Search results for: marketing constraints

Authors: Pui-Lai To, E-Ping Sung

Abstract:

The purpose of this study is to investigate hedonic online shopping motivations. A qualitative analysis was conducted to explore the factors influencing online hedonic shopping motivations. The results of the study indicate that traditional hedonic values, consisting of social, role, self-gratification, learning trends, pleasure of bargaining, stimulation, diversion, status, and adventure, and dimensions of flow theory, consisting of control, curiosity, enjoyment, and telepresence, exist in the online shopping environment. Two hedonic motivations unique to Internet shopping, privacy and online shopping achievement, were found. It appears that the most important hedonic value to online shoppers is having the choice to interact or not interact with others while shopping on the Internet. This study serves as a basis for the future growth of Internet marketing.

Keywords: Internet Shopping, Shopping Motivation, Hedonic Motivation.

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Authors: Carlos J. Costa, Manuela Aparício

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In this paper, we present the information life cycle, and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here does not correspond just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle employed in other contexts like manufacturing or marketing. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise, and in a manufacturing enterprise.

Keywords: Information systems/technology, informatio nsystems life cycle, organization engineering, information economics.

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Authors: K. C. Meher, R. K. Swain, C. K. Chanda

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This paper gives an intuition regarding glowworm swarm optimization (GSO) technique to solve dynamic economic dispatch (DED) problems of thermal generating units. The objective of the problem is to schedule optimal power generation of dedicated thermal units over a specific time band. In this study, Glowworm swarm optimization technique enables a swarm of agents to split into subgroup, exhibit simultaneous taxis towards each other and rendezvous at multiple optima (not necessarily equal) of a given multimodal function. The feasibility of the GSO method has been tested on ten-unit-test systems where the power balance constraints, operating limits, valve point effects, and ramp rate limits are taken into account. The results obtained by the proposed technique are compared with other heuristic techniques. The results show that GSO technique is capable of producing better results.

Keywords: Dynamic economic dispatch, Glowworm swarm optimization, Luciferin, Valve–point loading effect, Ramp rate limits.

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Authors: Jie Zhao, Meng Su

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Image recognition enables machine-like robotics to understand a scene and plays an important role in computer vision applications. Computer vision platforms as physical infrastructure, supporting Neural Networks for image recognition, are deterministic to leverage the performance of different Neural Networks. In this paper, three different computer vision platforms – edge AI (Jetson Nano, with 4GB), a standalone laptop (with RTX 3000s, using CUDA), and a web-based device (Google Colab, using GPU) are investigated. In the case study, four prominent neural network architectures (including AlexNet, VGG16, GoogleNet, and ResNet (34/50)), are deployed. By using public ImageNets (Cifar-10), our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: AlexNet, VGG, GoogleNet, ResNet, ImageNet, Cifar-10, Edge AI, Jetson Nano, CUDA, GPU.

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, M. E. S. Mvodo

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This study endeavors to evaluate the effects of farmers’ training program on the adoption of improved farming practices, the output of rice farming, and the income as well as the profit from rice farming by employing an ex-post non-experimental data in Sierra Leone. It was established that participating in farmers’ training program increased the possibility of adoption of the improved farming activities that were implemented in the study area. Through the training program also, the proceeds from rice production was also established to have increased considerably. These results were in line with the assumption that one of the main constraints on the growth in agricultural output particularly rice cultivation in most African states is the lack of efficient extension programs.

Keywords: Dissemination of information, improved farming practices, rice ecologies, Sierra Leone.

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Authors: Mohammed S. Al-Ansari

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This paper presents an analytical model to estimate the cost of an optimized design of reinforced concrete isolated footing base on structural safety. Flexural and optimized formulas for square and rectangular footingare derived base on ACI building code of design, material cost and optimization. The optimization constraints consist of upper and lower limits of depth and area of steel. Footing depth and area of reinforcing steel are to be minimized to yield the optimal footing dimensions. Optimized footing materials cost of concrete, reinforcing steel and formwork of the designed sections are computed. Total cost factor TCF and other cost factors are developed to generalize and simplify the calculations of footing material cost. Numerical examples are presented to illustrate the model capability of estimating the material cost of the footing for a desired axial load.

Keywords: Footing, Depth, Concrete, Steel, Formwork, Optimization, Material cost, Cost Factors.

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Authors: Seok-In Sohn, Dae-Hwan Park, Yeon-Seung Lee, Il-Kwon Oh

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This paper presents an optimization of the hull separation, i.e. transverse clearance. The main objective is to identify the feasible speed ranges and find the optimum transverse clearance considering the minimum wave-making resistance. The dimensions and the weight of hardware systems installed in the catamaran structured fuel cell powered USV (Unmanned Surface Vehicle) were considered as constraints. As the CAE (Computer Aided Engineering) platform FRIENDSHIP-Framework was used. The hull surface modeling, DoE (Design of Experiment), Tangent search optimization, tool integration and the process automation were performed by FRIENDSHIP-Framework. The hydrodynamic result was evaluated by XPAN the potential solver of SHIPFLOW.

Keywords: Full parametric modeling, Hull Separation, Wave-making resistance, Design Of Experiment, Tangent search method

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Authors: A. M. El Ansary, A. A. El Damatty, A. O. Nassef

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The aim of the current study is to develop a numerical tool that is capable of achieving an optimum shape and design of hyperbolic cooling towers based on coupling a non-linear finite element model developed in-house and a genetic algorithm optimization technique. The objective function is set to be the minimum weight of the tower. The geometric modeling of the tower is represented by means of B-spline curves. The finite element method is applied to model the elastic buckling behaviour of a tower subjected to wind pressure and dead load. The study is divided into two main parts. The first part investigates the optimum shape of the tower corresponding to minimum weight assuming constant thickness. The study is extended in the second part by introducing the shell thickness as one of the design variables in order to achieve an optimum shape and design. Design, functionality and practicality constraints are applied.

Keywords: B-splines, Cooling towers, Finite element, Genetic algorithm, Optimization

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network.

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Authors: Toru Murayama, Akinori Nagano, Zhi-Wei Luo

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In this research, we study a control method of a multivehicle system while considering the limitation of communication range for each vehicles. When we control networked vehicles with limitation of communication range, it is important to control the communication network structure of a multi-vehicle system in order to keep the network-s connectivity. From this, we especially aim to control the network structure to the target structure. We formulate the networked multi-vehicle system with some disturbance and the communication constraints as a hybrid dynamical system, and then we study the optimal control problems of the system. It is shown that the system converge to the objective network structure in finite time when the system is controlled by the receding horizon method. Additionally, the optimal control probrems are convertible into the mixed integer problems and these problems are solvable by some branch and bound algorithm.

Keywords: Hybrid system, multi-vehicle system, receding horizon control, topology control.

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Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

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This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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Authors: H. Shayeghi, M. Mahdavi

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Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.

Keywords: Adequacy Optimization, Transmission Expansion Planning, DCGA.

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Authors: Amir Lotfi, Seyed Hamid Hosseini

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During the recent past, due to the increase of electrical energy demand and governmental resources constraints in creating additional capacity in the generation, transmission, and distribution, privatization, and restructuring in electrical industry have been considered. So, in most of the countries, different parts of electrical industry like generation, transmission, and distribution have been separated in order to create competition. Considering these changes, environmental issues, energy growth, investment of private equity in energy generation units and difficulties of transmission lines expansion, distributed generation (DG) units have been used in power systems. Moreover, reduction in the need for transmission and distribution, the increase of reliability, improvement of power quality, and reduction of power loss have caused DG to be placed in power systems. On the other hand, considering low liquidity need, private investors tend to spend their money for DGs. In this project, the main goal is to offer an algorithm for planning and placing DGs in order to reduce the need for transmission and distribution network.

Keywords: Planning, transmission, distributed generation, power security, power systems.

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Authors: F. Amin, S. Feizi

Abstract:

Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: Big Data, Next Generation Networks, Network Transformation.

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Authors: Abdolali Mortazavi, Faegheh Taheran

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By giving an overview of previous arguments and findings concerned with the concept of competitive advantage, first, we define the overall concept of competitive advantage and discuss nuances of understanding such an important and strategic idea. Finally, by considering the major concerns of marketing academia, including globalization, Artificial Intelligence (AI)-based technologies, consumer well-being, and internal coopetition between a firm’s units, fruitful avenues to be explored by future studies are presented in the form of research propositions. In the end, relevant gaps mentioned by numerous studies that are worth investigating are demonstrated.

Keywords: Artificial Intelligence, competitive advantage, consumer well-being, coopetition, globalization, literature review, temporary competitive advantage.

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Authors: Amalia Suzianti

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This research elaborates decision models for product innovation in the early phases, focusing on one of the most widely implemented method in marketing research: conjoint analysis and the related conjoint-based models with special focus on heuristics programming techniques for the development of optimal product innovation. The concept, potential, requirements and limitations of conjoint analysis and its conjoint-based heuristics successors are analysed and the development of conceptual framework of Genetic Algorithm (GA) as one of the most widely implemented heuristic methods for developing product innovations are discussed.

Keywords: Product Innovation, Conjoint Analysis, Heuristic Model, Genetic Algorithm

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: Feature generation, feature learning, genetic algorithm, music information retrieval.

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Authors: Dimitrie Marinceu, Alan Murchison

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The Canadian Used Fuel Container (UFC) is a mid-size hemispherical headed copper coated steel container measuring 2.5 meters in length and 0.5 meters in diameter containing 48 used fuel bundles. The contained used fuel produces significant gamma radiation requiring automated assembly processes to complete the assembly. The design throughput of 2,500 UFCs per year places constraints on equipment and hot cell design for repeatability, speed of processing, robustness and recovery from upset conditions. After UFC assembly, the UFC is inserted into a Buffer Box (BB). The BB is made from adequately pre-shaped blocks (lower and upper block) and Highly Compacted Bentonite (HCB) material. The blocks are practically ‘sandwiching’ the UFC between them after assembly. This paper identifies one possible approach for the BB automatic assembly cell and processes. Automation of the BB assembly will have a significant positive impact on nuclear safety, quality, productivity, and reliability.

Keywords: Used fuel packing plant, automatic assembly cell, used fuel container, buffer box, deep geological repository.

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Authors: Kyaw Myo Lin, Pyone Lai Swe, Khine Zin Oo

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In this paper, an approach combining analytical method for the distributed generator (DG) sizing and meta-heuristic search for the optimal location of DG has been presented. The optimal size of DG on each bus is estimated by the loss sensitivity factor method while the optimal sites are determined by Particle Swarm Optimization (PSO) based optimal reactive power dispatch for minimizing active power loss. To confirm the proposed approach, it has been tested on IEEE-30 bus test system. The adjustments of operating constraints and voltage profile improvements have also been observed. The obtained results show that the allocation of DGs results in a significant loss reduction with good voltage profiles and the combined approach is competent in keeping the system voltages within the acceptable limits.

Keywords: Analytical approach, distributed generations, optimal size, optimal location, optimal reactive power dispatch, particle swarm optimization algorithm.

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Authors: Sahilu Wendeson Sahilu, Wan Fatimah Wan Ahmad, Nazleeni Samiha Haron

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Mobile learning (M-learning) integrates mobile devices and wireless computing technology to enhance the current conventional learning system. However, there are constraints which are affecting the implementation of platform and device independent M-learning. The main aim of this research is to fulfill the following main objectives: to develop platform independent mobile learning tool (M-LT) for structured programming course, and evaluate its effectiveness and usability using ADDIE instructional design model (ISD) as M-LT life cycle. J2ME (Java 2 micro edition) and XML (Extensible Markup Language) were used to develop platform independent M-LT. It has two modules lecture materials and quizzes. This study used Quasi experimental design to measure effectiveness of the tool. Meanwhile, questionnaire is used to evaluate the usability of the tool. Finally, the results show that the system was effective and also usability evaluation was positive.

Keywords: ADDIE, Conventional learning, ISD, J2ME, Mlearning, Quasi Experiment, Wireless Technology, XML

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Authors: Navid Mehdizadeh Afroozi, Khodakhast Isapour, Mojtaba Hakimzadeh, Abdolmohammad Davodi

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The objective of the Economic Dispatch(ED) Problems of electric power generation is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. This paper presents a new method of ED problems utilizing the Max-Min Ant System Optimization. Historically, traditional optimizations techniques have been used, such as linear and non-linear programming, but within the past decade the focus has shifted on the utilization of Evolutionary Algorithms, as an example Genetic Algorithms, Simulated Annealing and recently Ant Colony Optimization (ACO). In this paper we introduce the Max-Min Ant System based version of the Ant System. This algorithm encourages local searching around the best solution found in each iteration. To show its efficiency and effectiveness, the proposed Max-Min Ant System is applied to sample ED problems composed of 4 generators. Comparison to conventional genetic algorithms is presented.

Keywords: Economic Dispatch (ED), Ant Colony Optimization, Fuel Cost, Algorithm.

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Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

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Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: Adaptive housing, low-cost housing, overcrowding.

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Authors: A. Lovascio, A. D’Orazio, V. Centonze

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From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, small satellites, sub-sampling, TT&C.

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Authors: Marc C. Robini, Pierre-Jean Viverge, Yuemin Zhu, Jianhua Luo

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The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

Keywords:

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Authors: Vikas Pandey, T. L. Joshy, Vyshak Vijayan, N. Babu

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A new and cost effective robotic device was designed for remote tele surgery using dual tone multi frequency technology (DTMF). Tele system with Dual Tone Multiple Frequency has a large capability in sending and receiving of data in hardware and software. The robot consists of DC motors for arm movements and it is controlled manually through a mobile phone through DTMF Technology. The system enables the surgeon from base station to send commands through mobile phone to the patient’s robotic system which includes two robotic arms that translate the input into actual instrument manipulation. A mobile phone attached to the microcontroller 8051 which can activate robot through relays. The Remote robot-assisted tele surgery eliminates geographic constraints for getting surgical expertise where it is needed and allows an expert surgeon to teach or proctor the performance of surgical technique by real-time intervention.

Keywords: Robot, Microcontroller, DTMF, Tele surgery.

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Authors: Suselo Thomas, Suyoto, Dwiandiyanta B. Yudi

Abstract:

This paper explain about analysis and design a business directory for micro-scale businesses, small and medium enterprises (SMEs). Business Directory, if implemented will facilitate and optimize the access of SMEs to ease suppliers access to marketing. Business Directory will be equipped with the power of geocoding, so each location can be easily viewed SMEs on the map. The map will be constructed by using the functionality of a webbased Google Maps API. The information presented in the form of multimedia that can be more interesting and interactive. The method used to achieve the goal are: observation; interviews; modeling and classifying business directory for SMEs.

Keywords: Business directories, SMEs, Google maps API, multimedia, geocoding ommas.

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Authors: Katsunori Miura, Kiyoshi Akama, Hiroshi Mabuchi

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In the Equivalent Transformation (ET) computation model, a program is constructed by the successive accumulation of ET rules. A method by meta-computation by which a correct ET rule is generated has been proposed. Although the method covers a broad range in the generation of ET rules, all important ET rules are not necessarily generated. Generation of more ET rules can be achieved by supplementing generation methods which are specialized for important ET rules. A Specialization-by-Equation (Speq) rule is one of those important rules. A Speq rule describes a procedure in which two variables included in an atom conjunction are equalized due to predicate constraints. In this paper, we propose an algorithm that systematically and recursively generate Speq rules and discuss its effectiveness in the synthesis of ET programs. A Speq rule is generated based on proof of a logical formula consisting of given atom set and dis-equality. The proof is carried out by utilizing some ET rules and the ultimately obtained rules in generating Speq rules.

Keywords: Equivalent transformation, ET rule, Equation of two variables, Rule generation, Specialization-by-Equation rule

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Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: Customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine.

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Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

Abstract:

The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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Authors: Piyali Chaudhuri, Peter T. Martin, Aleksandar Z. Stevanovic, Chongkai Zhu

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Loop detectors report traffic characteristics in real time. They are at the core of traffic control process. Intuitively, one would expect that as density of detection increases, so would the quality of estimates derived from detector data. However, as detector deployment increases, the associated operating and maintenance cost increases. Thus, traffic agencies often need to decide where to add new detectors and which detectors should continue receiving maintenance, given their resource constraints. This paper evaluates the effect of detector spacing on freeway travel time estimation. A freeway section (Interstate-15) in Salt Lake City metropolitan region is examined. The research reveals that travel time accuracy does not necessarily deteriorate with increased detector spacing. Rather, the actual location of detectors has far greater influence on the quality of travel time estimates. The study presents an innovative computational approach that delivers optimal detector locations through a process that relies on Genetic Algorithm formulation.

Keywords: Detector, Freeway, Genetic algorithm, Travel timeestimate.

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