Search results for: practical problem.

Authors: Ratthapong Bunyanuwat

Abstract:

The purposes of this research were to study the citizen participation in preventing illegal drugs in one of a poor and small community of Bangkok, Thailand and to compare the level of participation and concern of illegal drugs problem by using demographic variables. This paper drew upon data collected from a local citizens survey conducted in Bangkok, Thailand during summer of 2012. A total of 200 respondents were elicited as data input for, and one way ANOVA test. The findings revealed that the overall citizen participation was in the level of medium. The mean score showed that benefit from the program was ranked as the highest and the decision to participate was ranked as second while the follow-up of the program was ranked as the lowest. In terms of the difference in demographic such as gender, age, level of education, income, and year of residency, the hypothesis testing’s result disclosed that there were no difference in their level of participation. However, difference in occupation showed a difference in their level of participation and concern which was significant at the 0.05 confidence level.

Keywords: Citizen Participation, Illegal drug, Preventing drug problem, Resolving drug problem

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Authors: Mauricio Otaíza Morales

Abstract:

This work shows a basic philosophical difficulty in the constructivist foundations of the cognitive posracionalist psychology of Vittorio Guidano. This is a difficulty caused by the problem of the existential crisis. It will be analyzed how Guidano-s suggestions about this problem depend on felt experience. Then it will appear how Guidano-s philosophy and psychotherapy must turn towards a phenomenological approach. Finally, some references are given about Eugen Gendlin-s philosophy which could be considered as a radical way to confront these questions.

Keywords: Cognitive posracionalist psychology of VittorioGuidano, Epistemological crisis, Existential crisis, Experience asdirectly felt.

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Authors: H. Shayeghi, M. Mahdavi, A. Kazemi

Abstract:

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, transmission expansion planning considering network adequacy restriction has not been investigated. Thus, in this paper, STNEP problem is being studied considering network adequacy restriction using discrete particle swarm optimization (DPSO) algorithm. The goal of this paper is obtaining a configuration for network expansion with lowest expansion cost and a specific adequacy. The proposed idea has been tested on the Garvers network and compared with the decimal codification genetic algorithm (DCGA). The results show that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is more than DCGA approach.

Keywords: DPSO algorithm, Adequacy restriction, STNEP.

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Authors: A. Schuchter, M. Promegger

Abstract:

The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: Flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Fábio A. S. Mota, Mauro A. S. S. Ravagnani, E. P. Carvalho

Abstract:

In the present paper the design of plate heat exchangers is formulated as an optimization problem considering two mathematical modelling. The number of plates is the objective function to be minimized, considering implicitly some parameters configuration. Screening is the optimization method used to solve the problem. Thermal and hydraulic constraints are verified, not viable solutions are discarded and the method searches for the convergence to the optimum, case it exists. A case study is presented to test the applicability of the developed algorithm. Results show coherency with the literature.

Keywords: Plate heat exchanger, optimization, modeling, simulation.

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Authors: Inaki Maulida Hakim, Alesandro Romero

Abstract:

This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck has efficiency with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost and increase the average of the truck efficiency per day.

Keywords: Logistic cost, milkrun, simulation, efficiency.

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Authors: Bashar Al-Shboul, Sung-Hyon Myaeng

Abstract:

K-Means (KM) is considered one of the major algorithms widely used in clustering. However, it still has some problems, and one of them is in its initialization step where it is normally done randomly. Another problem for KM is that it converges to local minima. Genetic algorithms are one of the evolutionary algorithms inspired from nature and utilized in the field of clustering. In this paper, we propose two algorithms to solve the initialization problem, Genetic Algorithm Initializes KM (GAIK) and KM Initializes Genetic Algorithm (KIGA). To show the effectiveness and efficiency of our algorithms, a comparative study was done among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA), and FCM [19].

Keywords: Clustering, Genetic Algorithms, K-means.

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Authors: Wissem Saidani, Yacine Morsly, Mohand Saïd Djouadi

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In this paper, we consider the problem of tracking multiple maneuvering targets using switching multiple target motion models. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the Extended Kalman filter because of its limitations and substitute it with the Unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (IMMUKF). To resolve the problem of data association, the JPDA approach is combined with the IMM-UKF algorithm, the derived algorithm is noted JPDA-IMM-UKF.

Keywords: Estimation, Kalman filtering, Multi-Target Tracking, Visual servoing, data association.

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Authors: Yasunori Sugita, Toshinori Yoshikawa

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The design problem of Infinite Impulse Response (IIR) digital filters is usually expressed as the minimization problem of the complex magnitude error that includes both the magnitude and phase information. However, the group delay of the filter obtained by solving such design problem may be far from the desired group delay. In this paper, we propose a design method of stable IIR digital filters with prespecified maximum group delay errors. In the proposed method, the approximation problems of the magnitude-phase and group delay are separately defined, and these two approximation problems are alternately solved using successive projections. As a result, the proposed method can design the IIR filters that satisfy the prespecified allowable errors for not only the complex magnitude but also the group delay by alternately executing the coefficient update for the magnitude-phase and the group delay approximation. The usefulness of the proposed method is verified through some examples.

Keywords: Filter design, Group delay approximation, Stable IIRfilters, Successive projection method.

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Authors: Hong Son Hoang, Remy Baraille

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The (sub)-optimal soolution of linear filtering problem with correlated noises is considered. The special recursive form of the class of filters and criteria for selecting the best estimator are the essential elements of the design method. The properties of the proposed filter are studied. In particular, for Markovian observation noise, the approximate filter becomes an optimal Gevers-Kailath filter subject to a special choice of the parameter in the class of given linear recursive filters.

Keywords: Linear dynamical system, filtering, minimum meansquare filter, correlated noise

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Authors: Chia-Min Lai, Wan-Ching Lin, Hahn-Ming Lee, Ching-Hao Mao

Abstract:

As world wild internet has non-stop developments, making profit by lending registered domain names emerges as a new business in recent years. Unfortunately, the larger the market scale of domain lending service becomes, the riskier that there exist malicious behaviors or malwares hiding behind parked domains will be. Also, previous work for differentiating parked domain suffers two main defects: 1) too much data-collecting effort and CPU latency needed for features engineering and 2) ineffectiveness when detecting parked domains containing external links that are usually abused by hackers, e.g., drive-by download attack. Aiming for alleviating above defects without sacrificing practical usability, this paper proposes ParkedGuard as an efficient and accurate parked domain detector. Several scripting behavioral features were analyzed, while those with special statistical significance are adopted in ParkedGuard to make feature engineering much more cost-efficient. On the other hand, finding memberships between external links and parked domains was modeled as a graph mining problem, and a coarse-to-fine strategy was elaborately designed by leverage the graphical locality such that ParkedGuard outperforms the state-of-the-art in terms of both recall and precision rates.

Keywords: Coarse-to-fine strategy, domain parking service, graphical locality analysis, parked domain.

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Authors: Anujendra, Parag Kumar Guha Thakurta

Abstract:

The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. So, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.

Keywords: Base station, channel, GA, Pareto-optimal, reliability.

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Authors: Ulrike Völlinger, Erik Lehmann, Rainer Stark

Abstract:

The intention of this paper is, to help the user of evolutionary algorithms to adapt them easier to their problem at hand. For a lot of problems in the technical field it is not necessary to reach an optimum solution, but to reach a good solution in time. In many cases the solution is undetermined or there doesn-t exist a method to determine the solution. For these cases an evolutionary algorithm can be useful. This paper intents to give the user rules of thumb with which it is easier to decide if the problem is suitable for an evolutionary algorithm and how to design them.

Keywords: Multi criteria optimization, Memetic algorithms

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Authors: C. Ardil

Abstract:

Multidimensional compromise programming evaluation of digital commerce websites is essential not only to have recommendations for improvement, but also to make comparisons with global business competitors. This research provides a multidimensional decision making model that prioritizes the objective criteria weights of various commerce websites using multidimensional compromise solution. Evaluation of digital commerce website quality can be considered as a complex information system structure including qualitative and quantitative factors for a multicriteria decision making problem. The proposed multicriteria decision making approach mainly consists of three sequential steps for the selection problem. In the first step, three major different evaluation criteria are characterized for website ranking problem. In the second step, identified critical criteria are weighted using the standard deviation procedure. In the third step, the multidimensional compromise programming is applied to rank the digital commerce websites.

Keywords: Standard deviation, commerce website, website evaluation, multicriteria decision making, multicriteria compromise programming, website quality, multidimensional decision analysis.

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Authors: Amirhossein Chambari, Seyed Habib Rahmaty, Vahid Hajipour, Aida Karimi

Abstract:

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing framework. We formulate this model with two perspectives simultaneously: (i) customers and (ii) service provider. The objectives of the model are to minimize (i) the total expected travelling and waiting time and (ii) the average facility idle-time. This model represents a mixed-integer nonlinear programming problem which belongs to the class of NP-hard problems. In addition, to solve the model, two metaheuristic algorithms including nondominated sorting genetic algorithms (NSGA-II) and non-dominated ranking genetic algorithms (NRGA) are proposed. Besides, to evaluate the performance of the two algorithms some numerical examples are produced and analyzed with some metrics to determine which algorithm works better.

Keywords: Queuing, Location, Bi-objective, NSGA-II, NRGA

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Authors: Gao Xian-Zhong, Hou Zhong-xi, Guo Zheng, Liu Jian-xia

Abstract:

Gliding during night without electric power is an efficient method to enhance endurance performance of solar aircrafts. The properties of maximum gliding endurance path are studied in this paper. The problem is formulated as an optimization problem about maximum endurance can be sustained by certain potential energy storage with dynamic equations and aerodynamic parameter constrains. The optimal gliding path is generated based on gauss pseudo-spectral method. In order to analyse relationship between altitude, velocity of solar UAVs and its endurance performance, the lift coefficient in interval of [0.4, 1.2] and flight envelopes between 0~30km are investigated. Results show that broad range of lift coefficient can improve solar aircrafts- long endurance performance, and it is possible for a solar aircraft to achieve the aim of long endurance during whole night just by potential energy storage.

Keywords: Solar UAVs, Gliding Endurance, gauss pseudo-spectral method, optimization problem

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Authors: F. Laaouad, M. Bouguerra, A. Hafaifa, A. Iratni

Abstract:

In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization.

Keywords: Compressor, Fuzzy logic, Surge control, Bilinearcontroller, Stability analysis, Nonlinear plant.

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Authors: Minghui Wang

Abstract:

Based on the classical algorithm LSQR for solving (unconstrained) LS problem, an iterative method is proposed for the least-squares like-minimum-norm symmetric solution of AXB+CYD=E. As the application of this algorithm, an iterative method for the least-squares like-minimum-norm biymmetric solution of AXB=E is also obtained. Numerical results are reported that show the efficiency of the proposed methods.

Keywords: Matrix equation, bisymmetric matrix, least squares problem, like-minimum norm, iterative algorithm.

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Authors: Simon E. Uguru, Victor E. Idigo, Obinna S. Oguejiofor, Naveed Nawaz

Abstract:

As the deployment of the Fifth Generation (5G) mobile communication networks take shape all over the world, achieving spectral efficiency, energy efficiency, and dealing with interference are among the greatest challenges encountered so far. The aim of this study is to mitigate inter-cell interference (ICI) in a multi-cell multi-antenna system while maximizing the spectral efficiency of the system. In this study, a system model was devised that showed a miniature representation of a multi-cell multi-antenna system. Based on this system model, a convex optimization problem was formulated to maximize the spectral efficiency of the system while mitigating the ICI. This optimization problem was solved using CVX, which is a modeling system for constructing and solving discipline convex programs. The solutions to the optimization problem are sub-optimal coordinated beamformers. These coordinated beamformers direct each data to the served user equipments (UEs) in each cell without interference during downlink transmission, thereby maximizing the system-wide spectral efficiency.

Keywords: coordinated beamforming, convex optimization, inter-cell interference, multi-antenna, multi-cell, spectral efficiency

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Authors: Nedal Tahat

Abstract:

Recently, many existing partially blind signature scheme based on a single hard problem such as factoring, discrete logarithm, residuosity or elliptic curve discrete logarithm problems. However sooner or later these systems will become broken and vulnerable, if the factoring or discrete logarithms problems are cracked. This paper proposes a secured partially blind signature scheme based on factoring (FAC) problem and elliptic curve discrete logarithms (ECDL) problem. As the proposed scheme is focused on factoring and ECDLP hard problems, it has a solid structure and will totally leave the intruder bemused because it is very unlikely to solve the two hard problems simultaneously. In order to assess the security level of the proposed scheme a performance analysis has been conducted. Results have proved that the proposed scheme effectively deals with the partial blindness, randomization, unlinkability and unforgeability properties. Apart from this we have also investigated the computation cost of the proposed scheme. The new proposed scheme is robust and it is difficult for the malevolent attacks to break our scheme.

Keywords: Cryptography, Partially Blind Signature, Factoring, Elliptic Curve Discrete Logarithms.

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Authors: Akbar H. Borzabadi, Omid S. Fard

Abstract:

In this paper we introduce an approach via optimization methods to find approximate solutions for nonlinear Fredholm integral equations of the first kind. To this purpose, we consider two stages of approximation. First we convert the integral equation to a moment problem and then we modify the new problem to two classes of optimization problems, non-constraint optimization problems and optimal control problems. Finally numerical examples is proposed.

Keywords: Fredholm integral equation, Optimization method, Optimal control, Nonlinear and linear programming

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Authors: Komeil Valipourian

Abstract:

Urban advances and the growing need for developing infrastructures has increased the importance of deep excavations. In this study, after the introducing probability analysis as an important issue, an attempt has been made to apply it for the deep excavation project of Bangkok’s Metro as a case study. For this, the numerical probability model has been developed based on the Finite Difference Method and Monte Carlo sampling approach. The results indicate that disregarding the issue of probability in this project will result in an inappropriate design of the retaining structure. Therefore, probabilistic redesign of the support is proposed and carried out as one of the applications of probability analysis. A 50% reduction in the flexural strength of the structure increases the failure probability just by 8% in the allowable range and helps improve economic conditions, while maintaining mechanical efficiency. With regard to the lack of efficient design in most deep excavations, by considering geometrical and geotechnical variability, an attempt was made to develop an optimum practical design standard for deep excavations based on failure probability. On this basis, a practical relationship is presented for estimating the maximum allowable horizontal displacement, which can help improve design conditions without developing the probability analysis.

Keywords: Numerical probability modeling, deep excavation, allowable maximum displacement, finite difference method, FDM.

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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Authors: V. Masilamani, C. Vanniarajan, Kamala Krithivasan

Abstract:

As the Computed Tomography(CT) requires normally hundreds of projections to reconstruct the image, patients are exposed to more X-ray energy, which may cause side effects such as cancer. Even when the variability of the particles in the object is very less, Computed Tomography requires many projections for good quality reconstruction. In this paper, less variability of the particles in an object has been exploited to obtain good quality reconstruction. Though the reconstructed image and the original image have same projections, in general, they need not be the same. In addition to projections, if a priori information about the image is known, it is possible to obtain good quality reconstructed image. In this paper, it has been shown by experimental results why conventional algorithms fail to reconstruct from a few projections, and an efficient polynomial time algorithm has been given to reconstruct a bi-level image from its projections along row and column, and a known sub image of unknown image with smoothness constraints by reducing the reconstruction problem to integral max flow problem. This paper also discusses the necessary and sufficient conditions for uniqueness and extension of 2D-bi-level image reconstruction to 3D-bi-level image reconstruction.

Keywords: Discrete Tomography, Image Reconstruction, Projection, Computed Tomography, Integral Max Flow Problem, Smooth Binary Image.

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Authors: C. Ardil

Abstract:

This paper introduces the concept of neutral sets (NSs) and explores various operations on NSs, along with their associated properties. The foundation of the Neutral Set framework lies in ontological neutrality and the principles of logic, including the Law of Non-Contradiction. By encompassing components for possibility, indeterminacy, and necessity, the NS framework provides a flexible representation of truth, uncertainty, and necessity, accommodating diverse ontological perspectives without presupposing specific existential commitments. The inclusion of Possibility acknowledges the spectrum of potential states or propositions, promoting neutrality by accommodating various viewpoints. Indeterminacy reflects the inherent uncertainty in understanding reality, refraining from making definitive ontological commitments in uncertain situations. Necessity captures propositions that must hold true under all circumstances, aligning with the principle of logical consistency and implicitly supporting the Law of Non-Contradiction. Subsequently, a neutral set-TOPSIS approach is applied in the maintenance strategy selection problem, demonstrating the practical applicability of the NS framework. The paper further explores uncertainty relations and presents the fundamental preliminaries of NS theory, emphasizing its role in fostering ontological neutrality and logical coherence in reasoning.

Keywords: Uncertainty sets, neutral sets, maintenance strategy selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, distance function, multiple attribute, decision making, selection method, uncertainty, TOPSIS

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Authors: Arkady Bolotin

Abstract:

Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.

Keywords: Categorization, Uncertain medical categories, Binomial regression model, Fuzzy dependent variable, Robustness.

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Authors: F. Bayatbabolghani, K. Parand

Abstract:

In this paper, we propose Hermite collocation method for solving Thomas-Fermi equation that is nonlinear ordinary differential equation on semi-infinite interval. This method reduces the solution of this problem to the solution of a system of algebraic equations. We also present the comparison of this work with solution of other methods that shows the present solution is more accurate and faster convergence in this problem.

Keywords: Collocation method, Hermite function, Semi-infinite, Thomas-Fermi equation.

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

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In this paper, the 1-D conduction-radiation problem is solved by the lattice Boltzmann method. The effects of various parameters such as the scattering albedo, the conduction–radiation parameter and the wall emissivity are studied. In order to check on the accuracy of the numerical technique employed for the solution of the considered problem, the present numerical code was validated with the published study. The found results are in good agreement with those published

Keywords: Conduction, lattice Boltzmann method, planar medium, radiation.

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Authors: Xijian Wang

Abstract:

This paper is concerned with the numerical minimization of energy functionals in BV ( ) (the space of bounded variation functions) involving total variation for gray-scale 1-dimensional inpainting problem. Applications are shown by finite element method and discontinuous Galerkin method for total variation minimization. We include the numerical examples which show the different recovery image by these two methods.

Keywords: finite element method, discontinuous Galerkin method, total variation minimization, inpainting

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