheduling is developed and discussed in this paper.

Keywords: Construction, GIS in construction, Scheduling, Project Management.

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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Authors: Giovanni Incerti

Abstract:

The motion planning technique described in this paper has been developed to eliminate or reduce the residual vibrations of belt-driven rotary platforms, while maintaining unchanged the motion time and the total angular displacement of the platform. The proposed approach is based on a suitable choice of the motion command given to the servomotor that drives the mechanical device; this command is defined by some numerical coefficients which determine the shape of the displacement, velocity and acceleration profiles. Using a numerical optimization technique, these coefficients can be changed without altering the continuity conditions imposed on the displacement and its time derivatives at the initial and final time instants. The proposed technique can be easily and quickly implemented on an actual device, since it requires only a simple modification of the motion command profile mapped in the memory of the electronic motion controller.

Keywords: Command shaping, residual vibrations, belt transmission, servomechanism.

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Authors: O. Benaziz, A. Dorbane, S. Djeraba

Abstract:

The objective of this work is to formulate a dry dispersible form of furosemide in the context of pediatric dose adjustment. To achieve this, we have produced a set of formulas that will be tested in process and after compression. The formula with the best results will be improved to optimize the final shape of the product. Furosemide is the most widely used pediatric diuretic because of its low toxicity. The manufacturing process was chosen taking into account all the data relating to the active ingredient and the excipients used and complying with the specifications and requirements of dispersible tablets. The process used to prepare these tablets was wet granulation. Different excipients were used: lactose, maize starch, magnesium stearate and two superdisintegrants. The mode of incorporation of super-disintegrant changes with each formula. The use of super-disintegrant in the formula allowed optimization of the disintegration time. Prepared tablets were evaluated for weight, content uniformity, hardness, disintegration time, friability and in vitro dissolution test. 

Keywords: Formulation, dispersible tablets, wet granulation, superdisintegrants, disintegration.

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Authors: M. Bouguerra, H. Meglouli, I. Habi

Abstract:

The great majority of the electric installations belong to the first and second category. In order to ensure a high level of reliability of their electric system feeder, two power supply sources are envisaged, one principal, the other of reserve, generally a cold reserve (electric diesel group). The principal source being under operation, its control can be ideal and sure, however for the reserve source being in stop, a preventive maintenance-s which proceeds on time intervals (periodicity) and for well defined lengths of time are envisaged, so that this source will always available in case of the principal source failure. The choice of the periodicity of preventive maintenance of the source of reserve influences directly the reliability of the electric feeder system. On the basis of the semi-markovians processes, the influence of the periodicity of the preventive maintenance of the source of reserve is studied and is given the optimal periodicity.

Keywords: Semi Markovians processes, reliability, optimization, electric network.

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Authors: Tarek Aboueldahab

Abstract:

In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.

Keywords: Global Search, Hybrid Model, Passive Congregation, Stock Market Prediction.

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Authors: Mohammad Ali Zazouli, Farzaneh Veisi, Amir Veisi

Abstract:

Bisphenol A (BPA) is an organic synthetic compound that has many applications in various industries and is known as persistent pollutant. The aim of this research was to evaluate the efficiency of bone ash and banana peel as adsorbents for BPA adsorption from aqueous solution by using Response Surface Methodology. The effects of some variables such as sorbent dose, detention time, solution pH, and BPA concentration on the sorption efficiency was examined. All analyses were carried out according to Standard Methods. The sample size was performed using Box-Benken design and also optimization of BPA removal was done using response surface methodology (RSM). The results showed that the BPA adsorption increases with increasing of contact time and BPA concentration. However, it decreases with higher pH. More adsorption efficiency of a banana peel is very smaller than a bone ash so that BPA removal for bone ash and banana peel is 62 and 28 percent, respectively. It is concluded that a bone ash has a good ability for the BPA adsorption.

Keywords: Adsorbent, banana peel, bisphenol A (BPA), bone ash, wastewater treatment.

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Authors: Shabbar Naqvi, Jonathan M. Garibaldi

Abstract:

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Transform Infrared Spectroscopy (FTIR) of cancer patients has been used for this study. The future work outlines the potential areas of fuzzy systems that can be used for the automation of breast cancer grading.

Keywords: Breast cancer, FTIR, fuzzy inference system, principal component analysis

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Authors: I. A. Farhat

Abstract:

The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand.  Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: Artificial Immune System (AIS), Dynamic Economic Dispatch (DED).

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Authors: Kenny Raharjo, Ramon Lawrence

Abstract:

Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: Game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics.

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Authors: Ibrahim M. Buamod, Muattaz Elaneizi

Abstract:

Mobile Ad hoc Network (MANET) is a wireless ad hoc self-configuring network of mobile routers (and associated hosts) connected by wireless links, the union of which forms an arbitrary topology, cause of the random mobility of the nodes. In this paper, an attempt has been made to compare these three protocols DSDV, AODV and DSR on the performance basis under different traffic protocols namely CBR and TCP in a large network. The simulation tool is NS2, the scenarios are made to see the effect of pause times. The results presented in this paper clearly indicate that the different protocols behave differently under different pause times. Also, the results show the main characteristics of different traffic protocols operating on MANETs and thus select the best protocol on each scenario.

Keywords: Awk, CBR, Random waypoint model, TCP.

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Authors: Nhon Do, Tuyen Trong Tran, Phan Hoai Truong

Abstract:

Nowadays e-Learning is more popular, in Vietnam especially. In e-learning, materials for studying are very important. It is necessary to design the knowledge base systems and expert systems which support for searching, querying, solving of problems. The ontology, which was called Computational Object Knowledge Base Ontology (COB-ONT), is a useful tool for designing knowledge base systems in practice. In this paper, a design method for knowledge base systems in education using COKB-ONT will be presented. We also present the design of a knowledge base system that supports studying knowledge and solving problems in higher mathematics.

Keywords: artificial intelligence, knowledge base systems, ontology, educational software.

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Authors: N. F. Jamaluddin, N. A. H. Aizam

Abstract:

This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed.

Keywords: Demands, educational timetabling, integer linear programming, scheduling, university examination timetabling problem.

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Authors: Ankit Mitra

Abstract:

An adder is one of the most integral component of a digital system like a digital signal processor or a microprocessor. Being an extremely computationally intensive part of a system, the optimization for speed and power consumption of the adder is of prime importance. In this paper we have designed a 1 bit full adder cell based on dynamic TSPC logic to achieve high speed operation. A high threshold voltage sleep transistor is used to reduce the static power dissipation in standby mode. The circuit is designed and simulated in TSPICE using TSMC 180nm CMOS process. Average power consumption, delay and power-delay product is measured which showed considerable improvement in performance over the existing full adder designs.

Keywords: CMOS, TSPC, MTCMOS, ALU, Clock gating, power gating, pipelining.

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Authors: B. Selma, S. Chouraqui

Abstract:

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.

Keywords: Adaptive neuro-fuzzy inference system (ANFIS), Fuzzy logic, neural network, nonlinear system, control

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