Search results for: low input farming

Authors: Halima Adel Halim Shnishah, David Mulvaney

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Applying traditional symmetric cryptography algorithms while computing encryption and decryption provides immunity to secret keys against different attacks. One of the popular techniques generating automated secret keys is evolutionary computing by using Eureqa API tool, which got attention in 2013. In this paper, we are generating automated secret keys for image encryption and decryption using Eureqa API (tool which is used in evolutionary computing technique). Eureqa API models pseudo-random input data obtained from a suitable source to generate secret keys. The validation of generated secret keys is investigated by performing various statistical tests (histogram, chi-square, correlation of two adjacent pixels, correlation between original and encrypted images, entropy and key sensitivity). Experimental results obtained from methods including histogram analysis, correlation coefficient, entropy and key sensitivity, show that the proposed image encryption algorithms are secure and reliable, with the potential to be adapted for secure image communication applications.

Keywords: image encryption algorithms, Eureqa, statistical measurements, automated key generation

Procedia PDF Downloads 483

Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Sireesha Tamada, Debraj Bhattacharjee, Pranab K. Dan, Prabha Bhola

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The most important component in an automotive transmission system is the gearbox which controls the speed of the vehicle. In an automatic transmission, the right positioning of actuators ensures efficient transmission mechanism embodiment, wherein the challenge lies in formulating the number of actuators associated with modelling a gearbox. Data with respect to actuation and gear shifting sequence has been retrieved from the available literature, including patent documents, and has been used in this proposed heuristics based methodology for modelling actuation sequence in a gear box. This paper presents a methodological approach in designing a gearbox for the purpose of obtaining an optimal shifting sequence. The computational model considers factors namely, the number of stages and gear teeth as input parameters since these two are the determinants of the gear ratios in an epicyclic gear train. The proposed transmission schematic or stick diagram aids in developing the gearbox layout design. The number of iterations and development time required to design a gearbox layout is reduced by using this approach.

Keywords: automatic transmission, gear-shifting, multi-stage planetary gearbox, rank ordered clustering

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Authors: M. Iqbal Mahmud, Haeng Muk Cho, Seo Hyun Sang, Wang Wen Hai, Chang Heon Yi, Man Ik Hwang, Dae Hoon Kang

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Solenoid operated electromagnetic control valve (ECV) playing an important role for car’s air conditioning control system. ECV is used in external variable displacement swash plate type compressor and controls the entire air conditioning system by means of a pulse width modulation (PWM) input signal supplying from an external source (controller). Complete form of ECV contains number of internal features like valve body, core, valve guide, plunger, guide pin, plunger spring, bellows etc. While designing the ECV; dimensions of different internal items must meet the standard requirements as it is quite challenging. In this research paper, especially the dimensioning of ECV body and its three pressure ports through which the air/refrigerant passes are considered. Here internal leakage test analysis of ECV body is being carried out from its discharge port (Pd) to crankcase port (Pc) when the guide valve is placed inside it. The experiments have made both in ordinary and digital system using different assumptions and thereafter compare the results.

Keywords: electromagnetic control valve (ECV), leakage, pressure port, valve body, valve guide

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Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: Balkar Singh, Gurpreet Singh, Vivek Aggarwal, Sehijpal Singh

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The present research focused to improve the machinability of Hastelloy C-276 at different machining speeds such as 31, 55, and 79 m/min. The use of CO2 gas and Minimum quantity lubrication (MQL) was applied as coolant and lubrication purposes to enhance the machinability of the superalloy. The output in the form of surface roughness (S.R) and heat generation was monitored under dry, MQL, and MQL-CO2-cooled conditions. The Design of the Experiment was prepared using MINITAB software utilizing Taguchi L-27 orthogonal arrays followed by ANOVA analysis for finding the impact of input variables on output responses. At different speeds and lubrication conditions, different behavioral patterns for Surface Roughness and the temperature was observed. ANOVA analysis depicted that the cooling environment impacted the S.R. majorly (50%) followed by cutting speed (29.84%), feed rate (5.09%), and least through depth of cut (4.95%). On the other side, the temperature was greatly influenced by cutting speed (69.12%), Cryo-MQL (8.09%), feed rate (7.59%), and depth of cut (6.20%). Experimental results revealed that Cryo-MQL cooling enhanced the Surface roughness by 12% compared to MQL condition.

Keywords: Hastelloy C-276, minimum quantity lubrication, olive oil, cryogenic Cooling (CO2)

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Authors: Anne Waithira Dormal

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Climate change is threatening pastoral livelihoods in Kajiado County, Kenya, through water shortages, livestock deaths, and increasing poverty. This study examines how these impacts differ for men and women within these communities. Limited access to resources, limited land and livestock rights, and limited decision-making power increase women's vulnerability, which is further burdened by traditional gender roles in water procurement. The research recognizes the complexity of climate change and emphasizes that factors such as wealth, family dynamics, and socioeconomic status also influence resilience. Effective adaptation strategies must address all genders. While livestock farming provides a safety net, socioeconomic empowerment through access to credit, healthcare, and education strengthens entire communities. An intersectional perspective that takes ethnicity, social status, and other factors into account is also crucial. This research, therefore, aims to examine how gender-specific adaptation strategies interact with gender and socioeconomic factors to determine the resilience of these Kenyan pastoralist communities. Such strategies, which address the specific needs and vulnerabilities of men and women, are expected to lead to increased resilience to climate change. The aim of the study is to identify effective, gender-specific adaptation strategies that can be integrated into climate change planning and implementation. Additionally, research awaits a deeper understanding of how socioeconomic factors interact with gender to influence vulnerability and resilience within these communities. The study uses a gender-sensitive qualitative approach with focus group discussions in four different pastoral and agropastoral communities. Both qualitative and demographic data are used to capture sources of income, education level, and household size of focus group respondents to increase the power of the analysis. While the research acknowledges the limitations of specific focus sites and potential biases in self-reporting, it offers valuable insights into gender and climate change in pastoral contexts. This study contributes to understanding gender-based vulnerabilities and building resilience in these communities.

Keywords: climate adaptation strategies, climate change, climate resilience, gendered vulnerability, pastoralism

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Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

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Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Jayesh Mahitkar, V. K. Singh, Surendra Singh Kachhwaha

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Wire Mesh Heat Pipe (WMHP) as an effective component of thermal control system in the payload of spacecraft, utilizing ammonia to transfer efficient amount of heat. One dimensional generic and robust mathematical model with partial-analytical hydraulic approach (PAHA) is developed to study inside behaviour of WMHP. In this model, inside performance during operation is investigated like mass flow rate, and velocity along the wire mesh as well as vapour core is modeled respectively. This numerical model investigate heat flow along length, pressure drop along wire mesh as well as vapour line in axial direction. Furthermore, WMHP is modeled into equivalent resistance network such that total thermal resistance of heat pipe, temperature drop across evaporator end and condenser end is evaluated. This numerical investigation should be carried out for single layer and double layer wire mesh each with heat input at evaporator section is 10W, 20 W and 30 W at condenser temperature maintained at 20˚C.

Keywords: ammonia, heat transfer, modeling, wire mesh

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Authors: Nolitha L. Skenjana, Bongani P. Kubheka, Maxwell A. Poswal

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The Eastern Cape Province of South Africa is characterized by subsistence farming, which is mostly distributed in the rural areas of the province. It is estimated that cereal crops such as maize and sorghum, and vegetables such as cabbage are grown in more than 400.000 rural households, with maize being the most dominant crop. However, compared to commercial agriculture, small-scale farmers receive minimal support from research and development, limited technology transfer on the latest production practices and systems and have poor production infrastructure and equipment. Similarly, there is limited farmers' appreciation on best practices in insect pest management and control. The paper presents findings from the primary literature and personal observations on insect pest management practices of small-scale farmers in the province. Inferences from literature and personal experiences in the production areas have led to a number of deductions regarding the level of exposure and extent of vulnerability. Farmers' pest management practices, which included not controlling at all though there is a pest problem, resulted in their crop stands to be more vulnerable to pest attacks. This became more evident with the recent brown locust, African armyworm, and Fall armyworm outbreaks, and with the incidences of opportunistic phytophagous insects previously collected on wild hosts only, found causing serious damages on crops. In most of these occurrences, damage to crops resulted in low or no yield. Improvements on farmers' reaction and response to pest problems were only observed in areas where focused awareness campaigns and trainings on specific pests and their management techniques were done. This then calls for a concerted effort from all role players in the sphere of small-scale crop production, to train and equip farmers with relevant skills, and provide them with information on affordable and climate-smart strategies and technologies in order to create a state of preparedness. This is necessary for the prevention of substantial crop losses that may exacerbate food insecurity in the province.

Keywords: Eastern Cape Province, small-scale farmers, insect pest management, vulnerability

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Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: Tennah Safia, Azzag Naouelle, Derdour Salima, Hafsi Fella, Laouadi Mourad, Laamari Abdalouahab, Ghalmi Farida, Kafidi Nacerredine

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Currently, goat farming is widely practiced among the rural population of Algeria. Although milk yield of goats is low (110 liters per goat and per year on average), this milk partly ensures the feeding of small children and provides raw milk, curd, and fermented milk to the whole family. In addition, given its investment cost, which is ten times lower than that of a cow, this level of production is still of interest. This interest is reinforced by the qualities of goat's milk, highly sought after for its nutritional value superior to that of cow's milk. In the same way, its aptitude for the transformation, in particular in quality cheeses, is very sought after. The objective of this study is to give the situation of goat milk production in rural areas of Algeria and to establish a classification of goat breeds according to their production potential. For this, a survey was carried out with goat farmers in Algerian steppe. Three indigenous breeds were encountered in this study: the breed Arabia, Mozabite, and Mekatia; Arabia being the most dominant. The Mekatia breed and the Mozabite breed appear to have higher production and milking abilities than other local breeds. They are therefore indicated to play the role of local dairy breeds par excellence. The other breed that could be improved milk performance is the Arabia breed. There, however, the milk performance of this breed is low. However, in order to increase milk production, uncontrolled crosses with imported breeds (mainly Saanen and Alpine) were carried out. The third population that can be included in the category for dairy production is the dairy breed group of imported origin. There are farms in Algeria composed of Alpine and Saanen breeds born locally. Improved milk performance of local goats, Crusader population, and dairy breeds of imported origin could be done by selection. For this, it is necessary to set up a milk control to detect the best animals. This control could be carried out among interested farmers in each large goat breeding area. In conclusion, sustained efforts must be made to enable the sustainable development of the goat sector in Algeria. It will, therefore, be necessary to deepen the reflection on a national strategy to valorize goat's milk, taking into account the specificities of the environment, the genetic biodiversity, and the eating habits of the Algerian consumer.

Keywords: goat, milk, Algeria, biodiversity

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Authors: Toumi Farah, Charallah Salima

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In the Algerian Sahara, goat farming is predominant, and it’s associated with other types of breeding, particularly camel and sheep; it also constitutes a significant proportion of breeding exclusively goat. This Saharan goat is a small ruminant with a black dress with white’s spots, hanging ears, and a coat more or less long. It is known for its hardiness and resistance to adverse conditions of arid zones and its perfect ecophysiological adaptation to harsh environmental conditions. However, pregnancy alterations, particularly abortion, degrade its productivity and cause economic losses, having both direct and indirect effects on animal production, like the costs of veterinary interventions and the reconstitution of livestock. The purpose of this work is to study the histological aspect of the liver of goats’ aborted living under nomadic herds in the region of Béni-Abbès (30° 7' N, 2° 10 'O). The organs were collected in physiological serum, rinsed, and then fixed with formaldehyde (37°, diluted at 10%). After that, these samples were processed for a topographic study. The morphometric study of the liver was performed by using an image analysis and processing software "Image J"; the various measurements obtained are intended to specify the supposed stage of development according to the body weight. The histological structure of the liver shows that the hepatic parenchyma consists of vascular conjunctive spaces surrounded by Glisson’s capsule. The sinusoids and hepatic portal vein are full of red blood cells, representing sinusoidal congestion and a thrombosed vein. At high magnification, the blood vessels show the presence of vascular thrombosis and haemorrhage in some areas of the hepatic parenchyma. Morphometric analysis shows that the number of liver parenchymal cells and the diameter of liver vessels vary according to the stage of development. The results obtained will provide details of the anatomical and cellular elements that can be used in the diagnosis of early or late abortion and late embryonic death. It would be interesting to find, by immunohistochemistry, some inflammatory markers useful for monitoring the progress of pregnancy and bioindicators of fetomaternal distress.

Keywords: aborting goat, arid zone, liver, histopathology

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Authors: B. Manoj Kumar, C. Malavika, E. S. Kannan

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The objective of this study is to investigate the switching behavior of two vertically aligned memristors connected by a shared top electrode, a configuration that significantly deviates from the conventional single oxide layer sandwiched between two electrodes. The device is fabricated by bridging copper electrodes with mechanically exfoliated van der Waals metal (specifically tantalum disulfide and tantalum diselenide). The device demonstrates threshold-switching behavior in its I-V characteristics. When the input voltage signal is ramped with voltages below the threshold, the output current shows spiking behavior, resembling integrated and firing actions without extra circuitry. We also investigated the self-reset behavior of the device. Using a continuous constant voltage bias, we activated the device to the firing state. After removing the bias and reapplying it shortly afterward, the current returned to its initial state. This indicates that the device can spontaneously return to its resting state. The outcome of this investigation offers a fresh perspective on memristor-based device design and an efficient method to construct hardware for neuromorphic computing systems.

Keywords: integrated and firing, memristor, spiking behavior, threshold switching

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Authors: Nahla Elazab, Mohamed Aboudina, Ghada Ibrahim, Hossam Fahmy, Ahmed Khalil

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This paper presents the developed memristor based demodulators for eight circular Quadrature Amplitude Modulation (QAM) and Binary Frequency Shift Keying (BFSK) operating at relatively high frequency. In our implementations, the experimental-based ‘nonlinear’ dopant drift model is adopted along with the proposed circuits providing incorporation of all known non-idealities of practically realized memristor and gaining high operation frequency. The suggested designs leverage the distinctive characteristics of the memristor device, definitely, its changeable average memristance versus the frequency, phase and amplitude of the periodic excitation input. The proposed demodulators feature small integration area, low power consumption, and easy implementation. Moreover, the proposed QAM demodulator precludes the requirement for the carrier recovery circuits. In doing so, the designs were validated by transient simulations using the nonlinear dopant drift memristor model. The simulations results show high agreement with the theory presented.

Keywords: BFSK, demodulator, high frequency memristor applications, memristor based analog circuits, nonlinear dopant drift model, QAM

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Pornpimol Chaiwuttisak

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The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

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Authors: Arakelian Vigen, Geng Jing, Le Baron Jean-Paul

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The paper deals with the design of parallel manipulators with balanced inertia forces and moments. The balancing of the resultant of the inertia forces of 3-RRR planar parallel manipulators is carried out through mass redistribution and centre of mass acceleration minimization. The proposed balancing technique is achieved in two steps: at first, optimal redistribution of the masses of input links is accomplished, which ensures the similarity of the end-effector trajectory and the manipulator’s common centre of mass trajectory, then, optimal trajectory planning of the end-effector by 'bang-bang' profile is reached. In such a way, the minimization of the magnitude of the acceleration of the centre of mass of the manipulator brings about a minimization of shaking force. To minimize the resultant of the inertia moments (shaking moment), the active balancing via inertia flywheel is applied. However, in this case, the active balancing is quite different from previous applications because it provides only a partial cancellation of the shaking moment due to the incomplete balancing of shaking force.

Keywords: dynamic balancing, inertia force minimization, inertia moment minimization, 3-RRR planar parallel manipulator

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Authors: M. Tehranizadeh, E. Shoushtari Rezvani

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Seismic performance of steel moment-resisting frame structures is investigated considering nonlinear soil-structure interaction (SSI) effects. 10-, 15-, and 20-story planar building frames with aspect ratio of 3 are designed in accordance with current building codes. Inelastic seismic demands of the superstructure are considered using concentrated plasticity model. The raft foundation system is designed for different soil types. Beam-on-nonlinear Winkler foundation (BNWF) is used to represent dynamic impedance of the underlying soil. Two sets of pulse-like as well as no-pulse near-fault earthquakes are used as input ground motions. The results show that the reduction in drift demands due to nonlinear SSI is characterized by a more uniform distribution pattern along the height when compared to the fixed-base and linear SSI condition. It is also concluded that beneficial effects of nonlinear SSI on displacement demands is more significant in case of pulse-like ground motions and performance level of the steel moment-resisting frames can be enhanced.

Keywords: soil-structure interaction, uplifting, soil plasticity, near-fault earthquake, tall building

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Authors: Hamed K. Arzani, Ahmad Amiri, Hamid K. Arzani, Salim Newaz Kazi, Ahmad Badarudin

Abstract:

The new design of heat exchangers utilizing an annular distributor opens a new gateway for realizing higher energy optimization. To realize this goal, graphene nanoplatelet-based water nanofluids with promising thermophysical properties were synthesized in the presence of covalent and noncovalent functionalization. Thermal conductivity, density, viscosity and specific heat capacity were investigated and employed as a raw data for ANSYS-Fluent to be used in two-phase approach. After validation of obtained results by analytical equations, two special parameters of convective heat transfer coefficient and pressure drop were investigated. The study followed by studying other heat transfer parameters of annular pass in the presence of graphene nanopletelesbased water nanofluids at different weight concentrations, input powers and temperatures. As a result, heat transfer performance and friction loss are predicted for both synthesized nanofluids.

Keywords: heat transfer, nanofluid, turbulent flow, forced convection flow, graphene nanoplatelet

Procedia PDF Downloads 431

Authors: Bibhuti Bhusan Sahoo, Ramakar Jha

Abstract:

Mapping of the extreme events (droughts) is one of the adaptation strategies to consequences of increasing climatic inconsistency and climate alterations. There is no operational practice to forecast the drought. One of the suggestions is to update mapping of drought prone areas for developmental planning. Drought indices play a significant role in drought mitigation. Many scientists have worked on different statistical analysis in drought and other climatological hazards. Many researchers have studied droughts individually for different sub-divisions or for India. Very few workers have studied district wise probabilities over large scale. In the present study, district wise drought probabilities over KBK (Kalahandi-Balangir-Koraput) districts of Odisha, India, Which are seriously prone to droughts, has been established using Hydrological drought index and Meteorological drought index along with the remote sensing drought indices to develop a multidirectional approach in the field of drought mitigation. Mapping for moderate and severe drought probabilities for KBK districts has been done and regions belonging different class intervals of probabilities of drought have been demarcated. Such type of information would be a good tool for planning purposes, for input in modelling and better promising results can be achieved.

Keywords: drought indices, KBK districts, proposed drought severity index, SPI

Procedia PDF Downloads 451

Authors: L. Rakesh, T. Y. Heblekar

Abstract:

This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

Procedia PDF Downloads 143