Search results for: optimal allocation

Authors: Sajeena Beevi. B, Jose P. P., G. Madhu

Abstract:

The aim of this study was to obtain the optimal conditions for biogas production from anaerobic digestion of organic fraction of municipal solid waste (OFMSW) using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The highest level of biogas produced was 53.4 L/Kg VS at optimum pH, substrate concentration and total organic carbon of 6.5, 99gTS/L and 20.32 g/L respectively.

Keywords: Anaerobic Digestion, Biogas, Optimization, Response Surface Methodology.

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Authors: Jung-Eun Park, Kyung-Whan Oh

Abstract:

Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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Authors: Mihai Caramihai, Irina Severin, Ana Aurelia Chirvase, Adrian Onu, Cristina Tanase, Camelia Ungureanu

Abstract:

An immunomodulator bioproduct is prepared in a batch bioprocess with a modified bacterium Pseudomonas aeruginosa. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The optimal bioprocess parameters were determined: temperature – 37 0C, agitation speed - 300 rpm, aeration rate – 40 L/min, pressure – 0.5 bar, Dow Corning Antifoam M-max. 4 % of the medium volume, duration - 6 hours. This kind of bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying. The aim of the paper is to present (by comparison) different models based on experimental data. The analysis criteria were modeling error and convergence rate. The estimated values and the modeling analysis were done by using the Table Curve 2D. The preliminary conclusions indicate Andrews-s model with a maximum specific growth rate of the bacterium in the range of 0.8 h-1.

Keywords: bioprocess modeling, Pseudomonas aeruginosa, kinetic models,

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Authors: T. Sopapirm, K-N. Areerak, K-L. Areerak, A. Srikaew

Abstract:

The paper presents the applications of artificial intelligence technique called adaptive tabu search to design the controller of a buck converter. The averaging model derived from the DQ and generalized state-space averaging methods is applied to simulate the system during a searching process. The simulations using such averaging model require the faster computational time compared with that of the full topology model from the software packages. The reported model is suitable for the work in the paper in which the repeating calculation is needed for searching the best solution. The results will show that the proposed design technique can provide the better output waveforms compared with those designed from the classical method.

Keywords: Buck converter, adaptive tabu search, DQ method, generalized state-space averaging method, modeling and simulation

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Authors: T. Vigneswari, M. A. Maluk Mohamed

Abstract:

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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Authors: Ismail I. Fasfous, Nedal Abu Farha

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The purpose of this research is to establish the experimental conditions for removal of Cibacron Brilliant Yellow 3G-P dye (CBY) from aqueous solutions by sorption onto coffee husks as a low-cost sorbent. The effects of various experimental parameters (e.g. initial CBY dye concentration, sorbent mass, pH, temperature) were examined and the optimal experimental conditions were determined. The results indicated that the removal of the dye was pH dependent and at initial pH of 2, the dye was removed effectively. The CBY dye sorption data were fitted to Langmuir, Freundlich, Temkin and Dubinin-Radushkevich equilibrium models. The maximum sorption capacity of CBY dye ions onto coffee husks increased from 24.04 to 35.04 mg g-1 when the temperature was increased from 293 to 313 K. The calculated sorption thermodynamic parameters including ΔG°, ΔH°, and ΔS° indicated that the CBY dye sorption onto coffee husks is a spontaneous, endothermic and mainly physical in nature.

Keywords: Coffee husks, equilibrium, reactive dyes, sorption.

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Authors: Dana Kristalova, Jan Mazal

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the Army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: Movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths.

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Authors: Whee Yen Wong, Chan Wai Lee, Kim Yeow Tshai

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Producing IT products/services required carefully designed. IT development process is intangible and labour intensive. Making optimal use of available resources, both soft (knowledge, skill-set etc.) and hard (computer system, ancillary equipment etc.), is vital if IT development is to achieve sensible economical advantages. Apart from the norm of Project Life Cycle and System Development Life Cycle (SDLC), there is an urgent need to establish a general yet widely acceptable guideline on the most effective and efficient way to precede an IT project in the broader view of Product Life Cycle. The current paper proposes such a framework with two major areas of concern: (1) an integration of IT Products and IT Services within an existing IT Process architecture and; (2) how IT Product and IT Services are built into the framework of Product Life Cycle, Project Life Cycle and SDLC.

Keywords: Mapping of Quality Relationship, IT Processes/IT Products/IT Services, Product Life Cycle, System Development Life Cycle.

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Authors: Liping Li, Changchun Liu, Ke Li, Chengyu Liu

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Non-stationary trend in R-R interval series is considered as a main factor that could highly influence the evaluation of spectral analysis. It is suggested to remove trends in order to obtain reliable results. In this study, three detrending methods, the smoothness prior approach, the wavelet and the empirical mode decomposition, were compared on artificial R-R interval series with four types of simulated trends. The Lomb-Scargle periodogram was used for spectral analysis of R-R interval series. Results indicated that the wavelet method showed a better overall performance than the other two methods, and more time-saving, too. Therefore it was selected for spectral analysis of real R-R interval series of thirty-seven healthy subjects. Significant decreases (19.94±5.87% in the low frequency band and 18.97±5.78% in the ratio (p<0.001)) were found. Thus the wavelet method is recommended as an optimal choice for use.

Keywords: empirical mode decomposition, heart rate variability, signal detrending, smoothness priors, wavelet

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: Travel characteristics analysis, transportation choice, travel sharing rate, neural network model, traffic resource allocation.

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Authors: H. Nikzad, S. Yoshitomi

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In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures.

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Authors: Tunchanok Nitipan, Siriporn Jongpatiwut, Thirasak Rirksomboon, Boonyarach Kitiyanan, Tivaporn Apphakvan

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In this study, the conversion of n-pentane to aromatics is investigated on HZSM-5 zeolites modified by Ga ion-exchange and silylation using tetraethyl orthosilicate (TEOS) via chemical liquid deposition (CLD). The effect of SiO2/Al2O3 ratios of HZSM-5 was also studied. Parameters in preparing catalysts i.e. TEOS loading and cycles of deposition were varied to obtain the optimal condition for enhancing p-xylene selectivity. The highest p-xylene selectivity 99.7% was achieved when the amount of TEOS was 20 vol.%.The catalysts were characterized by TPD, TPO, XRF, and BET. Results show that the conversion of n-pentane was influenced remarkably by the SiO2/Al2O3 ratios of HZSM-5. The highest p-xylene selectivity 99.7% was achieved when the amount of TEOS was 20 vol.%. And cycles of deposition greatly improves HZSM-5 shape-selectivity.

Keywords: Aromatization, Chemical Liquid Deposition (CLD), p-Xylene, ZSM-5 Zeolite

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Authors: C. Vrekos, C. Evagelides, N. Samarinas, G. Arampatzis

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As known, the water energy is a renewable and clean source of energy. Energy production from hydropower has been the first, and still is today a renewable source used to generate electricity. The optimal location and sizing of a small hydropower plant is a very important issue in engineering design which encourages investigation. The aim of this paper is to present a formula that can be utilized for locating the position of a small hydropower plant although there is a high dependence on economic, environmental, and social parameters. In this paper, the economic and technical side of the problem is considered. More specifically, there is a critical terrain slope that determines if the plant should be located at the end of the slope or not. Of course, this formula can be used for a first estimate and does not include detailed economic analysis. At the end, a case study is presented for the location of a small hydropower plant in order to demonstrate the validity of the proposed formula.

Keywords: Critical terrain slope, economic analysis, hydropower plant locating, renewable energy.

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Authors: Pakorn Traiprasertpong, Apichit Svang-Ariyaskul

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The production of ethyl tert-butyl ether (ETBE) was simulated through Aspen Plus. The objective of this work was to use the simulation results to be an alternative platform for ETBE production from naphtha cracking wastes for the industry to develop. ETBE is produced from isobutylene which is one of the wastes in naphtha cracking process. The content of isobutylene in the waste is less than 30% weight. The main part of this work was to propose a process to save the environment and to increase the product value by converting a great majority of the wastes into ETBE. Various processes were considered to determine the optimal production of ETBE. The proposed process increased ETBE production yield by 100% from conventional process with the purity of 96% weight. The results showed a great promise for developing this proposed process in an industrial scale.

Keywords: ETBE, process simulation, naphtha cracking, Aspen Plus

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Authors: Alesya Ya. Maruk, Olga E. Klementyeva, Ekaterina I. Lesik, Anton A. Larenkov, Alexander B. Bruskin

Abstract:

Alpfa-fetoprotein and its fragments may be an important vehicle for targeted delivery of radionuclides to the tumor. We investigated the effect of conditions on the labeling of biologically active synthetic peptide based on the (F-afp) with technetium-99m. The influence of the nature of the buffer solution, pH, concentration of reductant, concentration of the peptide and the reaction temperature on the yield of labeling was examined. As a result, the following optimal conditions for labeling of (F-afp) are found: pH 8.5 (phosphate and bicarbonate buffers) and pH from 1.7 to 7.0 (citrate buffer). The reaction proceeds with sufficient yield at room temperature for 30 min at the concentration of SnCl2 and (Fafp) (F-afp) is to be less than 10 mkg/ml and 25 mkg/ml, respectively. Investigations of the test drug accumulation in the tumor cells of human breast cancer were carried out. Results can be assumed that the in vivo study of the (F-afp) in experimental tumor lesions will show concentrations sufficient for imaging these lesions by SPECT.

Keywords: peptide, technetium-99m, tumor, SPECT.

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Authors: Sheeba V.S, Elizabeth Elias

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Optimization of filter banks based on the knowledge of input statistics has been of interest for a long time. Finite impulse response (FIR) Compaction filters are used in the design of optimal signal adapted orthonormal FIR filter banks. In this paper we discuss three different approaches for the design of interpolated finite impulse response (IFIR) compaction filters. In the first method, the magnitude squared response satisfies Nyquist constraint approximately. In the second and third methods Nyquist constraint is exactly satisfied. These methods yield FIR compaction filters whose response is comparable with that of the existing methods. At the same time, IFIR filters enjoy significant saving in the number of multipliers and can be implemented efficiently. Since eigenfilter approach is used here, the method is less complex. Design of IFIR filters in the least square sense is presented.

Keywords: Principal Component Filter Bank, InterpolatedFinite Impulse Response filter, Orthonormal Filter Bank, Eigen Filter.

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Authors: Ramin Karimzadeh, Nazi Rahimi, Mohammad Ghashghaee

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In the present research, steam cracking of two types of feedstocks i.e., naphtha and ethane is simulated for Pyrocrack1-1 and 2/2 coil configurations considering two key parameters of coil outlet temperature (COT) and coil capacity using a radical based kinetic model. The computer model is confirmed using the industrial data obtained from Amirkabir Petrochemical Complex. The results are in good agreement with performance data for naphtha cracking in a wide range of severity (0.4-0.7), and for ethane cracking on various conversions (50-70). It was found that Pyrocrack2-2 coil type is an appropriate choice for steam cracking of ethane at reasonable ethylene yield while resulting in much lower tube wall temperature while Pyrocrack1-1 coil type is a proper selection for liquid feedstocks i.e. naphtha. It can be used for cracking of liquid feedstocks at optimal ethylene yield whereas not exceeding the allowable maximum tube temperature.

Keywords: Coil configuration, Ethane, Naphtha, Steamcracking.

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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: Breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration (FNA).

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Authors: Michael Grigutsch, Marco Kennemann, Peter Nyhuis

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Due to the recovering global economy, enterprises are increasingly focusing on logistics. Investing in logistic measures for a production generates a large potential for achieving a good starting point within a competitive field. Unlike during the global economic crisis, enterprises are now challenged with investing available capital to maximize profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need an adequate model for logistically and monetarily evaluating measures in production. The Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems (IFA) developed a Logistic Information System which provides support in making decisions and is designed specifically for the forging industry. The aim of a project that has been applied for is to now transfer this process in order to develop a universal approach to logistically and monetarily evaluate measures in production.

Keywords: Measures in Production, Logistic Operating Curves, Transfer Functions, Production Logistics

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Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

Abstract:

This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: Busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling.

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Authors: Pankaj Swarnkar, Shailendra Jain, R.K Nema

Abstract:

Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. This paper deals with application of model reference adaptive control scheme in first order system. The rule which is used for this application is MIT rule. This paper also shows the effect of adaptation gain on the system performance. Simulation is done in MATLAB and results are discussed in detail.

Keywords: Adaptive control system, Adaptation gain, MIT rule, Model reference adaptive control.

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Authors: Huiming Peng, Jianguo Wen, Hongwei Li, Jeff Chang, Xiaobo Zhou

Abstract:

NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.

Keywords: Computational modeling, drug combination, inhibition effect, multiple myeloma, NFkB pathway.

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: Building energy management, machine learning, simulation-based optimization, operation planning.

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Authors: Djamal Atlaoui, Youcef Bouafia

Abstract:

This work deals with the experimental study of the mechanical behavior, by shear tests (fracture shear), elements of concrete beams reinforced with fibers in chips. These fibers come from the machining waste of the steel parts. The shear tests are carried out on prismatic specimens of dimensions 10 x 20 x 120 cm³. The fibers are characterized by mechanical resistance and tearing. The optimal composition of the concrete was determined by the workability test. Two fiber contents are selected for this study (W = 0.6% and W = 0.8%) and a BT control concrete (W = 0%) of the same composition as the matrix is developed to serve as a reference with a sand-to-gravel ratio (S/G) of concrete matrix equal to 1. The comparison of the different results obtained shows that the chips fibers confer a significant ductility to the material after cracking of the concrete. Also, the fibers used limit diagonal cracks in shear and improve strength and rigidity.

Keywords: Characterization, chips fibers, cracking mode, ductility, undulation, shear.

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Authors: Aldy Gunawan, Kien Ming Ng, Kim Leng Poh

Abstract:

This paper presents a hybrid algorithm for solving a timetabling problem, which is commonly encountered in many universities. The problem combines both teacher assignment and course scheduling problems simultaneously, and is presented as a mathematical programming model. However, this problem becomes intractable and it is unlikely that a proven optimal solution can be obtained by an integer programming approach, especially for large problem instances. A hybrid algorithm that combines an integer programming approach, a greedy heuristic and a modified simulated annealing algorithm collaboratively is proposed to solve the problem. Several randomly generated data sets of sizes comparable to that of an institution in Indonesia are solved using the proposed algorithm. Computational results indicate that the algorithm can overcome difficulties of large problem sizes encountered in previous related works.

Keywords: Timetabling problem, mathematical programming model, hybrid algorithm, simulated annealing.

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Authors: M. Sadeghzadeh, M. Teshnehlab

Abstract:

Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant colony optimization, Classification, Datamining, Feature selection.

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

Abstract:

Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Keywords: Aggregation, Packet Merging, Query Processing.

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Authors: P. Georgieva, S. Feyo de Azevedo

Abstract:

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

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The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: Flow-shop scheduling problem, makespan, Petri nets, state equation.

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