Search results for: switched function model.

Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are increasingly important in automated customer service. These models, adept at recognizing complex relationships between input and output sequences, are essential for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the model’s focus during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the context of chatbots utilizing the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Using the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k = 3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k = 3). These findings emphasize the crucial influence of selecting an appropriate attention-scoring function to enhance the performance of seq2seq models for chatbots, particularly highlighting the model integrating tanh activation as a promising approach to improving chatbot quality in customer support contexts.

Keywords: Attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence.

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Authors: Pallav Roxy, Durga Toshniwal

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Clustering unstructured text documents is an important issue in data mining community and has a number of applications such as document archive filtering, document organization and topic detection and subject tracing. In the real world, some of the already clustered documents may not be of importance while new documents of more significance may evolve. Most of the work done so far in clustering unstructured text documents overlooks this aspect of clustering. This paper, addresses this issue by using the Fading Function. The unstructured text documents are clustered. And for each cluster a statistics structure called Cluster Profile (CP) is implemented. The cluster profile incorporates the Fading Function. This Fading Function keeps an account of the time-dependent importance of the cluster. The work proposes a novel algorithm Clustering n-ary Merge Algorithm (CnMA) for unstructured text documents, that uses Cluster Profile and Fading Function. Experimental results illustrating the effectiveness of the proposed technique are also included.

Keywords: Clustering, Text Mining, Unstructured TextDocuments, Fading Function.

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Authors: Saleem Z. Ramadan, Gürsel A. Süer

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In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.

Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.

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Authors: Chieh-Yuan Tsai, Chuang-Cheng Chiu

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Biclustering aims at identifying several biclusters that reveal potential local patterns from a microarray matrix. A bicluster is a sub-matrix of the microarray consisting of only a subset of genes co-regulates in a subset of conditions. In this study, we extend the motif of subspace clustering to present a K-biclusters clustering (KBC) algorithm for the microarray biclustering issue. Besides minimizing the dissimilarities between genes and bicluster centers within all biclusters, the objective function of the KBC algorithm additionally takes into account how to minimize the residues within all biclusters based on the mean square residue model. In addition, the objective function also maximizes the entropy of conditions to stimulate more conditions to contribute the identification of biclusters. The KBC algorithm adopts the K-means type clustering process to efficiently make the partition of K biclusters be optimized. A set of experiments on a practical microarray dataset are demonstrated to show the performance of the proposed KBC algorithm.

Keywords: Microarray, Biclustering, Subspace clustering, Meansquare residue model.

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Authors: Sheroz Khan, A. F. Salami, W. A. Lawal, AHM Zahirul Alam, Shihab Abdel Hameed, M. J. E.Salami

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In this paper, a multi-branch power line is modeled using ABCD matrix to show its worth as a communication channel. The model is simulated using MATLAB in an effort to investigate the effects of multiple loading, multipath, and those as a result of load mismatching. The channel transfer function is obtained and investigated using different cable lengths, and different number of bridge taps under given loading conditions.

Keywords: Power line Communication, Transfer Function, Channel Modeling, Signal Transmission.

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Authors: M.Sujaritha, S. Annadurai

Abstract:

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.

Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.

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Authors: Minh T. N. Le, Cathleen Teh, Ng Shyh-Chang, Vladimir Korzh, Harvey F. Lodish, Bing Lim

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MicroRNAs are an important class of gene expression regulators that are involved in many biological processes including embryogenesis. miR-125b is a conserved microRNA that is enriched in the nervous system. We have previously reported the function of miR-125b in neuronal differentiation of human cell lines. We also discovered the function of miR-125b in regulating p53 in human and zebrafish. Here we further characterize the brain defects in zebrafish embryos injected with morpholinos against miR-125b. Our data confirm the essential role of miR-125b in brain morphogenesis particularly in maintaining the balance between proliferation, cell death and differentiation. We identified lunatic fringe (lfng) as an additional target of miR-125b in human and zebrafish and suggest that lfng may mediate the function of miR-125b in neurogenesis. Together, this report reveals new insights into the function of miR- 125b during neural development of zebrafish.

Keywords: microRNA, miR-125b, neurogenesis, zebrafish.

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Authors: Mahanijah Md Kamal., Dingli Yu

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This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Parvinder S. Sandhu, Porush Bassi, Amanpreet Singh Brar

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Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.

Keywords: Effort Estimation, Neural-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model.

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Authors: R. Gunabalan, V. Subbiah

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This paper discusses the novel graphical approach for stability analysis of multi induction motor drive controlled by a single inverter. Stability issue arises in parallel connected induction motors under unbalanced load conditions. The two powerful globally accepted modeling and simulation software packages such as MATLAB and LabVIEW are selected to perform the stability analysis. The stability investigation is performed for different load conditions and difference in stator and rotor resistances among the two motors. It is very simple and effective than the techniques presented to obtain the stability of the parallel connected induction motor drive under unbalanced load conditions. Approximate transfer functions are considered to model the induction motors, load dynamics, speed controllers and inverter. Simulink library tools are utilized to model the entire drive scheme in MATLAB. Stability study is discussed in LabVIEW using control design and simulation toolkits. Simulation results are illustrated for various running conditions to demonstrate the effectiveness of the transfer function method.

Keywords: Induction motor, Modeling, Stability analysis, Transfer function model.

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Authors: Srinath Shetty K., Shivashankar R., Rashmi P. Shetty

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Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

Keywords: Bearing pressure, granular bed, radial basis function neural network, strip footing.

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

Abstract:

Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: Diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography.

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Authors: Yin Yin Phyo, Tun Lin Naing

Abstract:

In this paper, the average input current mode control is proposed for two-phase interleaved boost converter with two separate input inductors operating in continuous conduction mode (CCM). The required mathematical model is obtained from the equivalent circuits of its different four modes of operation. The small ripple approximation is derived to find the transfer functions from dynamic model using switching function. In average input current mode control, the inner current loop and outer voltage loop are designed with PI controller using bode analysis. Anti-windup structure is applied for PI controllers in control system. Moreover, the simulation work is carried out by MATLAB/Simulink. And, the hardware prototype is implemented by using low-cost microcontroller Arduino Nano. Finally, the laboratory prototype, available from the local market, is constructed to validate the mathematical model. The results show that the output voltage response is the faster rise time and settling time with acceptable overshoot.

Keywords: Average input current mode control, interleaved boost converter, low-cost microcontroller, PI controller, switching function.

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Authors: Rasaki O. Olanrewaju

Abstract:

The driven processes of Wiener and Lévy are known self-standing Gaussian-Markov processes for fitting non-linear dynamical Vasciek model. In this paper, a coincidental Gaussian density stationarity condition and autocorrelation function of the two driven processes were established. This led to the conflation of Wiener and Lévy processes so as to investigate the efficiency of estimates incorporated into the one-dimensional Vasciek model that was estimated via the Maximum Likelihood (ML) technique. The conditional laws of drift, diffusion and stationarity process was ascertained for the individual Wiener and Lévy processes as well as the commingle of the two processes for a fixed effect and Autoregressive like Vasciek model when subjected to financial series; exchange rate of Naira-CFA Franc. In addition, the model performance error of the sub-merged driven process was miniature compared to the self-standing driven process of Wiener and Lévy.

Keywords: Wiener process, Lévy process, Vasciek model, drift, diffusion, Gaussian density stationary.

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Authors: Jing Zhang, Jie Chen

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In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: Parking system, optimal location, response time, S/R machine.

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Authors: Takashi Mitsuishi, Koji Saigusa

Abstract:

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular polar coordinates is also proposed.

Keywords: Defuzzification, periodic membership function, polar coordinates transformation.

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Authors: Mohamed Asaad Abdelrazek, Amir Taher El-Sheikh, M. Zayan, A.M. Elhady

Abstract:

The successful realization of complex systems is dependent not only on the technology issues and the process for implementing them, but on the management issues as well. Managing the systems development lifecycle requires technical management. Systems engineering management is the technical management. Systems engineering management is accomplished by incorporating many activities. The three major activities are development phasing, systems engineering process and lifecycle integration. Systems engineering management activities are performed across the system development lifecycle. Due to the ever-increasing complexity of systems as well the difficulty of managing and tracking the development activities, new ways to achieve systems engineering management activities are required. This paper presents a systematic approach used as a design management tool applied across systems engineering management roles. In this approach, Transdisciplinary System Development Lifecycle (TSDL) Model has been modified and integrated with Quality Function Deployment. Hereinafter, the name of the systematic approach is the Transdisciplinary Quality System Development Lifecycle (TQSDL) Model. The QFD translates the voice of customers (VOC) into measurable technical characteristics. The modified TSDL model is based on Axiomatic Design developed by Suh which is applicable to all designs: products, processes, systems and organizations. The TQSDL model aims to provide a robust structure and systematic thinking to support the implementation of systems engineering management roles. This approach ensures that the customer requirements are fulfilled as well as satisfies all the systems engineering manager roles and activities.

Keywords: Axiomatic design, quality function deployment, systems engineering management, system development lifecycle.

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Authors: Mahdieh Allahviranloo

Abstract:

This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of sensitivity analysis on port operation quantity provide useful information for managers to choose the best scenario for port planning with the lowest investment risks. Despite all limitations-due to data availability-the model offers a straightforward decision tools to port planners aspiring to achieve optimum port planning steps.

Keywords: MILP, Multipurpose Terminal, Port Operation Optimization, Port Anzali.

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Authors: Seung-Won Jung, Hye-Soo Kim, Le Thanh Ha, Seung-Jin Baek, Sung-Jea Ko

Abstract:

In this paper, a novel deinterlacing algorithm is proposed. The proposed algorithm approximates the distribution of the luminance into a polynomial function. Instead of using one polynomial function for all pixels, different polynomial functions are used for the uniform, texture, and directional edge regions. The function coefficients for each region are computed by matrix multiplications. Experimental results demonstrate that the proposed method performs better than the conventional algorithms.

Keywords: Deinterlacing, polynomial interpolation.

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Authors: M. Palanivel, R. Uthayakumar

Abstract:

In this paper, Economic Order Quantity (EOQ) based model for non-instantaneous Weibull distribution deteriorating items with power demand pattern is presented. In this model, the holding cost per unit of the item per unit time is assumed to be an increasing linear function of time spent in storage. Here the retailer is allowed a trade-credit offer by the supplier to buy more items. Also in this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This model aids in minimizing the total inventory cost by finding the optimal time interval and finding the optimal order quantity. The optimal solution of the model is illustrated with the help of numerical examples. Finally sensitivity analysis and graphical representations are given to demonstrate the model.

Keywords: Power demand pattern, Partial backlogging, Time dependent holding cost, Trade credit, Weibull deterioration.

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Authors: Zhizhong Jiang, Peter Naudé, Binghua Jiang

Abstract:

Effective evaluation of software development effort is an important issue during project plan. This study provides a model to predict development effort based on the software size estimated with function points. We generalize the average amount of effort spent on each phase of the development, and give the estimates for the effort used in software building, testing, and implementation. Finally, this paper finds a strong correlation between software defects and software size. As the size of software constantly increases, the quality remains to be a matter which requires major concern.

Keywords: Development effort, function points, software quality, software size.

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Authors: Y. Abdelrazig, A. Ghanem

Abstract:

Construction projects are information intensive in nature and involve many activities that are related to each other. Wireless technologies can be used to improve the accuracy and timeliness of data collected from construction sites and shares it with appropriate parties. Nonetheless, the construction industry tends to be conservative and shows hesitation to adopt new technologies. A main concern for owners, contractors or any person in charge on a job site is the cost of the technology in question. Wireless technologies are not cheap. There are a lot of expenses to be taken into consideration, and a study should be completed to make sure that the importance and savings resulting from the usage of this technology is worth the expenses. This research attempts to assess the effectiveness of using the appropriate wireless technologies based on criteria such as performance, reliability, and risk. The assessment is based on a utility function model that breaks down the selection issue into alternatives attribute. Then the attributes are assigned weights and single attributes are measured. Finally, single attribute are combined to develop one single aggregate utility index for each alternative.

Keywords: Analytic Hierarchy Process, Utility Function, Wireless Technologies, construction management.

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Authors: Saisundar. S., I Made Darmayuda, Zhou Jun, Krishna Mainali, Simon Ng Sheung Yan, Eran Ofek

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This paper compares the recent transformerless ACDC power converter architectures and provides an assessment of each. A prototype of one of the transformerless AC-DC converter architecture is also presented depicting the feasibility of a small form factor, power supply design. In this paper component selection guidelines to achieve high efficiency AC-DC power conversion are also discussed.

Keywords: AC-DC converter, digitally controlled, switched mode power supply, transformerless.

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Authors: M. Abdulkawi, Z. K. Eshkuvatov, N. M. A. Nik Long

Abstract:

This manuscript presents a method for the numerical solution of the Cauchy type singular integral equations of the first kind, over a finite segment which is bounded at the end points of the finite segment. The Chebyshev polynomials of the second kind with the corresponding weight function have been used to approximate the density function. The force function is approximated by using the Chebyshev polynomials of the first kind. It is shown that the numerical solution of characteristic singular integral equation is identical with the exact solution, when the force function is a cubic function. Moreover, it also shown that this numerical method gives exact solution for other singular integral equations with degenerate kernels.

Keywords: Singular integral equations, Cauchy kernel, Chebyshev polynomials, interpolation.

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Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira

Abstract:

In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.

Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.

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Authors: M. Momeni Feyli

Abstract:

Many recent high energy physics calculations involving charm and beauty invoke wave function at the origin (WFO) for the meson bound state. Uncertainties of charm and beauty quark masses and different models for potentials governing these bound states require a simple numerical algorithm for evaluation of the WFO's for these bound states. We present a simple algorithm for this propose which provides WFO's with high precision compared with similar ones already obtained in the literature.

Keywords: Mesons, Bound states, Schrodinger equation, Nonrelativistic quark model.

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Authors: Nadia M. G. AL-Saidi

Abstract:

Since 1984 many schemes have been proposed for digital signature protocol, among them those that based on discrete log and factorizations. However a new identification scheme based on iterated function (IFS) systems are proposed and proved to be more efficient. In this study the proposed identification scheme is transformed into a digital signature scheme by using a one way hash function. It is a generalization of the GQ signature schemes. The attractor of the IFS is used to obtain public key from a private one, and in the encryption and decryption of a hash function. Our aim is to provide techniques and tools which may be useful towards developing cryptographic protocols. Comparisons between the proposed scheme and fractal digital signature scheme based on RSA setting, as well as, with the conventional Guillou-Quisquater signature, and RSA signature schemes is performed to prove that, the proposed scheme is efficient and with high performance.

Keywords: Digital signature, Fractal, Iterated function systems(IFS), Guillou-Quisquater (GQ) protocol, Zero-knowledge (ZK)

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Authors: Eva Eggeling, Dieter W. Fellner, Torsten Ullrich

Abstract:

The objective of global optimization is to find the globally best solution of a model. Nonlinear models are ubiquitous in many applications and their solution often requires a global search approach; i.e. for a function f from a set A ⊂ Rn to the real numbers, an element x0 ∈ A is sought-after, such that ∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application, the question whether a found solution x0 is not only a local minimum but a global one is very important. This article presents a probabilistic approach to determine the probability of a solution being a global minimum. The approach is independent of the used global search method and only requires a limited, convex parameter domain A as well as a Lipschitz continuous function f whose Lipschitz constant is not needed to be known.

Keywords: global optimization, probability theory, probability of globality

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Authors: Ashwani K. Rana, Narottam Chand, Vinod Kapoor

Abstract:

This paper presents a new compact analytical model of the gate leakage current in high-k based nano scale MOSFET by assuming a two-step inelastic trap-assisted tunneling (ITAT) process as the conduction mechanism. This model is based on an inelastic trap-assisted tunneling (ITAT) mechanism combined with a semiempirical gate leakage current formulation in the BSIM 4 model. The gate tunneling currents have been calculated as a function of gate voltage for different gate dielectrics structures such as HfO2, Al2O3 and Si3N4 with EOT (equivalent oxide thickness) of 1.0 nm. The proposed model is compared and contrasted with santaurus simulation results to verify the accuracy of the model and excellent agreement is found between the analytical and simulated data. It is observed that proposed analytical model is suitable for different highk gate dielectrics simply by adjusting two fitting parameters. It was also shown that gate leakages reduced with the introduction of high-k gate dielectric in place of SiO2.

Keywords: Analytical model, High-k gate dielectrics, inelastic trap assisted tunneling, metal–oxide–semiconductor (MOS) devices.

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