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Article ; Online: Neuromorphic computing spiking neural network edge detection model for content based image retrieval.

Ambuj / Machavaram, Rajendra

2024 , Page(s) 1–31

Abstract: In contemporary times, content-based image retrieval (CBIR) techniques have gained widespread acceptance as a means for end-users to discern and extract specific image content from vast repositories. However, it is noteworthy that a substantial majority ... ...

Abstract	In contemporary times, content-based image retrieval (CBIR) techniques have gained widespread acceptance as a means for end-users to discern and extract specific image content from vast repositories. However, it is noteworthy that a substantial majority of CBIR studies continue to rely on linear methodologies such as gradient-based and derivative-based edge detection techniques. This research explores the integration of bioinspired Spiking Neural Network (SNN) based edge detection within CBIR. We introduce an innovative, computationally efficient SNN-based approach designed explicitly for CBIR applications, outperforming existing SNN models by reducing computational overhead by 2.5 times. The proposed SNN-based edge detection approach is seamlessly incorporated into three distinct CBIR techniques, each employing conventional edge detection methodologies including Sobel, Canny, and image derivatives. Rigorous experimentation and evaluations are carried out utilizing the Corel-10k dataset and crop weed dataset, a widely recognized and frequently adopted benchmark dataset in the realm of image analysis. Importantly, our findings underscore the enhanced performance of CBIR methodologies integrating the proposed SNN-based edge detection approach, with an average increase in mean precision values exceeding 3%. This study conclusively demonstrated the utility of our proposed methodology in optimizing feature extraction, thereby establishing its pivotal role in advancing edge centric CBIR approaches.
Language	English
Publishing date	2024-05-06
Publishing country	England
Document type	Journal Article
ZDB-ID	1026760-8
ISSN	1361-6536 ; 0954-898X
ISSN (online)	1361-6536
ISSN	0954-898X
DOI	10.1080/0954898X.2024.2348018
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Investigating the performance of a perforated pooled circular stepped cascade aeration system for intensive aquaculture.

Roy, Subha M / Machavaram, Rajendra / Pareek, C M / Kim, Taeho

Heliyon

2024 Volume 10, Issue 5, Page(s) e26367

Abstract: Aeration plays a crucial role in aquaculture to maintain adequate dissolved oxygen (DO) levels in water, which is essential for supporting aquatic life. However, traditional aeration systems such as paddlewheel aerators or diffused air aerators often ... ...

Abstract	Aeration plays a crucial role in aquaculture to maintain adequate dissolved oxygen (DO) levels in water, which is essential for supporting aquatic life. However, traditional aeration systems such as paddlewheel aerators or diffused air aerators often come with high energy consumption, frequent maintenance, and greater operational costs. To address these challenges, this research paper presents the development and evaluation of a more sustainable and cost-effective aerator, named the perforated pooled circular stepped cascade aerator (PPCSC), for intensive aquaculture. Laboratory experiments were conducted in a masonry tank to assess the performance of the PPCSC aerator with different bottom radii (R
Language	English
Publishing date	2024-02-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e26367
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Prediction of viscoelastic properties of peanut-based 3D printable food ink.

Kadival, Amaresh / Mitra, Jayeeta / Kaushal, Manish / Machavaram, Rajendra

Journal of texture studies

2023

Abstract: Viscoelastic properties of 3D printable peanut-based food ink were investigated using frequency sweep and relaxation test. The incorporation of xanthan gum (XG) improved the shear thinning behavior (n value ranging from 0.139 to 0.261) and lowered the η*, ...

Abstract	Viscoelastic properties of 3D printable peanut-based food ink were investigated using frequency sweep and relaxation test. The incorporation of xanthan gum (XG) improved the shear thinning behavior (n value ranging from 0.139 to 0.261) and lowered the η*, G', and G'' values, thus making food ink 3D printable. The addition of XG also caused a downward shift in the relaxation curve. This study evaluates the possibility of an artificial neural network (ANN) approach as a substitute for the Maxwell three-element and Peleg model for predicting the viscoelastic behavior of food ink. The results revealed that all three models accurately predicted the decay forces. The inclusion of XG decreased the hardness and enhanced the cohesiveness, so enabling the 3D printing of food ink. The hardness was highly positively correlated with Maxwell model parameters F
Language	English
Publishing date	2023-12-05
Publishing country	England
Document type	Journal Article
ZDB-ID	242507-5
ISSN	1745-4603 ; 0022-4901
ISSN (online)	1745-4603
ISSN	0022-4901
DOI	10.1111/jtxs.12817
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Applications of gravity aeration system in aquaculture—a systematic review

Roy, Subha M. / Tanveer, Mohammad / Machavaram, Rajendra

Aquaculture international. 2022 June, v. 30, no. 3 p.1593-1621

2022

Abstract: The exponentially growing population, rapid mechanization, urbanization, and modern agricultural operations diminish water resources, resulting in water scarcity. In a non-technologically feasible manner, worldwide aquaculture development is also ... ...

Abstract	The exponentially growing population, rapid mechanization, urbanization, and modern agricultural operations diminish water resources, resulting in water scarcity. In a non-technologically feasible manner, worldwide aquaculture development is also becoming a matter of concern, responsible for water pollution. Aeration is one of the alternative methods, which help to improve dissolved oxygen (DO) in water body. Dissolved oxygen (DO) can be enhanced by both natural and artificial means, whereas artificial aeration practice is more efficient and effective. While considering the various artificial aeration systems, gravity aeration is one of the most effective and low energy cost aeration practices. Gravity aerators expand the air–water mass exchange by creating air bubbles, expanding the surface area, and fulfilling the water body’s DO. Assessment of various operating parameters (geometric and dynamic) related to gravity aeration is necessary to improve the oxygen transfer performance. However, gravity aerators have started becoming popular among the researchers and the fish aquaculturists. The main objective of this study is to present a comprehensive review of gravity aeration systems. This paper is to present a brief overview of the aeration principle and various gravity aerators that are of importance to aquaculture. In addition, the economic feasibility of gravity aeration systems over other existing aeration practices is compared.
Keywords	aeration ; air ; aquaculture ; dissolved oxygen ; economic feasibility ; energy costs ; fish ; geometry ; gravity ; mechanization ; oxygen ; surface area ; surface water ; systematic review ; urbanization ; water pollution ; water shortages
Language	English
Dates of publication	2022-06
Size	p. 1593-1621.
Publishing place	Springer International Publishing
Document type	Article ; Online
Note	Review
ZDB-ID	1176356-5
ISSN	1573-143X ; 0967-6120
ISSN (online)	1573-143X
ISSN	0967-6120
DOI	10.1007/s10499-022-00851-5
Database	NAL-Catalogue (AGRICOLA)

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Article: Economic feasibility study of aerators in aquaculture using life cycle costing (LCC) approach

Roy, Subha M. / Machavaram, Rajendra / Moulick, Sanjib / Mukherjee, C.K.

Journal of environmental management. 2022 Jan. 15, v. 302

2022

Abstract: Selection of aerator is a very important aspect in aquaculture operations. The selected aerator must be economically efficient and should be able to fulfil the requirement of oxygen supply in the pond water. In the present study, economic feasibility of ... ...

Abstract	Selection of aerator is a very important aspect in aquaculture operations. The selected aerator must be economically efficient and should be able to fulfil the requirement of oxygen supply in the pond water. In the present study, economic feasibility of nine different types of aerators, namely, perforated pooled circular stepped cascade (PPCSC), pooled circular stepped cascade (PCSC), circular stepped cascade (CSC), paddle wheel (PWA), spiral aerator (SA), propeller-aspirator-pump (PAA), submersible (SUBA), impeller aerator (IA) and air-jet aerator (AJA) was assessed based on capitalization method, a life cycle costing (LCC) approach. The results revealed that the PPCSC aerator can be considered as the most suitable aerator when dissolved oxygen (DO) content in the pond water is less than equal to 3 mg/L, and pond water volume (V) is less than 2100 m³. In other situations, mostly when pond water volume is more, IA proves to be the most suitable aerator, followed by PWA, PPCSC, and other available aerators. The sensitivity analysis conducted by using varying stocking density and capital cost also showed the same trend with regard to selection of aerators. This life cycle costing approach for selection of aerator can be implemented for any types of cultured species at any prevailing environmental conditions.
Keywords	aquaculture ; capital costs ; dissolved oxygen ; economic feasibility ; environmental management ; feasibility studies ; impellers ; oxygen
Language	English
Dates of publication	2022-0115
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2021.114037
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Economic feasibility study of aerators in aquaculture using life cycle costing (LCC) approach.

Roy, Subha M / Machavaram, Rajendra / Moulick, Sanjib / Mukherjee, C K

Journal of environmental management

2021 Volume 302, Issue Pt A, Page(s) 114037

Abstract	Selection of aerator is a very important aspect in aquaculture operations. The selected aerator must be economically efficient and should be able to fulfil the requirement of oxygen supply in the pond water. In the present study, economic feasibility of nine different types of aerators, namely, perforated pooled circular stepped cascade (PPCSC), pooled circular stepped cascade (PCSC), circular stepped cascade (CSC), paddle wheel (PWA), spiral aerator (SA), propeller-aspirator-pump (PAA), submersible (SUBA), impeller aerator (IA) and air-jet aerator (AJA) was assessed based on capitalization method, a life cycle costing (LCC) approach. The results revealed that the PPCSC aerator can be considered as the most suitable aerator when dissolved oxygen (DO) content in the pond water is less than equal to 3 mg/L, and pond water volume (V) is less than 2100 m
MeSH term(s)	Animals ; Aquaculture ; Feasibility Studies ; Fresh Water ; Life Cycle Stages ; Oxygen
Chemical Substances	Oxygen (S88TT14065)
Language	English
Publishing date	2021-11-08
Publishing country	England
Document type	Journal Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2021.114037
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Detection of Coconut Clusters Based on Occlusion Condition Using Attention-Guided Faster R-CNN for Robotic Harvesting.

Divyanth, L G / Soni, Peeyush / Pareek, Chaitanya Madhaw / Machavaram, Rajendra / Nadimi, Mohammad / Paliwal, Jitendra

Foods (Basel, Switzerland)

2022 Volume 11, Issue 23

Abstract: Manual harvesting of coconuts is a highly risky and skill-demanding operation, and the population of people involved in coconut tree climbing has been steadily decreasing. Hence, with the evolution of tree-climbing robots and robotic end-effectors, the ... ...

Abstract	Manual harvesting of coconuts is a highly risky and skill-demanding operation, and the population of people involved in coconut tree climbing has been steadily decreasing. Hence, with the evolution of tree-climbing robots and robotic end-effectors, the development of autonomous coconut harvesters with the help of machine vision technologies is of great interest to farmers. However, coconuts are very hard and experience high occlusions on the tree. Hence, accurate detection of coconut clusters based on their occlusion condition is necessary to plan the motion of the robotic end-effector. This study proposes a deep learning-based object detection Faster Regional-Convolutional Neural Network (Faster R-CNN) model to detect coconut clusters as non-occluded and leaf-occluded bunches. To improve identification accuracy, an attention mechanism was introduced into the Faster R-CNN model. The image dataset was acquired from a commercial coconut plantation during daylight under natural lighting conditions using a handheld digital single-lens reflex camera. The proposed model was trained, validated, and tested on 900 manually acquired and augmented images of tree crowns under different illumination conditions, backgrounds, and coconut varieties. On the test dataset, the overall mean average precision (mAP) and weighted mean intersection over union (wmIoU) attained by the model were 0.886 and 0.827, respectively, with average precision for detecting non-occluded and leaf-occluded coconut clusters as 0.912 and 0.883, respectively. The encouraging results provide the base to develop a complete vision system to determine the harvesting strategy and locate the cutting position on the coconut cluster.
Language	English
Publishing date	2022-12-03
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2704223-6
ISSN	2304-8158
ISSN	2304-8158
DOI	10.3390/foods11233903
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Optimizing the seed-cell filling performance of an inclined plate seed metering device using integrated ANN-PSO approach

Pareek, C.M / Tewari, V.K / Machavaram, Rajendra / Nare, Brajesh

Artificial intelligence in agriculture. 2021, v. 5

2021

Abstract: Uniform seed distribution within the row is the prime objective of precision planters for better crop growth and yield. Inclined plate planters are generally used for sowing bold seeds like maize, groundnut, chickpea, and their operating parameters like ... ...

Abstract	Uniform seed distribution within the row is the prime objective of precision planters for better crop growth and yield. Inclined plate planters are generally used for sowing bold seeds like maize, groundnut, chickpea, and their operating parameters like the forward speed of operation, the seed metering plate inclination, and the seed level in the hopper affect the cell fill and subsequently the uniform seed distribution. Therefore, to achieve precise seed distribution, these parameters need to be optimized. In the present study, out of the different optimization techniques, a new intelligent optimization technique based on the integrated ANN-PSO approach has been used to achieve the set goal. A 3–5-1 artificial neural network (ANN) model was developed for predicting the cell fill of inclined plate seed metering device, and the particle swarm optimization (PSO) algorithm was applied to obtain the optimum values of the operating parameters corresponding to 100% cell fill. The most appropriate optimal values of the forward speed of operation, the seed metering plate inclination, and the seed level in the hopper for achieving 100% cell fill were found to be 3 km/h, 50-degree, and 75% of total height, respectively. The proposed integrated ANN-PSO approach was capable of predicting the optimal values of operating parameters with a maximum deviation of 2% compared to the experimental results, thus confirmed the reliability of the proposed optimization technique.
Keywords	agriculture ; algorithms ; artificial intelligence ; chickpeas ; corn ; height ; neural networks ; peanuts ; planters ; precision ; prediction ; reliability ; seeds ; sowing
Language	English
Size	p. 1-12.
Publishing place	Elsevier B.V.
Document type	Article
Note	NAL-light
ISSN	2589-7217
DOI	10.1016/j.aiia.2020.11.002
Database	NAL-Catalogue (AGRICOLA)

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Article: Optimizing the aeration performance of a perforated pooled circular stepped cascade aerator using hybrid ANN-PSO technique

Roy, Subha M. / Pareek, C.M. / Machavaram, Rajendra / Mukherjee, C.K.

Information processing in agriculture. 2021 Sept. 21,

2021

Abstract: Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species. The performance of an aerator is generally measured in terms of standard aeration efficiency (SAE), which is significantly ... ...

Abstract	Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species. The performance of an aerator is generally measured in terms of standard aeration efficiency (SAE), which is significantly affected by the different geometric and dynamic parameters of the aerator. Therefore, to enhance the aeration performance of an aerator, these parameters need to be optimized. In the present study, a perforated pooled circular stepped cascade (PPCSC) aerator was developed, and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency. The geometric parameters include consecutive step width ratio (Wᵢ₋₁/Wᵢ) and the perforation diameter to the bottom-most radius ratio (d/Rb), whereas the dynamic parameter includes the water flow rate (Q). A 3–6-1 ANN model coupled with particle swarm optimization (PSO) approach was used to obtain the optimum values of geometric and dynamic parameters corresponding to the maximum SAE. The optimal values of the consecutive step width ratio (Wᵢ₋₁/Wᵢ), the perforation diameter to the bottom-most radius ratio (d/Rb), and the water flow rate (Q) for maximizing the SAE were found to be 1.15, 0.002 7 and 0.016 7 m³/s, respectively. The cross-validation results showed a deviation of 3.07 % between the predicted and experimental SAE values, thus confirming the adequacy of the proposed hybrid ANN-PSO technique.
Keywords	aeration ; agriculture ; algorithms ; aquaculture ; aquatic organisms ; geometry ; hybrids ; information ; neural networks ; oxygen requirement ; water flow
Language	English
Dates of publication	2021-0921
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ZDB-ID	2732690-1
ISSN	2214-3173
ISSN	2214-3173
DOI	10.1016/j.inpa.2021.09.002
Database	NAL-Catalogue (AGRICOLA)

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Article: An image processing approach for measurement of chili plant height and width under field conditions

Gupta, Chanchal / Tewari, V.K. / Machavaram, Rajendra / Shrivastava, Prateek

Journal of the Saudi Society of Agricultural Sciences. 2021 July 24,

2021

Abstract: Plant height and width is an essential phenotypic parameter that can be used not only as an indicator of overall plant growth but also used to estimate the advanced parameters such as the design of agricultural machines, estimation of yield, and site- ... ...

Abstract	Plant height and width is an essential phenotypic parameter that can be used not only as an indicator of overall plant growth but also used to estimate the advanced parameters such as the design of agricultural machines, estimation of yield, and site-specific applications. Presently, chili plant height and width are mostly measured manually, which is laborious and time-consuming process. The goal of this study was to develop and evaluate a real-time phenotyping system using an image processing approach to measure chili plant height and width under field conditions. The image processing algorithm was developed and compiled in the open-source computer vision library (OpenCV) and Python language using PyCharm as an integrated development environment (IDE). The developed image processing algorithm was evaluated in both static and field conditions in two plots of chili plants. The developed system was able to capture a valid image of the chili plant under field conditions and accurately estimate the height and width of the plant with a RMSE in the ranges of 0.30-0.60 cm. The height and width measured by the proposed image processing algorithm were strongly correlated (R² = 0.80–0.95) with manually measured values. Furthermore, the image processing approach has much more advanced features to measure the more complex geometric traits of plants.
Keywords	algorithms ; computer software ; computer vision ; geometry ; phenotype ; plant growth ; plant height
Language	English
Dates of publication	2021-0724
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ZDB-ID	2635379-9
ISSN	1658-077X
ISSN	1658-077X
DOI	10.1016/j.jssas.2021.07.007
Database	NAL-Catalogue (AGRICOLA)

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