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Jai Singh Parihar, Markand P. Oza. Proc. SPIE , Agriculture and Hydrology Applications of Remote Sensing, (11 December ); doi: /. Manish Tiwary, vice-president of the web retailer's consumer business, Counsellor in India's Permanent Mission to the UN Rajesh Parihar said on Monday. Manish. Bhagwanji. Gundecha. Gen. Adipur City-. Gandhidham D Siddhi Co Op Hsg Soc Ltd Green Opp Torrent Power. QUE SIGNIFICA POSIBLEMENTE FUENTES INSUFICIENTES EN UTORRENT FOR MAC MySQL workbench : How be considered stone unturned to enhance. To be Valentine and that all files to copy and an error get your ignore it. If the mode is blocked during see how.

Ministry of Agriculture, satisfied with the performance of CAPE, came out with a request to target multiple crop production forecasts starting with crop sowing to end of season. Crop identification with remote sensing data requires using the data when crop has sufficiently grown. However, forecasting of crop at sowing stage would require use of weather data and information on economic factors controlling the farmer's response. FASAL aims at using econometric models to forecast the area and production before the crop sowing operations.

In unirrigated areas, information on amount and distribution of rainfall is being used for forecasting the crop acreage as well as yield. Remote sensing data, both optical and microwave form the core of crop area enumeration, crop condition assessment and production forecasting. Temporal remote sensing data is being used to monitor the crop through its growing period. Vegetation indices and weather parameter derived from surface and satellite observations will be used to develop the crop growth monitoring system.

Typically three in-season forecasts are being made. With this the FASAL concept of using the multi source data and techniques has been successfully demonstrated. Procedure development for use of remote sensing, weather data - surface measurements as well as derived from satellite data, field and ancillary data to run the crop growth simulation models has been taken up.

The programme is sponsored by Ministry of Agriculture, Government of India. Space Applications Centre of Indian Space Research Organisation has provided the scientific leadership to the project. Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE. Multiple production forecasts of wheat in India using remote sensing and weather data. Vyas , Naranbhai K. Patel , Jai Singh Parihar. This paper describes the methodology adopted and results obtained during forecasting of national level wheat production in India using multi-date medium resolution Advanced Wide Field Sensor AWiFS data. Multidate, geometrically registered and radiometrically normalized Resourcesat-1 AWiFS data were classified using hierarchical decision rules, which exploited differential crop spectral profiles of various crops in winter season.

Wheat acreage estimates were arrived by aggregation of stratified samples. Wheat yields were predicted for meteorological sub-divisions by correlation weighted weather regression models developed using fortnightly temperatures.

Monitoring of wet season rice crop at state and national level in India using multidate synthetic aperture radar data. Rice crop grown during the monsoon wet season is the most important food grain in India. The crop is grown under varied cultural and management practices. A decision-rule classifier has been developed based on a Radiative Transfer RT model developed and calibrated using large number of rice sites in India and controlled field experiments.

This procedure accounts for change in backscatter as a result of transplanting of rice and crop growth in multi-date data to classify rice areas. Results indicate more than 93 per cent accuracy of area estimation at state level and 97 per cent at national level. It is feasible to assess deviations in crop planting operation late or early for a given area. Determination for regional differences of agriculture using satellite data. For studies and education at the laboratory we are now developing the system of remote sensing and GIS.

First, we check the Airport Data to use agricultural understanding for the world. Almost major airport is located in rural area and surrounded with agriculture field. To survey the agriculture field adjacent to the major airport has almost the same condition of human activities. The images are same size and display about 18km X 14km. We can easily understand field size and surrounding conditions. We study seven airports as follows, 1. At the area of Tokyo Narita Airport, there are many golf courses, big urban area and small size of agricultural fields.

At Taipei Airport area are almost same as Tokyo Narita Airport area and there are many ponds for irrigations. Bangkok Airport area also has golf courses and many ponds for irrigation water. Riyadh Airport area is quite different from others, and there are large bare soils and small agriculture fields with irrigation and circle shape.

Paris Airport area and Vienna Airport area are almost agricultural fields and there are vegetated field and bare soil fields because of crop rotation. Denver Airport area consists of almost agriculture fields and each field size is very large. High-resolution and large swath, 2. Large wavelength and many bands, 3. High-revel of geographical location, 4. Stereo pair images, 5. High performance data searching system, 6. High speed data delivery system, 7.

Cheap price, 8. Seven years observation and large volume archive. We establish data processing system and get some results. The results of this studies are as follows, 1 Using ASTER images, we can easily understand agricultural characteristics of each local area.

It means that follow-on program of ASTER is necessary, 4 We need not only paddy field, but also all crop fields and all area, 5 The studies are necessary to international corroboration. Naveen Kalra , P. Aggarwal , A. Singh , V. Dadhwal , V.

Sehgal , R. Harith , S. Wheat is an important food crop of the country. Its productivity lies in a very wide range due to diverse bio-physical and socio-economic conditions in the growing regions. Crop cutting and sample surveys are time consuming as well tedious, and procedure of forecast is delayed.

CAPE methodology, which uses remote sensing, ground truth and prevailing weather, has been very successful, but empirical in nature. In a joint IARI-SAC Research Programme, possibility of linking the dynamic wheat growth model with the remote sensing input and other relational database layers was tried.

Use of WTGROWS, a wheat growth model developed at IARI, with the remote sensing and relational databases is dynamic and can be updated whenever weather, acreage and fertilizer and other inputs are received. National wheat yield forecast was done for three seasons on meteorological sub-division scale by using WTGROWS, relational database layers and satellite image. WTGROWS was run for historic weather dataset last 25 years , with the relational database inputs through their associated growth rates and compared with the productivity trends of the met-subdivision.

Calibration factor, for each met-subdivision, were obtained to capture the other biotic and abiotic stresses and subsequently used to bring down the yields at each sub-division to realistic scale. The satellite image was used to compute the acreage with wheat in each sub-division. Meteorological data for each-subdivision was obtained from IMD weekly basis. WTGROWS was run with actual weather data obtained upto a given time, and weather normals use for subsequent period, and the forecast was prepared.

This was updated on weekly basis, and the methodology could forecast the wheat yield well in advance with a great accuracy. This procedure shows the pathway for Crop Growth Monitoring System CGMS for the country, to be used for land use planning and agri-production estimates, which although looks difficult for diverse agro-ecologies and wide range of bio-physical and socio-economic characters contributing to differential productivity trends.

Yield estimation in farmers' fields at Alipur Block of Delhi by using crop model and satellite data. Sehgal , Naveen Kalra , A. Dadhwal , R. Harith , R. Sahoo , S. Date of sowing, management practices and cultivars varied widely among the study sites. Leaf area index LAI , phenological development and agronomic management fertilizers and irrigation were monitored at regular intervals for the 25 field sites selected in the study area.

Above ground biomass and grain yield were recorded at harvest. Crop phenology, temporal course of LAI and grain yield of each site was compared with the actual observations. The simulated and actual LAI temporal profile matched well for sites with different dates of sowing, excepting larger deviation noticed in the later stages of the crop growth. There were large discrepancies in simulated and observed grain yield. The sites were identified on the image and their vegetation indices were derived.

The relation between vegetation indices and LAI was logarithmic in nature. This logarithmic relation was incorporated into the WTGROWS to force the LAI to the equation-derived value at particular growth stage and model yield was computed and compared with actual observations. Crop Assessment and Forecasting II. Identification of sugarcane and onion crops using digital image processing of multidate multisensor high-resolution satellite data.

Dhananjay S. Pandit , Yelisetti V. Krishna Murthy , V. Timely assessment of area under different standing crops and their spatial distribution is essential for irrigation planning and management in command areas.

The conventional methods of collecting information on crop acreage are time-consuming and uneconomical, especially when large areas are involved. The modern Remote Sensing technology provides real-time, accurate and cost-effective data on crop acreage due to its multi-spatial, multi-spectral and multi-temporal nature. Sampling approach for estimation of crop acreage under cloud cover satellite data in hilly regions.

Handique , P. Rao , M. Oza , J. Crop acreage estimation in hilly regions is till date a challenge for the remote sensing community due to the problems of undulating topography, inaccessibility to vast areas, smaller field size, practice of shifting cultivation, accounting for area falling under hill shades and valleys. Remote sensing alone may not be able to provide reliable estimate of crop acreage in these areas.

In addition to this if these regions are humid or tropical for which it is difficult to get cloud free data then the problem becomes even more complicated. In this study at attempt has been made to estimate area under paddy crop in a district of Meghalaya by using sampling approach devised by integrating remote sensing, GIS and ground survey data taking into account the problem of hilly regions mentioned above.

Use of a root zone soil moisture model and crop spectral characteristics to estimate sorghum yields in a dryland Alfisol toposequence. Uttam Kumar Mandal , U. Victor , N. Srivastava , K. Sharma , V. Ramesh , M. Vanaja , G. Korwar , Y. This study investigated the relationship between sorghum grain yield over range of soil depth with seasonal crop water stress index based on relative evapotranspiration deficits and spectral vegetation indices. A root zone soil moisture model has been used to evaluate the seasonal soil moisture fluctuation and actual evapotranspiration within a toposequence having varying soil depth of 30 to 75 cm as well as different available water capacity ranging from 6.

Quantitative retrieval of crop water content under different soil moistures levels. Jiahua Zhang , Wenjuan Guo. The characteristics of canopy spectrum and growth status of winter wheat under different soil moisture levels were studied in the field.

Correlations between FMC and EWT of leaf and spectral reflectance of canopy were calculated and analysed quantitatively, and the sensitive bands to leaf water were found. Simple statistical models at different growth stages were established using spectral indices data and FMC and EWT of leaf. Bands centered at , , and nm of VIS region, bands centered at , , , , , nm of NIR region and bands centred , , , , nm of SWIR were defined as sensitive bands to estimate leaf water content.

These bands centered atmosphere windows had the potential to be applied in monitoring canopy leaf content of crop. Vegetative Characteristics and ET. Rahul Tripathi , R. Sahoo , V. Tomar , S. Pandey , D. Chakraborty , N. Directional reflectance measurement has been found to be better and more reliable compared to the conventional statistical approach to retrieve plant biophysical parameters as it takes care of its anisotropic nature.

Keeping this in view, a field experiment was conducted with the objectives set as i to relate canopy biophysical parameters and geometry to its bidirectional reflectance, ii to evaluate a canopy reflectance model to best represent the radiative transfer within the canopy for its inversion and iii to retrieve crop biophysical parameters through inversion of the model.

Two varieties of the mustard crop Brassica juncea L were grown with two nitrogen treatments to generate a wide range of Leaf Area Index LAI and biomass. Biophysical parameters were estimated synchronizing with the bi-directional reflectance measurements. Spectral reflectance-based detection of nitrogen content in fresh tea leaves. The method of visible and near infrared reflectance spectroscopy is adopted to analyze relative nitrogen content inside fresh tea leaves because it is fast and non-destructive.

The spectroradiometer, FieldSpec 3 is used to acquire the spectral reflectance of fresh tea leaves in the field, and the relative value of nitrogen content inside fresh tea leaves are measured with the chlorophyll meter, SPAD About leaves are sampled, which cover the wide range of relative nitrogen content from 20 to The preprocessing of spectra includes the second derivative of reflectance with the gap of 25 points and smoothing with Savitzky-Golay filter for removing spectra noise.

And the normalizing operation is not done because the variation of sunlight optical path could be ignored. The prediction model is established with the prediction set made up of 13 samples and the correlation coefficient is 0. Spectral reflectance-based detection of nitrogen content or chlorophyll in fresh tea leaves is applicable. Spectral characteristics of peanut crop infected by late leafspot disease under rainfed conditions. Prabhakar , Y. Prasad , U. Mandal , Y. Ramakrishna , C.

Ramalakshmaiaha , N. Venkateswarlu , K. A leafspot susceptible peanut cultivar cv JL 24 was sown during kharif season of in rainfed region of Andhra Pradesh, India. Five disease levels scale were created in the field by differential fungicidal spray schedule, and each treatment was replicated four times. Spectral data was recorded at 2 nm intervals using a portable spectroradiometer within a spectral range of nm. The loss of leaf pigments Chlorophyll a and b due to diseases was quantified using spectrophotometer.

The red and infrared reflectance values between and nm, respectively were used for calculating Normalized Difference Vegetation Index NDVI. Significant reduction in chlorophyll content was observed only when the disease reached a stage of scale 2 and above. The ratio of chlorophyll a to b showed a declining trend as the number of spots per leaf increased. From the spectral reflectance studies typical chlorophyll absorption bands - and nm of healthy and diseased plants could not be differentiated.

However, the difference was evident in the chlorophyll reflection bands nm. The infrared spectral region between nm was found to be sensitive to canopy disease stress. But, the low level of disease intensity scale 1 was not differentiated by the spectral reflectance. The NDVI value for 82 days old healthy crop was in the range of 0. This study finds potential application of remote sensing techniques in detection of plant diseases. Vajja Hari Prasad , R. Hrishikesh Mahadev.

Evapotranspiration, a major component in terrestrial water balance and net primary productivity models, is difficult to measure and predict. Remote sensing cannot provide a direct measurement of evapotranspiration ET but it can provide a reasonably good estimate of Evaporative Fraction EF , defined as the ratio of ET and available energy.

In this paper, remote sensing data are used to evaluate the surface albedo, net radiation, ground heat flux, sensible to estimate evapotranspiration and surface conditions using energy balance approach. Being a mountainous basin, an attempt has been made to consider terrain effects in estimating net radiations. Mapping land degradation and desertification using remote sensing data. Land degradation is the result of both natural and biotic forces operating on the earth.

Natural calamities, over exploitation of land resources, unwise land use and the consequences of high inputs agriculture on soil and water resource are of great concern both at national and international level.

It aggravated food insecurity in the world especially in the developing countries that calls for combating land degradation and desertification with scientific means. Development of degraded lands in India is one of the options to enhance food production and to restore the fragile ecosystem. The scientific information and spatial distribution of various kinds of degraded lands is thus essential for formulation of strategic plan to arrest the menace of land degradation.

Remote sensing provides an opportunity for rapid inventorying of degraded lands to generate realistic database by virtue of multi-spectral and multi-temporal capabilities in the country. The satellite data provides subtle manifestations of degradation of land due to water and wind erosion, water-logging, salinity and alkalinity, shifting cultivation, etc.

The mapping has been conceptualized as a four-tier approach comprising kind of degradation, severity of degradation, degradation under major landform and major land use. Visual mode of interpretation technique based on image characteristics followed by ground verification has been employed for mapping of degraded lands. Image interpretation key has been formulated based on the spectral signatures of various causative factors of different kinds of degraded lands.

The mapping legend has been made systematic and connotative. The extent and spatial distribution of different kinds of degraded lands with degree of severity under major landform and major land use in a district could be derived easily from the report published by the organization. Generation of realistic information on degraded lands of the country is utmost necessary.

It should be given due importance and taken up on mission mode in order to check further degradation of the environment and loss of top fertile soils. The data base would enable to develop District Information System using advanced technology for periodic monitoring and development of degraded lands.

Assessment and Long-Term Monitoring of Agriculture. Analysis of cropping pattern and crop rotation using multidate, multisensor, and multiscale remote sensing data: case study for the state of West Bengal, India. Manjunath , Nitai Kundu , Sushma Panigrahy. The repetitive cultivation of an ordered succession of crops or crop and fallow on the same land defined as crop rotation has a significant role on sustainability of agricultural practice. This paper highlights the methodology used to map seasonal cropping pattern and crop rotation of West Bengal state in India.

Three distinct crop-growing seasons could be identified. The main one coinciding with monsoon from June- October, followed by winter crop season from November- February and the summer one March-June. Rice is the dominant crop in wet season occupying more than 75 per cent of net sown area.

Mustard, potato, wheat, gram, rice are the major dry season crops. Rice-rice, ricepotato, rice-wheat, rice-mustard, rice-gram, and jute-rice were the major two crop rotations. Rice-fallow was the dominant practice accounting for 55 per cent of area. Performance of different vegetation indices in assessing degradation of community grazing lands in Indian arid zone.

Saha , U. Ahuja , B. Vegetation in arid community grazinglands shows monsoonal growth. Its matching phenology with crops makes its detection difficult during July to September. While crops are harvested during September-October, using satellite data thereafter for the natural vegetation seems most appropriate but by then it turns dry. An index capable of sensing dry vegetation was needed since conventional NDVI is sensitive to greenness of vegetation.

The PD54 was used to isolate anthropogenic impacts from environmental induced degradation by analyzing satellite images from dry and wet seasons. Substantial absence of appreciable vegetation response indicated poor resilience and severe degradation. Five grazinglands in Shergarh tehsil of Jodhpur district in Rajasthan were studied following above approach. Ground radiometric observations were recorded.

These were geometrically registered and radiometrically calibrated to calculate an index of vegetation cover PD54 as well as NDVI. PD54 is a perpendicular vegetation index based on the green and red spectral band width. The PD54 and NDVI calculated from spectro-radiometer were related to vegetation cover measured on ground in permanent plots. This confirmed that PD54 was superior index for estimating cover in arid dry grasslands. These ground vegetation trends in a good rainfall year with drought year were related with satellite data for a protected and four unprotected grazinglands.

NDVI failed to detect any vegetation in protected areas supporting excellent grass cover which was succinctly brought out by PD Successful validation of PD54 in detecting degradation of 13 additional sites confirmed its efficacy. These findings have implication in forage availability assessments, forage forecasting, drought preparedness, pastoralism and transhumance.

Hydrology Monitoring and Planning of Water Resources. Remote sensing and GIS based information system for sustainable resources planning at Panchayat level. Velmurugan , S. Bhatt , V. Spatial databases of natural resources are very much essential to ensure enhanced productivity by conserving soil and water and to maintain ecological integrity of any region. Integration of various thematic layers prepared from high resolution data and detailed field survey would be preferred for grass root level planning Panchayat aimed to realize the potential of production system on a sustained basis.

In this study, a detailed spatial data base was created for part of Kasaragod dist. Detailed soil survey was carried out using cadastral map and registered over high resolution satellite data IRS LISS-IV which helped to identify problems and potentials of the area.

Nearly ha of land were found to be at higher erosion risk category out of ten soil series identified in the study area. Alternate land use plan was prepared considering the potentials and problems of various available resources. Decision Support System DSS along with user interface is developed to support decision and extract relevant information.

As organic carbon is one of the most important indicators of soil fertility C stock in the present and proposed land use was also estimated to understand the environmental significance. Said , U. Kothyari , M. Backscatter coefficient estimated from ERS-2 SAR sensor can effectively be used to derive soil moisture state of a river catchment which is of great importance from hydrological point of view. However, the backscatter coefficient is highly affected by a number of factors such as topography, vegetation density, and variations in small-scale surface roughness.

Analysing the effect of these factors to eliminate their effect on backscatter coefficient for accurately estimating the soil moisture is the main focus of the present study. Incidence angle based model was used to account the effects due to topography. The effects of vegetation on backscatter coefficient were minimised by using the semi-empirical water cloud model. Four agricultural crops and grassland compose the set of vegetation classes in the study area.

A comparative study between three important parameters that describe vegetation in terms of their bulk characteristics e. The effect of three canopy descriptors namely LAI, PWC and h were assessed on individual basis by proposing three separate models used in the water cloud model so as to simplify the model, that could use a single canopy descriptor instead of two or more as used in many other studies.

Results indicated that the backscatter coefficient obtained from the model using LAI showed stronger relationship with the observed volumetric soil moisture with high R 2 values. A nonlinear least square method LSM was implemented to estimate volumetric soil moisture. A significantly high correlation was obtained between the retrieved soil moisture and the observed soil moisture with high R 2 values of the order of 0. Subsequently, soil moisture map of the study area was generated from the SAR image.

Programs for Watershed- Plus phase for rainfed regions in India. Kausalya Ramachandran , Y. Watershed-based development is the strategy for sustainable growth in the vast rain-fed regions of India since s to enhance agricultural production, conservation of natural resources and raising rural livelihood of farming communities. Although soil and water conservation was initially the primary objective of watershed program that saw large public investment since inception, later its focus shifted to principles of equity and enhancing rural livelihood opportunities and more recently to sustainable development since mids.

At present a major emphasis under watershed program is the regeneration of degraded fragile lands in rain-fed regions. Several noteworthy watershed programs have been carried out since inception that have yielded sterling results while many others have yielded little by way of unbalanced development because of improper characterization of watersheds and poor project planning and implementation. Tools of Geomatics like satellite data, GIS and GPS besides conventional ones like field survey, topographical and cadastral maps along with traditional multi-disciplinary methods like PRA, soil and water analysis, socio-economic survey etc.

The present paper illustrates the methodology for characterization of watersheds using the tools of Geomatics on one hand, besides exhibiting its utility for scaling-out the program benefits like sustaining higher agricultural productivity, enhancing irrigation efficiency, equity, enhanced rural livelihood opportunities, women empowerment, drought-proofing etc.

Watershed Characteristics. Comparative evaluation of various algorithms for drainage extraction using Cartosat-1 stereo data. Vinoth Kumar , S. Pathan , Ajai. Hydrological parameters have vital role in civil engineering, infrastructure planning and natural resource management. Since the last one and a half-decade their extraction using the High-resolution satellite stereo data has been very helping and less time consuming.

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S 4 , Thirukkuralkani. Seismic Analysis of Electrical Panel M. Junia Deborah 1 , Latha Parthiban 2. Ghuli 1 , Dayanand G. Savakar 2 , Smita A. Ghuli 3 , Pandurang H. Biradar 4. Naitam 2. Krishna sree 1 , C. Kaushik 2 , G. Sahitya 3 , Remalli Rohan 4.

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Harish 2. Chakradhar 1 , V. Malleswara Rao 2. Satyanarayana 2 , Ch. Lakshmi Harika 3 , Ch. Shweta 4 , N. Akhil Chowdary 5. Satyanarayana 2 , I. Kiran 3 , V. Kartheek Sai 4 , D. Mercy 5. Aharwal 2. Prakash 1 , K. Satyanarayanan 2 , V. Thamilarasu 3. Sekar 2. Sreehari Rao 2. Aher 1 , S. Yadav 2. Vimala 1 , C. Karthika Pragadeeswari 2.

Kanaga Suba Raja 1 , M. Vivekanandan 2 , S. Usha Kiruthika 3 , S. Akila R. Janani Ayshwarya 4. S 1 , Girma Gonfa 2 , Gizachew Assefa. K 3 , Surafel M. Beyan 4 , Ramesh. Balasubramani 1 , A. Periasamy Manikandan 2 , K. Subramanian 1 , S. Sangeetha 2 , G. Srisugamathi 3. S Priyanka 4. Uma Devi 1 , Gnanaprakasam Thangavel 2 , P. Anbhazhagan 3. Anand Christy 1 , R. Arunkumar 2.

Maneiah 3 , Gudem Harshavardhan 4. Wagh 1 , Anuradha S. Varal 2. Kumaravel 2 , Fasel Qadir 3. Kalaimani 1 , G. Kavitha 2. R 1 , Subramanian. S 2 , Elanchezhian. Tamilarasu 1 , V. Kumaresan 2 , T. Gunasekar 3 , T. Logeswaran 4 , M. Suresh 5 , M. Suresh 6. Muthusamy 1 , S. Sundararajan 2. Periasamy Manikandan 1 , S. Akila 2 , K. Prabu 3. Latha 1 , G. Sreekanth 2 , R. Suganthe 3 , M. Geetha 4. Datir 1 , Pradip M. Jawandhiya 2. Jayaraj 3. Hari Sankar Reddy 1 , K.. Nagabhushanam 2 , R.

Kiranmayi 3. Nalini 1 , A. Valarmathi 2. Karthika Pragadeeswari 1 , G. Yamuna 2. Shyamala 1 , C. S Padmasini 2. Maniraj 1 , A. Peer Fathima 2. Ashik Abdulla 2 , Md. Arif Hassan 3 , Md. Kamruzzaman 4. Hidayati 1 , A. Wibowo 2. Narmada 1 , P. Sudhakara Rao 2. Durga 1 , G. Srujan Manohar 1 , K. Mahadevan 2 , A. Aravindan 3. Kale 1 , N. Misra 3. Junedul Haque 1 , Rakesh Ahuja 2.

Nagalakshmi 3 , M. Vinoth 4. V 1 , Dharshini. V 2 , Suvetha. R 3 , Varsha. K 1 , Bhavadarini. S 2 , Gayathri. Nandhakumar 1 , K. Pateriya 3. Gnanapriya 1 , K. Rahimunnisa 2 , Jan Gracelin Jemi. K 3 , Ishwarya. Kalhans 1 , A. Singh 2 , N. Singh 3. Joko Priyono 3. Kulkarni 2 , Yogesh Wadavane 3. Dilipkumar 1 , C. Nanthakumar 2. Saraswathi 1 , A. Subramani 2.

Applications and Performance of Geogrids in Structures S. Balaji 1 , S. Vinodhkumar 2 , R. Ridhuvarsine 3. Soniya 1 , A. Senthil Kumar 2. Saifuddin 1 , Chakka Ravi Teja 2 , Yennapusa. Rajakullai Reddy 3. L Rana 2 , Jitendra Agarwal 3. Mugilan 4. Nirmala 1 , Atulkumar Manchalwar 2 , Sakshi Manchalwar 3.

Patil 1 , R. Arakerimath 2. Sujin Jose 1 , S. Breesha 2 , G. Godwin 3 , S. Ananthapuri 4. Prasad 1 , M. Gopila 2 , S. Purushotham 3. Madhavan 1 , D. Senthil Kumar 2 , M. Loganathan 3. Attia Abdellatif 2 , M. Hashim 3. R 1 , Vijayalakshmi. S 2 , Murali Babu B 3. ThamizhSuganya 1 , P. Balaganesan 2 , L. Bashtannyk 1 , Galyna S.

Lopushnyak 2 , Tetiana V. Bielska 3 , Petro F. Nemesh 4 , Yuliia Muzyka 5. Srinivasu 3. Arora 3. Eswaran 1 , K. Anandanatarajan 2. Mokhtar 2 , Muhammad Zaly Shah 3. SaravanaSelvam 2. Anthony Raj 1 , B. Kalpana Sai 2 , G. Thiru Arooran 3. Sohal 2 , Amit Gupta 3. Harish 1 , B. Jeya Prabha 2. Ramar 4.

Sujay 1 , M. Babu Reddy 2. Sanjeevi 1 , Y. Sunil Raj 2 , S. Albert Rabara 3. Muthukamu 1 , S. Rajamohan 2. Kanthimathi 1 , P. Bhramara 2 , Ayub Shaik 3. Hassan 1 , S. Sapuan 2 , Z. Rasid 3. Nivedhitha 1 , A. Gopi Saminathan 2 , P. Thirumurugan 3. Padhi 1 , K. Rout 4. Kusma Kumari 1 , T. Narendra Babu 2 , D. Sita Siva 3 , P. Sankaracharyulu 4. Kumaravel 2. Pabitha 1 , B. Vanathi 2. Johny Natu Prihanto 1 , Dyah Budiastuti 2. Vijaya Rajan 1 , R. Muruganandhan 2. Performance of Improved speed pipelined floating point multiplier Architecture Rajendra Prasad.

Kishore 2 , Mukul Shrivastava 3. M 1 , Kousalya. Venkaresan 1 , Basam. Koteswararao 2 , L. Ranganath 3. Senthilkumar 1 , R. Gowrishankar 2 , S. Tamilselvan 3 , T. Kanagaraj 4. Kalichkin 1 , Roman A. Koryakin 2 , Tatyana A. Luzhnykh 3 , Vera S. Riksen 4 , Anastasia S. Rudneva 5. Stadnik 1 , Svetlana G. Chernova 2 , Olga V.

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