Search results for: low input farming

Authors: Paolo Castaldo, Bruno Palazzo, Laura Lodato

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This study deals with the seizure effects of friction pendulum (FP) bearings on the seismic reliability of a 3D base-isolated nonlinear structural system, designed according to Italian seismic code (NTC08). The isolated system consists in a 3D reinforced concrete superstructure, a r.c. substructure and the FP devices, described by employing a velocity dependent model. The seismic input uncertainty is considered as a random variable relevant to the problem, by employing a set of natural seismic records selected in compliance with L’Aquila (Italy) seismic hazard as provided from NTC08. Several non-linear dynamic analyses considering the three components of each ground motion have been performed with the aim to evaluate the seismic reliability of the superstructure, substructure, and isolation level, also taking into account the seizure event of the isolation devices. Finally, a design solution aimed at increasing the seismic robustness of the base-isolated systems with FPS is analyzed.

Keywords: FP devices, seismic reliability, seismic robustness, seizure

Procedia PDF Downloads 413

Authors: Yue Wang, Fan Chen

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After the economic reform in 1978, the urbanization in China has grown fast. It urged cities to expand in an unprecedented high speed. Villages around were annexed unprepared, and it turned out to be a new type of community called 'village in city.' Two things happened here. First, the locals gave up farming and turned to secondary industry and tertiary industry, as a result of losing their land. Secondly, attracted by the high income in cities and low rent here, plenty of migrants came into the community. This area is important to a city in rapid growth for providing a transitional zone. But thanks to its passivity and low development, 'village in city' has caused lots of trouble to the city. Densities of population and construction are both high, while facilities are severely inadequate. Unplanned and illegal structures are built, which creates a complex mixed-function area and leads to a bad residential area. Besides, the locals have a strong property right consciousness for the land. It holds back the transformation and development of the community. Although the land capitalization can bring significant benefits, it’s inappropriate to make a great financial compensation to the locals, and considering the large population of city migrants, it’s important to explore the relationship among the 'village in city,' city immigrants and the city itself. Taking the example of Hangzhou, this paper analyzed the developing process, functions spatial distribution, industrial structure and current traffic system of 'village in city.' Above the research on the community, this paper put forward a common method to make urban planning through the following ways: adding city functions, building civil facilities, re-planning functions spatial distribution, changing the constitution of local industry and planning new traffic system. Under this plan, 'village in city' finally can be absorbed into cities and make its own contribution to the urbanization.

Keywords: China, city immigrant, urbanization, village in city

Procedia PDF Downloads 217

Authors: Elena Barbaro, Elena Gregoris, Rossano Piazza, Boris Mifka, Tatjana Ivošević, Ivo Orlić, Ana Alebić-Juretić, Andrea Gambaro, Daniele Contini

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The aim of the POSEIDON project is to quantify the relative contribution of maritime traffic and harbor activities to atmospheric pollutants concentration in four port-cities of the Adriatic Sea. This study focuses on the harbors of Venice and Rijeka. In order to investigate the main pollution sources, emission inventories were used as input for receptor models: PMF (positive matrix factorization) and PCA (principal components analysis); moreover source identification was also conducted using PAHs diagnostic ratios. The ship traffic impact was quantified: i) on gaseous and particulate PAHs, collected using a new method which consisted in a double simultaneous sampling, in different wind sectors; ii) applying PMF to data of metals, PAHs and ions in PM10; iii) using the vanadium concentration according to the Agrawal methodology.

Keywords: ship traffic, PMF, harbor, POSEIDON

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Authors: Harish K. Arya, Kulwant Singh, R. K. Saxena

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The heat flow in weldment changes its nature from 2D to 3D with the increase in plate thickness. For welding of thicker plates the heat loss in thickness direction increases the cooling rate of plate. Since the cooling rate changes, the various bead parameters like bead penetration, bead height and bead width also got affected by it. The present study incorporates the effect of variable plate thickness on penetration and bead width. The penetration reduces with increase in plate thickness due to heat loss in thickness direction for same heat input, while bead width increases for thicker plate due to faster cooling.

Keywords: submerged arc welding, plate thickness, bead geometry, cooling rate

Procedia PDF Downloads 332

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 122

Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

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A 1 kW power factor correction boost converter with an active snubber cell is presented in this paper. In the converter, the main switch turns on under zero voltage transition (ZVT) and turns off under zero current transition (ZCT) without any additional voltage or current stress. The auxiliary switch turns on and off under zero current switching (ZCS). Besides, the main diode turns on under ZVS and turns off under ZCS. The output current and voltage are controlled by the PFC converter in wide line and load range. The simulation results of converter are obtained for 1 kW and 100 kHz. One of the most important feature of the given converter is that it has direct power transfer as well as excellent soft switching techniques. Also, the converter has 0.99 power factor with the sinusoidal input current shape.

Keywords: power factor correction, direct power transfer, zero-voltage transition, zero-current transition, soft switching

Procedia PDF Downloads 962

Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

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We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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Authors: U. Chattaraj, D. Meena

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Growth of traffic brings various negative effects, such as road accidents. To avoid such problems, a model is developed for the purpose of highway safety. In such areas, fuzzy logic is the most well-known simulation in the larger field. A model is accomplished for hilly and steep terrain based on Fuzzy Inference System (FIS), for which output is super elevation and input data is horizontal radius, vertical gradient, accident rate (AR). This result shows that the system can be efficaciously applied as for highway safety tool distinguishing hazards components correlated to the characteristics of the highway and has a great influence to the making of decision for accident precaution in transportation models. From this model, a positive relationship between geometric elements, accident rate, and super elevation is also identified.

Keywords: accident rate, fuzzy inference system, fuzzy logic, gradient, radius, super elevation

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

Procedia PDF Downloads 130

Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

Procedia PDF Downloads 389

Authors: Stephy Saavedra, Annsy C. Arredondo, Gisele Monteiro, Adalberto Pessoa Jr, Carol N. Flores-Fernandez, Amparo I. Zavaleta

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L-asparaginase from bacterial sources is used in leukemic treatment and food industry. This enzyme is classified based on its affinity towards L-asparagine and L-glutamine. Likewise, ansZ genes express L-asparaginase with higher affinity to L-asparagine. The aim of this work was to clone and express of ansZ gene from Bacillus sp. CH11 isolated from Chilca salterns in Peru. The gene encoding L-asparaginase was cloned into pET15b vector and transformed in Escherichia coli BL21 (DE3) pLysS. The expression was carried out in a batch culture using LB broth and 0.5 mM IPTG. The recombinant L-asparaginase showed a molecular weight of ~ 39 kDa by SDS PAGE and a specific activity of 3.19 IU/mg of protein. The cloning and expression of ansZ gene from this halotolerant Bacillus sp. CH11 allowed having a biological input to improve a future scaling-up.

Keywords: ansZ gene, Bacillus sp, Chilca salterns, recombinant L-asparaginase

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Authors: Iva Nedelcheva

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This study is part of a doctoral thesis on the topic of Hyperfiction: Past, Present and Future of Storytelling through Hypertext. It explores in depth the impact of transmedia storytelling and the role of hypertext in the realm of the currently popular social media phenomenon Pokémon GO. Storytelling is a powerful method to engage and unite people. Moreover, the technology progress adds a whole new angle to the method, with hypertext and cross-platform sharing that enhance the traditional storytelling so much that transmedia storytelling gives unlimited opportunities to affect the everyday life of people across the globe. This research aims at examining the transmedia storytelling approach in Pokémon GO, and explaining how that contributed to its establishment as a massive worldwide hit in less than a week. The social engagement is investigated in all major media platforms, including traditional and online media channels. Observation and content analyses are reported in this paper to form the conclusion that transmedia storytelling with the input of hypertext has a promising future as a method of establishing a productive and rewarding communication strategy.

Keywords: communication, hypertext, Pokemon Go, storytelling, transmedia

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Ina Nasto, Denada Sota, Pudrila Haskoçelaj, Mariola Ismailaj, Hajdar Kicaj

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Most of the fishing areas of the Mediterranean Sea are considered to be overfished, consequently fishing has decreased or is static. Considering the continuous increase in demand for fish, the option of aquaculture production has had a growing development in recent decades. The environmental impact of aquaculture in the marine ecosystem has been a subject of study for several years in the Mediterranean. In the case of the Albanian waters, and in particular the Gulf of Vlora, have had a progressive growing of aquaculture activity in the last twenty years. Given the convenient and secluded location for tourist activities, the bay of Ragusa was considered as the most suitable area to install the aquaculture cage system for the breeding of sea bass and sea bream. The impact of aquaculture in on the soft bottom benthic communities has been assessed at the biggest commercial fish farm (Alb-Adriatico Sh.P.K) established in coastal waters of Ragusa bay 30–50 m deep, in the southern part of the Gulf of Vlora. In order to determine if there is a possible impact on the aquaculture cage in benthic communities, a comparative analysis was undertaken between transects and samples with differences in distances between them and with a gradient of distance from the fish cages. A total of 275 taxa were identified (1 Foraminifera, 1 Porifera, 3 Cnidaria, 2 Platyhelminthes, 2 Nemertea, 1 Bryozoa, 171 Mollusca, 39 Annelida, 35 Crustacea, 14 Echinodermata, 1 Hemichordata, and 5 Tunicata). The anaysis showed three main habitats in the area: biocoenosis of terrigenous mud, residual areas with Possidonia oceanica and also residual assemblages of algal coralligenous. Four benthic biotic indexes were calculated (Shannon H ’, BENTIX, Simpson's Diversity and Peilou’s J’) also benthic indicators as total abundance, number of taxa and species frequency to evaluate possible ecological impact of fish cages in Ragusa bay.

Keywords: Bentix index, Benthic community, invertebrates, aquaculture, Raguza bay

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Authors: Osama Aziz, Hamza Ahmad, Muhibur Rahman

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The performance of wireless communication systems has been suggested to be improved by UWB MIMO antenna systems. However, creating a successful UWB MIMO antenna is a difficult undertaking that calls for resolving a number of design issues, including radiation efficiency, size, and frequency range. This study's primary objective is to create a novel, highly effective, small-sized, ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna and investigate its potential applications in body-centric communication. Two radiating elements, shared ground plane, circular stubs, and t-shaped isolation elements are used to achieve the MIMO antenna. Outstanding multiplexing efficiency, significant peak gain across the entire UWB frequency spectrum, extremely low mutual coupling (S21=-16 dB), high diversity gain (DG>9), and low envelop correlation are achieved. The proposed antenna will be one of the promising candidates for body centric communication.

Keywords: UWB communication, UWB MIMO antennas, body-centric communication, diversity gain

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Authors: Mohamad Baqer Heidari, Hefzollah.Mohammadian

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This brief presents two original implementations of improved accuracy current-mode multiplier/divider circuits. Besides the advantage of their simplicity, these original multiplier/divider structures present the advantage of very small linearity errors that can be obtained as a result of the proposed design techniques (0.75% and 0.9%, respectively, for an extended range of the input currents). The original multiplier/divider circuits permit a facile reconfiguration, the presented structures representing the functional basis for implementing complex function synthesizer circuits. The proposed computational structures are designed for implementing in 0.18-µm CMOS technology, with a low-voltage operation (a supply voltage of 1.2 V). The circuits’ power consumptions are 60 and 75 µW, respectively, while their frequency bandwidths are 79.6 and 59.7 MHz, respectively.

Keywords: analog signal processing, current-mode operation, functional core, multiplier, reconfigurable circuits, industrial package systems

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: MD Mashiur Rahman, Muhammad Arshadul Haque

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Emerging conservation agriculture (CA) is an option for improving soil health and maintaining environmental sustainability for intensive agriculture, especially in the tropical climate. Three years lengthy research experiment was performed in arid climate from 2018 to 2020 at research field of Bangladesh Agricultural Research Station (RARS)F, Jamalpur (soil texture belongs to Agro-Ecological Zone (AEZ)-8/9, 24˚56'11''N latitude and 89˚55'54''E longitude and an altitude of 16.46m) to evaluate the effect of CA approaches on energy use efficiency and a streamlined life cycle greenhouse gas (GHG) emission of wheat production. For this, the conservation tillage practices (strip tillage (ST) and minimum tillage (MT)) were adopted in comparison to the conventional farmers' tillage (CT), with retained a fixed level (30 cm) of residue retention. This study examined the relationship between energy consumption and life cycle greenhouse gas (GHG) emission of wheat cultivation in Jamalpur region of Bangladesh. Standard energy equivalents megajoules (MJ) were used to measure energy from different inputs and output, similarly, the global warming potential values for the 100-year timescale and a standard unit kilogram of carbon dioxide equivalent (kg CO₂eq) was used to estimate direct and indirect GHG emissions from the use of on-farm and off-farm inputs. Farm efficiency analysis tool (FEAT) was used to analyze GHG emission and its intensity. A non-parametric data envelopment (DEA) analysis was used to estimate the optimum energy requirement of wheat production. The results showed that the treatment combination having MT with optimum energy inputs is the best suit for cost-effective, sustainable CA practice in wheat cultivation without compromising with the yield during the dry season. A total of 22045.86 MJ ha⁻¹, 22158.82 MJ ha⁻¹, and 23656.63 MJ ha⁻¹ input energy for the practice of ST, MT, and CT was used in wheat production, and output energy was calculated as 158657.40 MJ ha⁻¹, 162070.55 MJ ha⁻¹, and 149501.58 MJ ha⁻¹, respectively; where energy use efficiency/net energy ratio was found to be 7.20, 7.31 and 6.32. Among these, MT is the most effective practice option taken into account in the wheat production process. The optimum energy requirement was found to be 18236.71 MJ ha⁻¹ demonstrating for the practice of MT that if recommendations are followed, 18.7% of input energy can be saved. The total greenhouse gas (GHG) emission was calculated to be 2288 kgCO₂eq ha⁻¹, 2293 kgCO₂eq ha⁻¹ and 2331 kgCO₂eq ha⁻¹, where GHG intensity is the ratio of kg CO₂eq emission per MJ of output energy produced was estimated to be 0.014 kg CO₂/MJ, 0.014 kg CO₂/MJ and 0.015 kg CO₂/MJ in wheat production. Therefore, CA approaches ST practice with 30 cm residue retention was the most effective GHG mitigation option when the net life cycle GHG emission was considered in wheat production in the silt clay loam soil of Bangladesh. In conclusion, the CA approaches being implemented for wheat production involving MT practice have the potential to mitigate global warming potential in Bangladesh to achieve soil carbon footprint, where the life cycle assessment approach needs to be applied to a more diverse range of wheat-based cropping systems.

Keywords: conservation agriculture and tillage, energy use efficiency, life cycle GHG, Bangladesh

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Authors: Neha Bhadauria, Indu Gaur, Shilpi Shilpi, Susmita Goswami, Prabir K. Paul

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The aerial surface of plants colonized by Human Enteric Pathogens ()has been implicated in outbreaks of enteric diseases in humans. Practice of organic farming primarily using animal dung as manure and sewage water for irrigation are the most significant source of enteric pathogens on the surface of leaves, fruits and vegetables. The present work aims to have an insight into the molecular mechanism of interaction of Human Enteric Pathogens or their metabolites with cell wall receptors in plants. Tomato plants grown under aseptic conditions at 12 hours L/D photoperiod, 25±1°C and 75% RH were inoculated individually with S. fonticola and K. pneumonia. The leaves from treated plants were sampled after 24 and 48 hours of incubation. The cell wall and cytoplasmic proteins were extracted and isocratically separated on 1D SDS-PAGE. The sampled leaves were also subjected to formaldehyde treatment prior to isolation of cytoplasmic proteins to study protein-protein interactions induced by Human Enteric Pathogens. Protein bands extracted from the gel were subjected to MALDI-TOF-TOF MS analysis. The foremost interaction of Human Enteric Pathogens on the plant surface was found to be cell wall bound receptors which possibly set ups a wave a critical protein-protein interaction in cytoplasm. The study revealed the expression and suppression of specific cytoplasmic and cell wall-bound proteins, some of them being important components of signaling pathways. The results also demonstrated HEP induced rearrangement of signaling pathways which possibly are crucial for adaptation of these pathogens to plant surface. At the end of the study, it can be concluded that controlling the over-expression or suppression of these specific proteins rearrange the signaling pathway thus reduces the outbreaks of food-borne illness.

Keywords: cytoplasmic protein, cell wall-bound protein, Human Enteric Pathogen (HEP), protein-protein interaction

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Authors: Moses Obenade, Henry U. Okeke, Francis I. Okpiliya, Eugene J. Aniah

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Population growth in Eleme has been rapid over the past 75 years with its attendant pressure on the natural resources of the area. Between 1937 and 2006 the population of Eleme grew from 2,528 to 190,194 and is projected to be above 265,707 in 2016 based on an annual growth rate of 3.4%. Using the combined technologies of Geographic Information Systems (GIS), remote sensing (RS) and Demography techniques as its methodology, this paper examines the environmental implications of rapid population growth on land use dynamics in Eleme between 1986 and 2015. The study reveals that between 1986 and 2006, Built-up area and Farmland increased by 72.67 and 12.77% respectively, while light and thick vegetation recorded a decrease of -6.92 and -61.64% respectively. Water body remains fairly constant with minimal changes. Also, between 2006 and 2015 covering a period of 9 years, Built-up area further increased by 53% with an annual growth rate of 2.32 km2 gaining more land area on the detriment of other land uses. Built-up area has an annual growth rate of 2.32km2 and is expected to increase from 18.67km2 in 2006 to 41.87km2 in 2016.The observed Land used/Land cover dynamics is derived by the demographic characteristics of the Study area. Eleme has a total area of 138km2 out of which the Federal Government of Nigeria compulsorily acquired an estimated area of 59.34km2 for industrial purposes excluding acquisitions by the Rivers State Government. It is evident from the findings of this study that the carrying capacity of Eleme ecosystem is under threat due to the current population growth and land consumption rates. Therefore, measures such as use of appropriate technologies in farming techniques, waste management; investment in family planning and female empowerment, maternal health and education, afforestation programs; and amendment of Land Use Act of 1978 are recommended.

Keywords: population growth, Eleme, land use, GIS and remote sensing

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Authors: Kgopa Bontle, Tholen Sodi

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Climate change poses a major threat to the well-being of both people and the environment, with subsistence farmers most affected as they rely on local supply systems that are sensitive to climate variation. This study documented psychological resilience factors associated with climate change adaptations by subsistence farmers in Maruleng Municipality, Limpopo Province. A qualitative study was conducted to examine the notions of climate change by subsistence farmers, the psychological resilience factors, the strategies to cope with climate change, adaptation methods, and the development of subsistence farmers’ psychological resilience factors model. Data were collected through direct interactions with participants using a grounded theory research design. An open-ended interview was used to collect data with a sample of 15 participants selected through theoretical sampling in Maruleng Municipality. The participants were both Sepedi and Xitsonga speaking from 2 villages, mostly unemployed, pensioners and dependent on social grants. The study included both males and females who were predominately the elderly. The research findings indicate that farmers have limited knowledge of what climate change is and what causes it. Furthermore, the research reflects that although their responses were non-scientific but sensible enough to know what they were dealing with. They mentioned extreme weather, which includes hot days and less rainfall and changes in seasons, as some of the impacts brought by climate change. The results also indicated that participants have learned to adapt through several adaptation strategies, including mulching, changes in irrigation time slots and being innovative. The resilience factors that emerged from the study were a passion for farming, hope, enthusiasm, courage, acceptance/tolerance, livelihood and belief systems. Looking at the socio-economic factors of the current study setting argumentation leads to the conclusion that it is important that government should assist the subsistence farmers as it was observed from the participants that they felt neglected by the government and policymakers as they are small scale farmers and are not included like commercial farmers.

Keywords: climate change, psychological resilience factors, human adaptation, subsistence farmers

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Huey-Kuo Chen

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This paper applies directional marginal productivity model to study the shadow price of emissions by transportation modes in the years of 2011 and 2013 with the aim to provide a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) generated by road transportation modes were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the directional shadow price (DSP) of SOx is much higher than CO2 and NOx. Nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting public transportation and subsidizing electric vehicles to reduce the use of private vehicles.

Keywords: marginal productivity, road transportation modes, shadow price, undesirable outputs

Procedia PDF Downloads 147

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Sopida Vacharasukpo, Sudarat Khwan-On

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This paper proposes a high step-up DC-DC converter topology for renewable energy system applications. The proposed converter employs only a single power switch instead of using several switches. Compared to the conventional DC-DC step-up converters the higher voltage gain with small output ripples can be achieved by using the proposed high step-up DC-DC converter topology. It can step up the low input voltage (20-50Vdc) generated from the photovoltaic modules to the high output voltage level approximately 600Vdc in order to supply the three-phase inverter fed the three-phase motor drive. In this paper, the operating principle of the proposed converter topology and its control strategy under the continuous conduction mode (CCM) are described. Finally, simulation results are shown to demonstrate the effectiveness of the proposed high step-up DC-DC converter with its control strategy to increase the voltage step-up conversion ratio.

Keywords: DC-DC converter, high step-up ratio, renewable energy, single switch

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Authors: Oleg Oborin

Abstract:

This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: Thomas Kipkurgat, Silahs Chemwaina

Abstract:

Communication and ICT is a crucial component in realization of vision 2030, radio has played a key role in dissemination of information to mass audience. Since time immemorial, mass media has played a vital role in passing information on agricultural development issues both locally and internationally. This paper aimed at assessing the role of community radio stations in enhancing agricultural development in Kenya. The paper sought to identify the main contributions of KASS FM radio in the agricultural development especially in rural areas, the study also aimed to establish the appropriate adjustments in editorial policies of KASS FM radio in helping to promote agricultural development related programmes in rural areas. Despite some weaknesses in radio programming and the mode of interaction with the rural people, the findings of this study showed that the rural communities are better off today than in the old days when FM radios were non-existent. KASS FM has come up with different developmental programmes that have positively contributed to changing the rural people’s ways of life. These programmes include farming, health, marital values, environment, cultural issues, human rights, democracy, religious teachings, peace and reconciliation. Such programmes feature experts, professionals and opinion leaders who address numerous topics of interest to the community. The local people participate in the production of these programmes through letters to the editor, and phone-ins, among others. Programmes such as political talk shows, which feature in KASS FM, has become one of the most important ways of community participation. The interpretation and conclusions are based on the empirical data analysis and the theories of development advanced by international development communication scholars, as presented in the paper. The study ends with some recommendations on how KASS FM can best serve the interests of the poor people in rural areas, and helps improve their lives.

Keywords: agriculture, development, communication, KASS FM, radio, rural areas, Kenya

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Authors: Muhammad Ilyas, Awais Khan, Syed Ali Raza Shah

Abstract:

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is getting the interest of the scientific community in robotics, especially in the robotic arm, a flexible joint manipulator. The current research work is based on position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in hardware setup based on LabVIEW programming is slightly greater than simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the dc motor varies between 0-8V to ensure minimal steady error while tracking the position and speed of the DC motor.

Keywords: DC motor, labview, proportional integral derivative control, position tracking, speed tracking

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Authors: Ashkan Asgari, Korous Khoshbakht, Saeid Soufizadeh

Abstract:

Various factors including land lots can affect biodiversity indices in Agricultural systems. Field study conducted to evaluate factors affecting crop diversity in Sarpolzahab in 2012. Required data were collected through direct observation of farms and filling questionnaires. Total numbers of 140 questionnaires were filled, SAS Software was used to analyse data and Ecological Methodology Program was applied to calculate Shannon-Winner index, subsequently. Results of study indicated that average number of land lots for each farmer was 2.78 and various from 2.2 in Rikhak Olia Village to 4.31 in Golam Kaboud Olia Village which shows small size of land lots due to separating larger lots by children of deceased farmers. The correlation between number of land lots and species biodiversity (0.308**) was significant and Shannon-Winner index was (0.262**). Therefore, according to the mentioned results one can assume that increase in number of land lots results in improving of the target index. Multiple land lots allow farmers to cultivate various crops which results in increasing biodiversity of crops in agro ecosystem. Subsequently, this increase will facilitate economic sustainability of the farmers and distribution of work force in the region throughout the year. The correlation of seasonal workers with biodiversity of crop species (0.256**) and Shannon-Winner (0.286**) was statistically significant and increasing number of seasonal work forces had resulted in improving crop biodiversity and decreasing dominant species or single crop farming systems. Vegetable farms which have a significant diversity, require a significant number of work forces which describes correlation between number of workers and diversity of species.

Keywords: agricultural systems, biodiversity indices, Shannon-Winner index, sustainability, rural

Procedia PDF Downloads 538