Search results for: Precision agriculture
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 633

Search results for: Precision agriculture

153 Evaluation of Groundwater Unit Hydrograph of Kavar-Maharloo Aquifer

Authors: Mohammad Hosein Hojati, Fardin Boustani

Abstract:

Groundwater is one of the most important water resources in Fars province. Based on this study, 95 percent of the total annual water consumption in Fars is used for agriculture, whereas the percentages for domestic and industrial uses are 4 and 1 percent, respectively. Population growth, urban and industrial growth, and agricultural development in Fars have created a condition of water stress. In this province, farmers and other users are pumping groundwater faster than its natural replenishment rate, causing a continuous drop in groundwater tables and depletion of this resource. In this research variation of groundwater level, their effects and ways to help control groundwater levels in aquifer of the Kavar- Maharloo plains in Fars plain were evaluated .Excessive exploitation of groundwater in this aquifer caused the groundwater levels fall too fast or to unacceptable levels. The average drawdown of the groundwater level in this plain were 17 meters during 1995 to 2006. The purpose of this study is to evaluate water level changes in the Kavar-Maharloo Aquifer in the Fars province in order to determine the areas of greatest depletion, the cause of depletion, and predict the remaining life of the aquifer.

Keywords: Aquifer , ground water depletion, water table

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152 Optimization of Agricultural Water Demand Using a Hybrid Model of Dynamic Programming and Neural Networks: A Case Study of Algeria

Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

Abstract:

In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: ater management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network.

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151 A CT-based Monte Carlo Dose Calculations for Proton Therapy Using a New Interface Program

Authors: A. Esmaili Torshabi, A. Terakawa, K. Ishii, H. Yamazaki, S. Matsuyama, Y. Kikuchi, M. Nakhostin, H. Sabet, A. Ishizaki, W. Yamashita, T. Togashi, J. Arikawa, H. Akiyama, K. Koyata

Abstract:

The purpose of this study is to introduce a new interface program to calculate a dose distribution with Monte Carlo method in complex heterogeneous systems such as organs or tissues in proton therapy. This interface program was developed under MATLAB software and includes a friendly graphical user interface with several tools such as image properties adjustment or results display. Quadtree decomposition technique was used as an image segmentation algorithm to create optimum geometries from Computed Tomography (CT) images for dose calculations of proton beam. The result of the mentioned technique is a number of nonoverlapped squares with different sizes in every image. By this way the resolution of image segmentation is high enough in and near heterogeneous areas to preserve the precision of dose calculations and is low enough in homogeneous areas to reduce the number of cells directly. Furthermore a cell reduction algorithm can be used to combine neighboring cells with the same material. The validation of this method has been done in two ways; first, in comparison with experimental data obtained with 80 MeV proton beam in Cyclotron and Radioisotope Center (CYRIC) in Tohoku University and second, in comparison with data based on polybinary tissue calibration method, performed in CYRIC. These results are presented in this paper. This program can read the output file of Monte Carlo code while region of interest is selected manually, and give a plot of dose distribution of proton beam superimposed onto the CT images.

Keywords: Monte Carlo, CT images, Quadtree decomposition, Interface program, Proton beam

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150 Determination of Acute Toxicity of Atrazine Herbicide in Caspian Kutum, Rutilus frisii kutum, Larvae

Authors: Z. Khoshnood, L. Khoshnood

Abstract:

Pesticides and drugs used in agriculture and veterinary medicine may end up in aquatic environments and bioaccumulate in the food chain, thus causing serious problems for fauna and human health. For determination of the toxic effects of atrazine herbicide on Caspian kutum, Rutilus frisii kutum larvae, the 96-h LC50 of atrazine was measured for newly hatched larvae as 18.53 ppm. Toxicity of atrazine herbicide on Caspian kutum larvae was investigated using concentrations: 9.25ppm, 4.62 ppm and 2.31 ppm for 7 days. Comparison of the length, weight and condition factor showed that no significant differences between atrazine exposed and control groups. The concentration of Na+, K+, Ca2+, Mg2+ and Cl- in whole body of larvae in control and atrazine exposure groups were measured and the results showed that concentrations of all these ions is higher in atrazine exposure group than control group. It is obvious from this study that atrazine negatively affects osmoregulation process and changes ion compositions of the body even at sublethal concentration and acute exposure but have no effects on growth parameters of the body.

Keywords: Atrazine, Caspian Kutum, Acute Toxicity, Body Ions, LC50.

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149 Physiological and Biochemical Responses to Drought Stress of Chickpea Genotypes

Authors: E. Ceyhan, A. Kahraman, M. Önder, M.K. Ateş, S. Karadaş, R. Topak, M.A. Avcı

Abstract:

The experimental design was 4 x 5 factorial with three replications in fully controlled research greenhouse in Department of Soil Sciences and Plant Nutrition, Faculty of Agriculture, University of Selcuk in the year of 2009. Determination of tolerant chickpea genotypes to drought was made in the research. Additionally, sophisticated effects of drought on plant growth and development, biochemical and physical properties or physical defense mechanisms were presented. According to the results, the primary genotypes were Ilgın YP (0.0063 g/gh) for leaf water capacity, 22235 70.44(%) for relative water content, 22159 (82.47%) for real water content, 22159 (5.03 mg/l) for chlorophyll a+b, Ilgın YP (125.89 nmol H2O2.dak-1/ mg protein-1) for peroxidase, Yunak YP (769.67 unit/ mg protein-1) for superoxide dismutase, Seydişehir YP (16.74 μg.TA-1) for proline, Gökçe (80.01 nmol H2O2.dak-1/ mg protein-1) for catalase. Consequently, all the genotypes increased their enzyme activity depending on the increasing of drought stress consider with the effects of drought stress on leaf enzyme activity. Chickpea genotypes are increasing enzyme activity against to drought stress.

Keywords: Chickpea, drought, enzyme, tolerance to drought

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148 Cellulolytic Microbial Activator Influence on Decomposition of Rubber Factory Waste Composting

Authors: Thaniya Kaosol, Sirinthrar Wandee

Abstract:

In this research, an aerobic composting method is studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator (CMA) as the activator in the rubber factory waste composting. The performance of the composting process was monitored as a function of carbon and organic matter decomposition rate, temperature and moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory waste composted alone, the finished product does not achieve a standard of fertilizer, especially the C/N ratio. Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture content, temperature, and nutrients of the finished products are acceptable for agriculture use.

Keywords: composting, rubber waste, C/N ratio, sludge, cellulolytic microbial activator

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147 Machine Learning Techniques for COVID-19 Detection: A Comparative Analysis

Authors: Abeer Aljohani

Abstract:

The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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146 Characterization and Detection of Cadmium Ion Using Modification Calixarene with Multiwalled Carbon Nanotubes

Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suraini Abu Bakar

Abstract:

Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These studies focus on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this modification for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).The nanocomposites MWCNTs-calixarene have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications.

Keywords: Calixarene, Multiwalled Carbon Nanotubes, Cadmium, Surface Potential.

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145 Using Artificial Neural Network and Leudeking-Piret Model in the Kinetic Modeling of Microbial Production of Poly-β- Hydroxybutyrate

Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

Abstract:

Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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144 MiSense Hierarchical Cluster-Based Routing Algorithm (MiCRA) for Wireless Sensor Networks

Authors: Kavi K. Khedo, R. K. Subramanian

Abstract:

Wireless sensor networks (WSN) are currently receiving significant attention due to their unlimited potential. These networks are used for various applications, such as habitat monitoring, automation, agriculture, and security. The efficient nodeenergy utilization is one of important performance factors in wireless sensor networks because sensor nodes operate with limited battery power. In this paper, we proposed the MiSense hierarchical cluster based routing algorithm (MiCRA) to extend the lifetime of sensor networks and to maintain a balanced energy consumption of nodes. MiCRA is an extension of the HEED algorithm with two levels of cluster heads. The performance of the proposed protocol has been examined and evaluated through a simulation study. The simulation results clearly show that MiCRA has a better performance in terms of lifetime than HEED. Indeed, MiCRA our proposed protocol can effectively extend the network lifetime without other critical overheads and performance degradation. It has been noted that there is about 35% of energy saving for MiCRA during the clustering process and 65% energy savings during the routing process compared to the HEED algorithm.

Keywords: Clustering algorithm, energy consumption, hierarchical model, sensor networks.

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143 Adopting Artificial Intelligence and Deep Learning Techniques in Cloud Computing for Operational Efficiency

Authors: Sandesh Achar

Abstract:

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

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

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142 Prediction of Saturated Hydraulic Conductivity Dynamics in an Iowan Agriculture Watershed

Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

Abstract:

In this study, a physically-based, modeling framework was developed to predict saturated hydraulic conductivity (Ksat) dynamics in the Clear Creek Watershed (CCW), Iowa. The modeling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the Ksat field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured Ksat values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of Ksat variability in CCW due to the seasonal changes in climate and land use activities. 

Keywords: Saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools.

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141 Impact of HIV/AIDS on Food Security in Pala Sub-Location, Bondo District, Kenya

Authors: S. B. Otieno, Were Fred, E. W. Kabiru, K. Waza

Abstract:

Background: HIV/AIDS is leading to the loss of labor through sickness and subsequent death, this is leading to the neglect of farm and off-farm activities, with the subsequent loss of potential income and food security. The situation is sensitive to seasonal labour peaks in agriculture. This study was done to determine the impact of high HIV prevalence in farming systems and food security in Pala Bondo District, Kenya. Methods: In this study, 386 respondents were randomly chosen in Pala Sub-Location. The respondents and key informants were interviewed using structured questionnaire. The data were entered and analyzed using SPSS version 16. Results: It was established that majority of respondents (67%) were between 18 and 35 years {χ2 = (1, N = 386) = 13.430, p = 0.000} (chimney effect). The study also established that 83.5% of respondents were married {χ2 = (1, N= 370) = 166.277 p = 0.000} and predominant occupation being farming and fishing (61%), while 52.8% of farm labour was by hand, 26% by oxen, and 4.9% mechanized. 73.2% of respondents only farm 0.25 to 2 acres, 48% mentioned lack of labour in land preparation {χ2 ((1,N = 321) = 113.146, p = 0.000), in planting {χ2 (1, N = 321) = 29.28, p = 0.000}. Majority of respondents lack food from January to June, during which 93% buy food. Conclusion: The high HIV prevalence in Pala has affected the farm labour leading to food insecurity.

Keywords: Food security, HIV, AIDS, labour.

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140 Small Farm Diversification Opportunities in Viticulture-Winemaking Sector of Georgia

Authors: E. Kharaishvili

Abstract:

The paper analyses the role of small farms in socio-economic development of agriculture in Georgia and evaluates modern concepts regarding the development of the farms of this size. The scale of farms in Georgia is studied and the major problems are revealed. Opportunities and directions of diversification are discussed from the point of increasing the share of Georgian grapes and wine both on domestic and international markets. It’s shown that the size of vineyard areas is directly reflected on the grape and wine production potential. Accordingly, vineyard area and grape production dynamics is discussed. Comparative analysis of small farms in Georgia and Italy is made and the major differences are identified. Diversification is evaluated based on cost-benefit analysis on the one hand and on the other hand, from the point of promoting economic activities, protecting nature and rural area development. The paper provides proofs for the outcomes of diversification. The key hindering factors for the development of small farms are identified and corresponding conclusions are made, based on which recommendations for diversification of the farms of this size are developed.

Keywords: Farm diversification, scale of farms, small farms, viticulture-winemaking.

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139 Design and Development of a Mechanical Force Gauge for the Square Watermelon Mold

Authors: M. Malek Yarand, H. Saebi Monfared

Abstract:

This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: Mechanical Force Gauge, Mold, Reshaped Fruit, Square Watermelon.

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138 The Comparation of Limits of Detection of Lateral Flow Immunochromatographic Strips of Different Types of Mycotoxins

Authors: X. Zhao, F. Tian

Abstract:

Mycotoxins are secondary metabolic products of fungi. These are poisonous, carcinogens and mutagens in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even deaths. The rapid, simple and cheap detection methods of mycotoxins are of immense importance and in great demand in the food and beverage industry as well as in agriculture and environmental monitoring. Lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety, environment monitoring. 46 papers were identified and reviewed on Google Scholar and Scopus for their limit of detection and nanomaterial on Lateral flow ICSTs on different types of mycotoxins. The papers were dated 2001-2021. 25 papers were compared to identify the lowest limit of detection of among different mycotoxins (Aflatoxin B1: 10, Zearalenone: 5, Fumonisin B1: 5, Trichothecene-A: 5). Most of these highly sensitive strips are competitive. Sandwich structures are usually used in large scale detection. In conclusion, the limit of detection of Aflatoxin B1 is the lowest among these mycotoxins. Gold-nanoparticle based immunochromatographic test strips have the lowest limit of detection. Five papers involve smartphone detection and they all detect aflatoxin B1 with gold nanoparticles.

Keywords: Aflatoxin B1, limit of detection, gold nanoparticle, lateral flow immunochromatographic strips, mycotoxins, smartphone.

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137 Modeling a Multinomial Logit Model of Intercity Travel Mode Choice Behavior for All Trips in Libya

Authors: Manssour A. Abdulsalam Bin Miskeen, Ahmed Mohamed Alhodairi, Riza Atiq Abdullah Bin O. K. Rahmat

Abstract:

In the planning point of view, it is essential to have mode choice, due to the massive amount of incurred in transportation systems. The intercity travellers in Libya have distinct features, as against travellers from other countries, which includes cultural and socioeconomic factors. Consequently, the goal of this study is to recognize the behavior of intercity travel using disaggregate models, for projecting the demand of nation-level intercity travel in Libya. Multinomial Logit Model for all the intercity trips has been formulated to examine the national-level intercity transportation in Libya. The Multinomial logit model was calibrated using nationwide revealed preferences (RP) and stated preferences (SP) survey. The model was developed for deference purpose of intercity trips (work, social and recreational). The variables of the model have been predicted based on maximum likelihood method. The data needed for model development were obtained from all major intercity corridors in Libya. The final sample size consisted of 1300 interviews. About two-thirds of these data were used for model calibration, and the remaining parts were used for model validation. This study, which is the first of its kind in Libya, investigates the intercity traveler’s mode-choice behavior. The intercity travel mode-choice model was successfully calibrated and validated. The outcomes indicate that, the overall model is effective and yields higher precision of estimation. The proposed model is beneficial, due to the fact that, it is receptive to a lot of variables, and can be employed to determine the impact of modifications in the numerous characteristics on the need for various travel modes. Estimations of the model might also be of valuable to planners, who can estimate possibilities for various modes and determine the impact of unique policy modifications on the need for intercity travel.

Keywords: Multinomial logit model, improved intercity transport, intercity mode-choice behavior, disaggregate analysis.

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136 Drivers of Land Degradation in Trays Ecosystem as Modulated under a Changing Climate: Case Study of Côte d'Ivoire

Authors: Kadio Valere R. Angaman, Birahim Bouna Niang

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Land degradation is a serious problem in developing countries including Cote d’Ivoire, which has its economy focused on agriculture. It occurs in all kinds of ecosystems over the world. However, the drivers of land degradation vary from one region to another, and from one ecosystem to another. Thus, identifying these drivers is an essential prerequisite to develop and implement appropriate policies to reverse the trend of land degradation in the country, especially in the trays ecosystem. Using the binary logistic model with primary data obtained through 780 farmers surveyed, we analyze and identify the drivers of land degradation in the trays ecosystem. The descriptive statistics show that 52% of farmers interviewed have stated facing land degradation in their farmland. This high rate shows the extent of land degradation in this ecosystem. Also, the results obtained from the binary logit regression reveal that land degradation is significantly influenced by a set of variables such as sex, education, slope, erosion, pesticide, agricultural activity, deforestation, and temperature. The drivers identified are mostly local, as a result, the government must implement some policies and strategies that facilitate and incentive the adoption of sustainable land management practices by farmers to reverse the negative trend of land degradation.

Keywords: Drivers, land degradation, trays ecosystem, sustainable land management.

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135 An Analysis of Uncoupled Designs in Chicken Egg

Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: Uncoupled design, axiomatic design, nature design, design evaluation.

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134 Human Factors Considerations in New Generation Fighter Planes to Enhance Combat Effectiveness

Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: Combat effectiveness, emerging technologies, human factors, systems safety analysis.

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133 Mapping Paddy Rice Agriculture using Multi-temporal FORMOSAT-2 Images

Authors: Yi-Shiang Shiu, Meng-Lung Lin, Kang-Tsung Chang, Tzu-How Chu

Abstract:

Most paddy rice fields in East Asia are small parcels, and the weather conditions during the growing season are usually cloudy. FORMOSAT-2 multi-spectral images have an 8-meter resolution and one-day recurrence, ideal for mapping paddy rice fields in East Asia. To map rice fields, this study first determined the transplanting and the most active tillering stages of paddy rice and then used multi-temporal images to distinguish different growing characteristics between paddy rice and other ground covers. The unsupervised ISODATA (iterative self-organizing data analysis techniques) and supervised maximum likelihood were both used to discriminate paddy rice fields, with training areas automatically derived from ten-year cultivation parcels in Taiwan. Besides original bands in multi-spectral images, we also generated normalized difference vegetation index and experimented with object-based pre-classification and post-classification. This paper discusses results of different image classification methods in an attempt to find a precise and automatic solution to mapping paddy rice in Taiwan.

Keywords: paddy rice fields; multi-temporal; FORMOSAT-2images, normalized difference vegetation index, object-basedclassification.

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132 Characterization of the Microbial Induced Carbonate Precipitation Technique as a Biological Cementing Agent for Sand Deposits

Authors: Sameh Abu El-Soud, Zahra Zayed, Safwan Khedr, Adel M. Belal

Abstract:

The population increase in Egypt is urging for horizontal land development which became a demand to allow the benefit of different natural resources and expand from the narrow Nile valley. However, this development is facing challenges preventing land development and agriculture development. Desertification and moving sand dunes in the west sector of Egypt are considered the major obstacle that is blocking the ideal land use and development. In the proposed research, the sandy soil is treated biologically using Bacillus pasteurii bacteria as these bacteria have the ability to bond the sand partials to change its state of loose sand to cemented sand, which reduces the moving ability of the sand dunes. The procedure of implementing the Microbial Induced Carbonate Precipitation Technique (MICP) technique is examined, and the different factors affecting on this process such as the medium of bacteria sample preparation, the optical density (OD600), the reactant concentration, injection rates and intervals are highlighted. Based on the findings of the MICP treatment for sandy soil, conclusions and future recommendations are reached.

Keywords: Soil stabilization, biological treatment, MICP, sand cementation.

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131 Application of Different Ratios of Effluents of Ethyl Alcohol Factories on Germination of Barley

Authors: Azadeh Vaziri

Abstract:

Using effluent as a sustainable water resource for agriculture not only could provide part of water needs but also would save the existing water resources, durably. Vinasse, the effluent of ethyl alcohol factories, a by-product, which is derived from sugarcane molasses, is one of the water resources that could be effectively utilized for agricultural purposes. In the present study in order to investigate the application of different ratios of water: vinasse on germination and growth of barley seedlings an experiment was designed in pots with completely randomized design with three replications and control treatment. The consequences of four irrigation levels were studied with different water: effluent ratios (100% water, 90% water & 10% effluent, 75% water & 25% effluent, 50% water & 50% effluent) on germination and growth of barley seedling components in sandy-loam soil. The results showed that, with increasing the percentage of vinasse in the irrigation admixture, the germination percentage in barley seedlings decreased, significantly, so that the decrease in germination in comparison with the control samples in the second and third treatments was 20% and 93.33%, respectively. Seed germination percentage was about 46.66. The average stem length in seedlings was 14.3 mm and the average root length was 9.37 mm. The averages of the soils Electrical Conductivity (EC) and pH which were under irrigation with different ratios of vinasse (dSm-1) were 5.85 and 7.32, respectively, which showed a 76.2% increase in soil salinity.

Keywords: Electrical Conductivity, effluent, germination, vinasse, barley.

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130 Influence of Tool Geometry on Surface Roughness and Tool Wear When Turning AISI 304L Using Taguchi Optimisation Methodology

Authors: Salah Gariani, Taher Dao, Ahmed Lajili

Abstract:

This paper presents an experimental optimisation of surface roughness (Ra) and tool wear in the precision turning of AISI 304L alloy using a wiper and conventional cutting tools under wet cutting conditions. The machining trials were conducted based on Taguchi methodology employing an L9 orthogonal array design with four process parameters: feed rate, spindle speed, depth of cut, and cutting tool type. The experimental results were utilised to characterise the main factors affecting Ra and tool wear using the analyses of means (AOM) and variance (ANOVA). The results show that the wiper tools outperformed conventional tools in terms of surface quality and tool wear at optimal cutting conditions. The ANOVA results indicate that the main factors contributing to lower Ra are cutting tool type and feed rate, with percentage contribution ratios (PCRs) of 58.69% and 25.18% respectively. This confirms that tool type is the most significant factor affecting surface quality when turning AISI 304L. Additionally, a substantial reduction in tool wear was observed when a wiper insert was used, whereas noticeable increases in tool wear occurred when higher cutting speeds were employed for both tool types. These trends confirm the ANOVA outcomes that cutting speed has a significant effect on tool wear, with a PCR value of 39.22%, followed by tool type with a PCR of 27.40%. All machining trials generated similar continuous spiral or curl-shaped chips. A noticeable difference was found in the radius of the produced curl-shaped chips at different cutting speeds when turning AISI 304L under wet cutting conditions.

Keywords: AISI 304L alloy, conventional and wiper carbide tools, wet turning, average surface roughness, tool wear.

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129 A Cumulative Learning Approach to Data Mining Employing Censored Production Rules (CPRs)

Authors: Rekha Kandwal, Kamal K.Bharadwaj

Abstract:

Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Keywords: Censored production rules, cumulative learning, data mining, machine learning.

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128 A Review on the Mechanism Removal of Pesticides and Heavy Metal from Agricultural Runoff in Treatment Train

Authors: N. A. Ahmad Zubairi, H. Takaijudin, K. W. Yusof

Abstract:

Pesticides have been used widely over the world in agriculture to protect from pests and reduce crop losses. However, it affects the environment with toxic chemicals. Exceed of toxic constituents in the ecosystem will result in bad side effects. The hydrological cycle is related to the existence of pesticides and heavy metal which it can penetrate through varieties of sources into the soil or water bodies, especially runoff. Therefore, proper mechanisms of pesticide and heavy metal removal should be studied to improve the quality of ecosystem free or reduce from unwanted substances. This paper reviews the use of treatment train and its mechanisms to minimize pesticides and heavy metal from agricultural runoff. Organochlorine (OCL) is a common pesticide that was found in the agricultural runoff. OCL is one of the toxic chemicals that can disturb the ecosystem such as inhibiting plants' growth and harm human health by having symptoms as asthma, active cancer cell, vomit, diarrhea, etc. Thus, this unwanted contaminant gives disadvantages to the environment and needs treatment system. Hence, treatment train by bioretention system is suitable because removal efficiency achieves until 90% of pesticide removal with selected vegetated plant and additive.

Keywords: Pesticides, heavy metal, agricultural runoff, bioretention, mechanism removal, treatment train.

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127 Named Entity Recognition using Support Vector Machine: A Language Independent Approach

Authors: Asif Ekbal, Sivaji Bandyopadhyay

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Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.

Keywords: Named Entity (NE), Named Entity Recognition (NER), Support Vector Machine (SVM), Bengali, Hindi.

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126 Reverse Engineering of Agricultural Machinery: A Key to Food Sufficiency in Nigeria

Authors: Williams S. Ebhota, Virginia Chika Ebhota, Samuel A. Ilupeju

Abstract:

Agriculture employs about three-quarter of Nigeria's workforce and yet food sufficiency is a challenge in the country. This is largely due to poor and outdated pre-harvest and post-harvest farming practices. The land fallow system is still been practised as fertiliser production in the country is grossly inadequate and expensive. The few available post-harvest processing facilities are faced with ageing and are inefficient. Also, use of modern processing equipment is limited by farmers' lack of fund, adequate capacity to operate and maintain modern farming equipment. This paper, therefore, examines key barriers to agricultural products processing equipment in the country. These barriers include over-dependence on foreign technologies and expertise; poor and inadequate manufacturing infrastructure; and lack of political will by political leaders; lack of funds; and lack of adequate technical skills. This paper, however, sees the increase in the domestic manufacturing of pre-harvest and post-harvest machinery and equipment through reverse engineering approach as a key to food production sufficiency in Nigeria.

Keywords: Agricultural machinery, domestic manufacturing, forward engineering, production reverse engineering, technology.

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125 Decreasing Environmental Pollution in Superphosphate Production Using Apatite and Phosphorite Mixture

Authors: R. Guliyev

Abstract:

The enhanced need for food items is receiving more importance due to a gradual increase in the world population and, in this scenario, fertilizers play a very important role in agriculture. In this study, the production of the normal superphosphate was investigated with a continuous chamber method by adding potassium chloride to a mixture of Hibin apatite and Kingisepp phosphorite. In the experiments, the following parameters were selected: The concentration of sulfuric acid (54–66% (w/w)), the stoichiometric norm of sulfuric acid (100, 107, 110, 114% (w/w)), the ratio of apatite/phosphorite in the mixture of phosphate (95/5, 90/10, 85/15, 80/20, 75/25, 70/30, 65/35,60/40, 55/45, 50/50 (w/w)), potassium chloride/the mixture of phosphate (1/50, 2/50, 3/50,4/50, 5/50 (w/w)), and the reaction time (2–8 min). It was observed that by adding potassium chloride to a low-grade phosphorite and using it to substitute a fraction of high-grade apatite in the normal superphosphate production not only resulted in a high-quality product but also eliminated the waiting period for the maturation of superphosphate in the storage. The objective of this study was to produce a normal superphosphate fertilizer by using a continuous chamber method in order to accelerate the production process and to reduce the environmental pollution caused by fluoride gases by eliminating the maturation time in the storage.

Keywords: Continuous chamber method, environmental pollution, fluoride gases.

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124 Regulation of Transfer of 137cs by Polymeric Sorbents for Grow Ecologically Sound Biomass

Authors: A. H. Tadevosyan, S. K. Mayrapetyan, N. B. Tavakalyan, K. I. Pyuskyulyan, A. H. Hovsepyan, S. N. Sergeeva

Abstract:

Soil contamination with radiocesium has a long-term radiological impact due to its long physical half-life (30.1 years for 137Cs and 2 years for 134Cs) and its high biological availability. 137Cs causes the largest concerns because of its deleterious effect on agriculture and stock farming, and, thus, human life for decades. One of the important aspects of the problem of contaminated soils remediation is understand of protective actions aimed at the reduction of biological migration of radionuclides in soil-plant system. The most effective way to bind radionuclides is the use of selective sorbents. The proposed research mainly aims to achieve control on transfer of 137Cs in a system growing media – plant due to counter ions variation in the polymeric sorbents. As research object Japanese basil - Perilla frutescens was chosen. Productivity of plants depending on the presence (control-without presence of polymer) and type of polymer material, as well as content of 137Cs in plant material has been determined. The character of different polymers influences on the 137Cs migration in growing media – plant system as well as accumulation in the plants has been cleared up.

Keywords: Radioceaseum, Japanese basil, polymer, soil-plant system.

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