Search results for: Treatment methods

Authors: Snehal R. Pathak, Sachin S. Munnoli

Abstract:

Evaluation of dynamic earth pressure on retaining wall is a topic of primary importance. In present paper, dynamic active earth pressure and displacement of flexible cantilever retaining wall has been evaluated analytically using 2-DOF mass-spring-dashpot model by incorporating both wall and backfill properties. The effect of wall flexibility on dynamic active earth pressure and wall displacement are studied and presented in graphical form. The obtained results are then compared with the various conventional methods, experimental analysis and also with PLAXIS analysis. It is observed that the dynamic active earth pressure decreases with increase in the wall flexibility while wall displacement increases linearly with flexibility of the wall. The results obtained by proposed 2-DOF analytical model are found to be more realistic and economical.

Keywords: Earth pressure, earthquake, 2-DOF model, plaxis, wall movement, retaining walls.

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Authors: Roza Dastres, Mohsen Soori

Abstract:

Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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Authors: Manish Kumar

Abstract:

Reinforced cement concrete is getting extensively used for construction of different type of structures for the last one century. During this period, we have constructed many structures like buildings, bridges, industrial structures, pavement, water tanks etc. using this construction material. These structures have been created with huge investment of resources. It is essential to maintain those structures in functional condition. Since deterioration in RCC Structures is a common and natural phenomenon it is required to have a detailed plan, methodology for structural repair and rehabilitation shall be in place for dealing such issues. It is important to know exact reason of distress, type of distress and correct method of repair concrete structures. The different methods of repair are described in paper according to distress category which can be refereed for repair. Major finding of the study is that to protect our structure we need to have maintenance frequency and correct material to be chosen for repair. Also workmanship during repair needs to be taken utmost care for quality repair.

Keywords: Deterioration, functional condition, reinforced cement concrete, resources.

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Authors: Mansour A. Mohamed, George G. Karady, Ali M. Yousef

Abstract:

This paper proposes transient angle stability agents to enhance power system stability. The proposed transient angle stability agents divided into two strategy agents. The first strategy agent is a prediction agent that will predict power system instability. According to the prediction agent-s output, the second strategy agent, which is a control agent, is automatically calculating the amount of active power reduction that can stabilize the system and initiating a control action. The control action considered is turbine fast valving. The proposed strategies are applied to a realistic power system, the IEEE 50- generator system. Results show that the proposed technique can be used on-line for power system instability prediction and control.

Keywords: Multi-agents, Fast Valving, Power System Transient Stability, Prediction methods,

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Authors: D. S. Mohale, A. V. Chandewar

Abstract:

Aim- Study was undertaken to investigate the effect of altered behavioral condition like depression on various oxidative stress markers and biochemical parameters in rats. Methods- Rats were subjected for short (21 days) and long term (84 days) social isolation; the rats displayed an increase in depression on force swim test relative to control. Various markers of oxidative stress like lipid per oxidation (LPO), reduced glutathione (GSH), Supers oxide dismutase (SOD), catalase (CAT) and biochemical parameters like SGOT, SGPT, and blood glucose were determined. Results- There was significant increase in the level of LPO and decrease in the levels of GSH, SOD and CAT after long term isolation. Biochemical parameters were significantly altered after social isolation. Conclusion- Increased oxidative stress in depression which may leads to alteration of biochemical parameters.

Keywords: Depression, Glucose, LPO, Oxidative stress.

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Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

Abstract:

This paper is mainly concerned with the application of a novel technique of data interpretation for classifying measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artificial Neural Networks and Multi-Class Support Vector Machines have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compared with earlier methods.

Keywords: Tokamak, Classification, Artificial Neural Network, Support Vector Machines.

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Authors: R. O. B. Bitencourt, F. S. Farias, M. C. Freitas, C. J. R. Balduino, E.S. Mesquita, A. R. C. Corval, P. S. Gôlo, E. G. Pontes, V. R. E. P. Bittencourt, I. C. Angelo

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Aedes aegypti larval survival rate was assessed after exposure to blastopores or conidia (mineral oil-in-water formulation or aqueous suspension) of Beauveria bassiana CG 479 propagules (blastospores or conidia). Here, mineral oil was used in the fungal formulation to control Aedes aegypti larvae. 1%, 0.5% or 0.1% mineral oil-in-water solutions were used to evaluate mineral oil toxicity for mosquito larvae. In the oil toxicity test, 0.1% mineral oil solution reduced only 4.5% larval survival; accordingly, this concentration was chosen for fungal oil-in-water formulations. Aqueous suspensions were prepared using 0.01% Tween 80^® in sterile dechlorinated water. A. aegypti larvae (L₂) were exposed in aqueous suspensions or mineral oil-in-water fungal formulations at 1×107 propagules mL^-1; the survival rate (assessed daily, for 7 days) and the median survival time (S₅₀) were calculated. Seven days after the treatment, mosquito larvae survival rates were 8.56%, 16.22%, 58%, and 42.56% after exposure to oil-in-water blastospores, oil-in-water conidia, blastospores aqueous suspension and conidia aqueous suspension (respectively). Larvae exposed to 0.01% Tween 80^® had 100% survival rate and the ones treated with 0.1% mineral oil-in-water had 95.11% survival rate. Larvae treated with conidia (regardless the presence of oil) or treated with blastospores formulation had survival median time (S₅₀) ranging from one to two days. S₅₀ was not determined (ND) when larvae were exposed to blastospores aqueous suspension, 0.01% Tween 80^® (aqueous control) or 0.1% mineral oil-in-water formulation (oil control). B. bassiana conidia and blastospores (mineral oil-in-water formulated or suspended in water) had potential to control A. aegypti mosquito larvae, despite mineral oil-in-water formulation yielded better results in comparison to aqueous suspensions. Here, B. bassiana CG 479 isolate is suggested as a potential biocontrol agent of A. aegypti mosquito larvae.

Keywords: Blastospores, formulation, mosquitoes, conidia.

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Authors: Kazuya Sato, Toru Kasahara, Junji Kuroda, Tomoyuki Izu

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In this paper, an autonomous hovering control method of multicopter using only Web camera is proposed. Recently, various control method of an autonomous flight for multicopter are proposed. But, in the previous proposed methods, a motion capture system (i. e., OptiTrack) and laser range finder are often used to measure the position and posture of multicopter. To achieve an autonomous flight control of multicopter with simple equipments, we propose an autonomous flight control method using AR marker and Web camera. AR marker can measure the position of multicopter with Cartesian coordinate in three dimensional, then its position connects with aileron, elevator, and accelerator throttle operation. A simple PID control method is applied to the each operation and adjust the controller gains. Experimental results are given to show the effectiveness of our proposed method. Moreover, another simple operation method for autonomous flight control multicopter is also proposed.

Keywords: Autonomous hovering control, multicopter, Web camera.

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Authors: Vitalice K. Oduol, C. Ardil

Abstract:

The paper examines the performance of bit-interleaved parity (BIP) methods in error rate monitoring, and in declaration and clearing of alarms in those transport networks that employ automatic protection switching (APS). The BIP-based error rate monitoring is attractive for its simplicity and ease of implementation. The BIP-based results are compared with exact results and are found to declare the alarms too late, and to clear the alarms too early. It is concluded that the standards development and systems implementation should take into account the fact of early clearing and late declaration of alarms. The window parameters defining the detection and clearing thresholds should be set so as to build sufficient hysteresis into the system to ensure that BIP-based implementations yield acceptable performance results.

Keywords: Automatic protection switching, bit interleaved parity, excessive bit error rate

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Authors: K. Kumpas

Abstract:

Bologna process has influenced enhancing studentcentered learning in Estonian higher education since 2009, but there is no information about what helps or hinders students to achieve learning outcomes and how quality of student-centered learning might be improved. The purpose of this study is to analyze two questions from outcome-based course evaluation questionnaire which is used in Estonian Entrepreneurship University of Applied Sciences. In this qualitative research, 384 students from 22 different courses described what helped and hindered them to achieve learning outcomes. The analysis showed that the aspects that hinder students to achieve learning outcomes are mostly personal: time management, family and personal matters, motivation and non-academic activities. The results indicate that students- learning is commonly supported by school, where teacher, teaching and characteristics of teaching methods help mostly to achieve learning outcomes, also learning material, practical assignments and independent study was brought up as one of the key elements.

Keywords: Learning outcomes, learning quality, student-centered learning

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Authors: B. S. Raghavendra, D. Narayana Dutt

Abstract:

In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are provided to demonstrate the performance of the proposed method using parametric fractal signals. The estimation accuracy of the method is compared with that of Katz, Sevcik, and Higuchi methods. In addition, some properties of the FD are discussed.

Keywords: Box-counting, Fractal dimension, Higuchi method, Katz method, Parametric fractal signals, Sevcik method.

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Authors: G. Venkata Hari Prasad, P. Rajesh Kumar

Abstract:

Phonocardiography is important in appraisal of congenital heart disease and pulmonary hypertension as it reflects the duration of right ventricular systoles. The systolic murmur in patients with intra-cardiac shunt decreases as pulmonary hypertension develops and may eventually disappear completely as the pulmonary pressure reaches systemic level. Phonocardiography and auscultation are non-invasive, low-cost, and accurate methods to assess heart disease. In this work an objective signal processing tool to extract information from phonocardiography signal using Wavelet is proposed to classify the murmur as normal or abnormal. Since the feature vector is large, a Binary Particle Swarm Optimization (PSO) with mutation for feature selection is proposed. The extracted features improve the classification accuracy and were tested across various classifiers including Naïve Bayes, kNN, C4.5, and SVM.

Keywords: Phonocardiography, Coiflet, Feature selection, Particle Swarm Optimization.

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

Abstract:

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: Inverse problems, multi-component solutions, neural networks, Raman spectroscopy.

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Authors: Nebojsa B. Raicevic, Teodoros S. Prokic, Vladan Golubovic

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Recently, bianisotropic media again received increasing importance in electromagnetic theory because of advances in material science which enable the manufacturing of complex bianisotropic materials. By using Maxwell's equations and corresponding boundary conditions, the electromagnetic field distribution in bianisotropic solenoid coils is determined and the influence of the bianisotropic behaviour of coil to the impedance and Q-factor is considered. Bianisotropic media are the largest class of linear media which is able to describe the macroscopic material properties of artificial dielectrics, artificial magnetics, artificial chiral materials, left-handed materials, metamaterials, and other composite materials. Several special cases of coils, filled with complex substance, have been analyzed. Results obtained by using the analytical approach are compared with values calculated by numerical methods, especially by our new hybrid EEM/BEM method and FEM.

Keywords: Bianisotropic media, impedance and Q-factor, Maxwell`s equations, hybrid EEM/BEM method.

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Authors: Fardin Boustani , Mohammah Hosein Hojati

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The Beshar River is one aquatic ecosystem,which is affected by pollutants. This study was conducted to evaluate the effects of human activities on the water quality of the Beshar river. This river is approximately 190 km in length and situated at the geographical positions of 51° 20' to 51° 48' E and 30° 18' to 30° 52' N it is one of the most important aquatic ecosystems of Kohkiloye and Boyerahmad province next to the city of Yasuj in southern Iran. The Beshar river has been contaminated by industrial, agricultural and other activities in this region such as factories, hospitals, agricultural farms, urban surface runoff and effluent of wastewater treatment plants. In order to evaluate the effects of these pollutants on the quality of the Beshar river, five monitoring stations were selected along its course. The first station is located upstream of Yasuj near the Dehnow village; stations 2 to 4 are located east, south and west of city; and the 5th station is located downstream of Yasuj. Several water quality parameters were sampled. These include pH, dissolved oxygen, biological oxygen demand (BOD), temperature, conductivity, turbidity, total dissolved solids and discharge or flow measurements. Water samples from the five stations were collected and analysed to determine the following physicochemical parameters: EC, pH, T.D.S, T.H, No2, DO, BOD5, COD during 2008 to 2009. The study shows that the BOD5 value of station 1 is at a minimum (1.5 ppm) and increases downstream from stations 2 to 4 to a maximum (7.2 ppm), and then decreases at station 5. The DO values of station 1 is a maximum (9.55 ppm), decreases downstream to stations 2 - 4 which are at a minimum (3.4 ppm), before increasing at station 5. The amount of BOD and TDS are highest at the 4th station and the amount of DO is lowest at this station, marking the 4th station as more highly polluted than the other stations. The physicochemical parameters improve at the 5th station due to pollutant degradation and dilution. Finally the point and nonpoint pollutant sources of Beshar river were determined and compared to the monitoring results.

Keywords: Beshar river, physicochemical parameter, waterpollution, Yasuj

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: Image forensics, computer graphics, classification, deep learning, convolutional neural networks.

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Authors: Werner Reichenfelser, Harald Hackl, Josef Hufgard, Karin Gstaltner, Margit Gfoehler

Abstract:

Training with Functional Electrical Stimulation (FES) has both physiological and psychological benefits for spinal cord injured subjects. Commonly used methods for quantification of spasticity have shown controversial reliability. In this study we propose a method for quick determination of spasticity in spinal cord injured subjects on a cycling and measurement system. 23 patients did training sessions on an instrumented mobile FES cycle three times a week over two months as part of their clinical rehabilitation program. Spasticity (MAS) and the legs resistance to the pedaling motion were assessed before and after the FES training and measurements were done on the subjects ability to pedal with our without motor assistance. Measurements with test persons with incomplete spastic paraplegia have shown that spasticity is decreased after a 30 min cycling training with functional electrical stimulation (FES).

Keywords: Spasticity, paraplegia, spinal cord injury, functional electrical stimulation.

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Authors: Mandep Kaur, Surbhi Gupta, Parvinder S. Sandhu, Jagdeep Kaur

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Steganography meaning covered writing. Steganography includes the concealment of information within computer files [1]. In other words, it is the Secret communication by hiding the existence of message. In this paper, we will refer to cover image, to indicate the images that do not yet contain a secret message, while we will refer to stego images, to indicate an image with an embedded secret message. Moreover, we will refer to the secret message as stego-message or hidden message. In this paper, we proposed a technique called RGB intensity based steganography model as RGB model is the technique used in this field to hide the data. The methods used here are based on the manipulation of the least significant bits of pixel values [3][4] or the rearrangement of colors to create least significant bit or parity bit patterns, which correspond to the message being hidden. The proposed technique attempts to overcome the problem of the sequential fashion and the use of stego-key to select the pixels.

Keywords: Steganography, Stego Image, RGB Image, Cryptography, LSB.

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Authors: Brigitte Rafael, Stefan M. Oertl

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Music segmentation is a key issue in music information retrieval (MIR) as it provides an insight into the internal structure of a composition. Structural information about a composition can improve several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization. The authors of this paper present the MTSSM framework, a twolayer framework for the multi-track segmentation of symbolic music. The strength of this framework lies in the combination of existing methods for local track segmentation and the application of global structure information spanning via multiple tracks. The first layer of the MTSSM uses various string matching techniques to detect the best candidate segmentations for each track of a multi-track composition independently. The second layer combines all single track results and determines the best segmentation for each track in respect to the global structure of the composition.

Keywords: Pattern Recognition, Music Information Retrieval, Machine Learning.

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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Authors: A. Soikkeli

Abstract:

Early 20^th century functionalism aimed at generalising living and rationalising construction, thus laying the foundation for the standardisation of construction components and products. From the 1930s onwards, all measurement and quality instructions for building products, different types of building components, descriptions of working methods complying with advisable building practises, planning, measurement and calculation guidelines, terminology, etc. were called standards. Standardisation was regarded as a necessary prerequisite for the mass production of housing.

This article examines the early stages of standardisation in Finland in the 1940s and 1950s, as reflected on the working history of an individual architect, ErkkiKoiso-Kanttila (1914-2006). In 1950 Koiso-Kanttila was appointed the Head of Design of the Finnish Association of Architects’ Building Standards Committee, a position which he held until 1958. His main responsibilities were the development of the RT Building Information File and compiling of the files.

Keywords: Architecture, Post WWII period, Reconstruction, Standardisation.

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Authors: Slim Yacoub, Kosai Raoof

Abstract:

The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.

Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.

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Authors: Antonio D. Lee, Steven X. Jiang

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A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.

Keywords: Cognitive performance, intuitive pattern recognition, situation awareness, urban search and rescue.

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

Abstract:

There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: Motivation, online learning, pedagogy, podcast.

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Authors: San Nah Sze, Wei King Tiong

Abstract:

The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.

Keywords: Multiple Traveling Salesman Problem, GeneticAlgorithm, Nearest Neighbor Algorithm, k-Means Clustering.

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Authors: S. Chabrier, G. Molle, E. Conte, C. Carlier

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Fishing has always been an essential component of the Polynesians- life. Fishhooks, mostly in pearl shell, found during archaeological excavations are the artifacts related to this activity the most numerous. Thanks to them, we try to reconstruct the ancient techniques of resources exploitation, inside the lagoons and offshore. They can also be used as chronological and cultural indicators. The shapes and dimensions of these artifacts allow comparisons and classifications used in both functional approach and chrono-cultural perspective. Hence it is very important for the ethno-archaeologists to dispose of reliable methods and standardized measurement of these artifacts. Such a reliable objective and standardized method have been previously proposed. But this method cannot be envisaged manually because of the very important time required to measure each fishhook manually and the quantity of fishhooks to measure (many hundreds). We propose in this paper a detailed acquisition protocol of fishhooks and an automation of every step of this method. We also provide some experimental results obtained on the fishhooks coming from three archaeological excavations sites.

Keywords: Automated measures, extraction, fishhook, segmentation.

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Authors: Aliakbar Golshani, Armin Ramezanzad

Abstract:

Tensile strength which is an important parameter of the rock for engineering applications is difficult to measure directly through physical experiment (i.e. uniaxial tensile test). Therefore, indirect experimental methods such as Brazilian test have been taken into consideration and some relations have been proposed in order to obtain the tensile strength for rocks indirectly. In this research, to calculate numerically the tensile strength for granitic rocks, Particle Flow Code in three-dimension (PFC3D) software were used. First, uniaxial compression tests were simulated and the tensile strength was determined for Inada granite (from a quarry in Kasama, Ibaraki, Japan). Then, by simulating Brazilian test condition for Inada granite, the tensile strength was indirectly calculated again. Results show that the tensile strength calculated numerically agrees well with the experimental results obtained from uniaxial tensile tests on Inada granite samples.

Keywords: Numerical Simulation, PFC, Tensile Strength, Brazilian Test.

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Authors: Rooholah Hasanizadeh, Saadan Zokaei

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In the context of sensor networks, where every few dB saving counts, the novel node cooperation schemes are reviewed where MIMO techniques play a leading role. These methods could be treated as joint approach for designing physical layer of their communication scenarios. Then we analyzed the BER performance of transmission diversity schemes under a general fading channel model and proposed a power allocation strategy to the transmitting sensor nodes. This approach is then compared to an equal-power assignment method and its performance enhancement is verified by the simulation. Another key point of the contribution lies in the combination of optimal power allocation and sensor nodes- cooperation in a transmission diversity regime (MISO). Numerical results are given through figures to demonstrate the optimality and efficiency of proposed combined approach.

Keywords: Optimal power allocation, cooperative MISO scheme, sensor networks, diversity branch.

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