Search results for: indoor distribution networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3770

Search results for: indoor distribution networks

1730 Processing Web-Cam Images by a Neuro-Fuzzy Approach for Vehicular Traffic Monitoring

Authors: A. Faro, D. Giordano, C. Spampinato

Abstract:

Traffic management in an urban area is highly facilitated by the knowledge of the traffic conditions in every street or highway involved in the vehicular mobility system. Aim of the paper is to propose a neuro-fuzzy approach able to compute the main parameters of a traffic system, i.e., car density, velocity and flow, by using the images collected by the web-cams located at the crossroads of the traffic network. The performances of this approach encourage its application when the traffic system is far from the saturation. A fuzzy model is also outlined to evaluate when it is suitable to use more accurate, even if more time consuming, algorithms for measuring traffic conditions near to saturation.

Keywords: Neuro-fuzzy networks, computer vision, Fuzzy systems, intelligent transportation system.

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1729 Distributed Self-Healing Protocol for Unattended Wireless Sensor Network

Authors: E. Golden Julie, E. Sahaya Rose Vigita, S. Tamil Selvi

Abstract:

Wireless sensor network is vulnerable to a wide range of attacks. Recover secrecy after compromise, to develop technique that can detect intrusions and able to resilient networks that isolates the point(s) of intrusion while maintaining network connectivity for other legitimate users. To define new security metrics to evaluate collaborative intrusion resilience protocol, by leveraging the sensor mobility that allows compromised sensors to recover secure state after compromise. This is obtained with very low overhead and in a fully distributed fashion using extensive simulations support our findings.

Keywords: WSN security, intrusion resilience, compromised sensors, mobility.

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1728 Eight-State BB84: A C# Simulation

Authors: Liliana Zisu

Abstract:

The first and best known quantum protocol BB84, whose security is unconditional allows the transmission of a key with a length equal to that of the message. This key used with an encryption algorithm leads to an unbreakable cryptographic scheme. Despite advantages the protocol still can be improved in at least two aspects: its efficiency which is of about 50%, only half of the photons transmitted are used to create the encryption key and the second aspect refers to the communication that takes place on the classic channel, as it must be reduced or even eliminated. The paper presents a method that improves the two aspects of the BB84 protocol by using quantum memory and eight states of polarization. The implementation of both the proposed method and the BB84 protocol was done through a C# application.

Keywords: BB84, protocol, quantum cryptography, quantum key distribution.

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1727 Modeling UWSN Simulators – A Taxonomy

Authors: Christhu Raj, Rajeev Sukumaran

Abstract:

In this research article of modeling Underwater Wireless Sensor Network Simulators, we provide a comprehensive overview of the various currently available simulators used in UWSN modeling. In this work, we compare their working environment, software platform, simulation language, key features, limitations and corresponding applications. Based on extensive experimentation and performance analysis, we provide their efficiency for specific applications. We have also provided guidelines for developing protocols in different layers of the protocol stack, and finally these parameters are also compared and tabulated. This analysis is significant for researchers and designers to find the right simulator for their research activities.

Keywords: Underwater Wireless Sensor networks (UWSN), SUNSET, NS2, OPNET, WOSS, DESERT, RECORDS, Aqua- Sim, Aqua- Net Mate.

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1726 Monitoring and Prediction of Intra-Crosstalk in All-Optical Network

Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

Abstract:

Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: All-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk.

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1725 Red Diode Laser in the Treatment of Epidermal Diseases in PDT

Authors: Farhad H. Mustafa, Mohamad S. Jaafar , Asaad H. Ismail, Ahamad F. Omar, Zahra A. Timimi, Hend A. A. Houssein

Abstract:

The process of laser absorption in the skin during laser irradiation was a critical point in medical application treatments. Delivery the correct amount of laser light is a critical element in photodynamic therapy (PDT). More amounts of laser light able to affect tissues in the skin and small amount not able to enhance PDT procedure in skin. The knowledge of the skin tone laser dependent distribution of 635 nm radiation and its penetration depth in skin is a very important precondition for the investigation of advantage laser induced effect in (PDT) in epidermis diseases (psoriasis). The aim of this work was to estimate an optimum effect of diode laser (635 nm) on the treatment of epidermis diseases in different color skin. Furthermore, it is to improve safety of laser in PDT in epidermis diseases treatment. Advanced system analytical program (ASAP) which is a new approach in investigating the PDT, dependent on optical properties of different skin color was used in present work. A two layered Realistic Skin Model (RSM); stratum corneum and epidermal with red laser (635 nm, 10 mW) were used for irradiative transfer to study fluence and absorbance in different penetration for various human skin colors. Several skin tones very fair, fair, light, medium and dark are used to irradiative transfer. This investigation involved the principles of laser tissue interaction when the skin optically injected by a red laser diode. The results demonstrated that the power characteristic of a laser diode (635 nm) can affect the treatment of epidermal disease in various color skins. Power absorption of the various human skins were recorded and analyzed in order to find the influence of the melanin in PDT treatment in epidermal disease. A two layered RSM show that the change in penetration depth in epidermal layer of the color skin has a larger effect on the distribution of absorbed laser in the skin; this is due to the variation of the melanin concentration for each color.

Keywords: Photodynamic therapy, Realistic skin model, Laser, Light penetration, simulation, Optical properties of skin, Melanin.

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1724 Smart and Connected Aircraft Cabin: A Balancing Act between Operational Cabin Management, Airline Business and Passenger Expectations

Authors: Ralf God, Lothar Kerschgens, Leonardo Goratti, Steven Lemaire

Abstract:

Ubiquitous connectivity is a reality and a basic need for users on ground. Air travel connectivity in the cabin is also becoming increasingly important for passengers during cabin use. Wireless sensor networks that provide information to cabin management systems are being used by airlines to optimize cabin crew workload. In networked cabin systems, communications and digitally transmitted data must be managed by airlines in every direction. Security and privacy, information processing and knowledge management are the current and future requirements for a smart and connected cabin.

Keywords: Smart and connected cabin management, Internet of Things, power management, airline business.

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1723 Toward Indoor and Outdoor Surveillance Using an Improved Fast Background Subtraction Algorithm

Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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1722 An Architecture Based on Capsule Networks for the Identification of Handwritten Signature Forgery

Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

Abstract:

Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: Biometrics, deep learning, handwriting, signature forgery.

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1721 Performance Assessment and Optimization of the After-Sale Networks

Authors: H. Izadbakhsh, M.Hour Ali, A. Amirkhani, A. Montazeri, M. Saberi

Abstract:

The after–sales activities are nowadays acknowledged as a relevant source of revenue, profit and competitive advantage in most manufacturing industries. Top and middle management, therefore, should focus on the definition of a structured business performance measurement system for the after-sales business. The paper aims at filling this gap, and presents an integrated methodology for the after-sales network performance measurement, and provides an empirical application to automotive case companies and their official service network. This is the first study that presents an integrated multivariate approach for total assessment and improvement of after-sale services.

Keywords: Data Envelopment Analysis (DEA), Principal Component Analysis (PCA), Automotive companies, After-sale services.

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1720 A Comparative Study of Regional Climate Models and Global Coupled Models over Uttarakhand

Authors: Sudip Kumar Kundu, Charu Singh

Abstract:

As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: Global warming, rainfall, CMIP5, CORDEX, North Western Himalayan region.

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1719 History of Appearance and Distribution of Hijab and Its Types

Authors: K. Zh. Monkebayeva, N. Zh. Baitenova, A. A. Mustafayevа

Abstract:

According to historical legend, after the revelation of the holy Qur'an, which gave the hijab compulsory and women were required to cover the head and body with a handkerchief, and the general form of clothing in her veil, Muslim women have begun to comply with this worthy tradition. This article discusses the history of the rise and spread of the hijab and its types. And here is described in detail types of hijab and its intended value, style hijab in different regions. Now wearing the hijab, hijab in general the problem is important not only in the Arab world, but also in the world.

Keywords: Hijab, Islam, women's clothing, Arab world.

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1718 Stochastic Comparisons of Heterogeneous Samples with Homogeneous Exponential Samples

Authors: Nitin Gupta, Rakesh Kumar Bajaj

Abstract:

In the present communication, stochastic comparison of a series (parallel) system having heterogeneous components with random lifetimes and series (parallel) system having homogeneous exponential components with random lifetimes has been studied. Further, conditions under which such a comparison is possible has been established.

Keywords: Exponential distribution, Order statistics, Star ordering, Stochastic ordering.

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1717 Fuzzy Estimation of Parameters in Statistical Models

Authors: A. Falsafain, S. M. Taheri, M. Mashinchi

Abstract:

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.

Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.

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1716 Research and Development of Net-Centric Information Sharing Platform

Authors: Xiaoqing Wang, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

Abstract:

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: Net-centric environment, Information sharing, Metadata registry and catalog, Cross-domain data access control.

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1715 A New Scheduling Algorithm Based on Traffic Classification Using Imprecise Computation

Authors: Farzad Abtahi, Sahar Khanmohamadi, Bahram Sadeghi Bigham

Abstract:

Wireless channels are characterized by more serious bursty and location-dependent errors. Many packet scheduling algorithms have been proposed for wireless networks to guarantee fairness and delay bounds. However, most existing schemes do not consider the difference of traffic natures among packet flows. This will cause the delay-weight coupling problem. In particular, serious queuing delays may be incurred for real-time flows. In this paper, it is proposed a scheduling algorithm that takes traffic types of flows into consideration when scheduling packets and also it is provided scheduling flexibility by trading off video quality to meet the playback deadline.

Keywords: Data communication, Real-time, Scheduling, Video transport.

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1714 Application of Computational Intelligence for Sensor Fault Detection and Isolation

Authors: A. Jabbari, R. Jedermann, W. Lang

Abstract:

The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.

Keywords: Fault detection and Isolation, Neural network, Temperature measurement, measurement approximation and classification.

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1713 A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: Average run length, Bernoulli CUSUM chart, beta binomial posterior predictive distribution, clinical indicator, health care organization, highest posterior density interval.

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1712 On Improving Breast Cancer Prediction Using GRNN-CP

Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: Neural network, conformal prediction, cancer classification, regression.

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1711 Annual Power Load Forecasting Using Support Vector Regression Machines: A Study on Guangdong Province of China 1985-2008

Authors: Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang

Abstract:

Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

Keywords: combinatorial algorithm, data mining, load forecasting, support vector machines

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1710 Performance Enhancement Employing Vertical Beamforming for FFR Technique

Authors: P. Chaipanya, P. Uthansakul, M. Uthansakul

Abstract:

This paper proposes a vertical beamforming concept to a cellular network employing Fractional Frequency Reuse technique including with cell sectorization. Two different beams are utilized in cell-center and cell-edge, separately. The proposed concept is validated through computer simulation in term of SINR and channel capacity. Also, comparison when utilizing horizontal and vertical beam formation is in focus. The obtained results indicate that the proposed concept can improve the performance of the cellular networks comparing with the one using horizontal beamforming.

Keywords: Beamforming, Fractional Frequency Reuse, Inter- Cell Interference, cell sectorization.

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1709 Influence of Temperature and Precipitation Changes on Desertification

Authors: Kukuri Tavartkiladze, Nana Bolashvili

Abstract:

The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: Climate change, aridity, desertification, precipitation.

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1708 Security Management System of Cellular Communication: Case Study

Authors: Othman O. Khalifa, Abdulrazzag Aburas, A. Al Bagul, Meftah Hrairi, Muhammad Shahril bin Shahbuddin, Harman bin Mat Kasa

Abstract:

Cellular communication is being widely used by all over the world. The users of handsets are increasing due to the request from marketing sector. The important aspect that has to be touch in this paper is about the security system of cellular communication. It is important to provide users with a secure channel for communication. A brief description of the new GSM cellular network architecture will be provided. Limitations of cellular networks, their security issues and the different types of attacks will be discussed. The paper will go over some new security mechanisms that have been proposed by researchers. Overall, this paper clarifies the security system or services of cellular communication using GSM. Three Malaysian Communication Companies were taken as Case study in this paper.

Keywords: GSM, Security systems, SIM CARD, IMSI, Authentication.

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1707 A Comparative Study on Different Approaches to Evaluate Ship Equilibrium Point

Authors: Alessandro A. Zizzari, Francesca Calabrese, Giovanni Indiveri, Andrea Coraddu, Diego Villa

Abstract:

The aim of this paper is to present a comparative study on two different methods for the evaluation of the equilibrium point of a ship, core issue for designing an On Board Stability System (OBSS) module that, starting from geometry information of a ship hull, described by a discrete model in a standard format, and the distribution of all weights onboard calculates the ship floating conditions (in draught, heel and trim).

Keywords: Algorithms, Computer applications, Equilibrium, Marine applications, Stability System.

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1706 Decentralised Edge Authentication in the Industrial Enterprise IoT Space

Authors: C. P. Autry, A.W. Roscoe

Abstract:

Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: Authentication, enterprise IoT cybersecurity, public key infrastructure, trusted third party.

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1705 ANN-Based Classification of Indirect Immuno Fluorescence Images

Authors: P. Soda, G.Iannello

Abstract:

In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.

Keywords: Artificial neural networks, computer aided diagnosis, image classification, indirect immuno-fluorescence, pattern recognition.

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1704 Combining Diverse Neural Classifiers for Complex Problem Solving: An ECOC Approach

Authors: R. Ebrahimpour, M. Abbasnezhad Arabi, H. Babamiri Moghaddam

Abstract:

Combining classifiers is a useful method for solving complex problems in machine learning. The ECOC (Error Correcting Output Codes) method has been widely used for designing combining classifiers with an emphasis on the diversity of classifiers. In this paper, in contrast to the standard ECOC approach in which individual classifiers are chosen homogeneously, classifiers are selected according to the complexity of the corresponding binary problem. We use SATIMAGE database (containing 6 classes) for our experiments. The recognition error rate in our proposed method is %10.37 which indicates a considerable improvement in comparison with the conventional ECOC and stack generalization methods.

Keywords: Error correcting output code, combining classifiers, neural networks.

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1703 Comparative Study of Scheduling Algorithms for LTE Networks

Authors: Samia Dardouri, Ridha Bouallegue

Abstract:

Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, Multimedia flows, Scheduling algorithms.

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1702 Study on Optimization of Air Infiltration at Entrance of a Commercial Complex in Zhejiang Province

Authors: Yujie Zhao, Jiantao Weng

Abstract:

In the past decade, with the rapid development of China's economy, the purchasing power and physical demand of residents have been improved, which results in the vast emergence of public buildings like large shopping malls. However, the architects usually focus on the internal functions and streamlines of these buildings, ignoring the impact of the environment on the subjective feelings of building users. Only in Zhejiang province, the infiltration of cold air in winter frequently occurs at the entrance of sizeable commercial complex buildings that have been in operation, which will affect the environmental comfort of the building lobby and internal public spaces. At present, to reduce these adverse effects, it is usually adopted to add active equipment, such as setting air curtains to block air exchange or adding heating air conditioners. From the perspective of energy consumption, the infiltration of cold air into the entrance will increase the heat consumption of indoor heating equipment, which will indirectly cause considerable economic losses during the whole winter heating stage. Therefore, it is of considerable significance to explore the suitable entrance forms for improving the environmental comfort of commercial buildings and saving energy. In this paper, a commercial complex with apparent cold air infiltration problem in Hangzhou is selected as the research object to establish a model. The environmental parameters of the building entrance, including temperature, wind speed, and infiltration air volume, are obtained by Computational Fluid Dynamics (CFD) simulation, from which the heat consumption caused by the natural air infiltration in the winter and its potential economic loss is estimated as the objective metric. This study finally obtains the optimization direction of the building entrance form of the commercial complex by comparing the simulation results of other local commercial complex projects with different entrance forms. The conclusions will guide the entrance design of the same type of commercial complex in this area.

Keywords: Air infiltration, commercial complex, heat consumption, CFD simulation.

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1701 Database Compression for Intelligent On-board Vehicle Controllers

Authors: Ágoston Winkler, Sándor Juhász, Zoltán Benedek

Abstract:

The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.

Keywords: Data analysis, data compression, differentialencoding, run-length encoding, vehicle control.

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