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  • 1
    Online Resource
    Online Resource
    Screening of effective solvents for obtaining antioxidant‐rich seaweed extracts using principal component analysis
    Hindawi Limited ; 2020
    In:  Journal of Food Processing and Preservation Vol. 44, No. 9 ( 2020-09)
    Details
    In: Journal of Food Processing and Preservation, Hindawi Limited, Vol. 44, No. 9 ( 2020-09)
    Type of Medium: Online Resource
    ISSN: 0145-8892 , 1745-4549
    URL: Issue
    URL: Article
    DOI: 10.1111/jfpp.v44.9
    DOI: 10.1111/jfpp.14716
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2175273-4
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  • 2
    Online Resource
    Online Resource
    Weather Forecasting Method from Sensor Transmitted Data for Smart Cities Using IoT
    Hindawi Limited ; 2022
    In:  Scientific Programming Vol. 2022 ( 2022-9-19), p. 1-9
    Details
    In: Scientific Programming, Hindawi Limited, Vol. 2022 ( 2022-9-19), p. 1-9
    Abstract: India experiences severe weather events around the year. Severe thunderstorms occur during the premonsoon season (March-May), cyclonic storms occur over the Bay of Bengal/Arabian Sea during the premonsoon and postmonsoon seasons (October-December), and heavy rainfall occurs during the monsoon season (June-September). It causes a lot of damage to property and the lives of humans. Smart urban areas aim to improve residents’ personal satisfaction by utilizing data about urban scale procedures separated from heterogeneous information sources gathered on city-wide arrangements using sensors. The Internet of Things (IoT) is an empowering concept for forecasting weather situations on an urban scale. A multisource detecting framework influences IoT innovation to accomplish city-scale detection of climatic changes and forecasts them to citizens in a smart city. The existing models gather the data in an unstructured process that need to be structured. This is a complex task that needs to be reduced. The proposed model gathers data from various regions in a city and uses it to identify the weather regions. A novel approach is introduced to detect this climate information gathered by utilizing various sensors arranged in a city. The information gathered from the sensors is thoroughly examined to see if there is any inconsistency in weather reports in any of its key hubs, and cautions are activated to the city for prompt actions. In this proposed work, an efficient method for weather casting using an IoT mechanism is introduced, and the results state that the proposed method is effective in terms of accuracy and speed when contrasted with the traditional methodologies.
    Type of Medium: Online Resource
    ISSN: 1875-919X , 1058-9244
    URL: Article
    DOI: 10.1155/2022/1426575
    RVK:
    SA 7860
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2070004-0
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  • 3
    Online Resource
    Online Resource
    DHA and EPA Content and Fatty Acid Profile of 39 Food Fishes from India
    Hindawi Limited ; 2016
    In:  BioMed Research International Vol. 2016 ( 2016), p. 1-14
    Details
    In: BioMed Research International, Hindawi Limited, Vol. 2016 ( 2016), p. 1-14
    Abstract: Docosahexaenoic acid (DHA) is the principal constituent of a variety of cells especially the brain neurons and retinal cells and plays important role in fetal brain development, development of motor skills, and visual acuity in infants, lipid metabolism, and cognitive support and along with eicosapentaenoic acid (EPA) it plays important role in preventing atherosclerosis, dementia, rheumatoid arthritis, Alzheimer’s disease, and so forth. Being an essential nutrient, it is to be obtained through diet and therefore searching for affordable sources of these ω -3 polyunsaturated fatty acids (PUFA) is important for consumer guidance and dietary counseling. Fish is an important source of PUFA and has unique advantage that there are many food fish species available and consumers have a wide choice owing to availability and affordability. The Indian subcontinent harbors a rich fish biodiversity which markedly varies in their nutrient composition. Here we report the DHA and EPA content and fatty acid profile of 39 important food fishes (including finfishes, shellfishes, and edible molluscs from both marine water and freshwater) from India. The study showed that fishes Tenualosa ilisha , Sardinella longiceps , Nemipterus japonicus , and Anabas testudineus are rich sources of DHA and EPA. Promotion of these species as DHA rich species would enhance their utility in public health nutrition.
    Type of Medium: Online Resource
    ISSN: 2314-6133 , 2314-6141
    URL: Article
    DOI: 10.1155/2016/4027437
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2016
    detail.hit.zdb_id: 2698540-8
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  • 4
    Online Resource
    Online Resource
    Data Verification of Logical Pk-Anonymization with Big Data Application and Key Generation in Cloud Computing
    Hindawi Limited ; 2022
    In:  Journal of Function Spaces Vol. 2022 ( 2022-6-23), p. 1-10
    Details
    In: Journal of Function Spaces, Hindawi Limited, Vol. 2022 ( 2022-6-23), p. 1-10
    Abstract: Background. As more data becomes available about how frequently the cloud can be updated, a more comprehensive picture of its safety is emerging. The suggested artworks use a cloud-based gradual clustering device to cluster and refresh a large number of informational indexes in a useful manner. Purpose. Anonymization of data is done at the point of collection in order to safeguard the data. More secure than K-Anonymization, Pk-Anonymization is the area’s first randomization method. A cloud service provider (CSP) is an independent company that provides a cloud-based network and computing resources. Customers’ security and connection protection must be verified by an authority before facts may be transferred to cloud servers for storing information. Method. Logical Pk-Anonymization and key era techniques are proposed in this proposed artwork in order to verify the cloud records, as well as to store sensitive information in the cloud. Cloud-based informational indexes are used in the proposed framework, which is effective at handling large amounts of data through MapReduce; a parallel data preparation form is obtained; to get all information as new facts that joins after a while, information anonymization techniques to carry out each protection and immoderate information utilization while updating take place; information loss and clean time is reduced for substantial amounts of data. As a result, the safety and records software might be in sync.
    Type of Medium: Online Resource
    ISSN: 2314-8888 , 2314-8896
    URL: Article
    DOI: 10.1155/2022/8345536
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2861541-4
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  • 5
    Online Resource
    Online Resource
    Comparative Study on EDM Parameter Optimization for Adsorbed Si3N4–TiN using TOPSIS and GRA Coupled with TLBO Algorithm
    Hindawi Limited ; 2022
    In:  Adsorption Science & Technology Vol. 2022 ( 2022-9-30), p. 1-19
    Details
    In: Adsorption Science & Technology, Hindawi Limited, Vol. 2022 ( 2022-9-30), p. 1-19
    Abstract: Electrical discharge machining is a thermo-physical-based material removal technique. 25 combinations of process variables were formulated with the aid of Taguchi technique for EDM of adsorbed Si3N4–TiN. Machining variables like pulse current, pulse-on time, pulse-off time, dielectric pressure, and spark gap voltage varied, and impact of each variables on the performance metrics (MRR, EWR, SR, ROC, θ, CIR, and CYL) was assessed. MCDM strategies like grey relational analysis and TOPSIS are utilized to find out the ideal arrangement of machining parameters to achieve most acute productivity of the multitude of reactions. Likewise, metaheuristic algorithm in particular GRA combined with teaching-learning-based optimization algorithm is utilized for getting global optimized input factors. Important factors like pulse current, pulse-on time, and spark gap voltage characteristically affect the outputs. It is recognized that the pulse-on time and the pulse current are the most significant input factors than others. The ideal machining parameters in view of GRA and TOPSIS techniques for acquiring better output factors are I, 12 amps; PON, 7 μsec; POFF, 4 μsec; DP, 12 kg/cm2; and SV, 36 volts.
    Type of Medium: Online Resource
    ISSN: 2048-4038 , 0263-6174
    URL: Article
    DOI: 10.1155/2022/4112448
    RVK:
    VA 1500
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2017917-0
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  • 6
    Online Resource
    Online Resource
    HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images
    Hindawi Limited ; 2022
    In:  Computational Intelligence and Neuroscience Vol. 2022 ( 2022-6-28), p. 1-10
    Details
    In: Computational Intelligence and Neuroscience, Hindawi Limited, Vol. 2022 ( 2022-6-28), p. 1-10
    Abstract: The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish requires more time for catching and more resources, thus increasing the operational cost leading to low profitability. With the advent of artificial intelligence algorithms, designing intelligent algorithms for an effective prediction of fishing areas has reached new heights in terms of high accuracy (Acy) and less time. But still, predicting the location of potential fishing zones (PFZs) is always a daunting task. To reduce these issues, this work presented the novel hybrid prediction architecture of PFZs using remote sensing images. The proposed architecture integrates the deep convolutional layers and flitter bat optimized long short-term memory (FB-LSTM)-based recurrent neural networks (RNN). These convolutional layers are utilized to remove the various color features such as chlorophyll, sea surface temperature (SST), and GPS location from the satellite images, and FB-LTSM is utilized to predict the potential locations for fishing. The extensive experimentations are carried out utilizing the satellite data from Indian National Centre for Ocean Information Services (INCOIS) and implemented using TensorFlow 1.18 with Keras API. The performance metrics such as prediction Acy, precision (Pscn), recall (Rcl) or sensitivity (Sty), specificity (Sfy), and F1-score and compared with other existing intelligent learning models. From our observations, the proposed architecture (99% prediction Acy) has outperformed the other existing algorithms and finds its best place in designing an intelligent system for better predicting of PFZs.
    Type of Medium: Online Resource
    ISSN: 1687-5273 , 1687-5265
    URL: Article
    DOI: 10.1155/2022/5081541
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2388208-6
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