Search results for: fuzzy mathematical programming

Authors: Jian-Jun Shu

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It is common knowledge that many physical problems (such as non-linear shallow-water waves and wave motion in plasmas) can be described by the Korteweg-de Vries (KdV) equation, which possesses certain special solutions, known as solitary waves or solitons. As a marriage of the KdV equation and the classical Burgers (KdVB) equation, the Korteweg-de Vries-Burgers (KdVB) equation is a mathematical model of waves on shallow water surfaces in the presence of viscous dissipation. Asymptotic analysis is a method of describing limiting behavior and is a key tool for exploring the differential equations which arise in the mathematical modeling of real-world phenomena. By using variable transformations, the asymptotic expansion of the KdVB equation is presented in this paper. The asymptotic expansion may provide a good gauge on the validation of the corresponding numerical scheme.

Keywords: asymptotic expansion, differential equation, Korteweg-de Vries-Burgers (KdVB) equation, soliton

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Authors: Ogar Ofut Tumenayu, Olga Shabalina

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This paper describes the application of two types of pedagogical agents’ technology with different functions in an adaptive educational game with the sole aim of improving learning and enhancing interactivities in Digital Educational Games (DEG). This idea could promote the elimination of some problems of DEG, like isolation in game-based learning, by introducing a tutor and tutee pedagogical agents. We present an analysis of a learning companion interacting in a peer tutoring environment as a step toward improving social interactions in the educational game environment. We show that tutor and tutee agents use different interventions and interactive approaches: the tutor agent is engaged in tracking the learner’s activities and inferring the learning state, while the tutee agent initiates interactions with the learner at the appropriate times and in appropriate manners. In order to provide motivation to prevent mistakes and clarity a game task, the tutor agent uses the help dialog tool to provide assistance, while the tutee agent provides collaboration assistance by using the hind tool. We presented our idea on a prototype game called “Pyramid Programming Game,” a 2D game that was developed using Libgdx. The game's Pyramid component symbolizes a programming task that is presented to the player in the form of a puzzle. During gameplay, the Agents can instruct, direct, inspire, and communicate emotions. They can also rapidly alter the instructional pattern in response to the learner's performance and knowledge. The pyramid must be effectively destroyed in order to win the game. The game also teaches and illustrates the advantages of utilizing educational agents such as TrA and TeA to assist and motivate students. Our findings support the idea that the functionality of a pedagogical agent should be dualized into an instructional and learner’s companion agent in order to enhance interactivity in a game-based environment.

Keywords: tutor agent, tutee agent, learner’s companion interaction, agent collaboration

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Authors: L. Freeman, D. Bax, V. K. Sapong

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Community-based, preventative approaches to violent extremism may be effective and yet remain an underutilised method. In a realm where security approaches dominate, with the focus on countering violence extremism and combatting radicalisation, community resilience programming remains sparse. This paper will present a survey tool that aims to measure the risk and protective factors that can lead to violent extremism in Mozambique and Tanzania. Conducted in four districts in the Cabo Delgado region of Mozambique and one district in Pwani, Tanzania, the survey uses a combination of BRAVE-14, Afrocentric and context-specific questions in order to more fully understand community resilience opportunities and challenges in preventing and countering violent extremism. Developed in Australia and Canada to measure radicalisation risks in individuals and communities, BRAVE-14 is a tool not yet applied in the African continent. Given the emerging threat of Islamic extremism in Northern Mozambique and Eastern Tanzania, which both experience a combination of socio-political exclusion, resource marginalisation and religious/ideological motivations, the development of the survey is timely and fills a much-needed information gap in these regions. Not only have these Islamist groups succeeded in tapping into the grievances of communities by radicalising and recruiting individuals, but their presence in these regions has been characterised by extreme forms of violence, leaving isolated communities vulnerable to attack. The expected result of these findings will facilitate the contextualisation and comparison of the protective and risk factors that inhibit or promote the radicalisation of the youth in these communities. In identifying sources of resilience and vulnerability, this study emphasises the implementation of context-specific intervention programming and provides a strong research tool for understanding youth and community resilience to violent extremism.

Keywords: community resilience, Mozambique, preventing violent extremism, radicalisation, Tanzania

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Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: J. Ritonja, B. Grcar

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For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

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Authors: Aya Al Masri, Stefaan Carpentier, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis and ulceration to appear. In order to prevent these deterministic effects, an accurate calculation of the patient skin-dose mapping is essential. For most machines, the 'Dose Area Product (DAP)' and fluoroscopy time are the only information available for the operator. These two parameters are a very poor indicator of the peak skin dose. We developed a mathematical model that reconstructs the magnitude (delivered dose), shape, and localization of each irradiation field on the patient skin. In case of critical dose exceeding, the system generates warning alerts. We present the results of its comparison with clinical studies. Materials and methods: Two series of comparison of the skin-dose mapping of our mathematical model with clinical studies were performed: 1. At a first time, clinical tests were performed on patient phantoms. Gafchromic films were placed on the table of the IR machine under of PMMA plates (thickness = 20 cm) that simulate the patient. After irradiation, the film darkening is proportional to the radiation dose received by the patient's back and reflects the shape of the X-ray field. After film scanning and analysis, the exact dose value can be obtained at each point of the mapping. Four experimentation were performed, constituting a total of 34 acquisition incidences including all possible exposure configurations. 2. At a second time, clinical trials were launched on real patients during real 'Chronic Total Occlusion (CTO)' procedures for a total of 80 cases. Gafchromic films were placed at the back of patients. We performed comparisons on the dose values, as well as the distribution, and the shape of irradiation fields between the skin dose mapping of our mathematical model and Gafchromic films. Results: The comparison between the dose values shows a difference less than 15%. Moreover, our model shows a very good geometric accuracy: all fields have the same shape, size and location (uncertainty < 5%). Conclusion: This study shows that our model is a reliable tool to warn physicians when a high radiation dose is reached. Thus, deterministic effects can be avoided.

Keywords: clinical experimentation, interventional radiology, mathematical model, patient's skin-dose mapping.

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Authors: Petri Solanti, Russell Klein

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Many designers are asking for an automated path from an abstract mathematical MATLAB model to a high-quality Register-Transfer Level (RTL) hardware description. Manual transformations of MATLAB or intermediate code are needed, when the design abstraction is changed. Design conversion is problematic as it is multidimensional and it requires many different design steps to translate the mathematical representation of the desired functionality to an efficient hardware description with the same behavior and configurability. Yet, a manual model conversion is not an insurmountable task. Using currently available design tools and an appropriate design methodology, converting a MATLAB model to efficient hardware is a reasonable effort. This paper describes a simple and flexible design methodology that was developed together with several design teams.

Keywords: design methodology, high-level synthesis, MATLAB, verification

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Alexander N. Savostyanov, Tatyana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Yulia V. Kovas

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The present study compared spectral-power indexes and cortical topography of brain activity in a sample characterized by different levels of trait and mathematical anxiety. 52 healthy Russian-speakers (age 17-32; 30 males) participated in the study. Participants solved an error recognition task under 3 conditions: A lexical condition (simple sentences in Russian), and two numerical conditions (simple arithmetic and complicated algebraic problems). Trait and mathematical anxiety were measured using self-repot questionnaires. EEG activity was recorded simultaneously during task execution. Event-related spectral perturbations (ERSP) were used to analyze spectral-power changes in brain activity. Additionally, sLORETA was applied in order to localize the sources of brain activity. When exploring EEG activity recorded after tasks onset during lexical conditions, sLORETA revealed increased activation in frontal and left temporal cortical areas, mainly in the alpha/beta frequency ranges. When examining the EEG activity recorded after task onset during arithmetic and algebraic conditions, additional activation in delta/theta band in the right parietal cortex was observed. The ERSP plots reveled alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three (lexical, arithmetic and algebraic) conditions. The level of trait anxiety was positively correlated with the amplitude of alpha/beta desynchronization. The level of mathematical anxiety was negatively correlated with the amplitude of theta synchronization and of alpha/beta desynchronization. Overall, trait anxiety was related with an increase in brain activation during task execution, whereas mathematical anxiety was associated with increased inhibitory-related activity. We gratefully acknowledge the support from the №11.G34.31.0043 grant from the Government of the Russian Federation.

Keywords: anxiety, EEG, lexical and numerical error-recognition tasks, alpha/beta desynchronization

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The aim of optimization of store management is not only designing the situation of store management itself including its equipment, technology and operation. In optimization of store management we need to consider also synchronizing of technological, transport, store and service operations throughout the whole process of logistic chain in such a way that a natural flow of material from provider to consumer will be achieved the shortest possible way, in the shortest possible time in requested quality and quantity and with minimum costs. The paper deals with the application of the queuing theory for optimization of warehouse processes. The first part refers to common information about the problematic of warehousing and using mathematical methods for logistics chains optimization. The second part refers to preparing a model of a warehouse within queuing theory. The conclusion of the paper includes two examples of using queuing theory in praxis.

Keywords: queuing theory, logistics system, mathematical methods, warehouse optimization

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Vedat Senol, Gursoy Turan, Anders Helmersson, Vortechz Andersson

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In developing a mathematical model of a real structure, the simulation results of the model may not match the real structural response. This is a general problem that arises during dynamic motion of the structure, which may be modeled by means of parameter variations in the stiffness, damping, and mass matrices. These changes in parameters need to be estimated, and the mathematical model is updated to obtain higher control performances and robustness. In this study, a linear fractional transformation (LFT) is utilized for uncertainty modeling. Further, a general approach to the design of an H∞ control of a magneto-rheological damper (MRD) for vibration reduction in a building with mass, damping, and stiffness uncertainties is presented.

Keywords: uncertainty modeling, structural control, MR Damper, H∞, robust control

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Authors: Mohammedi Ferhate

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This work presents details of the study of the entire flow inside the facility where the exothermic chemical reaction process in the chemical laser cavity is analyzed. In our paper we will describe the principles of chemical lasers where flow reversal is produced by chemical reactions. We explain the device for converting chemical potential energy laser energy. We see that the phenomenon thus has an explosive trend. Finally, the feasibility and effectiveness of the proposed method is demonstrated by computer simulation

Keywords: genetic, lasers, nozzle, programming

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Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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Authors: Amal G. Kurian

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The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

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Authors: Hussein Altartouri

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In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

Abstract:

The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

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Authors: Abhishek N. Srivastava, Rahul Singh, Sumedha Chakma

Abstract:

The rapid urbanization in the developing countries is generating an enormous amount of waste leading to the creation of unregulated landfill sites at various places at its disposal. The liquid waste, known as leachate, produced from these landfills sites is severely affecting the surrounding water quality. The water quality in the proximity areas of the landfill is found affected by various physico-chemical parameters of leachate such as pH, alkalinity, total hardness, conductivity, chloride, total dissolved solids (TDS), total suspended solids (TSS), sulphate, nitrate, phosphate, fluoride, sodium and potassium, biological parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), Faecal coliform, and heavy metals such as cadmium (Cd), lead (Pb), iron (Fe), mercury (Hg), arsenic (As), cobalt (Co), manganese (Mn), zinc (Zn), copper (Cu), chromium (Cr), nickel (Ni). However, all these parameters are distributive in leachate that produced according to the nature of waste being dumped at various landfill sites, therefore, it becomes very difficult to predict the main responsible parameter of leachate for water quality contamination. The present study is endeavour the comparative analysis of the physical, chemical and biological parameters of various landfills in India viz. Okhla landfill, Ghazipur landfill, Bhalswa ladfill in NCR Delhi, Deonar landfill in Mumbai, Dhapa landfill in Kolkata and Kodungayaiyur landfill, Perungudi landfill in Chennai. The statistical analysis of the parameters was carried out using the Statistical Packages for the Social Sciences (SPSS) and LandSim 2.5 model to simulate the long term effect of various parameters on different time scale. Further, the uncertainties characterization of various input parameters has also been analysed using fuzzy alpha cut (FAC) technique to check the sensitivity of various water quality parameters at the proximity of numerous landfill sites. Finally, the study would help to suggest the best method for the prevention of pollution migration from the landfill sites on priority basis.

Keywords: landfill leachate, water quality, LandSim, fuzzy alpha cut

Procedia PDF Downloads 114

Authors: Doru Anastasiu Popescu, Raducanu Dragos Ionut

Abstract:

In this paper the presentation of a tool which measures the similarity between two websites is made. The websites are compound only from webpages created with HTML. The tool uses three ways of calculating the similarity between two websites based on certain results already published. The first way compares all the webpages within a website, the second way compares a webpage with all the pages within the second website and the third way compares two webpages. Java programming language and technologies such as spring, Jsoup, log4j were used for the implementation of the tool.

Keywords: Java, Jsoup, HTM, spring

Procedia PDF Downloads 373

Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek

Abstract:

Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.

Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying

Procedia PDF Downloads 113

Authors: Hilal Uslu, Salih Eroglu, Betul Ozkan, Ozcan Bulantekin, Alper Kuscu

Abstract:

In this study, the strawberry (Fragaria L.) fruits, which were pretreated with ultrasound (US), were worked on in the microwave by using 90W power. Then mathematical modelling was applied to dried fruits by using different experimental thin layer models. The sliced fruits were subjected to ultrasound treatment at a frequency of 40 kHz for 10, 20, and 30 minutes, in an ultrasonic water bath, with a ratio of 1:4 to fruit/water. They are then dried in the microwave (90W). The drying process continued until the product moisture was below 10%. By analyzing the moisture change of the products at a certain time, eight different thin-layer drying models, (Newton, page, modified page, Midilli, Henderson and Pabis, logarithmic, two-term, Wang and Singh) were tested for verification of experimental data. MATLAB R2015a statistical program was used for the modelling, and the best suitable model was determined with R²adj (coefficient of determination of compatibility), and root mean square error (RMSE) values. According to analysis, the drying model that best describes the drying behavior for both drying conditions was determined as the Midilli model by high R²adj and low RMSE values. Control, 10, 20, and 30 min US for groups R²adj and RMSE values was established as respectively; 0,9997- 0,005298; 0,9998- 0,004735; 0,9995- 0,007031; 0,9917-0,02773. In addition, effective diffusion coefficients were calculated for each group and were determined as 3,80x 10⁻⁸, 3,71 x 10⁻⁸, 3,26 x10⁻⁸ ve 3,5 x 10⁻⁸ m/s, respectively.

Keywords: mathematical modelling, microwave drying, strawberry, ultrasound

Procedia PDF Downloads 142

Authors: Zhu-Qing Jia, Tao Lin, Tong Zhou

Abstract:

The recognition method of Optical Character Recognition has been expensively utilized, while it is rare to be employed specifically in recognition of electronic components. This paper suggests a high-effective algorithm on appearance identification of integrated circuit components based on the existing methods of character recognition, and analyze the pros and cons.

Keywords: optical character recognition, fuzzy page identification, mutual correlation matrix, confidence self-adaptation

Procedia PDF Downloads 522