A CommonKADS Model Framework for Web Based Agricultural Decision Support System

Increased demand of farm products and depletion of natural resources compel the agriculture community to increase the use of Information and Communication Technology (ICT) in various farming processes. Agricultural Decision Support Systems (DSS) proved useful in this regard. The majority of available Agricultural DSSs are either crop or task specific. Less emphasis has been placed on the development of comprehensive DSS, which are non-specific regarding crops or farming processes. The crop or task specific DSSs are mainly developed with rule based or knowledge transfer based approaches. The DSSs based on these methodologies lack the ability for scaling up and generalization. The Knowledge engineering modeling approach is more suitable for the development of large and generalized DSS. Unfortunately the model based knowledge engineering approach is not much exploited for the development of Agricultural DSS. CommonKADS is one of the popular modeling frameworks used for the development of Knowledge Based System (KBS). The paper presents the organization, agent, task, communication, knowledge and design models based on the CommonKADS approach for the development of scalable Agricultural DSS. A specific web based DSS application is used for demonstrating the multi agent CommonKADS modeling approach. The system offers decision support for irrigation scheduling and weather based disease forecasting for the popular crops of India. The proposed framework along with the required expert knowledge, provides a platform on which the larger DSS can be built for any crop at a given location

Towards glass-box CNNs

With the substantial performance of neural networks in sensitive fields increases the need for interpretable deep learning models. Major challenge is to uncover the multiscale and distributed representation hidden inside the basket mappings of the deep neural networks. Researchers have been trying to comprehend it through visual analysis of features, mathematical structures, or other data-driven approaches. Here, we work on implementation invariances of CNN-based representations and present an analytical binary prototype that provides useful insights for large scale real-life applications. We begin by unfolding conventional CNN and then repack it with a more transparent representation. Inspired by the attainment of neural networks, we choose to present our findings as a three-layer model. First is a representation layer that encompasses both the class information (group invariant) and symmetric transformations (group equivariant) of input images. Through these transformations, we decrease intra-class distance and increase the inter-class distance. It is then passed through a dimension reduction layer followed by a classifier. The proposed representation is compared with the equivariance of AlexNet (CNN) internal representation for better dissemination of simulation results. We foresee following immediate advantages of this toy version: i) contributes pre-processing of data to increase the feature or class separability in large scale problems, ii) helps designing neural architecture to improve the classification performance in multi-class problems, and iii) helps building interpretable CNN through scalable functional blocks

ECALTOOL: fuzzy logic based computer program to calibrate the Hargreaves equation for accurate estimation of evapotranspiration

A reference evapotranspiration rate (ET0) is vital information for irrigation scheduling as well as plant growth modeling.  Estimation of evapotranspiration using environmental variables is a convenient approach compare to direct measurement.  Several mathematical models have been proposed for the estimation of ET0.  Among all these, the Hargreaves equation has received maximum attention of the agricultural fraternity as it needs minimum weather data.  However, requirement of minimal weather data in the Hargreaves equation makes it a simple and pragmatic model for estimation of ET0.  The minimalist approach makes the equation incapable to estimate ET0 accurately under extreme weather conditions.  The calibration or adjustment of the Hargreaves equation parameter CH and EH for different climate conditions is well accepted approach to accomplish error free estimation from the equation.  The establish calibration methods are empirical and time consuming.  Further, the results obtained by these methods are valid only for the restricted area and season only.  This paper presents Evapotranspiration CALibration TOOL (ECALTOOL), which is a fuzzy based universal computer program developed on the platform of NI LabVIEW to calibrate CH and EH.  The key features of the tool are its ability to provide calibration of ET0 for 1100 locations of 190 countries, and its user friendliness.  The performance of the tool is compared and validated against the benchmark Penman-Monteith equation as well as the experimentally calibrated values for various locations with diverse climate conditions.  Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) is in the range of 0.4856 – 1.1562 and 1.21%– 2.06% respectively.  The calibrated values of CH and EH are proved to be accurate in comparison with experimentally carried out calibration.  The developed tool eliminates the need of location specific experimental calibration process for the Hargreaves equation.Keywords: evapotranspiration, fuzzy logic, Hargreaves equation, LabVIE

Triple mesh technique in repair of recurrent lumbar incisional hernia

Lumbar hernias occur infrequently and can be congenital, primary (inferior or Petit type, and superior or Grynfeltt type), post-traumatic, or incisional. They are bounded by the 12th rib, the iliac crest, the erector spinae, and the external oblique muscle. Most postoperative incisional hernias occur in nephrectomy or aortic aneurysm repair incisions for which various surgical method in context of meshplasty are available. In this case 60 yr. male hypertensive patient presented to the outpatient clinic of institute with recurrent left side lumbar incisional hernia, patient was previously operated for left side nephrolithiasis 15 years back and onlay meshplasty 2 years back for incisional hernia. The patient was operated under high risk for recurrent incisional hernia repair by triple layered meshplasties in the same sitting. Lumbar incisional hernias are often diffuse with fascial defects that are usually hard to appreciate. Computed tomography scan is the diagnostic modality of choice with adjuvant clinical findings, which allows differentiating them from abdominal wall musculature denervation atrophy complicating flank incisions. Repairing these hernias is difficult due to the surrounding structures for which our surgical approach included a triple mesh repair consisting of underlay, inlay and onlay meshplasty thereby anticipating further such incidences of incisional hernia

Synthesis and anti-tubercular activity of novel pyrazol-5(H)-one derivatives

In the present investigation, a series of 1-isonicotinoyl-3-methyl-4-(2-(substituted-phenyl)hydrazono)-1H-pyrazol-5(H)-ones were synthesized by the reaction between isonicotinohydrazide with substituted ethylacetoacetate derivatives using acetic acid as solvent which yielded substituted pyrazol-5(H)-one derivatives. Newly synthesized compounds were tested for their in vitro anti-tubercular activity against Mycobacterium tuberculosis H37Rv using the BACTEC 460 radiometric system. Among the synthesized compounds, 4-(2-(2,6-dichlorophenyl)hydrazono)-1-isonicotinoyl-3-methyl-1H-pyrazol-5(4H)-one and 4-(2-(1-isonicotinoyl-3-methyl-5-oxo-1H-pyrazol-4(5H)-ylidene)hydrazinyl) benzene-sulfonamide were found to be more active agent against M. tuberculosis H37Rv with minimum inhibitory concentration of 0.0034, 0.0032 µM at actual MIC 1.66 and 1.64 µg/mL, respectively

A CommonKADS Model Framework for Web Based Agricultural Decision Support System

Increased demand of farm products and depletion of natural resources compel the agriculture community to increase the use of Information and Communication Technology (ICT) in various farming processes. Agricultural Decision Support Systems (DSS) proved useful in this regard. The majority of available Agricultural DSSs are either crop or task specific. Less emphasis has been placed on the development of comprehensive DSS, which are non-specific regarding crops or farming processes. The crop or task specific DSSs are mainly developed with rule based or knowledge transfer based approaches. The DSSs based on these methodologies lack the ability for scaling up and generalization. The Knowledge engineering modeling approach is more suitable for the development of large and generalized DSS. Unfortunately the model based knowledge engineering approach is not much exploited for the development of Agricultural DSS. CommonKADS is one of the popular modeling frameworks used for the development of Knowledge Based System (KBS). The paper presents the organization, agent, task, communication, knowledge and design models based on the CommonKADS approach for the development of scalable Agricultural DSS. A specific web based DSS application is used for demonstrating the multi agent CommonKADS modeling approach. The system offers decision support for irrigation scheduling and weather based disease forecasting for the popular crops of India. The proposed framework along with the required expert knowledge, provides a platform on which the larger DSS can be built for any crop at a given location

A CommonKADS Model Framework for Web Based Agricultural Decision Support System

Increased demand of farm products and depletion of natural resources compel the agriculture community to increase the use of Information and Communication Technology (ICT) in various farming processes. Agricultural Decision Support Systems (DSS) proved useful in this regard. The majority of available Agricultural DSSs are either crop or task specific. Less emphasis has been placed on the development of comprehensive DSS, which are non-specific regarding crops or farming processes. The crop or task specific DSSs are mainly developed with rule based or knowledge transfer based approaches. The DSSs based on these methodologies lack the ability for scaling up and generalization. The Knowledge engineering modeling approach is more suitable for the development of large and generalized DSS. Unfortunately the model based knowledge engineering approach is not much exploited for the development of Agricultural DSS. CommonKADS is one of the popular modeling frameworks used for the development of Knowledge Based System (KBS). The paper presents the organization, agent, task, communication, knowledge and design models based on the CommonKADS approach for the development of scalable Agricultural DSS. A specific web based DSS application is used for demonstrating the multi agent CommonKADS modeling approach. The system offers decision support for irrigation scheduling and weather based disease forecasting for the popular crops of India. The proposed framework along with the required expert knowledge, provides a platform on which the larger DSS can be built for any crop at a given location

<span style="font-size:13.0pt;font-family: "Times New Roman","serif";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Filled and unfilled glass/jute-epoxy methacrylate of 1,1’-bis(4-hydroxy phenyl) cyclohexane composites: Mechanical and electrical properties</span>

153-157<span style="font-size:11.0pt;font-family: " times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" hi"="" lang="EN-GB">Epoxy methacrylate of 1,1’-bis(4-hydroxyphenyl)cyclohexane has been synthesized and styrenated (EMAS) for the preparation of silica and calcium carbonate filled glass and jute composites. Both jute and glass composites displayed good tensile and flexural properties. Tensile strength is found to be improved, while flexural strength decreased due to rigid and brittle nature of the filled composites. Better improvement is observed for silica filled composites. Both tensile and flexural strengths of silica filled glass composites decreased with silica content in the composites. For calcium carbonate filled glass composites, tensile strength is found to increase with filler content up to 6% and then it is decreased with increasing filler content. For silica filled jute composites electric strength is found to increase with filler content. Calcium carbonate filled jute composites show electric strength to increase with filler content up to 6% and then it is found to decrease. For silica filled glass composites, electric strength is found to increase with filler content up to 4% and then it is decreased with filler content. For calcium carbonate filled glass composites, it is found to increase with filler content. Practically no effect of filler content is observed on volume resistivity of filled jute composites. Silica filler caused almost doubled improvement of volume resistivity. For calcium carbonate filled glass composites volume resistivity is found to increase with filler content. Comparatively calcium carbonate filled composites show better tensile and flexural properties than those of silica filled composites, while silica filled composites show somewhat better electrical properties than those of calcium carbonate filled composites. Composites may find their applications as low load bearing housing units in building and construction industries as well as in electrical and electronic industries as insulating materials.</span