Search results for: Real time databases

Authors: Pavel Janak

Abstract:

This paper studies, maps and explains the interactions between downloaders and uploaders pertaining to the Internet film piracy. This study also covers several motivational factors that influence users to upload or download movies, and thus to engage in film piracy over the Internet. The essay also proposes a model that describes user behavior including their relationships and influences. Moreover, proposed theoretical interactions and motivational factors are applied to the real world scenario, using examples of a data storage webpage server Ulozto.net and webpage Piratebay.org gathering information about downloadable BitTorrents. Moreover, the theory is further supported by description of behavior of real Internet uploaders.

Keywords: Download, film piracy, internet, motivational factors for uploading.

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Lu Zou, Dianfu MA, Ying Wang, Xianqi Zhao

Abstract:

Avionic software architecture has transit from a federated avionics architecture to an integrated modular avionics (IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the executable model have been brought up, however with less consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic interaction order sequence. In this paper, we proposed an AADL-based model-driven design methodology to fulfill the purpose to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the mapping rules between the AADL653 elements and the elements in Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our approach. Finally, we give the related work and future research directions.

Keywords: IMA, ARINC653, AADL653, code generation.

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Authors: R. Borghol, T. Aguili

Abstract:

In this paper, we investigate theoretically the waves propagation in a lossless double-negative grounded slab (DNG). This study is performed by the Transverse Resonance Method (TRM). The proper or improper nature of real and complex modes is observed. They are highly dependent on metamaterial parameters, i.e. ɛ_r-negative, µ_r-negative, or both. Numerical results provided that only the proper complex modes (i.e., leaky modes) exist in DNG slab, and only the improper complex modes exist in single-negative grounded slab.

Keywords: Double-negative grounded slab, real and complex modes, single-negative grounded slab, transverse resonance method.

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Authors: Arslan Qamar Malik, Jehanzeb Ahmad

Abstract:

The paper presents a novel idea to control computer mouse cursor movement with human eyes. In this paper, a working of the product has been described as to how it helps the special people share their knowledge with the world. Number of traditional techniques such as Head and Eye Movement Tracking Systems etc. exist for cursor control by making use of image processing in which light is the primary source. Electro-oculography (EOG) is a new technology to sense eye signals with which the mouse cursor can be controlled. The signals captured using sensors, are first amplified, then noise is removed and then digitized, before being transferred to PC for software interfacing.

Keywords: Human Computer Interaction, Real-Time System, Electro-oculography, Signal Processing.

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Authors: Zixin Liu

Abstract:

The problem of robust stability and robust stabilization for a class of discrete-time uncertain systems with time delay is investigated. Based on Tchebychev inequality, by constructing a new augmented Lyapunov function, some improved sufficient conditions ensuring exponential stability and stabilization are established. These conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. Compared with some previous results derived in the literature, the new obtained criteria have less conservatism. Two numerical examples are provided to demonstrate the improvement and effectiveness of the proposed method.

Keywords: Robust stabilization, robust stability, discrete-time system, time delay.

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Authors: F. Yilmaz, Y. Saylan, A. Derazshamshir, S. Atay, A. Denizli

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A quartz crystal microbalance (QCM) nanosensor was developed to detect lysozyme enzyme by functionalizing its gold surface with the attachment of poly(methacroyl-L-phenylalanine) (PMAPA) nanoparticles. PMAPA was chosen as a hydrophobic matrix. The hydrophobic nanoparticles were synthesized by micro-emulsion polymerization method. Hydrophobic QCM nanosensor was tested for real time detection of lysozyme enzyme from aqueous solution. The kinetic and affinity studies were determined by using lysozyme solutions with different concentrations. The responses related with mass (Δm) and frequency (Δf) shifts were used to evaluate adsorption properties. 

 

Keywords: HIC, lysozyme, nanosensor, QCM.

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Authors: S. H. Oudjana, A. Hellal, I. Hadj Mahammed

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Photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.

Keywords: Photovoltaic Power Forecasting, Regression, Neural Networks.

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

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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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Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, Paul Joseph K.

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Analysis of heart rate variability (HRV) has become a popular non-invasive tool for assessing the activities of autonomic nervous system. Most of the methods were hired from techniques used for time series analysis. Currently used methods are time domain, frequency domain, geometrical and fractal methods. A new technique, which searches for pattern repeatability in a time series, is proposed for quantifying heart rate (HR) time series. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are able to distinguish HR data clearly from noise and electroencephalogram (EEG). The results of analysis using these measures give an insight into the fundamental difference between the composition of HR time series with respect to EEG and noise.

Keywords: Approximate entropy, heart rate variability, noise, pattern repeatability, and sample entropy.

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Authors: Yongxin Yuan

Abstract:

The problem of updating damped gyroscopic systems using measured modal data can be mathematically formulated as following two problems. Problem I: Given Ma ∈ Rn×n, Λ = diag{λ1, ··· , λp} ∈ Cp×p, X = [x1, ··· , xp] ∈ Cn×p, where p<n and both Λ and X are closed under complex conjugation in the sense that λ2j = λ¯2j−1 ∈ C, x2j = ¯x2j−1 ∈ Cn for j = 1, ··· , l, and λk ∈ R, xk ∈ Rn for k = 2l + 1, ··· , p, find real-valued symmetric matrices D,K and a real-valued skew-symmetric matrix G (that is, GT = −G) such that MaXΛ2 + (D + G)XΛ + KX = 0. Problem II: Given real-valued symmetric matrices Da, Ka ∈ Rn×n and a real-valued skew-symmetric matrix Ga, find (D, ˆ G, ˆ Kˆ ) ∈ SE such that Dˆ −Da2+Gˆ−Ga2+Kˆ −Ka2 = min(D,G,K)∈SE (D− Da2 + G − Ga2 + K − Ka2), where SE is the solution set of Problem I and · is the Frobenius norm. This paper presents an iterative algorithm to solve Problem I and Problem II. By using the proposed iterative method, a solution of Problem I can be obtained within finite iteration steps in the absence of roundoff errors, and the minimum Frobenius norm solution of Problem I can be obtained by choosing a special kind of initial matrices. Moreover, the optimal approximation solution (D, ˆ G, ˆ Kˆ ) of Problem II can be obtained by finding the minimum Frobenius norm solution of a changed Problem I. A numerical example shows that the introduced iterative algorithm is quite efficient.

Keywords: Model updating, iterative algorithm, gyroscopic system, partially prescribed spectral data, optimal approximation.

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Authors: Suwardo, Madzlan B. Napiah, Ibrahim B. Kamaruddin

Abstract:

Stage bus operated in the mixed traffic might always meet many problems about low quality and reliability of services. The low quality and reliability of bus service can make the system not attractive and directly reduce the interest of using bus service. This paper presents the result of field investigation and analysis of on-time performance and service regularity of stage bus in mixed traffic. Data for analysis was collected from the field by on-board observation along the Ipoh-Lumut corridor in Perak, Malaysia. From analysis and discussion, it can be concluded that on-time performance and service regularity varies depend on station, typical day, time period, operation characteristics of bus and characteristics of traffic. The on-time performance and service regularity of stage bus in mixed traffic can be derived by using data collected by onboard survey. It is clear that on-time performance and service regularity of the existing stage bus system was low.

Keywords: mixed traffic, on-time performance, service regularity, stage bus

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Authors: A.K. Baliarsingh, S. Panda, A.K. Mohanty, C. Ardil

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This paper presents a systematic approach for designing Unified Power Flow Controller (UPFC) based supplementary damping controllers for damping low frequency oscillations in a single-machine infinite-bus power system. Detailed investigations have been carried out considering the four alternatives UPFC based damping controller namely modulating index of series inverter (mB), modulating index of shunt inverter (mE), phase angle of series inverter (δB ) and phase angle of the shunt inverter (δE ). The design problem of the proposed controllers is formulated as an optimization problem and Real- Coded Genetic Algorithm (RCGA) is employed to optimize damping controller parameters. Simulation results are presented and compared with a conventional method of tuning the damping controller parameters to show the effectiveness and robustness of the proposed design approach.

Keywords: Power System Oscillations, Real-Coded Genetic Algorithm (RCGA), Flexible AC Transmission Systems (FACTS), Unified Power Flow Controller (UPFC), Damping Controller.

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Authors: Mamoon M. Atout

Abstract:

The Middle East Gulf region has witnessed rapid growth and development in many areas over the last two decades. The development of the real-estate sector, construction industry and infrastructure projects are a major share of the development that has participated in the civilization of the countries of the Gulf. Construction industry projects were planned and managed by different types of experts, who came from all over the world having different types of experiences in construction management and industry. Some of these projects were completed on time, while many were not, due to many accumulating factors. Many accumulated factors are considered as the principle reason for the problem experienced at the project construction stage, which reflected negatively on the project success. Specific causes of delay have been identified by construction managers to avoid any unexpected delays through proper analysis and considerations to some implications such as risk assessment and analysis for many potential problems to ensure that projects will be delivered on time. Construction management implications were adopted and considered by project managers who have experience and knowledge in applying the techniques of the system of engineering construction management. The aim of this research is to determine the benefits of the implications of construction management by the construction team and level of considerations of the techniques and processes during the project development and construction phases to avoid any delay in the projects. It also aims to determine the factors that participate to project completion delays in case project managers are not well committed to their roles and responsibilities. The results of the analysis will determine the necessity of the applications required by the project team to avoid the causes of delays that help them deliver projects on time, e.g. verifying tender documents, quantities and preparing the construction method of the project.

Keywords: Construction management, control process, cost control, planning and scheduling, roles and responsibilities.

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Authors: Nael Hirzalla

Abstract:

The legality of some countries or agencies’ acts to spy on personal phone calls of the public became a hot topic to many social groups’ talks. It is believed that this act is considered an invasion to someone’s privacy. Such act may be justified if it is singling out specific cases but to spy without limits is very unacceptable. This paper discusses the needs for not only a simple and light weight technique to secure mobile voice calls but also a technique that is independent from any encryption standard or library. It then presents and tests one encrypting algorithm that is based of Frequency scrambling technique to show fair and delay-free process that can be used to protect phone calls from such spying acts.

Keywords: Frequency Scrambling, Mobile Applications, Real- Time Voice Encryption, Spying on Calls.

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Authors: Yanli Qi, Ning Lv, Jing Li

Abstract:

Sub-Nyquist sampling jamming method (SNSJ) is a well known deception jamming method for inverse synthetic aperture radar (ISAR). However, the anti-decoy of the SNSJ method performs easier since the amplitude of the false-target images are weaker than the real-target image; the false-target images always lag behind the real-target image, and all targets are located in the same cross-range. In order to overcome the drawbacks mentioned above, a simple modulation based on SNSJ (M-SNSJ) is presented in this paper. The method first uses amplitude modulation factor to make the amplitude of the false-target images consistent with the real-target image, then uses the down-range modulation factor and cross-range modulation factor to make the false-target images move freely in down-range and cross-range, respectively, thus the capacity of deception is improved. Finally, the simulation results on the six available combinations of three modulation factors are given to illustrate our conclusion.

Keywords: Inverse synthetic aperture radar, ISAR, deceptive jamming, Sub-Nyquist sampling jamming method, SNSJ, modulation based on Sub-Nyquist sampling jamming method, M-SNSJ.

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Authors: Sung Ho Ha, Seong Hyeon Joo

Abstract:

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.

Keywords: Data mining, medical decisions, medical domainknowledge, chest pain.

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Authors: Wiroon Sriborrirux, Sorakrai Kraipui, Nakorn Indra-Payoong

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One of the most importance of intelligence in-car and roadside systems is the cooperative vehicle-infrastructure system. In Thailand, ITS technologies are rapidly growing and real-time vehicle information is considerably needed for ITS applications; for example, vehicle fleet tracking and control and road traffic monitoring systems. This paper defines the communication protocols and software design for middleware components of B-VIS (Burapha Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.

Keywords: Middleware, RFID sensor network, Cooperativevehicle-infrastructure system, Enterprise Java Bean.

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Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

Abstract:

Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.

Keywords: Interaction graph, Negative training data, Protein-Protein interaction, Support vector machine.

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Authors: D. de Matías Batalla

Abstract:

This paper develops and extended eclectic paradigm to fit the firm internationalization process with the real international business world. The approach is based on Dunning´s, introducing new concepts like mode of entry, international joint venture o international mergers and acquisitions. At the same time is presented a model to describe the Spanish international mergers and acquisitions in order to determinate the most important factor that influence in this type of foreign direct investment.

Keywords: Dunning, eclectic paradigm, foreign direct investment, IJV, international business, international management, multinational firms, firm internationalization process, M&A.

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Authors: Mustafa Kisa, Fatih Mehmet Botsali

Abstract:

Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.

Keywords: Image possessing, vehicle tracking, license plate detection, computer vision.

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

Abstract:

The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: Bio-signals, DC Component, Doppler Effect, ellipse fitting, radar, SDR.

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

Abstract:

Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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Authors: Petr Vcelak, Jana Kleckova

Abstract:

Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Keywords: DASTA, De-identification, DICOM, Health Level Seven, Medical data, OCR, Personal data

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Authors: Samit Ari, Goutam Saha

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Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

Keywords: ANN, Classification of heart diseases, murmurs, optimization, Phonocardiogram, QRcp, SVD.

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Authors: Theodor D. Popescu

Abstract:

The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.

Keywords: Independent Component Analysis, second order statistics, simulation, time series forecasting

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Authors: Dimitar Karastoyanov, Vladimir Monov

Abstract:

The paper is concerned with the state examination as well as the problems during the post surgical (orthopedic) rehabilitation of the knee and ankle joint. An observation of the current appliances for a passive rehabilitation devices is presented. The major necessary and basic features of the intelligent rehabilitation devices are considered. An approach for a new intelligent appliance is suggested. The main advantages of the device are: both active as well as passive rehabilitation of the patient based on the human - patient reactions and a real time feedback. The basic components: controller; electrical motor; encoder, force – torque sensor are discussed in details. The main modes of operation of the device are considered.

Keywords: Ankle, knee, rehabilitation, computer control.

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Authors: T. Teo, S. W. Lye, Y. F. Li, Z. Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that using a developed channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available brain computer interface (BCI) 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring, ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: Neurophysiology, monitoring, EEG, outliers, electroencephalography.

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data

Keywords: Rule induction, decision table, missing data, noise.

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Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

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