Search results for: model base testing

Authors: A. Ourici

Abstract:

Rapid progress in process automation and tightening quality standards result in a growing demand being placed on fault detection and diagnostics methods to provide both speed and reliability of motor quality testing. Doubly fed induction generators are used mainly for wind energy conversion in MW power plants. This paper presents a detection of an inter turn stator and an open phase faults, in a doubly fed induction machine whose stator and rotor are supplied by two pulse width modulation (PWM) inverters. The method used in this article to detect these faults, is based on Park-s Vector Approach, using a neural network.

Keywords: Doubly fed induction machine, inter turn stator fault, neural network, open phase fault, Park's vector approach, PWMinverter.

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Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang

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A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.

Keywords: Computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, wave energy converter.

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Authors: Kuo-Lung Lor, Chi-Hsuan Tsou, Yeun-Chung Chang, Chung-Ming Chen

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For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.

Keywords: active contour model, airway wall, COPD, geometric spring structure

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Authors: K. Y. Tseng, C. Y. Wu

Abstract:

This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.

Keywords: Differential evolution, truss structure optimization, optimal chiller loading, modified binary differential evolution.

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Authors: Geon-Woo Kim, Do-Woo Kim, Jun-Ho Lee, Jin-Beon Hwang, Jong-Wook Han

Abstract:

As various mobile sensing technologies, remote control and ubiquitous infrastructure are developing and expectations on quality of life are increasing, a lot of researches and developments on home network technologies and services are actively on going, Until now, we have focused on how to provide users with high-level home network services, while not many researches on home network security for guaranteeing safety are progressing. So, in this paper, we propose an access control model specific to home network that provides various kinds of users with home network services up one-s characteristics and features, and protects home network systems from illegal/unnecessary accesses or intrusions.

Keywords: Home network security, RBAC, access control, authentication.

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Authors: Amit Gil, Helman Stern, Yael Edan

Abstract:

A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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Authors: Morten Brøgger, Kim Wittchen

Abstract:

Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.

Keywords: Building stock energy modelling, energy-savings, archetype.

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Authors: Farouq Twaiq, Mustafa Nasser, Siham Al-Hajri, Mansoor Al-Hasani

Abstract:

Adsorption of methanol and ethanol over mesoporous siliceous material are studied in the current paper. The pure mesoporous silica is prepared using tetraethylorthosilicate (TEOS) as silica source and dodecylamine as template at low pH. The prepared material was characterized using nitrogen adsorption,nX-ray diffraction (XRD) and scanning electron microscopy (SEM). The adsorption kinetics of methanol and ethanol from aqueous solution were studied over the prepared mesoporous silica material. The percent removal of alcohol was calculated per unit mass of adsorbent used. The 1st order model is found to be in agreement with both adsorbates while the 2nd order model fit the adsorption of methanol only.

Keywords: Adsorption, Kinetics, Mesoprous silica, Methanol

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Authors: Buket Metin

Abstract:

Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: Construction process, construction technology, decision making, environmental performance, subcontractors.

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Authors: Yin Runmin, Song Changfeng

Abstract:

Image-based Rendering(IBR) techniques recently reached in broad fields which leads to a critical challenge to build up IBR-Driven visualization platform where meets requirement of high performance, large bounds of distributed visualization resource aggregation and concentration, multiple operators deploying and CSCW design employing. This paper presents an unique IBR-based visualization dataflow model refer to specific characters of IBR techniques and then discusses prominent feature of IBR-Driven distributed collaborative visualization (DCV) system before finally proposing an novel prototype. The prototype provides a well-defined three level modules especially work as Central Visualization Server, Local Proxy Server and Visualization Aid Environment, by which data and control for collaboration move through them followed the previous dataflow model. With aid of this triple hierarchy architecture of that, IBR oriented application construction turns to be easy. The employed augmented collaboration strategy not only achieve convenient multiple users synchronous control and stable processing management, but also is extendable and scalable.

Keywords: Image-Based Rendering, Distributed CollaborativeVisualization, Computer Supported Cooperative Work, Model andSimulation, Modular Visualization Environment.

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Authors: A. Magesh, B. Preetha, T. Viruthagiri

Abstract:

Direct fermentation of 226 white rose tapioca stem to ethanol by Fusarium oxysporum was studied in a batch reactor. Fermentation of ethanol can be achieved by sequential pretreatment using dilute acid and dilute alkali solutions using 100 mesh tapioca stem particles. The quantitative effects of substrate concentration, pH and temperature on ethanol concentration were optimized using a full factorial central composite design experiment. The optimum process conditions were then obtained using response surface methodology. The quadratic model indicated that substrate concentration of 33g/l, pH 5.52 and a temperature of 30.13oC were found to be optimum for maximum ethanol concentration of 8.64g/l. The predicted optimum process conditions obtained using response surface methodology was verified through confirmatory experiments. Leudeking-piret model was used to study the product formation kinetics for the production of ethanol and the model parameters were evaluated using experimental data.

Keywords: Fusarium oxysporum, Lignocellulosic biomass, Product formation kinetics, Statistical experimental design

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Authors: Nurul Bahiyah Ahmad Khairudin, Habibah A Wahab

Abstract:

A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.

Keywords: 3D model, Chicken villin headpiece subdomain, Molecular dynamic simulation NMR-MDavg, RMSD.

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Authors: T. Thompson, E. F. Zegeye

Abstract:

Bacterial Cellulose (BC) is a structural organic compound produced in the anaerobic process. This material can be a useful eco-friendly substitute for commercial textiles that are used in industries today. BC is easily and sustainably produced and has the capabilities to be used as a replacement in textiles. However, BC is extremely fragile when it completely dries. This research was conducted to improve the mechanical properties of the BC by reinforcing with an organic polymer and exfoliated graphite (EG). The BC films were grown over a period of weeks in a green tea and kombucha solution at 30 °C, then cleaned and added to an enhancing solution. The enhancing solutions were a mixture of 2.5 wt% polymer and 2.5 wt% latex solution, a 5 wt% polymer solution, a 0.20 wt% graphite solution and were each allowed to sit in a furnace for 48 h at 50 °C. Tensile test samples were prepared and tested until fracture at a strain rate of 8 mm/min. From the research with the addition of a 5 wt% polymer solution, the flexibility of the BC has significantly improved with the maximum strain significantly larger than that of the base sample. The addition of EG has also increased the modulus of elasticity of the BC by about 25%.

Keywords: Bacterial cellulose, exfoliated graphite, kombucha scoby, tensile test.

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Authors: A. Pérard Lecomte, G. Fokoua, A. Mehel, A. Tanière

Abstract:

Automotive experimental measurements in wind tunnel are often conducted on reduced scale. Depending on the study, different similitude parameters are used by researchers to best reproduce the flow at full scale. In this paper, two parameters are investigated, which are Reynolds number and upstream velocity when dealing with airflow of typical urban speed range, below 15 m.s-1. Their impact on flow structures and aerodynamic drag in the wake of a heavy truck model are explored. To achieve this, Computational Fluid Dynamics (CFD) simulations have been conducted with the aim of modeling the wake airflow of full- and reduced-scaled heavy trucks (1/4 and 1/28). The Reynolds Average Navier-Stokes (RANS) approach combined to the Reynolds Stress Model (RSM) as the turbulence model closure was used. Both drag coefficients and upstream velocity profiles (flow topology) were found to be close one another for the three investigated scales, when the dynamical similitude Reynolds is achieved. Moreover, the difference is weak for the simulations based on the same inlet air velocity. Hence, for the relative low velocity range investigated here, the impact of the scale factor is limited.

Keywords: Aerodynamics, CFD, heavy truck, recirculation area, scale effects, similitude parameters.

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Authors: Martin Cermak, Stanislav Sysala

Abstract:

In this paper we present the efficient parallel implementation of elastoplastic problems based on the TFETI (Total Finite Element Tearing and Interconnecting) domain decomposition method. This approach allow us to use parallel solution and compute this nonlinear problem on the supercomputers and decrease the solution time and compute problems with millions of DOFs. In our approach we consider an associated elastoplastic model with the von Mises plastic criterion and the combination of linear isotropic-kinematic hardening law. This model is discretized by the implicit Euler method in time and by the finite element method in space. We consider the system of nonlinear equations with a strongly semismooth and strongly monotone operator. The semismooth Newton method is applied to solve this nonlinear system. Corresponding linearized problems arising in the Newton iterations are solved in parallel by the above mentioned TFETI. The implementation of this problem is realized in our in-house MatSol packages developed in MatLab.

Keywords: Isotropic-kinematic hardening, TFETI, domain decomposition, parallel solution.

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Authors: Ahmed Mahmoudi, Imen Mejri, Mohamed A. Abbassi, Ahmed Omri

Abstract:

A numerical study based on the Lattice Boltzmann Method (LBM) is proposed to solve one, two and three dimensional heat and mass transfer for isothermal carbonization of thick wood particles. To check the validity of the proposed model, computational results have been compared with the published data and a good agreement is obtained. Then, the model is used to study the effect of reactor temperature and thermal boundary conditions, on the evolution of the local temperature and the mass distributions of the wood particle during carbonization

Keywords: Lattice Boltzmann Method, pyrolysis conduction, carbonization, Heat and mass transfer.

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Authors: F. Ardestani, S. S. A. Fatemi, B. Yakhchali

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Mycophenolic acid (MPA) is a secondary metabolite produced by Penicillium brevicompactum, which has antibiotic and immunosuppressive properties. In this study, the first, mycophenolic acid was produced in a fermentation process by Penicillium brevicompactum MUCL 19011 in shake flask using a base medium. The maximum MPA production, product yield and productivity of process were 1.379 g/L, 18.6 mg/g glucose and 4.9 mg/L. h, respectively. Also the glucose consumption, biomass and MPA production profiles were investigated during batch cultivation. Obtained results showed that MPA production starts approximately after 180 hours and reaches to a maximum at 280 h. In the next step, the effects of some various concentrations of enzymatically hydrolyzed casein on MPA production were evaluated. Maximum MPA production, product yield and productivity as 3.63 g/L, 49 mg/g glucose and 12.96 mg/L.h, respectively were obtained with using 30 g/L enzymatically hydrolyzed casein in culture medium. These values show an enhanced MPA production, product yield and process productivity pr as 116.8%, 132.8% and 163.2%, respectively.

Keywords: Penicillium brevicompactum, Enzymatically hydrolyzed casein, Mycophenolic acid, Submerged culture

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Authors: Jiajun Wang, Xiaoge Li

Abstract:

The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose an aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: Aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree.

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Authors: Gholamreza Zahedi, M. Tarin, M. Biglari

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This work investigated the steady state and dynamic simulation of a fixed bed industrial naphtha reforming reactors. The performance of the reactor was investigated using a heterogeneous model. For process simulation, the differential equations are solved using the 4th order Runge-Kutta method .The models were validated against measured process data of an existing naphtha reforming plant. The results of simulation in terms of components yields and temperature of the outlet were in good agreement with empirical data. The simple model displays a useful tool for dynamic simulation, optimization and control of naphtha reforming.

Keywords: Dynamic simulation, fixed bed reactor, modeling, reforming

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Authors: Rajib Ul Alam Uzzal, Ion Stiharu, Waiz Ahmed

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This paper presents the modeling of a MEMS based accelerometer in order to detect the presence of a wheel flat in the railway vehicle. A haversine wheel flat is assigned to one wheel of a 5 DOF pitch plane vehicle model, which is coupled to a 3 layer track model. Based on the simulated acceleration response obtained from the vehicle-track model, an accelerometer is designed that meets all the requirements to detect the presence of a wheel flat. The proposed accelerometer can survive in a dynamic shocking environment with acceleration up to ±150g. The parameters of the accelerometer are calculated in order to achieve the required specifications using lumped element approximation and the results are used for initial design layout. A finite element analysis code (COMSOL) is used to perform simulations of the accelerometer under various operating conditions and to determine the optimum configuration. The simulated results are found within about 2% of the calculated values, which indicates the validity of lumped element approach. The stability of the accelerometer is also determined in the desired range of operation including the condition under shock.

Keywords: MEMS accelerometer, Pitch plane vehicle, wheel flat.

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Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

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There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: Face recognition, Labeled Faces in the Wild (LFW) database, Random Local Descriptor (RLD), random features.

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Authors: Costin Badica, Maria Ganzha, Maciej Gawinecki, Pawel Kobzdej, Marcin Paprzycki

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Recently, we have presented an initial implementation of a model agent-based e-commerce system, which utilized a simple price negotiation mechanism–English Auction. In this note we discuss how a Dutch Auction involving multiple units of a product can be included in our system. We present UML diagrams of agents involved in price negotiations and briefly discuss rule-based mechanism exemplifying Dutch Auction.

Keywords: e-commerce, rule-based price negotiation mechanism, Dutch Auction, agent system.

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Authors: Anuj K. Sharma, Amit Sharma, Kulbhushan Agnihotri

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In this work, we propose and analyze a model of Phytoplankton-Zooplankton interaction with harvesting considering that some species are exploited commercially for food. Criteria for local stability, instability and global stability are derived and some threshold harvesting levels are explored to maintain the population at an appropriate equilibrium level even if the species are exploited continuously.Further,biological and bionomic equilibria of the system are obtained and an optimal harvesting policy is also analysed using the Pantryagin’s Maximum Principle.Finally analytical findings are also supported by some numerical simulations.

Keywords: Phytoplankton-Zooplankton, Global stability, Bionomic Equilibrium, Pontrying-Maximum Principal.

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Authors: Manouchehre Ansari, Mahmoud Dehghan Nayeri, Reza Yousefi Zenouz

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In order to develop any strategy, it is essential to first identify opportunities, threats, weak and strong points. Assessment of technology level provides the possibility of concentrating on weak and strong points. The results of technology assessment have a direct effect on decision making process in the field of technology transfer or expansion of internal research capabilities so it has a critical role in technology management. This paper presents a conceptual model to analyze the technology capability of a company as a whole and in four main aspects of technology. This model was tested on 10 automotive parts manufacturers in IRAN. Using this model, capability level of manufacturers was investigated in four fields of managing aspects, hard aspects, human aspects, and information and knowledge aspects. Results show that these firms concentrate on hard aspect of technology while others aspects are poor and need to be supported more. So this industry should develop other aspects of technology as well as hard aspect to have effective and efficient use of its technology. These paper findings are useful for the technology planning and management in automotive part manufactures in IRAN and other Industries which are technology followers and transport their needed technologies.

Keywords: Technology, Technological evaluation, TechnologyMaturity

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Authors: Rajoo Balaji, Omar Yaakob

Abstract:

The Ballast Water Convention requires less than 5% of the world tonnage for ratification. Consequently, ships will have to comply with the requirements. Compliance evaluation and enforcement will become mandatory. Ship owners have to invest in treatment systems and shipboard personnel have to operate them and ensure compliance. The monitoring and enforcement will be the responsibilities of the Administrations. Herein, a review of the current status of the Ballast Water Management and the issues faced by these are projected. Issues range from efficacy and economics of the treatment systems to sampling and testing. Health issues of chemical systems, paucity of data for decision support etc., are other issues. It is emphasized that management of ballast water must be extended to ashore and sustainable solutions must be researched upon. An exemplar treatment system based on ship’s waste heat is also suggested.

Keywords: Ballast water management, Compliance evaluation, Compliance enforcement, Sustainability.

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Authors: Barry Ardley, Abi Hunt, Nick Taylor

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As a theoretical and practical framework this study uses the student as producer approach to learning in higher education, as adopted by the Lincoln International Business School, University of Lincoln, UK. Student as producer positions learners as skilled and capable agents, able to participate as partners with tutors in live research projects. To illuminate the nature of this approach to learning and to highlight its critical issues, the authors report on two guided student consultancy projects. These were set up with the assistance of two local organisations in the city of Lincoln UK. Using the student as producer model to deliver the projects enabled learners to acquire and develop a range of key skills and knowledge, not easily accessible in more traditional educational settings. This paper presents a systematic case study analysis of the eight organising principles of the student as producer model, as adopted by university tutors. The experience of tutors implementing student as producer suggests that the model can be widely applied to benefit not only the learning and teaching experiences of higher education students, and staff, but additionally, a university’s research programme and its community partners.

Keywords: Experiential learning, consultancy clients, student as producer.

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Authors: George Yungchih Wang

Abstract:

This paper argues that increased uncertainty, in certain situations, may actually encourage investment. Since earlier studies mostly base their arguments on the assumption of geometric Brownian motion, the study extends the assumption to alternative stochastic processes, such as mixed diffusion-jump, mean-reverting process, and jump amplitude process. A general approach of Monte Carlo simulation is developed to derive optimal investment trigger for the situation that the closed-form solution could not be readily obtained under the assumption of alternative process. The main finding is that the overall effect of uncertainty on investment is interpreted by the probability of investing, and the relationship appears to be an invested U-shaped curve between uncertainty and investment. The implication is that uncertainty does not always discourage investment even under several sources of uncertainty. Furthermore, high-risk projects are not always dominated by low-risk projects because the high-risk projects may have a positive realization effect on encouraging investment.

Keywords: real options, geometric Brownian motion, mixeddiffusion-jump process, mean- reverting process, jump amplitudeprocess

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Authors: Kavitha Thamadharan, Nurazean Maarop

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The implementation of e-assessment as tool to support the process of teaching and learning in university has become a popular technological means in universities. E-Assessment provides many advantages to the users especially the flexibility in teaching and learning. The e-assessment system has the capability to improve its quality of delivering education. However, there still exists a drawback in terms of security which limits the user acceptance of the online learning system. Even though there are studies providing solutions for identified security threats in e-learning usage, there is no particular model which addresses the factors that influences the acceptance of e-assessment system by lecturers from security perspective. The aim of this study is to explore security aspects of eassessment in regard to the acceptance of the technology. As a result a conceptual model of secure acceptance of e-assessment is proposed. Both human and security factors are considered in formulation of this conceptual model. In order to increase understanding of critical issues related to the subject of this study, interpretive approach involving convergent mixed method research method is proposed to be used to execute the research. This study will be useful in providing more insightful understanding regarding the factors that influence the user acceptance of e-assessment system from security perspective.

Keywords: Secure Technology Acceptance, E-Assessment Security, E-Assessment, Education Technology.

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Authors: Randy Gomez, Keisuke Nakamura, Kazuhiro Nakadai

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Distant-talking voice-based HCI system suffers from performance degradation due to mismatch between the acoustic speech (runtime) and the acoustic model (training). Mismatch is caused by the change in the power of the speech signal as observed at the microphones. This change is greatly influenced by the change in distance, affecting speech dynamics inside the room before reaching the microphones. Moreover, as the speech signal is reflected, its acoustical characteristic is also altered by the room properties. In general, power mismatch due to distance is a complex problem. This paper presents a novel approach in dealing with distance-induced mismatch by intelligently sensing instantaneous voice power variation and compensating model parameters. First, the distant-talking speech signal is processed through microphone array processing, and the corresponding distance information is extracted. Distance-sensitive Gaussian Mixture Models (GMMs), pre-trained to capture both speech power and room property are used to predict the optimal distance of the speech source. Consequently, pre-computed statistic priors corresponding to the optimal distance is selected to correct the statistics of the generic model which was frozen during training. Thus, model combinatorics are post-conditioned to match the power of instantaneous speech acoustics at runtime. This results to an improved likelihood in predicting the correct speech command at farther distances. We experiment using real data recorded inside two rooms. Experimental evaluation shows voice recognition performance using our method is more robust to the change in distance compared to the conventional approach. In our experiment, under the most acoustically challenging environment (i.e., Room 2: 2.5 meters), our method achieved 24.2% improvement in recognition performance against the best-performing conventional method.

Keywords: Human Machine Interaction, Human Computer Interaction, Voice Recognition, Acoustic Model Compensation, Acoustic Speech Enhancement.

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: Distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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