Search results for: data center

Authors: Eklas Hossain, Sheroz Khan, Ahad Ali

Abstract:

Power line communications may be used as a data communication channel in public and indoor distribution networks so that it does not require the installing of new cables. Industrial low voltage distribution network may be utilized for data transfer required by the on-line condition monitoring of electric motors. This paper presents a pilot distribution network for modeling low voltage power line as data transfer channel. The signal attenuation in communication channels in the pilot environment is presented and the analysis is done by varying the corresponding parameters for the signal attenuation.

Keywords: Data communication, indoor distribution networks, low voltage, power line.

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Authors: Norashikin Ahmad, Damminda Alahakoon

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Self-organizing map (SOM) provides both clustering and visualization capabilities in mining data. Dynamic self-organizing maps such as Growing Self-organizing Map (GSOM) has been developed to overcome the problem of fixed structure in SOM to enable better representation of the discovered patterns. However, in mining large datasets or historical data the hierarchical structure of the data is also useful to view the cluster formation at different levels of abstraction. In this paper, we present a technique to generate concept trees from the GSOM. The formation of tree from different spread factor values of GSOM is also investigated and the quality of the trees analyzed. The results show that concept trees can be generated from GSOM, thus, eliminating the need for re-clustering of the data from scratch to obtain a hierarchical view of the data under study.

Keywords: dynamic self-organizing map, concept formation, clustering.

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Authors: Arash Kosari, Ali Araghi

Abstract:

A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: Absorption, data throughput, depolarization, optical fiber.

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Authors: George E. Tsekouras, Dimitris Papageorgiou, Sotiris Kotsiantis, Christos Kalloniatis, Panagiotis Pintelas

Abstract:

We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters.

Keywords: Categorical data, cultural data, fuzzy logic clustering, fuzzy c-modes, cluster validity index.

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Authors: A. Harifi, A. Aghagolzadeh

Abstract:

The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.

Keywords: Pattern recognition, Persian digits, NeuralNetwork.

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Authors: N. Mansouri, A. Asadi

Abstract:

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: Data grid, data replication, simulation, replica selection, replica placement.

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Authors: Zhe JIN, Motomichi TOYAMA

Abstract:

PPX(Pretty Printer for XML) is a query language that offers a concise description method of formatting the XML data into HTML. In this paper, we propose a simple specification of formatting method that is a combination description of automatic layout operators and variables in the layout expression of the GENERATE clause of PPX. This method can automatically format irregular XML data included in a part of XML with layout decision rule that is referred to DTD. In the experiment, a quick comparison shows that PPX requires far less description compared to XSLT or XQuery programs doing same tasks.

Keywords: PPX, Irregular XML data, Layout decision rule, HTML.

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Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson, Göran Falkman

Abstract:

Data mining has been used very frequently to extract hidden information from large databases. This paper suggests the use of decision trees for continuously extracting the clinical reasoning in the form of medical expert-s actions that is inherent in large number of EMRs (Electronic Medical records). In this way the extracted data could be used to teach students of oral medicine a number of orderly processes for dealing with patients who represent with different problems within the practice context over time.

Keywords: Data mining, Oral Medicine, Decision Trees, WEKA.

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Authors: Hanieh Alipour, Alireza Nemaney Pour

Abstract:

One of the most important applications of wireless sensor networks is data collection. This paper proposes as efficient approach for data collection in wireless sensor networks by introducing Member Forward List. This list includes the nodes with highest priority for forwarding the data. When a node fails or dies, this list is used to select the next node with higher priority. The benefit of this node is that it prevents the algorithm from repeating when a node fails or dies. The results show that Member Forward List decreases power consumption and latency in wireless sensor networks.

Keywords: Data Collection, Wireless Sensor Network, SensorNode, Tree-Based

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Authors: Binu Thomas, Raju G., Sonam Wangmo

Abstract:

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algorithm and its extensions, we propose a modification to the cmeans algorithm to overcome the limitations of it in calculating the new cluster centers and in finding the membership values with natural data. The efficiency of the new modified method is demonstrated on real data collected for Bhutan-s Gross National Happiness (GNH) program.

Keywords: Adaptive fuzzy clustering, clustering, fuzzy logic, fuzzy clustering, c-means.

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Authors: Seiya Teshima, Kazushige Magatani

Abstract:

Currently, many types of no-reversible compressed sound source, represented by MP3 (MPEG Audio Layer-3) are popular in the world and they are widely used to make the music file size smaller. The sound data created in this way has less information as compared to pre-compressed data. The objective of this study is by analyzing EEG to determine if people can recognize such difference as differences in sound. A measurement system that can measure and analyze EEG when a subject listens to music were experimentally developed. And ten subjects were studied with this system. In this experiment, a WAVE formatted music data and a MP3 compressed music data that is made from the WAVE formatted data were prepared. Each subject was made to hear these music sources at the same volume. From the results of this experiment, clear differences were confirmed between two wound sources.

Keywords: EEG, Biological signal , Sound , MP3

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Authors: Sašo Pečnik, Borut Žalik

Abstract:

This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR datasets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: Filtering, graphics, level-of-details, LiDAR, realtime visualization.

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Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.

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Authors: Nicole S. McKinney

Abstract:

The purpose of the study was to determine if, among 32 brain injured adults in community rehabilitation programs, there is a statistically significant relationship between the degree of severity of brain injury and these adults- level of self-esteem and stress. The researcher hypothesized there would be a statistically significant difference and a statistically significant relationship in self-esteem and stress levels among and TBI adults. A Pearson product moment correlational analysis was implemented and results found a statistically significant relationship between self-esteem and stress levels. Future recommendations were suggested upon completion of research.

Keywords: anxiety, community recovery center, head-trauma persons, self-concept

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Authors: Joo-Hyung Oh, Dongwan Kang, JunHyung Cho, Chaetae Im

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As the mobile Internet has become widespread in recent years, communication based on mobile networks is increasing. As a result, security threats have been posed with regard to the abnormal traffic of mobile networks, but mobile security has been handled with focus on threats posed by mobile malicious codes, and researches on security threats to the mobile network itself have not attracted much attention. In mobile networks, the IP address of the data packet is a very important factor for billing purposes. If one mobile terminal use an incorrect IP address that either does not exist or could be assigned to another mobile terminal, billing policy will cause problems. We monitor and analyze 3G mobile data networks traffics for a period of time and finds some abnormal IP packets. In this paper, we analyze the reason for abnormal IP packets on 3G Mobile Data Networks. And we also propose an algorithm based on IP address table that contains addresses currently in use within the mobile data network to detect abnormal IP packets.

Keywords: WCDMA, 3G, Abnormal IP address, Mobile Data Network Attack

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

Abstract:

In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: Ontology, OpenStreetMap, visually impaired people, TTS, taxonomy.

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Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

Abstract:

In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

Abstract:

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: Infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer.

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Authors: S. Lecheb, A. Chellil, H. Mechakra, A. Zeggane, H. Kebir

Abstract:

In this work, repaired crack in 6061- T6 aluminum plate with composite patches presented, firstly we determine the displacement, strain and stress, also the first six mode shape of the plate, secondly we took the same model adding central crack initiation, which is located in the center of the plate, its seize vary from 20 mm to 60 mm and we compare the first results with second. Thirdly we repair various cracks with composite patch (carbon/ epoxy) and for (2 layers, 4 layers). Finally the comparison of stress, strain, displacement and six first natural frequencies between un-cracked specimen, crack propagation and composite patch repair.

Keywords: Composite patch repair, crack growth, aluminum alloy plate, stress.

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Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun

Abstract:

Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.

Keywords: iris, pupil, specular highlights, reflection removal

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Authors: Firas M. Tuaimah

Abstract:

This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity.

The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: Short-Term Load Forecasting, Artificial Neural Networks, Back propagation learning.

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Authors: Yi-Fang Hung, Jinn-Tsyy Lai

Abstract:

Lycopene, which can be extracted from plants and is very popular for fruit intake, is restricted for healthy food development due to its high price. On the other hand, it will get great safety concerns, especially in the food or cosmetic application, if the raw material of lycopene is produced by chemical synthesis. In this project, we provide a key technology to bridge the limitation as mentioned above. Based on the abundant bioresources of BCRC (Bioresource Collection and Research Center, Taiwan), a promising lycopene output will be anticipated by the introduction of fermentation technology along with industry-related core energy. Our results showed that addition of tween 80(0.2%) and span 20 produced higher amount of lycopene. And piperidine, when was added at 48hr to the cultivation medium, could promote lycopene excretion effectively also.

Keywords: photosynthetic bacteria, lycopene, tween80, Piperidine

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Authors: S. Sarumathi, N. Shanthi, P. Ranjetha

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Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.

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Authors: S. Kannimuthu, K. Premalatha

Abstract:

This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.

Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.

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Authors: Darn H. Hsiao, Zhu-Yun Zheng

Abstract:

Since Taiwan is located between the Eurasian and Filipino plates and earthquakes often thus occur. The coastal plains in western Taiwan are alluvial plains, and the soils of the alluvium are mostly from the Lao-Shan belt in the central mountainous area of ​​southern Taiwan. It could come mostly from sand/shale and slate. The previous investigation found that the soils in the Kaohsiung area of ​​southern Taiwan are mainly composed of slate, shale, quartz, low-plastic clay, silt, silty sand and so on. It can also be found from the past earthquakes that the soil in Kaohsiung is highly susceptible to soil subsidence due to liquefaction. Insufficient bearing capacity of building will cause soil liquefaction disasters. In this study, the boring drilling data from nine districts among the Love River Basin in the city center, and some factors affecting liquefaction include the content of fines (FC), standard penetration test N value (SPT N), the thickness of clay layer near ground-surface, and the thickness of possible liquefied soil were further discussed for liquefaction potential as well as groundwater level. The results show that the liquefaction potential is higher in the areas near the riverside, the backfill area, and the west area of ​​the study area. This paper also uses the old paleo-geological map, soil particle distribution curve, compared with LPI map calculated from the analysis results. After all the parameters finally were studied for five sub zones in the Love River Basin by maximum-minimum method, it is found that both of standard penetration test N value and the thickness of the clay layer will be most influential.

Keywords: Liquefaction, western Taiwan, liquefaction potential map, factors influence high liquefaction potential areas, LPI analysis.

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Authors: Won-Sub Lee, Sung-Gaun Kim

Abstract:

Rotational Smart Lighting Control System can supply the quantity of lighting which is required to run plants by rotating few LED and Fluorescent instead of that are used in the existing plant factories.The initial installation of the existing plants factory is expensive, so in order to solve the problem with smart lighting control system was developed. The beam required intensity for the growth of crops, Photosynthetic Photon Flux Density(PPFD)is calculated; and the number of LED, are installed on the blades, set; using the Lighting Simulation Program.Relux, it is able to confirm that the difference of the beam intensity between the center and the outer of lighting system when the lighting device is rotating.

Keywords: Plant Factory, Lighting Control System, Rotational Lighting System, Lighting Equipment

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces  high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: Activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss.

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Authors: H. S. Huang, J. C. Jao, K. L. Yen, C. T. Tsai

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The purpose of this article applies the monthly final energy yield and failure data of 202 PV systems installed in Taiwan to analyze the PV operational performance and system availability. This data is collected by Industrial Technology Research Institute through manual records. Bad data detection and failure data estimation approaches are proposed to guarantee the quality of the received information. The performance ratio value and system availability are then calculated and compared with those of other countries. It is indicated that the average performance ratio of Taiwan-s PV systems is 0.74 and the availability is 95.7%. These results are similar with those of Germany, Switzerland, Italy and Japan.

Keywords: availability, performance ratio, PV system, Taiwan

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Authors: N. Veerasamy, C. J. Cheyne

Abstract:

Users of computer systems may often require the private transfer of messages/communications between parties across a network. Information warfare and the protection and dominance of information in the military context is a prime example of an application area in which the confidentiality of data needs to be maintained. The safe transportation of critical data is therefore often a vital requirement for many private communications. However, unwanted interception/sniffing of communications is also a possibility. An elementary stealthy transfer scheme is therefore proposed by the authors. This scheme makes use of encoding, splitting of a message and the use of a hashing algorithm to verify the correctness of the reconstructed message. For this proof-of-concept purpose, the authors have experimented with the random sending of encoded parts of a message and the construction thereof to demonstrate how data can stealthily be transferred across a network so as to prevent the obvious retrieval of data.

Keywords: Construction, encode, interception, stealthy.

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