Search results for: Conventional conveyor line

Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

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This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.

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Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu

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In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.

Keywords: Connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control.

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Authors: Asmaa M. El-Bandrawy, Afaf M. Botla, Ghada E. El-Refaye, Hassan O. Ghareeb

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Background: Urinary incontinence is a common problem among adults. Its incidence increases with age and it is more frequent in women. Pelvic floor muscle training (PFMT) is the first-line therapy in the treatment of pelvic floor dysfunction (PFD) either alone or combined with biofeedback-assisted PFMT. The aim of the work: The purpose of this study is to evaluate the efficacy of biofeedback-assisted PFMT in postoperative stress urinary incontinence. Settings and Design: A single blind controlled trial design was. Methods and Material: This study was carried out in 30 volunteer patients diagnosed as severe degree of stress urinary incontinence and they were admitted to surgical treatment. They were divided randomly into two equal groups: (Group A) consisted of 15 patients who had been treated with post-operative biofeedback-assisted PFMT and home exercise program (Group B) consisted of 15 patients who had been treated with home exercise program only. Assessment of all patients in both groups (A) and (B) was carried out before and after the treatment program by measuring intra-vaginal pressure in addition to the visual analog scale. Results: At the end of the treatment program, there was a highly statistically significant difference between group (A) and group (B) in the intra-vaginal pressure and the visual analog scale favoring the group (A). Conclusion: biofeedback-assisted PFMT is an effective method for the symptomatic relief of post-operative female stress urinary incontinence.

Keywords: Stress urinary incontinence, pelvic floor muscles, pelvic floor exercises, biofeedback.

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Authors: Vasudha Bansal, M. L. Singla, C. Ghanshyam

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The effect of nonthermal pulsed electric field (PEF) and thermal treatment (90⁰C for 60s) was studied on quality parameters of emblica officinalis juice for the period of 6 weeks at 4⁰C using monopolar rectangular pulse of 1µs width. The PEF treatment was given using static chamber at 24kV/cm for 500µs. The quality of emblica officinalis juice was investigated in terms of non enzymatic browning index (NEBI), 5-hydroxymethyl-2-furfural (HMF), total polyphenol content and antioxidant capacity. ⁰Brix, pH and conductivity were evaluated as physical parameters. The aim of the work was to investigate the effect of PEF on the retention of bioactive compounds and retardation of browning activity. The results showed that conventional thermal treatment had led to a significant (p < 0.05) decrease of 48.15% in polyphenol content (129.56 mg of GAE L^-1), with higher NEBI and HMF formation (p < 0.05) whilst PEF suppressed NEBI and retained higher polyphenol compounds (168.59 mg GAE L^-1) with limiting the loss to 32.56% along maximum free radical scavenging activity (92.07%). However, pH, ⁰brix and electrical conductivity of treated juice samples remain unaffected. Therefore, PEF can be considered as an effective nonthermal treatment for retaining bioactive compounds along suppressing browning of emblica juice.

 

Keywords: Emblica officinalis juice, Free radical scavenging activity, Pulsed electric field, Total polyphenol content.

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Authors: Hossein Mohammadzadeh, Mojtaba Heydarizad

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Among various water resources, the surface water has a dominant role in providing water supply in the arid and semi-arid region of Iran. Andarokh-Kardeh basin is located in 50 km from Mashhad city - the second biggest city of Iran (NE of Iran), draining by Kardeh river which provides a significant portion of potable and irrigation water needs for Mashhad. The stable isotopes (¹⁸O, ²H,¹³C-DIC, and ¹³C-DOC), as reliable and precious water fingerprints, have been measured in Kardeh river (Kharket, Mareshk, Jong, All and Kardeh stations) and in Kardeh dam reservoirs (at five different sites S1 to S5) during March to June 2011 and June 2012. On δ¹⁸O vs. δ²H diagram, the river samples were plotted between Global and Eastern Mediterranean Meteoric Water lines (GMWL and EMMWL) which demonstrate that various moisture sources are providing humidity for precipitation events in this area. The enriched δ¹⁸O and δ²H values (-6.5 ‰ and -44.5 ‰ VSMOW) of Kardeh dam reservoir are compared to Kardeh river (-8.6‰and-54.4‰), and its deviation from Mashhad meteoric water line (MMWL- δ²H=7.16δ¹⁸O+11.22) is due to evaporation from the open surface water body. The enriched value of δ ¹³C-DIC and high amount of DIC values (-7.9 ‰ VPDB and 57.23 ppm) in the river and Kardeh dam reservoir (-7.3 ‰ VPDB and 55.53 ppm) is due to dissolution of Mozdooran Carbonate Formation lithology (Jm1 to Jm3 units) (contains enriched δ¹³C DIC values of 9.2‰ to 27.7‰ VPDB) in the region. Because of the domination of C3 vegetations in Andarokh_Kardeh basin, the δ¹³C-DOC isotope of the river (-28.4‰ VPDB) and dam reservoir (-32.3‰ VPDB) demonstrate depleted values. Higher DOC concentration in dam reservoir (2.57 ppm) compared to the river (0.72 ppm) is due to more biologogical activities and organic matters in dam reservoir.

Keywords: Dam reservoir, Iran, Kardeh river, Khorasan razavi, Stable isotopes.

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Authors: A. Nasiri Pour, B. Rostami Tabar, A.Rahimzadeh

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Accurate demand forecasting is one of the most key issues in inventory management of spare parts. The problem of modeling future consumption becomes especially difficult for lumpy patterns, which characterized by intervals in which there is no demand and, periods with actual demand occurrences with large variation in demand levels. However, many of the forecasting methods may perform poorly when demand for an item is lumpy. In this study based on the characteristic of lumpy demand patterns of spare parts a hybrid forecasting approach has been developed, which use a multi-layered perceptron neural network and a traditional recursive method for forecasting future demands. In the described approach the multi-layered perceptron are adapted to forecast occurrences of non-zero demands, and then a conventional recursive method is used to estimate the quantity of non-zero demands. In order to evaluate the performance of the proposed approach, their forecasts were compared to those obtained by using Syntetos & Boylan approximation, recently employed multi-layered perceptron neural network, generalized regression neural network and elman recurrent neural network in this area. The models were applied to forecast future demand of spare parts of Arak Petrochemical Company in Iran, using 30 types of real data sets. The results indicate that the forecasts obtained by using our proposed mode are superior to those obtained by using other methods.

Keywords: Lumpy Demand, Neural Network, Forecasting, Hybrid Approach.

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Authors: Panatcha Bovornseripatai, Siriporn Jongpatiwut, Somchai Osuwan, Suchada Butnark

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Hydrogenated biodiesel is one of the most promising renewable fuels. It has many advantages over conventional biodiesel, including higher cetane number, higher heating value, lower viscosity, and lower corrosiveness due to its absence of oxygen. From previous work, Pd/TiO2 gave high conversion and selectivity in hydrogenated biodiesel. In this work, the effect of biomass feedstocks (i.e. beef fat, chicken fat, pork fat, and jatropha oil) on the production of hydrogenated biodiesel over Pd/TiO2 has been studied. Biomass feedstocks were analyzed by ICP-OES (inductively coupled plasma optical emission spectrometry) to identify the content of impurities (i.e. P, K, Ca, Na, and Mg). The deoxygenation catalyst, Pd/TiO2, was prepared by incipient wetness impregnation (IWI) and tested in a continuous flow packed-bed reactor at 500 psig, 325°C, H2/feed molar ratio of 30, and LHSV of 4 h-1 for its catalytic activity and selectivity in hydrodeoxygenation. All feedstocks gave high selectivity in diesel specification range hydrocarbons and the main hydrocarbons were n-pentadecane (n-C15) and n-heptadecane (n- C17), resulting from the decarbonylation/decarboxylation reaction. Intermediates such as oleic acid, stearic acid, palmitic acid, and esters were also detected in minor amount. The conversion of triglycerides in jatropha oil is higher than those of chicken fat, pork fat, and beef fat, respectively. The higher concentration of metal impurities in feedstock, the lower conversion of feedstock.

Keywords: Hydrogenated biodiesel, hydrodeoxygenation, Pd/TiO2, biomass feedstock

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Authors: Festus A. Olutoge, Ahmed A. Akintunde, Anuoluwapo S. Kolade, Aaron A. Chadee, Jovanca Smith

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Geopolymer concrete's (GPC) compressive strength was investigated. The GPC was incorporated with rice husk ash (RHA) and ground granulated blast furnace slag (GGBFS), which may have potential in the construction industry to replace Portland limestone cement (PLC) concrete. The sustainable construction binders used were GGBFS and RHA, and a solution of sodium hydroxide (NaOH) and sodium silicate gel (Na2SiO3) was used as the 12-molar alkaline activator. Five GPC mixes comprising fine aggregates, coarse aggregates, GGBS, and RHA, and the alkaline solution in the ratio 2: 2.5: 1: 0.5, respectively, were prepared to achieve grade 40 concrete, and PLC was substituted with GGBFS and RHA in the ratios of 0:100, 25:75, 50:50, 75:25, and 100:0. A control mix was also prepared which comprised of 100% water and 100% PLC as the cementitious material. The GPC mixes were thermally cured at 60-80 ºC in an oven for approximately 24 h. After curing for 7 and 28 days, the compressive strength test results of the hardened GPC samples showed that GPC-Mix #3, comprising 50% GGBFS and 50% RHA, was the most efficient geopolymer mix. The mix had compressive strengths of 35.71 MPa and 47.26 MPa, 19.87% and 8.69% higher than the PLC concrete samples, which had 29.79 MPa and 43.48 MPa after 7 and 28 days, respectively. Therefore, GPC containing GGBFS incorporated with RHA is an efficient method of decreasing the use of PLC in conventional concrete production and reducing the high amounts of CO2 emitted into the atmosphere in the construction industry.

Keywords: Alkaline solution, cementitious material, geopolymer concrete, ground granulated blast furnace slag, rice husk ash.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.

Keywords: Spacecraft, neural network, FPGA, VHDL.

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Authors: R. Malathy

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High performance concrete is not only characterized by its high strength, workability, and durability but also by its smartness in performance without human care since the first day. If the concrete can cure on its own without external curing without compromising its strength and durability, then it is said to be high performance self-curing concrete. In this paper, an attempt is made on the performance study of internally cured concrete using biomaterials, namely Spinacea pleracea and Calatropis gigantea as self-curing agents, and it is compared with the performance of concrete with existing self-cure chemical, namely polyethylene glycol. The present paper focuses on workability, strength, and durability study on M20, M30, and M40 grade concretes replacing 30% of fly ash for cement. The optimum dosage of Spinacea pleracea, Calatropis gigantea, and polyethylene glycol was taken as 0.6%, 0.24%, and 0.3% by weight of cement from the earlier research studies. From the slump tests performed, it was found that there is a minimum variation between conventional concrete and self-cured concrete. The strength activity index is determined by keeping compressive strength of conventionally cured concrete for 28 days as unity and observed that, for self-cured concrete, it is more than 1 after 28 days and more than 1.15 after 56 days because of secondary reaction of fly ash. The performance study of concretes in aggressive environment like acid attack, sea water attack, and chloride attack was made, and the results are positive and encouraging in bio-self-cured concretes which are ecofriendly, cost effective, and high performance materials.

Keywords: Biomaterials, Calatropis gigantea, polyethylene glycol, Spinacea oleracea, self-curing concrete.

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Authors: Nanjiang Chen

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In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experience of space. Addressing these gaps, this paper presents a continuous visibility algorithm, providing a potentially valuable approach to measuring urban spaces from a human - centric perspective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this technique allows for a continuous range of visibility assessment, closely mirroring human visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Beijing's urban setting. Its key distinction lies in its potential to benefit a broad spectrum of stakeholders, ranging from urban developers to public policymakers, aiding in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.

Keywords: Visual openness, spatial continuity, ray-tracing algorithms, urban computation.

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: Butterfly valve, fluid-structure interaction, automatic CFD analysis, flow coefficient.

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: Adaptive algorithm, fuzzy systems, membership functions, observer.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%-40% compared to a traditional RL model.

Keywords: Control system, hydroponics, machine learning, reinforcement learning.

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Authors: M. Pisol B Mat Isa, Asmak Ab Rahman, Hezlina Bt M Hashim, Abd Mutalib B Embong

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Al-Murabahah is an Islamic financing facility used in asset financing, the profit rate of the contract is determined by components which are also being used in the conventional banking. Such are cost of fund, overhead cost, risk premium cost and bank-s profit margin. At the same time, the profit rate determined by Islamic banking system also refers to Inter-Bank Offered Rate (LIBOR) in London as a benchmark. This practice has risen arguments among Muslim scholars in term of its validity of the contract; whether the contract maintains the Shariah compliance or not. This paper aims to explore the view of Shariah towards the above components practiced by Islamic Banking in determining the profit rate of al-murabahah asset financing in Malaysia. This is a comparative research which applied the views of Muslim scholars from all major mazahibs in Islamic jurisprudence and examined the practices by Islamic banks in Malaysia for the above components. The study found that the shariah accepts all the components with conditions. The cost of fund is accepted as a portion of al-mudarabah-s profit, the overhead cost is accepted as a cost of product, risk premium cost consist of business risk and mitigation risk are accepted through the concept of alta-awun and bank-s profit margin is accepted as a right of bank after venturing in risky investment.

Keywords: Islamic banking, Islamic finance, al-murabahah and asset financing

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Authors: Aizreena Azaman, Mai Ishibashi, Masanori Ishizawa, Shin-Ichiroh Yamamoto

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Sensory input plays an important role to human posture control system to initiate strategy in order to counterpart any unbalance condition and thus, prevent fall. In previous study, joint stiffness was observed able to describe certain issues regarding to movement performance. But, correlation between balance ability and joint stiffness is still remains unknown. In this study, joint stiffening strategy at ankle and hip were observed under different sensory manipulations and its correlation with conventional clinical test (Functional Reach Test) for balance ability was investigated. In order to create unstable condition, two different surface perturbations (tilt up-tilt (TT) down and forward-backward (FB)) at four different frequencies (0.2, 0.4, 0.6 and 0.8 Hz) were introduced. Furthermore, four different sensory manipulation conditions (include vision and vestibular system) were applied to the subject and they were asked to maintain their position as possible. The results suggested that joint stiffness were high during difficult balance situation. Less balance people generated high average joint stiffness compared to balance people. Besides, adaptation of posture control system under repetitive external perturbation also suggested less during sensory limited condition. Overall, analysis of joint stiffening response possible to predict unbalance situation faced by human

Keywords: Balance ability, joint stiffness, sensory, adaptation, dynamic.

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Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material.

In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved.

In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: Thermal effect, Conduction, Heat dissipation, Thermal conductivity, Solar cell, PV module, Nodes, 3D-TLM.

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Authors: Takashi Ueda, Shinichi Enoki

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Forging parts is used to automobiles; because, they have high strength and it is possible to press them into complicated shape. When itis possible to manufacture hollow forging parts, it leads to reduce weightof the automobiles. But, hollow forging parts are confined to axisymmetrical shape. Hollowforging parts that were pressed to complicated shape are expected. Therefore, we forge a blank that aluminum alloy was inserted in stainless steel. After that, we can providecomplex forging parts that are reduced weight,ifit is possible to be melted the aluminum alloy away by using different of melting points.It is necessary to establish heat forging analysis methodon blank consist of stainless steel and aluminum alloy. Because,this forging is different from conventional forging and this technology is not confirmed. In this study, we compared forging experiment with numerical analysis on the view point of forming load and shape after forming and establish how to set the material temperaturesof two metals and material property of stainless steel on the analysis method. Consequently, temperature difference of stainless steel and aluminum alloy was obtained by experiment. We got material property of stainless steel on forging experimental by compression tests. We had compared numerical analysis that was used the temperature difference of two metals and the material property of stainless steel on forging experimental with forging experiment. Forging analysis method on blankconsist of two metals was established by result of numerical analysis having agreedwith result of forging experiment.

Keywords: Forging, lightweight, analysis, hollow.

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Authors: Siddeeq Y. Ameen, Mohammed K. Yousif

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Cooperative communication systems are considered to be a promising technology to improve the system capacity, reliability and performances over fading wireless channels. Cooperative relaying system with a single antenna will be able to reach the advantages of multiple antenna communication systems. It is ideally suitable for the distributed communication systems; the relays can cooperate and form virtual MIMO systems. Thus the paper will aim to investigate the possible enhancement of cooperated system using decode and forward protocol. On the decode and forward an attempt to cancel or at least reduce the interference instead of increasing the SNR values is achieved. The latter can be achieved via the use group of relays depending on the channel status from source to relay and relay to destination respectively.

In the proposed system, the transmission time has been divided into two phases to be used by the decode and forward protocol. The first phase has been allocated for the source to transmit its data whereas the relays and destination nodes are in receiving mode. On the other hand, the second phase is allocated for the first and second groups of relay nodes to relay the data to the destination node. Simulations results have shown an improvement in performance is achieved compared to the conventional decode and forward in terms of BER and transmission rate.

Keywords: Cooperative systems, decode and forward, interference cancellation, virtual MIMO.

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Authors: T. Aboumahboub, R. Brecha, H. B. Shrestha, U. F. Hutfilter, A. Geiges, W. Hare, M. Schaeffer, L. Welder, M. Gidden

Abstract:

The proposed stringent mitigation targets require an immediate start for a drastic transformation of the whole energy system. The current Australian energy system is mainly centralized and fossil fuel-based in most states with coal and gas-fired plants dominating the total produced electricity over the recent past. On the other hand, the country is characterized by a huge, untapped renewable potential, where wind and solar energy could play a key role in the decarbonization of the Australia’s future energy system. However, integrating high shares of such variable renewable energy sources (VRES) challenges the power system considerably due to their temporal fluctuations and geographical dispersion. This raises the concerns about flexibility gap in the system to ensure the security of supply with increasing shares of such intermittent sources. One main flexibility dimension to facilitate system integration of high shares of VRES is to increase the cross-sectoral integration through coupling of electricity to other energy sectors alongside the decarbonization of the power sector and reinforcement of the transmission grid. This paper applies a multi-sectoral energy system optimization model for Australia. We investigate the cost-optimal configuration of a renewable-based Australian energy system and its transformation pathway in line with the ambitious range of proposed climate change mitigation targets. We particularly analyse the implications of linking the electricity and transport sectors in a prospective, highly renewable Australian energy system.

Keywords: Decarbonization, energy system modeling, sector coupling, variable renewable energies.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

Abstract:

Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Keywords: Satellite, neural network, MATLAB, power system.

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Authors: Nan-Chyuan Tsai, Chao-Wen Chiang, Bai-Lu Wang

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The three-time-scale plant model of a wind power generator, including a wind turbine, a flexible vertical shaft, a Variable Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB) unit and the applied wind sequence, is constructed. In order to make the wind power generator be still able to operate as the spindle speed exceeds its rated speed, the VIF is equipped so that the spindle speed can be appropriately slowed down once any stronger wind field is exerted. To prevent any potential damage due to collision by shaft against conventional bearings, the AMB unit is proposed to regulate the shaft position deviation. By singular perturbation order-reduction technique, a lower-order plant model can be established for the synthesis of feedback controller. Two major system parameter uncertainties, an additive uncertainty and a multiplicative uncertainty, are constituted by the wind turbine and the VIF respectively. Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed to account for these uncertainties and suppress the unmodeled higher-order plant dynamics. At last, the efficacy of the FSSMC is verified by intensive computer and experimental simulations for regulation on position deviation of the shaft and counter-balance of unpredictable wind disturbance.

Keywords: Sliding Mode Control, Singular Perturbation, Variable Inertia Flywheel.

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Authors: Mohammed T. Hayajneh

Abstract:

Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: Composite, fuzzy, tool life, wear.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: A. S. Abdel-Razek, M. M. M. Abd-Elgawad

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The potential of entomopathogenic nematodes in suppressing T. squalida population on cauliflower from transplanting to harvest was evaluated. Significant reductions in plant infestation percentage and population density (/m2) were recorded throughout the plantation seasons, 2011 and 2012 before and after spraying the plants. The percent reduction in numbers/m2 was the highest in March for the treatments with Heterorhabditis indica Behera and Heterorhabditis bacteriophora Giza during the plantation season 2011, while at the plantation season 2012, the reduction in population density was the highest in January for Heterorhabditis Indica Behera and in February for H . bacteriophora Giza treatments. In a comparison test with conventional insecticides Hostathion and Lannate, there were no significant differences in control measures resulting from treatments with H. indica Behera, H. bacteriophora Giza and Lannate. At the plantation season is 2012. Also, the treatments reduced the economic threshold of T. squalida on cauliflower in this experiment as compared with before and after spraying with both the two entomopathogenic nematodes at both seasons 2011 and 2012. This means an increase in the marketability of heads harvested as a consequence of monthly treatments. 

Keywords: Cruciferous plants, chemical insecticides, microbial control, Scarabiead beetles, seasonal monitoring.

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Authors: Ali Reza Manashty, Mohammad Reza Ahmadzadeh Raji, Zahra Forootan Jahromi, Amir Rajabzadeh

Abstract:

The ARMrayan Multimedia Mobile CMS (Content Management System) is the first mobile CMS that gives the opportunity to users for creating multimedia J2ME mobile applications with their desired content, design and logo; simply, without any need for writing even a line of code. The low-level programming and compatibility problems of the J2ME, along with UI designing difficulties, makes it hard for most people –even programmers- to broadcast their content to the widespread mobile phones used by nearly all people. This system provides user-friendly, PC-based tools for creating a tree index of pages and inserting multiple multimedia contents (e.g. sound, video and picture) in each page for creating a J2ME mobile application. The output is a standalone Java mobile application that has a user interface, shows texts and pictures and plays music and videos regardless of the type of devices used as long as the devices support the J2ME platform. Bitmap fonts have also been used thus Middle Eastern languages can be easily supported on all mobile phone devices. We omitted programming concepts for users in order to simplify multimedia content-oriented mobile applictaion designing for use in educational, cultural or marketing centers. Ordinary operators can now create a variety of multimedia mobile applications such as tutorials, catalogues, books, and guides in minutes rather than months. Simplicity and power has been the goal of this CMS. In this paper, we present the software engineered-designed concepts of the ARMrayan MCMS along with the implementation challenges faces and solutions adapted.

Keywords: Mobile CMS, MCMS, Mobile Content Builder, J2ME Application, Multimedia Mobile Application, MultimediaCMS, Multimedia Mobile CMS, Content Management System.

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Authors: Hazem M. El-Bakry, Ahmed Atwan

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Computer networks are essential part in computerbased information systems. The performance of these networks has a great influence on the whole information system. Measuring the usability criteria and customers satisfaction on small computer network is very important. In this article, an effective approach for measuring the usability of business network in an information system is introduced. The usability process for networking provides us with a flexible and a cost-effective way to assess the usability of a network and its products. In addition, the proposed approach can be used to certify network product usability late in the development cycle. Furthermore, it can be used to help in developing usable interfaces very early in the cycle and to give a way to measure, track, and improve usability. Moreover, a new approach for fast information processing over computer networks is presented. The entire data are collected together in a long vector and then tested as a one input pattern. Proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Usability Criteria, Computer Networks, Fast Information Processing, Cross Correlation, Frequency Domain.

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Authors: Zhichao Jiao, Craig Farnham, Jihui Yuan, Kazuo Emura

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It is common to use the outdoor design weather data to select the air-conditioning capacity in the building design stage. The meteorological elements of outdoor design weather data are usually selected based on their excess frequency separately while the dependency between the elements is not well considered. It means that the simultaneous occurrence probability of these elements is smaller than the original excess frequency which may cause an overestimation of selecting air-conditioning capacity. Therefore, the copula approach which can capture the dependency between multivariate data was used to model the joint distributions of the meteorological elements, like air temperature and global solar radiation. We suggest a method based on the specific simultaneous occurrence probability of these two elements of selecting more credible outdoor design conditions. The hourly weather data at 12 noon from 2001 to 2010 in Tokyo, Japan are used to analyze the dependency structure and joint distribution, the Gaussian copula represents the dependence of data best. According to calculating the air temperature and global solar radiation in specific simultaneous occurrence probability and the common exceeding, the results show that both the air temperature and global solar radiation based on simultaneous occurrence probability are lower than these based on the conventional method in the same probability.

Keywords: Copula approach, Design weather database, energy conservation, HVAC.

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Authors: J. Gu, W.B. Lee, C.F. Cheung, E. Tsui, W.M. Wang

Abstract:

Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Keywords: Knowledge-Based System, Knowledge Elicitation, Knowledge Management, Taxonomy, Unstructured Information Management

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Authors: Sangeeta Mandal, Rajib Kar, Durbadal Mandal, Sakti Prasad Ghoshal

Abstract:

In this paper, an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA) has been presented. In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. Given the filter specifications to be realized, the PSO-CFIWA algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristic. In this paper, for the given problem, the designs of the optimal FIR high pass filters of different orders have been performed. The simulation results have been compared to those obtained by the well accepted algorithms such as Parks and McClellan algorithm (PM), genetic algorithm (GA). The results justify that the proposed optimal filter design approach using PSOCFIWA outperforms PM and GA, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

Keywords: FIR Filter; PSO-CFIWA; PSO; Parks and McClellanAlgorithm, Evolutionary Optimization Technique; MagnitudeResponse; Convergence; High Pass Filter

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