Search results for: low input farming

Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

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ALOHA code was used to calculate the concentration under the CO₂ storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan

Procedia PDF Downloads 198

Authors: Garba K. Adamu

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This research was carried out in the catchments of five major rivers in Kano State. The catchments have considerable Fadama lands; these include: River Gari which is located in the northwestern part of Kano state, Rivers Challawa and Watari from southernparts of Kano and Katsina states. River Tomas from the northern parts of Kano state, River Jakara which has its source from the Old Kano city, part of Central Business Districts and Industrial Estates. The study was carried out with aim of assessing the fertility status of the Fadama soils found in these major river catchments. A transect was designed to collect samples along farming villages in the five river channels for the study. The findings indicate that the soils are predominantly sandy. The bulk density values vary significantly and range from 0.98mg/m to 1.36mg/m. The pH values for all the sites studied ranges from slightly acidic to slightly alkaline. The OC ranged from low to very low in the sites. The EC ranges from 66.3µs/cm to 198µs/cm for all the sites. The mean CEC ranges from 3.864 cm/kg to 10.114 Cmol/kg. The range of values for the SAR was 0.0106 to 0.069. Nitrogen ranges from0.03 to 0.1230ppm. The range of P value fell between 9.9 to 41.1mg/kg.Ca values ranges from 1.0170 to 14.9850 and K values ranges from 4.6550 – 64.40.Mg values range from 0.1380 to 1.8580 and Zn values range from 1.0170 to 14.9850. The Fe values ranged from 15.6500mg/kg to 69.8000mg/kg. The B values range from0.2060 to13.5450. Generally, the values obtained shows a low to medium fertility levels for all the parameters tested and the areas will require the in cooperation of organic manure and chemical fertilizers to improve soil structure and supplements other macro nutrients.

Keywords: assessment, Fadama soils, fertility status, river catchment

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Authors: Balwinder Singh, Veerpaul Kaur Mann

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A composite material is formed by the combination of two or more phases or materials. Natural minerals-derived Basalt fiber is a kind of fiber being introduced in the polymer composite industry due to its good mechanical properties similar to synthetic fibers and low cost, environment friendly. Also, there is a rising trend towards the use of industrial wastes as fillers in polymer composites with the aim of improving the properties of the composites. The mechanical properties of the fiber-reinforced polymer composites are influenced by various factors like fiber length, fiber weight %, filler weight %, filler size, etc. Thus, a detailed study has been done on the characterization of short-chopped Basalt fiber-reinforced polymer matrix composites using fly ash as filler. Taguchi’s L9 orthogonal array has been used to develop the composites by considering fiber length (6, 9 and 12 mm), fiber weight % (25, 30 and 35 %) and filler weight % (0, 5 and 10%) as input parameters with their respective levels and a thorough analysis on the mechanical characteristics (tensile strength and impact strength) has been done using ANOVA analysis with the help of MINITAB14 software. The investigation revealed that fiber weight is the most significant parameter affecting tensile strength, followed by fiber length and fiber weight %, respectively, while impact characterization showed that fiber length is the most significant factor, followed by fly ash weight, respectively. Introduction of fly ash proved to be beneficial in both the characterization with enhanced values upto 5% fly ash weight. The present study on the natural fibres reinforced epoxy composites using fly ash as filler material to study the effect of input parameters on the tensile strength in order to maximize tensile strength of the composites. Fabrication of composites based on Taguchi L9 orthogonal array design of experiments by using three factors fibre type, fibre weight % and fly ash % with three levels of each factor. The Optimization of composition of natural fibre reinforces composites using ANOVA for obtaining maximum tensile strength on fabricated composites revealed that the natural fibres along with fly ash can be successfully used with epoxy resin to prepare polymer matrix composites with good mechanical properties. Paddy- Paddy fibre gives high elasticity to the fibre composite due to presence of approximately hexagonal structure of cellulose present in paddy fibre. Coir- Coir fibre gives less tensile strength than paddy fibre as Coir fibre is brittle in nature when it pulls breakage occurs showing less tensile strength. Banana- Banana fibre has the least tensile strength in comparison to the paddy & coir fibre due to less cellulose content. Higher fibre weight leads to reduction in tensile strength due to increased nuclei of air pockets. Increasing fly ash content reduces tensile strength due to nonbonding of fly ash particles with natural fibre. Fly ash is also not very strong as compared to the epoxy resin leading to reduction in tensile strength.

Keywords: tensile strength and epoxy resin. basalt Fiber, taguchi, polymer matrix, natural fiber

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Authors: D. Kakulia, L. Shoshiashvili, G. Sapharishvili

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The results of the study are related to the direction of plastic mine detection research using electromagnetic induction, the development of appropriate equipment, and the evaluation of expected results. Electromagnetic induction sensing is effectively used in the detection of metal objects in the soil and in the discrimination of unexploded ordnances. Metal objects interact well with a low-frequency alternating magnetic field. Their electromagnetic response can be detected at the low-frequency range even when they are placed in the ground. Detection of plastic things such as plastic mines by electromagnetic induction is associated with difficulties. The interaction of non-conducting bodies or low-conductive objects with a low-frequency alternating magnetic field is very weak. At the high-frequency range where already wave processes take place, the interaction increases. Interactions with other distant objects also increase. A complex interference picture is formed, and extraction of useful information also meets difficulties. Sensing by electromagnetic induction at the intermediate MHz frequency range is the subject of research. The concept of detecting plastic mines in this range can be based on the study of the electromagnetic response of non-conductive cavity in a low-conductivity environment or the detection of small metal components in plastic mines, taking into account constructive features. The detector node based on the amplitude and phase detector 'Analog Devices ad8302' has been developed for experimental studies. The node has two inputs. At one of the inputs, the node receives a sinusoidal signal from the generator, to which a transmitting coil is also connected. The receiver coil is attached to the second input of the node. The additional circuit provides an option to amplify the signal output from the receiver coil by 20 dB. The node has two outputs. The voltages obtained at the output reflect the ratio of the amplitudes and the phase difference of the input harmonic signals. Experimental measurements were performed in different positions of the transmitter and receiver coils at the frequency range 1-20 MHz. Arbitrary/Function Generator Tektronix AFG3052C and the eight-channel high-resolution oscilloscope PICOSCOPE 4824 were used in the experiments. Experimental measurements were also performed with a low-conductive test object. The results of the measurements and comparative analysis show the capabilities of the simple detector node and the prospects for its further development in this direction. The results of the experimental measurements are compared and analyzed with the results of appropriate computer modeling based on the method of auxiliary sources (MAS). The experimental measurements are driven using the MATLAB environment. Acknowledgment -This work was supported by Shota Rustaveli National Science Foundation (SRNSF) (Grant number: NFR 17_523).

Keywords: EM induction sensing, detector, plastic mines, remote sensing

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Authors: Sun Lim, Kyun Jung

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In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

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Authors: Yongqin Zhang, John Lett

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Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.

Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements

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Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

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An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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Authors: Amal Ezzidani, Abdelghani Ben Tahar, Mohamed Hanini

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A sequence of finite tandem queue is considered for this study. Each one has a single server, which operates under the egalitarian processor sharing discipline. External customers arrive at each queue according to a renewal input process and having a general service times distribution. Upon completing service, customers leave the current queue and enter to the next. Under mild assumptions, including critical data, we prove the existence and the uniqueness of the fluid solution. For asymptotic behavior, we provide necessary and sufficient conditions for the invariant state and the convergence to this invariant state. In the end, we establish the convergence of a correctly normalized state process to a fluid limit characterized by a system of algebraic and integral equations.

Keywords: fluid limit, fluid model, measure valued process, processor sharing, tandem queue

Procedia PDF Downloads 323

Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: C. Patrascioiu

Abstract:

The paper describes the modeling and simulation of the heat pumps domain processes. The main objective of the study is the use of the heat pump in propene–propane distillation processes. The modeling and simulation instrument is the Unisim^® Design simulator. The paper is structured in three parts: An overview of the compressing gases, the modeling and simulation of the freezing systems, and the modeling and simulation of the heat pumps. For each of these systems, there are presented the Unisim^® Design simulation diagrams, the input–output system structure and the numerical results. Future studies will consider modeling and simulation of the propene–propane distillation process with heat pump.

Keywords: distillation, heat pump, simulation, unisim design

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Authors: Tejinder Singh

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This paper describes a new more efficient Hydraulic System which uses lesser work to produce more output. Conventional Hydraulic System like Hydraulic Lifts and Rams use lots of water to be pumped to produce output. TejHydroLift will do the equal amount of force with lesser input of water. The paper will show that force applied can be increased manifold without requiring to move smaller force by more distance which used to be required in Conventional Hydraulic Lifts. The paper describes one of the configurations of TejHydroLift System called “Slim Antenna TejHydroLift Configuration”. The TejHydroLift uses lesser water and hence demands lesser work to be performed to move the same load.

Keywords: alternate, hydraulic system, efficient, TejHydroLift

Procedia PDF Downloads 260

Authors: Aman Sharma, Sonali Sengupta

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The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

Procedia PDF Downloads 182

Authors: Yogita M. Ahire, Nedal M. Mohammed, Ahmed A. Hamoud

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Scientific computation outsourcing is gaining popularity because it allows customers with limited computing resources and storage devices to outsource complex computation workloads to more powerful service providers. However, it raises some security and privacy concerns and challenges, such as customer input and output privacy, as well as cloud cheating behaviors. This study was motivated by these concerns and focused on privacy-preserving Two-Point Boundary Value Problems (BVP) as a common and realistic instance for verifiable safe multiparty computing. We'll look at the safe and verifiable schema with correctness guarantees by utilizing standard multiparty approaches to compute the result of a computation and then solely using verifiable ways to check that the result was right.

Keywords: verifiable computing, cloud computing, secure and privacy BVP, secure computation outsourcing

Procedia PDF Downloads 97

Authors: Abdelali Laamari, Morad Faiz, Ali Amamou And Mohamed Elkoudrim

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This research seeks to develop multi-disciplinary, multi-criteria, and multi-institutional approaches that consider the three main pillars of sustainability (environmental, economic, and social aspects) at the level of decision making regarding the adoption of improved technologies in the targeted case study region in Morocco. The study is aimed at combining sound R&I with extensive skills in applied research and policy evaluation. The intention is to provide new simple, and transferable tools and agricultural practices that will enable the uptake of sustainability and the resiliency of agro-ecosystems. The study will understand the state-of-the-art of the impact of climate change and identify the core bottlenecks and climate change’s impact on crop and livestock productivity of the targeted value chains in Morocco. Studies conducted during 2021-2022 showed that most of the farmers are using since 2010 the direct seeding and the system can be improved by adopting new fertilizer and varieties of wheat. The alley-cropping technology is based on Atriplex plant or olive trees. The introduction of new varieties of oat and quinoa has improved biomass and grain production in a dry season. The research is targeting other issues, such as social enterprises, to diversify women’s income resources and create new job opportunities through diversification of end uses of durum wheat and barley grains. Women’s local knowledge is rich on the different end uses of durum and barley grains that can improve their added value if they are transformed as couscous, pasta, or any other products.

Keywords: agriculture, climate, production system, integration

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Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

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Authors: Vinay Patil, Swapnil Kekade, Ashish Supare, Vinayak Pawar, Shital Jadhav, Rajkumar Singh

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In recent days, bainitic steel is used in automobile and non-automobile sectors due to its high strength. Bainitic steel is difficult to machine because of its high hardness, hence in this paper machinability of bainitic steel is studied by using Taguchi design of experiments (DOE) approach. Convectional turning experiments were done by using L16 orthogonal array for three input parameters viz. cutting speed, depth of cut and feed. The Taguchi method is applied to study the performance characteristics of machining parameters with surface roughness (Ra), cutting force and tool wear rate. By using Taguchi analysis, optimized process parameters for best surface finish and minimum cutting forces were analyzed.

Keywords: conventional turning, Taguchi method, S/N ratio, bainitic steel machining

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

Procedia PDF Downloads 513

Authors: Zhao Weijie, Lin Xinjian, Liu Xiaojuan, Li Lihua

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The Howland current pump is widely used in bio-impedance measurement. Much attention has been focused on the output impedance of the Howland circuit. Here we focus on the maximum load of the Howland source and discuss the relationship between the circuit parameters at maximum load. We conclude that the signal input terminal of the feedback resistor should be as large as possible, but that the current-limiting resistor should be smaller. The op-amp saturation voltage should also be high. The bandwidth of the circuit is proportional to the bandwidth of the op-amp. The Howland current pump was simulated using multisim12. When the AD8066AR was selected as the op-amp, the maximum load was 11.5 kΩ, and the Howland current pump had a stable output ipp to 2mAp up to 200 kHz. However, with an OPA847 op-amp and a load of 6.3 kΩ, the output current was also stable, and the frequency was as high as 3 MHz.

Keywords: bio-impedance, improved Howland current pump, load characteristics, bioengineering

Procedia PDF Downloads 513

Authors: J. R. Wang, W. Y. Li, H. T. Lin, J. H. Yang, C. Shih, S. W. Chen

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Fuel rod analysis program transient (FRAPTRAN) code was used to study the fuel rod performance during a postulated large break loss of coolant accident (LBLOCA) in Maanshan nuclear power plant (NPP). Previous transient results from thermal hydraulic code, TRACE, with the same LBLOCA scenario, were used as input boundary conditions for FRAPTRAN. The simulation results showed that the peak cladding temperatures and the fuel center line temperatures were all below the 10CFR50.46 LOCA criteria. In addition, the maximum hoop stress was 18 MPa and the oxide thickness was 0.003 mm for the present simulation cases, which are all within the safety operation ranges. The present study confirms that this analysis method, the FRAPTRAN code combined with TRACE, is an appropriate approach to predict the fuel integrity under LBLOCA with operational ECCS.

Keywords: FRAPTRAN, TRACE, LOCA, PWR

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Authors: Jonathan N. Nayga, Emelita B. Valdez, Mila R. Andres, Beulah B. Estrada, Emelina A. Lopez, Rogelio B. Tamayo, Aubrey Joy M. Balbin

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Goat production is one of the activities included in integrated farming in the Philippines. Goats are raised for its meat and regardless of breed the animal is slaughtered for this purpose. In order to document the carcass yield of different goats slaughtered, five (5) different breeds of goats to include Purebred Boer and Anglo-nubian, Crossbred Boer and Anglo-nubian and Philippine Native goat were used in the study. Data on slaughter parameters, carcass characteristics, and sensory evaluation were gathered and analyzed using Complete Random Design (CRD) at 5% level of significance and the results of carcass conformation were assessed descriptively. Results showed that slaughter data such as slaughter/live weight, hot and chilled carcass weights, dressing percentage and percentage drip loss were significantly different (P>0.05) among breeds. On carcass and meat characteristics, pure breed and upgraded Boer were found to be moderately muscular while Native goat was rated as thin muscular. The color of the carcass also revealed that Purebred and crossbred Boer were described dark red, while Native goat was noted to be slightly pale. On sensory evaluation, the results indicated that there was no significant difference (P>0.05) among breeds evaluated. It is therefore concluded that purebred goat has heavier carcass, while both purebred Boer and upgrade are rated slightly muscular. It is further confirms that regardless of breed, goat will have the same sensory characteristics. Thus, it is recommended to slaughter heavier goats to obtain more carcasses with better conformation and quality.

Keywords: carcass quality, goat, sensory evaluation, slaughter

Procedia PDF Downloads 349

Authors: Seyed Sadegh Naseralavi

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This paper presents a Kernel parallelization equation for damage identification in structures under unknown periodic excitations. Herein, the dynamic differential equation of the motion of structure is viewed as a mapping from displacements to external forces. Utilizing this viewpoint, a new method for damage detection in structures under periodic loads is presented. The developed method requires only two periods of load. The method detects the damages without finding the input loads. The method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering the concept, kernel parallelization equation (KPE) is derived for damage detection under unknown periodic loads. The method is verified for a case study under periodic loads.

Keywords: Kernel, unknown periodic load, damage detection, Kernel parallelization equation

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Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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Authors: Khuram Nawaz Sadozai, Sonia

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The agriculture sector is deemed more vulnerable to climate change as its variation can directly affect the crop’s productivity, but farmers’ adaptation strategies play a vital role in climate change-agriculture relationship. Therefore, this research has been undertaken to assess the Climate Change impact on wheat productivity and farmers’ adaptability strategies in Khyber Pakhtunkhwa province, Pakistan. The panel dataset was analyzed to gauge the impact of changing climate variables (i.e., temperature, rainfall, and humidity) on wheat productivity from 1985 to 2015. Amid the study period, the fixed effect estimates confirmed an inverse relationship of temperature and rainfall on the wheat yield. The impact of temperature is observed to be detrimental as compared to the rainfall, causing 0.07 units reduction in the production of wheat with 1C upsurge in temperature. On the flip side, humidity revealed a positive association with the wheat productivity by confirming that high humidity could be beneficial to the production of the crop over time. Thus, this study ensures significant nexus between agricultural production and climatic parameters. However, the farming community in the underlying study area has limited knowledge about the adaptation strategies to lessen the detrimental impact of changing climate on crop yield. It is recommended that farmers should be well equipped with training and advanced agricultural management practices under the realm of climate change. Moreover, innovative technologies pertinent to the agriculture system should be encouraged to handle the challenges arising due to variations in climate factors.

Keywords: climate change, fixed effect model, panel data, wheat productivity

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Authors: Zeineb Seboui, Samar Dabbabi

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In this paper, we study the performance of Cu₂ZnSnS₄ (CZTS) based solar cell. In our knowledge, it is for the first time that the FTO/ZnO:Co/CZTS structure is simulated using the SILVACO-Atlas 2D simulation. Cu₂ZnSnS₄ (CZTS), ZnO:Co and FTO (SnO₂:F) layers have been deposited on glass substrates by the spray pyrolysis technique. The extracted physical properties, such as thickness and optical parameters of CZTS layer, are considered to create a new input data of CZTS based solar cell. The optimization of CZTS electron affinity and thickness is performed to have the best FTO/ZnO: Co/CZTS efficiency. The use of CZTS absorber layer with 3.99 eV electron affinity and 3.2 µm in thickness leads to the higher efficiency of 16.86 %, which is very important in the development of new technologies and new solar cell devices.

Keywords: CZTS solar cell, characterization, electron affinity, thickness, SILVACO-atlas 2D simulation

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: V. H. Nguyen, A. Castalone, C. Jamieson, M. Gummert

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Rice straw is an abundant biomass resource in Asian countries that can be used for bioenergy. In continuously flooded rice fields, it can be removed without reducing the levels of soil organic matter. One suitable bioenergy technology is anaerobic digestion (AD), but it needs to be further verified using rice straw as a feedstock. For this study, a batch AD system was developed using rice straw and cow dung. It is low cost, farm scale, with the batch capacity ranging from 5 kg to 200 kg of straw mixed with 10% of cow dung. The net energy balance obtained was from 3000 to 4000 MJ per ton of straw input at 15-18% moisture content. Net output energy obtained from biogas and digestate ranged from 4000 to 5000 MJ per ton of straw. This indicates AD as a potential solution for converting rice straw from a waste to a clean fuel, reducing the environmental footprint caused by current disposal practices.

Keywords: rice straw, anaerobic digestion, biogas, bioenergy

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Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang

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In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz^2/3 and 72.11 dB·Hz^2/3 under different RF powers.

Keywords: microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent

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Authors: Nabil Majd Alawi, Gia Hung Pham, Ahmed Barifcani

Abstract:

Dry reforming of methane that converts two greenhouses gases (CH₄ and CO₂) to synthesis gas (a mixture of H₂ and CO) was studied in a commercial bench scale microwave (MW) plasma reactor system at atmospheric pressure. The CO₂, CH₄ and N₂ conversions; H₂, CO selectivities and yields, and syngas ratio (H₂/CO) were investigated in a wide range of total feed flow rate (0.45 – 2.1 L/min), MW power (700 – 1200 watt) and CO₂/CH₄ molar ratio (2 – 5). At the feed flow rates of CH₄, CO₂ and N₂ of 0.2, 0.4 and 1.5 L/min respectively, and the MWs input power of 700 W, the highest conversions of CH₄ and CO₂, selectivity and yield of H₂, CO and H₂/CO ratio of 79.35%, 44.82%, 50.12, 58.42, 39.77%, 32.89%, and 0.86, respectively, were achieved. The results of this work show that the product ratio increases slightly with the increasing total feed flow rate, but it decreases significantly with the increasing MW power and feeds CO₂/CH₄ ratio.

Keywords: dry reforming of methane, microwave discharge, plasma technology, synthesis gas production

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

Abstract:

This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

Procedia PDF Downloads 177