Search results for: Comprehensive language input
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2602

Search results for: Comprehensive language input

1492 Effect of Low Frequency Memory on High Power 12W LDMOS Transistors Intermodulation Distortion

Authors: A. Alghanim, J. Benedikt, P. J. Tasker

Abstract:

The increasing demand for higher data rates in wireless communication systems has led to the more effective and efficient use of all allocated frequency bands. In order to use the whole bandwidth at maximum efficiency, one needs to have RF power amplifiers with a higher linear level and memory-less performance. This is considered to be a major challenge to circuit designers. In this thesis the linearity and memory are studied and examined via the behavior of the intermodulation distortion (IMD). A major source of the in-band distortion can be shown to be influenced by the out-of-band impedances presented at either the input or the output of the device, especially those impedances terminated the low frequency (IF) components. Thus, in order to regulate the in-band distortion, the out of-band distortion must be controllable. These investigations are performed on a 12W LDMOS device characterised at 2.1 GHz within a purpose built, high-power measurement system.

Keywords: Low Frequency Memory, IntermodulationDistortion (IMD).

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1491 Face Recognition Using Discrete Orthogonal Hahn Moments

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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1490 Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process

Authors: H.Mohammadi Majd, M.Jalali Azizpour, A.V. Hoseini

Abstract:

In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: Back-propagation artificial neural network(BPANN), deep drawing, prediction, limiting drawing ratio (LDR).

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1489 Enhanced Character Based Algorithm for Small Parsimony

Authors: Parvinder Singh Sandhu, Sumeet Kaur Sehra, Karmjit Kaur

Abstract:

Phylogenetic tree is a graphical representation of the evolutionary relationship among three or more genes or organisms. These trees show relatedness of data sets, species or genes divergence time and nature of their common ancestors. Quality of a phylogenetic tree requires parsimony criterion. Various approaches have been proposed for constructing most parsimonious trees. This paper is concerned about calculating and optimizing the changes of state that are needed called Small Parsimony Algorithms. This paper has proposed enhanced small parsimony algorithm to give better score based on number of evolutionary changes needed to produce the observed sequence changes tree and also give the ancestor of the given input.

Keywords: Phylogenetic Analysis, Small Parsimony, EnhancedFitch Algorithm, Enhanced Sakoff Algorithm.

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1488 Application of BP Neural Network Model in Sports Aerobics Performance Evaluation

Authors: Shuhe Shao

Abstract:

This article provides partial evaluation index and its standard of sports aerobics, including the following 12 indexes: health vitality, coordination, flexibility, accuracy, pace, endurance, elasticity, self-confidence, form, control, uniformity and musicality. The three-layer BP artificial neural network model including input layer, hidden layer and output layer is established. The result shows that the model can well reflect the non-linear relationship between the performance of 12 indexes and the overall performance. The predicted value of each sample is very close to the true value, with a relative error fluctuating around of 5%, and the network training is successful. It shows that BP network has high prediction accuracy and good generalization capacity if being applied in sports aerobics performance evaluation after effective training.

Keywords: BP neural network, sports aerobics, performance, evaluation.

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1487 Day Type Identification for Algerian Electricity Load using Kohonen Maps

Authors: Mohamed Tarek Khadir, Damien Fay, Ahmed Boughrira

Abstract:

Short term electricity demand forecasts are required by power utilities for efficient operation of the power grid. In a competitive market environment, suppliers and large consumers also require short term forecasts in order to estimate their energy requirements in advance. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior to modelling. This identification, known as day-type identification, must be included in the modelling stage either by segmenting the data and modelling each day-type separately or by including the day-type as an input. Day-type identification is the main focus of this paper. A Kohonen map is employed to identify the separate day-types in Algerian data.

Keywords: Day type identification, electricity Load, Kohonenmaps, load forecasting.

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1486 Chatter Suppression in Boring Process Using Passive Damper

Authors: V. Prasannavenkadesan, A. Elango, S. Chockalingam

Abstract:

During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Keywords: Boring, chatter, mass damping, passive damping.

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1485 Prediction the Limiting Drawing Ratio in Deep Drawing Process by Back Propagation Artificial Neural Network

Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi

Abstract:

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm

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1484 Transmission Mains Earthing Design and Concrete Pole Deployments

Authors: M. Nassereddine, J. Rizk, A. Hellany, M. Nagrial

Abstract:

The High Voltage (HV) transmission mains into the community necessitate earthing design to ensure safety compliance of the system. Concrete poles are widely used within HV transmission mains; which could have an impact on the earth grid impedance and input impedance of the system from the fault point of view. This paper provides information on concrete pole earthing to enhance the split factor of the system; further, it discusses the deployment of concrete structures in high soil resistivity area to reduce the earth grid system of the plant. This paper introduces the cut off soil resistivity SC ρ when replacing timber poles with concrete ones.

Keywords: Concrete Poles, Earth Grid, EPR, High Voltage, Soil Resistivity.

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1483 Evaluation of Biomass Introduction Methods in Coal Co-Gasification

Authors: Ruwaida Abdul Rasid, Kevin J. Hughes, Peter J. Heggs, Mohamed Pourkashanian

Abstract:

Heightened concerns over the amount of carbon emitted from coal-related processes are generating shifts to the application of biomass. In co-gasification, where coal is gasified along with biomass, the biomass may be fed together with coal (cofeeding) or an independent biomass gasifier needs to be integrated with the coal gasifier. The main aim of this work is to evaluate the biomass introduction methods in coal co-gasification. This includes the evaluation of biomass concentration input (B0 to B100) and its gasification performance. A process model is developed and simulated in Aspen HYSYS, where both coal and biomass are modelled according to its ultimate analysis. It was found that the syngas produced increased with increasing biomass content for both co-feeding and independent schemes. However, the heating values and heat duties decreases with biomass concentration as more CO2 are produced from complete combustion.

Keywords: Aspen HYSYS, biomass, coal, co-gasification modelling and simulation.

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1482 Grid-based Supervised Clustering - GBSC

Authors: Pornpimol Bungkomkhun, Surapong Auwatanamongkol

Abstract:

This paper presents a supervised clustering algorithm, namely Grid-Based Supervised Clustering (GBSC), which is able to identify clusters of any shapes and sizes without presuming any canonical form for data distribution. The GBSC needs no prespecified number of clusters, is insensitive to the order of the input data objects, and is capable of handling outliers. Built on the combination of grid-based clustering and density-based clustering, under the assistance of the downward closure property of density used in bottom-up subspace clustering, the GBSC can notably reduce its search space to avoid the memory confinement situation during its execution. On two-dimension synthetic datasets, the GBSC can identify clusters with different shapes and sizes correctly. The GBSC also outperforms other five supervised clustering algorithms when the experiments are performed on some UCI datasets.

Keywords: supervised clustering, grid-based clustering, subspace clustering

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1481 Contextual Distribution for Textual Alignment

Authors: Yuri Bizzoni, Marianne Reboul

Abstract:

Our program compares French and Italian translations of Homer’s Odyssey, from the XVIth to the XXth century. We focus on the third point, showing how distributional semantics systems can be used both to improve alignment between different French translations as well as between the Greek text and a French translation. Although we focus on French examples, the techniques we display are completely language independent.

Keywords: Translation studies, machine translation, computational linguistics, distributional semantics.

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1480 Analysis of CNT Bundle and its Comparison with Copper for FPGAs Interconnects

Authors: Kureshi Abdul Kadir, Mohd. Hasan

Abstract:

Each new semiconductor technology node brings smaller transistors and wires. Although this makes transistors faster, wires get slower. In nano-scale regime, the standard copper (Cu) interconnect will become a major hurdle for FPGA interconnect due to their high resistivity and electromigration. This paper presents the comprehensive evaluation of mixed CNT bundle interconnects and investigates their prospects as energy efficient and high speed interconnect for future FPGA routing architecture. All HSPICE simulations are carried out at operating frequency of 1GHz and it is found that mixed CNT bundle implemented in FPGAs as interconnect can potentially provide a substantial delay and energy reduction over traditional interconnects at 32nm process technology.

Keywords: CMOS, Copper Interconnect, Mixed CNT Bundle Interconnect, FPGAs.

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1479 Micropower Fuzzy Linguistic-Hedges Circuit in Current-Mode Approach

Authors: E. Farshidi

Abstract:

In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (<200nW), immunity from body effect and wide input dynamic range (>60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.

Keywords: Current-mode, Linguistic-Hedge, Fuzzy Logic, lowpower

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1478 Skin Detection using Histogram depend on the Mean Shift Algorithm

Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun

Abstract:

In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.

Keywords: Skin region detection, mean shift, histogram approximation.

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1477 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network

Authors: Katsumi Hirata

Abstract:

Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: Bispectrum, convolutional neural network, environmental sound, slice bispectrogram, spectrogram.

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1476 Categorical Data Modeling: Logistic Regression Software

Authors: Abdellatif Tchantchane

Abstract:

A Matlab based software for logistic regression is developed to enhance the process of teaching quantitative topics and assist researchers with analyzing wide area of applications where categorical data is involved. The software offers an option of performing stepwise logistic regression to select the most significant predictors. The software includes a feature to detect influential observations in data, and investigates the effect of dropping or misclassifying an observation on a predictor variable. The input data may consist either as a set of individual responses (yes/no) with the predictor variables or as grouped records summarizing various categories for each unique set of predictor variables' values. Graphical displays are used to output various statistical results and to assess the goodness of fit of the logistic regression model. The software recognizes possible convergence constraints when present in data, and the user is notified accordingly.

Keywords: Logistic regression, Matlab, Categorical data, Influential observation.

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1475 Utilization of Process Mapping Tool to Enhance Production Drilling in Underground Metal Mining Operations

Authors: Sidharth Talan, Sanjay Kumar Sharma, Eoin Joseph Wallace, Nikita Agrawal

Abstract:

Underground mining is at the core of rapidly evolving metals and minerals sector due to the increasing mineral consumption globally. Even though the surface mines are still more abundant on earth, the scales of industry are slowly tipping towards underground mining due to rising depth and complexities of orebodies. Thus, the efficient and productive functioning of underground operations depends significantly on the synchronized performance of key elements such as operating site, mining equipment, manpower and mine services. Production drilling is the process of conducting long hole drilling for the purpose of charging and blasting these holes for the production of ore in underground metal mines. Thus, production drilling is the crucial segment in the underground metal mining value chain. This paper presents the process mapping tool to evaluate the production drilling process in the underground metal mining operation by dividing the given process into three segments namely Input, Process and Output. The three segments are further segregated into factors and sub-factors. As per the study, the major input factors crucial for the efficient functioning of production drilling process are power, drilling water, geotechnical support of the drilling site, skilled drilling operators, services installation crew, oils and drill accessories for drilling machine, survey markings at drill site, proper housekeeping, regular maintenance of drill machine, suitable transportation for reaching the drilling site and finally proper ventilation. The major outputs for the production drilling process are ore, waste as a result of dilution, timely reporting and investigation of unsafe practices, optimized process time and finally well fragmented blasted material within specifications set by the mining company. The paper also exhibits the drilling loss matrix, which is utilized to appraise the loss in planned production meters per day in a mine on account of availability loss in the machine due to breakdowns, underutilization of the machine and productivity loss in the machine measured in drilling meters per unit of percussion hour with respect to its planned productivity for the day. The given three losses would be essential to detect the bottlenecks in the process map of production drilling operation so as to instigate the action plan to suppress or prevent the causes leading to the operational performance deficiency. The given tool is beneficial to mine management to focus on the critical factors negatively impacting the production drilling operation and design necessary operational and maintenance strategies to mitigate them. 

Keywords: Process map, drilling loss matrix, availability, utilization, productivity, percussion rate.

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1474 A Fuzzy Predictive Filter for Sinusoidal Signals with Time-Varying Frequencies

Authors: X. Z. Gao, S. J. Ovaska, X. Wang

Abstract:

Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.

Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.

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1473 Comanche – A Compiler-Driven I/O Management System

Authors: Wendy Zhang, Ernst L. Leiss, Huilin Ye

Abstract:

Most scientific programs have large input and output data sets that require out-of-core programming or use virtual memory management (VMM). Out-of-core programming is very error-prone and tedious; as a result, it is generally avoided. However, in many instance, VMM is not an effective approach because it often results in substantial performance reduction. In contrast, compiler driven I/O management will allow a program-s data sets to be retrieved in parts, called blocks or tiles. Comanche (COmpiler MANaged caCHE) is a compiler combined with a user level runtime system that can be used to replace standard VMM for out-of-core programs. We describe Comanche and demonstrate on a number of representative problems that it substantially out-performs VMM. Significantly our system does not require any special services from the operating system and does not require modification of the operating system kernel.

Keywords: I/O Management, Out-of-core, Compiler, Tile mapping.

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1472 Using ALOHA Code to Evaluate CO2 Concentration for Maanshan Nuclear Power Plant

Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

Abstract:

ALOHA code was used to calculate the concentration under the CO2 storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan.

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1471 ANFIS Modeling of the Surface Roughness in Grinding Process

Authors: H. Baseri, G. Alinejad

Abstract:

The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.

Keywords: Grinding, ANFIS, Neural network, Disc dressing.

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1470 Unified Power Flow Controller Placement to Improve Damping of Power Oscillations

Authors: M. Salehi, A. A. Motie Birjandi, F. Namdari

Abstract:

Weak damping of low frequency oscillations is a frequent phenomenon in electrical power systems. These frequencies can be damped by power system stabilizers. Unified power flow controller (UPFC), as one of the most important FACTS devices, can be applied to increase the damping of power system oscillations and the more effect of this controller on increasing the damping of oscillations depends on its proper placement in power systems. In this paper, a technique based on controllability is proposed to select proper location of UPFC and the best input control signal in order to enhance damping of power oscillations. The effectiveness of the proposed technique is demonstrated in IEEE 9 bus power system.

Keywords: Unified power flow controller (UPFC), controllability, small signal analysis, eigenvalues.

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1469 Modelling and Simulation of the Freezing Systems and Heat Pumps Using Unisim® Design

Authors: C. Patrascioiu

Abstract:

The paper describes the modeling and simulation of the heat pumps domain processes. The main objective of the study is the use of the heat pump in propene–propane distillation processes. The modeling and simulation instrument is the Unisim® Design simulator. The paper is structured in three parts: An overview of the compressing gases, the modeling and simulation of the freezing systems, and the modeling and simulation of the heat pumps. For each of these systems, there are presented the Unisim® Design simulation diagrams, the input–output system structure and the numerical results. Future studies will consider modeling and simulation of the propene–propane distillation process with heat pump.

Keywords: Distillation, heat pump, simulation, Unisim Design.

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1468 On Two Control Approaches for The Output Voltage Regulation of a Boost Converter

Authors: Abdelaziz Sahbani, Kamel Ben Saad, Mohamed Benrejeb

Abstract:

This paper deals with the comparison between two proposed control strategies for a DC-DC boost converter. The first control is a classical Sliding Mode Control (SMC) and the second one is a distance based Fuzzy Sliding Mode Control (FSMC). The SMC is an analytical control approach based on the boost mathematical model. However, the FSMC is a non-conventional control approach which does not need the controlled system mathematical model. It needs only the measures of the output voltage to perform the control signal. The obtained simulation results show that the two proposed control methods are robust for the case of load resistance and the input voltage variations. However, the proposed FSMC gives a better step voltage response than the one obtained by the SMC.

Keywords: Boost DC-DC converter, Sliding Mode Control (SMC), Fuzzy Sliding Mode Control (FSMC), Robustness.

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1467 Design and Analysis of Two-Phase Boost DC-DC Converter

Authors: Taufik Taufik, Tadeus Gunawan, Dale Dolan, Makbul Anwari

Abstract:

Multiphasing of dc-dc converters has been known to give technical and economical benefits to low voltage high power buck regulator modules. A major advantage of multiphasing dc-dc converters is the improvement of input and output performances in the buck converter. From this aspect, a potential use would be in renewable energy where power quality plays an important factor. This paper presents the design of a 2-phase 200W boost converter for battery charging application. Analysis of results from hardware measurement of the boost converter demonstrates the benefits of using multiphase. Results from the hardware prototype of the 2-phase boost converter further show the potential extension of multiphase beyond its commonly used low voltage high current domains.

Keywords: Multiphase, boost converter, power electronics.

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1466 A Methodology for Creating a Conceptual Model Under Uncertainty

Authors: Bogdan Walek, Jiri Bartos, Cyril Klimes

Abstract:

This article deals with the conceptual modeling under uncertainty. First, the division of information systems with their definition will be described, focusing on those where the construction of a conceptual model is suitable for the design of future information system database. Furthermore, the disadvantages of the traditional approach in creating a conceptual model and database design will be analyzed. A comprehensive methodology for the creation of a conceptual model based on analysis of client requirements and the selection of a suitable domain model is proposed here. This article presents the expert system used for the construction of a conceptual model and is a suitable tool for database designers to create a conceptual model.

Keywords: Conceptual model, conceptual modeling, database, methodology, uncertainty, information system, entity, attribute, relationship, conceptual domain model, fuzzy.

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1465 Intellectual Capital Report for Universities

Authors: Yolanda Ramírez Córcoles, Ángel Tejad Ponce, Agustín Baidez González

Abstract:

Intellectual capital reporting becomes critical at universities, mainly due to the fact that knowledge is the main output as well as input in these institutions. In addition, universities have continuous external demands for greater information and transparency about the use of public funds, and are increasingly provided with greater autonomy regarding their organization, management, and budget allocation. This situation requires new management and reporting systems. The purpose of the present study is to provide a model for intellectual capital report in Spanish universities. To this end, a questionnaire was sent to every member of the Social Councils of Spanish public universities in order to identify which intangible elements university stakeholders demand most. Our proposal for an intellectual capital report aims to act as a guide to help the Spanish universities on the road to the presentation of information on intellectual capital which can assist stakeholders to make the right decisions.

Keywords: Intellectual capital, Spain, report, universities.

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1464 Mining Multicity Urban Data for Sustainable Population Relocation

Authors: Xu Du, Aparna S. Varde

Abstract:

In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: Data Mining, Environmental Modeling, Sustainability, Urban Planning.

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1463 An Improved Optimal Sliding Mode Control for Structural Stability

Authors: Leila Fatemi, Morteza Moradi, Azadeh Mansouri

Abstract:

In this paper, the modified optimal sliding mode control with a proposed method to design a sliding surface is presented. Because of the inability of the previous approach of the sliding mode method to design a bounded and suitable input, the new variation is proposed in the sliding manifold to obviate problems in a structural system. Although the sliding mode control is a powerful method to reject disturbances and noises, the chattering problem is not good for actuators. To decrease the chattering phenomena, the optimal control is added to the sliding mode control. Not only the proposed method can decline the intense variations in the inputs of the system but also it can produce the efficient responses respect to the sliding mode control and optimal control that are shown by performing some numerical simulations.

Keywords: Structural Control, optimal control, optimal sliding mode controller, modified sliding surface.

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