Temporal dynamics of nutrient flux across hydrologic unit boundaries

The study was done in Dry Run Creek watershed, a small sub-urban watershed in the northwestern part of Black Hawk County, Iowa. Different hydrologic units like, wetland, agricultural area, urban area, and stream channels were compared in terms of nutrient transport. Soil, surface water, and groundwater samples were collected from May, 2012 to October, 2012. Among the hydrologic units, agricultural land has the highest organic matter percentages, infiltration rate, soil nitrate, and total phosphorus. High infiltration rate and amount of nutrients in agricultural soil made those areas more vulnerable to vertical infiltration of pollutants. Agricultural and urban soils had similar organic matter percentages. A constructed wetland in the study area is actively recycling nutrients from its surface water. Stream bank soil has low nitrate and phosphorus but high chloride compared to other units. In general nitrate and total phosphorus concentrations are high during the months of agricultural activities (May-July), indicating active influx from agricultural lands. Urban areas contribute significant amount of phosphorus and total suspended sediment into the stream. Spatial and temporal variations of nutrients in soil and water indicate active recycling of nutrients within the watershed and their interactions with other hydrologic units. Nutrient distribution in soil at different depth profiles indicates active vertical movement of nutrients. Though agricultural soil has high nitrate compared to urban areas, groundwater from urban areas shows high dissolved nitrate compared to agricultural areas. Total nitrate-N, phosphorus, and TSS load leaving the watershed in three months (June-August) was calculated as 2.5x105 kg, 594 kg, and 2.2x105 kg respectively. During the study period precipitation was very low and the year was unusually dry. Repetition of the study in a year of greater rainfall will give valuable information regarding the consistency of the results and effects of dry weather in nutrient transport

高純度なイオン液体合成のための電気透析によるユニバーサルな合成法

熊本大

Decision Support System for Water Management in the Besut Rice Irrigation Scheme

A decision support system (DSS) model was developed to improve decision-making with respect to water release schedules and timely water distribution in a large double cropping rice irrigation scheme. The model focuses mainly on water allocation decisions and timely water distribution. The DSS model includes data management, model management, a knowledge base and a user interface. Data management and model management systems are external to the DSS. The data management system is composed of the following subsystems: meteorological data, hydrological data, irrigation canal data, soil data and crop data. Four mathematical models; crop water, stochastic rainfall, canal simulation and water balance models were developed for the model management system. The Penman-Monteith method was applied for estimating reference evapotranspiration. Then the crop water model was developed from reference evapotranspiration and crop coefficient. Evapotranspiration was found to be 4.20 mm/day and 3.99 mm/day for off season and main season crop respectively. Crop evapotranspiration was higher during the off season crop compared to that of the main season crop, mainly as a result of prevailing weather conditions. A stochastic rainfall model was developed using 30 years daily rainfall data from six stations. A first order Markov chain was used to simulate the occurrence of rainfall, and a skewed normal distribution was applied to fit the amount of rainfall for a rainy day. The stochastic rainfall model verification was performed with a separate set of data. Results obtained showed that the model could be used to generate rainfall data in the area satisfactorily. A water balance model was utilized to determine irrigation water requirements. It was observed that a modification of the existing irrigation schedules would have saved a considerable amount of irrigation water during the main season and off season. Based on field water requirements during the pre-saturation and normal irrigation supply periods and available flows at the intake structures, canal simulation was performed using the CanalMan model. Results have shown that pre-saturation should not be done continuously unless flow rates are at least 9.00 m3/sec and 3.00 m3/sec at the Besut and Angga intake gates respectively. If the flow rates fall below these values, then pre-saturation should be done in two stages. However, when the flow rate is between 5.00 and 5.65 m3/sec at the Besut intake, pre-saturation should be done over three stages. During the normal irrigation supply period, flow rates of 5.00 m3/sec and 1.50 m3/sec at the Besut and Angga intake gates respectively, are to be maintained for the whole irrigation scheme. Otherwise selective irrigation or irrigation on a rotational basis has to be adopted.The knowledge base for the DSS was developed from the knowledge derived from domain experts as well as the results from the model management system. The models were used to extract knowledge related to aspects of irrigation water management. The knowledge extracted was checked with domain experts in order to verify the reliability of the knowledge. The knowledge extracted was then added to the final decision support system in the form of rules. The knowledge generated together with the domain experts’ knowledge, were compiled with rules and incorporated to the menu driven DSS, developed using the wxCLIPS software. The knowledge base thus created was continually tested for the consistency and appropriateness, and updated during the development stage. The DSS was evaluated to assess its decision-making capability using one-year water management data, which was not used in the development of the DSS. Based on the evaluation, it can be inferred that the DSS developed can be an effective tool for use in decisionmaking on water management under practical situations

An Agent-based Grouping Strategy for Federated Grid Computing

Characterizing users based on their requirements and forming groups among providers accordingly to deliver them the stronger quality of service is a challenge for federated grid community Federated grid computing allows providers to behave cooperatively to ensure required utility by users Grouping grid providers under such an environment thus enhance the possibility of more jobs executed whereas a single provider or organization might not be able to do the same In this paper we propose an agent-based iterative Contract Net Protocol which supports in building federated grid via negotiating distributed providers The main focus of this paper is to minimize the number of iterations using a grouping mechanism Minimizing the number of iterations would produce less communication overhead which results in the minimum queue waiting time for users to publish their jobs Simulation results further ensure the feasibility of our approach in terms of profit and resource utilization compared to that of the traditional non-grouped marke

Stochastic Rainfall Model for Irrigation Projects

Stochastic rainfall models are concerned with the time of occurrence and depth of rainfall. Various rainfall models have been using different time scales. Daily rainfall models have gained wide applicability as being appropriate for use in detailed water balance and agricultural and environmental models. In this study a stochastic daily rainfall generation model was adapted for the Besut Irrigation Scheme located in Terengganu, Malaysia. The model simulates the sequence of rainfall occurrence using the method of transitional probability matrices, while daily rainfall amount was generated using a skewed normal distribution. Rainfall data from six meteorological stations located at the Besut Irrigation Scheme were used for this model. The model parameters were estimated from historical rainfall records. The model validation was then performed with a separate set of data. Results obtained showed that the model could be used to generate rainfall data satisfactorily

Decision support tool for water management of double cropping rice system: water allocation

Besut Irrigation Scheme is one of the main rice growing areas in Malaysia. This scheme faces water scarcity especially during pre-saturation period with the traditional water supply. It is necessary to evolve an innovative approach for water distribution and management. A decision support tool was developed to improve decision-making with respect to water release policies and timely water distribution in the large double cropping rice irrigation project. The tool was designed to focus on water allocation and release decisions in rice growing area. The decision support tool includes database management, a model management, a knowledge base, and a user interface. The knowledge base of the decision support tool was developed from the knowledge derived from field experts and from the results of the model management system. This paper presents an integrated decision support tool for generating alternative water allocation based on water availability. Thus, the final output is given in the form of specific water management actions for the irrigated areas

A Universal Amplifier Module (UAM) in 0.18 µm CMOS (CMOSP18/TSMC) Technology With Some Applications in Analog Signal Processing

The amplifiers such as operational amplifier, operational transconductance amplifier, operational transresistance amplifier, current conveyor etc. are the basic building blocks in analog circuits and systems. These important basic amplifiers find wide spread applications in the integration of several electronic systems. However, different analog devices are preferred for different systems. It is difficult to use a single type of device to cater for the needs of different systems with diverse input output impedance environments. In this thesis work, a Universal Amplifier Module (UAM) is designed and implemented in a modern 0.18µm CMOS (CMOSP18/TSMC) technology and its applications toward realization of second order voltage and current – mode filters are reported. Concepts of network transposition and nullor equivalent of ideal active devices are utilized to realize both voltage and current – mode filters using the same UAM module which is able to provide all the voltage and current mode operations (such as, OP-AMP with VCVS, OTA with VCCS, OTRA with CCVS, and CCCS)

Bibliometric Analysis of the E-Journal of Library Philosophy and Practice During the Period of 2014-2018

The present study is based on the Bibliometrics analysis of the articles published in Library Philosophy and Practice (E-Journal) for the period 2014–2018. During this period, a total of 1046 scholarly papers have been published by LIS researchers around the world. The study analyzes the documents based on various bibliometric aspects like year wise contribution of articles, year wise growth of publication, average publication per author, subject wise distribution of articles, the geographical distribution of articles, authorship pattern, author productivity, degree of collaboration, reference distribution pattern and length of reference distribution. In all with an average 209.2 articles were published each year and the highest numbers (421) of articles were published in 2018. From the 35 of the world contributed countries Nigeria is in top rank with 36.33% contributions. Two authorship is leading authorship trend, and also Multi-Authored has shown the unique number of contribution with the 0. 71 rates of the degree of collaboration

Convolutional neural network training incorporating rotation-based generated patterns and handwritten numeral recognition of major Indian scripts

Handwritten numeral recognition has gained much interest in recent times because of its diverse application potentials. Bangla and Hindi are the two major languages in Indian subcontinent and a large number of population in vast land scape uses Bangla and Devnagari numeral scripts of these two languages. Well-performed handwritten numeral recognition system for Bangla and Devnagari is challenging because of similar shaped numerals in both scripts; few numerals differ from their similar ones with a very few variation even in printed form. In this study, convolutional neural network (CNN) based two different methods have been investigated for better recognition of Bangla and Devnagari handwritten numerals. Both the methods use rotation-based generated patterns along with ordinary patterns to train CNN but in two different modes. In multiple CNN case, three different training sets (one with ordinary patterns and two with clockwise and anti-clockwise rotation-based generated patterns) are prepared; three different CNNs are trained individually with each of these training sets; and their decisions are combined for final system decision. On the other hand, in the case of single CNN, combination of above three training sets is used to train one CNN. A moderated pre-processing is also employed while generating patterns from the scanned images. The proposed methods have been tested on prominent benchmark handwritten numeral datasets and have achieved remarkable recognition accuracies. The achieved recognition accuracies are found better than reported recognition accuracies of prominent existing methods; and such outperformance mounted proposed methods as better recognition systems. Moreover, CNN's performance improvement due to use of generated patterns has also been clearly identified from the presented experimental results