Search results for: cluster computing
805 DAG Design and Tradeoff for Full Live Virtual Machine Migration over XIA Network
Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang
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Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.Keywords: DAG, downtime, virtual machine migration, XIA
Procedia PDF Downloads 846804 SciPaaS: a Scientific Execution Platform for the Cloud
Authors: Wesley H. Brewer, John C. Sanford
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SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics
Procedia PDF Downloads 581803 Modeling and Experimental Verification of Crystal Growth Kinetics in Glass Forming Alloys
Authors: Peter K. Galenko, Stefanie Koch, Markus Rettenmayr, Robert Wonneberger, Evgeny V. Kharanzhevskiy, Maria Zamoryanskaya, Vladimir Ankudinov
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We analyze the structure of undercooled melts, crystal growth kinetics and amorphous/crystalline microstructure of rapidly solidifying glass-forming Pd-based and CuZr-based alloys. A dendrite growth model is developed using a combination of the kinetic phase-field model and mesoscopic sharp interface model. The model predicts features of crystallization kinetics in alloys from thermodynamically controlled growth (governed by the Gibbs free energy change on solidification) to the kinetically limited regime (governed by atomic attachment-detachment processes at the solid/liquid interface). Comparing critical undercoolings observed in the crystallization kinetics with experimental data on melt viscosity, atomistic simulation's data on liquid microstructure and theoretically predicted dendrite growth velocity allows us to conclude that the dendrite growth kinetics strongly depends on the cluster structure changes of the melt. The obtained data of theoretical and experimental investigations are used for interpretation of microstructure of samples processed in electro-magnetic levitator on board International Space Station in the frame of the project "MULTIPHAS" (European Space Agency and German Aerospace Center, 50WM1941) and "KINETIKA" (ROSKOSMOS).Keywords: dendrite, kinetics, model, solidification
Procedia PDF Downloads 109802 Performance Analysis and Optimization for Diagonal Sparse Matrix-Vector Multiplication on Machine Learning Unit
Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu
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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication
Procedia PDF Downloads 119801 A Conceptual Framework of Digital Twin for Homecare
Authors: Raja Omman Zafar, Yves Rybarczyk, Johan Borg
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This article proposes a conceptual framework for the application of digital twin technology in home care. The main goal is to bridge the gap between advanced digital twin concepts and their practical implementation in home care. This study uses a literature review and thematic analysis approach to synthesize existing knowledge and proposes a structured framework suitable for homecare applications. The proposed framework integrates key components such as IoT sensors, data-driven models, cloud computing, and user interface design, highlighting the importance of personalized and predictive homecare solutions. This framework can significantly improve the efficiency, accuracy, and reliability of homecare services. It paves the way for the implementation of digital twins in home care, promoting real-time monitoring, early intervention, and better outcomes.Keywords: digital twin, homecare, older adults, healthcare, IoT, artificial intelligence
Procedia PDF Downloads 47800 Determinants of Breastfeeding in Thailand
Authors: Patarapan Odton
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This study investigates demographic and socio-economic factors of breastfeeding practice, including exclusively breastfeeding among children in Thailand using the Multiple Indicator Cluster Survey (MICS3 and MICS4). Logistic regression models were used to examine the determinants of initial breastfeeding, exclusively breastfeeding, and predominant breastfeeding, using data from women and children section of the survey. For initial breastfeeding, women live in rural area were more likely to start breastfeeding within one day of birth rather than who live in urban area in both round of the surveys. In year 2012, there were significantly higher probabilities of women in rural area started breastfeeding within one hour of birth compare to urban area. Women in southern Thailand have higher probabilities of start breastfeeding within one hour and one day than women in Bangkok and central region. During the year 2005-2006, children aged less than 5 years old lived in rural area have been breastfed higher than children in urban area. Children live in the northeast region were more likely to have been breastfed than the other regions. Only the second wealth quintile group was significant higher probability of ever been breastfed than the poorest group. The findings in the second round of the survey are different from the year 2005-06. In 2012, there was no difference in probability of ever been breastfed among children live in urban and rural area, children in Bangkok and central region were less probability of ever been breastfed than the others.Keywords: Breastfeeding, Exclusive Breastfeeding, Predominant Breastfeeding, Urban-Rural Difference
Procedia PDF Downloads 258799 Separating Landform from Noise in High-Resolution Digital Elevation Models through Scale-Adaptive Window-Based Regression
Authors: Anne M. Denton, Rahul Gomes, David W. Franzen
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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression
Procedia PDF Downloads 122798 Managers’ Mobile Information Behavior in an Openness Paradigm Era
Authors: Abd Latif Abdul Rahman, Zuraidah Arif, Muhammad Faizal Iylia, Mohd Ghazali, Asmadi Mohammed Ghazali
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Mobile information is a significant access point for human information activities. Theories and models of human information behavior have developed over several decades but have not yet considered the role of the user’s computing device in digital information interactions. This paper reviews the literature that leads to developing a conceptual framework of a study on the managers mobile information behavior. Based on the literature review, dimensions of mobile information behavior are identified, namely, dimension information needs, dimension information access, information retrieval and dimension of information use. The study is significant to understand the nature of librarians’ behavior in searching, retrieving and using information via the mobile device. Secondly, the study would provide suggestions about various kinds of mobile applications which organization can provide for their staff to improve their services.Keywords: mobile information behavior, information behavior, mobile information, mobile devices
Procedia PDF Downloads 336797 Evaluating Service Trustworthiness for Service Selection in Cloud Environment
Authors: Maryam Amiri, Leyli Mohammad-Khanli
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Cloud computing is becoming increasingly popular and more business applications are moving to cloud. In this regard, services that provide similar functional properties are increasing. So, the ability to select a service with the best non-functional properties, corresponding to the user preference, is necessary for the user. This paper presents an Evaluation Framework of Service Trustworthiness (EFST) that evaluates the trustworthiness of equivalent services without need to additional invocations of them. EFST extracts user preference automatically. Then, it assesses trustworthiness of services in two dimensions of qualitative and quantitative metrics based on the experiences of past usage of services. Finally, EFST determines the overall trustworthiness of services using Fuzzy Inference System (FIS). The results of experiments and simulations show that EFST is able to predict the missing values of Quality of Service (QoS) better than other competing approaches. Also, it propels users to select the most appropriate services.Keywords: user preference, cloud service, trustworthiness, QoS metrics, prediction
Procedia PDF Downloads 277796 Multi-Scaled Non-Local Means Filter for Medical Images Denoising: Empirical Mode Decomposition vs. Wavelet Transform
Authors: Hana Rabbouch
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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets
Procedia PDF Downloads 133795 Cryptography and Cryptosystem a Panacea to Security Risk in Wireless Networking
Authors: Modesta E. Ezema, Chikwendu V. Alabekee, Victoria N. Ishiwu, Ifeyinwa NwosuArize, Chinedu I. Nwoye
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The advent of wireless networking in computing technology cannot be overemphasized, it opened up easy accessibility to information resources, networking made easier and brought internet accessibility to our doorsteps, but despite all these, some mishap came in with it that is causing mayhem in today ‘s overall information security. The cyber criminals will always compromise the integrity of a message that is not encrypted or that is encrypted with a weak algorithm.In other to correct the mayhem, this study focuses on cryptosystem and cryptography. This ensures end to end crypt messaging. The study of various cryptographic algorithms, as well as the techniques and applications of the cryptography for efficiency, were all considered in the work., present and future applications of cryptography were dealt with as well as Quantum Cryptography was exposed as the current and the future area in the development of cryptography. An empirical study was conducted to collect data from network users.Keywords: algorithm, cryptography, cryptosystem, network
Procedia PDF Downloads 335794 Succeeding through Disruption: Exploring the Factors Influencing the Adoption of Disruptive Technologies in the Mobile Telecommunications Industry in Zimbabwe
Authors: Africa Makasi
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The research explored factors influencing the adoption of disruptive technologies in the mobile telecommunications industry in Zimbabwe. Data was gathered from the second biggest competitor in the industry with over 3 million subscribers as the main case of study. The survey was conducted by purposively selecting 70 respondents from a population of 3,000,000 (three million) active subscribers from the company’s database. A skip interval of 42,857 was used to randomly select the sample. Customer representatives were selected from the company’s five regional offices using a two-stage cluster sampling technique. Employee participants were purposively selected from the company’s head office. Self-administered questionnaires were used in the research. A pilot test was conducted and the assessment of the reliability of the research instruments used in the research performed. Results of the pilot study were analyzed to test for reliability using SPSS. The results confirmed that the style of leadership and its thrust may help speed up or reduce the adoption of disruptive technologies. This was reflected by a p–value of 0.01 which is less than 0.05. The null hypothesis was thus rejected and the strong relationship between leadership and adoption of disruptive technology is confirmed. Similar results were also obtained with respect to staff competence, availability of funding and the type of infrastructure available Future research should look at organizational ambidexterity as well as exploitation and exploration paradigms in organizations in the telecommunications industry and their impact on the adoption of disruptive technologies.Keywords: disruptive innovation, adoption, mobile telecommunication industry, exploration and exploitation
Procedia PDF Downloads 358793 Multi-Level Priority Based Task Scheduling Algorithm for Workflows in Cloud Environment
Authors: Anju Bala, Inderveer Chana
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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation
Procedia PDF Downloads 509792 Automatic Number Plate Recognition System Based on Deep Learning
Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi
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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.Keywords: ANPR, CS, CNN, deep learning, NPL
Procedia PDF Downloads 296791 The UAV Feasibility Trajectory Prediction Using Convolution Neural Networks
Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry
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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices
Procedia PDF Downloads 18790 Quantitative Structure-Activity Relationship Analysis of Binding Affinity of a Series of Anti-Prion Compounds to Human Prion Protein
Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić
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The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR
Procedia PDF Downloads 294789 Spatiotemporal Propagation and Pattern of Epileptic Spike Predict Seizure Onset Zone
Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger
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Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.Keywords: spike propagation, spike pattern, clustering, SOZ
Procedia PDF Downloads 52788 Application of Deep Learning in Top Pair and Single Top Quark Production at the Large Hadron Collider
Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf
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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approachKeywords: top tagger, multivariate, deep learning, LHC, single top
Procedia PDF Downloads 103787 Characteristics and Item Parameters Fitness on Chemistry Teacher-Made Test Instrument
Authors: Rizki Nor Amelia, Farida A. Setiawati
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This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test
Procedia PDF Downloads 226786 Application of Statistical Linearized Models for Investigations of Digital Dynamic Pulse-Frequency Control Systems
Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov
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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller
Procedia PDF Downloads 482785 Forward Stable Computation of Roots of Real Polynomials with Only Real Distinct Roots
Authors: Nevena Jakovčević Stor, Ivan Slapničar
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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy
Procedia PDF Downloads 405784 Post-Quantum Resistant Edge Authentication in Large Scale Industrial Internet of Things Environments Using Aggregated Local Knowledge and Consistent Triangulation
Authors: C. P. Autry, A. W. Roscoe, Mykhailo Magal
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We discuss the theoretical model underlying 2BPA (two-band peer authentication), a practical alternative to conventional authentication of entities and data in IoT. In essence, this involves assembling a virtual map of authentication assets in the network, typically leading to many paths of confirmation between any pair of entities. This map is continuously updated, confirmed, and evaluated. The value of authentication along multiple disjoint paths becomes very clear, and we require analogues of triangulation to extend authentication along extended paths and deliver it along all possible paths. We discover that if an attacker wants to make an honest node falsely believe she has authenticated another, then the length of the authentication paths is of little importance. This is because optimal attack strategies correspond to minimal cuts in the authentication graph and do not contain multiple edges on the same path. The authentication provided by disjoint paths normally is additive (in entropy).Keywords: authentication, edge computing, industrial IoT, post-quantum resistance
Procedia PDF Downloads 190783 Mean Square Responses of a Cantilever Beam with Various Damping Mechanisms
Authors: Yaping Zhao, Yimin Zhang
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In the present paper, the stationary random vibration of a uniform cantilever beam is investigated. Two types of damping mechanism, i.e. the external and internal viscous dampings, are taken into account simultaneously. The excitation form is the support motion, and it is ideal white. Because two type of damping mechanism are considered concurrently, the product of the modal damping ratio and the natural frequency is not a constant anymore. As a result, the infinite definite integral encountered in the process of computing the mean square response is more complex than that in the existing literature. One signal progress of this work is to have calculated these definite integrals accurately. The precise solution of the mean square response is thus obtained in the infinite series form finally. Numerical examples are supplied and the numerical outcomes acquired confirm the validity of the theoretical analyses.Keywords: random vibration, cantilever beam, mean square response, white noise
Procedia PDF Downloads 375782 Hardware for Genetic Algorithm
Authors: Fariborz Ahmadi, Reza Tati
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Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.Keywords: hardware, genetic algorithm, computer science, engineering
Procedia PDF Downloads 494781 Investigation of Genetic Variation among Anemone narcissiflora L. Population Using PCR-RAPD Molecular Marker
Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian
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Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR
Procedia PDF Downloads 465780 Effect of Haemophilus Influenzae Type B (HIB) Vaccination on Child Anthropometry in India: Evidence from Young Lives Study
Authors: Swati Srivastava, Ashish Kumar Upadhyay
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Haemophilus influenzae Type B (Hib) cause infections of pneumonia, meningitis, epiglottises and other invasive disease exclusively among children under age five. Occurrence of these infections may impair child growth by causing micronutrient deficiency. Using longitudinal data from first and second waves of Young Lives Study conducted in India during 2002 and 2006-07 respectively and multivariable logistic regression models (using generalised estimation equation to take into account the cluster nature of sample), this study aims to examine the impact of Hib vaccination on child anthropometric outcomes (stunting, underweight and wasting) in India. Bivariate result shows that, a higher percent of children were stunted and underweight among those who were not vaccinated against Hib (39% & 48% respectively) as compare to those who were vaccinated (31% and 39% respectively).The risk of childhood stunting and underweight was significantly lower among children who were vaccinated against Hib (odds ratio: 0.77, 95% CI: 0.62-0.96 and odds ratio: 0.79, 95% C.I: 0.64-0.98 respectively) as compare to the unvaccinated children. No significant association was found between vaccination status against Hib and childhood wasting. Moreover, in the statistical models, about 13% of stunting and 12% of underweight could be attributable to lack of vaccination against Hib in India. Study concludes that vaccination against Hib- in addition to being a major intervention for reducing childhood infectious disease and mortality- can be consider as a potential tool for reducing the burden of undernutrition in India. Therefore, the Government of India must include the vaccine against Hib into the Universal Immunization Programme in India.Keywords: Haemophilus influenzae Type-B, Stunting, Underweight, Wasting, Young Lives Study (YLS), India
Procedia PDF Downloads 328779 Deploying a Platform as a Service Cloud Solution to Support Student Learning
Authors: Jiangping Wang
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This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.Keywords: PaaS, database environment, e-learning, web server
Procedia PDF Downloads 259778 Pregnancy Nutritional Status in Ethiopia: A Case Study of Pregnant Women in Shashemene District, Southern Oromia Region
Authors: Yoseph Gela Ali
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Inadequate quality and quantity diet is one of the major reasons for high levels of malnutrition in pregnant women. Across-sectional survey was conducted in Shashemene District, Southern Oromia Region. A two-stage cluster sampling technique was used to select a representative sample of 15190 pregnant women aged 20-50 years from four rural villages Energy and nutrient intakes from foods were calculated from one-day weighed food records on a sub-sample (n = 83). The result of the study showed that the intakes of most nutrients were lower than the recommended intake. The energy intake of the study participants both in 2nd and 3rd trimesters of pregnancy were 2,308 kcal and 1,420.5 kcal compared to the recommended 2,340 kcal and 2,452 kcal, respectively. Except iron, almost all micronutrient intakes were lower than the recommended intake. Vitamin A intake was 3 µg compared with the recommended 800 µg, while protein intake of the study respondents in 2nd and 3rd trimester of pregnancy was 45.9 g and 31.5 g, respectively, compared with the recommended 71 g. Risk factors for under nutrition were multiple pregnancy and no consumption of cereal-based foods. This study revealed that the energy and nutrient intake of the pregnant women in the study area was below the recommended intakes. Furthermore, the situation might be aggravated by the high phytate content food consumption reported. Nutritional status of pregnant women in the study area was not adequate to support the increased energy and nutrient requirement of the participants.Keywords: nutrition, pregnancy, protein, vitamin, energy
Procedia PDF Downloads 129777 3D Visualization for the Relationship of the Urban Rule and Building Form by Using CityEngine
Authors: Chin Ku, Han liang Lin
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The purpose of this study is to visualize how the rule related to urban design influences the building form by 3D modeling software CityEngine. In order to make the goal of urban design clearly connect to urban form, urban planner or designer should understand how the rule affects the form, especially the building form. In Taiwan, the rule pertained to urban design includes traditional zoning, urban design review and building codes. However, zoning cannot precisely expect the outcome of building form and lack of thinking about public realm and 3D form. In addition to that, urban design review is based on case by case, do not have a comprehensive regulation plan and the building code is just for general regulation. Therefore, rule cannot make the urban form reach the vision or goal of the urban design. Consequently, another kind of zoning called Form-based code (FBC) has arisen. This study uses the component of FBC which pertained to urban fabric such as street width, block and plot size, etc., to be the variants of building form, and find out the relationship between the rule and building form. There are three stages of this research, it will start from a field survey of Taichung City in Taiwan to induce the rule-building form relationship by using cluster analysis and descriptive Statistics. Second, visualize the relationship through the parameterized and codified process in CityEngine which is the procedural modeling, and can analyze, monitor and visualize the 3D world. Last, compare the CityEngine result with real world to examine how extent do this model represent the real world appearance.Keywords: 3D visualization, CityEngine, form-based code, urban form
Procedia PDF Downloads 538776 Neural Changes Associated with Successful Antidepressant Treatment in Adolescents with Major Depressive Disorder
Authors: Dung V. H. Pham, Kathryn Cullen
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Introduction: 40% of adolescents with major depression (MDD) are unresponsive to 1st line antidepressant treatment. The neural mechanism underlying treatment-responsive and treatment-resistant depression in adolescent are unclear. Amygdala is important for emotion processing and has been implicated in mood disorders. Past research has shown abnormal amygdala connectivity in adolescents with MDD. This research study changes in amygdala resting-state functional connectivity to find neural correlates of successful antidepressant treatment. Methods: Thirteen adolescents aged 12-19 underwent rfMRI before and after 8-week antidepressant treatment and completed BDI-II at each scan. A whole-brain approach, using anatomically defined amygdala ROIs (1) identified brain regions that are highly synchronous with the amygdala, (2) correlated neural changes with changes in overall depression and specific symptom clusters within depression. Results: Some neural correlates were common across domains: (1) decreased amygdala RSFC with the default mode network (posterior cingulate, precuneus) is associated with improvement in overall depression and many symptom clusters, (2) increased amygdala RSFC with fusiform gyrus is associated with symptom improvement across many symptom clusters. We also found unique neural changes associated with symptom improvement in each symptom cluster. Conclusion: This is the first preliminary study that looks at neural correlates of antidepressant treatment response to overall depression as well as different clusters of symptoms of depression. The finding suggests both overlapping and distinct neural mechanisms underlying improvement in each symptom clusters within depression. Some brain regions found are also implicated in MDD among adults in previous literature.Keywords: depression, adolescents, fMRI, antidepressants
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