Search results for: constant modulus algorithm

Authors: M. S. Nourbakhsh, M. E. Khosroshahi

Abstract:

Laser soldering is based on applying some soldering material (albumin) onto the approximated edges of the cut and heating the solder (and the underlying tissues) by a laser beam. Endogenous and exogenous materials such as indocyanine green (ICG) are often added to solders to enhance light absorption. Gold nanoshells are new materials which have an optical response dictated by the plasmon resonance. The wavelength at which the resonance occurs depends on the core and shell sizes, allowing nanoshells to be tailored for particular applications. The purposes of this study was use combination of ICG and different concentration of gold nanoshells for skin tissue soldering and also to examine the effect of laser soldering parameters on the properties of repaired skin. Two mixtures of albumin solder and different combinations of ICG and gold nanoshells were prepared. A full thickness incision of 2×20 mm2 was made on the surface and after addition of mixtures it was irradiated by an 810nm diode laser at different power densities. The changes of tensile strength σt due to temperature rise, number of scan (Ns), and scan velocity (Vs) were investigated. The results showed at constant laser power density (I), σt of repaired incisions increases by increasing the concentration of gold nanoshells in solder, Ns and decreasing Vs. It is therefore important to consider the tradeoff between the scan velocity and the surface temperature for achieving an optimum operating condition. In our case this corresponds to σt =1800 gr/cm2 at I~ 47 Wcm-2, T ~ 85ºC, Ns =10 and Vs=0.3mms-1.

Keywords: Tissue soldering, gold nanoshells, indocyanine green, combination, tensile strength.

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Authors: K.Alkhulaifi, M. Hamdalla

Abstract:

Most of ignition delay correlations studies have been developed in a constant volume bombs which cannot capture the dynamic variation in pressure and temperature during the ignition delay as in real engines. Watson, Assanis et. al. and Hardenberg and Hase correlations have been developed based on experimental data of diesel engines. However, they showed limited predictive ability of ignition delay when compared to experimental results. The objective of the study was to investigate the dependency of ignition delay time on engine brake power. An experimental investigation of the effect of automotive diesel and water diesel emulsion fuels on ignition delay under steady state conditions of a direct injection diesel engine was conducted. A four cylinder, direct injection naturally aspirated diesel engine was used in this experiment over a wide range of engine speeds and two engine loads. The ignition delay experimental data were compared with predictions of Assanis et. al. and Watson ignition delay correlations. The results of the experimental investigation were then used to develop a new ignition delay correlation. The newly developed ignition delay correlation has shown a better agreement with the experimental data than Assanis et. al. and Watson when using automotive diesel and water diesel emulsion fuels especially at low to medium engine speeds at both loads. In addition, the second derivative of cylinder pressure which is the most widely used method in determining the start of combustion was investigated.

Keywords: gnition delay correlation, water diesel emulsion, direct injection diesel engine

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Authors: Salvatore L., Pires B., Campos M. C. M., De Souza Jr M. B.

Abstract:

It is estimated that the total cost of abnormal conditions to US process industries is around $20 billion dollars in annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum refineries is a conversion process that leads to high profitable economical returns. However, this is a difficult process to control because it is operated continuously, with high hydrogen pressures and it is also subject to disturbances in feed properties and catalyst performance. So, the automatic detection of fault and diagnosis plays an important role in this context. In this work, a hybrid approach based on neural networks together with a pos-processing classification algorithm is used to detect faults in a simulated HDT unit. Nine classes (8 faults and the normal operation) were correctly classified using the proposed approach in a maximum time of 5 minutes, based on on-line data process measurements.

Keywords: Fault detection, hydrotreatment, hybrid systems, neural networks.

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

Abstract:

In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: M. Ghazikhani, M. R. Kalateh, Y. K. Toroghi, M. Dehnavi

Abstract:

In this study, effects of EGR on CO and HC emissions of a dual fuel HCCI-DI engine are investigated. Tests were conducted on a single-cylinder variable compression ratio (VCR) diesel engine with compression ratio of 17.5. Premixed gasoline is provided by a carburetor connected to intake manifold and equipped with a screw to adjust premixed air-fuel ratio, and diesel fuel is injected directly into the cylinder through an injector at pressure of 250 bars. A heater placed at inlet manifold is used to control the intake charge temperature. Optimal intake charge temperature was 110-115ºC due to better formation of a homogeneous mixture causing HCCI combustion. Timing of diesel fuel injection has a great effect on stratification of in-cylinder charge in HCCI combustion. Experiments indicated 35 BTDC as the optimum injection timing. Coolant temperature was maintained 50ºC during the tests. Results show that increasing engine speed at a constant EGR rate leads to increase in CO and UHC emissions due to the incomplete combustion caused by shorter combustion duration and less homogeneous mixture. Results also show that increasing EGR reduces the amount of oxygen and leads to incomplete combustion and therefore increases CO emission due to lower combustion temperature. HC emission also increases as a result of lower combustion temperatures.

Keywords: Dual fuel HCCI engine, EGR, engine speed, CO andUHC emissions.

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Authors: Chidentree Treesatayapun

Abstract:

A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.

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Authors: Francisco J. Lopez-Jaquez, Sandra E. Ramirez-Jara

Abstract:

This paper presents an implementation and performance test of a distributed motion control system based on a master-slave configuration used to move a plasma-cutting torch over a predefined trajectory. The master is a general-purpose computer running on an open source operating system platform and software developer. Software running in the master computer generates commands on real time and we measure performance based on a selected set of differences between expected and observed distances. We are testing the null hypothesis that the outcome trajectory is identical to the input against the alternative hypothesis that there is a shift to the right or left of the input one. We used the Wilcoxon signed ranks test method for the hypothesis test.

Keywords: Distributed, motion, control, real-time, contouring.

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Authors: Mahdi Zolfaghari, Seyed Hossein Hosseinian, Hossein Askarian Abyaneh, Mehrdad Abedi

Abstract:

This paper presents a virtual active power filter (VAPF) using vehicle to grid (V2G) technology to maintain power quality requirements. The optimal discrete operation of the power converter of electric vehicle (EV) is based on recognizing desired switching states using the model predictive control (MPC) algorithm. A fast dynamic response, lower total harmonic distortion (THD) and good reference tracking performance are realized through the presented control strategy. The simulation results using MATLAB/Simulink validate the effectiveness of the scheme in improving power quality as well as good dynamic response in power transferring capability.

Keywords: Virtual active power filter, V2G technology, model predictive control, electric vehicle, power quality.

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Authors: Jae Keun Park, Sung Je Hong, Kyong Hoon Kim, Tae Heum Kang, Wan Yeon Lee

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In this paper, we propose a routing scheme that guarantees the residual lifetime of wireless sensor networks where each sensor node operates with a limited budget of battery energy. The scheme maximizes the communications QoS while sustaining the residual battery lifetime of the network for a specified duration. Communication paths of wireless nodes are translated into a directed acyclic graph(DAG) and the maximum-flow algorithm is applied to the graph. The found maximum flow are assigned to sender nodes, so as to maximize their communication QoS. Based on assigned flows, the scheme determines the routing path and the transmission rate of data packet so that any sensor node on the path would not exhaust its battery energy before a specified duration.

Keywords: Sensor network, battery, residual lifetime, routingscheme, QoS

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Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan

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This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.

Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.

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Authors: Mahmoud S. Ahmed, Hany A. Mohamed, Mohamed A. Omara, Mohamed F. Abdeen

Abstract:

Experimental study of natural convection heat transfer inside smooth and rough surfaces of vertical and inclined equilateral triangular channels of different inclination angles with a uniformly heated surface are performed. The inclination angle is changed from 15º to 90º. Smooth and rough surface of average roughness (0.02mm) are used and their effect on the heat transfer characteristics are studied. The local and average heat transfer coefficients and Nusselt number are obtained for smooth and rough channels at different heat flux values, different inclination angles and different Rayleigh numbers (Ra) 6.48 × 105 ≤ Ra ≤ 4.78 × 106. The results show that the local Nusselt number decreases with increase of axial distance from the lower end of the triangular channel to a point near the upper end of channel, and then, it slightly increases. Higher values of local Nusselt number for rough channel along the axial distance compared with the smooth channel. The average Nusselt number of rough channel is higher than that of smooth channel by about 8.1% for inclined case at θ = 45o and 10% for vertical case. The results obtained are correlated using dimensionless groups for both rough and smooth surfaces of the inclined and vertical triangular channels.

Keywords: Natural heat transfer convection, constant heat flux, open channels, heat transfer.

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Authors: Uttam Vijay, Nitin Gupta

Abstract:

Due to heavy energy constraints in WSNs clustering is an efficient way to manage the energy in sensors. There are many methods already proposed in the area of clustering and research is still going on to make clustering more energy efficient. In our paper we are proposing a minimum spanning tree based clustering using divide and conquer approach. The MST based clustering was first proposed in 1970’s for large databases. Here we are taking divide and conquer approach and implementing it for wireless sensor networks with the constraints attached to the sensor networks. This Divide and conquer approach is implemented in a way that we don’t have to construct the whole MST before clustering but we just find the edge which will be the part of the MST to a corresponding graph and divide the graph in clusters there itself if that edge from the graph can be removed judging on certain constraints and hence saving lot of computation.

Keywords: Algorithm, Clustering, Edge-Weighted Graph, Weighted-LEACH.

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Authors: Liu Gang, Gu Nai-jie, Bi Kun, Tu Kun, Dong Wan-li

Abstract:

All-to-all personalized communication, also known as complete exchange, is one of the most dense communication patterns in parallel computing. In this paper, we propose new indirect algorithms for complete exchange on all-port ring and torus. The new algorithms fully utilize all communication links and transmit messages along shortest paths to completely achieve the theoretical lower bounds on message transmission, which have not be achieved among other existing indirect algorithms. For 2D r × c ( r % c ) all-port torus, the algorithm has time complexities of optimal transmission cost and O(c) message startup cost. In addition, the proposed algorithms accommodate non-power-of-two tori where the number of nodes in each dimension needs not be power-of-two or square. Finally, the algorithms are conceptually simple and symmetrical for every message and every node so that they can be easily implemented and achieve the optimum in practice.

Keywords: Complete exchange, collective communication, all-to-all personalized communication, parallel computing, wormhole routing, torus.

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore , the number of centers will be considered since it affects the performance of approximation.

Keywords: Extended kalmin filter (EKF), classification problem, radial basis function networks (RBFN), finite impulse response (FIR)filter.

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Authors: Alireza Vakili, Mohsen Danesh Mesgaran, Majid Abdollazade

Abstract:

In this study four Holstein steers with rumen fistula fed 7 kg of dry matter (DM) of diets differing in concentrate to alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin square design. The pH of the ruminal fluid was measured before the morning feeding (0.0 h) to 8 h post feeding. In this study, a two-layered feed-forward neural network trained by the Levenberg-Marquardt algorithm was used for modelling of ruminal pH. The input variables of the network were time, concentrate to alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral detergent fiber (NDF). The output variable was the ruminal pH. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 >0.96). Therefore, we suggest using these model-derived biological values to summarize continuously recorded pH data.

Keywords: Ruminal pH, Artificial Neural Network (ANN), Non Fiber Carbohydrate, Neutral Detergent Fiber.

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Authors: Maythapolnun Athimethphat, Boontarika Lerteerawong

Abstract:

There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.

Keywords: multiclass classification, hierarchical classification, binary classification tree, clustering, observation-based clustering

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Authors: Alima Damak Masmoudi, Randa Boukhris Trabelsi, Dorra Sellami Masmoudi

Abstract:

Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).

Keywords: fingerprint, fingervein, LBP, MonoLBP, fusion, biometric trait.

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Authors: Amon Lasomboon

Abstract:

Since the world printing industry has to confront globalization with a constant change, the Thai printing industry, as a small but increasingly significant part of the world printing industry, cannot inevitably escape but has to encounter with the similar change and also the need to revamp its production processes, designs and technology to make them more appealing to both international and domestic market. The essential question is what is the Thai competitive edge in the printing industry in changing environment? This research is aimed to study the Thai level of competitive edge in terms of marketing, technology, environment friendly, and the level of satisfaction of the process of using printing machines. To access the extent to which is the trends in competitiveness of Thai printing industry, both quantitative and qualitative study were conducted. The quantitative analysis was restricted to 100 respondents. The qualitative analysis was restricted to a focus group of 10 individuals from various backgrounds in the Thai printing industry. The findings from the quantitative analysis revealed that the overall mean scores are 4.53, 4.10, and 3.50 for the competitiveness of marketing, the competitiveness of technology, and the competitiveness of being environment friendly respectively. However, the level of satisfaction for the process of using machines has a mean score only 3.20. The findings from the qualitative analysis have revealed that target customers have increasingly reordered due to their contentment in both low prices and the acceptable quality of the products. Moreover, the Thai printing industry has a tendency to convert to ambient green technology which is friendly to the environment. The Thai printing industry is choosing to produce or substitute with products that are less damaging to the environment. It is also found that the Thai printing industry has been transformed into a very competitive industry which bargaining power rests on consumers who have a variety of choices.

Keywords: Competitiveness, Printing Industry

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Authors: Ameni Mokni , Hatem Mhiri , Georges Le Palec , Philippe Bournot

Abstract:

In mechanical and environmental engineering, mixed convection is a frequently encountered thermal fluid phenomenon which exists in atmospheric environment, urban canopy flows, ocean currents, gas turbines, heat exchangers, and computer chip cooling systems etc... . This paper deals with a numerical investigation of mixed convection in a vertical heated channel. This flow results from the mixing of the up-going fluid along walls of the channel with the one issued from a flat nozzle located in its entry section. The fluiddynamic and heat-transfer characteristics of vented vertical channels are investigated for constant heat-flux boundary conditions, a Rayleigh number equal to 2.57 1010, for two jet Reynolds number Re=3 103 and 2104 and the aspect ratio in the 8-20 range. The system of governing equations is solved with a finite volumes method and an implicit scheme. The obtained results show that the turbulence and the jet-wall interaction activate the heat transfer, as does the drive of ambient air by the jet. For low Reynolds number Re=3 103, the increase of the aspect Ratio enhances the heat transfer of about 3%, however; for Re=2 104, the heat transfer enhancement is of about 12%. The numerical velocity, pressure and temperature fields are post-processed to compute the quantities of engineering interest such as the induced mass flow rate, and average Nusselt number, in terms of Rayleigh, Reynolds numbers and dimensionless geometric parameters are presented.

Keywords: Aspect Ratio, Channel, Jet, Mixed convection

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Authors: P. Sawatnatee, S. Udomsuk, K-N. Areerak, K-L. Areerak, A. Srikaew

Abstract:

The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

 

Keywords: Indirect Vector Control, Induction Motor, Adaptive Tabu Search, Control Design, Artificial Intelligence.

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Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen

Abstract:

The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model

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Authors: H. Shayeghi, A. Safari, H. A. Shayanfar

Abstract:

In this paper, multiobjective design of multi-machine Power System Stabilizers (PSSs) using Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning problem is converted to an optimization problem which is solved by PSO with the eigenvalue-based multiobjective function. The proposed PSO based PSSs is tested on a multimachine power system under different operating conditions and disturbances through eigenvalue analysis and some performance indices to illustrate its robust performance.

Keywords: PSS Design, Particle Swarm Optimization, Dynamic Stability, Multiobjective Optimization.

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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: Cheng-Lung Huang, Han-Yu Chien, Michael Conyette

Abstract:

Social bookmarking is an environment in which the user gradually changes interests over time so that the tag data associated with the current temporal period is usually more important than tag data temporally far from the current period. This implies that in the social tagging system, the newly tagged items by the user are more relevant than older items. This study proposes a novel recommender system that considers the users- recent tag preferences. The proposed system includes the following stages: grouping similar users into clusters using an E-M clustering algorithm, finding similar resources based on the user-s bookmarks, and recommending the top-N items to the target user. The study examines the system-s information retrieval performance using a dataset from del.icio.us, which is a famous social bookmarking web site. Experimental results show that the proposed system is better and more effective than traditional approaches.

Keywords: Recommender systems, Social bookmarking, Tag

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Authors: L. Rodriguez-Benitez, J. Moreno-Garcia, J.J. Castro-Schez, C. Solana, L. Jimenez

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In this paper the use of sequential machines for recognizing actions taken by the objects detected by a general tracking algorithm is proposed. The system may deal with the uncertainty inherent in medium-level vision data. For this purpose, fuzzification of input data is performed. Besides, this transformation allows to manage data independently of the tracking application selected and enables adding characteristics of the analyzed scenario. The representation of actions by means of an automaton and the generation of the input symbols for finite automaton depending on the object and action compared are described. The output of the comparison process between an object and an action is a numerical value that represents the membership of the object to the action. This value is computed depending on how similar the object and the action are. The work concludes with the application of the proposed technique to identify the behavior of vehicles in road traffic scenes.

Keywords: Approximate reasoning, finite state machines, video analysis.

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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: M. R. Vaezi, R. Ghasemi, A. Akramizadeh

Abstract:

Frequency stability of microgrids under islanded operation attracts particular attention recently. A new cooperative frequency control strategy based on centralized multi-agent system (CMAS) is proposed in this study. Based on this strategy, agents sent data and furthermore each component has its own to center operating decisions (MGCC).After deciding on the information, they are returned. Frequency control strategies include primary and secondary frequency control and disposal of multi-stage load in which this study will also provide a method and algorithm for load shedding. This could also be a big problem for the performance of micro-grid in times of disaster. The simulation results show the promising performance of the proposed structure of the controller based on multi agent systems.

Keywords: Frequency Control, Islanded Micro-grid, Load shedding, Multi-agent System.

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Authors: G. M. Mir, N. A. Shah, Moinuddin

Abstract:

Efficient handoff algorithms are a cost-effective way of enhancing the capacity and QoS of cellular system. The higher value of hysteresis effectively prevents unnecessary handoffs but causes undesired cell dragging. This undesired cell dragging causes interference or could lead to dropped calls in microcellular environment. The problems are further exacerbated by the corner effect phenomenon which causes the signal level to drop by 20-30 dB in 10-20 meters. Thus, in order to maintain reliable communication in a microcellular system new and better handoff algorithms must be developed. A fuzzy based handoff algorithm is proposed in this paper as a solution to this problem. Handoff on the basis of ratio of slopes of normal signal loss to the actual signal loss is presented. The fuzzy based solution is supported by comparing its results with the results obtained in analytical solution.

Keywords: Slope ratio, handoff, corner effect, fuzzy logic.

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Authors: Janet B. Badong-Badilla

Abstract:

In Jesuit universities, laypersons, who come from the same or different faith backgrounds or traditions, are considered as collaborators in mission. The Jesuits themselves support the contributions of the lay partners in realizing the mission of the Society of Jesus and recognize the important role that they play in education. This study aims to investigate and generate particular notions and understandings of lived experiences of being a lay partner in Jesuit universities in the Philippines, particularly those involved in higher education. Using the qualitative approach as introduced by grounded theorist Barney Glaser, the lay partners’ concept of being a partner, as lived in higher education, is generated systematically from the data collected in the field primarily through in-depth interviews, field notes and observations. Glaser’s constant comparative method of analysis of data is used going through the phases of open coding, theoretical coding, and selective coding from memoing to theoretical sampling to sorting and then writing. In this study, Glaser’s grounded theory as a methodology will provide a substantial insight into and articulation of the layperson’s actual experience of being a partner of the Jesuits in education. Such articulation provides a phenomenological approach or framework to an understanding of the meaning and core characteristics of Jesuit-Lay partnership in Jesuit educational institution of higher learning in the country. This study is expected to provide a framework or model for lay partnership in academic institutions that have the same practice of having lay partners in mission.

Keywords: Grounded theory, Jesuit mission in higher education, lay partner, lived experience.

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