Search results for: discrete-time neutral networks

Authors: Kati Kõrbe Kaare, Kristjan Kuhi, Ott Koppel

Abstract:

Transportation authorities need to provide the services and facilities that are critical to every country-s well-being and development. Management of the road network is becoming increasingly challenging as demands increase and resources are limited. Public sector institutions are integrating performance information into budgeting, managing and reporting via implementing performance measurement systems. In the face of growing challenges, performance measurement of road networks is attracting growing interest in many countries. The large scale of public investments makes the maintenance and development of road networks an area where such systems are an important assessment tool. Transportation agencies have been using performance measurement and modeling as part of pavement and bridge management systems. Recently the focus has been on extending the process to applications in road construction and maintenance systems, operations and safety programs, and administrative structures and procedures. To eliminate failure and dysfunctional consequences the importance of obtaining objective data and implementing evaluation instrument where necessary is presented in this paper

Keywords: Key performance indicators, performance measurement system, evaluation, system architecture.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

Abstract:

Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: D. Plikynas, S. Masteika, A. Budrionis

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This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.

Keywords: field-based coordination, multi-agent systems, information-rich social networks, pervasive information field

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Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read

Abstract:

The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Keywords: Wireless sensor networks, remote method invocation, transmission time.

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Authors: Miloš Šeda

Abstract:

Finding the shortest path between two positions is a fundamental problem in transportation, routing, and communications applications. In robot motion planning, the robot should pass around the obstacles touching none of them, i.e. the goal is to find a collision-free path from a starting to a target position. This task has many specific formulations depending on the shape of obstacles, allowable directions of movements, knowledge of the scene, etc. Research of path planning has yielded many fundamentally different approaches to its solution, mainly based on various decomposition and roadmap methods. In this paper, we show a possible use of visibility graphs in point-to-point motion planning in the Euclidean plane and an alternative approach using Voronoi diagrams that decreases the probability of collisions with obstacles. The second application area, investigated here, is focused on problems of finding minimal networks connecting a set of given points in the plane using either only straight connections between pairs of points (minimum spanning tree) or allowing the addition of auxiliary points to the set to obtain shorter spanning networks (minimum Steiner tree).

Keywords: motion planning, spanning tree, Steiner tree, Delaunay triangulation, Voronoi diagram.

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Authors: Maryam Mirdehghani, S. Amirhassan Monadjemi

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Web sites are rapidly becoming the preferred media choice for our daily works such as information search, company presentation, shopping, and so on. At the same time, we live in a period where visual appearances play an increasingly important role in our daily life. In spite of designers- effort to develop a web site which be both user-friendly and attractive, it would be difficult to ensure the outcome-s aesthetic quality, since the visual appearance is a matter of an individual self perception and opinion. In this study, it is attempted to develop an automatic system for web pages aesthetic evaluation which are the building blocks of web sites. Based on the image processing techniques and artificial neural networks, the proposed method would be able to categorize the input web page according to its visual appearance and aesthetic quality. The employed features are multiscale/multidirectional textural and perceptual color properties of the web pages, fed to perceptron ANN which has been trained as the evaluator. The method is tested using university web sites and the results suggested that it would perform well in the web page aesthetic evaluation tasks with around 90% correct categorization.

Keywords: Web Page Design, Web Page Aesthetic, Color Spaces, Texture, Neural Networks

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Authors: N. Drir, L. Barazane, M. Loudini

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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.

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Authors: F.Alilat, S.Loumi, H.Merrad, B.Sansal

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In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.

Keywords: Neural Networks, fuzzy ART, fuzzy ARTMAP, Remote sensing, multispectral Classification.

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Authors: Jamila Bhar, Ridha Ouni, Kholdoun Torki, Salem Nasri

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To support user mobility for a wireless network new mechanisms are needed and are fundamental, such as paging, location updating, routing, and handover. Also an important key feature is mobile QoS offered by the WATM. Several ATM network protocols should be updated to implement mobility management and to maintain the already ATM QoS over wireless ATM networks. A survey of the various schemes and types of handover is provided. Handover procedure allows guarantee the terminal connection reestablishment when it moves between areas covered by different base stations. It is useful to satisfy user radio link transfer without interrupting a connection. However, failure to offer efficient solutions will result in handover important packet loss, severe delays and degradation of QoS offered to the applications. This paper reviews the requirements, characteristics and open issues of wireless ATM, particularly with regard to handover. It introduces key aspects of WATM and mobility extensions, which are added in the fixed ATM network. We propose a flexible approach for handover management that will minimize the QoS deterioration. Functional entities of this flexible approach are discussed in order to achieve minimum impact on the connection quality when a MT crosses the BS.

Keywords: Handover, HDL synthesis, QoS, Wireless ATM.

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Authors: Karina Natali, Wei-Hwa Chiang

Abstract:

This study examines the stack ventilation performance of an office building located in Taipei, Taiwan. Atriums in this building act as stacks that facilitate buoyancy-driven ventilation. Computational Fluid Dynamic (CFD) simulations are used to identify interior airflow patterns, and then used these patterns to assess the building’s heat expulsion efficiency. Ambient temperatures of 20°C were adopted as the typical seasonal spring temperature range in Taipei. Further, “zero-wind” conditions are established to ensure simulation results reflected only the buoyancy effect. After checking results against neutral pressure level (NPL) level, airflow, air velocity, and indoor temperature stratification, the lower stack is modified to reduce the NPL in order to remove heat accumulated on the top floor.

Keywords: Natural ventilation, side outlet, stack effect, thermal comfort.

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Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: Big data, cooperative jamming, energy balance, physical layer, two-hop transmission, wireless security.

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Authors: Narendra Singh Yadav, R.P.Yadav

Abstract:

Mobile ad hoc network is a collection of mobile nodes communicating through wireless channels without any existing network infrastructure or centralized administration. Because of the limited transmission range of wireless network interfaces, multiple "hops" may be needed to exchange data across the network. In order to facilitate communication within the network, a routing protocol is used to discover routes between nodes. The primary goal of such an ad hoc network routing protocol is correct and efficient route establishment between a pair of nodes so that messages may be delivered in a timely manner. Route construction should be done with a minimum of overhead and bandwidth consumption. This paper examines two routing protocols for mobile ad hoc networks– the Destination Sequenced Distance Vector (DSDV), the table- driven protocol and the Ad hoc On- Demand Distance Vector routing (AODV), an On –Demand protocol and evaluates both protocols based on packet delivery fraction, normalized routing load, average delay and throughput while varying number of nodes, speed and pause time.

Keywords: AODV, DSDV, MANET, relative performance

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Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

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Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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Authors: Yanqi Yang, Chongshan Liao, Cheuk Hin Ho, Susan Bridges

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Aim: To investigate students’ perceptions of using e-models in an inquiry-based curriculum. Approach: 52 second-year dental students completed a pre- and post-test questionnaire relating to their perceptions of e-models and their use in inquiry-based learning. The pre-test occurred prior to any learning with e-models. The follow-up survey was conducted after one year's experience of using e-models. Results: There was no significant difference between the two sets of questionnaires regarding students’ perceptions of the usefulness of e-models and their willingness to use e-models in future inquiry-based learning. Most students preferred using both plaster models and e-models in tandem. Conclusion: Students did not change their attitude towards e-models and most of them agreed or were neutral that e-models are useful in inquiry-based learning. Whilst recognizing the utility of 3D models for learning, students' preference for combining these with solid models has implications for the development of haptic sensibility in an operative discipline.

Keywords: E-models, inquiry-based curriculum, education.

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Authors: Abdi T. Abdalla, Justinian Anatory

Abstract:

This paper investigates the possibility of improving throughputs of some Media Access Controls protocols such as ALOHA, slotted ALOHA and Carrier Sense Multiple Access with Collision Avoidance with the aim of increasing the performance of Powerline access networks. In this investigation, the real Powerline network topology in Tanzania located in Dar es Salaam City, Kariakoo area was used as a case study. During this investigation, Wireshark Network Protocol Analyzer was used to analyze data traffic of similar existing network for projection purpose and then the data were simulated using MATLAB. This paper proposed and analyzed three improvement techniques based on collision domain, packet length and combination of the two. From the results, it was found that the throughput of Carrier Sense Multiple Access with Collision Avoidance protocol improved noticeably while ALOHA and slotted ALOHA showed insignificant changes especially when the hybrid techniques were employed.

Keywords: Access Network, ALOHA, Broadband Powerline Communication, Slotted ALOHA, CSMA/CA and MAC Protocols.

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Authors: R. Asokan, A. M. Natarajan

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Mobile adhoc network (MANET) is a collection of mobile devices which form a communication network with no preexisting wiring or infrastructure. Multiple routing protocols have been developed for MANETs. As MANETs gain popularity, their need to support real time applications is growing as well. Such applications have stringent quality of service (QoS) requirements such as throughput, end-to-end delay, and energy. Due to dynamic topology and bandwidth constraint supporting QoS is a challenging task. QoS aware routing is an important building block for QoS support. The primary goal of the QoS aware protocol is to determine the path from source to destination that satisfies the QoS requirements. This paper proposes a new energy and delay aware protocol called energy and delay aware TORA (EDTORA) based on extension of Temporally Ordered Routing Protocol (TORA).Energy and delay verifications of query packet have been done in each node. Simulation results show that the proposed protocol has a higher performance than TORA in terms of network lifetime, packet delivery ratio and end-to-end delay.

Keywords: EDTORA, Mobile Adhoc Networks, QoS, Routing, TORA

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Authors: Abdelaziz Zaidi, Belkacem Ould Bouamama, Moncef Tagina

Abstract:

Bond Graph as a unified multidisciplinary tool is widely used not only for dynamic modelling but also for Fault Detection and Isolation because of its structural and causal proprieties. A binary Fault Signature Matrix is systematically generated but to make the final binary decision is not always feasible because of the problems revealed by such method. The purpose of this paper is introducing a methodology for the improvement of the classical binary method of decision-making, so that the unknown and identical failure signatures can be treated to improve the robustness. This approach consists of associating the evaluated residuals and the components reliability data to build a Hybrid Bayesian Network. This network is used in two distinct inference procedures: one for the continuous part and the other for the discrete part. The continuous nodes of the network are the prior probabilities of the components failures, which are used by the inference procedure on the discrete part to compute the posterior probabilities of the failures. The developed methodology is applied to a real steam generator pilot process.

Keywords: Redundancy relations, decision-making, Bond Graph, reliability, Bayesian Networks.

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Authors: He Ronghui, Ma Guoqing, Wang Chunlei, Fang Lan

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This paper focuses on wormhole attacks detection in wireless sensor networks. The wormhole attack is particularly challenging to deal with since the adversary does not need to compromise any nodes and can use laptops or other wireless devices to send the packets on a low latency channel. This paper introduces an easy and effective method to detect and locate the wormholes: Since beacon nodes are assumed to know their coordinates, the straight line distance between each pair of them can be calculated and then compared with the corresponding hop distance, which in this paper equals hop counts × node-s transmission range R. Dramatic difference may emerge because of an existing wormhole. Our detection mechanism is based on this. The approximate location of the wormhole can also be derived in further steps based on this information. To the best of our knowledge, our method is much easier than other wormhole detecting schemes which also use beacon nodes, and to those have special requirements on each nodes (e.g., GPS receivers or tightly synchronized clocks or directional antennas), ours is more economical. Simulation results show that the algorithm is successful in detecting and locating wormholes when the density of beacon nodes reaches 0.008 per m2.

Keywords: Beacon node, wireless sensor network, worm hole attack.

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Authors: Thanut Kallaka, Ching-Jong Wang

Abstract:

High level and high velocity flood flows are potentially harmful to bridge piers as evidenced in many toppled piers, and among them the single-column piers were considered as the most vulnerable. The flood flow characteristic parameters including drag coefficient, scouring and vortex shedding are built into a pier-flood interaction model to investigate structural safety against flood hazards considering the effects of local scouring, hydrodynamic forces, and vortex induced resonance vibrations. By extracting the pier-flood simulation results embedded in a neural networks code, two cases of pier toppling occurred in typhoon days were reexamined: (1) a bridge overcome by flash flood near a mountain side; (2) a bridge washed off in flood across a wide channel near the estuary. The modeling procedures and simulations are capable of identifying the probable causes for the tumbled bridge piers during heavy floods, which include the excessive pier bending moments and resonance in structural vibrations.

Keywords: Bridge piers, Neural networks, Scour depth, Structural safety, Vortex shedding

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Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read

Abstract:

The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data.  This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI.  Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Keywords: Wireless sensor networks, remote method invocation, transmission time.

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Authors: S. H. Kazmi, T. Ahmed, K. Javed, A. Ghani

Abstract:

In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.

Keywords: Islanding, under-frequency load shedding, frequency rate of change, static UFLS.

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Authors: Tessa Berg, Emma Guion Akdag

Abstract:

Summative feedback forms are used in academia for gathering data on course quality and student understanding. Students answer a series of questions based on the course they are soon to finish in these forms. Feedback forms are notorious for being homogenised and limiting and thus the data captured is often neutral and lacking in tacit emotional responses. This paper contrasts student feedback forms with collaborative drawing. We analyse 19 pictures drawn by international students on a pre-sessional course. Through visuals we present an approach to enable a holistic level of student understanding. Visuals communicate irrespective of possible language, cultural and educational barriers. This paper sought to discover if the pictures mirrored the feedback given on a typical feedback form. Findings indicate a considerable difference in the two approaches and thus we highlight the value of collaborative drawing as a complimentary resource to aid the understanding of student experience.

Keywords: Feedback forms, visualisation, student experience, collaborative drawing.

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Authors: Mofleh S. Awawdeh

Abstract:

Ten lactating multiparous Holstein cows were used in a cross-over design with two dietary treatments and 28-d periods (with 14 d as an adaptation) to study the effect of restaurant fat on milk production and composition. Each cow was offered 14.7 kg DM /d of the basal concentrate diet based on barley and corn (crude protein = 17.7%, neutral detergent fiber = 23.5%, and acid detergent fiber = 5.8% of dry matter) with free access to alfalfa. Dietary treatments were arranged as supplying each cow with 0 (CONTROL) or 150 g/day (RF) of restaurant fat. Supplemental RF did not significantly (P > 0.25) affect milk yield, composition, and composition yields, except for milk fat contents. Milk fat contents were depressed (P < 0.05) with supplemental RF. Our results indicate that RF could depress milk fat without affecting milk yield and that the depression in milk fat in response to RF precedes the depression in milk yield.

Keywords: Dairy Cows, Restaurant Fat, Lipids.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Keywords: Distributes estimation, sensor networks, adaptive filter, IDLMS.

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Authors: Jian-Wei Li, Yao-Tien Wang, Yi-Chun Chang

Abstract:

Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.

Keywords: k-nearest neighbor classification, learning community, Cooperative/Collaborative Learning and Environments.

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Authors: Ilham S. M. Elsayed

Abstract:

The purpose of this study is to investigate Alahsa Governorate status and its vulnerability to generate urban heat islands. Alahsa Governorate is a famous oasis in the Arabic Peninsula including several oil centers. Extensive literature review was done to collect previous relative data on the urban heat island of Alahsa Governorate. Data used for the purpose of this research were collected from authorized bodies who control weather station networks over Alahsa Governorate, Eastern Province, Saudi Arabia. Although, the number of weather station networks within the region is very limited and the analysis using GIS software and its techniques is difficult and limited, the data analyzed confirm an increase in temperature for more than 2 °C from 2004 to 2014. Such increase is considerable whenever human health and comfort are the concern. The increase of temperature within one decade confirms the availability of urban heat islands. The study concludes that, Alahsa Governorate is vulnerable to create urban heat islands and more attention should be drawn to strategic planning of the governorate that is developing with a high pace and considerable increasing levels of urbanization.

Keywords: Urban heat island, Alahsa Governorate, weather station, population density.

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Authors: Ogunduyile O. Oluwgbenga

Abstract:

Recent advancements in sensor technologies and Wireless Body Area Networks (WBANs) have led to the development of cost-effective healthcare devices which can be used to monitor and analyse a person-s physiological parameters from remote locations. These advancements provides a unique opportunity to overcome current healthcare challenges of low quality service provisioning, lack of easy accessibility to service varieties, high costs of services and increasing population of the elderly experienced globally. This paper reports on a prototype implementation of an architecture that seamlessly integrates Wireless Body Area Network (WBAN) with Web services (WS) to proactively collect physiological data of remote patients to recommend diagnostic services. Technologies based upon WBAN and WS can provide ubiquitous accessibility to a variety of services by allowing distributed healthcare resources to be massively reused to provide cost-effective services without individuals physically moving to the locations of those resources. In addition, these technologies can reduce costs of healthcare services by allowing individuals to access services to support their healthcare. The prototype uses WBAN body sensors implemented on arduino fio platforms to be worn by the patient and an android smart phone as a personal server. The physiological data are collected and uploaded through GPRS/internet to the Medical Health Server (MHS) to be analysed. The prototype monitors the activities, location and physiological parameters such as SpO2 and Heart Rate of the elderly and patients in rehabilitation. Medical practitioners would have real time access to the uploaded information through a web application.

Keywords: Android Smart phone, Arduino Fio, Web application server, Wireless Body Area Networks.

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Authors: Mohanad Alhabo, Naveed Nawaz, Mahmoud Al-Faris

Abstract:

The dense deployment of small cells is a promising solution to enhance the coverage and capacity of the heterogeneous networks (HetNets). However, the unplanned deployment could bring new challenges to the network ranging from interference, unnecessary handovers and handover failures. This will cause a degradation in the quality of service (QoS) delivered to the end user. In this paper, we propose an integrated Grey Rational Analysis Standard Deviation based handover method (GRA-SD) for HetNet. The proposed method integrates the Standard Deviation (SD) technique to acquire the weight of the handover metrics and the GRA method to select the best handover base station. The performance of the GRA-SD method is evaluated and compared with the traditional Multiple Attribute Decision Making (MADM) methods including Simple Additive Weighting (SAW) and VIKOR methods. Results reveal that the proposed method has outperformed the other methods in terms of minimizing the number of frequent unnecessary handovers and handover failures, in addition to improving the energy efficiency.

Keywords: Energy efficiency, handover, HetNets, MADM, small cells.

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Authors: Florin Gorunescu

Abstract:

Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.

Keywords: Endoscopic ultrasound elastography, exploratorydata analysis, neural networks, non-invasive cancer detection.

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

Abstract:

This paper aims to provide an interpretation of artificial neural networks (ANNs) and explore some of its implications. The interpretation views ANNs as a memory which encodes instances of experience. An experiment explores the behavior of encoding and retrieval of instances from memory. A localised representation ANN is created that allows control over encoding and retrieved memory sample size and is experimented with using the MNIST digits dataset. The relationship between input familiarity, conflict within retrieved samples, and error rates is described and demonstrated to be an effective driver for memory encoding. Results indicate that selective encoding and retrieval samples that allow detection of memory conflicts produce optimal performance, and that error rates are normally distributed with input familiarity and conflict. By using input familiarity and sample consistency to guide memory encoding, the number of encoding trials on the dataset were reduced to 18.33% of the training data while maintaining good recognition performance on the test data.

Keywords: Artificial Neural Networks, ANNs, representation, memory, conflict monitoring, confidence.

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