Search results for: Wireless body area networks

Authors: Wen-Tsann Lin, Yung-Tsan Jou, Yih-Chuan Wu, Yuan-Du Hsiao

Abstract:

The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.

Keywords: Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.

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Authors: Kriuk Boris, Kriuk Fedor

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This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we present a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Keywords: Siamese networks, Semantic textual similarity, Similarity functions, STS Benchmark dataset, Threshold selection.

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: Big Data, Social Networks, Sentiment Analysis.

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Authors: Nadia Hmad, Tony Allen

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This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia dialectic and 34 speakers from the Center for Spoken Language Understanding (CSLU2002) database of speakers with different dialectics from 12 Arabic countries. Results for the KAPD and CSLU2002 Arabic databases show phoneme recognition performances of 72.31% and 38.20% respectively.

Keywords: Arabic phonemes recognition, echo state networks (ESNs), neural networks (NNs), supervised learning.

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Authors: M. Guillard, M. Philippe, F. Laurent, J. Martinerie, J. P. Lachaux, G. Florence

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One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.

Keywords: Classification, EEG Synchrony, alpha, resting situation.

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

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Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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Authors: Roza Dastres, Mohsen Soori

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Networks are vulnerable devices due to their basic feature of facilitating remote access and data communication. The information in the networks needs to be kept secured and safe in order to provide an effective communication and sharing device in the web of data. Due to challenges and threats of the data in networks, the network security is one of the most important considerations in information technology infrastructures. As a result, the security measures are considered in the network in order to decrease the probability of accessing the secured data by the hackers. The purpose of network security is to protect the network and its components from unauthorized access and abuse in order to provide a safe and secured communication device for the users. In the present research work a review in recent development of network threats and security measures is presented and future research works are also suggested. Different attacks to the networks and security measured against them are discussed in order to increase security in the web of data. So, new ideas in the network security systems can be presented by analyzing the published papers in order to move forward the research field.

Keywords: Network threats, network security, security measures, firewalls.

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Authors: Chien-Sheng Chen, Szu-Lin Su, Chuan-Der Lu

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Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

Keywords: Time of arrival (TOA), angle of arrival (AOA), non-line-of-sight (NLOS).

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

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Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder Bias Voltage, switching voltage, radio-over-fiber, RF gain.

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Authors: A. Pajaziti, H. Cana

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In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: Robotic Arm, Neural Network, Genetic Algorithm, Optimization.

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb

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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.

Keywords: ElectroMyoGraphic (EMG) signals, Experimental approach, Handwriting process, Radial Basis Functions (RBF) neural networks, Velocity Modeling.

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Authors: Karim A. Tahboub

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This article discusses the problem of estimating the orientation of inclined ground on which a human subject stands based on information provided by the vestibular system consisting of the otolith and semicircular canals. It is assumed that body segments are not necessarily aligned and thus forming an open kinematic chain. The semicircular canals analogues to a technical gyrometer provide a measure of the angular velocity whereas the otolith analogues to a technical accelerometer provide a measure of the translational acceleration. Two solutions are proposed and discussed. The first is based on a stand-alone Kalman filter that optimally fuses the two measurements based on their dynamic characteristics and their noise properties. In this case, no body dynamic model is needed. In the second solution, a central extended disturbance observer that incorporates a body dynamic model (internal model) is employed. The merits of both solutions are discussed and demonstrated by experimental and simulation results.

Keywords: Kalman filter, orientation estimation, otolith-canalfusion, vestibular system.

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity is associated with increased fat mass as well as fat percentage. Minerals are the elements, which are of vital importance. In this study, the relationships between body as well as bone mineral profile and the percentage as well as mass values of fat, fat-free portion, protein, skeletal muscle were evaluated in adult men with normal body mass index (N-BMI), and those classified according to different stages of obesity. A total of 103 adult men classified into five groups participated in this study. Ages were within 19-79 years range. Groups were N-BMI (Group 1), overweight (OW) (Group 2), first level of obesity (FLO) (Group 3), second level of obesity (SLO) (Group 4) and third level of obesity (TLO) (Group 5). Anthropometric measurements were performed. BMI values were calculated. Obesity degree, total body fat mass, fat percentage, basal metabolic rate (BMR), visceral adiposity, body mineral mass, body mineral percentage, bone mineral mass, bone mineral percentage, fat-free mass, fat-free percentage, protein mass, protein percentage, skeletal muscle mass and skeletal muscle percentage were determined by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical package (SPSS) for Windows Version 16.0 was used for statistical evaluations. The values below 0.05 were accepted as statistically significant. All the groups were matched based upon age (p > 0.05). BMI values were calculated as 22.6 ± 1.7 kg/m², 27.1 ± 1.4 kg/m², 32.0 ± 1.2 kg/m², 37.2 ± 1.8 kg/m², and 47.1 ± 6.1 kg/m² for groups 1, 2, 3, 4, and 5, respectively. Visceral adiposity and BMR values were also within an increasing trend. Percentage values of mineral, protein, fat-free portion and skeletal muscle masses were decreasing going from normal to TLO. Upon evaluation of the percentages of protein, fat-free portion and skeletal muscle, statistically significant differences were noted between NW and OW as well as OW and FLO (p < 0.05). However, such differences were not observed for body and bone mineral percentages. Correlation existed between visceral adiposity and BMI was stronger than that detected between visceral adiposity and obesity degree. Correlation between visceral adiposity and BMR was significant at the 0.05 level. Visceral adiposity was not correlated with body mineral mass but correlated with bone mineral mass whereas significant negative correlations were observed with percentages of these parameters (p < 0.001). BMR was not correlated with body mineral percentage whereas a negative correlation was found between BMR and bone mineral percentage (p < 0.01). It is interesting to note that mineral percentages of both body as well as bone are highly affected by the visceral adiposity. Bone mineral percentage was also associated with BMR. From these findings, it is plausible to state that minerals are highly associated with the critical stages of obesity as prominent parameters.

Keywords: Bone, men, minerals, obesity.

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Authors: Xiaomei Wang, Shouming Zhong

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In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known results. One example is given to show the feasibility and effectiveness of our results.

Keywords: Bi-directional associative memory (BAM) neural networks, mixed delays, Lyapunov stability theory, contraction mapping theorem, existence, equilibrium, globally exponential stability.

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Authors: Anwar Sadat

Abstract:

Today, the Internet based communication has widen the opportunity of event monitoring system in the medical field. There is always a need of analyzing and designing secure and reliable mobile communication between the hospital and biomedical engineers mobile units. This study has been carried out to find possible solution using SIP-based event notification for alerting the technical staff about the Biomedical Device (BMD) status and Patients treatment session. The Session Initiation Protocol (SIP) can be used to create a medical event notification system. SIP can work on a variety of devices. Its adoption as the protocol of choice for third generation wireless networks allows for a robust and scalable environment. One of the advantages of SIP is that it supports personal mobility through the separation of user addressing and device addressing. The solution for Telemed alert notification system is based on SIP - Specific Event Notification. The aim of this project is to extend mobility service to the hospital technicians who are using Telemedicine system.

Keywords: Biomedical, Mobility Service, Notify, Proxy Server, SIP, Subscribe, Telemedicine.

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Authors: Toshihiko Sasama, Takahide Yanaka, Kazunori Sugahara, Hiroshi Masuyama

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In order to monitor for traffic traversal, sensors can be deployed to perform collaborative target detection. Such a sensor network achieves a certain level of detection performance with the associated costs of deployment and routing protocol. This paper addresses these two points of sensor deployment and routing algorithm in the situation where the absolute quantity of sensors or total energy becomes insufficient. This discussion on the best deployment system concluded that two kinds of deployments; Normal and Power law distributions, show 6 and 3 times longer than Random distribution in the duration of coverage, respectively. The other discussion on routing algorithm to achieve good performance in each deployment system was also addressed. This discussion concluded that, in place of the traditional algorithm, a new algorithm can extend the time of coverage duration by 4 times in a Normal distribution, and in the circumstance where every deployed sensor operates as a binary model.

Keywords: binary sensor, coverage rate, power energy consumption, routing algorithm, sensor deployment

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: Diah Tri Widayati, Sunendar, Kresno Suharto, Pudji Asuti, Aris Junaid

Abstract:

Eight Etawah cross bred does were divided into two groups based on body condition score (BCS). Group I (BSC 2, body weight 25-30 kg; n = 4), and Group II (BSC 3, body weight, 35-40 kg, n=4). All does received intravaginal controlled internal drug release devices (CIDR) for 10 days, and a prostaglandin F2α at 48 h before CIDR removal. Estrus detection was carried out using vasectomized buck. Vaginal epithelium was taken to determine estrus cycle. Blood samples were taken every 3-6 hours, started from moment of CIDR removal until the end of estrus. The results showed vaginal histological indicated estrus occurred at the hours of 25 to 60 and 30 to 70 post CIDR removal in BCS 2 and 3, respectively. Progesterone peak of BCS 2 and BCS 3 were 0.18±0.31 and 0.48±0.31 ng/mL on the hour 0 post CIDR removal. Estradiol -17ß peak of each group was 53.25±35.08 and 89.91±92.84 pg/mL at 48 post CIDR removal. LH surge only occurred on BCS 3 groups, the LH concentrations were 9.9± 9.1; 4.5± 4.0; and 18.2± 9.1 ng/mL at 45, 48 and 51 hours post CIDR removal, respectively. It was concluded that the BCS had effects on vaginal histological changes and LH surge.

Keywords: Estrus synchronization, Vaginal histological changes, Progesterone, Estradiol -17ß , LH

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Authors: John Hadden, Ashutosh Tiwari, Rajkumar Roy, Dymitr Ruta

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The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customer complaints data and provides a comparative analysis of neural networks, regression trees and regression in their capabilities of predicting customer churn.

Keywords: Churn, Decision Trees, Neural Networks, Regression.

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Authors: Biplab Bag

Abstract:

In this paper, the design of a coaxial feed single layer rectangular microstrip patch antenna for three different wireless communication band applications is presented. The proposed antenna is designed by using substrate Roger RT/duroid 5880 having permittivity of about 2.2 and tangent loss of 0.0009. The characteristics of the substrate are designed and to evaluate the performance of modeled antenna using HFSS v.11 EM simulator, from Ansoft. The proposed antenna has small in size and operates at 2.25GHz, 3.76GHz and 5.23GHz suitable for mobile satellite service (MSS) network, WiMAX and WLAN applications. The dimension of the patch and slots are optimized to obtain these desired functional frequency ranges. The simulation results with frequency response, radiation pattern and return loss, VSWR, Input Impedance are presented with appropriate table and graph.

Keywords: Microstrip, Tangent Loss, MSS, WiMAX, WLAN, Radiation Pattern, Return Loss, VSWR.

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Authors: N. Ojaroudi Parchin, H. Jahanbakhsh Basherlou, Y. Al-Yasir, A. M. Abdulkhaleq, R. A. Abd-Alhameed, P. S. Excell

Abstract:

A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1x8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.

Keywords: MM-wave communications, multi-sector array, patch antenna, small cell networks.

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Authors: Samia Salah, M’hamed Hadj Sadok, Abderrezak Guessoum

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In this paper, we propose a new modular approach called neuroglial consisting of two neural networks slow and fast which emulates a biological reality recently discovered. The implementation is based on complex multi-time scale systems; validation is performed on the model of the asynchronous machine. We applied the geometric approach based on the Gerschgorin circles for the decoupling of fast and slow variables, and the method of singular perturbations for the development of reductions models.

This new architecture allows for smaller networks with less complexity and better performance in terms of mean square error and convergence than the single network model.

Keywords: Gerschgorin’s Circles, Neuroglial Network, Multi time scales systems, Singular perturbation method.

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Authors: Jean-Pierre Dubois, Rania Minkara, Rafic Ayoubi

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Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.

Keywords: Bit error rate, femto-internet cells, generalized maximal ratio combining, signal-to-scattering noise ratio.

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Authors: Po-Hsieh Lin, Jyi-Tsong Lin

Abstract:

A vertical SOI-based MOSFET with trench body structure operated as 1T DRAM cell at various temperatures has been studied and investigated. Different operation temperatures are assigned for the device for its performance comparison, thus the thermal stability is carefully evaluated for the future memory device applications. Based on the simulation, the vertical SOI-based MOSFET with trench body structure demonstrates the electrical characteristics properly and possess conspicuous kink effect at various operation temperatures. Transient characteristics were also performed to prove that its programming window values and retention time behaviors are acceptable when the new 1T DRAM cell is operated at high operation temperature.

Keywords: SOI, 1T DRAM, thermal stability.

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Authors: Liu Shengnan, Sun Liping, Zhu Jianxun

Abstract:

Based on three dimensional potential flow theory and hinged rigid body motion equations, structure RAOs of Pelamis wave energy converter is analyzed. Analysis of numerical simulation is carried out on Pelamis in the irregular wave conditions, and the motion response of structures and total generated power is obtained. The paper analyzes influencing factors on the average power including diameter of floating body, section form of floating body, draft, hinged stiffness and damping. The optimum parameters are achieved in Zhejiang Province. Compared with the results of the pelamis experiment made by Glasgow University, the method applied in this paper is feasible.

Keywords: Pelamis, Hinge, Floating multibody, Wave energy

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Authors: Muhammad Suryanegara, Dendi Wijayatullah, Dadang Gunawan

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We review a knowledge extractor model in constructing 3G Killer Applications. The success of 3G is essential for Government as it became part of Telecommunications National Strategy. The 3G wireless technologies may reach larger area and increase country-s ICT penetration. In order to understand future customers needs, the operators require proper information (knowledge) lying inside. Our work approached future customers as complex system where the complex knowledge may expose regular behavior. The hidden information from 3G future customers is revealed by using fractal-based questionnaires. Afterward, further statistical analysis is used to match the results with operator-s strategic plan. The developments of 3G applications also consider its saturation time and further improvement of the application.

Keywords: 3G Killer Applications, Knowledge, Telecommunications Strategy.

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Authors: Nader Nabhani, Amir Tofighi

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Nanotechnology is the science of creating, using and manipulating objects which have at least one dimension in range of 0.1 to 100 nanometers. In other words, nanotechnology is reconstructing a substance using its individual atoms and arranging them in a way that is desirable for our purpose. The main reason that nanotechnology has been attracting attentions is the unique properties that objects show when they are formed at nano-scale. These differing characteristics that nano-scale materials show compared to their nature-existing form is both useful in creating high quality products and dangerous when being in contact with body or spread in environment. In order to control and lower the risk of such nano-scale particles, the main following three topics should be considered: 1) First of all, these materials would cause long term diseases that may show their effects on body years after being penetrated in human organs and since this science has become recently developed in industrial scale not enough information is available about their hazards on body. 2) The second is that these particles can easily spread out in environment and remain in air, soil or water for very long time, besides their high ability to penetrate body skin and causing new kinds of diseases. 3) The third one is that to protect body and environment against the danger of these particles, the protective barriers must be finer than these small objects and such defenses are hard to accomplish. This paper will review, discuss and assess the risks that human and environment face as this new science develops at a high rate.

Keywords: Nanotechnology, risk assessment, environment.

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Authors: Hsu-Yung Cheng, Victor Gau, Chih-Wei Huang, Jenq-Neng Hwang, Chih-Chang Yu

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In order to achieve better road utilization and traffic efficiency, there is an urgent need for a travel information delivery mechanism to assist the drivers in making better decisions in the emerging intelligent transportation system applications. In this paper, we propose a relayed multicast scheme under heterogeneous networks for this purpose. In the proposed system, travel information consisting of summarized traffic conditions, important events, real-time traffic videos, and local information service contents is formed into layers and multicasted through an integration of WiMAX infrastructure and Vehicular Ad hoc Networks (VANET). By the support of adaptive modulation and coding in WiMAX, the radio resources can be optimally allocated when performing multicast so as to dynamically adjust the number of data layers received by the users. In addition to multicast supported by WiMAX, a knowledge propagation and information relay scheme by VANET is designed. The experimental results validate the feasibility and effectiveness of the proposed scheme.

Keywords: Intelligent Transportation Systems, RelayedMulticast, WiMAX, Vehicular Ad hoc Networks (VANET).

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Authors: Yasser F. Hassan

Abstract:

The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: Rough Sets, Rough Neural Networks, Cellular Automata, Image Processing.

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