Search results for: Knowledge work
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5810

Search results for: Knowledge work

740 Low Resolution Single Neural Network Based Face Recognition

Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

Abstract:

This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

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739 Blind Source Separation for Convoluted Signals Based on Properties of Acoustic Transfer Function in Real Environments

Authors: Takaaki Ishibashi

Abstract:

Frequency domain independent component analysis has a scaling indeterminacy and a permutation problem. The scaling indeterminacy can be solved by use of a decomposed spectrum. For the permutation problem, we have proposed the rules in terms of gain ratio and phase difference derived from the decomposed spectra and the source-s coarse directions. The present paper experimentally clarifies that the gain ratio and the phase difference work effectively in a real environment but their performance depends on frequency bands, a microphone-space and a source-microphone distance. From these facts it is seen that it is difficult to attain a perfect solution for the permutation problem in a real environment only by either the gain ratio or the phase difference. For the perfect solution, this paper gives a solution to the problems in a real environment. The proposed method is simple, the amount of calculation is small. And the method has high correction performance without depending on the frequency bands and distances from source signals to microphones. Furthermore, it can be applied under the real environment. From several experiments in a real room, it clarifies that the proposed method has been verified.

Keywords: blind source separation, frequency domain independent component analysys, permutation correction, scale adjustment, target extraction.

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738 Effects of Canned Cycles and Cutting Parameters on Hole Quality in Cryogenic Drilling of Aluminum 6061-6T

Authors: M. N. Islam, B. Boswell, Y. R. Ginting

Abstract:

The influence of canned cycles and cutting parameters on hole quality in cryogenic drilling has been investigated experimentally and analytically. A three-level, three-parameter experiment was conducted by using the design-of-experiment methodology. The three levels of independent input parameters were the following: for canned cycles—a chip-breaking canned cycle (G73), a spot drilling canned cycle (G81), and a deep hole canned cycle (G83); for feed rates—0.2, 0.3, and 0.4 mm/rev; and for cutting speeds—60, 75, and 100 m/min. The selected work and tool materials were aluminum 6061-6T and high-speed steel (HSS), respectively. For cryogenic cooling, liquid nitrogen (LN2) was used and was applied externally. The measured output parameters were the three widely used quality characteristics of drilled holes—diameter error, circularity, and surface roughness. Pareto ANOVA was applied for analyzing the results. The findings revealed that the canned cycle has a significant effect on diameter error (contribution ratio 44.09%) and small effects on circularity and surface finish (contribution ratio 7.25% and 6.60%, respectively). The best results for the dimensional accuracy and surface roughness were achieved by G81. G73 produced the best circularity results; however, for dimensional accuracy, it was the worst level.

Keywords: Circularity, diameter error, drilling canned cycle, Pareto ANOVA, surface roughness.

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737 Efficiency of Investments, Financed from EU Funds in Small and Medium Enterprises in Poland

Authors: Jolanta Brodowska-Szewczuk

Abstract:

The article includes the results and conclusions from empirical researches that had been done. The research focuses on the impact of investments made in small and medium-sized enterprises financed from EU funds on the competitiveness of these companies. The researches includes financial results in sales revenue and net income, expenses, and many other new products/services on offer, higher quality products and services, more modern methods of production, innovation in management processes, increase in the number of customers, increase in market share, increase in profitability of production and provision of services. The main conclusions are that, companies with direct investments under this measure shall apply the modern methods of production. The consequence of this is to increase the quality of our products and services. Furthermore, both small and medium-sized enterprises have introduced new products and services. Investments were carried out, thus enabling better work organization in enterprises. Entrepreneurs would guarantee higher quality of service, which would result in better relationships with their customers, what is more, noting the rise in number of clients. More than half of the companies indicated that the investments contributed to the increase in market share. Same thing as for market reach and brand recognition of particular company. An interesting finding is that, investments in small enterprises were more effective than medium-sized enterprises.

Keywords: Competitiveness, efficiency, EU funds, small and medium-sized enterprises.

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736 Novel Hybrid Method for Gene Selection and Cancer Prediction

Authors: Liping Jing, Michael K. Ng, Tieyong Zeng

Abstract:

Microarray data profiles gene expression on a whole genome scale, therefore, it provides a good way to study associations between gene expression and occurrence or progression of cancer. More and more researchers realized that microarray data is helpful to predict cancer sample. However, the high dimension of gene expressions is much larger than the sample size, which makes this task very difficult. Therefore, how to identify the significant genes causing cancer becomes emergency and also a hot and hard research topic. Many feature selection algorithms have been proposed in the past focusing on improving cancer predictive accuracy at the expense of ignoring the correlations between the features. In this work, a novel framework (named by SGS) is presented for stable gene selection and efficient cancer prediction . The proposed framework first performs clustering algorithm to find the gene groups where genes in each group have higher correlation coefficient, and then selects the significant genes in each group with Bayesian Lasso and important gene groups with group Lasso, and finally builds prediction model based on the shrinkage gene space with efficient classification algorithm (such as, SVM, 1NN, Regression and etc.). Experiment results on real world data show that the proposed framework often outperforms the existing feature selection and prediction methods, say SAM, IG and Lasso-type prediction model.

Keywords: Gene Selection, Cancer Prediction, Lasso, Clustering, Classification.

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735 Computational Investigation of Air-Gas Venturi Mixer for Powered Bi-Fuel Diesel Engine

Authors: Mofid Gorjibandpy, Mehdi Kazemi Sangsereki

Abstract:

In a bi-fuel diesel engine, the carburetor plays a vital role in switching from fuel gas to petrol mode operation and viceversa. The carburetor is the most important part of the fuel system of a diesel engine. All diesel engines carry variable venturi mixer carburetors. The basic operation of the carburetor mainly depends on the restriction barrel called the venturi. When air flows through the venturi, its speed increases and its pressure decreases. The main challenge focuses on designing a mixing device which mixes the supplied gas is the incoming air at an optimum ratio. In order to surmount the identified problems, the way fuel gas and air flow in the mixer have to be analyzed. In this case, the Computational Fluid Dynamics or CFD approach is applied in design of the prototype mixer. The present work is aimed at further understanding of the air and fuel flow structure by performing CFD studies using a software code. In this study for mixing air and gas in the condition that has been mentioned in continuance, some mixers have been designed. Then using of computational fluid dynamics, the optimum mixer has been selected. The results indicated that mixer with 12 holes can produce a homogenous mixture than those of 8-holes and 6-holes mixer. Also the result showed that if inlet convergency was smoother than outlet divergency, the mixture get more homogenous, the reason of that is in increasing turbulence in outlet divergency.

Keywords: Computational Fluid Dynamics, Venturi mixer, Air-fuel ratio, Turbulence.

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734 Pattern Recognition Based Prosthesis Control for Movement of Forearms Using Surface and Intramuscular EMG Signals

Authors: Anjana Goen, D. C. Tiwari

Abstract:

Myoelectric control system is the fundamental component of modern prostheses, which uses the myoelectric signals from an individual’s muscles to control the prosthesis movements. The surface electromyogram signal (sEMG) being noninvasive has been used as an input to prostheses controllers for many years. Recent technological advances has led to the development of implantable myoelectric sensors which enable the internal myoelectric signal (MES) to be used as input to these prostheses controllers. The intramuscular measurement can provide focal recordings from deep muscles of the forearm and independent signals relatively free of crosstalk thus allowing for more independent control sites. However, little work has been done to compare the two inputs. In this paper we have compared the classification accuracy of six pattern recognition based myoelectric controllers which use surface myoelectric signals recorded using untargeted (symmetric) surface electrode arrays to the same controllers with multichannel intramuscular myolectric signals from targeted intramuscular electrodes as inputs. There was no significant enhancement in the classification accuracy as a result of using the intramuscular EMG measurement technique when compared to the results acquired using the surface EMG measurement technique. Impressive classification accuracy (99%) could be achieved by optimally selecting only five channels of surface EMG.

Keywords: Discriminant Locality Preserving Projections (DLPP), myoelectric signal (MES), Sparse Principal Component Analysis (SPCA), Time Frequency Representations (TFRs).

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733 Collaborative Reflexive/Reflective Teaching and Action Research in TESL

Authors: O. F. Elkommos

Abstract:

Teaching English as a Second Language (TESL) has become a very rich area of research. Practitioners or teachers of English as a foreign or a second language are now promoting both collaborative learning and collaborative teaching. Students learning a language collaboratively and cooperatively are learning in a better environment of team work where they learn from each other. Further, teaching English collaboratively also creates an enriching environment that is also very enriching to students’ and teachers’ experiences of learning and teaching. Moreover, action research stems from actual teacher concerns and students’ needs. Reflection in turn, on the experience of the material taught and the delivery of material is becoming an integral part of the teaching and learning experience self- evaluation and self-development. In this case, the concern of the research field in the area of TESL will be the development of teaching delivery, material and quality of learning. In the present research, the TESL module taught to year two students in the Faculty of Arts and Humanities, British University in Egypt (BUE) will be evaluated reflexively by the students and teachers. The module was taught to students in two different specialisms. It was taught and delivered through collaborative teaching and was evaluated by both teachers and students as very successful and enjoyable. The reflections of both teachers and students as well as student results confirm that it was a success.

Keywords: Action research, addressing differentiation, collaborative teaching, reflective teaching and learning, reflexive learning, reflexive teaching, self-development, self-evaluation, TESL.

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732 Sleep Scheduling Schemes Based on Location of Mobile User in Sensor-Cloud

Authors: N. Mahendran, R. Priya

Abstract:

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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731 Determination of Skills Gap between School-Based Learning and Laboratory-Based Learning in Omar Al-Mukhtar University

Authors: Aisha Othman, Crinela Pislaru, Ahmed Impes

Abstract:

This paper provides an identification of the existing practical skills gap between school-based learning (SBL) and laboratory based learning (LBL) in the Computing Department within the Faculty of Science at Omar Al-Mukhtar University in Libya. A survey has been conducted and the first author has elicited the responses of two groups of stakeholders, namely the academic teachers and students.

The primary goal is to review the main strands of evidence available and argue that there is a gap between laboratory and school-based learning in terms of opportunities for experiment and application of skills. In addition, the nature of experimental work within the laboratory at Omar Al-Mukhtar University needs to be reconsidered. Another goal of our study was to identify the reasons for students’ poor performance in the laboratory and to determine how this poor performance can be eliminated by the modification of teaching methods. Bloom’s taxonomy of learning outcomes has been applied in order to classify questions and problems into categories, and the survey was formulated with reference to third year Computing Department students. Furthermore, to discover students’ opinions with respect to all the issues, an exercise was conducted. The survey provided questions related to what the students had learnt and how well they had learnt. We were also interested in feedback on how to improve the course and the final question provided an opportunity for such feedback.

Keywords: Bloom’s taxonomy, e-learning, Omar Al-Mukhtar University.

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730 Vacuum Membrane Distillation for Desalination of Ground Water by using Flat Sheet Membrane

Authors: Bhausaheb L. Pangarkar, M.G. Sane, Saroj B. Parjane, Mahendra Guddad

Abstract:

The possibility of producing drinking water from brackish ground water using Vacuum membrane distillation (VMD) process was studied. It is a rising technology for seawater or brine desalination process. The process simply consists of a flat sheet hydrophobic micro porous PTFE membrane and diaphragm vacuum pump without a condenser for the water recovery or trap. In this work, VMD performance was investigated for aqueous NaCl solution and natural ground water. The influence of operational parameters such as feed flow rate (30 to 55 l/h), feed temperature (313 to 333 K), feed salt concentration (5000 to 7000 mg/l) and permeate pressure (1.5 to 6 kPa) on the membrane distillation (MD) permeation flux have been investigated. The maximum flux reached to 28.34 kg/m2 h at feed temperature, 333 K; vacuum pressure, 1.5 kPa; feed flow rate, 55 l/h and feed salt concentration, 7000 mg/l. The negligible effects in the reduction of permeate flux found over 150 h experimental run for salt water. But for the natural ground water application over 75 h, scale deposits observed on the membrane surface and 29% reduction in the permeate flux over 75 h. This reduction can be eliminated by acidification of feed water. Hence, promote the research attention in apply of VMD for the ground water purification over today-s conventional RO operation.

Keywords: VMD, hydrophobic PTFE flat membrane, desalination, ground water

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729 Extraction of Bran Protein Using Enzymes and Polysaccharide Precipitation

Authors: Sudarat Jiamyangyuen, Tipawan Thongsook, Riantong Singanusong, Chanida Saengtubtim

Abstract:

Rice bran is normally used as a raw material for rice bran oil production or sold as feed with a low price. Conventionally, the protein in defatted rice bran was extracted using alkaline extraction and acid precipitation, which involves in chemical usage and lowering some nutritious component. This study was conducted in order to extract of rice bran protein concentrate (RBPC) from defatted rice bran using enzymes and employing polysaccharides in a precipitating step. The properties of RBPC obtained will be compared to those of a control sample extracted using a conventional method. The results showed that extraction of protein from rice bran using enzymes exhibited the higher protein recovery compared to that extraction with alkaline. The extraction conditions using alcalase 2% (v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield (32.09%) in extracted solution compared to other enzymes. Rice bran protein concentrate powder prepared by a precipitation step using alginate (protein in solution: alginate 1:0.016) exhibited the highest protein (27.55%) and yield (6.84%). Precipitation using alginate was better than that of acid. RBPC extracted with alkaline (ALK) or enzyme alcalase (ALC), then precipitated with alginate (AL) (samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation rate of 75% and 91.30%, respectively. Therefore, protein precipitation using alginate was then selected. Amino acid profile of control sample, and sample precipitated with alginate, as compared to casein and soy protein isolated, showed that control sample showed the highest content among all sample. Functional property study of RBP showed that the highest nitrogen solubility occurred in pH 8-10. There was no statically significant between emulsion capacity and emulsion stability of control and sample precipitated by alginate. However, control sample showed a higher of foaming capacity and foaming stability compared to those of sample precipitated with alginate. The finding was successful in terms of minimizing chemicals used in extraction and precipitation steps in preparation of rice bran protein concentrate. This research involves in a production of value-added product in which the double amount of protein (28%) compared to original amount (14%) contained in rice bran could be beneficial in terms of adding to food products e.g. healthy drink with high protein and fiber. In addition, the basic knowledge of functional property of rice bran protein concentrate was obtained, which can be used to appropriately select the application of this value-added product from rice bran.

Keywords: Alginate, carrageenan, rice bran, rice bran protein.

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728 Calibration of Syringe Pumps Using Interferometry and Optical Methods

Authors: E. Batista, R. Mendes, A. Furtado, M. C. Ferreira, I. Godinho, J. A. Sousa, M. Alvares, R. Martins

Abstract:

Syringe pumps are commonly used for drug delivery in hospitals and clinical environments. These instruments are critical in neonatology and oncology, where any variation in the flow rate and drug dosing quantity can lead to severe incidents and even death of the patient. Therefore it is very important to determine the accuracy and precision of these devices using the suitable calibration methods. The Volume Laboratory of the Portuguese Institute for Quality (LVC/IPQ) uses two different methods to calibrate syringe pumps from 16 nL/min up to 20 mL/min. The Interferometric method uses an interferometer to monitor the distance travelled by a pusher block of the syringe pump in order to determine the flow rate. Therefore, knowing the internal diameter of the syringe with very high precision, the travelled distance, and the time needed for that travelled distance, it was possible to calculate the flow rate of the fluid inside the syringe and its uncertainty. As an alternative to the gravimetric and the interferometric method, a methodology based on the application of optical technology was also developed to measure flow rates. Mainly this method relies on measuring the increase of volume of a drop over time. The objective of this work is to compare the results of the calibration of two syringe pumps using the different methodologies described above. The obtained results were consistent for the three methods used. The uncertainties values were very similar for all the three methods, being higher for the optical drop method due to setup limitations.

Keywords: Calibration, interferometry, syringe pump, optical method, uncertainty.

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727 Embedded Semi-Fragile Signature Based Scheme for Ownership Identification and Color Image Authentication with Recovery

Authors: M. Hamad Hassan, S.A.M. Gilani

Abstract:

In this paper, a novel scheme is proposed for Ownership Identification and Color Image Authentication by deploying Cryptography & Digital Watermarking. The color image is first transformed from RGB to YST color space exclusively designed for watermarking. Followed by color space transformation, each channel is divided into 4×4 non-overlapping blocks with selection of central 2×2 sub-blocks. Depending upon the channel selected two to three LSBs of each central 2×2 sub-block are set to zero to hold the ownership, authentication and recovery information. The size & position of sub-block is important for correct localization, enhanced security & fast computation. As YS ÔèÑ T so it is suitable to embed the recovery information apart from the ownership and authentication information, therefore 4×4 block of T channel along with ownership information is then deployed by SHA160 to compute the content based hash that is unique and invulnerable to birthday attack or hash collision instead of using MD5 that may raise the condition i.e. H(m)=H(m'). For recovery, intensity mean of 4x4 block of each channel is computed and encoded upto eight bits. For watermark embedding, key based mapping of blocks is performed using 2DTorus Automorphism. Our scheme is oblivious, generates highly imperceptible images with correct localization of tampering within reasonable time and has the ability to recover the original work with probability of near one.

Keywords: Hash Collision, LSB, MD5, PSNR, SHA160

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726 Development and in vitro Characterization of Self-nanoemulsifying Drug Delivery Systems of Valsartan

Authors: P. S. Rajinikanth, Yeoh Suyu, Sanjay Garg

Abstract:

The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.

Keywords: Self Emulsifying Drug Delivery System, Valsartan, Bioavailability, poorly soluble drug.

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725 Influence of Power Flow Controller on Energy Transaction Charges in Restructured Power System

Authors: Manisha Dubey, Gaurav Gupta, Anoop Arya

Abstract:

The demand for power supply increases day by day in developing countries like India henceforth demand of reactive power support in the form of ancillary services provider also has been increased. The multi-line and multi-type Flexible alternating current transmission system (FACTS) controllers are playing a vital role to regulate power flow through the transmission line. Unified power flow controller and interline power flow controller can be utilized to control reactive power flow through the transmission line. In a restructured power system, the demand of such controller is being popular due to their inherent capability. The transmission pricing by using reactive power cost allocation through modified matrix methodology has been proposed. The FACTS technologies have quite costly assembly, so it is very useful to apportion the expenses throughout the restructured electricity industry. Therefore, in this work, after embedding the FACTS devices into load flow, the impact on the costs allocated to users in fraction to the transmission framework utilization has been analyzed. From the obtained results, it is clear that the total cost recovery is enhanced towards the Reactive Power flow through the different transmission line for 5 bus test system. The fair pricing policy towards reactive power can be achieved by the proposed method incorporating FACTS controller towards cost recovery of the transmission network.

Keywords: Inter line power flow controller, Transmission Pricing, Unified power flow controller, cost allocation.

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724 Artificial Intelligent Approach for Machining Titanium Alloy in a Nonconventional Process

Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama

Abstract:

Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.

Keywords: Ti-5Al-2.5Sn, material removal rate, copper tungsten, positive polarity, artificial neural network, multi-layer perceptron.

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723 Heat Transfer and Entropy Generation in a Partial Porous Channel Using LTNE and Exothermicity/Endothermicity Features

Authors: Mohsen Torabi, Nader Karimi, Kaili Zhang

Abstract:

This work aims to provide a comprehensive study on the heat transfer and entropy generation rates of a horizontal channel partially filled with a porous medium which experiences internal heat generation or consumption due to exothermic or endothermic chemical reaction. The focus has been given to the local thermal non-equilibrium (LTNE) model. The LTNE approach helps us to deliver more accurate data regarding temperature distribution within the system and accordingly to provide more accurate Nusselt number and entropy generation rates. Darcy-Brinkman model is used for the momentum equations, and constant heat flux is assumed for boundary conditions for both upper and lower surfaces. Analytical solutions have been provided for both velocity and temperature fields. By incorporating the investigated velocity and temperature formulas into the provided fundamental equations for the entropy generation, both local and total entropy generation rates are plotted for a number of cases. Bifurcation phenomena regarding temperature distribution and interface heat flux ratio are observed. It has been found that the exothermicity or endothermicity characteristic of the channel does have a considerable impact on the temperature fields and entropy generation rates.

Keywords: Entropy generation, exothermicity, endothermicity, forced convection, local thermal non-equilibrium, analytical modeling.

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722 Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording

Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

Abstract:

Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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721 Development of Cellulose Panels with Porous Structure for Sustainable Building Insulation

Authors: P. Garbagnoli, M. Musitelli, B. Del Curto, MP. Pedeferri

Abstract:

The study and development of an innovative material for building insulation is really important for a sustainable society in order to improve comfort and reducing energy consumption. The aim of this work is the development of insulating panels for sustainable buildings based on an innovative material made by cardboard and Phase Change Materials (PCMs). The research has consisted in laboratory tests whose purpose has been the obtaining of the required properties for insulation panels: lightweight, porous structures and mechanical resistance. PCMs have been used for many years in the building industry as smart insulation technology because of their properties of storage and release high quantity of latent heat at useful specific temperatures [1]- [2]. The integration of PCMs into cellulose matrix during the waste paper recycling process has been developed in order to obtain a composite material. Experiments on the productive process for the realization of insulating panels were done in order to make the new material suitable for building application. The addition of rising agents demonstrated the possibility to obtain a lighter structure with better insulation properties. Several tests were conducted to verify the new panel properties. The results obtained have shown the possibility to realize an innovative and sustainable material suitable to replace insulating panels currently used.

Keywords: Sustainability, recycling, waste cardboard, PCM, cladding system, insulating materials.

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720 Embodiment Design of an Azimuth-Altitude Solar Tracker

Authors: M. Culman, O. Lengerke

Abstract:

To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.

Keywords: Azimuth-altitude sun tracker, dual-axis solar tracker, photovoltaic system, solar energy, stand-alone power system.

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719 Effect of Moisture Content Compaction in the Geometry Definition of Earth Dams

Authors: Julian B. García, Virginie Q. R. Pinto, André P. Assis

Abstract:

This paper presents numerical flow and slope stability simulations in three typical sections of earth dams built in tropical regions, two homogeneous with different slope inclinations, and the other one heterogeneous with impermeable core. The geotechnical material parameters used in this work were obtained from a lab testing of physical characterization, compaction, consolidation, variable load permeability and saturated triaxial type CD for compacted soil samples with standard proctor energy at optimum moisture content (23%), optimum moisture content + 2% and optimum moisture content +5%. The objective is to analyze the general behavior of earth dams built in rainy regions where optimum moisture is exceeded. The factor of safety is satisfactory for the three sections compacted in all moisture content during the stages of operation and end of construction. On The other hand, the rapid drawdown condition is the critical phase for homogeneus dams configuration, the factor of safety obtained were unsatisfactory. In general, the heterogeneous dam behavior is more efficient due to the fact that the slopes are made up of gravel, which favors the dissipation of pore pressures during the rapid drawdown. For the critical phase, the slopes should have lower inclinations of the upstream and downstream slopes to guarantee stability, although it increases the costs.

Keywords: Earth dams, flow, moisture content, slope stability.

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718 Traffic Forecasting for Open Radio Access Networks Virtualized Network Functions in 5G Networks

Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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717 Detecting Geographically Dispersed Overlay Communities Using Community Networks

Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: Social networks, community detection, modularity optimization, geographically dispersed communities.

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716 Surrogate based Evolutionary Algorithm for Design Optimization

Authors: Maumita Bhattacharya

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Optimization is often a critical issue for most system design problems. Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, finding optimal solution to complex high dimensional, multimodal problems often require highly computationally expensive function evaluations and hence are practically prohibitive. The Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model presented in our earlier work [14] reduced computation time by controlled use of meta-models to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the meta-model are generated from a single uniform model. Situations like model formation involving variable input dimensions and noisy data certainly can not be covered by this assumption. In this paper we present an enhanced version of DAFHEA that incorporates a multiple-model based learning approach for the SVM approximator. DAFHEA-II (the enhanced version of the DAFHEA framework) also overcomes the high computational expense involved with additional clustering requirements of the original DAFHEA framework. The proposed framework has been tested on several benchmark functions and the empirical results illustrate the advantages of the proposed technique.

Keywords: Evolutionary algorithm, Fitness function, Optimization, Meta-model, Stochastic method.

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715 The Transfer of Energy Technologies in a Developing Country Context Towards Improved Practice from Past Successes and Failures

Authors: Lindiwe O. K. Mabuza, Alan C. Brent, Maxwell Mapako

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Technology transfer of renewable energy technologies is very often unsuccessful in the developing world. Aside from challenges that have social, economic, financial, institutional and environmental dimensions, technology transfer has generally been misunderstood, and largely seen as mere delivery of high tech equipment from developed to developing countries or within the developing world from R&D institutions to society. Technology transfer entails much more, including, but not limited to: entire systems and their component parts, know-how, goods and services, equipment, and organisational and managerial procedures. Means to facilitate the successful transfer of energy technologies, including the sharing of lessons are subsequently extremely important for developing countries as they grapple with increasing energy needs to sustain adequate economic growth and development. Improving the success of technology transfer is an ongoing process as more projects are implemented, new problems are encountered and new lessons are learnt. Renewable energy is also critical to improve the quality of lives of the majority of people in developing countries. In rural areas energy is primarily traditional biomass. The consumption activities typically occur in an inefficient manner, thus working against the notion of sustainable development. This paper explores the implementation of technology transfer in the developing world (sub-Saharan Africa). The focus is necessarily on RETs since most rural energy initiatives are RETs-based. Additionally, it aims to highlight some lessons drawn from the cited RE projects and identifies notable differences where energy technology transfer was judged to be successful. This is done through a literature review based on a selection of documented case studies which are judged against the definition provided for technology transfer. This paper also puts forth research recommendations that might contribute to improved technology transfer in the developing world. Key findings of this paper include: Technology transfer cannot be complete without satisfying pre-conditions such as: affordability, maintenance (and associated plans), knowledge and skills transfer, appropriate know how, ownership and commitment, ability to adapt technology, sound business principles such as financial viability and sustainability, project management, relevance and many others. It is also shown that lessons are learnt in both successful and unsuccessful projects.

Keywords: Technology transfer, technology management, renewable energy, sustainable development.

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714 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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713 A Microcontroller Implementation of Constrained Model Predictive Control

Authors: Amira Kheriji Abbes, Faouzi Bouani, Mekki Ksouri

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Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprisers as well as a transformer of organizations and markets. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In this paper, we propose an efficient firmware for the implementation of constrained MPC in the performed STM32 microcontroller using interior point method. Indeed, performances study shows good execution speed and low computational burden. These results encourage to develop predictive control algorithms to be programmed in industrial standard processes. The PID anti windup controller was also implemented in the STM32 in order to make a performance comparison with the MPC. The main features of the proposed constrained MPC framework are illustrated through two examples.

Keywords: Embedded software, microcontroller, constrainedModel Predictive Control, interior point method, PID antiwindup, Keil tool, C/Cµ language.

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712 Microbial Oil Production by Mixed Culture of Microalgae Chlorella sp. KKU-S2 and Yeast Torulaspora maleeae Y30

Authors: Ratanaporn Leesing, Rattanaporn Baojungharn, Thidarat Papone

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Compared to oil production from microorganisms, little work has been performed for mixed culture of microalgae and yeast. In this article it is aimed to show high oil accumulation potential of mixed culture of microalgae Chlorella sp. KKU-S2 and oleaginous yeast Torulaspora maleeae Y30 using sugarcane molasses as substrate. The monoculture of T. maleeae Y30 grew faster than that of microalgae Chlorella sp. KKU-S2. In monoculture of yeast, a biomass of 6.4g/L with specific growth rate (m) of 0.265 (1/d) and lipid yield of 0.466g/L were obtained, while 2.53g/L of biomass with m of 0.133 (1/d) and lipid yield of 0.132g/L were obtained for monoculture of Chlorella sp. KKU-S2. The biomass concentration in the mixed culture of T. maleeae Y30 with Chlorella sp. KKU-S2 increased faster and was higher compared with that in the monoculture and mixed culture of microalgae. In mixed culture of microalgae Chlorella sp. KKU-S2 and C. vulgaris TISTR8580, a biomass of 3.47g/L and lipid yield of 0.123 g/L were obtained. In mixed culture of T. maleeae Y30 with Chlorella sp. KKU-S2, a maximum biomass of 7.33 g/L and lipid yield of 0.808g/L were obtained. Maximum cell yield coefficient (YX/S, 0.229g/L), specific yield of lipid (YP/X, 0.11g lipid/g cells) and volumetric lipid production rate (QP, 0.115 g/L/d) were obtained in mixed culture of yeast and microalgae. Clearly, T. maleeae Y30 and Chlorella sp. KKU-S2 use sugarcane molasses as organic nutrients efficiently in mixed culture under mixotrophic growth. The biomass productivity and lipid yield are notably enhanced in comparison with monoculture.

Keywords: Microbial oil, Chlorella sp. KKU-S2, Chlorella vulgaris, Torulaspora maleeae Y30, mixed culture, biodiesel.

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711 Resource Leveling Optimization in Construction Projects of High Voltage Substations Using Nature-Inspired Intelligent Evolutionary Algorithms

Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: High voltage substations, nature-inspired algorithms, project management, meta-heuristics.

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