Search results for: guzheng playing techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6947

Search results for: guzheng playing techniques

3857 Comparison Between Genetic Algorithms and Particle Swarm Optimization Optimized Proportional Integral Derirative and PSS for Single Machine Infinite System

Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

Abstract:

Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

Procedia PDF Downloads 62
3856 Is Ag@TiO2 Core-Shell Nanoparticles Superior to Ag Surface Doped TiO2 Nanostructures?

Authors: Xiaohong Yang, Haitao Fu, Xizhong An, Aibing Yu

Abstract:

Silver@titanium dioxide (Ag@TiO2) core-shell nanostructures and Ag surface doped TiO2 particles (TiO2@Ag) have been designed and synthesized by sol-gel and hydrothermal methods under mild conditions. These two types of Ag/TiO2 nanocomposites were characterized in terms of their properties by various techniques such as transmission electron microscope (TEM), X-ray diffraction (XRD), Brunauer Emmett Teller (BET) and ultra violet-visible absorption spectroscopy (UV-Vis). Specifically, the photocatalystic performance and antibacterial behavior of such nanocomposites have been investigated and compared. It was found that The Ag@TiO2 core-shell nanostructures exhibit superior photocatalytic property to the Ag surface doped TiO2 particles under the reported conditions. While with UV pre-irradiation, the Ag@TiO2 core-shell composites exhibit better bactericidal performance. This is probably because the Ag cores tend to facilitate charge separation for TiO2, producing greater hydroxyl radicals on the surface of the TiO2 particles. These findings would be useful for the design and synthesis of Ag/TiO2 nanocomposites with desirable photocatalystic and antimicrobial activity for environmental applications.

Keywords: Ag@TiO2 core-shell nanoparticles, Ag surface doped TiO2 nanoparticles, photocatalysis, antibacterial

Procedia PDF Downloads 465
3855 The Impact of the Composite Expanded Graphite PCM on the PV Panel Whole Year Electric Output: Case Study Milan

Authors: Hasan A Al-Asadi, Ali Samir, Afrah Turki Awad, Ali Basem

Abstract:

Integrating the phase change material (PCM) with photovoltaic (PV) panels is one of the effective techniques to minimize the PV panel temperature and increase their electric output. In order to investigate the impact of the PCM on the electric output of the PV panels for a whole year, a lumped-distributed parameter model for the PV-PCM module has been developed. This development has considered the impact of the PCM density variation between the solid phase and liquid phase. This contribution will increase the assessment accuracy of the electric output of the PV-PCM module. The second contribution is to assess the impact of the expanded composite graphite-PCM on the PV electric output in Milan for a whole year. The novel one-dimensional model has been solved using MATLAB software. The results of this model have been validated against literature experiment work. The weather and the solar radiation data have been collected. The impact of expanded graphite-PCM on the electric output of the PV panel for a whole year has been investigated. The results indicate this impact has an enhancement rate of 2.39% for the electric output of the PV panel in Milan for a whole year.

Keywords: PV panel efficiency, PCM, numerical model, solar energy

Procedia PDF Downloads 156
3854 Improved Throttled Load Balancing Approach for Cloud Environment

Authors: Sushant Singh, Anurag Jain, Seema Sabharwal

Abstract:

Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to sell their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The improved procedure has been tested using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, load balancing, throttled

Procedia PDF Downloads 235
3853 Effectuation in Production: How Production Managers Can Apply Decision-Making Techniques of Successful Entrepreneurs

Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

Abstract:

What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

Procedia PDF Downloads 331
3852 Comparison Learning Vocabulary Implicitly and Explicitly

Authors: Akram Hashemi

Abstract:

This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.

Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy

Procedia PDF Downloads 319
3851 Efficiency and Limits of Physicochemical Treatment of Dairy Wastewater: A Case Study of Dairy Industry in Western Algeria

Authors: Khedidja Benouis

Abstract:

Environmental issues in the food industry are related to the water because it consumes water and release large volumes of wastewater. The treatment of such discharges techniques can be adapted to different situations encountered. For dairy effluents, it is necessary and very effective to use a treatment that eliminates much of the pollutant load,thus, to drastically reduce the organic loading rate. This study aims to evaluate the Efficiency and limitations of physicochemical treatment by coagulation - flocculation of liquid effluent from this type of food industry in Algeria, to give an example of the type and the degree of pollution generated by this sector and in order to reduce pollution and minimize its environmental issues. Coagulation - flocculation-sedimentation was carried out using lime without addition of additive (flocculant), the processing efficiency is indicated by the concentration of pollutants in treated water. The results show that treatment is not sufficient to remove organic pollution, but it has significantly reduced the Total suspended solids (TSS), nitrate (NO3-N) and phosphate (PO4-P).

Keywords: Algeria, coagulation-flocculation, dairy effluent, treatment

Procedia PDF Downloads 405
3850 Identify Users Behavior from Mobile Web Access Logs Using Automated Log Analyzer

Authors: Bharat P. Modi, Jayesh M. Patel

Abstract:

Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

Procedia PDF Downloads 344
3849 Effect of Gamma Irradiation on the Crystalline Structure of Poly(Vinylidene Fluoride)

Authors: Adriana Souza M. Batista, Cláubia Pereira, Luiz O. Faria

Abstract:

The irradiation of polymeric materials has received much attention because it can produce diverse changes in chemical structure and physical properties. Thus, studying the chemical and structural changes of polymers is important in practice to achieve optimal conditions for the modification of polymers. The effect of gamma irradiation on the crystalline structure of poly(vinylidene fluoride) (PVDF) has been investigated using differential scanning calorimetry (DSC) and X-ray diffraction techniques (XRD). Gamma irradiation was carried out in atmosphere air with doses between 100 kGy at 3,000 kGy with a Co-60 source. In the melting thermogram of the samples irradiated can be seen a bimodal melting endotherm is detected with two melting temperature. The lower melting temperature is attributed to melting of crystals originally present and the higher melting peak due to melting of crystals reorganized upon heat treatment. These results are consistent with those obtained by XRD technique showing increasing crystallinity with increasing irradiation dose, although the melting latent heat is decreasing.

Keywords: differential scanning calorimetry, gamma irradiation, PVDF, X-ray diffraction technique

Procedia PDF Downloads 383
3848 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm

Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

Abstract:

Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

Procedia PDF Downloads 391
3847 Opto-Electronic Study of the Silicon Nitride Doped Cerium Thin Films Deposed by Evaporation

Authors: Bekhedda Kheira

Abstract:

Rare earth-doped luminescent materials (Ce, Eu, Yb, Tb, etc.) are now widely used in flat-screen displays, fluorescent lamps, and photovoltaic solar cells. They exhibit several fine emission bands in a spectral range from near UV to infrared when added to inorganic materials. This study chose cerium oxide (CeO2) because of its exceptional intrinsic properties, energy levels, and ease of implementation of doped layer synthesis. In this study, thin films were obtained by the evaporation deposition technique of cerium oxide (CeO2) on silicon Nitride (SiNx) layers and then annealing under nitrogen N2. The characterization of these films was carried out by different techniques, scanning electron microscopy (SEM) to visualize morphological properties and (EDS) was used to determine the elemental composition of individual dots, optical analysis characterization of thin films was studied by a spectrophotometer in reflectance mode to determine different energies gap of the nanostructured layers and to adjust these values for the photovoltaic application.

Keywords: thin films, photovoltaic, rare earth, evaporation

Procedia PDF Downloads 61
3846 Modeling Food Popularity Dependencies Using Social Media Data

Authors: DEVASHISH KHULBE, MANU PATHAK

Abstract:

The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

Procedia PDF Downloads 100
3845 Mechanical Properties of ECAP-Biomedical Titanium Materials: A Review

Authors: Mohsin Talib Mohammed, Zahid A. Khan, Arshad N. Siddiquee

Abstract:

The wide use of titanium (Ti) materials in medicine gives impetus to a search for development new techniques with elevated properties such as strength, corrosion resistance and Young's modulus close to that of bone tissue. This article presents the most recent state of the art on the use of equal channel angular pressing (ECAP) technique in evolving mechanical characteristics of the ultrafine-grained bio-grade Ti materials. Over past few decades, research activities in this area have grown enormously and have produced interesting results, including achieving the combination of conflicting properties that are desirable for biomedical applications by severe plastic deformation (SPD) processing. A comprehensive review of the most recent work in this area is systematically presented. The challenges in processing ultrafine-grained Ti materials are identified and discussed. An overview of the biomedical Ti alloys processed with ECAP technique is given in this review, along with a summary of their effect on the important mechanical properties that can be achieved by SPD processing. The paper also offers insights in the mechanisms underlying SPD.

Keywords: mechanical properties, ECAP, titanium, biomedical applications

Procedia PDF Downloads 441
3844 Student Performance and Confidence Analysis on Education Virtual Environments through Different Assessment Strategies

Authors: Rubén Manrique, Delio Balcázar, José Parrado, Sebastián Rodríguez

Abstract:

Hand in hand with the evolution of technology, education systems have moved to virtual environments to provide increased coverage and facilitate the access to education. However, measuring student performance in virtual environments presents significant challenges to ensure students are acquiring the expected skills. In this study, the confidence and performance of engineering students in virtual environments is analyzed through different evaluation strategies. The effect of the assessment strategy in student confidence is identified using educational data mining techniques. Four assessment strategies were used. First, a conventional multiple choice test; second, a multiple choice test with feedback; third, a multiple choice test with a second chance; and fourth; a multiple choice test with feedback and second chance. Our results show that applying testing with online feedback strategies can influence positively student confidence.

Keywords: assessment strategies, educational data mining, student performance, student confidence

Procedia PDF Downloads 338
3843 Improvement of the Aerodynamic Behaviour of a Land Rover Discovery 4 in Turbulent Flow Using Computational Fluid Dynamics (CFD)

Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

Abstract:

The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

Procedia PDF Downloads 298
3842 Multi-Disciplinary Optimisation Methodology for Aircraft Load Prediction

Authors: Sudhir Kumar Tiwari

Abstract:

The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

Procedia PDF Downloads 337
3841 High-Capacity Image Steganography using Wavelet-based Fusion on Deep Convolutional Neural Networks

Authors: Amal Khalifa, Nicolas Vana Santos

Abstract:

Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

Procedia PDF Downloads 63
3840 A Deep Learning Based Approach for Dynamically Selecting Pre-processing Technique for Images

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 135
3839 Heart Attack Prediction Using Several Machine Learning Methods

Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

Procedia PDF Downloads 126
3838 Evaluation of Wound Healing Activity of Curcuma purpurascens BI. Rhizomes in Rats

Authors: Elham Rouhollahi, Soheil Zorofchian Moghadamtousi, Salma Baig, Mahmood Ameen Abdulla, Zahurin Mohamed

Abstract:

This study was designed to assess cutaneous wound healing potential of hexane extract of Curcuma purpurascens rhizomes (HECP). Twenty-four rats were divided into 4 groups: 1. Negative, 2. Low dose, 3. High dose and 4. Treatment, with 6 rats in each group. Full-thickness incisions with a diameter of 2 cm were made on the back of each rat. Rats were topically treated two times a day for 15 days. Group 1-4 were treated with sterile distilled water, 5% and 10% of extract and intrasite gel, respectively. Masson's trichrome and hematoxylin staining techniques are employed for histological analysis revealed strong wound healing potential closer to that of conventional drug intrasite gel. HECP significantly decreased wound area and an increase in hydroxyproline, cellular proliferation, the number of blood vessels and the level of collagen synthesis was observed. Thus, it could be concluded that HECP possesses strong wound healing potential.

Keywords: Curcuma purpurascens, wound healing, histopathology, hematoxylin staining

Procedia PDF Downloads 418
3837 A Machine Learning-Based Approach to Capture Extreme Rainfall Events

Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

Procedia PDF Downloads 72
3836 Effects of Analogy Method on Children's Learning: Practice of Rainbow Experiments

Authors: Hediye Saglam

Abstract:

This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.

Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments

Procedia PDF Downloads 492
3835 Talent Sourcing Practices in Sri Lankan Software Industry

Authors: Malmi Amadoru, Chandana Gamage

Abstract:

Sri Lanka is emerging as a global IT-BPO hub topping up among the 20 global outsourcing destinations. When setting up a new venture in Sri Lanka, talent sourcing plays one of the key functions due to the rapid growth of workforce. Getting competent people with right skills for right positions leads organizations achieving its vision, mission and objectives. It also drives in earning competitive advantage over industry competitors. Thus it is crucial to scan and recruit the best employees to an organization. However there is no published information available on recruitment methods utilized in Sri Lankan software industry, as a study of this nature had not being conducted previously in Sri Lanka. The main objective of this study was to explore various talent sourcing practices exploited in Sri Lankan software industry. Also this study analyses the extent which Sri Lanka has adopted different recruitment strategies utilized in worldwide and its deviations. The research outcome is beneficial for HR professionals to identify the current trends in recruitment practices. Moreover investors who are interested in IT-BPO engagements can gain a thorough knowledge about talent sourcing techniques in Sri Lankan software industry. Finally, this research clues trending areas which can be further investigated in future.

Keywords: IT-BPO, recruitment, Sri Lanka, software industry, talent

Procedia PDF Downloads 474
3834 Software Quality Assurance in Component Based Software Development – a Survey Analysis

Authors: Abeer Toheed Quadri, Maria Abubakar, Mehreen Sirshar

Abstract:

Component Based Software Development (CBSD) is a new trend in software development. Selection of quality components is not enough to ensure software quality in Component Based Software System (CBSS). A software product is considered to be a quality product if it satisfies its customer’s needs and has minimum defects. Authors’ survey different research papers and analyzes various techniques which ensure software quality in component based software development. This paper includes an investigation about how to improve the quality of a component based software system without effecting quality attributes. The reported information is identified from literature survey. The developments of component based systems are rising as they reduce the development time, effort and cost by means of reuse. After analysis, it has been explored that in order to achieve the quality in a CBSS we need to have the components that are certified through software measure because the predictability of software quality attributes of system depend on the quality attributes of the constituent components, integration process and the framework used.

Keywords: CBSD (component based software development), CBSS (component based software system), quality components, SQA (software quality assurance)

Procedia PDF Downloads 396
3833 Vibration Measurements of Single-Lap Cantilevered SPR Beams

Authors: Xiaocong He

Abstract:

Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.

Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions

Procedia PDF Downloads 413
3832 Data Analysis to Uncover Terrorist Attacks Using Data Mining Techniques

Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

Abstract:

Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

Procedia PDF Downloads 388
3831 Experimental, Computational Fluid Dynamics and Theoretical Study of Cyclone Performance Based on Inlet Velocity and Particle Loading Rate

Authors: Sakura Ganegama Bogodage, Andrew Yee Tat Leung

Abstract:

This paper describes experimental, Computational Fluid Dynamics (CFD) and theoretical analysis of a cyclone performance, operated 1.0 g/m3 solid loading rate, at two different inlet velocities (5 m/s and 10 m/s). Comparing experimental results with theoretical and CFD simulation results, it is pronounced that the influence of solid in processing flow is significant than expected. Experimental studies based on gas- solid flows of cyclone separators are complicated as they required advanced sensitive measuring techniques, especially flow characteristics. Thus, CFD modelling and theoretical analysis are economical in analyzing cyclone separator performance but detailed clarifications of the application of these in cyclone separator performance evaluation is not yet discussed. The present study shows the limitations of influencing parameters of CFD and theoretical considerations, comparing experimental results and flow characteristics from CFD modelling.

Keywords: cyclone performance, inlet velocity, pressure drop, solid loading rate

Procedia PDF Downloads 222
3830 DNA Barcoding of Tree Endemic Campanula Species From Artvi̇n, Türki̇ye

Authors: Hayal Akyildirim Beğen, Özgür Emi̇nağaoğlu

Abstract:

DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch.

Keywords: campanula, DNA barcoding, endemic, türkiye, artvin

Procedia PDF Downloads 57
3829 Ontology-Based Backpropagation Neural Network Classification and Reasoning Strategy for NoSQL and SQL Databases

Authors: Hao-Hsiang Ku, Ching-Ho Chi

Abstract:

Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

Procedia PDF Downloads 248
3828 Synthesis, Characterization and Coating of the Zinc Oxide Nanoparticles on Cotton Fabric by Mechanical Thermo-Fixation Techniques to Impart Antimicrobial Activity

Authors: Imana Shahrin Tania, Mohammad Ali

Abstract:

The present study reports the synthesis, characterization and application of nano-sized zinc-oxide (ZnO) particles on a cotton fabric surface. The aim of the investigations is to impart the antimicrobial activity on textile cloth. Nanoparticle is synthesized by wet chemical method from zinc sulphate and sodium hydroxide. SEM (scanning electron micrograph) images are taken to demonstrate the surface morphology of nanoparticles. XRD analysis is done to determine the crystal size of the nanoparticle. With the conformation of nanoformation, the cotton woven fabric is treated with ZnO nanoparticle by mechanical thermo-fixation (pad-dry-cure) technique. To increase the wash durability of nano treated fabric, an acrylic binder is used as a fixing agent. The treated fabric shows up to 90% bacterial reduction for S. aureus (Staphylococcus aureus) and 87% for E. coli (Escherichia coli) which is appreciable for bacteria protective clothing.

Keywords: nanoparticle, zinc oxide, cotton fabric, antibacterial activity, binder

Procedia PDF Downloads 117