Search results for: intermediate inputs
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1233

Search results for: intermediate inputs

603 Identification and Control the Yaw Motion Dynamics of Open Frame Underwater Vehicle

Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

Abstract:

The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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602 Energy Absorption Capacity of Aluminium Foam Manufactured by Kelvin Model Loaded Under Different Biaxial Combined Compression-Torsion Conditions

Authors: H. Solomon, A. Abdul-Latif, R. Baleh, I. Deiab, K. Khanafer

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Aluminum foams were developed and tested due to their high energy absorption abilities for multifunctional applications. The aim of this research work was to investigate experimentally the effect of quasi-static biaxial loading complexity (combined compression-torsion) on the energy absorption capacity of highly uniform architecture open-cell aluminum foam manufactured by kelvin cell model. The two generated aluminum foams have 80% and 85% porosities, spherical-shaped pores having 11mm in diameter. These foams were tested by means of several square-section specimens. A patented rig called ACTP (Absorption par Compression-Torsion Plastique), was used to investigate the foam response under quasi-static complex loading paths having different torsional components (i.e., 0°, 37° and 53°). The main mechanical responses of the aluminum foams were studied under simple, intermediate and severe loading conditions. In fact, the key responses to be examined were stress plateau and energy absorption capacity of the two foams with respect to loading complexity. It was concluded that the higher the loading complexity and the higher the relative density, the greater the energy absorption capacity of the foam. The highest energy absorption was thus recorded under the most complicated loading path (i.e., biaxial-53°) for the denser foam (i.e., 80% porosity).

Keywords: open-cell aluminum foams, biaxial loading complexity, foams porosity, energy absorption capacity, characterization

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601 Alloy Design of Single Crystal Ni-base Superalloys by Combined Method of Neural Network and CALPHAD

Authors: Mehdi Montakhabrazlighi, Ercan Balikci

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The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

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600 Monodisperse Hallow Sandwich MOF for the Catalytic Oxidation of Benzene at Room Temperature

Authors: Srinivasapriyan Vijayan

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Phenol is one of the most vital chemical in industry. Nowadays, phenol production is based upon the three-step cumene process, which involves a hazardous cumene hydroperoxide intermediate and produces nearly equimolar amounts of acetone as a coproduct. An attractive route in phenol production is the direct one-step selective hydroxylation of benzene using eco-friendly oxidants such as O2, N2O, and H2O2. In particular, the direct hydroxylation of benzene to form phenol with O2 has recently attracted extensive research attention because this process is green clean and eco-friendly. However, most of the catalytic systems involving O2 have a low rate of hydroxylation because the direct introduction of hydroxyl functionality into benzene is challenging. Almost all the developed catalytic systems require an elevated temperature and suffer from low conversion because of the notoriously low reactivity of aromatic C–H bonds. Moreover, increased reactivity of phenol relative to benzene makes the selective oxidation of benzene to phenol very difficult, especially under heating conditions. Hollow spheres, a very fascinating class of materials with good permeation and low density, highly monodisperse MOF hollow sandwich spheres have been rationally synthesized using monodisperse polystyrene (PS) nanoparticles as templates through a versatile step-by-step self-assembly strategy. So, our findings could pave the way toward highly efficient nonprecious catalysts for low-temperature oxidation reactions in heterogeneous catalysis. Because it is easy post-reaction separation, its cheap, green and recyclable.

Keywords: benzene hydroxylation, Fe-based metal organic frameworks, molecular oxygen, phenol

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599 A Multigranular Linguistic ARAS Model in Group Decision Making

Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

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Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

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598 A New Smart Plug for Home Energy Management

Authors: G. E. Kiral, O. Elma, A. T. Ince, B. Vural, U. S. Selamogullari, M. Uzunoglu

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Energy is an indispensable resource to meet the needs of people. Depending on the needs of people, the correct and efficient use of electrical energy has became important nowadays. Besides the need for the electrical energy is also increasing with the rapidly developing technology and continuously changing living standards. Due to the depletion of energy sources and increased demand for electricity, efficient energy use is an important research topic. Recently, ideas like smart cities, smart buildings and smart homes have been widely used under smart grid concept. With smart grid infrastructure, it will be possible to monitor electrical demand of a residential customer and control each electricity generation center for more efficient energy flow. The smallest component of the smart grid can be considered as smart homes. Better utilization of the electrical grid can be achieved through the communication of the smart home with both other customers in the grid and appliances in the house itself since generation can effectively be scheduled by having more precise demand data. Smart Plugs are used for the communication with the household appliances in the house. Smart Plug is an intermediate control element, which can be mounted on the existing outlet, and thus can be used to monitor the energy consumption of the plugged device and also can provide on/off control energy remotely. This study proposes a Smart Plug for energy monitoring and energy management. Proposed design is composed of five subsystems: micro controller embedded system with communication system, metering circuitry, power supply and switching circuitry. The developed smart plug offers efficient use of electrical energy.

Keywords: energy efficiency, home energy management, smart home, smart plug

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597 Anisotropic Behavior of Sand Stabilized with Colloidal Silica

Authors: Eleni Maria Pavlopoulou, Vasiliki N. Georgiannou, Filippos C. Chortis

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The response of M31 sand stabilized with colloidal silica (CS) aqueous gel is investigated in the laboratory. CS is introduced in the water regime, forming a hydrosol. The low viscosity hydrosol thickens in a controllable manner to form a stable, non-toxic gel; the gel fills the pore space, retains the pore water, and supports the grain structure. The role of colloidal silica on subsequent sand behavior is examined with the aid of direct shear, triaxial, and normal compression tests. Under the examined loading modes, while the strength of the treated sand is enhanced, its stiffness may reduce, and its compressibility increase. However, in most geotechnical problems, the loading conditions are complex, involving changes in both stress magnitude and direction. Rotation of principal stresses (σ1, σ2, σ3) in varying amounts expressed as angle α, (from α=0° to 90°) in concurrence with increasing shear stress loading is commonly encountered in soil structures such as foundations, embankments, underwater slopes. To assess the influence of anisotropy on the response of sands before and after their stabilization, hollow cylinder tests were performed. The behavior of stabilized sand is compared with the characteristic sand behavior, i.e., a reduction in peak stress ratio associated with a softer stress-strain response with the increasing angle a. The influence of the magnitude of the intermediate principal stress (σ2) on the mechanical response of treated and untreated sand is also examined.

Keywords: anisotropy, colloidal silica, laboratory tests, sands, soil stabilization

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596 Green It-Outsourcing Assurance Model for It-Outsourcing Vendors

Authors: Siffat Ullah Khan, Rahmat Ullah Khan, Rafiq Ahmad Khan, Habibullah Khan

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Green IT or green computing has emerged as a fast growing business paradigm in recent years in order to develop energy-efficient Software and peripheral devices. With the constant evolution of technology and the world critical environmental status, all private and public information technology (IT) businesses are moving towards sustainability. We identified, through systematic literature review and questionnaire survey, 9 motivators, in total, faced by vendors in IT-Outsourcing relationship. Amongst these motivators 7 were ranked as critical motivators. We also identified 21, in total, practices for addressing these critical motivators. Based on these inputs we have developed Green IT-Outsourcing Assurance Model (GITAM) for IT-Outsourcing vendors. The model comprises four different levels. i.e. Initial, White, Green and Grey. Each level comprises different critical motivators and their relevant practices. We conclude that our model, GITAM, will assist IT-Outsourcing vendors in gauging their level in order to manage IT-Outsourcing activities in a green and sustainable fashion to assist the environment and to reduce the carbon emission. The model will assist vendors in improving their current level by suggesting various practices. The model will contribute to the body of knowledge in the field of Green IT.

Keywords: Green IT-outsourcing Assurance Model (GITAM), Systematic Literature Review, Empirical Study, Case Study

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595 The Analysis Fleet Operational Performance as an Indicator of Load and Haul Productivity

Authors: Linet Melisa Daubanes, Nhleko Monique Chiloane

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The shovel-truck system is the most prevalent material handling system used in surface mining operations. Material handling entails the loading and hauling of material from production areas to dumping areas. The material handling process has operational delays that have a negative impact on the productivity of the load and haul fleet. Factors that may contribute to operational delays include shovel-truck mismatch, haul routes, machine breakdowns, extreme weather conditions, etc. The aim of this paper is to investigate factors that contribute to operational delays affecting the productivity of the load and haul fleet at the mine. Productivity is the measure of the effectiveness of producing products from a given quantity of units, the ratio of output to inputs. Productivity can be improved by producing more outputs with the same or fewer units and/or introducing better working methods etc. Several key performance indicators (KPI) for the evaluation of productivity will be discussed in this study. These KPIs include but are not limited to hauling conditions, bucket fill factor, cycle time, and utilization. The research methodology of this study is a combination of on-site time studies and observations. Productivity can be optimized by managing the factors that affect the operational performance of the haulage fleet.

Keywords: cycle time, fleet performance, load and haul, surface mining

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594 Food and Agricultural Waste Management for Sustainable Agriculture

Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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593 Prediction of Distillation Curve and Reid Vapor Pressure of Dual-Alcohol Gasoline Blends Using Artificial Neural Network for the Determination of Fuel Performance

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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592 Hot Deformation Behavior and Recrystallization of Inconel 718 Superalloy under Double Cone Compression

Authors: Wang Jianguo, Ding Xiao, Liu Dong, Wang Haiping, Yang Yanhui, Hu Yang

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The hot deformation behavior of Inconel 718 alloy was studied by uniaxial compression tests under the deformation temperature of 940~1040℃ and strain rate of 0.001-10s⁻¹. The double cone compression (DCC) tests develop strains range from 30% to the 79% strain including all intermediate values of stains at different temperature (960~1040℃). DCC tests were simulated by finite element software which shown the strain and strain rates distribution. The result shows that the peak stress level of the alloy decreased with increasing deformation temperature and decreasing strain rate, which could be characterized by a Zener-Hollomon parameter in the hyperbolic-sine equation. The characterization method of hot processing window containing recrystallization volume fraction and average grain size was proposed for double cone compression test of uniform coarse grain, mixed crystal and uniform fine grain double conical specimen in hydraulic press and screw press. The results show that uniform microstructures can be obtained by low temperature with high deformation followed by high temperature with small deformation on the hydraulic press and low temperature, medium deformation, multi-pass on the screw press. The two methods were applied in industrial forgings process, and the forgings with uniform microstructure were obtained successfully.

Keywords: inconel 718 superalloy, hot processing windows, double cone compression, uniform microstructure

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591 Monitoring the Drying and Grinding Process during Production of Celitement through a NIR-Spectroscopy Based Approach

Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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590 Estimating Anthropometric Dimensions for Saudi Males Using Artificial Neural Networks

Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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589 Correlation between Speech Emotion Recognition Deep Learning Models and Noises

Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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588 Closed Loop Traffic Control System Using PLC

Authors: Chinmay Shah

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The project is all about development of a close loop traffic light control system using PLC (Programmable Logic Controller). This project is divided into two parts which are hardware and software. The hardware part for this project is a model of four way junction of a traffic light. Three indicator lamps (Red, Yellow and Green) are installed at each lane for represents as traffic light signal. This traffic control model is a replica of actuated traffic control. Actuated traffic control system is a close loop traffic control system which controls the timing of the indicator lamps depending on the fluidity of traffic for a particular lane. To make it autonomous, in each lane three IR sensors are placed which helps to sense the percentage of traffic present on any particular lane. The IR Sensors and Indicator lamps are connected to LG PLC XGB series. The PLC controls every signal which is coming from the inputs (IR Sensors) to software and display to the outputs (Indicator lamps). Default timing for the indicator lamps is 30 seconds for each lane. But depending on the percentage of traffic present, if the traffic is nearly 30-35%, green lamp will be on for 10 seconds, for 65-70% traffic it will be 20 seconds, for full 100% traffic it will be on for full 30 seconds. The software part that operates with LG PLC is “XG 5000” Programmer. Using this software, the ladder logic diagram is programmed to control the traffic light base on the flow chart. At the end of this project, the traffic light system is actuated successfully by PLC.

Keywords: close loop, IR sensor, PLC, light control system

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587 Modeling and Estimating Reserve of the Ali Javad Porphyry Copper-Gold Deposit, East Azerbaijan, Iran

Authors: Behzad Hajalilou, Nasim Hajalilou, Saeid Ansari

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The study area is located in East Azerbaijan province, north of Ahar city, and 1/100000 geological map of Varzgan. This region is located in the middle of Iran zone. Ali Javad Porphyry copper-gold ore deposit has been created in a magmatic complex containing intrusive masses, combining Granodiorite and quartz Monzonite that penetrates into the Eocene volcanic aggregate. The most important mineralization includes primary oxides minerals (magnetite), sulfide (pyrite, chalcopyrite, Molybdenite, Bornite, Chalcocite, Covollite), secondary oxide or hydroxide minerals (hematite, goethite, limonite), and carbonate (malachite and Azurite). The mineralization forms into the vein-veinlets and scattered system. The alterations observed in the region include intermediate Argillic, advanced Argillic, Phyllic, silica, Propylitic, chlorite and Potassic. The 3D model of mineralization of the Alijavad is provided by Data DATAMINE software and based on the study of 700 polished sections of 32 drilled boreholes in the region. This model is completely compatible with the model provided by Lowell and Gilbert for the mineralization of porphyry copper deposits of quartz Monzonite type. The estimated cumulative residual value of copper for Ali Javad deposit is 81.5 million tons with 0.75 percent of copper, and for gold is 8.37 million tons with 1.8 ppm.

Keywords: porphyry copper, mineralization, Ali Javad, modeling, reserve estimation

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586 Soil Organic Carbon and Nutrients in Smallholding Land Uses in Southern Ethiopia

Authors: Mekdes Lulu

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This study assessed the soil organic C (SOC) and soil nutrients in smallholding home garden, woodlot, grazing land, and cropland at two soil depths and two sites in Wolaita Zone, southern Ethiopia. The results showed that soil properties were significantly influenced by land use. The home garden had significantly higher (p < 0.05) SOC and soil nutrients when compared to the cropland. When the home garden was compared to the woodlot and grazing land uses, it had significantly higher (p < 0.05) values except in SOC, total N (TN), cation exchange capacity (CEC), and exchangeable Ca. Cropland, in comparison with grazing land and woodlot, had a non-significant difference except TN. The SOC stock (0–40 cm) in the home garden, woodlot, grazing land and cropland was 79.5, 68.0, 65.0, and 58.1 Mg ha–1, respectively. Home garden significantly differed (p <0.05) in SOC only from cropland, and this was attributed not only to the relatively higher organic input in the home garden but also to the little organic matter input and frequently tillage of the cropland. The similar SOC among the home garden, woodlot and grazing lands may imply that the balance between inputs and outputs could be nearly similar for the land uses. Soil TN and CEC had a nearly similar pattern of difference as in SOC among the land uses because of their close relationship with SOC. In general, the land use influence on soil nutrients can be in the order: home garden > wood land » grazing land » cropland, with home garden showing the least difference from the woodlot and the greatest from the cropland. In the agroecosystem, in general, the influence of smallholding home garden on SOC and soil nutrient was marginally different from Eucalyptus woodlot and grazing lands but evidently different from cropland.

Keywords: cropland, grazing land, home garden, soc stock, soil nutrients, woodlot

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585 Turkish University Level EFL Learners’ Collocational Knowledge at Receptive and Productive Levels

Authors: Nazife Duygu Bagci

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Collocations are an important part of vocabulary knowledge, and it is a subject that has recently attracted attention, while still in need of more research. The aim of this study is to answer three research questions related to the collocational knowledge of Turkish university level EFL learners at different proficiency levels of English. The first research question aims to compare the pre-intermediate (PIN) and the advanced (ADV) level learners’ collocational knowledge at receptive and productive levels. The second one is to analyze the performance of the PIN and the ADV students in two main collocation categories; lexical and grammatical. Lastly, the performance of both groups are focused on to find the collocation type (among verb-noun, adjective- noun, adjective-preposition, noun-preposition collocation types) they show the best performance in. Two offline tests were used to answer these questions. The results show that there is a significant difference between the PIN and the ADV groups at both receptive and productive levels. It can be concluded that proficiency is an important criterion in collocational knowledge, and learners do not necessarily know the collocates of the vocabulary items that they know. Although there is no significant difference between the PIN group’s performance in lexical and grammatical collocations, the ADV group showed a better performance in lexical collocations. Lastly, the PIN group at receptive and the ADV group at both receptive and productive levels showed the best performance in verb-noun collocations, which is in line with the previous research focusing on different collocation types.

Keywords: collocational knowledge, EFL, language proficiency, testing

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584 Design of Fuzzy Logic Based Global Power System Stabilizer for Dynamic Stability Enhancement in Multi-Machine Power System

Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

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This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

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583 Spatiotemporal Analysis of Visual Evoked Responses Using Dense EEG

Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

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A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: brain activity, categorization, dense EEG, evoked responses, spatio-temporal analysis, SVM, time perception

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582 A Comparison of Energy Calculations for a Single-Family Detached Home with Two Energy Simulation Methods

Authors: Amir Sattari

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For newly produced houses and energy renovations, an energy calculation needs to be conducted. This is done to verify whether the energy consumption criteria of the house -to reach the energy targets by 2020 and 2050- are in-line with the norms. The main purpose of this study is to confirm whether easy to use energy calculation software or hand calculations used by small companies or individuals give logical results compared to advanced energy simulation program used by researchers or bigger companies. There are different methods for calculating energy consumption. In this paper, two energy calculation programs are used and the relation of energy consumption with solar radiation is compared. A hand calculation is also done to validate whether the hand calculations are still reasonable. The two computer programs which have been used are TMF Energi (the easy energy calculation variant used by small companies or individuals) and IDA ICE - Indoor Climate and Energy (the advanced energy simulation program used by researchers or larger companies). The calculations are done for a standard house from the Swedish house supplier Fiskarhedenvillan. The method is based on having the same conditions and inputs in the different calculation forms so that the results can be compared and verified. The house has been faced differently to see how the orientation affects energy consumption in different methods. The results for the simulations are close to each other and the hand calculation differs from the computer programs by only 5%. Even if solar factors differ due to the orientation of the house, energy calculation results from different computer programs and even hand calculation methods are in line with each other.

Keywords: energy calculation, energy consumption, energy simulation, IDA ICE, TMF energi

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581 A Verification Intellectual Property for Multi-Flow Rate Control on Any Single Flow Bus Functional Model

Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

Abstract:

In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

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580 Decision Framework for Cross-Border Railway Infrastructure Projects

Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in decision process and –many times- the investment and business risks are high. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analyzed. Adopting the on system of system methodological approach, the decision making framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey and Bulgaria.

Keywords: decision making, system of system, cross-border, infrastructure project

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579 Major Depressive Disorder: Diagnosis based on Electroencephalogram Analysis

Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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578 Characterization and Quantification of Relatives Amounts of Phosphorylated Glucosyl Residues in C6 and C3 Position in Banana Starch Granules by 31P-NMR

Authors: Renata Shitakubo, Hanyu Yangcheng, Jay-lin Jane, Fernanda Peroni Okita, Beatriz Cordenunsi

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In the degradation transitory starch model, the enzymatic activity of glucan/water dikinase (GWD) and phosphoglucan/water dikinase (PWD) are essential for the granule degradation. GWD and PWD phosphorylate glucose molecules in the positions C6 and C3, respectively, in the amylopectin chains. This action is essential to allow that β-amylase degrade starch granules without previous action of α-amylase. During banana starch degradation, as part of banana ripening, both α- and β-amylases activities and proteins were already detected and, it is also known that there is a GWD and PWD protein bounded to the starch granule. Therefore, the aim of this study was to quantify both Gluc-6P and Gluc-3P in order to estimate the importance of the GWD-PWD-β-amylase pathway in banana starch degradation. Starch granules were isolated as described by Peroni-Okita et al (Carbohydrate Polymers, 81:291-299, 2010), from banana fruit at different stages of ripening, green (20.7%), intermediate (18.2%) and ripe (6.2%). Total phosphorus content was determinate following the Smith and Caruso method (1964). Gluc-6P and Gluc-3P quantifications were performed as described by Lim et al (Cereal Chemistry, 71(5):488-493, 1994). Total phosphorous content in green banana starch is found as 0.009%, intermediary banana starch 0.006% and ripe banana starch 0.004%, both by the colorimetric method and 31P-NMR. The NMR analysis showed the phosphorus content in C6 and C3. The results by NMR indicate that the amylopectin is phosphorylate by GWD and PWD before the bananas become ripen. Since both the total content of phosphorus and phosphorylated glucose molecules at positions C3 and C6 decrease with the starch degradation, it can be concluded that this phosphorylation occurs only in the surface of the starch granule and before the fruit be harvested.

Keywords: starch, GWD, PWD, 31P-NMR

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577 Contribution of Urban Agriculture to the Livelihood of Urban Dwellers in Ilorin West Local Government Area of Kwara State, Nigeria

Authors: Okunola Solomon Olufemi

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The study focused on the contribution of urban agriculture to the livelihood of 107 respondents in Kwara State of Nigeria. The study employed structured questionnaire to collect relevant data for the study while descriptive statistics such as frequency distribution and percentage were employed to analyses the objectives. Most respondents (82.9%), were one time or the other in a married state and they had formal education (80.4%) while many of the lot (58.9%) had superior education ranging from OND to Ph.D level. These farmers were either retired government workers or those trying to argument their family income or trying to be food sufficient. Most of the respondents (77.4%) had a farm size of less than or equal to 3 hectares showing that most the urban farmers were smallholders which might be as a result of stiff completion for land resource. Most of the respondents had a relatively large family size of 6 and above members. Most respondents used family labor (59.8%). Respondents in the study area also made use of the cooperatives and daily contributions for loanable funds, while few respondents utilized the formal sector. .Urban agriculture accounted for 84.4% of the Livelihood outcomes of the respondents. While non-farming activities contributed 17.6%.Most of the respondents (31.8%) participated in non-farming activities to generate extra income while their major constraints were shortage of land both in term of access and tenure (34.1%), limited access to resource and agricultural inputs (29.3%), and prohibitive urban policies and regulation (23.2%).

Keywords: poverty throes, urban agriculture, rigors of farming, non-farming, married state

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576 Experimental Validation of a Mathematical Model for Sizing End-of-Production-Line Test Benches for Electric Motors of Electric Vehicle

Authors: Emiliano Lustrissimi, Bonifacio Bianco, Sebastiano Caravaggi, Antonio Rosato

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A mathematical framework has been designed to enhance the configuration of an end-of-production-line (EOL) test bench. This system can be used to assess the performance of electric motors or axles intended for electric vehicles. The model has been developed to predict the behaviour of EOL test benches and electric motors/axles under various boundary conditions, eliminating the need for extensive physical testing and reducing the corresponding power consumption. The suggested model is versatile, capable of being utilized across various types of electric motors or axles, and adaptable to accommodate varying power ratings of electric motors or axles. The maximum performance to be guaranteed by the EMs according to the car maker's specifications are taken as inputs in the model. Then, the required performance of each main EOL test bench component is calculated, and the corresponding systems available on the market are selected based on manufacturers’ catalogues. In this study, an EOL test bench has been designed according to the proposed model outputs for testing a low-power (about 22 kW) electric axle. The performance of the designed EOL test bench has been measured and used to validate the proposed model and assess both the consistency of the constraints as well as the accuracy of predictions in terms of electric demands. The comparison between experimental and predicted data exhibited a reasonable agreement, allowing to demonstrate that, despite some discrepancies, the model gives an accurate representation of the EOL test benches' performance.

Keywords: electric motors, electric vehicles, end-of-production-line test bench, mathematical model, field tests

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575 Development of LSM/YSZ Composite Anode Materials for Solid Oxide Electrolysis Cells

Authors: Christian C. Vaso, Rinlee Butch M. Cervera

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Solid oxide electrolysis cell (SOEC) is a promising technology for hydrogen production that will contribute to the sustainable energy of the future. An important component of this SOEC is the anode material and one of the promising anode material for such application is the Sr-doped LaMnO3 (LSM) and Yttrium-stabilized ZrO2 (YSZ) composite material. In this study, LSM/YSZ with different weight percent compositions of LSM and YSZ were synthesized using solid-state reaction method. The obtained samples, 60LSM/40YSZ, 50LSM/50YSZ, and 40LSM/60YSZ, were fully characterized for its microstructure using X-ray diffraction, FTIR, and SEM/EDS. EDS analysis confirmed the elemental composition and distribution of the synthesized samples. Surface morphology of the sample using SEM exhibited a well sintered and densified samples and revealed a beveled cube-like LSM morphology while the YSZ phase appeared to have a sphere-like microstructure. Density measurements using Archimedes principle showed relative densities greater than 90%. In addition, AC impedance measurement of the synthesized samples have been investigated at intermediate temperature range (400-700 °C) in an inert and oxygen gas flow environment. At pure states, LSM exhibited a high electronic conductivity while YSZ demonstrated an ionic conductivity of 3.25 x 10-4 S/cm at 700 °C under Oxygen gas environment with calculated activation energy of 0.85eV. The composite samples were also studied and revealed that as the YSZ content of the composite electrode increases, the total conductivity decreases.

Keywords: ceramic composites, fuel cells, strontium lanthanum manganite, yttria partially-stabilized zirconia

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574 Mapping of Solar Radiation Anomalies Based on Climate Change

Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Francisco Pereira, Elton Rossini

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The use of alternative energy sources to meet energy demand reduces environmental damage. To diversify an energy matrix and to minimize global warming, a solar energy is gaining space, being an important source of renewable energy, and its potential depends on the climatic conditions of the region. Brazil presents a great solar potential for a generation of electric energy, so the knowledge of solar radiation and its characteristics are fundamental for the study of energy use. Due to the above reasons, this article aims to verify the climatic variability corresponding to the variations in solar radiation anomalies, in the face of climate change scenarios. The data used in this research are part of the Intercomparison of Interconnected Models, Phase 5 (CMIP5), which contributed to the preparation of the fifth IPCC-AR5 report. The solar radiation data were extracted from The Australian Community Climate and Earth System Simulator (ACCESS) model using the RCP 4.5 and RCP 8.5 scenarios that represent an intermediate structure and a pessimistic framework, the latter being the most worrisome in all cases. In order to allow the use of solar radiation as a source of energy in a given location and/or region, it is important, first, to determine its availability, thus justifying the importance of the study. The results pointed out, for the 75-year period (2026-2100), based on a pessimistic scenario, indicate a drop in solar radiation of the approximately 12% in the eastern region of Rio Grande do Sul. Factors that influence the pessimistic prospects of this scenario should be better observed by the responsible authorities, since they can affect the possibility to produce electricity from solar radiation.

Keywords: climate change, energy, IPCC, solar radiation

Procedia PDF Downloads 192