Search results for: Photon Detection Efficiency

Authors: Chan-Sik Kim, Jong-Seong Kim, Se Won Lee, Hoo-Gon Choi

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In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effectively and efficiently through good strategy, and treated by optimal responses to minimize risk cost. Four strategies are adopted to handle the risks in this study. The optimal responses are characterized by high reduction of risk costs with high efficiency. This study suggests a framework to decide the optimal responses considering the core risks, risk costs, response efficiency and response costs for successful NPD projects. Both binary particles warm optimization (BPSO) and multi-objective particle swarm optimization (MOPSO) methods are mainly used in the framework. Although several limitations exist in use for real industries, the frame work shows good strength for handling the risks with highly scientific ways through an example.

Keywords: NPD projects, risk cost, strategy, optimal responses, Particle Swarm Optimization.

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: Comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control.

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Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: Edge effect, scale optimization, small crack locating, spatial wavelet.

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Authors: Eman. K. Ramadan, Abdelgawad. S. El-Tahawy

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The objective of this study was to evaluate the effects of calving season on the production and economic efficiency of dairy farms in Egypt. Our study was performed at dairy production farms in the Alexandria, Behera, and Kafr El-Sheikh provinces of Egypt from summer 2010 to winter 2013. The randomly selected dairy farms had herds consisting of Baladi, Holstein-Friesian, or cross-bred (Baladi × Holstein-Friesian) cows. The data were collected from production records and responses to a structured questionnaire. The average total return differed significantly (P < 0.05) between the different cattle breeds and calving seasons. The average total return was highest for the Holstein- Friesian cows that calved in the winter (29106.42 EGP/cow/year), and it was lowest for Baladi cows that calved in the summer (12489.79 EGP/cow/year). Differences in total returns between the cows that calved in the winter or summer or between the foreign and native breeds, as well as variations in calf prices, might have contributed to the differences in milk yield. The average net profit per cow differed significantly (P < 0.05) between the cattle breeds and calving seasons. The average net profit values for the Baladi cows that calved in the winter or summer were 2413 and 2994.96 EGP/cow/year, respectively, and those for the Holstein- Friesian cows were 10744.17 and 7860.56 EGP/cow/year, respectively, whereas those for the cross-bred cows were 10174.86 and 7571.33 EGP/cow/year, respectively. The variations in net profit might have resulted from variation in the availability or price of feed materials, milk prices, or sales volumes. Our results show that the breed and calving season of dairy cows significantly affected the economic efficiency of dairy farms in Egypt. The cows that calved in the winter produced more milk than those that calved in the summer, which may have been the result of seasonal influences, such as temperature, humidity, management practices, and the type of feed or green fodder available.

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Authors: Chris K. Y. Lo, Andy C. L. Yeung, T. C. Edwin Cheng

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ISO 9000 is the most popular and widely adopted meta-standard for quality and operational improvements. However, only limited empirical research has been conducted to examine the impact of ISO 9000 on operational performance based on objective and longitudinal data. To reveal any causal relationship between the adoption of ISO 9000 and operational performance, we examined the timing and magnitude of change in time-based performance as a result of ISO 9000 adoption. We analyzed the changes in operating cycle, inventory days, and account receivable days prior and after the implementation of ISO 9000 in 695 publicly listed manufacturing firms. We found that ISO 9000 certified firms shortened their operating cycle time by 5.28 days one year after the implementation of ISO 9000. In the long-run (3 years after certification), certified firms showed continuous improvement in time-based efficiency, and experienced a shorter operating cycle time of 11 days than that of non-certified firms. There was an average of 6.5% improvement in operating cycle time for ISO 9000 certified firms. Both inventory days and account receivable days showed similar significant improvements after the implementation of ISO 9000, too.

Keywords: ISO 9000, Operating Cycle, Time-based efficiency.

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Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: Hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff.

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Authors: Indrasen Raghupatruni, Michael Glora, Ralf Diekmann, Thomas Demmer

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As the trend in automotive technology is fast moving towards hybridization and electrification to curb emissions as well as to improve the fuel efficiency, air-conditioning systems in passenger cars have not caught up with this trend and still remain as the major energy consumers amongst others. Adsorption based air-conditioning systems, e.g. with silica-gel water pair, which are already in use for residential and commercial applications, are now being considered as a technology leap once proven feasible for the passenger cars. In this paper we discuss a methodology, challenges and feasibility of implementing an adsorption based air-conditioning system in a passenger car utilizing the exhaust waste heat. We also propose an optimized control strategy with interfaces to the engine control unit of the vehicle for operating this system with reasonable efficiency supported by our simulation and validation results in a prototype vehicle, additionally comparing to existing implementations, simulation based as well as experimental. Finally we discuss the influence of start-stop and hybrid systems on the operation strategy of the adsorption air-conditioning system.

Keywords: Adsorption air-conditioning, feasibility study, optimized control strategy, prototype vehicle.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: Sandesh Achar

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Artificial intelligence (AI) is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remains a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: Artificial intelligence, AI, cloud computing, deep learning, machine learning, ML, internet of things, IoT.

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Authors: Rohit Tripathi, Sumit Tiwari, G. N. Tiwari

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In present study, an approach is adopted where photovoltaic thermal flat plate collector is integrated with compound parabolic concentrator. Analytical expression of temperature dependent electrical efficiency of N number of partially covered Photovoltaic Thermal (PVT) - Compound Parabolic Concentrator (CPC) water collector connected in series has been derived with the help of basic thermal energy balance equations. Analysis has been carried for winter weather condition at Delhi location, India. Energy and exergy performance of N - partially covered Photovoltaic Thermal (PVT) - Compound Parabolic Concentrator (CPC) Water collector system has been compared for two cases: (i) 25% area of water collector covered by PV module, (ii) 75% area of water collector covered by PV module. It is observed that case (i) has been best suited for thermal performance and case (ii) for electrical energy as well as overall exergy.

Keywords: Compound parabolic concentrator, Energy, Photovoltaic thermal, Temperature dependent electrical efficiency.

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Authors: Junting Xiang, Jörg Uwe Schlüter, Fei Duan

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The miniaturization of gas turbines promises many advantages. Miniature gas turbines can be used for local power generation or the propulsion of small aircraft, such as UAV and MAV. However, experience shows that the miniaturization of conventional gas turbines, which are optimized at their current large size, leads to a substantial loss of efficiency and performance at smaller scales. This may be due to a number of factors, such as the Reynolds-number effect, the increased heat transfer, and manufacturing tolerances. In the present work, we focus on computational investigations of the Reynolds number effect and the wall heat transfer on the performance of axial compressor during its size change. The NASA stage 35 compressor is selected as the configuration in this study and computational fluid dynamics (CFD) is used to carry out the miniaturization process and simulations. We perform parameter studies on the effect of Reynolds number and wall thermal conditions. Our results indicate a decrease of efficiency, if the compressor is miniaturized based on its original geometry due to the increase of viscous effects. The increased heat transfer through wall has only a small effect and will actually benefit compressor performance based on our study.

Keywords: Axial compressor, CFD, heat transfer, miniature gas turbines, Reynolds number.

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Authors: Mahmoud A. Rabah

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The present study shows a method to recover lead metal from wastewater of wet scrubber in secondary lead smelter. The wastewater is loaded with 42,000 ppm of insoluble lead compounds (TSP) submicron in diameter. The technical background benefits the use of cationic polyfloc solution to flocculate these colloidal solids before press filtration. The polymer solution is injected in the wastewater stream in a countercurrent flow design. The study demonstrates the effect of polymer dose, temperature, pH, flow velocity of the wastewater and different filtration media on the filtration extent. Results indicated that filtration rate (¦_r), quality of purified water, purifying efficiency (¦_e) and floc diameter decrease regularly with increase in mass flow rate and velocity up to turbulence of 0.5 m.sec^-1. Laminar flow is in favor of flocculation. Polyfloc concentration of 0.75 – 1.25 g/m³ wastewater is convenient. Increasing temperature of the wastewater and pneumatic pressure of filtration enhances ¦_r. High pH value deforms floc formation and assists degradation of the filtration fabric. The overall efficiency of the method amounts to 93.2 %. Lead metal was recovered from the filtrate cake using carbon as a reducing agent at 900°C.

Keywords: Wastewater, wet scrubbers, filtration, secondary lead.

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Authors: Vahid Aryanpur , Ehsan Shafiei

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This paper presents an environmental and technoeconomic evaluation of light duty vehicles in Iran. A comprehensive well-to-wheel (WTW) analysis is applied to compare different automotive fuel chains, conventional internal combustion engines and innovative vehicle powertrains. The study examines the competitiveness of 15 various pathways in terms of energy efficiencies, GHG emissions, and levelized cost of different energy carriers. The results indicate that electric vehicles including battery electric vehicles (BEV), fuel cell vehicles (FCV) and plug-in hybrid electric vehicles (PHEV) increase the WTW energy efficiency by 54%, 51% and 46%, respectively, compared to common internal combustion engines powered by gasoline. On the other hand, greenhouse gas (GHG) emissions per kilometer of FCV and BEV would be 48% lower than that of gasoline engines. It is concluded that BEV has the lowest total cost of energy consumption and external cost of emission, followed by internal combustion engines (ICE) fueled by CNG. Conventional internal combustion engines fueled by gasoline, on the other hand, would have the highest costs.

Keywords: Well-to-Wheel analysis, Energy Efficiency, GHG emissions, Levelized cost of energy, Alternative fuel vehicles.

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Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: Aerial image, land-cover, LiDAR, soil fertility degradation.

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Authors: M.Suganthi, M.Madheswaran

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This paper presents a novel approach to finding a priori interesting regions in mammograms. In order to delineate those regions of interest (ROI-s) in mammograms, which appear to be prominent, a topographic representation called the iso-level contour map consisting of iso-level contours at multiple intensity levels and region segmentation based-thresholding have been proposed. The simulation results indicate that the computed boundary gives the detection rate of 99.5% accuracy.

Keywords: Breast Cancer, Mammogram, and Segmentation.

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Authors: Nafe Moradkhani, Frederick Benaben, Benoit Montreuil, Ali Vatankhah Barenji, Dima Nazzal

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In the context of the global pandemic, the practical management of the 2020 presidential election in the USA was a strong concern. To anticipate and prepare for this election accurately, one of the main challenges was to confront: (i) forecasts of voter turnout, (ii) capacities of the facilities and, (iii) potential configuration options of resources. The approach chosen to conduct this anticipative study consists of collecting data about forecasts and using simulation models to work simultaneously on resource allocation and facility configuration of polling places in Fulton County, Georgia’s largest county. This article presents the results of the simulations of such places facing pre-identified potential risks. These results are oriented towards the efficiency of these places according to different criteria (health, trust, comfort). Then a dynamic framework is introduced to describe risks as physical forces perturbing the efficiency of the observed system. Finally, the main benefits and contributions resulting from this simulation campaign are presented.

Keywords: performance, decision support, simulation, artificial intelligence, risk management, election, pandemics, information system

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Authors: A. Thakur, P. S. Panesar, M. S. Saini

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Extraction of lactic acid by emulsion liquid membrane technology (ELM) using n-trioctyl amine (TOA) in n-heptane as carrier within the organic membrane along with sodium carbonate as acceptor phase was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined effect of five independent variables, vizlactic acid concentration in aqueous phase (c_l), sodium carbonate concentration in stripping phase (c_s), carrier concentration in membrane phase (ψ), treat ratio, and batch extraction time (τ)  with equal volume of organic and external aqueous phase on lactic acid extraction efficiency. The maximum lactic acid extraction efficiency (ηext) of 98.21%from aqueous phase in a batch reactor using ELM was found at the optimized values for test variables, cl, cs, ψ,
and τ as 0.06 [M], 0.18 [M], 4.72 (%,v/v), 1.98 (v/v) and 13.36 min respectively. 

Keywords: Emulsion liquid membrane, extraction, lactic acid, n-trioctylamine, response surface methodology.

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Authors: Ghazi AL-Sukkar, Iyad Jafar, Khalid Darabkh, Raed Al-Zubi, Mohammed Hawa

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Smart Grids employ wireless sensor networks for their control and monitoring. Sensors are characterized by limitations in the processing power, energy supply and memory spaces, which require a particular attention on the design of routing and data management algorithms. Since most routing algorithms for sensor networks, focus on finding energy efficient paths to prolong the lifetime of sensor networks, the power of sensors on efficient paths depletes quickly, and consequently sensor networks become incapable of monitoring events from some parts of their target areas. In consequence, the design of routing protocols should consider not only energy efficiency paths, but also energy efficient algorithms in general. In this paper we propose an energy efficient routing protocol for wireless sensor networks without the support of any location information system. The reliability and the efficiency of this protocol have been demonstrated by simulation studies where we compare them to the legacy protocols. Our simulation results show that these algorithms scale well with network size and density.

Keywords: Data-centric storage, Dynamic Address Allocation, Sensor networks, Smart Grid Communications.

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Authors: Hsien-cheng Chou, Fei-pei Lai, Hung-chang Lee

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At present, dictionary attack has been the basic tool for recovering key passwords. In order to avoid dictionary attack, users purposely choose another character strings as passwords. According to statistics, about 14% of users choose keys on a keyboard (Kkey, for short) as passwords. This paper develops a framework system to attack the password chosen from Kkeys and analyzes its efficiency. Within this system, we build up keyboard rules using the adjacent and parallel relationship among Kkeys and then use these Kkey rules to generate password databases by depth-first search method. According to the experiment results, we find the key space of databases derived from these Kkey rules that could be far smaller than the password databases generated within brute-force attack, thus effectively narrowing down the scope of attack research. Taking one general Kkey rule, the combinations in all printable characters (94 types) with Kkey adjacent and parallel relationship, as an example, the derived key space is about 240 smaller than those in brute-force attack. In addition, we demonstrate the method's practicality and value by successfully cracking the access password to UNIX and PC using the password databases created

Keywords: Brute-force attack, dictionary attack, depth-firstsearch, password attack.

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Authors: Christoph Speer

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Decentralized ventilation systems should combine a small and economical design with high aerodynamic and thermal efficiency. The Counter Flow Heat Recovery Fan (CHRF) provides the ability to meet these requirements by using only one cross flow fan with a large number of blades to generate both airflows and which simultaneously acts as a regenerative counter flow heat exchanger. The successful development of the first laboratory prototype has shown the potential of this ventilation system. Occurring condensate on the surfaces of the fan blades during the cold and dry season can be recovered through the characteristic mode of operation. Hence the CHRF provides the possibility to avoid the need for frost protection and condensate drain. Through the implementation of system-specific solutions for flow balancing and summer bypass the required functionality is assured. The scalability of the CHRF concept allows the use in renovation as well as in new buildings from single-room devices through to systems for office buildings. High aerodynamic and thermal efficiency and the lower number of required mechatronic components should enable a reduction in investment as well as operating costs. The rotor is the key component of the system, the requirements and possible implementation variants are presented.

Keywords: CHRF, counter flow heat recovery fan, decentralized ventilation system, renovation.

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Authors: S. Phanyaem

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Exponentially weighted moving average control chart (EWMA) is a popular chart used for detecting shift in the mean of parameter of distributions in quality control. The objective of this paper is to compare the efficiency of control chart to detect an increases in the mean of a process. In particular, we compared the Maximum Exponentially Weighted Moving Average (MaxEWMA) and Maximum Generally Weighted Moving Average (MaxGWMA) control charts when the observations are Exponential distribution. The criteria for evaluate the performance of control chart is called, the Average Run Length (ARL). The result of comparison show that in the case of process is small sample size, the MaxEWMA control chart is more efficiency to detect shift in the process mean than MaxGWMA control chart. For the case of large sample size, the MaxEWMA control chart is more sensitive to detect small shift in the process mean than MaxGWMA control chart, and when the process is a large shift in mean, the MaxGWMA control chart is more sensitive to detect mean shift than MaxEWMA control chart.

Keywords: Maximum Exponentially Weighted Moving Average, Maximum General Weighted Moving Average, Average Run Length.

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Authors: Saeid Nahi, Seyed Mohammad Hossein Nabavi

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Nowadays, power systems, energy generation by wind has been very important. Noting that the production of electrical energy by wind turbines on site to several factors (such as wind speed and profile site for the turbines, especially off the wind input speed, wind rated speed and wind output speed disconnect) is dependent. On the other hand, several different types of turbines in the market there. Therefore, selecting a turbine that its capacity could also answer the need for electric consumers the efficiency is high something is important and necessary. In this context, calculating the amount of wind power to help optimize overall network, system operation, in determining the parameters of wind power is very important. In this article, to help calculate the amount of wind power plant, connected to the national network in the region Manjil wind, selecting the best type of turbine and power delivery profile appropriate to the network using Monte Carlo method has been. In this paper, wind speed data from the wind site in Manjil, as minute and during the year has been. Necessary simulations based on Random Numbers Simulation method and repeat, using the software MATLAB and Excel has been done.

Keywords: wind turbine, efficiency, wind turbine work points, Random Numbers, reliability

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: Sensors, endocrine disruptors, nanoparticles, electrochemical, microscopy.

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Authors: Akshaya Kumar Verma, Puspendu Bhunia*, Rajesh Roshan Dash

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Magnesium chloride, though cost wise roughly same as of ferrous sulphate, is less commonly used coagulant in comparison to the ferrous sulphate for the treatment of wastewater. The present study was conducted to investigate the comparative effectiveness of ferrous sulphate (FeSO4.7H2O) as iron based salt and magnesium chloride (MgCl2) as magnesium based salt in terms of decolorization and chemical oxygen demand (COD) reduction efficiency of textile wastewater. The coagulants were evaluated for synthetic textile wastewater containing two diazo dyes namely Reactive Black 5 (RB5) and Congo Red (CR) and one anthraquinone dye as Disperse Blue 3 (DB3), in seven possible equi-ratio combinations. Other chemical constituents that are normally released from different textile processing units were also added to replicate a practical scenario. From this study, MgCl2/Lime was found to be a superior coagulant system as compared to FeSO4.7H2O/Lime, FeSO4.7H2O/NaOH and MgCl2/NaOH.

Keywords: Coagulation, Color removal, Magnesium chloride, Textile wastewater

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Authors: B.P. Bezruchko, D.A. Smirnov

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Quantitative characterization of nonlinear directional couplings between stochastic oscillators from data is considered. We suggest coupling characteristics readily interpreted from a physical viewpoint and their estimators. An expression for a statistical significance level is derived analytically that allows reliable coupling detection from a relatively short time series. Performance of the technique is demonstrated in numerical experiments.

Keywords: Nonlinear time series analysis, directional couplings, coupled oscillators.

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Authors: Ammar Elyas babiker, M.Nordin B. Zakaria, Hassan Yosif, Samir B. Ibrahim

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Variable channel conditions in underwater networks, and variable distances between sensors due to water current, leads to variable bit error rate (BER). This variability in BER has great effects on energy efficiency of error correction techniques used. In this paper an efficient energy adaptive hybrid error correction technique (AHECT) is proposed. AHECT adaptively changes error technique from pure retransmission (ARQ) in a low BER case to a hybrid technique with variable encoding rates (ARQ & FEC) in a high BER cases. An adaptation algorithm depends on a precalculated packet acceptance rate (PAR) look-up table, current BER, packet size and error correction technique used is proposed. Based on this adaptation algorithm a periodically 3-bit feedback is added to the acknowledgment packet to state which error correction technique is suitable for the current channel conditions and distance. Comparative studies were done between this technique and other techniques, and the results show that AHECT is more energy efficient and has high probability of success than all those techniques.

Keywords: Underwater communication, wireless sensornetworks, error correction technique, energy efficiency

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

Abstract:

Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: Y. Aldali, F. Ahwide

Abstract:

This paper investigates the application of large scale (LS-PV) two-axis tracking photovoltaic power plant in Al-Jagbob, Libya. A 50MW PV-grid connected (two-axis tracking) power plant design in Al-Jagbob, Libya has been carried out presently. A hetero-junction with intrinsic thin layer (HIT) type PV module has been selected and modeled. A Microsoft Excel-VBA program has been constructed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency for this system, for tracking system. The results for energy production show that the total energy output is 128.5 GWh/year. The average module efficiency is 16.6%. The electricity generation capacity factor (CF) and solar capacity factor (SCF) were found to be 29.3% and 70.4% respectively. A 50MW two axis tracking power plant with a total energy output of 128.5 GWh/year would reduce CO₂ pollution by 85,581 tonnes of each year. The payback time for the proposed LS-PV photovoltaic power plant was found to be 4 years.

Keywords: Large PV power plant, solar energy, environmental impact, Dual-axis tracking system.

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Authors: F. Hafdhi, T. Khir, A. Ben Yahia, A. Ben Brahim

Abstract:

An Energetic and exergetic analysis is conducted on a Steam Turbine Power Plant of an existing Phosphoric Acid Factory. The heat recovery systems used in different parts of the plant are also considered in the analysis. Mass, thermal and exergy balances are established on the main compounds of the factory. A numerical code is established using EES software to perform the calculations required for the thermal and exergy plant analysis. The effects of the key operating parameters such as steam pressure and temperature, mass flow rate as well as seawater temperature, on the cycle performances are investigated. A maximum Exergy Loss Rate of about 72% is obtained for the melters, followed by the condensers, heat exchangers and the pumps. The heat exchangers used in the phosphoric acid unit present exergetic efficiencies around 33% while 60% to 72% are obtained for steam turbines and blower. For the explored ranges of HP steam temperature and pressure, the exergy efficiencies of steam turbine generators STGI and STGII increase of about 2.5% and 5.4% respectively. In the same way optimum HP steam flow rate values, leading to the maximum exergy efficiencies are defined.

Keywords: Steam turbine generator, energy efficiency, exergy efficiency, phosphoric acid plant.

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Authors: Jahedul Islam Chowdhury, Bao Kha Nguyen, David Thornhill, Roy Douglas, Stephen Glover

Abstract:

Organic Rankine Cycle (ORC) is the most commonly used method for recovering energy from small sources of heat. The investigation of the ORC in supercritical condition is a new research area as it has a potential to generate high power and thermal efficiency in a waste heat recovery system. This paper presents a steady state ORC model in supercritical condition and its simulations with a real engine’s exhaust data. The key component of ORC, evaporator, is modelled using finite volume method, modelling of all other components of the waste heat recovery system such as pump, expander and condenser are also presented. The aim of this paper is to investigate the effects of mass flow rate and evaporator outlet temperature on the efficiency of the waste heat recovery process. Additionally, the necessity of maintaining an optimum evaporator outlet temperature is also investigated. Simulation results show that modification of mass flow rate is the key to changing the operating temperature at the evaporator outlet.

Keywords: Organic Rankine cycle, supercritical condition, steady state model, waste heat recovery.

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