Search results for: watermark data rate.

Authors: S. Kumaravel, B. Venkataramani

Abstract:

In the literature, Improved Recycling Folded Cascode (IRFC) Operational Transconductance Amplifier (OTA) is proposed for enhancing the DC gain and the Unity Gain Bandwidth (UGB) of the Recycling Folded Cascode (RFC) OTA. In this paper, an enhanced IRFC (EIRFC) OTA which uses positive feedback at the cascode node is proposed for enhancing the differential mode (DM) gain without changing the unity gain bandwidth (UGB) and lowering the Common mode (CM) gain. For the purpose of comparison, IRFC and EIRFC OTAs are implemented using UMC 90nm CMOS technology and studied through simulation. From the simulation, it is found that the DM gain and CM gain of EIRFC OTA is higher by 6dB and lower by 38dB respectively, compared to that of IRFC OTA for the same power and area. The slew rate of EIRFC OTA is also higher by a factor of 1.5.

Keywords: Cascode Amplifier, CMRR, gm/ID Methodology, Recycling, Slew Rate.

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Authors: Nuraini Yusoff, Harun Budin, Salemah Ismail

Abstract:

A climate dependent model is proposed to simulate the population of Aedes aegypti mosquito. In developing the model, average temperature of Shah Alam, Malaysia was used to determine the development rate of each stage of the life cycle of mosquito. Rainfall dependent function was proposed to simulate the hatching rate of the eggs under several assumptions. The proposed transition matrix was obtained and used to simulate the population of eggs, larvae, pupae and adults mosquito. It was found that the peak of mosquito abundance comes during a relatively dry period following a heavy rainfall. In addition, lag time between the peaks of mosquito abundance and dengue fever cases in Shah Alam was estimated.

Keywords: simulation, Aedes aegypti, Lefkovitch matrix, rainfall dependent model, Shah Alam

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Authors: H. Aghayan, F. A. Hashemi, R. Yavari, S. Zolghadri

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In this work, a new composite adsorbent based on a mesoporous silica SBA-15 with platelet morphology and tin salt of tungstomolybdophosphoric (TWMP) acid was synthesized and applied for uranium adsorption from aqueous solution. The sample was characterized by X-ray diffraction, Fourier transfer infra-red, and N₂ adsorption-desorption analysis, and then, effect of various parameters such as concentration of metal ions and contact time on adsorption behavior was examined. The experimental result showed that the adsorption process was explained by the Langmuir isotherm model very well, and predominant reaction mechanism is physisorption. Kinetic data of adsorption suggest that the adsorption process can be described by the pseudo second-order reaction rate model.

Keywords: Platelet SBA-15, tungstomolybdophosphoric acid, adsorption, uranium ion.

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Authors: Ayşen Edirneligil, Mehmet Mucuk

Abstract:

In developing countries, one of the most important restrictions about the economic growth is the lack of national savings which are supposed to finance the investments. In order to overcome this restriction and achieve the higher rate of economic growth by increasing the level of output, countries choose the external borrowing. However, there is a dispute in the literature over the correlation between external debt and economic growth. The aim of this study is to examine the effects of external debt on Turkish economic growth by using VAR analysis with the quarterly data over the period of 2002:01-2014:04. In this respect, Johansen Cointegration Test, Impulse- Response Function and Variance Decomposition Tests will be used for analyses. Empirical findings show that there is no cointegration in the long run.

Keywords: Economic growth, external debt, time series analysis, Turkish economy.

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

Abstract:

Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.

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Authors: Hyun-Jun Shin, Jae-Jeong Kim, Hyoung-Kyu Song

Abstract:

In broadcasting and cellular system, a cooperative  scheme is proposed for the improvement of performance of bit error  rate. Up to date, the coverage of broadcasting system coexists with the  coverage of cellular system. Therefore each user in a cellular coverage  is frequently involved in a broadcasting coverage. The proposed  cooperative scheme is derived from the shared areas. The users receive  signals from both broadcasting station and cellular station. The  proposed scheme selects a cellular base station of a worse channel to  achieve better performance of bit error rate in cooperation. The  performance of the proposed scheme is evaluated in fading channel.

Keywords: Cooperative communication, diversity, STBC, CDD, channel condition, broadcasting system, cellular system.

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Authors: Joseph S. Ojo, Vincent A. Akpan, Oladayo G. Ajileye, Olalekan L, Ojo

Abstract:

In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.

Keywords: Fuzzy logic, intelligent algorithm, Nigeria, QoS, satellite applications, tropical weather.

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Authors: Soo- Young Ye, Dong-Hyun Kim

Abstract:

Obstructive sleep apnea in patients, between 70 and 80 percent, can be cured with just a posture correcting. The most import thing to do this is detection of obstructive sleep apnea. Detection of obstructive sleep apnea can be performed through heart rate variability analysis using power spectrum density analysis. After HRV analysis we needed to know the current position information for correcting the position. The pressure sensors of the array type were used to obtain position information. These sensors can obtain information from the experimenter about position. In addition, air cylinder corrected the position of the experimenter by lifting the bed. The experimenter can be changed position without breaking during sleep by the system. Polysomnograph recording were obtained from 10 patients. The results of HRV analysis were that NLF and LF/HF ratio increased, while NHF decreased during OSA. Position change had to be done the periods.

Keywords: Obstructive sleep apnea, Heart rate variability, Air cylinder, PSD, RR interval, ANS

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Authors: Wei Lifan, Zhang Huaiyu, Yang Yunbin, Li Jia

Abstract:

Through the analysis of the process digital design based on digital mockup, the fact indicates that a distributed cooperative supporting environment is the foundation conditions to adopt design approach based on DMU. Data access authorization is concerned firstly because the value and sensitivity of the data for the enterprise. The access control for administrators is often rather weak other than business user. So authors established an enhanced system to avoid the administrators accessing the engineering data by potential approach and without authorization. Thus the data security is improved.

Keywords: access control, DMU, PLM, virtual prototype.

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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Authors: M. Nikbakht, N. Choupani

Abstract:

In this paper delamination phenomenon in Carbon-Epoxy laminated composite material is investigated numerically. Arcan apparatus and specimen is modeled in ABAQUS finite element software for different loading conditions and crack geometries. The influence of variation of crack geometry on interlaminar fracture stress intensity factor and energy release rate for various mixed mode ratios and pure mode I and II was studied. Also, correction factors for this specimen for different crack length ratios were calculated. The finite element results indicate that for loading angles close to pure mode-II loading, a high ratio of mode-II to mode-I fracture is dominant and there is an opposite trend for loading angles close to pure mode-I loading. It confirms that by varying the loading angle of Arcan specimen pure mode-I, pure mode-II and a wide range of mixed-mode loading conditions can be created and tested. Also, numerical results confirm that the increase of the mode- II loading contribution leads to an increase of fracture resistance in the CF/PEI composite (i.e., a reduction in the total strain energy release rate) and the increase of the crack length leads to a reduction of interlaminar fracture resistance in the CF/PEI composite (i.e., an increase in the total interlaminar strain energy release rate).

Keywords: Fracture Mechanics, Mixed Mode, Arcan Specimen, Finite Element.

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Authors: Sayali Sandbhor, Ravindra Bapat, N. B. Chaphalkar

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Decisions for investment, buying and selling of properties depend upon the market value of that property. Issues arise in arriving at the actual value of the property as well as computing the rate of returns from the estate. Addressing valuation related issues through an understanding of behavior of real property rates provide the means to explore the quality of past decisions and to make valid future decisions. Pune, an important city in India, has witnessed a high rate of growth in past few years. Increased demand for housing and investment in properties has led to increase in the rates of real estate. An attempt has been made to study the change and behavior of rates of real estate and factors influencing the same in Pune city.

Keywords: Real estate, valuation, property rates, trend analysis

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Authors: Ashish Dhamaniya, Satish Chandra

Abstract:

Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: Normal distribution, percentile speed, speed spread ratio, traffic volume.

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Authors: A. Eman Mohammed

Abstract:

Algae-based fuel are considered a promising sources of clean energy, and because it has many advantages over traditional biofuel, research and business ventures have driven into developing and producing Algal-biofuel. But its production stages create a cost structure that it is not competitive with traditional fuels. Therefore, cost becomes the main obstacle in commercial production purpose. However, the present research which aims at using cost structure model, and designed MS-Dose program, to investigate the a mount of production cost and determined the parameter had great effect on it, second to measured the amount of contribution rate of algae in process the pollution by capturing Co2 from air . The result generated from the model shows that the production cost of biomass is between $0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than cost of other studies, while gallon costs between $3.4 - 3.5, more than traditional sources of oil about $1 ,which regarded as a rate of contribution of algal in capturing CO2 from air.

Keywords: Cost Structure Model, Operation Costs(Production Cost), Capital Costs, Algae.

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Authors: Amel Abdoullah Ahmed Dghais, Mohd Tahir Ismail

Abstract:

In this paper the core objective is to apply discrete wavelet transform and maximal overlap discrete wavelet transform functions namely Haar, Daubechies2, Symmlet4, Coiflet2 and discrete approximation of the Meyer wavelets in non stationary financial time series data from Dow Jones index (DJIA30) of US stock market. The data consists of 2048 daily data of closing index from December 17, 2004 to October 23, 2012. Unit root test affirms that the data is non stationary in the level. A comparison between the results to transform non stationary data to stationary data using aforesaid transforms is given which clearly shows that the decomposition stock market index by discrete wavelet transform is better than maximal overlap discrete wavelet transform for original data.

Keywords: Discrete wavelet transform, maximal overlap discrete wavelet transform, stationarity, autocorrelation function.

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Authors: K. Chinda, P. Luangpaiboon

Abstract:

This paper presents the comparative study of coded data methods for finding the benefit of concealing the natural data which is the mercantile secret. Influential parameters of the number of replicates (rep), treatment effects (τ) and standard deviation (σ) against the efficiency of each transformation method are investigated. The experimental data are generated via computer simulations under the specified condition of the process with the completely randomized design (CRD). Three ways of data transformation consist of Box-Cox, arcsine and logit methods. The difference values of F statistic between coded data and natural data (Fc-Fn) and hypothesis testing results were determined. The experimental results indicate that the Box-Cox results are significantly different from natural data in cases of smaller levels of replicates and seem to be improper when the parameter of minus lambda has been assigned. On the other hand, arcsine and logit transformations are more robust and obviously, provide more precise numerical results. In addition, the alternate ways to select the lambda in the power transformation are also offered to achieve much more appropriate outcomes.

Keywords: Experimental Designs, Box-Cox, Arcsine, Logit Transformations.

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Authors: K.H. Yang

Abstract:

After the terrorist attack on September 11, 2001 in U.S., the container security issue got high attention, especially by U.S. government, which deployed a lot of measures to promote or improve security systems. U.S. government not only enhances its national security system, but allies with other countries against the potential terrorist attacks in the future. For example CSI (Container Security Initiative), it encourages foreign ports outside U.S. to become CSI ports as a part of U.S. anti-terrorism network. Although promotion of the security could partly reach the goal of anti-terrorism, that will influence the efficiency of container supply chain, which is the main concern when implementing the inspection measurements. This paper proposes a quick estimation methodology for an inspection service rate by a berth allocation heuristic such that the inspection activities will not affect the original container supply chain. Theoretical and simulation results show this approach is effective.

Keywords: Berth allocation, Container, Heuristic, Inspection.

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Authors: Kadkhodaie A., Bagheri M.

Abstract:

Evaluation of crop plants resistance to environmental stresses specially in germination stage is a critical factor in their selection in different conditions of cultivation. Therefore use of a procedure in controllable situation can help to evaluate plants reaction to stress quickly and precisely. In order to study germination characteristics of flax in water and salinity stress conditions were conducted two laboratories experimental. The two experimental were conducted in 4-replicant completing random design for salinity and water stress. The treatment, for salinity and water stress was three potential (zero, 40, 80 mM) of NaCl and three potential (zero, -2, -4 bar) of PEG respectively. Germination percentage and rate, in addition to Radical and plumule length and dry-weight and plumule/Radical ration were measured. All of characteristics reduce under water stress conditions. salinity stress significant reduce germination rate and Radical and plumule length of flax seeds. Hydropriming and osmopriming significant increased germination rate, plumule length and plumule/Radical ration ration of flax seeds. But germination percentage and Radical and plumule dry weight significant increased only in hydropriming treat. Hydropriming and osmopriming could not be used to improved germination under saline and drought stress. But has more tolerance in salinity and drought stress in flax by less reduce in Radical and plumule length under saline and drought stress.

Keywords: linseed, salt stress, water stress, seed treatment, Germination

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Authors: A. Ghafouri, A. Falavand Jozaei, M. Salari

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In this paper, effects of using Alumina-water nanofluid on the rate of heat transfer have been investigated numerically. Physical model is a square enclosure with insulated top and bottom horizontal walls, while the vertical walls are kept at different constant temperatures. Two appropriate models are used to evaluate the viscosity and thermal conductivity of nanofluid. The governing stream-vorticity equations are solved using a second order central finite difference scheme, coupled to the conservation of mass and energy. The study has been carried out for the Richardson number 0.1 to 10 and the solid volume fraction 0 to 0.04. Results are presented by isotherms lines, average Nusselt number and normalized Nusselt number in different range of φ and Ri for forced, combined and natural convection dominated regime. It is found that higher heat transfer rate is predicted when the effects of nanoparticle is taken into account.

Keywords: Nanofluid, Heat Transfer Enhancement, Square Enclosure, Nusselt number.

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Authors: Barış Can Yalçın

Abstract:

Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: Calibration of sensors, data acquisition.

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Authors: Manpreet Singh, Parvinder Singh, Suman

Abstract:

The data is available in abundance in any business organization. It includes the records for finance, maintenance, inventory, progress reports etc. As the time progresses, the data keep on accumulating and the challenge is to extract the information from this data bank. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of business. For the development of accurate and required information for particular problem, business analyst needs to develop multidimensional models which give the reliable information so that they can take right decision for particular problem. If the multidimensional model does not possess the advance features, the accuracy cannot be expected. The present work involves the development of a Multidimensional data model incorporating advance features. The criterion of computation is based on the data precision and to include slowly change time dimension. The final results are displayed in graphical form.

Keywords: Multidimensional, data precision.

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Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

Abstract:

Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: Artificial neural network, EDM, metal removal rate, modeling, surface roughness.

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Authors: Sanjeev Gupta, Mayank Dave

Abstract:

The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.

Keywords: Cluster head, data reliability, real time communication, wireless sensor networks.

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Authors: Mokgadi Moletsane-Kekae, Robert Kananga Mukuna

Abstract:

The study focused on the analysis of the Adjusted Rorschach Comprehensive System’s responses. The objective of this study is to analyse the participants’ response rate of the Adjusted Rorschach Comprehensive System with regards to critical psychology approach. The use of critical psychology theory in this study was crucial because it responds to the current inadequate western theory or practice in the field of psychology. The study adopted a qualitative approach and a case study design. The study was grounded on interpretivist paradigm. The sample size comprised six learners (three boys and three girls, aged of 14 years) from historically disadvantaged school in the Western Cape, South Africa. The Adjusted Rorschach Comprehensive System (ARCS) administration procedure, biographical information, semi-structured interviews, and observation were used to collect data. Data was analysed using thematic framework. The study found out that, factors that increased the response rates during the administration of ARCS were, language, seating arrangement, drawing, viewing, and describing. The study recommended that, psychological test designers take into consideration the philosophy or worldviews of the local people for whom the test is designed to minimize low response rates.

Keywords: Adjusted Rorschach comprehensive system, critical psychology, learners, responses.

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Authors: David Calderón Villegas, Thomas Kalitzky

Abstract:

Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes’ cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an internal rate of return (IRR) 1.5 times higher than the discount rate. 

Keywords: small hydropower, renewable energy, RoR schemes, optimal sizing, financial analysis

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

Abstract:

In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.

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Authors: Habtu Alemayehu, G. Radhakrishnamacharya

Abstract:

An analytical solution for dispersion of a solute in the peristaltic motion of a couple stress fluid in the presence of magnetic field with both homogeneous and heterogeneous chemical reactions is presented. The average effective dispersion coefficient has been found using Taylor-s limiting condition and long wavelength approximation. The effects of various relevant parameters on the average effective coefficient of dispersion have been studied. The average effective dispersion coefficient tends to decrease with magnetic field parameter, homogeneous chemical reaction rate parameter and amplitude ratio but tends to increase with heterogeneous chemical reaction rate parameter.

Keywords: Dispersion, Peristalsis, Couple stress fluid, Chemicalreaction, Magnetic field.

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Authors: F. Javier Benitez, Francisco J. Real, Juan Luis Acero, Francisco Casas

Abstract:

Three emerging contaminants (amitriptyline hydrochloride, methyl salicylate and 2-phenoxyethanol) frequently found in waste-waters were selected to be individually degraded in ultra-pure water by the combined advanced oxidation process constituted by UV radiation and chlorine. The influence of pH, initial chlorine concentration and nature of the contaminants was firstly explored. The trend for the reactivity of the selected compounds was deduced: amitriptyline hydrochloride > methyl salicylate > 2-phenoxyethanol. A later kinetic study was carried out and focused on the specific evaluation of the first-order rate constants and the determination of the partial contribution to the global reaction of the direct photochemical pathway and the radical pathway. A comparison between the rate constant values among photochemical experiments without and with the presence of Cl₂ reveals a clear increase in the oxidation efficiency of the combined process with respect to the photochemical reaction alone. In a second stage, the simultaneous oxidation of mixtures of the selected contaminants in several types of water (ultrapure water, surface water from a reservoir, and two secondary effluents) was also performed by the same combination UV/Cl₂ under more realistic operating conditions. The efficiency of this combined system UV/Cl₂ was compared to other oxidants such as the UV/S₂O₈^2- and UV/H₂O₂ AOPs. Results confirmed that the UV/Cl₂ system provides higher elimination efficiencies among the AOPs tested.

Keywords: Emerging contaminants, amitriptyline, methyl salicylate, 2-phenoxyethanol, chlorination, photolysis, rate constants, UV/chlorine advanced oxidation process.

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Authors: B. Skrabic, N. Tomic-Plazibat

Abstract:

In this paper real money demand function is analyzed within multivariate time-series framework. Cointegration approach is used (Johansen procedure) assuming interdependence between money demand determinants, which are nonstationary variables. This will help us to understand the behavior of money demand in Croatia, revealing the significant influence between endogenous variables in vector autoregrression system (VAR), i.e. vector error correction model (VECM). Exogeneity of the explanatory variables is tested. Long-run money demand function is estimated indicating slow speed of adjustment of removing the disequilibrium. Empirical results provide the evidence that real industrial production and exchange rate explains the most variations of money demand in the long-run, while interest rate is significant only in short-run.

Keywords: Cointegration, Long-run equilibrium, Money demand function, Vector error correction model.

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Authors: Mohd. Noor Md. Sap, A. Majid Awan

Abstract:

Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.

Keywords: Pattern analysis, clustering, kernel methods, spatial data, crop yield

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