Search results for: Graphical processing unit

Authors: A. Ehsani, A. Karimizadeh, H. Fallahi, A. Jalali

Abstract:

In an electric power system, spinning reserve requirements can be determined by using deterministic and/or probabilistic measures. Although deterministic methods are usual in many systems, application of probabilistic methods becomes increasingly important in the new environment of the electric power utility industry. This is because of the increased uncertainty associated with competition. In this paper 1) a new probabilistic method is presented which considers the reliability of transmission system in a simplified manner and 2) deterministic and probabilistic methods are compared. The studied methods are applied to the Roy Billinton Test System (RBTS).

Keywords: Reliability, Spinning Reserve, Risk, Transmission, Unit Commitment.

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Authors: Chiung-Ju Huang

Abstract:

This study examines whether the Taiwan’s public debt is sustainable utilizing an unrestricted two-regime threshold autoregressive (TAR) model with an autoregressive unit root. The empirical results show that Taiwan’s public debt appears as a nonlinear series and is stationary in regime 1 but not in regime 2. This result implies that while Taiwan’s public debt was mostly sustainable over the 1996 to 2013 period examined in the study, it may no longer be sustainable in the most recent two years as the public debt ratio has increased cumulatively to 3.618%.

Keywords: Nonlinearity, public debt, sustainability, threshold autoregressive model.

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Authors: Kgatla T.E, Howard S.S., Hiss D.C.

Abstract:

Prickly pear (Opuntia spp) fruit has received renewed interest since it contains a betalain pigment that has an attractive purple colour for the production of juice. Prickly pear juice was prepared by homogenizing the fruit and treating the pulp with 48 g of pectinase from Aspergillus niger. Titratable acidity was determined by diluting 10 ml prickly pear juice with 90 ml deionized water and titrating to pH 8.2 with 0.1 N NaOH. Brix was measured using a refractometer and ascorbic acid content assayed spectrophotometrically. Colour variation was determined colorimetrically (Hunter L.a.b.). Hunter L.a.b. analysis showed that the red purple colour of prickly pear juice had been affected by juice treatments. This was indicated by low light values of colour difference meter (CDML*), hue, CDMa* and CDMb* values. It was observed that non-treated prickly pear juice had a high (colour difference meter of light) CDML* of 3.9 compared to juice treatments (range 3.29 to 2.14). The CDML* significantly (p<0.05) decreased as the juice was preserved. Spectrophotometric colour analysis showed that browning was low in all treated prickly juice samples as indicated by high values at 540 nm and low values at 476 nm (browning index). The brightness of prickly pear had been affected by acidification compared to other juice treatments. This study presents evidence that processing has a positive effect on the colour quality attribute that offers a clear advantage for the production of red-purple prickly pear juice.

Keywords: Colour, Hunter L.a.b, Prickly pear juice, processing, physicochemical.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Mliki Bouchmel, Belgacem Nabil, Abbassi Mohamed Ammar, Geudri Kamel, Omri Ahmed

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In this numerical work, mixed convection and entropy generation of Cu–water nanofluid in a lid-driven square cavity have been investigated numerically using the Lattice Boltzmann Method. Horizontal walls of the cavity are adiabatic and vertical walls have constant temperature but different values. The top wall has been considered as moving from left to right at a constant speed, U0. The effects of different parameters such as nanoparticle volume concentration (0–0.05), Rayleigh number (104–106) and Reynolds numbers (1, 10 and 100) on the entropy generation, flow and temperature fields are studied. The results have shown that addition of nanoparticles to the base fluid affects the entropy generation, flow pattern and thermal behavior especially at higher Rayleigh and low Reynolds numbers. For pure fluid as well as nanofluid, the increase of Reynolds number increases the average Nusselt number and the total entropy generation, linearly. The maximum entropy generation occurs in nanofluid at low Rayleigh number and at high Reynolds number. The minimum entropy generation occurs in pure fluid at low Rayleigh and Reynolds numbers. Also at higher Reynolds number, the effect of Cu nanoparticles on enhancement of heat transfer was decreased because the effect of lid-driven cavity was increased. The present results are validated by favorable comparisons with previously published results. The results of the problem are presented in graphical and tabular forms and discussed.

Keywords: Entropy generation, mixed convection, nanofluid, lattice Boltzmann method.

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Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: Clary sage, heavy metals, phytoremediation, polluted soils.

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Authors: Junghwan Choi, Seongsoo Lee

Abstract:

Histogram equalization is often used in image enhancement, but it can be also used in auto exposure. However, conventional histogram equalization does not work well when many pixels are concentrated in a narrow luminance range.This paper proposes an auto exposure method based on 2-way histogram equalization. Two cumulative distribution functions are used, where one is from dark to bright and the other is from bright to dark. In this paper, the proposed auto exposure method is also designed and implemented for image signal processors with full-HD images.

Keywords: Histogram equalization, Auto exposure, Image signal processor, Low-cost, Full HD Video.

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Authors: Jia-Rong Yeh, Ai-Hsien Li, Jiann-Shing Shieh, Yen-An Su, Chi-Yu Yang

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In this paper, an automatic detecting algorithm for QRS complex detecting was applied for analyzing ECG recordings and five criteria for dangerous arrhythmia diagnosing are applied for a protocol type of automatic arrhythmia diagnosing system. The automatic detecting algorithm applied in this paper detected the distribution of QRS complexes in ECG recordings and related information, such as heart rate and RR interval. In this investigation, twenty sampled ECG recordings of patients with different pathologic conditions were collected for off-line analysis. A combinative application of four digital filters for bettering ECG signals and promoting detecting rate for QRS complex was proposed as pre-processing. Both of hardware filters and digital filters were applied to eliminate different types of noises mixed with ECG recordings. Then, an automatic detecting algorithm of QRS complex was applied for verifying the distribution of QRS complex. Finally, the quantitative clinic criteria for diagnosing arrhythmia were programmed in a practical application for automatic arrhythmia diagnosing as a post-processor. The results of diagnoses by automatic dangerous arrhythmia diagnosing were compared with the results of off-line diagnoses by experienced clinic physicians. The results of comparison showed the application of automatic dangerous arrhythmia diagnosis performed a matching rate of 95% compared with an experienced physician-s diagnoses.

Keywords: Signal processing, electrocardiography (ECG), QRS complex, arrhythmia.

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Authors: Serap Akcan, Ali Kokangul

Abstract:

We consider a single-echelon, single-item inventory system where both demand and lead-time are stochastic. Continuous review policy is used to control the inventory system. The objective is to calculate the reorder point level under stochastic parameters. A case study is presented in Neonatal Intensive Care Unit.

Keywords: Inventory control system, reorder point level, stochastic demand, stochastic lead time

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Authors: Ali Samadi Afshar, Hamed Harrafi, S.M.Javad Gharib Zahedi

Abstract:

IFP Group Technology “Sulfrex process" was used in Iran-s South Pars Gas Complex Refineries for removing sulfur compounds such as mercaptans, carbonyl sulfide and hydrogen sulfide, which uses sulfonated cobalt phthalocyanine dispersed in alkaline solution as catalyst. In this technology, catalyst and alkaline solution were used circularly. However the stability of catalyst due to effect of some parameters would reduce with the running of the unit and therefore sweetening efficiency would be decreased. Hence, the aim of this research is study the factors effecting on the stability of catalyst.

Keywords: sulfonated cobalt phthalocyanine, mercaptans, stability, catalyst, sulfur.

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and timeconsuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: Soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil.

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Authors: Jameela Ali Alkrimi, Loay E. George, Azizah Suliman, Abdul Rahim Ahmad, Karim Al-Jashamy

Abstract:

Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents established 3ⁿ enumeration procedure for mixed integer optimization problems for solving multi-objective reliability and redundancy allocation problem subject to design constraints. The formulated problem is to find the optimum level of unit reliability and the number of units for each subsystem. A number of illustrative examples are provided and compared to indicate the application of the superiority of the proposed method.

Keywords: Integer programming, mixed integer programming, multi-objective optimization, reliability redundancy allocation.

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Authors: R. Bharanidaran, B. T. Ramesh

Abstract:

High precision in motion is required to manipulate the micro objects in precision industries for micro assembly, cell manipulation etc. Precision manipulation is achieved based on the appropriate mechanism design of micro devices such as microgrippers. Design of a compliant based mechanism is the better option to achieve a highly precised and controlled motion. This research article highlights the method of designing a compliant based three fingered microgripper suitable for holding asymmetric objects. Topological optimization technique, a systematic method is implemented in this research work to arrive a topologically optimized design of the mechanism needed to perform the required micro motion of the gripper. Optimization technique has a drawback of generating senseless regions such as node to node connectivity and staircase effect at the boundaries. Hence, it is required to have post processing of the design to make it manufacturable. To reduce the effect of post processing stage and to preserve the edges of the image, a cubic spline interpolation technique is introduced in the MATLAB program. Structural performance of the topologically developed mechanism design is tested using finite element method (FEM) software. Further the microgripper structure is examined to find its fatigue life and vibration characteristics.

Keywords: Compliant mechanism, Cubic spline interpolation, FEM, Topology optimization.

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Authors: Ashly Joseph

Abstract:

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: Seongmin Yim, Hyun-Kyu Kang

Abstract:

As a part of evaluation system for R&D program, the Korean government has applied feasibility analysis since 2008. Various professionals put forth a great effort in order to catch up the high degree of freedom of R&D programs, and make contributions to evolving the feasibility analysis. We analyze diverse R&D programs from various viewpoints, such as technology, policy, and Economics, integrate the separate analysis, and finally arrive at a definite result; whether a program is feasible or unfeasible. This paper describes the concept and method of the feasibility analysis as a decision making tool. The analysis unit and content of each criterion, which are key elements in a comprehensive decision making structure, are examined

Keywords: Decision Making of New Government R&D Program, Feasibility Analysis Study

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Authors: YuLung Wu

Abstract:

In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.

Keywords: Knowledge Structure Graph, On-line LearningDiagnosis

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Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

Abstract:

Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.). 

Keywords: Motion detection, motion tracking, trajectory analysis, video surveillance.

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Authors: El Miloud Ar Reyouchi, Kamal Ghoumid, Koutaiba Ameziane, Otman El Mrabet, Slimane Mekaoui

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In this paper we focus on the Round Trip Delay (RTD) time measurement technique which is an easy way to obtain the operating condition information in wireless network (WN). RTD measurement is affected by various parameters of wireless network. We illustrate how these RTD parameters vary (in a telemanagement application) versus distance, baud rates, number of hops, between nodes, using radio modem & router unit as a means of transmission and wireless routing.

Keywords: Wireless Network, Round Trip Delay, Radio modem, Router.

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Authors: S. Bouharati, I. Bouharati, C. Benzidane, F. Alleg, M. Belmahdi

Abstract:

Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.

Keywords: Sensors, Sensivity, fuzzy logic, analysis, physiological parameters, medical diagnosis.

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Authors: P. Kaladevi, N. Giridharan

Abstract:

The system for analyzing and eliciting public grievances serves its main purpose to receive and process all sorts of complaints from the public and respond to users. Due to the more number of complaint data becomes big data which is difficult to store and process. The proposed system uses HDFS to store the big data and uses MapReduce to process the big data. The concept of cache was applied in the system to provide immediate response and timely action using big data analytics. Cache enabled big data increases the response time of the system. The unstructured data provided by the users are efficiently handled through map reduce algorithm. The processing of complaints takes place in the order of the hierarchy of the authority. The drawbacks of the traditional database system used in the existing system are set forth by our system by using Cache enabled Hadoop Distributed File System. MapReduce framework codes have the possible to leak the sensitive data through computation process. We propose a system that add noise to the output of the reduce phase to avoid signaling the presence of sensitive data. If the complaints are not processed in the ample time, then automatically it is forwarded to the higher authority. Hence it ensures assurance in processing. A copy of the filed complaint is sent as a digitally signed PDF document to the user mail id which serves as a proof. The system report serves to be an essential data while making important decisions based on legislation.

Keywords: Big Data, Hadoop, HDFS, Caching, MapReduce, web personalization, e-governance.

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Authors: Chiharu Okuma, Jun Murakami, Naoki Yamamoto

Abstract:

In digital signal processing it is important to approximate multi-dimensional data by the method called rank reduction, in which we reduce the rank of multi-dimensional data from higher to lower. For 2-dimennsional data, singular value decomposition (SVD) is one of the most known rank reduction techniques. Additional, outer product expansion expanded from SVD was proposed and implemented for multi-dimensional data, which has been widely applied to image processing and pattern recognition. However, the multi-dimensional outer product expansion has behavior of great computation complex and has not orthogonally between the expansion terms. Therefore we have proposed an alterative method, Third-order Orthogonal Tensor Product Expansion short for 3-OTPE. 3-OTPE uses the power method instead of nonlinear optimization method for decreasing at computing time. At the same time the group of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is also developed with SVD extensions for multi-dimensional data. 3-OTPE and HOSVD are similarly on the rank reduction of multi-dimensional data. Using these two methods we can obtain computation results respectively, some ones are the same while some ones are slight different. In this paper, we compare 3-OTPE to HOSVD in accuracy of calculation and computing time of resolution, and clarify the difference between these two methods.

Keywords: Singular value decomposition (SVD), higher-order SVD (HOSVD), higher-order tensor, outer product expansion, power method.

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Authors: Ventura Assuncao

Abstract:

In automotive systems almost all steps concerning the calibration of several control systems, e.g., low idle governor or boost pressure governor, are made with the vehicle because the timeto- production and cost requirements on the projects do not allow for the vehicle analysis necessary to build reliable models. Here is presented a procedure using parametric and NN (neural network) models that enables the generation of vehicle system models based on normal ECU engine control unit) vehicle measurements. These models are locally valid and permit pre and follow-up calibrations so that, only the final calibrations have to be done with the vehicle.

Keywords: Automotive systems, neuro-hybrid models, demodulator, nonlinear systems, identification, and neural networks.

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Authors: C. Lodato, S. Lopes

Abstract:

The image segmentation method described in this paper has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. This method solves the problem of whole objects extraction from background and it produces images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The segmentation algorithm is based on the cooperation among an optical flow evaluation method, edge detection and region growing procedures. The optical flow estimator belongs to the class of differential methods. It permits to detect motions ranging from a fraction of a pixel to a few pixels per frame, achieving good results in presence of noise without the need of a filtering pre-processing stage and includes a specialised model for moving object detection. The first task of the presented method exploits the cues from motion analysis for moving areas detection. Objects and background are then refined using respectively edge detection and seeded region growing procedures. All the tasks are iteratively performed until objects and background are completely resolved. The method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Image Segmentation, Motion Detection, Object Extraction, Optical Flow

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Authors: A. H. Kheireddine, A. A. Khalil, A. H. Ammouri, G. T. Kridli, R. F. Hamade

Abstract:

Solidification cracking and hydrogen cracking are some defects generated in the fusion welding of ultrahigh carbon steels. However, friction stir welding (FSW) of such steels, being a solid-state technique, has been demonstrated to alleviate such problems encountered in traditional welding. FSW include different process parameters that must be carefully defined prior processing. These parameters included but not restricted to: tool feed, tool RPM, tool geometry, tool tilt angle. These parameters form a key factor behind avoiding warm holes and voids behind the tool and in achieving a defect-free weld. More importantly, these parameters directly affect the microstructure of the weld and hence the final mechanical properties of weld. For that, 3D finite element (FE) thermo-mechanical model was developed using DEFORM 3D to simulate FSW of carbon steel. At points of interest in the joint, tracking is done for history of critical state variables such as temperature, stresses, and strain rates. Typical results found include the ability to simulate different weld zones. Simulations predictions were successfully compared to experimental FSW tests. It is believed that such a numerical model can be used to optimize FSW processing parameters to favor desirable defect free weld with better mechanical properties.

Keywords: Carbon Steels, DEFORM 3D, FEM, Friction stir welding.

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Authors: Zelalem Teshome Wale

Abstract:

The notions of I-vague normal groups with membership and non-membership functions taking values in an involutary dually residuated lattice ordered semigroup are introduced which generalize the notions with truth values in a Boolean algebra as well as those usual vague sets whose membership and non-membership functions taking values in the unit interval [0, 1]. Various operations and properties are established.

Keywords: Involutary dually residuated lattice ordered semigroup, I-vague set, I-vague group and I-vague normal group.

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Authors: Mamta Patel, R. N. Patel

Abstract:

Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault.

Keywords: Wavelet, Discrete wavelet transform, Multiresolution analysis, Transient energy

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: Artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization.

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Authors: Yuichi Miyamoto

Abstract:

In regards to the energy sector in the modern period, two points were raised. First is a vast and growing energy demand, and second is an environmental impact associated with it. The enormous consumption of fossil fuel to the mobile unit is leading to its rapid depletion. Nuclear power is not the only problem. A modal shift that utilizes personal transporters and independent power, in order to realize a sustainable society, is very effective. The author proposes that the world will continue to work on this. Energy of the future society, innovation in battery technology and the use of natural energy is a big key. And it is also necessary in order to save on energy consumption.

Keywords: Natural energy, Modal shift, Personal transporter, Battery.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.

Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing

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