Search results for: Effective Electric Field and Effective Mobility Model.

Authors: Rana Khalid Naeem, Asif Mansoor

Abstract:

Periodicities in the environmetric time series can be idyllically assessed by utilizing periodic models. In this communication fugitive emission of gases from open sewer channel Lyari which follows periodic behaviour are approximated by employing periodic autoregressive model of order p. The orders of periodic model for each season are selected through the examination of periodic partial autocorrelation or information criteria. The parameters for the selected order of season are estimated individually for each emitted air toxin. Subsequently, adequacies of fitted models are established by examining the properties of the residual for each season. These models are beneficial for schemer and administrative bodies for the improvement of implemented policies to surmount future environmental problems.

Keywords: Exchange of Gases, Goodness of Fit, Open Sewer Channel, PAR(p) Models, Periodicities, Season Wise Models.

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Authors: Kai Jin, Hyder Abdul-Razzak, Yousri Elkassabgi, Hong Zhou, Aaron Herrera

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Six Sigma is a well known discipline that reduces variation using complex statistical tools and the DMAIC model. By integrating Goldratts-s Theory of Constraints, the Five Focusing Points and System Thinking tools, Six Sigma projects can be selected where it can cause more impact in the company. This research defines an integrated model of six sigma and constraint management that shows a step-by-step guide using the original methodologies from each discipline and is evaluated in a case study from the production line of a Automobile engine monoblock V8, resulting in an increase in the line capacity from 18.7 pieces per hour to 22.4 pieces per hour, a reduction of 60% of Work-In-Process and a variation decrease of 0.73%.

Keywords: Constraint Management, Manufacturing Process Improvement, Six Sigma, System Thinking.

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Authors: Namchul Do, Jihun Cho

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Modeling product configurations needs large amounts of knowledge about technical and marketing restrictions on the product. Previous attempts to automate product configurations concentrate on representations and management of the knowledge for specific domains in fixed and isolated computing environments. Since the knowledge about product configurations is subject to continuous change and hard to express, these attempts often failed to efficiently manage and exchange the knowledge in collaborative product development. In this paper, XML Topic Map (XTM) is introduced to represent and exchange the knowledge about product configurations in collaborative product development. A product configuration model based on XTM along with its merger and inference facilities enables configuration engineers in collaborative product development to manage and exchange their knowledge efficiently. A prototype implementation is also presented to demonstrate the proposed model can be applied to engineering information systems to exchange the product configuration knowledge.

Keywords: Knowledge exchange, product configurations, XML topic map.

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: Anomaly detection, digital twin, Generalised Additive Model, Power Consumption Model.

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Authors: Lucian Pîslaru-Dănescu, George-Claudiu Zărnescu, Laurențiu Constantin Lipan, Rareș-Andrei Chihaia

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In recent years, the utilization of supercapacitors for energy storage (ES) devices that are designed for energy harvesting (EH) applications has increased substantially. The use of supercapacitors as energy storage devices in hybrid energy harvesting systems allows the miniaturization of electronic structures for energy storage. This study is concerned with the concept of energy management capacitors – supercapacitors and the new electronic structures for energy storage used for energy harvesting devices. Supercapacitors are low-voltage devices, and electronic overvoltage protection is needed for powering the source. The power management device that uses these proposed new electronic structures for energy storage is better than conventional electronic structures used for this purpose, like rechargeable batteries, supercapacitors, and hybrid systems. A hybrid energy harvesting system with energy storage management is able to simultaneously use several energy sources with recovery from the environment. The power management device uses a summing electronic block to combine the electric power obtained from piezoelectric composite plates and from a photovoltaic conversion system. Also, an overvoltage protection circuit used as a voltage detector and an improved concept of charging supercapacitors is presented. The piezoelectric composite plates are realized only by pressing two printed circuit boards together without damaging or prestressing the piezoceramic elements. The photovoltaic conversion system has the advantage that the modules are covered with glass plates with nanostructured film of ZnO with the role of anti-reflective coating and to improve the overall efficiency of the solar panels.

Keywords: Supercapacitors, energy storage, electronic overvoltage protection, energy harvesting.

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Authors: Chansheng He, Carlo DeMarchi

Abstract:

A physically based, spatially-distributed water quality model is being developed to simulate spatial and temporal distributions of material transport in the Great Lakes Watersheds of the U.S. Multiple databases of meteorology, land use, topography, hydrography, soils, agricultural statistics, and water quality were used to estimate nonpoint source loading potential in the study watersheds. Animal manure production was computed from tabulations of animals by zip code area for the census years of 1987, 1992, 1997, and 2002. Relative chemical loadings for agricultural land use were calculated from fertilizer and pesticide estimates by crop for the same periods. Comparison of these estimates to the monitored total phosphorous load indicates that both point and nonpoint sources are major contributors to the total nutrient loads in the study watersheds, with nonpoint sources being the largest contributor, particularly in the rural watersheds. These estimates are used as the input to the distributed water quality model for simulating pollutant transport through surface and subsurface processes to Great Lakes waters. Visualization and GIS interfaces are developed to visualize the spatial and temporal distribution of the pollutant transport in support of water management programs.

Keywords: Distributed Large Basin Runoff Model, Great LakesWatersheds, nonpoint source pollution, and point sources.

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: State estimation, fluid systems, observer systems, unscented Kalman filter.

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Authors: M. B. El_Mashade, I. I. Mahamoud, M. S. El_Tokhy

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Improving the performance of the QCL through block diagram as well as mathematical models is the main scope of this paper. In order to enhance the performance of the underlined device, the mathematical model parameters are used in a reliable manner in such a way that the optimum behavior was achieved. These parameters play the central role in specifying the optical characteristics of the considered laser source. Moreover, it is important to have a large amount of radiated power, where increasing the amount of radiated power represents the main hopping process that can be predicted from the behavior of quantum laser devices. It was found that there is a good agreement between the calculated values from our mathematical model and those obtained with VisSim and experimental results. These demonstrate the strength of mplementation of both mathematical and block diagram models.

Keywords: Quantum Cascaded Lasers (QCLs), Modeling, Block Diagram Programming, Intersubband transitions

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Authors: Ibrahim Mnafeg, Azgal Abichou, Lotfi Beji

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Traditional mechanical control systems in thrust vectoring are efficient in rocket thrust guidance but their costs and their weights are excessive. The fluidic injection in the nozzle divergent constitutes an alternative procedure to achieve the goal. In this paper, we present a 3D analytical model for fluidic injection in a supersonic nozzle integrating an orifice. The fluidic vectoring uses a sonic secondary injection in the divergent. As a result, the flow and interaction between the main and secondary jet has built in order to express the pressure fields from which the forces and thrust vectoring are deduced. Under various separation criteria, the present analytical model results are compared with the existing numerical and experimental data from the literature.

Keywords: Flow separation, Fluidic thrust vectoring, Nozzle, Secondary jet, Shock wave.

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Authors: Jenny Paola Forero Pachón, Sonia Cristina Gamboa Sarmiento, Luis Carlos Gómez Flórez

Abstract:

The Colombian government has defined an e-government strategy to take advantage of Information Technologies (IT) in order to contribute to the building of a more efficient, transparent and participative State that provides better services to citizens and businesses. In this regard, the Justice sector is one of the government sectors where IT has generated more expectation considering that the country has a judicial processes backlog. This situation has led to the search for alternative forms of access to justice that speed up the process while providing a low cost for citizens. To this end, the Colombian government has authorized the use of Alternative Dispute Resolution methods (ADR), a remedy where disputes can be resolved more quickly compared to judicial processes while facilitating greater communication between the parties, without recourse to judicial authority. One of these methods is conciliation, which includes a special modality that takes advantage of IT for the development of itself known as virtual conciliation. With this option the conciliation is supported by information systems, applications or platforms and communications are provided through it. This paper evaluates the level of maturity in how the service of virtual conciliation is under the framework of this strategy. This evaluation is carried out considering Shahkooh's 5-phase model for e-government. As a result, it is evident that in the context of conciliation, maturity does not reach the necessary level in the model so that it can be considered as virtual conciliation; therefore, it is necessary to define strategies to maximize the potential of IT in this context.

Keywords: Alternative dispute resolution, e-government, evaluation of maturity, Shahkooh model, virtual conciliation.

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Authors: Yiannis Smirlis, Dimitris K. Despotis

Abstract:

This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.

Keywords: Data envelopment analysis, Greek universities, operating expenditures, ordinal data.

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Authors: Amado, M. P., Amado, A., Poggi, F., Correia de Freitas, J.

Abstract:

Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.

In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.

Keywords: Solar urban planning, solar smart city, urban development, energy efficiency.

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Authors: Weihao Chung, Iau-Teh Wang, Yu-Hsi Hu

Abstract:

This is the second part of the paper. It, aside from the core subroutine test reported previously, focuses on the simulation of turbulence governed by the full STF Navier-Stokes equations on a large scale. Law of the wall is found plausible in this study as a model of the boundary layer dynamics. Model validations proceed to include velocity profiles of a stationary turbulent Couette flow, pure sloshing flow simulations, and the identification of water-surface inclination due to fluid accelerations. Errors resulting from the irrotational and hydrostatic assumptions are explored when studying a wind-driven water circulation with no shakings. Illustrative examples show that this numerical strategy works for the simulation of sloshing-shear mixed flow in a 3-D rigid rectangular base tank.

Keywords: potential flow theory, sloshing flow, space-timefiltering, order of accuracy.

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Authors: Y. Kerboua Ziari, M. Benouahlima, A. Benzaoui

Abstract:

We are interested in this paper to the thermal effects occurring during the filling of hydrogen tanks. The consequence of this heating on the storage performance of these speakers was appreciated. The motivation comes from the fact that the development of hydrogen as an energy carrier of the future will require strong evolution in the field of storage modes to smaller, less expensive lighter, with a strong security interest and considerable autonomy.

Keywords: Hydrogen, Fuel, Storage, Energy, Modeling, Simulation.

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Authors: Manish K. Khandelwal, P. Bera, A. Chakrabarti

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This article presents a numerical study of the doublediffusive mixed convection in a vertical channel filled with porous medium by using non-equilibrium model. The flow is assumed fully developed, uni-directional and steady state. The controlling parameters are thermal Rayleigh number (RaT ), Darcy number (Da), Forchheimer number (F), buoyancy ratio (N), inter phase heat transfer coefficient (H), and porosity scaled thermal conductivity ratio (γ). The Brinkman-extended non-Darcy model is considered. The governing equations are solved by spectral collocation method. The main emphasize is given on flow profiles as well as heat and solute transfer rates, when two diffusive components in terms of buoyancy ratio are in favor (against) of each other and solid matrix and fluid are thermally non-equilibrium. The results show that, for aiding flow (RaT = 1000), the heat transfer rate of fluid (Nuf ) increases upto a certain value of H, beyond that decreases smoothly and converges to a constant, whereas in case of opposing flow (RaT = -1000), the result is same for N = 0 and 1. The variation of Nuf in (N, Nuf )-plane shows sinusoidal pattern for RaT = -1000. For both cases (aiding and opposing) the flow destabilize on increasing N by inviting point of inflection or flow separation on the velocity profile. Overall, the buoyancy force have significant impact on the non-Darcy mixed convection under LTNE conditions.

Keywords: buoyancy ratio, mixed convection, non-Darcy model, thermal non-equilibrium

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Authors: Jesus Orbe, Vicente Nunez-Anton

Abstract:

In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.

Keywords: Censored response variable, regression, bias.

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Authors: Eleftherios Giovanis

Abstract:

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.

Keywords: ANFIS, discrete choice models, financial crisis, USeconomy

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Authors: Hun Go, Ji-Su Kim, Dong-Ho Lee

Abstract:

This study considers the problem of determining operation and maintenance schedules for a containership equipped with components during its sailing according to a pre-determined navigation schedule. The operation schedule, which specifies work time of each component, determines the due-date of each maintenance activity, and the maintenance schedule specifies the actual start time of each maintenance activity. The main constraints are component requirements, workforce availability, working time limitation, and inter-maintenance time. To represent the problem mathematically, a mixed integer programming model is developed. Then, due to the problem complexity, we suggest a heuristic for the objective of minimizing the sum of earliness and tardiness between the due-date and the starting time of each maintenance activity. Computational experiments were done on various test instances and the results are reported.

Keywords: Containerships, operation and preventive maintenance schedules, integer programming, heuristic

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Authors: W. Hou, X. Shan, X. Ye

Abstract:

Bidding is a very important business function to find latent contractors of construction projects. Moreover, bid markup is one of the most important decisions for a bidder to gain a reasonable profit. Since the bidding system is a complex adaptive system, bidding agent need a learning process to get more valuable knowledge for a bid, especially from past public bidding information. In this paper, we proposed an iterative agent leaning model for bidders to make markup decisions. A classifier for public bidding information named PIBS is developed to make full use of history data for classifying new bidding information. The simulation and experimental study is performed to show the validity of the proposed classifier. Some factors that affect the validity of PIBS are also analyzed at the end of this work.

Keywords: bidding markup, decision making, agent learning, information similarity.

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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Authors: S. Rajabi, M. ArdebiliPoor, M. Shahabadi

Abstract:

In this paper we propose a method for modeling the correlation between the received signals by two or more antennas operating in a multipath environment. Considering the maximum excess delay in the channel being modeled, an elliptical region surrounding both transmitter and receiver antennas is produced. A number of scatterers are randomly distributed in this region and scatter the incoming waves. The amplitude and phase of incoming waves are computed and used to obtain statistical properties of the received signals. This model has the distinguishable advantage of being applicable for any configuration of antennas. Furthermore the common PDF (Probability Distribution Function) of received wave amplitudes for any pair of antennas can be calculated and used to produce statistical parameters of received signals.

Keywords: MIMO (Multiple Input Multiple Output), SIMO (Single Input Multiple Output), GBSBEM (Geometrically Based Single Bounce Elliptical Model).

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Authors: Hsin-Yun Lee, Hao-Hsi Tseng

Abstract:

Previous studies mass evacuation route network does not fully reflect the step-by-step behavior and evacuees make routing decisions. Therefore, they do not work as expected when applied to the evacuation route planning is valid. This article describes where evacuees may have to make a direction to select all areas were identified as guiding points to improve evacuation routes network. This improved route network can be used as a basis for the layout can be used to guide the signs indicate that provides the required evacuation direction. This article also describes that combines simulation and artificial bee colony algorithm to provide the proposed routing solutions, to plan an integrated routing mode. The improved network and the model used is the cinema as a case study to assess the floor. The effectiveness of guidance solution in the total evacuation time is significant by verification.

Keywords: Artificial bee colony, Evacuation, Simulation.

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Authors: Habibi Said Mustafa, Hiroko Ono

Abstract:

Since 2006, Afghanistan is dealing with one of the most dramatic trend of urban movement in its history, cities and towns are expanding in size and number. Kabul is the capital of Afghanistan and as well as the fast-growing city in the Asia. The influx of the returnees from neighbor countries and other provinces of Afghanistan caused high rate of artificial growth which slums increased. As an unwanted consequence of this growth, today informal settlements have covered a vast portion of the city. Land Readjustment (LR) has proved to be an important tool for developing informal settlements and reorganizing urban areas but its implementation always varies from country to country and region to region within the countries. Consequently, to successfully develop the informal settlements in Kabul, we need to define an Afghan model of LR specifically for Afghanistan which needs to incorporate all those factors related to the socio-economic condition of the country. For this purpose, a part of the old city of Kabul has selected as a study area which is located near the Central Business District (CBD). After the further analysis and incorporating all needed factors, the result shows a positive potential for the implementation of an adaptable Land Readjustment model for Kabul city which is more sustainable and socio-economically friendly. It will enhance quality of life and provide better urban services for the residents. Moreover, it will set a vision and criteria by which sustainable developments shall proceed in other similar informal settlements of Kabul.

Keywords: Adaptation, informal settlements, Kabul, land readjustment, preservation.

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Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

Abstract:

Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: Force variations, linear direct drive, modeling and system identification, variable excitation flux.

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Authors: José M. Merigó, Montserrat Casanovas

Abstract:

We analyze the problem of decision making under ignorance with regrets. Recently, Yager has developed a new method for decision making where instead of using regrets he uses another type of transformation called negrets. Basically, the negret is considered as the dual of the regret. We study this problem in detail and we suggest the use of geometric aggregation operators in this method. For doing this, we develop a different method for constructing the negret matrix where all the values are positive. The main result obtained is that now the model is able to deal with negative numbers because of the transformation done in the negret matrix. We further extent these results to another model developed also by Yager about mixing valuations and negrets. Unfortunately, in this case we are not able to deal with negative numbers because the valuations can be either positive or negative.

Keywords: Decision Making, Aggregation operators, Negret, OWA operator, OWG operator.

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Authors: Shigeaki Sakurai, Ryohei Orihara

Abstract:

This paper proposes an improvement method of classification efficiency in a classification model. The model is used in a risk search system and extracts specific labels from articles posted at bulletin board sites. The system can analyze the important discussions composed of the articles. The improvement method introduces ensemble learning methods that use multiple classification models. Also, it introduces expressions related to the specific labels into generation of word vectors. The paper applies the improvement method to articles collected from three bulletin board sites selected by users and verifies the effectiveness of the improvement method.

Keywords: Text mining, Risk search system, Corporate reputation, Bulletin board site, Ensemble learning

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Authors: Mohamed Abdelwahed

Abstract:

The aeration process via injectors is used to combat the lack of oxygen in lakes due to eutrophication. A 3D numerical simulation of the resulting flow using a simplified model is presented. In order to generate the best dynamic in the fluid with respect to the aeration purpose, the optimization of the injectors location is considered. We propose to adapt to this problem the topological sensitivity analysis method which gives the variation of a criterion with respect to the creation of a small hole in the domain. The main idea is to derive the topological sensitivity analysis of the physical model with respect to the insertion of an injector in the fluid flow domain. We propose in this work a topological optimization algorithm based on the studied asymptotic expansion. Finally we present some numerical results, showing the efficiency of our approach

Keywords: Quasi Stokes equations, Numerical simulation, topological optimization, sensitivity analysis.

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Authors: Jiqing Han, Rongchun Gao

Abstract:

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Keywords: Channel Compensation, Channel Robustness, MAP, Speaker Identification

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Authors: Mikhail P. Strongin, Ragupathi Soundararajan

Abstract:

The purpose of this work is fast design optimization of the seal chamber. The study includes the mass transfer between lower and upper chamber on seal chamber for hot water application pumps. The use of Fluent 12.1 commercial code made it possible to capture complex flow with heat-mass transfer, radiation, Tailor instability, and buoyancy effect. Realizable k-epsilon model was used for turbulence modeling. Radiation heat losses were taken into account. The temperature distribution at seal region is predicted with respect to heat addition. Results show the possibilities of the model simplifications by excluding the water domain in low chamber from calculations. CFD simulations permit to improve seal chamber design to meet target water temperature around the seal. This study can be used for the analysis of different seal chamber configurations.

Keywords: CFD, heat transfer, seal chamber, high temperature water

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

Abstract:

In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: Image processing, Illumination equalization, Shadow filtering, Object detection, Colour models, Image segmentation.

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