Search results for: weather architecture.

Authors: M. Bohlouli, M. Analoui

Abstract:

For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.

Keywords: Active Database, Grid Computing, ResourceRequirement Prediction, Scheduling,

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Authors: Yunbin Yang, Liangli He, Fengjun Wang

Abstract:

The essentiality of maintenance assessment and maintenance optimization in design stage is analyzed, and the existent problems of conventional maintenance design method are illuminated. MDMVM (Maintenance Design Method based Virtual Maintenance) is illuminated, and the process of MDMVM established, and the MDMVM architecture is given out. The key techniques of MDMVM are analyzed, and include maintenance design based KBE (Knowledge Based Engineering) and virtual maintenance based physically attribute. According to physical property, physically based modeling, visual object movement control, the simulation of operation force and maintenance sequence planning method are emphatically illuminated. Maintenance design system based virtual maintenance is established in foundation of maintenance design method.

Keywords: Digital mock-up, virtual maintenance, knowledge engineering, maintenance sequence planning.

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Authors: Asha Rani, Christian Micheloni, Gian Luca Foresti

Abstract:

In this paper, a neural tree (NT) classifier having a simple perceptron at each node is considered. A new concept for making a balanced tree is applied in the learning algorithm of the tree. At each node, if the perceptron classification is not accurate and unbalanced, then it is replaced by a new perceptron. This separates the training set in such a way that almost the equal number of patterns fall into each of the classes. Moreover, each perceptron is trained only for the classes which are present at respective node and ignore other classes. Splitting nodes are employed into the neural tree architecture to divide the training set when the current perceptron node repeats the same classification of the parent node. A new error function based on the depth of the tree is introduced to reduce the computational time for the training of a perceptron. Experiments are performed to check the efficiency and encouraging results are obtained in terms of accuracy and computational costs.

Keywords: Neural Tree, Pattern Classification, Perceptron, Splitting Nodes.

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Authors: Souleymane Oumtanaga, Kadjo Tanon Lambert, Koné Tiémoman, Tety Pierre, Kimou KouadioProsper

Abstract:

Multicast transmissions allow an host (the source) to send only one flow bound for a group of hosts (the receivers). Any equipment eager to belong to the group may explicitly register itself to that group via its multicast router. This router will be given the responsibility to convey all information relating to the group to all registered hosts. However in an environment in which the final receiver or the source frequently moves, the multicast flows need particular treatment. This constitutes one of the multicast transmissions problems around which several proposals were made in the Mobile IPv6 case in general. In this article, we describe the problems involved in this IPv6 multicast mobility and the existing proposals for their resolution. Then architecture will be proposed aiming to satisfy and optimize these transmissions in the specific case of a mobile multicast receiver in NC-HMIPv6 environment.

Keywords: Mobile IP, NC-HMIPv6, Multicast, MLD, PIM, SSM, Rendezvous Point.

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Authors: Ahmed Chalak Shakir, GuXuemai, Jia Min

Abstract:

Recently, wireless sensor networks have been paid more interest, are widely used in a lot of commercial and military applications, and may be deployed in critical scenarios (e.g. when a malfunctioning network results in danger to human life or great financial loss). Such networks must be protected against human intrusion by using the secret keys to encrypt the exchange messages between communicating nodes. Both the symmetric and asymmetric methods have their own drawbacks for use in key management. Thus, we avoid the weakness of these two cryptosystems and make use of their advantages to establish a secure environment by developing the new method for encryption depending on the idea of code conversion. The code conversion-s equations are used as the key for designing the proposed system based on the basics of logic gate-s principals. Using our security architecture, we show how to reduce significant attacks on wireless sensor networks.

Keywords: logic gates, code conversions, Gray-code, and clustering.

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Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: Bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques.

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Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

Abstract:

The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient.

In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake.

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Authors: Saipunidzam Mahamad, Mohammad Noor Ibrahim, Rozana Kasbon, Chap Samol

Abstract:

Animated graph gives some good impressions in presenting information. However, not many people are able to produce it because the process of generating an animated graph requires some technical skills. This work presents Content Management System with Animated Graph (CMS-AG). It is a webbased system enabling users to produce an effective and interactive graphical report in a short time period. It allows for three levels of user authentication, provides update profile, account management, template management, graph management, and track changes. The system development applies incremental development approach, object-oriented concepts and Web programming technologies. The design architecture promotes new technology of reporting. It also helps user cut off unnecessary expenses, save time and learn new things on different levels of users. In this paper, the developed system is described.

Keywords: Animated Graph, Content Management System.

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Authors: Ahmad Aljaafreh

Abstract:

Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.

Keywords: Driving monitoring system, In-vehicle embedded system, Hierarchical fuzzy system.

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Authors: Salvador Mandujano

Abstract:

This paper describes the design and results of FROID, an outbound intrusion detection system built with agent technology and supported by an attacker-centric ontology. The prototype features a misuse-based detection mechanism that identifies remote attack tools in execution. Misuse signatures composed of attributes selected through entropy analysis of outgoing traffic streams and process runtime data are derived from execution variants of attack programs. The core of the architecture is a mesh of self-contained detection cells organized non-hierarchically that group agents in a functional fashion. The experiments show performance gains when the ontology is enabled as well as an increase in accuracy achieved when correlation cells combine detection evidence received from independent detection cells.

Keywords: Outbound intrusion detection, knowledge management, multiagent systems, ontology.

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Authors: F. Matusek, G. Pujolle, R. Reda

Abstract:

Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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Authors: Bakr Hashem Paumey Ahmed Alashwal

Abstract:

The urban transformation processes in its framework and its general significance became a fundamental and vital subject of consideration for both the developed and the developing societies. It has become important to regulate the architectural systems adopted by the city, to sustain the present development on one hand, and on the other hand, to facilitate its future growth. Thus, the study dealt with the phenomenon of urban transformation of the Mediterranean cities, and the city of Alexandria in particular, because of its significant historical and cultural legacy, its historical architecture and its contemporary urbanization. This article investigates the entirety of cities in the Mediterranean region through the analysis of the relationship between inflation and growth of these cities and the extent of the complexity of the city barriers. We hope to analyze not only the internal transformations, but the external relationships (both imperial and post-colonial) that have shaped Alexandria city growth from the nineteenth century until today.

Keywords: Urban Transformations, Mediterranean cities, Modern Era, Alexandria.

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Authors: Vikram Jeganathan, A. V. Sai Balasubramanian, N. Ravi Shankar, S. Subbaraman, R. Rengaraj

Abstract:

Heating systems are a necessity for regions which brace extreme cold weather throughout the year. To maintain a comfortable temperature inside a given place, heating systems making use of- Hydronic boilers- are used. The principle of a single pipe system serves as a base for their working. It is mandatory for these heating systems to control the room temperature, thus maintaining a warm environment. In this paper, the concept of regulation of the room temperature over a wide range is established by using an Adaptive Fuzzy Controller (AFC). This fuzzy controller automatically detects the changes in the outside temperatures and correspondingly maintains the inside temperature to a palatial value. Two separate AFC's are put to use to carry out this function: one to determine the quantity of heat needed to reach the prospective temperature required and to set the desired temperature; the other to control the position of the valve, which is directly proportional to the error between the present room temperature and the user desired temperature. The fuzzy logic controls the position of the valve as per the requirement of the heat. The amount by which the valve opens or closes is controlled by 5 knob positions, which vary from minimum to maximum, thereby regulating the amount of heat flowing through the valve. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.

Keywords: Adaptive fuzzy controller, Hydronic heating system

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Authors: Rohana Musa, Yuzman Yusoff, Chia Chieu Yin, Hanif Che Lah

Abstract:

This paper presents the design and characterization of a low power Complementary Metal Oxide Semiconductor (CMOS) process sensor. The design is targeted for implementation using Silterra’s 180 nm CMOS process technology. The proposed process sensor employs a voltage threshold (V_th) extractor architecture for detection of variations in the fabrication process. The process sensor generates output voltages in the range of 401 mV (fast-fast corner) to 443 mV (slow-slow corner) at nominal condition. The power dissipation for this process sensor is 6.3 µW with a supply voltage of 1.8V with a silicon area of 190 µm X 60 µm. The preliminary result of this process sensor that was fabricated indicates a close resemblance between test and simulated results.

Keywords: CMOS Process sensor, Process, Voltage and Temperature (PVT) sensor, threshold extractor circuit, Vth extractor circuit.

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Authors: E. Tarantino, G. Disciglio, G. Gatta, L. Frabboni, A. Libutti, A. Tarantino

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Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD₅, Na⁺, Ca²⁺, Mg²⁺, NH₄-N, PO₄-P, K⁺, SAR and CaCO₃, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.

Keywords: Agro-industrial wastewater, broccoli, long-term re-use, tomato.

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Authors: U K Chakrabarti, Jigisha Parikh

Abstract:

Hazardous Material transportation by road is coupled with inherent risk of accidents causing loss of lives, grievous injuries, property losses and environmental damages. The most common type of hazmat road accident happens to be the releases (78%) of hazardous substances, followed by fires (28%), explosions (14%) and vapour/ gas clouds (6 %.). The paper is discussing initially the probable 'Impact Zones' likely to be caused by one flammable (LPG) and one toxic (ethylene oxide) chemicals being transported through a sizable segment of a State Highway connecting three notified Industrial zones in Surat district in Western India housing 26 MAH industrial units. Three 'hotspots' were identified along the highway segment depending on the particular chemical traffic and the population distribution within 500 meters on either sides. The thermal radiation and explosion overpressure have been calculated for LPG / Ethylene Oxide BLEVE scenarios along with toxic release scenario for ethylene oxide. Besides, the dispersion calculations for ethylene oxide toxic release have been made for each 'hotspot' location and the impact zones have been mapped for the LOC concentrations. Subsequently, the maximum Initial Isolation and the protective zones were calculated based on ERPG-3 and ERPG-2 values of ethylene oxide respectively which are estimated taking the worst case scenario under worst weather conditions. The data analysis will be helpful to the local administration in capacity building with respect to rescue / evacuation and medical preparedness and quantitative inputs to augment the District Offsite Emergency Plan document.

Keywords: Hotspot, Ethylene Oxide, LPG, MAH (MajorAccident Hazard).

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: Aissam Belghiat, Mustapha Bourahla

Abstract:

Models are placed by modeling paradigm at the center of development process. These models are represented by languages, like UML the language standardized by the OMG which became necessary for development. Moreover the ontology engineering paradigm places ontologies at the center of development process; in this paradigm we find OWL the principal language for knowledge representation. Building ontologies from scratch is generally a difficult task. The bridging between UML and OWL appeared on several regards such as the classes and associations. In this paper, we have to profit from convergence between UML and OWL to propose an approach based on Meta-Modelling and Graph Grammars and registered in the MDA architecture for the automatic generation of OWL ontologies from UML class diagrams. The transformation is based on transformation rules; the level of abstraction in these rules is close to the application in order to have usable ontologies. We illustrate this approach by an example.

Keywords: ATOM3, MDA, Ontology, OWL, UML

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Authors: J. Szolomicki, H. Golasz-Szolomicka

Abstract:

This paper presents elements of architectural and structural analysis of selected high-rise buildings in the Polish capital city of Warsaw. When analyzing the architecture of Warsaw, it can be concluded that it is currently a rapidly growing city with technologically advanced skyscrapers that belong to the category of intelligent buildings. The constructional boom over the last dozen years has seen the erection of postmodern skyscrapers for office and residential use. This article focuses on how Warsaw has recently joined the most architecturally interesting cities in Europe. Warsaw is currently in fifth place in Europe in terms of the number of skyscrapers and is considered the second most preferred city in Europe (after London) for investment related to them. However, the architectural development of the city could not take place without the participation of eminent Polish and foreign architects such as Stefan Kuryłowicz, Lary Oltmans, Helmut Jahn or Daniel Libeskind.

Keywords: Core structure, raft foundation, tall buildings.

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Authors: L. Basha, E. Gjika

Abstract:

This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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Authors: L. Ramirez, E. Guillén, J. Sánchez

Abstract:

Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: Analytics, telemedicine, internet of things, cloud computing.

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Authors: Kamaraju.M, Lal Kishore.K, Tilak.A.V.N

Abstract:

The general purpose processors that are used in embedded systems must support constraints like execution time, power consumption, code size and so on. On the other hand an Application Specific Instruction-set Processor (ASIP) has advantages in terms of power consumption, performance and flexibility. In this paper, a 16-bit Application Specific Instruction-set processor for the sensor data transfer is proposed. The designed processor architecture consists of on-chip transmitter and receiver modules along with the processing and controlling units to enable the data transmission and reception on a single die. The data transfer is accomplished with less number of instructions as compared with the general purpose processor. The ASIP core operates at a maximum clock frequency of 1.132GHz with a delay of 0.883ns and consumes 569.63mW power at an operating voltage of 1.2V. The ASIP is implemented in Verilog HDL using the Xilinx platform on Virtex4.

Keywords: ASIP, Data transfer, Instruction set, Processor

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Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: Cellular automata, neural cellular automata, deep learning, classification.

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Authors: Che Z. Zulkifli, Nursyahida M. Noor, Siti N. Semunab, Shafawati A. Malek

Abstract:

Wireless sensors, also known as wireless sensor nodes, have been making a significant impact on human daily life. The Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two complementary technologies; hence, an integrated implementation of these technologies expands the overall functionality in obtaining long-range and real-time information on the location and properties of objects and people. An approach for integrating ZigBee and RFID networks is proposed in this paper, to create an energy-efficient network improved by the benefits of combining ZigBee and RFID architecture. Furthermore, the compatibility and requirements of the ZigBee device and communication links in the typical RFID system which is presented with the real world experiment on the capabilities of the proposed RFID system.

Keywords: Mesh network, RFID, wireless sensor network, zigbee.

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Authors: Belabbas Yagoubi, Yahya Slimani

Abstract:

Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.

Keywords: Grid computing, load balancing, workload, tree based model.

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Authors: Mohamed Othmani, Yassine Khlifi

Abstract:

This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3D object, optimization, parametrization, Polywog wavelets, reconstruction, wavelet networks.

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Authors: Siripen Yiamjanya, Kevin Wongleedee

Abstract:

This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: Decision Making, Destination Choice, International Tourist, Pull Factor, Push Factor, Thailand, Travel Motivation.

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Authors: Yasser M. Abd El-Latif, Fatma S.Abousaleh, Daoud S. S.

Abstract:

L-system is a tool commonly used for modeling and simulating the growth of fractal plants. The aim of this paper is to join some problems of the computational geometry with the fractal geometry by using the L-system technique to generate fractal plant in 3D. L-system constructs the fractal structure by applying rewriting rules sequentially and this technique depends on recursion process with large number of iterations to get different shapes of 3D fractal plants. Instead, it was reiterated a specific number of iterations up to three iterations. The vertices generated from the last stage of the Lsystem rewriting process are used as input to the triangulation algorithm to construct the triangulation shape of these vertices. The resulting shapes can be used as covers for the architectural objects and in different computer graphics fields. The paper presents a gallery of triangulation forms which application in architecture creates an alternative for domes and other traditional types of roofs.

Keywords: Computational geometry, fractal geometry, L-system, triangulation.

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Authors: Avadhesh Yadav, V.K. Bajpai

Abstract:

A solar powered air heating system using one ended evacuated tubes is experimentally investigated. A solar air heater containing forty evacuated tubes is used for heating purpose. The collector surface area is about 4.44 m2. The length and outer diameters of the outer glass tube and absorber tube are 1500, 47 and 37 mm, respectively. In this experimental setup, we have a header (heat exchanger) of square shape (190 mm x 190 mm). The length of header is 1500 mm. The header consists of a hollow pipe in the center whose diameter is 60 mm through which the air is made to flow. The experimental setup contains approximately 108 liters of water. Water is working as heat collecting medium which collects the solar heat falling on the tubes. This heat is delivered to the air flowing through the header pipe. This heat flow is due to natural convection and conduction. The outlet air temperature depends upon several factors along with air flow rate and solar radiation intensity. The study has been done for both up-flow and down-flow of air in header in similar weather conditions, at different flow rates. In the present investigations the study has been made to find the effect of intensity of solar radiations and flow rate of air on the out let temperature of the air with time and which flow is more efficient. The obtained results show that the system is highly effective for the heating in this region. Moreover, it has been observed that system is highly efficient for the particular flow rate of air. It was also observed that downflow configuration is more effective than up-flow condition at all flow rates due to lesser losses in down-flow. The results show that temperature differences of upper head and lower head, both of water and surface of pipes on the respective ends is lower in down-flow.

Keywords: air flow direction, Evacuated tube solar collector, solar air heating, solar thermal utilization.

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Authors: Jagmohan Mago, Parvinder S. Sandhu, Neeru Chawla

Abstract:

In this paper, a Bayesian Network (BN) based system is presented for providing clinical decision support to healthcare practitioners in rural or remote areas of India for young infants or children up to the age of 5 years. The government is unable to appoint child specialists in rural areas because of inadequate number of available pediatricians. It leads to a high Infant Mortality Rate (IMR). In such a scenario, Intelligent Pediatric System provides a realistic solution. The prototype of an intelligent system has been developed that involves a knowledge component called an Intelligent Pediatric Assistant (IPA); and User Agents (UA) along with their Graphical User Interfaces (GUI). The GUI of UA provides the interface to the healthcare practitioner for submitting sign-symptoms and displaying the expert opinion as suggested by IPA. Depending upon the observations, the IPA decides the diagnosis and the treatment plan. The UA and IPA form client-server architecture for knowledge sharing.

Keywords: Network, Based Intelligent, Pediatric System

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