Search results for: output coupling

Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Shirin jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani

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Biosensors in forensic analysis are ideal biological tools that can be used for rapid and sensitive initial screening and testing to detect of suspicious components like biological and chemical agent in crime scenes. The wide use of different biomolecules such as proteins, nucleic acids, microorganisms, antibodies and enzymes makes it possible. These biosensors have great advantages such as rapidity, little sample manipulation and high sensitivity, also Because of their stability, specificity and low cost they have become a very important tool to Forensic analysis and detection of crime. In crime scenes different substances such as rape samples, Semen, saliva fingerprints and blood samples, act as a detecting elements for biosensors. On the other hand, successful fluid recovery via biosensor has the propensity to yield a highly valuable source of genetic material, which is important in finding the suspect. Although current biological fluid testing techniques are impaired for identification of body fluids. But these methods have disadvantages. For example if they are to be used simultaneously, Often give false positive result. These limitations can negatively result the output of a case through missed or misinterpreted evidence. The use of biosensor enable criminal researchers the highly sensitive and non-destructive detection of biological fluid through interaction with several fluid-endogenous and other biological and chemical contamination at the crime scene. For this reason, using of the biosensors for detecting the biological fluid found at the crime scenes which play an important role in identifying the suspect and solving the criminal.

Keywords: biosensors, forensic analysis, biological fluid, crime detection

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Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

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In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

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Authors: Ese Urhie, Olabisi Popoola, Obindah Gershon, Olabanji Ewetan

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Modern agriculture involves the use of improved tools and equipment (instead of crude and ineffective tools) like tractors, hand operated planters, hand operated fertilizer drills and combined harvesters - which increase agricultural productivity. Farmers in Nigeria still have huge potentials to enhance their productivity. The study argues that the increase in agricultural output due to increased productivity, orchestrated by modern agriculture will promote forward linkages and opportunities in the processing sub-sector; both the manufacturing of machines and the processing of raw materials. Depending on existing incentives, foreign investment could be attracted to augment local investment in the sector. The availability of raw materials in large quantity – which prices are competitive – will attract investment in other industries. In addition, potentials for backward linkages will also be created. In a nutshell, adopting the unbalanced growth theory in favour of the agricultural sector could engender industrialization in a country with untapped potentials. The paper highlights the numerous potentials of modern agriculture that are yet to be tapped in Nigeria and also provides a theoretical analysis of how the realization of such potentials could promote industrialization in the country. The study adopts the Lewis’ theory of structural–change model and Hirschman’s theory of unbalanced growth in the design of the analytical framework. The framework will be useful in empirical studies that will guide policy formulation.

Keywords: modern agriculture, industrialization, structural change model, unbalanced growth

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Corinna Barraco, Ornella Salimbene

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This research involves the Ethiopian locality of Jeldi (North Africa), an area particularly affected by water shortage and in which the pumping and treatment of drinking water are extremely sensitive issues. The study aims to develop and apply low-cost tools for the design of solar water pumping and water purification systems in a not developed country. Consequently, two technical tools have been implemented in Excel i) Solar photovoltaic Pumping (Spv-P) ii) Water treatment (Wt). The Spv-P tool was applied to the existing well (depth 110 [m], dynamic water level 90 [m], static water level 53 [m], well yield 0.1728 [m³h⁻¹]) in the Jeldi area, where estimated water demand is about 50 [m3d-1]. Through the application of the tool, it was designed the water extraction system of the well, obtaining the number of pumps and solar panels necessary for water pumping from the well of Jeldi. Instead, the second tool Wt has been applied in the subsequent phase of extracted water treatment. According to the chemical-physical parameters of the water, Wt returns as output the type of purification treatment(s) necessary to potable the extracted water. In the case of the well of Jeldi, the tool identified a high criticality regarding the turbidity parameter (12 [NTU] vs 5 [NTU]), and a medium criticality regarding the exceeding limits of sodium concentration (234 [mg/L Na⁺] vs 200 [mg/L Na⁺]) and ammonia (0.64 [mg/L NH³-N] vs 0.5 [mg/L NH³-N]). To complete these tools, two specific manuals are provided for the users. The joint use of the two tools would help reduce problems related to access to water resources compared to the current situation and represents a simplified solution for the design of pumping systems and analysis of purification treatments to be performed in undeveloped countries.

Keywords: drinking water, Ethiopia, treatments, water pumping

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Authors: Hossein Edrisi

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To study the impact of the amount and volume of power of isolation transformer on the lamps in airfield Ground Lighting Systems. A test was conducted in Persian Gulf International Airport, This airport is situated in the south of Iran and it is one of the most cutting-edge airports, the same one that owns modern devices. Iran uses materials and auxiliary equipment which are made by ADB Company from Belgium. Airfield ground lighting (AGL) systems are responsible for providing visual issue to aircrafts and helicopters in the runways. In an AGL system a great deal of lamps are connected in serial circuits to each other and each ring has its individual constant current regulators (CCR), which through that provide energy to the lamps. Control of lamps is crucial for maintenance and operation in the AGL systems. Thanks to the Programmable Logic Controller (PLC) that is a cutting-edge technology can help the system to connect the elements from substations and ATC (TOWER). For this purpose, a test in real conditions of the airport done for all element that used in the airport such as isolation transformer in different power capacity and different consuming power and brightness of the lamps. The data were analyzed with Lux meter and Multimeter. The results had shown that the increase in the power of transformer caused a significant increase in brightness. According to the Ohm’s law and voltage division, without changing the characteristics of the light bulb, it is not possible to change the voltage, just need to change the amount of transformer with which it connects to the lamps. When the voltage is increased, the current through the bulb has to increase as well, because of Ohm's law: I=V/R and I=V/R which means that if V increases, so do I increase. The output voltage on the constant current regulator emerges between the lamps and the transformers.

Keywords: AGL, CCR, lamps, transformer, Ohm’s law

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Authors: Julia R. Beulig, Stefan Ohla, Detlev Belder

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In contrast to off-line analytical methods, lab-on-a-chip technology delivers direct information about the observed reaction. Therefore, microfluidic devices make an important scientific contribution, e.g. in the field of synthetic chemistry. Herein, the rapid generation of analytical data can be applied for the optimization of chemical reactions. These microfluidic devices enable a fast change of reaction conditions as well as a resource saving method of operation. In the presented work, we focus on the investigation of multiphase regimes, more specifically on a biphasic microfluidic droplet systems. Here, every single droplet is a reaction container with customized conditions. The biggest challenge is the rapid qualitative and quantitative readout of information as most detection techniques for droplet systems are non-specific, time-consuming or too slow. An exception is the electrospray mass spectrometry (ESI-MS). The combination of a reaction screening platform with a rapid and specific detection method is an important step in droplet-based microfluidics. In this work, we present a novel approach for synthesis optimization on the nanoliter scale with direct ESI-MS detection. The development of a droplet-based microfluidic device, which enables the modification of different parameters while simultaneously monitoring the effect on the reaction within a single run, is shown. By common soft- and photolithographic techniques a polydimethylsiloxane (PDMS) microfluidic chip with different functionalities is developed. As an interface for the MS detection, we use a steel capillary for ESI and improve the spray stability with a Teflon siphon tubing, which is inserted underneath the steel capillary. By optimizing the flow rates, it is possible to screen parameters of various reactions, this is exemplarity shown by a Domino Knoevenagel Hetero-Diels-Alder reaction. Different starting materials, catalyst concentrations and solvent compositions are investigated. Due to the high repetition rate of the droplet production, each set of reaction condition is examined hundreds of times. As a result, of the investigation, we receive possible reagents, the ideal water-methanol ratio of the solvent and the most effective catalyst concentration. The developed system can help to determine important information about the optimal parameters of a reaction within a short time. With this novel tool, we make an important step on the field of combining droplet-based microfluidics with organic reaction screening.

Keywords: droplet, mass spectrometry, microfluidics, organic reaction, screening

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Authors: Salem Alsanusi, Loubna Bentaher

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Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.

Keywords: mix proportioning, response surface methodology, compressive strength, optimal design

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Authors: Shilpa Khobragade, Carlos Da Silva Granja, Niklas Sandström, Igor Efimov, Victor P. Ostanin, Wouter van der Wijngaart, David Klenerman, Sourav K. Ghosh

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Rapid, label-free and direct detection of pathogenic bacteria is critical for the prevention of disease outbreaks. This paper for the first time attempts to probe the nonlinear acoustic response of quartz crystal resonator (QCR) functionalized with specific DNA aptamers for direct detection and quantification of viable E. coli KCTC 2571 bacteria. DNA aptamers were immobilized through biotin and streptavidin conjugation, onto the gold surface of QCR to capture the target bacteria and the detection was accomplished by shift in amplitude of the peak 3f signal (3 times the drive frequency) upon binding, when driven near fundamental resonance frequency. The developed nonlinear acoustic aptasensor system demonstrated better reliability than conventional resonance frequency shift and energy dissipation monitoring that were recorded simultaneously. This sensing system could directly detect 10⁽⁵⁾ cells/mL target bacteria within 30 min or less and had high specificity towards E. coli KCTC 2571 bacteria as compared to the same concentration of S.typhi bacteria. Aptasensor response was observed for the bacterial suspensions ranging from 10⁽⁵⁾-10⁽⁸⁾ cells/mL. Conclusively, this nonlinear acoustic aptasensor is simple to use, gives real-time output, cost-effective and has the potential for rapid, specific, label-free direction detection of bacteria.

Keywords: acoustic, aptasensor, detection, nonlinear

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Authors: Arabi Abderrazak, Bourouba Nacerdine, Ayad Mouloud, Belaout Abdeslam

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In this paper, a new test technique of analog circuits using time mode simulation is proposed for the single catastrophic faults detection in analog circuits. This test process is performed to overcome the problem of catastrophic faults being escaped in a DC mode test applied to the inverter amplifier in previous research works. The circuit under test is a second-order low pass filter constructed around this type of amplifier but performing a function that differs from that of the previous test. The test approach performed in this work is based on two key- elements where the first one concerns the unique square pulse signal selected as an input vector test signal to stimulate the fault effect at the circuit output response. The second element is the filter response conversion to a square pulses sequence obtained from an analog comparator. This signal conversion is achieved through a fixed reference threshold voltage of this comparison circuit. The measurement of the three first response signal pulses durations is regarded as fault effect detection parameter on one hand, and as a fault signature helping to hence fully establish an analog circuit fault diagnosis on another hand. The results obtained so far are very promising since the approach has lifted up the fault coverage ratio in both modes to over 90% and has revealed the harmful side of faults that has been masked in a DC mode test.

Keywords: analog circuits, analog faults diagnosis, catastrophic faults, fault detection

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Naheem Olakunle Adesina

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The memristor is considered as one of the promising candidates for mamoelectronic engineering and applications. Owing to its high compatibility with CMOS, nanoscale size, and low power consumption, memristor has been employed in the design of commonly used circuits such as phase-locked loop (PLL). In this paper, we designed a memristor-based loop filter (LF) together with other components of PLL. Following this, we evaluated the noise-rejection feature of loop filter by comparing the noise levels of input and output signals of the filter. Our SPICE simulation results showed that memristor behaves like a linear resistor at high frequencies. The result also showed that loop filter blocks the high-frequency components from phase frequency detector so as to provide a stable control voltage to the voltage controlled oscillator (VCO). In addition, we examined the effects of temperature on the performance of the designed phase locked loop circuit. A critical temperature, where there is frequency drift of VCO as a result of variations in control voltage, is identified. In conclusion, the memristor is a suitable choice for nanoelectronic systems owing to a small area, low power consumption, dense nature, high switching speed, and endurance. The proposed memristor-based loop filter, together with other components of the phase locked loop, can be designed using memristive emulator and EDA tools in current CMOS technology and simulated.

Keywords: Fast Fourier Transform, hysteresis curve, loop filter, memristor, noise, phase locked loop, voltage controlled oscillator

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Authors: Gbenga Martins, Christopher J. Olowookere, Lateef Bamidele, Kehinde O. Olatunji

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The aims of this research are to measure the scattered dose rate during an X-ray examination in an X-ray room, compare the scattered dose rate with exposure parameters based on the body region examined, and examine the X-ray examination done with an over couch tube. The research was carried out using Gamma Scout software installation on the computer system (Laptop) to record the radiation counts, pulse rate, and dose rate. The measurement was employed by placing the detector at 900 to the incident X-ray. Proforma was used for the collection of patients’ data such as age, sex, examination type, and initial diagnosis. Data such as focus skin distance (FSD), body mass index (BMI), body thickness of the patients, the beam output (kVp) were collected at Obafemi Awolowo University, Ile-Ife, Western Nigeria. Total number of 136 patients was considered during this research. Dose rate range between 14.21 and 86.78 µSv/h for the plain abdominal region, 85.70 and 2.86 µSv/h for the lumbosacral region,1.3 µSv/yr and 3.6 µSv/yr in the pelvis region, 2.71 µSv/yr and 28.88 µSv/yr for leg region, 3.06 µSv/yr and 29.98 µSv/yr in hand region. The results of this study were compared with those of other studies carried out in other countries. The findings of this study indicated that the number of exposure parameters selected for each diagnostic examination contributed to the dose rate recorded. Therefore, these results call for a quality assurance program (QAP) in diagnostic X-ray units in Nigerian hospitals.

Keywords: X-radiation, exposure parameters, dose rate, pulse rate, number of counts, tube current, tube potential, diagnostic examination, scattered radiation

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Authors: Leticia Cervantes, Edith Garcia, Oscar Castillo

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At today, there are several control problems where the main objective is to obtain the best control in the study to decrease the error in the application. Many techniques can use to control these problems such as Neural Networks, PID control, Fuzzy Logic, Optimization techniques and many more. In this case, fuzzy logic with fuzzy system and an optimization technique are used to control the case of study. In this case, Ant Lion Optimization is used to optimize a fuzzy system to control the velocity of a simple treadmill. The main objective is to achieve the control of the velocity in the control problem using the ALO optimization. First, a simple fuzzy system was used to control the velocity of the treadmill it has two inputs (error and error change) and one output (desired speed), then results were obtained but to decrease the error the ALO optimization was developed to optimize the fuzzy system of the treadmill. Having the optimization, the simulation was performed, and results can prove that using the ALO optimization the control of the velocity was better than a conventional fuzzy system. This paper describes some basic concepts to help to understand the idea in this work, the methodology of the investigation (control problem, fuzzy system design, optimization), the results are presented and the optimization is used for the fuzzy system. A comparison between the simple fuzzy system and the optimized fuzzy systems are presented where it can be proving the optimization improved the control with good results the major findings of the study is that ALO optimization is a good alternative to improve the control because it helped to decrease the error in control applications even using any control technique to optimized, As a final statement is important to mentioned that the selected methodology was good because the control of the treadmill was improve using the optimization technique.

Keywords: ant lion optimization, control problem, fuzzy control, fuzzy system

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Authors: Ifeanyi Charles Otuokere, Victoria Nneoma Nnochiri

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Entrepreneurship generally and specifically within the rural communities in Nigeria is a fast means of bringing development within the communities. This is made possible by utmost maximization and management of available local resources to develop rural areas through good management of these local resources. This study anchors on the rural development paradigm and the integrated rural development theories to understudy the knowledge of rural entrepreneurs on rural economic development. The research study made use of surveys and descriptive analysis. The assessable population for the study, which was randomly selected, is 100 rural entrepreneurs from ten rural communities within the Ikwuano Local Government Area of Abia State. The study made use of both primary and secondary as a source of data collection with much emphasis on a primary source, although secondary data such as journals, textbooks electronic sources were also utilised. A carefully structured questionnaire drafted to extract raw data was administered to selected entrepreneurs. The findings of the study showed that developments within rural communities can only be achieved through rural entrepreneurship. This is evidenced in increased output, job creation, and most importantly, reduction of rural to urban migration, among other things. Recommendations were also made based on these findings; the researchers recommended that infrastructural developments should be made available in the rural communities and government policies should create enabling environments along with other assistance to help these rural entrepreneurs achieve their sole aim.

Keywords: economic developments, rural communities, rural development, rural entrepreneurship

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Authors: Anjana Jain, S. Jayanth Kumar

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Polyvinylidene fluoride (PVDF) is a well-known material for remarkable mechanical properties, resistance to chemicals and superior ferroelectric performances. This endows PVDF the potential for application in supercapacitor devices. The dielectric properties of PVDF, however, are not very high. To improve the dielectric properties of Polyvinylidene fluoride (PVDF), Piezoelectric polymer nanocomposites are prepared without affecting the other useful properties of PVDF. Polyaniline (PANI) was chosen as a filler material to prepare the nanocomposites. PVDF-PANI nanocomposite films were prepared using solvent cast method with different volume fractions of PANI varying from 0.04% to 0.048% of PANI content. The films are characterized for structural, mechanical, and surface morphological properties using X-ray diffraction, differential scanning calorimeter, Raman spectra, Infrared spectra, tensile testing, and scanning electron microscopy. The X-ray diffraction analysis shows that, prepared films were in β-phase. The DSC scans indicated that the degree of crystallinity in PVDF-PANI is improved. Raman and Infrared spectrum further confirm the presence of β-phase of PVDF-PANI film. Tensile properties of PVDF-PANI films were in good agreement with those reported in literature. The surface feature shows that PANI is uniformly distributed in PVDF and also results in disappearance of spherulites. The influence of volume fraction of PANI in PVDF on dielectric properties was analyzed. The results showed that the dielectric permittivity of PVDF-PANI (120) was much higher than that of PVDF (12). The sensitivity of these films was studied on application of a pressure and a constant output voltage was obtained.

Keywords: dielectric Properties, PANI, PVDF, smart materials

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Authors: Hassan Athari, Alireza Ruhi Sales, Amin Pourafshar, Seyyed Mehdi Pestei, Marc. A. Rosen

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In order to achieve high efficiency and high specific work with lower emissions, the use of advanced gas turbine cycles for power generation is useful and advantageous. Here, evaporative inlet air cooling is analyzed thermodynamically in the form of air film blade cooling of gas turbines. As the ambient temperature increases during summer months, the performance of gas turbines particularly the output power and energy efficiency are significantly decreased. The utilization of evaporative inlet cooling in gas turbine cycles increases gas turbine performance, which can assist to solve the problem in meeting the increasing demands for electrical power and offsetting shortages during peak load times. In the present research, because of the importance of turbine blade cooling, the turbine is investigated with cold compressed air used for cooling the turbine blades. The investigation of the basic and modified cycles shows that, by adding an evaporative cooler to a simple gas turbine cycle, for a turbine inlet temperature of 1400 °C, an ambient temperature of 45 °C and a relative humidity of 15%, the specific work can reach 331 (kJ/kg air), while the maximum specific work of a simple cycle for the same conditions is 273.7 (kJ/kg air). The exergy results reveal that the highest exergy destruction occurs in the combustion chamber, where the large temperature differences and highly exothermic chemical reactions are the main sources of the irreversibility.

Keywords: energy, exergy, wet compression, air-film cooling blade, gas turbine

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Sagar Shiwakoti, Narendra Man Shakya

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The lumped conceptual hydrological model HBV is applied to the Karnali River Basin to estimate runoff at several gauging stations and to analyze the changes in catchment hydrology and future flood magnitude due to climate change. The performance of the model is analyzed to assess its suitability to simulate streamflow in snow fed mountainous catchments. Due to the structural complexity, the model shows difficulties in modeling low and high flows accurately at the same time. It is observed that the low flows were generally underestimated and the peaks were correctly estimated except for some sharp peaks due to isolated precipitation events. In this study, attempt has been made to evaluate the importance of snow melt discharge in the runoff regime of the basin. Quantification of contribution of snowmelt to annual, summer and winter runoff has been done. The contribution is highest at the beginning of the hot months as the accumulated snow begins to melt. Examination of this contribution under conditions of increased temperatures indicate that global warming leading to increase in average basin temperature will significantly lead to higher contributions to runoff from snowmelt. Forcing the model with the output of HadCM3 GCM and the A1B scenario downscaled to the station level show significant changes to catchment hydrology in the 2040s. It is observed that the increase in runoff is most extreme in June - July. A shift in the hydrological regime is also observed.

Keywords: hydrological modeling, HBV light, rainfall runoff modeling, snow melt, climate change

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Authors: T. Asefi, J. Faiz, M. A. Khan

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This paper introduces dual rotor axial flux machines with surface mounted and spoke type ferrite permanent magnets with concentrated windings; they are introduced as alternatives to a generator with surface mounted Nd-Fe-B magnets. The output power, voltage, speed and air gap clearance for all the generators are identical. The machine designs are optimized for minimum mass using a population-based algorithm, assuming the same efficiency as the Nd-Fe-B machine. A finite element analysis (FEA) is applied to predict the performance, emf, developed torque, cogging torque, no load losses, leakage flux and efficiency of both ferrite generators and that of the Nd-Fe-B generator. To minimize cogging torque, different rotor pole topologies and different pole arc to pole pitch ratios are investigated by means of 3D FEA. It was found that the surface mounted ferrite generator topology is unable to develop the nominal electromagnetic torque, and has higher torque ripple and is heavier than the spoke type machine. Furthermore, it was shown that the spoke type ferrite permanent magnet generator has favorable performance and could be an alternative to rare-earth permanent magnet generators, particularly in wind energy applications. Finally, the analytical and numerical results are verified using experimental results.

Keywords: axial flux, permanent magnet generator, dual rotor, ferrite permanent magnet generator, finite element analysis, wind turbines, cogging torque, population-based algorithms

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Authors: Dimitri Bigot, Bruno Malet-Damour, Jérôme Vigneron

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Many studies have been made about using bio-based materials in buildings. The goal is to reduce its environmental footprint by analyzing its life cycle. This can lead to minimize the carbon emissions or energy consumption. A previous work proposed to numerically study the feasibility of using wood chips to regulate relative humidity inside a building. This has shown the capability of a wood chips bed to regulate humidity inside the building, to improve thermal comfort, and so potentially reduce building energy consumption. However, it also shown that some physical parameters of the wood chips must be identified to validate the proposed model and the associated results. This paper presents an experimental setup able to study such a wood chips bed with different solicitations. It consists of a simple duct filled with wood chips and crossed by an air flow with variable temperature and relative humidity. Its main objective is to study the thermal behavior of the wood chips bed by controlling temperature and relative humidity of the air that enters into it and by observing the same parameters at the output. First, the experimental set up is described according to previous results. A focus is made on the particular properties that have to be characterized. Then some case studies are presented in relation to the previous results in order to identify the key physical properties. Finally, the feasibility of the proposed technology is discussed, and some model validation paths are given.

Keywords: wood chips bed, experimental set-up, bio-based material, desiccant, relative humidity, water content, thermal behaviour, air treatment

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Authors: Icaro V. Soares, Guilherme L. F. Brandao, Ursula D. C. Resende, Glaucio L. Siqueira

Abstract:

Electrical energy can be wirelessly transmitted through resonant coupled coils that operate in the near-field region. Once in this region, the field has evanescent character, the efficiency of Resonant Wireless Power Transfer (RWPT) systems decreases proportionally with the inverse cube of distance between the transmitter and receiver coils. The commercially available RWPT systems are restricted to short and mid-range applications in which the distance between coils is lesser or equal to the coil size. An alternative to overcome this limitation is applying metamaterial structures to enhance the coupling between coils, thus reducing the field decay along the distance between them. Metamaterials can be conceived as composite materials with periodic or non-periodic structure whose unconventional electromagnetic behaviour is due to its unit cell disposition and chemical composition. This new kind of material has been used in frequency selective surfaces, invisibility cloaks, leaky-wave antennas, among other applications. However, for RWPT it is mainly applied as superlenses which are lenses that can overcome the optical limitation and are made of left-handed media, that is, a medium with negative magnetic permeability and electric permittivity. As RWPT systems usually operate at wavelengths of hundreds of meters, the metamaterial unit cell size is much smaller than the wavelength. In this case, electric and magnetic field are decoupled, therefore the double negative condition for superlenses are not required and the negative magnetic permeability is enough to produce an artificial magnetic medium. In this work, the influence of the magnetic permeability of a metamaterial slab inserted between two loosely coupled coils is studied in order to find the condition that leads to the maximum transmission efficiency. The metamaterial used is formed by a subwavelength unit cell that consist of a capacitor-loaded split ring with an inner spiral that is designed and optimized using the software Computer Simulation Technology. The unit cell permeability is experimentally characterized by the ratio of the transmission parameters between coils measured with and without the presence of the metamaterial slab. Early measurements results show that the transmission coefficient at the resonant frequency after the inclusion of the metamaterial is about three times higher than with just the two coils, which confirms the enhancement that this structure brings to RWPT systems.

Keywords: electromagnetic lens, loosely coupled coils, magnetic permeability, metamaterials, resonant wireless power transfer, subwavelength unit cells

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Authors: Alice Robba, Renaud Bouchet, Celine Barchasz, Jean-Francois Colin, Erik Elkaim, Kristina Kvashnina, Gavin Vaughan, Matjaz Kavcic, Fannie Alloin

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With their high theoretical energy density (~2600 Wh.kg-1), lithium/sulfur (Li/S) batteries are highly promising, but these systems are still poorly understood due to the complex mechanisms/equilibria involved. Replacing S8 by Li2S as the active material allows the use of safer negative electrodes, like silicon, instead of lithium metal. S8 and Li2S have different conductivity and solubility properties, resulting in a profoundly changed activation process during the first cycle. Particularly, during the first charge a high polarization and a lack of reproducibility between tests are observed. Differences observed between raw Li2S material (micron-sized) and that electrochemically produced in a battery (nano-sized) may indicate that the electrochemical process depends on the particle size. Then the major focus of the presented work is to deepen the understanding of the Li2S material charge mechanism, and more precisely to characterize the effect of the initial Li2S particle size both on the mechanism and the electrode preparation process. To do so, Li2S nanoparticles were synthetized according to two ways: a liquid path synthesis and a dissolution in ethanol, allowing Li2S nanoparticles/carbon composites to be made. Preliminary chemical and electrochemical tests show that starting with Li2S nanoparticles could effectively suppress the high initial polarization but also influence the electrode slurry preparation. Indeed, it has been shown that classical formulation process - a slurry composed of Polyvinylidone Fluoride polymer dissolved in N-methyle-2-pyrrolidone - cannot be used with Li2S nanoparticles. This reveals a complete different Li2S material behavior regarding polymers and organic solvents when going at the nanometric scale. Then the coupling between two operando characterizations such as X-Ray Diffraction (XRD) and X-Ray Absorption and Emission Spectroscopy (XAS/XES) have been carried out in order to interpret the poorly understood first charge. This study discloses that initial particle size of the active material has a great impact on the working mechanism and particularly on the different equilibria involved during the first charge of the Li2S based Li-ion batteries. These results explain the electrochemical differences and particularly the polarization differences observed during the first charge between micrometric and nanometric Li2S-based electrodes. Finally, this work could lead to a better active material design and so to more efficient Li2S-based batteries.

Keywords: Li-ion/Sulfur batteries, Li2S nanoparticles effect, Operando characterizations, working mechanism

Procedia PDF Downloads 263

Authors: Kelvin Lo

Abstract:

Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

Procedia PDF Downloads 45

Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

Abstract:

Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

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Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

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In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

Procedia PDF Downloads 276

Authors: Keaghan Brown

Abstract:

The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

Procedia PDF Downloads 68

Authors: Anders Schou Simonsen, Kim Sorensen, Thomas Condra

Abstract:

Wet scrubbers are used for flue gas desulfurization by injecting water directly into the flue gas stream from a set of sprayers. The water droplets will flow freely inside the scrubber, and flow down along the scrubber walls as a thin wall film while reacting with the gas phase to remove SO₂. This complex multiphase phenomenon can be divided into three main contributions: the continuous gas phase, the liquid droplet phase, and the liquid wall film phase. This study proposes a complete model, where all three main contributions are taken into account and resolved using OpenFOAM for the continuous gas phase, and MATLAB for the liquid droplet and wall film phases. The 3D continuous gas phase is composed of five species: CO₂, H₂O, O₂, SO₂, and N₂, which are resolved along with momentum, energy, and turbulence. Source terms are present for four species, energy and momentum, which are affecting the steady-state solution. The liquid droplet phase experiences breakup, collisions, dynamics, internal chemistry, evaporation and condensation, species mass transfer, energy transfer and wall film interactions. Numerous sub-models have been implemented and coupled to realise the above-mentioned phenomena. The liquid wall film experiences impingement, acceleration, atomization, separation, internal chemistry, evaporation and condensation, species mass transfer, and energy transfer, which have all been resolved using numerous sub-models as well. The continuous gas phase has been coupled with the liquid phases using source terms by an approach, where the two software packages are couples using a link-structure. The complete CFD model has been verified using 16 experimental tests from an existing scrubber installation, where a gradient-based pattern search optimization algorithm has been used to tune numerous model parameters to match the experimental results. The CFD model needed to be fast for evaluation in order to apply this optimization routine, where approximately 1000 simulations were needed. The results show that the complex multiphase phenomena governing wet scrubbers can be resolved in a single model. The optimization routine was able to tune the model to accurately predict the performance of an existing installation. Furthermore, the study shows that a coupling between OpenFOAM and MATLAB is realizable, where the data and source term exchange increases the computational requirements by approximately 5%. This allows for exploiting the benefits of both software programs.

Keywords: desulfurization, discrete phase, scrubber, wall film

Procedia PDF Downloads 253