Search results for: video data transmission.

Authors: Samrat Vikramaditya Tiwari, Atul Sewaiwar, Yeon-Ho Chung

Abstract:

Device-to-device (D2D) communication is considered a promising technique to provide wireless peer-to-peer communication services. Due to increasing demand on mobile services, available spectrum for radio frequency (RF) based communications becomes scarce. Recently, visible light communications (VLC) has evolved as a high speed wireless data transmission technology for indoor environments with abundant available bandwidth. In this paper, a novel VLC based D2D communication that provides wireless peer-to-peer communication is proposed. Potential low operating power devices for an efficient D2D communication over increasing distance of separation between devices is analyzed. Optical repeaters (OR) are also proposed to enhance the performance in an environment where direct D2D communications yield degraded performance. Simulation results show that VLC plays an important role in providing efficient D2D communication up to a distance of 1 m between devices. It is also found that the OR significantly improves the coverage distance up to 3.5 m.

Keywords: Visible light communication, light emitting diode, device-to-device, optical repeater.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, M. Sharmila

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There have been a lot of efforts and researches undertaken in developing efficient tools for performing several tasks in data mining. Due to the massive amount of information embedded in huge data warehouses maintained in several domains, the extraction of meaningful pattern is no longer feasible. This issue turns to be more obligatory for developing several tools in data mining. Furthermore the major aspire of data mining software is to build a resourceful predictive or descriptive model for handling large amount of information more efficiently and user friendly. Data mining mainly contracts with excessive collection of data that inflicts huge rigorous computational constraints. These out coming challenges lead to the emergence of powerful data mining technologies. In this survey a diverse collection of data mining tools are exemplified and also contrasted with the salient features and performance behavior of each tool.

Keywords: Business Analytics, Data Mining, Data Analysis, Machine Learning, Text Mining, Predictive Analytics, Visualization.

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Authors: Dennis A. Apuan

Abstract:

Categorical data based on description of the agricultural landscape imposed some mathematical and analytical limitations. This problem however can be overcome by data transformation through coding scheme and the use of non-parametric multivariate approach. The present study describes data transformation from qualitative to numerical descriptors. In a collection of 103 random soil samples over a 60 hectare field, categorical data were obtained from the following variables: levels of nitrogen, phosphorus, potassium, pH, hue, chroma, value and data on topography, vegetation type, and the presence of rocks. Categorical data were coded, and Spearman-s rho correlation was then calculated using PAST software ver. 1.78 in which Principal Component Analysis was based. Results revealed successful data transformation, generating 1030 quantitative descriptors. Visualization based on the new set of descriptors showed clear differences among sites, and amount of variation was successfully measured. Possible applications of data transformation are discussed.

Keywords: data transformation, numerical descriptors, principalcomponent analysis

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Authors: Hans R. Márquez, Cesar Hernández, Ingrid Páez

Abstract:

This paper develops a multiple channel assignment model, which allows to take advantage of spectrum opportunities in cognitive radio networks in the most efficient way. The developed scheme allows making several assignments of available and frequency adjacent channel, which require a bigger bandwidth, under an equality environment. The hybrid assignment model it is made by two algorithms, one that makes the ranking and selects available frequency channels and the other one in charge of establishing the Max-Min Fairness for not restrict the spectrum opportunities for all the other secondary users, who also claim to make transmissions. Measurements made were done for average bandwidth, average delay, as well as fairness computation for several channel assignments. Reached results were evaluated with experimental spectrum occupational data from captured GSM frequency band. The developed model shows evidence of improvement in spectrum opportunity use and a wider average transmission bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: Bandwidth, fairness, multichannel, secondary users.

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

Abstract:

Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: Semantic data integration, biological ontology, linked data, semantic web, OWL, RDF.

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Authors: C. Arunachalaperumal, B. Chandru, J. M. Mathana

Abstract:

In recent years parasitic antenna play major role in MIMO systems because of their gain and spectral efficiency. In this paper, single RF chain MIMO transmitter is designed using reconfigurable parasitic antenna. The Spatial Modulation (SM) is a recently proposed scheme in MIMO scenario which activates only one antenna at a time. The SM entirely avoids ICI and IAS, and only requires a single RF chain at the transmitter. This would switch ON a single transmit-antenna for data transmission while all the other antennas are kept silent. The purpose of the parasitic elements is to change the radiation pattern of the radio waves which is emitted from the driven element and directing them in one direction and hence introduces transmit diversity. Diode is connect between the patch and ground by changing its state (ON and OFF) the parasitic element act as reflector and director and also capable of steering azimuth and elevation angle. This can be achieved by changing the input impedance of each parasitic element through single RF chain. The switching of diode would select the single parasitic antenna for spatial modulation. This antenna is expected to achieve maximum gain with desired efficiency.

Keywords: MIMO system, single RF chain, Parasitic Antenna.

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Authors: Pimploi Tirastittam, Sawanath Treesathon, Amornrath Ongkawat

Abstract:

Learning Management System (LMS) is the system which uses to manage the learning in order to grouping the content and learning activity between the lecturer and learner including online examination and evaluation. Nowadays, it is the borderless learning era so the learning activities can be accessed from everywhere in the world and also anytime via the information technology and media. The learner can easily access to the knowledge so the different in time and distance is not a constraint for learning anymore. The learning pattern which was used in this research is the integration of the in-class learning and online learning via internet and will be able to monitor the progress by the Learning management system which will create the fast response and accessible learning process via the social media. In order to increase the capability and freedom of the learner, the system can show the current and history of the learning document, video conference and also has the chat room for the learner and lecturer to interact to each other. So the objectives of the “The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject” are to expand the opportunity of learning and to increase the efficiency of learning as well as increase the communication channel between lecturer and student. The data of this research was collect from 30 users of the system which are students who enroll in the subject. And the result of the research is in the “Very Good” which is conformed to the hypothesis.

Keywords: Learning Management System, Social Media.

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca De Marchi

Abstract:

This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes a larger monitored area available. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary, the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: Data compression, ultrasonic communication, guided waves, FEM analysis.

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Authors: Adam Abdalla Elbashir Adam, Xiaomin Cheng, Xiang Shui Miao

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In this work, the effect of the magnetron sputtering system parameters on the optical properties of the Mn doped GeTe were investigated. The optical properties of the Ge_1-xMn_xTe thin films with different thicknesses are determined by analyzing the transmittance and reflectance data. The energy band gaps of the amorphous Mn-doped GeTe thin films with different thicknesses were calculated. The obtained results demonstrated that the energy band gap values of the amorphous films are quite different and they are dependent on the films thicknesses. The extinction coefficients of amorphous Mn-doped GeTe thin films as function of wavelength for different thicknesses were measured. The results showed that the extinction coefficients of all films are varying inversely with their optical transmission. Moreover, the results emphasis that, not only the microstructure, electrical and magnetic properties of Mn doped GeTe thin films vary with the films thicknesses but also the optical properties differ with the film thickness.

Keywords: Phase change magnetic materials, transmittance, absorbance, extinction coefficients.

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Authors: Theodore Grosch, Felipe Koji Godinho Hoshino

Abstract:

In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.

Keywords: Bit error rate, crest factor reduction, OFDM, physical layer simulation.

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Authors: Junghwan Choi, Seongsoo Lee

Abstract:

Histogram equalization is often used in image enhancement, but it can be also used in auto exposure. However, conventional histogram equalization does not work well when many pixels are concentrated in a narrow luminance range.This paper proposes an auto exposure method based on 2-way histogram equalization. Two cumulative distribution functions are used, where one is from dark to bright and the other is from bright to dark. In this paper, the proposed auto exposure method is also designed and implemented for image signal processors with full-HD images.

Keywords: Histogram equalization, Auto exposure, Image signal processor, Low-cost, Full HD Video.

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Authors: C. Matiz C., N. Olarte L., A. Rubiano F.

Abstract:

This paper presents the design related to the electronic system design of the respiratory signal, including phases for processing, followed by the transmission and reception of this signal and finally display. The processing of this signal is added to the ECG and temperature sign, put up last year. Under this scheme is proposed that in future also be conditioned blood pressure signal under the same final printed circuit and worked.

Keywords: Conditioning, Respiratory Signal, Storage, Teleconsultation.

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Authors: Simon E. Uguru, Victor E. Idigo, Obinna S. Oguejiofor, Naveed Nawaz

Abstract:

As the deployment of the Fifth Generation (5G) mobile communication networks take shape all over the world, achieving spectral efficiency, energy efficiency, and dealing with interference are among the greatest challenges encountered so far. The aim of this study is to mitigate inter-cell interference (ICI) in a multi-cell multi-antenna system while maximizing the spectral efficiency of the system. In this study, a system model was devised that showed a miniature representation of a multi-cell multi-antenna system. Based on this system model, a convex optimization problem was formulated to maximize the spectral efficiency of the system while mitigating the ICI. This optimization problem was solved using CVX, which is a modeling system for constructing and solving discipline convex programs. The solutions to the optimization problem are sub-optimal coordinated beamformers. These coordinated beamformers direct each data to the served user equipments (UEs) in each cell without interference during downlink transmission, thereby maximizing the system-wide spectral efficiency.

Keywords: coordinated beamforming, convex optimization, inter-cell interference, multi-antenna, multi-cell, spectral efficiency

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Authors: Yunus Doğan, Ahmet Durap

Abstract:

Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: Clustering algorithms, coastal engineering, data mining, data summarization, statistical methods.

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Authors: Charles D. Otine, Samuel B. Kucel, Lena Trojer

Abstract:

Selecting the data modeling technique for an information system is determined by the objective of the resultant data model. Dimensional modeling is the preferred modeling technique for data destined for data warehouses and data mining, presenting data models that ease analysis and queries which are in contrast with entity relationship modeling. The establishment of data warehouses as components of information system landscapes in many organizations has subsequently led to the development of dimensional modeling. This has been significantly more developed and reported for the commercial database management systems as compared to the open sources thereby making it less affordable for those in resource constrained settings. This paper presents dimensional modeling of HIV patient information using open source modeling tools. It aims to take advantage of the fact that the most affected regions by the HIV virus are also heavily resource constrained (sub-Saharan Africa) whereas having large quantities of HIV data. Two HIV data source systems were studied to identify appropriate dimensions and facts these were then modeled using two open source dimensional modeling tools. Use of open source would reduce the software costs for dimensional modeling and in turn make data warehousing and data mining more feasible even for those in resource constrained settings but with data available.

Keywords: About Database, Data Mining, Data warehouse, Dimensional Modeling, Open Source.

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Authors: Seung-Mok Han, Woo-Jin Nam, Seongsoo Lee

Abstract:

This paper proposes and implements an core transform architecture, which is one of the major processes in HEVC video compression standard. The proposed core transform architecture is implemented with only adders and shifters instead of area-consuming multipliers. Shifters in the proposed core transform architecture are implemented in wires and multiplexers, which significantly reduces chip area. Also, it can process from 4×4 to 16×16 blocks with common hardware by reusing processing elements. Designed core transform architecture in 0.13um technology can process a 16×16 block with 2-D transform in 130 cycles, and its gate count is 101,015 gates.

Keywords: HEVC, Core transform, Low area, Shift-and-add, PE reuse

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Authors: Wei-hua Ai, Wei Yan, Xiang Li

Abstract:

Data compression is used operationally to reduce bandwidth and storage requirements. An efficient method for achieving lossless weather radar data compression is presented. The characteristics of the data are taken into account and the optical linear prediction is used for the PPI images in the weather radar data in the proposed method. The next PPI image is identical to the current one and a dramatic reduction in source entropy is achieved by using the prediction algorithm. Some lossless compression methods are used to compress the predicted data. Experimental results show that for the weather radar data, the method proposed in this paper outperforms the other methods.

Keywords: Lossless compression, weather radar data, optical linear prediction, PPI image

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Authors: Sabina Jordan, Miha Tomšič, Friderik Knez, Marjana Šijanec Zavrl

Abstract:

To determine the possibilities for the implementation of sustainable building indicators in Slovenia, testing of the first version of the indicators, developed in the CARE4CLIMATE project and based on the EU Level(s) framework, was carried out in 2022. Invited and interested stakeholders of the construction process were provided with video content and instructions on the Slovenian e-platform of sustainable building indicators. In addition, workshops and lectures with individual subjects were also performed. The final phase of the training and testing procedure included a questionnaire, which was used to obtain information about the participants' opinions regarding the indicators. The analysis of the results of the testing, which was focused on level 2, confirmed the key preliminary finding of the development group, namely that currently, due to the lack of certain knowledge, data, and tools, all indicators for this level are not yet feasible in practice. The research also highlighted the greater need for training and specialization of experts in this field. At the same time, it showed that the testing of the first version itself was a big challenge: only 30 experts fully participated and filled out the online questionnaire. This number seems alarmingly low at first glance, but compared to level(s) testing in the EU member states, it is much more than 50 times higher. However, for the further execution of the indicators in Slovenia, it will therefore be necessary to invest a lot of effort and engagement. It is likely that state support will also be needed, for example, in the form of financial mechanisms or incentives and/or legislative background.

Keywords: Sustainability, building indicator, project CARE4CLIMATE, alpha version SLO kTG, Level(s), sustainable construction stakeholders.

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

Abstract:

The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: Data management, digitization, Industry 4.0, knowledge engineering, metamodel.

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Authors: Bogdan Walek, Cyril Klimes

Abstract:

In present days the area of data migration is very topical. Current tools for data migration in the area of relational database have several disadvantages that are presented in this paper. We propose a methodology for data migration of the database tables and their data between various types of relational database systems (RDBMS). The proposed methodology contains an expert system. The expert system contains a knowledge base that is composed of IFTHEN rules and based on the input data suggests appropriate data types of columns of database tables. The proposed tool, which contains an expert system, also includes the possibility of optimizing the data types in the target RDBMS database tables based on processed data of the source RDBMS database tables. The proposed expert system is shown on data migration of selected database of the source RDBMS to the target RDBMS.

Keywords: Expert system, fuzzy, data migration, database, relational database, data type, relational database management system.

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Authors: Hyung-Weon Cho, Youngyoon Lee, Seung Goo Kang, Dahae Chong, Myungsoo Lee, Chonghan Song, Seokho Yoon

Abstract:

This paper proposes a novel spectrum sensing technique for the digital video broadcasting-terrestrial (DVB-T) systems, which utilizes the periodicity of pilot signals in the orthogonal frequency division multiplexing (OFDM) symbols. The proposed scheme can overcome the effect of the timing synchronization error by recorrelating the correlation values in the same sample distances. The numerical results demonstrate that the detection probability performance of the proposed scheme outperforms that of the conventional scheme when there exists a timing synchronization error.

Keywords: DVB-T, spectrum sensing, OFDM, timing synchronizationerror.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry

Abstract:

Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.

Keywords: Effective band inference based power control algorithm (EBIA), Power Selection MRMC Unification Protocol (PMMUP), MRMC State unification Variable Prediction (MRSUP), Wireless Mesh Networks (WMNs).

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Authors: K. Hardy, A. Maurushat

Abstract:

Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: Big data, open data, productivity, transparency.

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

Abstract:

Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: Big data, correlation analysis, data recommendation system, urban data network.

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

Abstract:

With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: Data integration, disease-related malnutrition, expert systems, mobile health.

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Authors: Steve Hung-Lung Tu, Yu-Hsuan Cheng

Abstract:

A novel and efficient approach to realize fractional-order capacitors is investigated in this paper. Meanwhile, a new approach which is more efficient for semiconductor implementation of fractional-order capacitors is proposed. The feasibility of the approach has been verified with the preliminary measured results.

Keywords: Fractional-order, field-effect transistors, RC transmission lines.

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Authors: Narendra Singh Yadav, R.P.Yadav

Abstract:

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

Keywords: AODV, DSDV, MANET, relative performance

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Authors: Geeta Sikka, Arvinder Kaur Takkar, Moin Uddin

Abstract:

Missing data is a persistent problem in almost all areas of empirical research. The missing data must be treated very carefully, as data plays a fundamental role in every analysis. Improper treatment can distort the analysis or generate biased results. In this paper, we compare and contrast various imputation techniques on missing data sets and make an empirical evaluation of these methods so as to construct quality software models. Our empirical study is based on NASA-s two public dataset. KC4 and KC1. The actual data sets of 125 cases and 2107 cases respectively, without any missing values were considered. The data set is used to create Missing at Random (MAR) data Listwise Deletion(LD), Mean Substitution(MS), Interpolation, Regression with an error term and Expectation-Maximization (EM) approaches were used to compare the effects of the various techniques.

Keywords: Missing data, Imputation, Missing Data Techniques.

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Authors: George E. Tsekouras, Evi Sampanikou

Abstract:

We compare three categorical data clustering algorithms with respect to the problem of classifying cultural data related to the aesthetic judgment of comics artists. Such a classification is very important in Comics Art theory since the determination of any classes of similarities in such kind of data will provide to art-historians very fruitful information of Comics Art-s evolution. To establish this, we use a categorical data set and we study it by employing three categorical data clustering algorithms. The performances of these algorithms are compared each other, while interpretations of the clustering results are also given.

Keywords: Aesthetic judgment, comics artists, cluster analysis, categorical data.

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Authors: Femi Elegbeleye, Seani Rananga

Abstract:

This paper focused on cost effective storage architecture using fog and cloud data storage gateway, and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. Several results obtained from this study on data privacy models show that when two or more data privacy models are integrated via a fog storage gateway, we often have more secure data. Our main focus in the study is to design a framework for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, including its structure, and its interrelationships.

Keywords: IoT, fog storage, cloud storage, data analysis, data privacy.

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