Search results for: farm crop budget analysis

Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: Counter-cyclical policy, fiscal rules, government effectiveness, procyclical policy.

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Authors: Popa Cosmin, Chiran Aurel

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The study aimed to identify the logical structure of data and particularities of developing and testing a website designed for selling farm products through online auctions. The research is based on a short literature review in the field and exploratory trials of some successful models from other industries, in order to identify the advantages of using such tool, as well as the optimal structure and functionality of an auction portal. In the last part, the study focuses on the results of testing the website by the potential beneficiaries. Conclusions of the study underlines that the particularities of some agricultural products could raise difficulties in the process of selling them through online auctions, but the use of such system it is perceived to bring significant improvements in the supply chain. The results of scientific investigations require a more detailed study regarding the importance of using quality standards for agricultural products sold via online auction, the impact that implementation of an online payment system could have on trade with agricultural products and problems which could arise in using the website in different countries.

Keywords: E-commerce, online auctions, marketing.

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Authors: Pingping Lin, Xudong Luo

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Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: Natural language processing, sentiment analysis, application, online comments.

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Authors: Junghoon Lee, Gyung-Leen Park, Ho-Young Kwak, Cheol Min Kim

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This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.

Keywords: sensor network, intelligent farm, middleware, event detection

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Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially the fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, ma-chine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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Authors: Achmad Zamroni, Masahiro Yamao

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Seaweed farming is emerging as a viable alternative activity in the Indonesian fisheries sector. This paper aims to investigate people-s perceptions of seaweed farming, to analyze its social and economic impacts and to identify the problems and obstacles hindering its continued development. Structured and semi-structured questionnaires were prepared to obtain qualitative data, and interviews were conducted with fishermen who also plant seaweed. The findings showed that fishermen in the Laikang Bay were enthusiastic about cultivating seaweeds and that seaweed plays a major role in supporting the household economy of fishermen. However, current seaweed drying technologies cannot support increased seaweed production on a farm or plot, especially in the rainy season. Additionally, variable monsoon seasons and long marketing channels are still major constraints on the development of the industry. Finally, capture fisheries, the primary economic livelihood of fishermen of older generations, is being slowly replaced by seaweed farming.

Keywords: Coastal management, perception, seaweed development and livelihood diversification

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Authors: Syed Kamarul Bakri Syed Ahmad Bokharey, Kalaikumar Vallyutham, Narayanan Sambu Potty, Nabilah Abu Bakar

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Infrastructure investments are important in developing countries, it will not only help to foster the economic growth of a nation, but it will also act as a platform in which new forms of partnership and collaboration can be developed mainly in East Asian countries. Since the last two decades, many infrastructure projects had been completed through build-operate-transfer (BOT) type of procurement. The developments of BOT have attracted participation of local and foreign private sector investor to secure funding and to deliver projects on time, within the budget and to the required specifications. Private sectors are preferred by the government in East Asia to participate in BOT projects due to lack of public funding. The finding has resulted that the private sector or promoter of the BOT projects is exposed to multiple risks which have been discussed in this paper. Effective risk management methods and good managerial skills are required in ensuring the success of the project. The review indicated that mitigation measures should be employed by the promoter throughout the concession period and support from the host government is also required in ensuring the success of the BOT project.

Keywords: BOT project, risks management, concessionaire, consortium.

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Authors: Hassan Masoumi, Rashed Alavi

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Wheat is one of the strategic crops in Iran, on which the household food basket is highly dependent. Although this crop is cultivated and produced in almost all provinces of the country, its production efficiency is lower than the global and regional averages due to the lack of optimal use of allocated resources. In this research, which was carried out with a documentary and library method, first, the total and partial productivity indices of irrigated wheat production were calculated in large, medium and small exploitation scales in different provinces of the country, and then the provinces were clustered in terms of these indices. The results showed that the total productivity of production factors had a direct correlation with the scale of exploitation, so that with the increase in the size of exploitations, the total productivity index increased. On the scale of small exploitations, North Khorasan, Zanjan, Chaharmahal and Bakhtiari Province, on a medium scale, Chaharmahal and Bakhtiari Province and on the scale of large exploitations, Zanjan, Chaharmahal and Bakhtiari provinces, Kohkiloyeh and Boyer Ahmad and North Khorasan, with better use of production resources compared to other provinces, were placed in the best cluster in terms of total productivity index. The high total productivity index in Zanjan, Chaharmahal and Bakhtiari Province is related to the higher productivity of factors such as mechanization and land in these provinces. Finally, the methods of using these factors in productive provinces, along with technical and specialized regional guidelines, can facilitate the improvement of productivity in less productive provinces.

Keywords: Clustering, Irrigated wheat, Iran, total productivity.

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

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Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

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The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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Authors: Mohammad Abdollahi

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Tomato (Lycopersicon esculentum Mill.) is one of the most popular, widely grown and the second most important vegetable crop, after potatoes. Nematodes have been identified as one of the major pests affecting tomato production throughout the world. The most destructive nematodes are the genus Meloidogyne. Most widespread and devastating species of this genus are M. incognita, M. javanica, and M. arenaria. These species can cause complete crop loss under adverse growing conditions. There are several potential methods for management of the root knot nematodes. Although the chemicals are widely used against the phytonematodes, because of hazardous effects of these compounds on non-target organisms and on the environment, there is a need to develop other control strategies. Nowadays, non-chemical measures are widely used to control the plant parasitic nematodes. Biocontrol of phytonematodes is an important method among environment-friendly measures of nematode management. There are some soil-inhabiting fungi that have biocontrol potential on phytonematodes, which can be used in nematode management program. The fungus Metarhizium anisopliae, originally is an entomopathogenic bioagent. Biocontrol potential of this fungus on some phytonematodes has been reported earlier. Recently, use of organic soil amendments as well as the use of bioagents is under special attention in sustainable agriculture. This research aimed to reduce the pesticide use in control of root-knot nematode, Meloidogyne javanica in tomato. The effects of M. anisopliae IMI 330189 and different levels of oak tree debris on M. javanica were determined. The combination effect of the fungus as well as the different rates of soil amendments was determined. Pots were filled with steam pasteurized soil mixture and the six leaf tomato seedlings were inoculated with 3000 second stage larvae of M. javanica/kg of soil. After eight weeks, plant growth parameters and nematode reproduction factors were compared. Based on the results of our experiment, combination of M. anisopliae IMI 330189 and oak debris caused more than 90% reduction in reproduction factor of nematode, at the rates of 100 and 150 g/kg soil (P ≤ 0.05). As compared to control, the reduction in number of galls was 76%. It was 86% for nematode reproduction factor, showing the significance of combined effect of both tested agents. Our results showed that plant debris can increase the biological activity of the tested bioagent. It was also proved that there was no adverse effect of oak debris, which potentially has antimicrobial activity, on antagonistic power of applied bioagent.

Keywords: Biological control, nematode management, organic soil, Quercus branti, root knot nematode, soil amendment.

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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Authors: Simeon Karafolas, Maciej Woźniak

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Mostly of public financing programs at national and regional level are funded from European Union sources. EU can participate directly to a national and regional program (example LEADER initiative, URBAN…) or indirectly by funding regional or national funds.Funds from European Union are provided from EU multiannual financial framework form which the annual budget is programmed. The adjusted program 2007-2013 of the EU considered commitments of almost 1 trillion Euros for the EU-28 countries. Provisions of the new program 2014-2020 consider commitments of more than 1 trillion Euros. Sustainable growth, divided to Cohesion and Competitiveness for Growth an Employment, is one of the two principal categories; the other is the preservation and management of natural resources.Through this financing process SMEs benefited of EU and public sources by receiving grants for their investments. Most of the financial instruments are available indirectly through the national financial intermediaries. Part of them is managed by the European Investment Fund.The paper focuses on the public financing to SMEs by examining case studies on divers forms of public help. It tries to distinguish the efficiency of the examined good practices and therefore try to have some conclusions on the possibility of application to other regions.

Keywords: DIFASS, financing, grants, SMEs.

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Authors: S. Kotsiantis, A. Kostoulas, S. Lykoudis, A. Argiriou, K. Menagias

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Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.

Keywords: regression algorithms, supervised machine learning.

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Authors: Wilaiwan Sornpoon, Sebastien Bonnet, Poonpipope Kasemsap, Savitri Garivait

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The understanding on the contribution of root respiration to total soil respiration is still very limited, especially for sugarcane. In this study, trenching experiments in sugarcane plantations were conducted to separate and investigate soil respiration for this crop. The measurements were performed for the whole growing period of 344 days to quantify root respiration. The obtained monitoring data showed that the respiration rate is increasing with the age of the plant, accounting for up to 29% of the total soil respiration before harvesting. The root to soil respiration ratio increased rapidly during the young seedling stage, i.e. first five months, then declined and finally got stabilized during yield formation and ripening stages, respectively. In addition, the results from the measurements confirmed that soil respiration was positively correlated with soil moisture content.

Keywords: Soil respiration, root respiration, trenching experiment, sugarcane.

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Authors: Sayed Amir Hamzeh Mirkheshti

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Offshore wind energy as a strategic renewable energy, has been growing rapidly due to availability, abundance and clean nature of it. On the other hand, budget of this project is incredibly higher in comparison with other renewable energies and it takes more duration. Accordingly, precise estimation of time and cost is needed in order to promote awareness in the developers and society and to convince them to develop this kind of energy despite its difficulties. Occurrence risks during on project would cause its duration and cost constantly changed. Therefore, to develop offshore wind power, it is critical to consider all potential risks which impacted project and to simulate their impact. Hence, knowing about these risks could be useful for the selection of most influencing strategies such as avoidance, transition, and act in order to decrease their probability and impact. This paper presents an evaluation of the feasibility of 500 MV offshore wind project in the Persian Gulf and compares its situation with uncertainty resources and risk. The purpose of this study is to evaluate time and cost of offshore wind project under risk circumstances and uncertain resources by using Monte Carlo simulation. We analyzed each risk and activity along with their distribution function and their effect on the project.

Keywords: Wind energy project; uncertain resources; risks; Monte Carlo simulation.

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Authors: S. Padmapriya, M. Tamilarasi

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Femtocells are regarded as a milestone for next generation cellular networks. As femtocells are deployed in an unplanned manner, there is a chance of assigning same resource to neighboring femtocells. This scenario may induce co-channel interference and may seriously affect the service quality of neighboring femtocells. In addition, the dominant transmit power of a femtocell will induce co-tier interference to neighboring femtocells. Thus to jointly handle co-tier and co-channel interference, we propose an interference-free power and resource block allocation (IFPRBA) algorithm for closely located, closed access femtocells. Based on neighboring list, inter-femto-base station distance and uplink noise power, the IFPRBA algorithm assigns non-interfering power and resource to femtocells. The IFPRBA algorithm also guarantees the quality of service to femtouser based on the knowledge of resource requirement, connection type, and the tolerable delay budget. Simulation result shows that the interference power experienced in IFPRBA algorithm is below the tolerable interference power and hence the overall service success ratio, PRB efficiency and network throughput are maximum when compared to conventional resource allocation framework for femtocell (RAFF) algorithm.

Keywords: Co-channel interference, co-tier interference, femtocells, guaranteed QoS, power optimization, resource assignment.

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Authors: A.R Alesaadi, M. Nafar, A.H. Gheisari

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In this paper sensitivity analysis is performed for reliability evaluation of power systems. When examining the reliability of a system, it is useful to recognize how results change as component parameters are varied. This knowledge helps engineers to understand the impact of poor data, and gives insight on how reliability can be improved. For these reasons, a sensitivity analysis can be performed. Finally, a real network was used for testing the presented method.

Keywords: sensitivity analysis, reliability evaluation, powersystems.

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Authors: Amir Gandomkar

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Kish Islands in South of Iran is located in coastal water near Hormozgan Province. Based on the wind 3-hour statistics in Kish station, the mean annual windspeed in this Island is 8.6 knot (4.3 m/s). The maximum windspeed recorded in this stations 47 knot (23.5 m/s). In 45.7 percent of recorded times, windspeed has been Zero or less than 8 knot which is not suitable to use the wind energy. But in 54.3 percent of recorded times, windspeed has been more than 8 knot and suitable to use wind energy to run turbines. In 40.2 percent of recorded times, windspeed has been between 8 to 16 knot, in 13 percent of times between 16 to 24 knot and in 1 percent of times it has been higher than 24 knot. In this station, the direction of winds higher than 8 is west and wind direction in Kish station is stable in most times of the year.With regard to high – speed and stable direction winds during the year and also shallow coasts near this is land, it is possible to build offshore wind farms near Kish Island and utilize wind energy produce the electricity required in this Island during most of the year.

Keywords: Kish Island, Wind energy, Offshore wind farm, Windspeed, Wind direction

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.

Keywords: Time-series forecasting, weather modeling.

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Authors: Masoud Rafiee, Fatemeh Abdipoor, Hosain Lari

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An attempt was made to study of nitrogen components response of corn (Zea mays L.) to drought stress. A farm research was done in RCBD as split-plot with four replications in Khorramabad, west Iran. Drought stress levels as irrigation regimes after 75 (control), 100, and 120 (stress) mm cumulative evaporation were in main plots, and four seed corn varieties include 500 (medium maturity), 647, 700, and 704 (long maturity) were as subplots. Soluble protein, nitrate and proline amino acid were measured in shoot and root at flowering stage, and grain yield was measured in harvesting stage. As the drought progressed, the amount of nitrate and proline followed an increasing trend, but soluble protein decreased in shoot and root. The highest amount of nitrate and proline was observed in longer maturity varieties than shorter ones, but decrease yield of long maturity varieties was higher than medium maturity varieties in drought condition, because of long duration of stress.

Keywords: Nitrate, Proline, Soluble protein, Yield

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Authors: U. Ben-Hamed, H. Seddighi, K. Thomas

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UK breweries generate extensive by products in the form of spent grain, slurry and yeast. Much of the spent grain is produced by large breweries and processed in bulk for animal feed. Spent brewery grains contain up to 20% protein dry weight and up to 60% fiber and are useful additions to animal feed. Bulk processing is economic and allows spent grain to be sold so providing an income to the brewery. A proportion of spent grain, however, is produced by small local breweries and is more variably distributed to farms or other users using intermittent collection methods. Such use is much less economic and may incur losses if not carefully assessed for transport costs. This study reports an economic returns of using wet brewery spent grain (WBSG) in animal feed using the Co-product Optimizer Decision Evaluator model (Cattle CODE) developed by the University of Nebraska to predict performance and economic returns when byproducts are fed to finishing cattle. The results indicated that distance from brewery to farm had a significantly greater effect on the economics of use of small brewery spent grain and that alternative uses than cattle feed may be important to develop.

Keywords: Animal Feed, Brewery Spent Grains, cattle CODE, Economic returns.

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Authors: Alexiou Dimitra, Fragkaki Maria

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The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.

Keywords: Multiple factorial correspondence analysis, principal component analysis, factor analysis, E.U.-28 countries, statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu statistics.

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Authors: J. R. Wang, W. Y. Cheng, J. S. Yeh, S. W. Chen, Y. M. Ferng, J. H. Yang, W. S. Hsu, C. Shih

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To understand the risk for dry storage concrete casks in the cask loading, transfer, and storage phase, the purpose of this research is to establish the probabilistic risk assessment (PRA) analysis methodology for dry storage concrete casks by using SAPHIRE 8 code. This analysis methodology is used to perform the study of Taiwan nuclear power plants (NPPs) dry storage system. The process of research has three steps. First, the data of the concrete casks and Taiwan NPPs are collected. Second, the PRA analysis methodology is developed by using SAPHIRE 8. Third, the PRA analysis is performed by using this methodology. According to the analysis results, the maximum risk is the multipurpose canister (MPC) drop case.

Keywords: PRA, Dry storage, concrete cask, SAPHIRE.

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Authors: L. G. Karancsi, K. Máriás

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We examined the crop yield results of hybrids in 2012. We found out that in the control treatments the lowest yield was reached with the hybrid PR37M81: 10,012 kg ha^-1. The highest yield was in case of hybrid P37N01: 11,581 kg ha^-1. As we raised the nutrient doses the lowest yield of all examined nutrient levels was in case of hybrid PR37M81. We measured at N₆₀+PK nutrient level 12,517 kg ha^-1, at N₁₂₀+PK nutrient level 12,760 kg ha^-1, and at N₁₅₀+PK nutrient level 12,535 kg ha^-1 yield results. At N₆₀+PK and N₁₂₀+PK nutrient level the highest yield was reached with the hybrid P9494 (N₆₀+PK: 13,970 kg ha^-1, N₁₂₀+PK: 13,871 kg ha^-1). In case of the N₁₅₀+PK fertilization treatment the hybrid P37N01 gave the highest yield results (13,962 kg ha^-1).

Keywords: Hybrids, maize, nutrient levels, SPAD and LAI values.

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Authors: M. Peña Aguilar Juan, E. Nava Galván Claudia, Pastrana Palma Alberto

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In this work was developed and implemented a thermal fogging disinfection system to counteract pathogens from poultry feces in agribusiness farms, to reduce mortality rates and increase biosafety in them. The control system consists of two phases for the conditioning of the farm during the sanitary break. In the first phase, viral and bacterial inactivation was performed by treating the stool dry cleaning, along with the development of a specialized product that foster the generation of temperatures above 55 °C in less than 24 hr, for virus inactivation. In the second phase, a process for disinfection by fogging was implemented, along with the development of a specialized disinfectant that guarantee no risk for the operators’ health or birds. As a result of this process, it was possible to minimize the level of mortality of chickens on farms from 12% to 5.49%, representing a reduction of 6.51% in the death rate, through the formula applied to the treatment of poultry litter based on oxidising agents used as antiseptics, hydrogen peroxide solutions, glacial acetic acid and EDTA in order to act on bacteria, viruses, micro bacteria and spores.

Keywords: Innovation, triple-helix, innovation, poultry farms.

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Authors: Saeed Rezaeian, M. Rezaee Boroon

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Nitrogen accumulates in soils during the process of fertilizer addition to promote the plant growth. When the organic matter decomposes, the form of available nitrogen produced is in the form of nitrate, which is highly mobile. The most significant health effect of nitrate ingestion is methemoglobinemia in infants under six months of age (blue baby syndrome). The mobile nutrients, like nitrate nitrogen, are not stored in the soil as the available forms for the long periods and in large amounts. It depends on the needs for the crops such as vegetables. On the other hand, the vegetables will compete actively for nitrate nitrogen as a mobile nutrient and water. The mobile nutrients must be shared. The fewer the plants, the larger this share is for each plant. Also, this nitrate nitrogen is poisonous for the people who use these vegetables. Nitrate is converted to nitrite by the existing bacteria in the stomach and the Gastro-Intestinal (GI) tract. When nitrite is entered into the blood cells, it converts the hemoglobin to methemoglobin, which causes the anoxemia and cyanosis. The increasing use of pesticides and chemical fertilizers, especially the fertilizers with nitrates compounds, which have been common for the increased production of agricultural crops, has caused the nitrate pollution in the (soil, water, and environment). They have caused a lot of damage to humans and animals. In this research, the nitrate accumulation in different kind of vegetables such as; green pepper, tomatoes, egg plants, watermelon, cucumber, and red pepper were observed in the suburbs of Mashhad, Neisabour, and Sabzevar cities. In some of these cities, the information forms of agronomical practices collected were such as; different vegetable crops fertilizer recommendations, varieties, pesticides, irrigation schedules, etc., which were filled out by some of our colleagues in the research areas mentioned above. Analysis of the samples was sent to the soil and water laboratory in our department in Mashhad. The final results from the chemical analysis of samples showed that the mean levels of nitrates from the samples of the fruit crops in the mentioned cities above were all lower than the critical levels. These fruit crop samples were in the order of: 35.91, 8.47, 24.81, 6.03, 46.43, 2.06 mg/kg dry matter, for the following crops such as; tomato, cucumber, eggplant, watermelon, green pepper, and red pepper. Even though, this study was conducted with limited samples and by considering the mean levels, the use of these crops from the nutritional point of view will not cause the poisoning of humans.

Keywords: Environmental pollution, human health, nitrate accumulations, nitrate fertilizers.

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Authors: Wang Chengcheng, Li Chuanri, Xu Fei, Guo Ying

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Aiming at most of the aviation products are facing the problem of fatigue fracture in vibration environment, we makes use of the testing result of a bracket, analysis for the structure with ANSYS-Workbench, predict the life of the bracket by different ways, and compared with the testing result. With the research on analysis methods, make an organic combination of simulation analysis and testing, Not only ensure the accuracy of simulation analysis and life predict, but also make a dynamic supervision of product life process, promote the application of finite element simulation analysis in engineering practice.

Keywords: Random vibration, finite element simulation, fatigue, frequency domain.

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Authors: Omid Gervei, Ahmad Ayatollahi, Navid Gervei

Abstract:

In this paper we present an approach for 3D face recognition based on extracting principal components of range images by utilizing modified PCA methods namely 2DPCA and bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing stage was implemented on the images to smooth them using median and Gaussian filtering. In the normalization stage we locate the nose tip to lay it at the center of images then crop each image to a standard size of 100*100. In the face recognition stage we extract the principal component of each image using both 2DPCA and (2D) 2 PCA. Finally, we use Euclidean distance to measure the minimum distance between a given test image to the training images in the database. We also compare the result of using both methods. The best result achieved by experiments on a public face database shows that 83.3 percent is the rate of face recognition for a random facial expression.

Keywords: 3D face recognition, 2DPCA, (2D) 2 PCA, Rangeimage

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Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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