Search results for: small baseline subset algorithm

Authors: Kougioumtzis Konstantin, Rylander Pär, Karlsteen Magnus

Abstract:

Ball skills as a subset of fundamental motor skills are predictors for performance in sports. Currently, most tools evaluate ball skills utilizing subjective ratings. The aim of this study was to examine the psychometric properties of a newly developed instrument to objectively measure ball handling skills (BHS-test) utilizing digital instrument. Participants were a convenience sample of 213 adolescents (age M = 17.1 years, SD =3.6; 55% females, 45% males) recruited from upper secondary schools and invited to a sports hall for the assessment. The 8-item instrument incorporated both accuracy-based ball skill tests and repetitive-performance tests with a ball. Testers counted performance manually in the four tests (one throwing and three juggling tasks). Furthermore, assessment was technologically enhanced in the other four tests utilizing a ball machine, a Kinect camera and balls with motion sensors (one balancing and three rolling tasks). 3D printing technology was used to construct equipment, while all results were administered digitally with smart phones/tablets, computers and a specially constructed application to send data to a server. The instrument was deemed reliable (α = .77) and principal component analysis was used in a random subset (53 of the participants). Furthermore, latent variable modeling was employed to confirm the structure with the remaining subset (160 of the participants). The analysis showed good factorial-related validity with one factor explaining 57.90 % of the total variance. Four loadings were larger than .80, two more exceeded .76 and the other two were .65 and .49. The one factor solution was confirmed by a first order model with one general factor and an excellent fit between model and data (χ² = 16.12, DF = 20; RMSEA = .00, CI90 .00–.05; CFI = 1.00; SRMR = .02). The loadings on the general factor ranged between .65 and .83. Our findings indicate good reliability and construct validity for the BHS-test. To develop the instrument further, more studies are needed with various age-groups, e.g. children. We suggest using the BHS-test for diagnostic or assessment purpose for talent development and sports participation interventions that focus on ball games.

Keywords: ball-handling skills, ball-handling ability, technologically-enhanced measurements, assessment

Procedia PDF Downloads 78

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

Abstract:

Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 352

Authors: Y. Wang

Abstract:

The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CN_maxn²) where C is the iterations, N_max is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem

Procedia PDF Downloads 222

Authors: Ben Mansour Mouin, Elloumi Abdelkarim

Abstract:

We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

Procedia PDF Downloads 184

Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

Procedia PDF Downloads 324

Authors: Zhe Li, Aihua Cai

Abstract:

Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

Procedia PDF Downloads 63

Authors: Sarah Abdourraziq, Rachid Elbachtiri

Abstract:

The use of solar energy as a source for pumping water is one of the promising areas in the photovoltaic (PV) application. The energy of photovoltaic pumping systems (PVPS) can be widely improved by employing an MPPT algorithm. This will lead consequently to maximize the electrical motor speed of the system. This paper presents a modified incremental conductance (IncCond) MPPT algorithm with direct control method applied to a standalone PV pumping system. The influence of the algorithm parameters on system behavior is investigated and compared with the traditional (INC) method. The studied system consists of a PV panel, a DC-DC boost converter, and a PMDC motor-pump. The simulation of the system by MATLAB-SIMULINK is carried out. Simulation results found are satisfactory.

Keywords: photovoltaic pumping system (PVPS), incremental conductance (INC), MPPT algorithm, boost converter

Procedia PDF Downloads 387

Authors: Khaled Salah

Abstract:

Model order reduction has been one of the most challenging topics in the past years. In this paper, a hybrid solution of genetic algorithm (GA) and simulated annealing algorithm (SA) are used to approximate high-order transfer functions (TFs) to lower-order TFs. In this approach, hybrid algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. Compared to conventional mathematical methods that have been used to obtain a reduced order model of high order complex models, our proposed method provides better results in terms of reducing run-time. Thus, the proposed technique could be used in electronic design automation (EDA) tools.

Keywords: genetic algorithm, simulated annealing, model reduction, transfer function

Procedia PDF Downloads 134

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

Abstract:

In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

Procedia PDF Downloads 208

Authors: Baha-Aldeen S. Algmati, Ahmed R. Ballil

Abstract:

Multiphase flows occur widely in many engineering and industrial processes as well as in the environment we live in. In particular, bubbly flows are considered to be crucial phenomena in fluid flow applications and can be studied and analyzed experimentally, analytically, and computationally. In the present paper, the dynamic motion of an air bubble rising within a column of liquid is numerically simulated using an open-source CFD modeling tool 'OpenFOAM'. An interface tracking numerical algorithm called MULES algorithm, which is built-in OpenFOAM, is chosen to solve an appropriate mathematical model based on the volume of fluid (VOF) numerical method. The bubbles initially have a spherical shape and starting from rest in the stagnant column of liquid. The algorithm is initially verified against numerical results and is also validated against available experimental data. The comparison revealed that this algorithm provides results that are in a very good agreement with the 2D numerical data of other CFD codes. Also, the results of the bubble shape and terminal velocity obtained from the 3D numerical simulation showed a very good qualitative and quantitative agreement with the experimental data. The simulated rising bubbles yield a very small percentage of error in the bubble terminal velocity compared with the experimental data. The obtained results prove the capability of OpenFOAM as a powerful tool to predict the behavior of rising characteristics of the spherical bubbles in the stagnant column of liquid. This will pave the way for a deeper understanding of the phenomenon of the rise of bubbles in liquids.

Keywords: CFD simulations, multiphase flows, OpenFOAM, rise of bubble, volume of fluid method, VOF

Procedia PDF Downloads 112

Authors: Kholod Mohammad Abualnaja

Abstract:

A new algorithm is presented to find some new iterative methods for solving nonlinear equations F(x)=0 by using the variational iteration method. The efficiency of the considered method is illustrated by example. The results show that the proposed iteration technique, without linearization or small perturbation, is very effective and convenient.

Keywords: variational iteration method, nonlinear equations, Lagrange multiplier, algorithms

Procedia PDF Downloads 525

Authors: Jessada Monthasuwan, Charinsak Saetiaw, Chanchai Thongsopa

Abstract:

This paper presents the development and design of the curved rectangular patch arrays antenna for small missile application. This design uses a 0.1mm flexible copper sheet on the front layer and back layer, and a 1.8mm PVC substrate on a middle layer. The study used a small missile model with 122mm diameter size with speed 1.1 Mach and frequency range on ISM 2.4 GHz. The design of curved antenna can be installation on a cylindrical object like a missile. So, our proposed antenna design will have a small size, lightweight, low cost, and simple structure. The antenna was design and analysis by a simulation result from CST microwave studio and confirmed with a measurement result from a prototype antenna. The proposed antenna has a bandwidth covering the frequency range 2.35-2.48 GHz, the return loss below -10 dB and antenna gain 6.5 dB. The proposed antenna can be applied with a small guided missile effectively.

Keywords: rectangular patch arrays, small missile antenna, antenna design and simulation, cylinder PVC tube

Procedia PDF Downloads 301

Authors: O. Hakim, K. Hart, P. McCabe, J. Berry, L. E. Rhodes, N. Spyrou, A. Alfuraih, S. Lanham-New

Abstract:

It is known that skin pigmentation reduces the penetration of ultraviolet radiation (UVR) and thus photosynthesis of 25(OH)D. However, the ethnic differences in 25(OH)D production remain to be fully elucidated. This study aimed to investigate the differences in vitamin D production between Asian and Caucasian postmenopausal women, in response to a defined, controlled UVB exposure. Seventeen women; nine white Caucasian (skin phototype II and III), eight South Asian women (skin phototype IV and V) participated in the study, acting as their controls. Three blood samples were taken for measurement of 25(OH)D during the run-in period (nine days, no sunbed exposure) after which all subjects underwent an identical UVR exposure protocol irrespective of skin colour (nine days, three sunbed sessions: 6, 8 and 8 minutes respectively with approximately 80% of body surface exposed). Skin tone was measured four times during the study. Both groups showed a gradual increase in 25(OH)D with final levels significantly higher than baseline (p<0.01). 25(OH)D concentration mean from a baseline of 43.58±19.65 to 57.80±17.11 nmol/l among Caucasian and from 27.03±23.92 to 44.73±17.74 nmol/l among Asian women. The baseline status of vitamin D was classified as deficient among the Asian women and insufficient among the Caucasian women. The percentage increase in vitamin D3 among Caucasians was 39.86% (21.02) and 207.78% (286.02) in Asian subjects respectively. This greater response to UVR exposure reflects the lower baseline levels of the Asian subjects. The mixed linear model analysis identified a significant effect of duration of UVR exposure on the production of 25(OH)D. However, the model shows no significant effect of ethnicity and skin tone on the production of 25(OH)D. These novel findings indicate that people of Asian ethnicity have the full capability to produce a similar amount of vitamin D compared to the Caucasian group; initial vitamin D concentration influences the amount of UVB needed to reach equal serum concentrations.

Keywords: ethnicity, Caucasian, South Asian, vitamin D, ultraviolet radiation, UVR

Procedia PDF Downloads 523

Authors: Aishwarya Talapuru, Sri Silpa Padmanabhuni, B. Jyoshna

Abstract:

Cryptography helps in preventing threats to information security by providing various algorithms. This study introduces a new symmetric key encryption algorithm for information security which is linked with the "raagas" which means Indian traditional scale and pattern of music notes. This algorithm takes the plain text as input and starts its encryption process. The algorithm then randomly selects a raaga from the list of raagas that is assumed to be present with both sender and the receiver. The plain text is associated with the thus selected raaga and an intermediate cipher-text is formed as the algorithm converts the plain text characters into other characters, depending upon the rules of the algorithm. This intermediate code or cipher text is arranged in various patterns in three different rounds of encryption performed. The total number of rounds in the algorithm is equal to the multiples of 3. To be more specific, the outcome or output of the sequence of first three rounds is again passed as the input to this sequence of rounds recursively, till the total number of rounds of encryption is performed. The raaga selected by the algorithm and the number of rounds performed will be specified at an arbitrary location in the key, in addition to important information regarding the rounds of encryption, embedded in the key which is known by the sender and interpreted only by the receiver, thereby making the algorithm hack proof. The key can be constructed of any number of bits without any restriction to the size. A software application is also developed to demonstrate this process of encryption, which dynamically takes the plain text as input and readily generates the cipher text as output. Therefore, this algorithm stands as one of the strongest tools for information security.

Keywords: cipher text, cryptography, plaintext, raaga

Procedia PDF Downloads 274

Authors: Ammarah Irum, Muhammad Ali Tahir

Abstract:

Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

Procedia PDF Downloads 57

Authors: Shaimaa M. Mohamed, Haitham S. Hamza, Imane A. Saroit

Abstract:

Many wireless sensor network applications require K-coverage of the monitored area. In this paper, we propose a scalable harmony search based algorithm in terms of execution time, K-Coverage Enhancement Algorithm (KCEA), it attempts to enhance initial coverage, and achieve the required K-coverage degree for a specific application efficiently. Simulation results show that the proposed algorithm achieves coverage improvement of 5.34% compared to K-Coverage Rate Deployment (K-CRD), which achieves 1.31% when deploying one additional sensor. Moreover, the proposed algorithm is more time efficient.

Keywords: Wireless Sensor Networks (WSN), harmony search algorithms, K-Coverage, Mobile WSN

Procedia PDF Downloads 513

Authors: Mehmet Hakan Karaata

Abstract:

In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

Procedia PDF Downloads 373

Authors: Hyunchul Ahn, William X. S. Wong

Abstract:

Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

Procedia PDF Downloads 284

Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

Abstract:

Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

Procedia PDF Downloads 119

Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

Abstract:

In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

Procedia PDF Downloads 621

Authors: Cheng-Lin Liu, Fei Liu

Abstract:

For the multi-agent systems with agent's dynamics described by high-order integrator, and usual consensus algorithm composed of the state coordination control parts is proposed. Under communication delay, consensus algorithm in asynchronously-coupled form just can make the agents achieve a stationary consensus, and sufficient consensus condition is obtained based on frequency-domain analysis. To recover the original consensus state of the high-order agents without communication delay, besides, a predictor-based consensus algorithm is constructed via multiplying the delayed neighboring agents' states by a delay-related compensation part, and sufficient consensus condition is also obtained. Simulation illustrates the correctness of the results.

Keywords: high-order dynamic agents, communication delay, consensus, predictor-based algorithm

Procedia PDF Downloads 557

Authors: S. I. Nwadioha, M. S. Odimayo, G. T. A. Jombo, E. O. P. Nwokedi

Abstract:

Aims and Objectives: To determine the baseline CD4 positive T lymphocytes count of HIV/AIDS treatment naïve adults clients presenting for the first time treatment in Benue State University Teaching Hospital. Subjects and Methods: A total of 700 subjects age between 18 years to 70 years, were recruited for the study, comprising 600 HIV sero-positive patients and 100 healthy controls in Benue State University Teaching Hospital, Makurdi from 2013 to 2014. The CD4 counts of the subjects were evaluated using a Partec flow cytometer. Results: CD4 count of 200-299 cells/μl peaked with 25% (n=150/600)[control; 0%( n= 0/100)]. The study also showed that 44% (266/600) of HIV subjects had acquired immunodeficiency syndrome as defined by low CD4 counts below 200 cells/μl. Seventy-five per cent (n=451/600)of our patients would require to be placed on antiretroviral therapy with CD4 count of less than 350 cells/μl. At CD4 350 baseline criterion, age group 20-29 years had the highest demand 35%(160/451) for ARV followed by age groups 30-39 and 40-49 years with 28%(128/451) and 22%(98/451) respectively. Conclusion: There is a high prevalence of acquired immunodeficiency syndrome as defined by CD4 counts below 200 cells/μl, among the young active productive age group. The strict adopting of the ART WHO 2010 scale- up criteria doubles the number of the HIV clients that would qualify for ART with its attendant health benefits on the long run.

Keywords: CD4 counts, HIV patients, young age group, Nigeria

Procedia PDF Downloads 315

Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

Abstract:

This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

Procedia PDF Downloads 244

Authors: Mitat Uysal

Abstract:

A new met heuristic optimization algorithm called as Migrating Birds Optimization is used for curve fitting by rational cubic Bezier Curves. This requires solving a complicated multivariate optimization problem. In this study, the solution of this optimization problem is achieved by Migrating Birds Optimization algorithm that is a powerful met heuristic nature-inspired algorithm well appropriate for optimization. The results of this study show that the proposed method performs very well and being able to fit the data points to cubic Bezier Curves with a high degree of accuracy.

Keywords: algorithms, Bezier curves, heuristic optimization, migrating birds optimization

Procedia PDF Downloads 325

Authors: E. Tandis, E. Assareh

Abstract:

Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

Procedia PDF Downloads 309

Authors: Mayurachat Kanyamee, Srisuda Rassameepong, Narunest Chulakarn

Abstract:

This experimental pretest-posttest control group design aimed to examine the effects of a family-based intervention on increasing fruit and vegetable intake and reduce fat and sugar intake and nutritional status among school-age children. Children were randomized to experimental 68 children and control 68 children. The experimental group received the intervention based on Social Cognitive Theory. The control group received the school’s usual educational program regarding healthy eating behavior. Data were collected via three questionnaires including: demographic characteristics; fruit and vegetable intake; and fat and sugar intake at baseline, sixteen weeks after baseline. Analysis of the data included the use of descriptive statistic and independent t-test. Results revealed the significant differences between the experimental and control group, regarding: fruit and vegetable intake, fat and sugar intake and nutritional status at sixteenth week after baseline. The findings suggest a family-based intervention, based on SCT, appears to be effective to improve eating behavior, and nutritional status of school -age children. So, the intervention can be applied to improve eating behavior among other groups of children.

Keywords: family-based intervention, children, unhealthy food, food safety

Procedia PDF Downloads 262

Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

Abstract:

The skew detection and correction form an important part of digital document analysis. This is because uncompensated skew can deteriorate document features and can complicate further document image processing steps. Efficient text document analysis and digitization can rarely be achieved when a document is skewed even at a small angle. Once the documents have been digitized through the scanning system and binarization also achieved, document skew correction is required before further image analysis. Research efforts have been put in this area with algorithms developed to eliminate document skew. Skew angle correction algorithms can be compared based on performance criteria. Most important performance criteria are accuracy of skew angle detection, range of skew angle for detection, speed of processing the image, computational complexity and consequently memory space used. The standard Hough Transform has successfully been implemented for text documentation skew angle estimation application. However, the standard Hough Transform algorithm level of accuracy depends largely on how much fine the step size for the angle used. This consequently consumes more time and memory space for increase accuracy and, especially where number of pixels is considerable large. Whenever the Hough transform is used, there is always a tradeoff between accuracy and speed. So a more efficient solution is needed that optimizes space as well as time. In this paper, an improved Hough transform (HT) technique that optimizes space as well as time to robustly detect document skew is presented. The modified algorithm of Hough Transform presents solution to the contradiction between the memory space, running time and accuracy. Our algorithm starts with the first step of angle estimation accurate up to zero decimal place using the standard Hough Transform algorithm achieving minimal running time and space but lacks relative accuracy. Then to increase accuracy, suppose estimated angle found using the basic Hough algorithm is x degree, we then run again basic algorithm from range between ±x degrees with accuracy of one decimal place. Same process is iterated till level of desired accuracy is achieved. The procedure of our skew estimation and correction algorithm of text images is implemented using MATLAB. The memory space estimation and process time are also tabulated with skew angle assumption of within 00 and 450. The simulation results which is demonstrated in Matlab show the high performance of our algorithms with less computational time and memory space used in detecting document skew for a variety of documents with different levels of complexity.

Keywords: hough-transform, skew-detection, skew-angle, skew-correction, text-document

Procedia PDF Downloads 146

Authors: S. M. Javad Davoodi, Mojtaba Shourian

Abstract:

Groundwater table close to the ground surface causes major problems in construction and mining operation. One of the methods to control groundwater in such cases is using pumping wells. These pumping wells remove excess water from the site project and lower the water table to a desirable value. Although the efficiency of this method is acceptable, it needs high expenses to apply. It means even small improvement in a design of pumping wells can lead to substantial cost savings. In order to minimize the total cost in the method of pumping wells, a simulation-optimization approach is applied. The proposed model integrates MODFLOW as the simulation model with Firefly as the optimization algorithm. In fact, MODFLOW computes the drawdown due to pumping in an aquifer and the Firefly algorithm defines the optimum value of design parameters which are numbers, pumping rates and layout of the designing wells. The developed Firefly-MODFLOW model is applied to minimize the cost of the dewatering project for the ancient mosque of Kerman city in Iran. Repetitive runs of the Firefly-MODFLOW model indicates that drilling two wells with the total rate of pumping 5503 m3/day is the result of the minimization problem. Results show that implementing the proposed solution leads to at least 1.5 m drawdown in the aquifer beneath mosque region. Also, the subsidence due to groundwater depletion is less than 80 mm. Sensitivity analyses indicate that desirable groundwater depletion has an enormous impact on total cost of the project. Besides, in a hypothetical aquifer decreasing the hydraulic conductivity contributes to decrease in total water extraction for dewatering.

Keywords: groundwater dewatering, pumping wells, simulation-optimization, MODFLOW, firefly algorithm

Procedia PDF Downloads 285

Authors: Terry Lucas

Abstract:

Calculations are performed to quantify the potential contribution of each greenhouse gas emission reduction strategy. This approach facilitates the visualisation of the relative benefits of each, and it provides a potential baseline for the development of a plan of action that is rooted in quantitative evaluation. Emissions reductions are converted to potential de-escalation of global average temperature. A comprehensive plan is then presented which shows the potential benefits all the way out to year 2100. A target temperature de-escalation of 2oC was selected, but the plan shows a benefit of only 1.225oC. This latter disappointing result is in spite of new and powerful technologies introduced into the equation. These include nuclear fusion and alternative nuclear fission processes. Current technologies such as wind, solar and electric vehicles show surprisingly small constributions to the whole.

Keywords: climate change, emissions, drawdown, energy

Procedia PDF Downloads 122

Authors: Utkan Caliskan

Abstract:

Two types of numerical codes based on finite volume method are developed in order to solve compressible Euler equations to simulate the flow through forward facing step channel. Both algorithms have AUSM+- up (Advection Upstream Splitting Method) scheme for flux splitting and two-stage Runge-Kutta scheme for time stepping. In this study, the flux calculations differentiate between the algorithm based on OpenFOAM mesh format which is called 'face-based' algorithm and the basic algorithm which is called 'element-based' algorithm. The face-based algorithm avoids redundant flux computations and also is more flexible with hybrid grids. Moreover, some of OpenFOAM’s preprocessing utilities can be used on the mesh. Parallelization of the face based algorithm for which atomic operations are needed due to the shared memory model, is also presented. For several mesh sizes, 2.13x speed up is obtained with face-based approach over the element-based approach.

Keywords: cell centered finite volume method, compressible Euler equations, OpenFOAM mesh format, OpenMP

Procedia PDF Downloads 307