Search results for: Power generation.

Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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Authors: D. Kreutzer, S. Müller-Abdelrazeq, I. Isenhardt

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Resource scarcity, energy transition and the planned climate neutrality pose enormous challenges for manufacturing companies. In order to achieve these goals and a holistic sustainable development, the European Union has listed the circular economy as part of the Circular Economy Action Plan. In addition to a reduction in resource consumption, reduced emissions of greenhouse gases and a reduced volume of waste, the principles of the circular economy also offer enormous economic potential for companies, such as the generation of new circular business models. However, many manufacturing companies, especially small and medium-sized enterprises, do not have the necessary capacity to plan their transformation. They need support and strategies on the path to circular transformation because this change affects not only production but also the entire company. Maturity models offer an approach to determine the current status of companies’ transformation processes. In addition, companies can use the models to identify transformation strategies and thus promote the transformation process. While maturity models are established in other areas, e.g., IT or project management, only a few circular economy maturity models can be found in the scientific literature. The aim of this paper is to analyze the identified maturity models of the circular economy through a systematic literature review (SLR) and, besides other aspects, to check their completeness as well as their quality. For this purpose, circular economy maturity models at the company's (micro) level were identified from the literature, compared, and analyzed with regard to their theoretical and methodological structure. A specific focus was placed, on the one hand, on the analysis of the business units considered in the respective models and, on the other hand, on the underlying metrics and indicators in order to determine the individual maturity level of the entire company. The results of the literature review show, for instance, a significant difference in the number and types of indicators as well as their metrics. For example, most models use subjective indicators and very few objective indicators in their surveys. It was also found that there are rarely well-founded thresholds between the levels. Based on the generated results, concrete ideas and proposals for a research agenda in the field of circular economy maturity models are made.

Keywords: Circular economy, maturity model, maturity assessment, systematic literature review.

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Authors: A. El Shahat, A. Keyhani, H. El Shewy

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High Speed PM Generators driven by micro-turbines are widely used in Smart Grid System. So, this paper proposes comparative study among six classical, optimized and genetic analytical design cases for 400 kW output power at tip speed 200 m/s. These six design trials of High Speed Permanent Magnet Synchronous Generators (HSPMSGs) are: Classical Sizing; Unconstrained optimization for total losses and its minimization; Constrained optimized total mass with bounded constraints are introduced in the problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six analytical design examples comparisons are introduced with study of machines waveforms, THD and rotor losses.

Keywords: High Speed, Micro - Turbines, Optimization, PM Generators, Smart Grid, MATLAB.

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Authors: Jun Wang, Tingcun Wei

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The digital pulse width modulator (DPWM) is the crucial building block for digitally-controlled DC-DC switching converter, which converts the digital duty ratio signal into its analog counterpart to control the power MOSFET transistors on or off. With the increase of switching frequency of digitally-controlled DC-DC converter, the DPWM with higher time resolution is required. In this paper, a 15-bits DPWM with three-level hybrid structure is presented; the first level is composed of a7-bits counter and a comparator, the second one is a 5-bits delay line, and the third one is a 3-bits digital dither. The presented DPWM is designed and implemented using the PLL megafunction of FPGA (Field Programmable Gate Arrays), and the required frequency of clock signal is 128 times of switching frequency. The simulation results show that, for the switching frequency of 2 MHz, a DPWM which has the time resolution of 15 ps is achieved using a maximum clock frequency of 256MHz. The designed DPWM in this paper is especially useful for high-frequency digitally-controlled DC-DC switching converters.

Keywords: DPWM, PLL megafunction, FPGA, time resolution, digitally-controlled DC-DC switching converter.

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: LTE-Advanced, carrier aggregation, MIMO, capacity, peak data rate, spectral efficiency.

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Authors: B. T. Aluko, O. I. Oloyede

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Ocimum americanum L (Lamiaceae) is an annual herb that is native to tropical Africa. The in vitro and in vivo antioxidant activity of its aqueous extract was carefully investigated by assessing the DPPH radical scavenging activity, ABTS radical scavenging activity and hydrogen peroxide radical scavenging activity. The reducing power, total phenol, total flavonoids and flavonols content of the extract were also evaluated. The data obtained revealed that the extract is rich in polyphenolic compounds and scavenged the radicals in a concentration dependent manner. This was done in comparison with the standard antioxidants such as BHT and Vitamin C. Also, the induction of oxidative damage with paracetamol (2000 mg/kg) resulted in the elevation of lipid peroxides and significant (P < 0.05) decrease in activities of superoxide dismutase, glutathione peroxidase, glutathione reductase and catalase in the liver and kidney of rats. However, the pretreatment of rats with aqueous extract of O. americanum leaves (200 and 400 mg/kg) and silymarin (100 mg/kg) caused a significant (P < 0.05) reduction in the values of lipid peroxides and restored the levels of antioxidant parameters in these organs. These findings suggest that the leaves of O. americanum have potent antioxidant properties which may be responsible for its acclaimed folkloric uses.

Keywords: Antioxidants, free radicals, Ocimum americanum, scavenging activity.

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Authors: S. Farahat, E. Khorasani Nejad, S. M. Hoseini Sarvari

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In this paper multi-objective genetic algorithms are employed for Pareto approach optimization of ideal Turboshaft engines. In the multi-objective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are specific thrust (F/m& 0), specific fuel consumption ( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O η . These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters (compressor pressure ratio, turbine temperature ratio and Mach number). At the first stage single objective optimization has been investigated and the method of NSGA-II has been used for multiobjective optimization. Optimization procedures are performed for two and four objective functions and the results are compared for ideal Turboshaft engine. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of four objective optimization the results are given in tables.

Keywords: Multi-objective, Genetic algorithm, Turboshaft Engine.

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Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).

Keywords: aeration system, Fuel cell, Artificial intelligence (AI) techniques, fuzzy logic control

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Authors: Ana Paula P. dos Santos, Claudia R. Andrade, Edson L. Zaparoli

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Pressure loss in ductworks is an important factor to be considered in design of engineering systems such as power-plants, refineries, HVAC systems to reduce energy costs. Ductwork can be composed by straight ducts and different types of fittings (elbows, transitions, converging and diverging tees and wyes). Duct fittings are significant sources of pressure loss in fluid distribution systems. Fitting losses can be even more significant than equipment components such as coils, filters, and dampers. At the present work, a conventional 90^o round elbow under turbulent incompressible airflow is studied. Mass, momentum, and k-e turbulence model equations are solved employing the finite volume method. The SIMPLE algorithm is used for the pressure-velocity coupling. In order to validate the numerical tool, the elbow pressure loss coefficient is determined using the same conditions to compare with ASHRAE database. Furthermore, the effect of Reynolds number variation on the elbow pressure loss coefficient is investigated. These results can be useful to perform better preliminary design of air distribution ductworks in air conditioning systems.

Keywords: Duct fitting, Pressure loss, Elbow.

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Authors: Ahmed Kiani

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The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: Electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations.

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine.

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Authors: Jandot Aurélia

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In France, in the main media, the concern about nuclear safety and security has not really appeared before the beginning of the 1970s. The gradual changes in its perception are studied here through the arguments given in the main French news magazines, linked with several parameters. As this represents a considerable amount of copies and thus of information, are selected here the main articles as well as the main “mental images” aiming to persuade the readers and which have led the public awareness to evolve. Indeed, in the 1970s, in France, these evolutions were not made in one day. Indeed, over the period, many articles were still in favor of nuclear power plants and promoted the technological advances that were made in this field. They had to be taken into account. But, gradually, grew up arguments and mental images discrediting the perception of nuclear technology. Among these were the environmental impacts of this industry, as the question of pollution progressively appeared. So, between 1970 and 1979, the language has changed, as the perceptible objectives of the communication, allowing to discern the deepest intentions of the editorial staffs of the French news magazines. This is all these changes that are emphasized here, over a period when the safety and security concern linked to the nuclear technology, to there a field for specialists, has become progressively a social issue seemingly open to all.

Keywords: French media discourse, nuclear safety and security, public awareness, persuasion.

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Authors: Seemaa Diwedi

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The study area receives a wide variety of wastes generated by municipalities and the industries like paints and pigments, metal processing industries, thermal power plants electroprocessing industries etc. The Physico-chemical and structural investigation of water from river Pandu indicated high level of chlorides and calcium which made the water unsuitable for human use. Algae like Cyclotella fumida, Asterionella Formosa, Cladophora glomerata, Pediastrum simplex, Scenedesmus bijuga, Cladophora glomerata were the dominant pollution tolerant species recorded under these conditions. The sensitive and less abundant species of algae included Spirogyra sps., Merismopedia sps. The predominance colonies of Zygnema sps, Phormidium sps, Mycrocystis aeruginosa, Merismopedia minima, Pandorina morum, seems to correlate with high organic contents of Pandu river water. This study assumes significance as some algae can be used as bioindicators of water pollution and algal floral of a municipal drain carrying waste effluents from industrial area Kanpur and discharge them into the river Pandu flowing onto southern outskirts of Kanpur city.

Keywords: Kanpur, North India, Physico-chemical, Pollution, River Pandu.

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Authors: Wei Hua Ho

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Vortices can develop in intakes of turbojet and turbo fan aero engines during high power operation in the vicinity of solid surfaces. These vortices can cause catastrophic damage to the engine. The factors determining the formation of the vortex include both geometric dimensions as well as flow parameters. It was shown that the threshold at which the vortex forms or disappears is also dependent on the initial flow condition (i.e. whether a vortex forms after stabilised non vortex flow or vice-versa). A computational fluid dynamics study was conducted to determine the difference in thresholds between the two conditions. This is the first reported numerical investigation of the “memory effect". The numerical results reproduce the phenomenon reported in previous experimental studies and additional factors, which had not been previously studied, were investigated. They are the rate at which ambient velocity changes and the initial value of ambient velocity. The former was found to cause a shift in the threshold but not the later. It was also found that the varying condition thresholds are not symmetrical about the neutral threshold. The vortex to no vortex threshold lie slightly further away from the neutral threshold compared to the no vortex to vortex threshold. The results suggests that experimental investigation of vortex formation threshold performed either in vortex to no vortex conditions, or vice versa, solely may introduce mis-predictions greater than 10%.

Keywords: Jet Engine Test Cell, Unsteady flow, Inlet Vortex

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.

Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.

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Authors: Chun-Wei Lin, Yu-Lin Chen

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As global industry developed rapidly, the energy demand also rises simultaneously. In the production process, there’s a lot of energy consumed in the process. Formally, the energy used in generating the heat in the production process. In the total energy consumption, 40% of the heat was used in process heat, mechanical work, chemical energy and electricity. The remaining 50% were released into the environment. It will cause energy waste and environment pollution. There are many ways for recovering the waste heat in factory. Organic Rankine Cycle (ORC) system can produce electricity and reduce energy costs by recovering the waste of low temperature heat in the factory. In addition, ORC is the technology with the highest power generating efficiency in low-temperature heat recycling. However, most of factories executives are still hesitated because of the high implementation cost of the ORC system, even a lot of heat are wasted. Therefore, this study constructs a nonlinear mathematical model of waste heat recovery equipment configuration to maximize profits. A particle swarm optimization algorithm is developed to generate the optimal facility installation plan for the ORC system.

Keywords: Green facility planning, organic rankine cycle, particle swarm optimization, waste heat recovery.

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Feed-forward Large Neural Network, Short-TermLoad Forecasting, Continuous Genetic Algorithm.

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Authors: Chiang-Ho Cheng, An-Shik Yang, Hong-Yih Cheng, Ming-Yu Lai

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This paper presents the design and fabrication of a novel piezoelectric actuator for a gas micro pump with check valve having the advantages of miniature size, light weight and low power consumption. The micro pump is designed to have eight major components, namely a stainless steel upper cover layer, a piezoelectric actuator, a stainless steel diaphragm, a PDMS chamber layer, two stainless steel channel layers with two valve seats, a PDMS check valve layer with two cantilever-type check valves and an acrylic substrate. A prototype of the gas micro pump, with a size of 52 mm × 50 mm × 5.0 mm, is fabricated by precise manufacturing. This device is designed to pump gases with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micro pump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micro pump and the displacement of the piezoelectric actuator, simultaneously. The gas micro pump obtained higher output performance under the sinusoidal waveform of 250 Vpp. The micro pump achieved the maximum pumping rates of 1185 ml/min and back pressure of 7.14 kPa at the corresponding frequency of 120 and 50 Hz.

Keywords: PDMS, Check valve, Micro pump, Piezoelectric.

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Authors: M. Chaichanyut, S. Tungjitkusolmun

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This research is presented with microwave (MW) ablation by using the T-Prong monopole antennas. In the study, three-dimensional (3D) finite-element methods (FEM) were utilized to analyse: the tissue heat flux, temperature distributions (heating pattern) and volume destruction during MW ablation in liver cancer tissue. The configurations of T-Prong monopole antennas were considered: Three T-prong antenna, Expand T-Prong antenna and Arrow T-Prong antenna. The 3D FEMs solutions were based on Maxwell and bio-heat equations. The microwave power deliveries were 10 W; the duration of ablation in all cases was 300s. Our numerical result, heat flux and the hotspot occurred at the tip of the T-prong antenna for all cases. The temperature distribution pattern of all antennas was teardrop. The Arrow T-Prong antenna can induce the highest temperature within cancer tissue. The microwave ablation was successful when the region where the temperatures exceed 50°C (i.e. complete destruction). The Expand T-Prong antenna could complete destruction the liver cancer tissue was maximized (6.05 cm³). The ablation pattern or axial ratio (Widest/length) of Expand T-Prong antenna and Arrow T-Prong antenna was 1, but the axial ratio of Three T-prong antenna of about 1.15.

Keywords: Liver cancer, T-Prong antenna, Finite element, Microwave ablation.

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Authors: Thomas O. Olwal, Michael A. van Wyk, Barend J. van Wyk

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In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.

Keywords: discrete polyphase matched filters, maximum likelihood estimators, soft timing phase estimation, wireless mobile systems.

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: ATR, HRRP, motion compensation, SFW, TMP.

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub

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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.

Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control

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Authors: P. Kamphikul, P. Krachodnok, R. Wongsan

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This paper presents the gain improvement of a sector antenna for mobile phone base station by using the new technique to enhance its gain for microstrip antenna (MSA) array without construction enlargement. The curved woodpile Electromagnetic Band Gap (EBG) has been utilized to improve the gain instead. The advantages of this proposed antenna are reducing the length of MSAs array but providing the higher gain and easy fabrication and installation. Moreover, it provides a fan-shaped radiation pattern, wide in the horizontal direction and relatively narrow in the vertical direction, which appropriate for mobile phone base station. The paper also presents the design procedures of a 1x8 MSAs array associated with U-shaped reflector for decreasing their back and side lobes. The fabricated curved woodpile EBG exhibits bandgap characteristics at 2.1 GHz and is utilized for realizing a resonant cavity of MSAs array. This idea has been verified by both the Computer Simulation Technology (CST) software and experimental results. As the results, the fabricated proposed antenna achieves a high gain of 20.3 dB and the half-power beam widths in the E- and H-plane of 36.8 and 8.7 degrees, respectively. Good qualitative agreement between measured and simulated results of the proposed antenna was obtained.

Keywords: Gain Improvement, Microstrip Antenna Array, Electromagnetic Band Gap, Base Station.

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Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

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In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: Agriculture, human factors, product design, soil moisture control.

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Authors: Sudip Ghosh, Dipanwita Roy, Dipan Chatterjee, Paramita Bhattacharjee, Satadal Das

Abstract:

Highest yield of eugenol-rich fractions from Cinnamomum tamala (bay leaf) leaves were obtained by supercritical carbon dioxide (SC-CO₂), compared to hydro-distillation, organic solvents, liquid CO₂ and subcritical CO₂ extractions. Optimization of SC-CO₂ extraction parameters was carried out to obtain an extract with maximum eugenol content. This was achieved using a sample size of 10g at 55°C, 512 bar after 60min at a flow rate of 25.0 cm³/sof gaseous CO₂. This extract has the best combination of phytochemical properties such as phenolic content (1.77mg gallic acid/g dry bay leaf), reducing power (0.80mg BHT/g dry bay leaf), antioxidant activity (IC₅₀ of 0.20mg/ml) and anti-inflammatory potency (IC₅₀ of 1.89mg/ml). Identification of compounds in this extract was performed by GC-MS analysis and its antimicrobial potency was also evaluated. The MIC values against E. coli, P. aeruginosa and S. aureus were 0.5, 0.25 and 0.5mg/ml, respectively. 

Keywords: Antimicrobial potency, Cinnamomum tamala, eugenol, supercritical carbon dioxide extraction.

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Authors: George Leventakis, George Kokkinis, Nikos Moustakidis, George Papalexandratos, Ioanna Vasiliadou

Abstract:

Enhancing the feeling of public safety and crime prevention are tasks customarily assigned to the Police. Police departments have, however, recognized that traditional ways of policing methods are becoming obsolete; Community Policing (CP) philosophy; however, when applied appropriately, leads to seamless collaboration between various stakeholders like the Police, NGOs and the general public and provides the opportunity to identify risks, assist in solving problems of crime, disorder, safety and crucially contribute to improving the quality of life for everyone in a community. Social Media, on the other hand, due to its high level of infiltration in modern life, constitutes a powerful mechanism which offers additional and direct communication channels to reach individuals or communities. These channels can be utilized to improve the citizens’ perception of the Police and to capture individual and community needs, when their feedback is taken into account by Law Enforcement Agencies (LEAs) in a structured and coordinated manner. This paper presents research conducted under INSPEC²T (Inspiring CitizeNS Participation for Enhanced Community PoliCing AcTions), a project funded by the European Commission’s research agenda to bridge the gap between CP as a philosophy and as an organizational strategy, capitalizing on the use of Social Media. The project aims to increase transparency, trust, police accountability, and the role of civil society. It aspires to build strong, trusting relationships between LEAs and the public, supporting two-way, contemporary communication while at the same time respecting anonymity of all affected parties. Results presented herein summarize the outcomes of four online multilingual surveys, focus group interviews, desktop research and interviews with experts in the field of CP practices. The above research activities were conducted in various EU countries aiming to capture requirements of end users from diverse backgrounds (social, cultural, legal and ethical) and determine public expectations regarding CP, community safety and crime prevention.

Keywords: Community partnerships, next generation community policing, public safety, social media.

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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Authors: Romain Bosquet, Pierre-Olivier Vandanjon, Alex Coiret, Tristan Lorino

Abstract:

In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Keywords: High-speed train, energy, model, track profile, infrastructure

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