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Tools and framework for cyber-physical agricultural systems
The development of cyber-physical agricultural systems (CPASs) has created new opportunities for precision farming, sustainable food production, and efficient use of resources. CPAS leverages advanced technologies such as the Internet of Things, artificial intelligence (AI), and machine learning (ML) to collect, analyze, and utilize data to improve farming practices. However, the implementation of CPAS requires the use of various tools and frameworks to ensure seamless integration and communication between different components of the system. One of the key tools for CPAS is sensors. This chapter focuses on key tools for CPAS, such as sensors that can collect data on environmental factors, including temperature, humidity, soil moisture, and nutrient levels, enabling farmers to monitor crop growth and identify issues. The use of drones equipped with cameras and sensors can provide a birds eye view of farmland, allowing farmers to detect issues that are difficult to detect otherwise. Frameworks such as the Open Platform Communication Unified Architecture (OPC-UA) provide a standardized approach to communication between different devices and systems in agricultural systems. OPC-UA enables secure and efficient data exchange between sensors, machines, and other components, enabling the integration of various tools and frameworks within CPAS. This framework ensures that different components of CPAS can communicate seamlessly, leading to more efficient and effective farming practices. Another critical framework for CPAS is the decision support system (DSS). DSS utilizes AI and ML algorithms to analyze data from various sources and provide recommendations to farmers. For example, DSS can provide guidance on crop selection, planting dates, irrigation schedules, and pest management. This framework can assist farmers in making informed decisions that can increase yield, reduce waste, and improve sustainability. 2024 Elsevier Inc. All rights reserved. -
Tool wear and tool life estimation based on linear regression learning
Tools have remained an integral part of the society without which stimulation of certain aspects of human evolution would not have been possible. In recent times the modern tools are used in the manufacturing of high precision components. We know that the accuracy and surface finish of these components can be achieved only by the usage of accurate tools. Sharp edged tools may loosen their sharpness due to repeated usage and machining parameters. Hence to address this issue we propose a system to monitor tool wear by using the captured image of cutting tool tip. We used vision system since it is the primitive method of predicting tool wear and two main machining parameters feed rate and depth of cut. The image of flank wear cutting edge at tool tip is captured by examining under profile projector. The system uses linear regression model to calculate tool wear which is mapped onto continuous 2-D coordinates with feed rate and depth of cut as axis from a captured digital image. Thus the proposed intelligent system uses profile projector and digital image processing methods to estimate tool wear continuously and predictively like humans rather than using strict rules. By estimating tool wear continuously the machine can better perform and machine components accurately by using the resultant values of feed rate and depth of cut as a threshold which are arrived as a result. 2015 IEEE. -
Tomato Plant Disease Classification Using Transfer Learning
Detecting and categorizing diseases in tomato plants poses a significant hurdle for farmers, resulting in considerable agricultural losses and economic harm. The prompt underscores the significance of promptly identifying and classifying diseases to enact successful management strategies. Convolutional Neural Networks (CNNs) have demonstrated their effectiveness in tasks involving image classification, notably in categorizing diseases that impact tomato plants. However, CNN models can be computationally expensive to train and require large datasets of labeled images. Utilizing advanced CNN models can enhance the efficacy of classification models for tomato plant diseases, simultaneously decreasing computational expenses and the demand for extensive training data. Enhanced CNN models can be developed using a variety of techniques, such as transfer learning, data augmentation, and residual networks. This project aims to implement a tomato plant disease classification model using an enhanced convolution neural network. This work uses the lifelong learning method which is the model that allows one to learn new tasks without forgetting previous knowledge. Leveraging sophisticated CNN models can improve the effectiveness of classification models for tomato plant diseases, while also reducing computational costs and the need for extensive training data. It is beneficial for tasks where there is limited data available to train a model from scratch. 2024 IEEE. -
Tobacco Farming, Addiction, Promotion of Gender Equality, Well-being and Monopoly of the Indian Market
Womens land rights are still suppressed in India because men hold most of the land, and men decide what crops to grow. Tobacco use and farming are both detriments to ones health. It causes cancer, and cancer treatment is unavailable in the majority of Indias remote areas. On the other hand, tobacco is grown in remote regions of India, and cancer hospitals are concentrated in major cities. There are eight states in Indias north-eastern region, but only one cancer treatment facility in Guwahati, Assam. There is a need for new cancer hospitals in the north-eastern part of the country, where there is just one cancer hospital for eight states. Mindfulness training and tobacco harmful effects awareness education should be integrated into the educational curriculum and community centres. The school curriculum should include more mindfulness and psychoeducation about tobaccos detrimental effects. The pandemic situation in India and elsewhere make any community-based response difficult right now. Some parts of India, such as A&I Island, the North-Eastern region of India, and J&K, lack high-speed internet connectivity; therefore, radio, television, audio CDs, audio files, recorded videos, reading materials, and cell phones may be the best ways to reach out. Internetbased outreach is another option. A non-governmental organisation (NGO) or other organisation would be required to create regional language reading material, audio files, and video files. Given the global pandemic crisis, such programmes must be put in place as soon as possible. A team of specialists, regional language experts, local cultural experts, and volunteers would be needed to achieve these objectives. 2022 -
To study the factors of consumer involvement in fashion clothing /
International Journal Of Science And Research, Vol.3, Issue 7, pp.542-546, ISSN No: 2319-7064. -
To merge or not to merge: A case study of an EPC
Start ups face multiple challenges since inception and it is their response to these challenges that decides their success or failure. This case study examines the challenges of an EPC firm working in the field of alternative energy. It hopes to show that while initial growth may follow the path drawn by the entrepreneur, a point is reached when options for future growth inevitably face a dilemma. On the one hand getting investors to bring in funds is difficult in the absence of an order book for projects. On the other hand getting firms to give it project orders without the support of funds is also equally challenging. This is a turning point and the future of the firm depends on how it is able to surmount this challenge. However during the course of its journey the firm gets a foothold in the market and based on its unique competencies builds up a strategic position which can be exploited by a bigger player in the segment. This is in line with the Resource Based View of mergers and acquisitions that holds that gaining competitive advantage is the primary motive for an acquisition. The case follows the story of entrepreneur Deb who set up Streamline Energy, an EPC firm in 2015-16 in Navi Mumbai hoping to carve out a slice of the market in the growing field of alternative energy. 2020 Ecological Society of India. All rights reserved. -
Titanium based dual behavioral magnetic nanocomposite for ipso-hydroxylation and selective oxidation reactions under white light
A new titanium-based magnetic nanocomposite was prepared using facile method. The characterization of the prepared nanocomposite by various analytical techniques confirmed the successful coating of TiO2 on to the magnetic surface. A vital role of the prepared nanocomposite as photocatalyst for the selective oxidation of benzyl alcohols to their corresponding aldehydes and ipso-hydroxylation of aryl boronic acids under the illumination of tailor-made set up employing white light was demonstrated. The nanocatalyst was recycled and it retained excellent catalytic activity towards both the reactions upto several cycles demonstrating the excellent heterogeneous nature and possible application in the industries ensuring the sustainability. 2024 Elsevier B.V. -
Titania Doped CDs as Effective CT-DNA Binders: A Novel Fluorescent Probe via Green Synthesis
Carbon dots (CDs), which belong to the class of zero-dimensional carbon-based nanomaterials, have garnered significant interest owing to their wide array of applications spanning from the electronics industry to the healthcare sector. This work employs a facile, inexpensive approach to synthesize green luminescent carbon dots (J-10) from a potential medicinal plant named Justicia Wynaadensis by the one-step hydrothermal method. A nanocomposite (JT-10) of the CDs is prepared by adding TiO2 nanoparticles derived from green synthesis of Lavandula leaves. The J-10 and JT-10 are further characterized by X-ray Diffraction spectroscopy (XRD), Transmission Electron Microscopy (TEM), Raman analysis X-ray Photoelectron Spectroscopy (XPS), and Fourier transform infrared techniques (FTIR), UVvis spectroscopy, Photoluminescence (PL), and Fluorescence or PL lifetime analysis. The average size of synthesized CDs is 1.85 nm and exhibits an excitation-dependent fluorescence nature at 320 nm. PL lifetime analysis of J-10 and JT-10 is calculated to be 5.80 and 2.84 ns respectively. Offering these unique optical properties and biocompatibility, the synthesised material is suitable for investigating their binding affinity and interaction mechanisms with DNA. The use of JT-10 in DNA binding studies contributes to the development of sustainable and efficient nanomaterials for applications in biosensors, drug delivery, and gene therapy. 2024 Wiley-VCH GmbH. -
Tissue-Specific Profile and Activity Patterns of Glycosyl Hydrolases from Trichosanthes Anguina (Snake Gourd)
Plant glycosyl hydrolases (GH) and their function have been extensively studied using biochemical and molecular genetic approaches. GHs are involved in metabolism of various glycoconjugates specifically by the hydrolysis of glycosidic bonds and also in N-glycan processing. Several GHs have been extensively characterized from various plant sources and their diverse functional roles in cell wall polysaccharide metabolism, glycan biosynthesis and remodulation, signaling, symbiosis, secondary metabolism, etc. have been studied. However, information on tissue specific distribution of these enzymes, which is crucial for further understanding their physiological roles in plants is highly limited. In these lines, the present study was aimed at qualitative analysis of selected GHs from different tissues of a model plant, Snake Gourd (Trichosanthes anguina). The qualitative analysis of GHs such as ?-mannosidase, ?-hexosaminidase, ?-galactosidase, ?-glucosidase, ?-glucuronidase, ?-glucosidase, ?-galactosidase, ?-mannosidase and ?-fucosidase from seeds, sprouts, roots, stem, leaves, flowers and fruits of the Snake Gourd plant was carried out. Activities of different GHs varied in a tissue specific manner. The ?-mannosidase activity was maximum in ripened fruits whereas ?-hexosaminidase showed highest activity in roots. Interestingly, flowers had maximum activities of ?-glucuronidase and ?-fucosidase. The correlation analysis suggested significant correlations between various GHs which altered in tissue specific manner. (2023) Association of Carbohydrate Chemists and Technologists. -
TiO2-sodium alginate core-shell nanosystem for higher antimicrobial wound healing application
Wounds that are not properly managed can cause complications. Prompt and proper care is essential, to prevent microbial infection. Growing interest in metal oxide nanoparticles (NPs) for innovative wound treatments targeting healing and microbial infections. In this research, sodium alginate-coated titanium dioxide (TiSA) NPs are synthesized through a green co-precipitation method, combining inorganic TiO2 (Titanium dioxide) and SA (sodium alginate). Analysis via XRD and TEM revealed that the resulting TiSA NPs possessed an anatase phase and polygonal structure, respectively. Biomedical investigations demonstrated that TiSA NPs exhibited enhanced antimicrobial activity compared to the positive control, as well as its counterparts, and showed higher wound healing capabilities compared to TiO2 NPs. The antimicrobial effectiveness of TiSA NPs relied on various physicochemical factors, including small particle size, an altered band gap, and the presence of oxygen vacancies, resulting in microbial cell death. Moreover, TiSA NPs treatment demonstrated higher wound healing activity (98 1.09 %) compared to its counterparts after 24 h of incubation. Assessment of cytotoxicity on healthy fibroblast cells (L929) revealed that TiSA NPs exhibited lower toxicity compared to TiO2 NPs. These findings support the potential of TiSA NPs as promising agents for antimicrobial activity and wound healing. 2025 Elsevier B.V. -
Time-periodic heating in boussinesq-stokes suspension with three diffusing components
The effect of time-periodic heating in Boussinesq-Stokes suspension with three diffusing components has been carried out for the linear case. The correction Rayleigh number is obtained by applying the perturbation method to effectually control the convective flow by varying amplitude and frequency of modulation, and the eigenvalues are obtained by the Venezian approach. The time-periodic heating has been carried out for three cases: symmetric, asymmetric, and modulating only the lower boundary. It is found that the system is stable for smaller values whereas unstable for moderate values of frequency of modulation. 2021 by the authors. -
Time-Dependent Nonlinear Convective Flow and Radiative Heat Transfer of Cu-Al2O3-H2O Hybrid Nanoliquid with Polar Particles Suspension: a Statistical and Exact Analysis
The statistical and exact analysis of heat transfer rate and skin friction coefficient of a nonlinear convective flow of Cu ? Al2O3 ? H2O hybrid nanofluid with polar particle suspension is performed. The heat transport phenomenon includes radiative heat effect. A micropolar fluid model is accounted. Exact solutions to the governing problem are found via Laplace transform method (LTM). The heat transfer rate and skin friction are analysed critically via statistical methods like probable error and regression models. The slope of linear regression of data points for skin friction and Nusselt number is estimated to quantify the increase/decrease. The Nusselt number and thermophysical properties for twenty-four different hybrid nanofluids are presented. A novel idea of a nonlinear convective flow of Cu ? Al2O3 ? H2O hybrid nanofluid with polar particle suspension is investigated for the first time. Opposite behaviour of velocity and microrotation profile are established when the physical parameters are varied. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Time-dependent flow due to noncoaxial rotation of an infinite vertical surface subjected to an exponential space-dependent heat source: An exact analysis /
Heat Transfer Asian Research, Vol.48, Issue 7, pp.3162-3185 -
Time-dependent flow due to noncoaxial rotation of an infinite vertical surface subjected to an exponential space-dependent heat source: An exact analysis
The effect of an exponential space-dependent heat source on heat and mass transfer flow of a viscous fluid past an infinite vertical plate is examined. The flow is generated due to noncoaxial rotation of the infinite plate. The noncoaxial rotation creates sine or cosine oscillation in its plane and the fluid at infinity. The flow is assumed to be laminar and time-dependent. The mathematical formulation is developed by considering certain physical initial and boundary conditions. The Laplace transform method is utilized to obtain the exact solutions of the concentration, temperature as well as velocity fields. The Sherwood number, Nusselt number, and skin-friction coefficient are also calculated and presented in tabular form for various embedded parameters. The velocity distributions are obtained for three different cases. The obtained analytical expressions are found to be identical with published results in the limiting sense. 2019 Wiley Periodicals, Inc. -
Time Series Forecasting of Stock Market Volatility Using LSTM Networks
Forecasting stock market volatility is a pivotal concern for investors and financial institutions alike. This research paper employs Long Short-Term Memory (LSTM) networks, a potent class of recurrent neural networks, to predict stock market volatility. LSTM networks have proven adept at capturing intricate temporal dependencies, rendering them a fitting choice for time series data analysis. We commence by elucidating the notion of stock market volatility and its profound significance in financial decision-making. Traditional methodologies, such as GARCH models, exhibit shortcomings in deciphering the convoluted dynamics inherent in financial time series data. LSTM networks, with their capacity to model extended temporal relationships, present an encouraging alternative. In this study, we assemble historical stock price and trading volume data for a diverse array of assets, diligently preprocessing it to ensure its aptness for LSTM modeling. We systematically explore various network architectures, hyperparameter configurations, and input features to optimize the efficacy of our models. Our empirical investigations decisively underscore the supremacy of LSTM networks in capturing the subtleties of stock market volatility compared to conventional techniques. As the study progresses, we delve deeper into the complexities of LSTM network training, leveraging advanced techniques such as batch normalization and dropout to fortify model resilience. Moreover, we delve into the interpretability of LSTM models within the context of stock market forecasting. 2023 IEEE. -
Time series forecasting for understanding potential buyer behavior with ecommerce
Ecommerce is a platform for e-business Companies and hawkers for dynamically responding consumer demand and supply. Furthermore, responses to the consumer include blot-from-blue service with great quality of appurtenances. Moreover, the Indian retail industry is currently ranking in the world's top five concerning the growth. Thus, data is a new oil for this era of digitization. Henceforth, Cluster and distance classifier plays an important role in data-related findings. Besides, the cluster will give an identical pattern of data with the inclusion of centroid for finding out useful information. Furthermore, an already formed identical cluster pattern will be useful for mapping with another cluster. Thus, in this way cluster mapping done. Mapped cluster pattern will be useful in establishing the customer relationship with products. Moreover, it leads to the profitability of the e-commerce platform. Thereafter, cluster mapping is align with the new RFM model for getting more clarity about the consumer-buying pattern. Besides, it helps in identifying the potential buyer consumer. Moreover, time series results obtained are positive for potential buyer behavior. Thus, when time series forecasting is used on the RFM model it gives rise potential buyer loyalty with an e-commerce platform. 2020 Ecological Society of India. All rights reserved. -
Time resolved spectroscopy of a GRS 1915 + 105 flare during its unusual low state using AstroSat
Since its disco v ery in 1992, GRS 1915 + 105 has been among the brightest sources in the X-ray sky. Ho we ver, in early 2018, it dimmed significantly and has stayed in this faint state ever since. We report on AstroSat and NuSTAR observation of GRS 1915 + 105 in its unusual low/hard state during 2019 May. We performed time-resolved spectroscopy of the X-ray flares observed in this state and found that the spectra can be fitted well using highly ionized absorption models. We further show that the spectra can also be fitted using a highly relativistic reflection dominated model, where for the lamp post geometry, the X-ray emitting source is al w ays very close to the central black hole. For both interpretations, the flare can be attributed to a change in the intrinsic flux, rather than dramatic variation in the absorption or geometry. These reflection dominated spectra are very similar to the reflection dominated spectra reported for active galactic nuclei in their low flux states. 2024 The Author(s). -
Time Efficient Hash Key Generation for Blockchain Enabled Framework
Blockchain, in general, helps organizations to improve the transparency and governance by removing its shortfalls and building better control overall. Blockchain network, public or private, is a competent technology when used in order with an optimized hashing technique. In a blockchain network, one of the common issues is performance while registering any transactions. Blockchain must need to do some preliminary checks to avoid double-spending before registering the transaction. Here, we implement one of the optimization aspects of the hashing technique, which can contribute to the blockchain mining processes and save time. It enables the blockchain to perform efficiently and reliably. In addition, we examine how well different hashing algorithms perform when added to the blockchain network's processes. In this research, we analyze several hashing techniques that are employed in the blockchain and are also applied in the supply chain domain due to their efficacy in mitigating past attacks. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The proposed hashing technique achieves approx. 10-90% performance gain improvements over other existing technique. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The study also examines how the supply chain management contributes in increasing of overall lead time where process optimization or technological enhancement plays key roles in minimizing the time of some or all the processes. Lead time is one of the common issues of supply chain which impacts on overall order delivery time. We address on how the conjunction of blockchain with optimized hashing technique can address supply chain lead time issues. 2013 IEEE. -
Time allocation between paid and unpaid work among men and women: An empirical study of indian villages
The paper examines the time allocation between paid work (wage earning or self-em-ployed work generally termed as employment work) and unpaid (domestic chores/care work generally termed as non-employment work) along with wage rates, imputed earnings, and occupational structure among men and women and according to different social groups to establish the extent to which the rural labour market is discriminated by sex and social group. The major objective of the paper is to show the differential in wage income between men and women in farm and non-farm activities. The paper also shows the division of time between employment and non-employ-ment activities by men and women. The paper uses high-frequency data and applies econometric techniques to know the factors behind time allocation among different activities across gender. The study finds that males spend more hours on employment work and work at a higher wage rate than females. As a result, a vast monetary income gap between men and women is observed, even though women worked more hours if employment and non-employment activities are jointly taken into consideration. Time spent on employment work and non-employment (mainly domestic chores) has been found to vary significantly due to social identity, household wealth, land, income, educa-tion, and skill. The segregation of labour market by sex was evident in this study, with men shifting to non-farm occupations with greater monetary returns and continued dependence on womens farm activities. Enhancing the ownership of land and other assets, encouraging womens participation particularly among minorities, and improving health are some of the policy recommendations directed from this study to enhance participation in employment work and shifting towards higher wage income employment. 2021 by the authors. Licensee MDPI, Basel, Switzerland.