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  • Open Access

    ARTICLE

    Design Features of Grocery Product Recognition Using Deep Learning

    E. Gothai1,*, Surbhi Bhatia2, Aliaa M. Alabdali3, Dilip Kumar Sharma4, Bhavana Raj Kondamudi5, Pankaj Dadheech6

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1231-1246, 2022, DOI:10.32604/iasc.2022.026264

    Abstract At a grocery store, product supply management is critical to its employee's ability to operate productively. To find the right time for updating the item in terms of design/replenishment, real-time data on item availability are required. As a result, the item is consistently accessible on the rack when the client requires it. This study focuses on product display management at a grocery store to determine a particular product and its quantity on the shelves. Deep Learning (DL) is used to determine and identify every item and the store's supervisor compares all identified items with a preconfigured item planning that was… More >

  • Open Access

    ARTICLE

    Extended Speckle Reduction Anisotropic Diffusion Filter to Despeckle Ultrasound Images

    P. L. Joseph Raj, K. Kalimuthu*, Sabitha Gauni, C. T. Manimegalai

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1187-1196, 2022, DOI:10.32604/iasc.2022.026052

    Abstract Speckle Reduction Anisotropic Diffusion filter which is used to despeckle ultrasound images, perform well at homogeneous region than in heterogeneous region resulting in loss of information available at the edges. Extended SRAD filter does the same, preserving better the edges in addition, compared to the existing SRAD filter. The proposed Extended SRAD filter includes the intensity of four more neighboring pixels in addition with other four that is meant for SRAD filter operation. So, a total of eight pixels are involved in determining the intensity of a single pixel. This improves despeckling performance by maintaining the information accessible at an… More >

  • Open Access

    ARTICLE

    Adaptive Resource Allocation Neural Network-Based Mammogram Image Segmentation and Classification

    P. Indra, G. Kavithaa*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 877-893, 2022, DOI:10.32604/iasc.2022.025982

    Abstract Image processing innovations assume a significant part in diagnosing and distinguishing diseases and monitoring these diseases’ quality. In Medical Images, detection of breast cancer in its earlier stage is most important in this field. Because of the low contrast and uncertain design of the tumor cells in breast images, it is still challenging to classify breast tumors only by visual testing by the radiologists. Hence, improvement of computer-supported strategies has been introduced for breast cancer identification. This work presents an efficient computer-assisted method for breast cancer classification of digital mammograms using Adaptive Resource Allocation Network (ARAN). At first, breast cancer… More >

  • Open Access

    ARTICLE

    Automatic Annotation Performance of TextBlob and VADER on Covid Vaccination Dataset

    Badriya Murdhi Alenzi, Muhammad Badruddin Khan, Mozaherul Hoque Abul Hasanat, Abdul Khader Jilani Saudagar*, Mohammed AlKhathami, Abdullah AlTameem

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1311-1331, 2022, DOI:10.32604/iasc.2022.025861

    Abstract With the recent boom in the corpus size of sentiment analysis tasks, automatic annotation is poised to be a necessary alternative to manual annotation for generating ground truth dataset labels. This article aims to investigate and validate the performance of two widely used lexicon-based automatic annotation approaches, TextBlob and Valence Aware Dictionary and Sentiment Reasoner (VADER), by comparing them with manual annotation. The dataset of 5402 Arabic tweets was annotated manually, containing 3124 positive tweets, 1463 negative tweets, and 815 neutral tweets. The tweets were translated into English so that TextBlob and VADER could be used for their annotation. TextBlob… More >

  • Open Access

    ARTICLE

    IoT Based Disease Prediction Using Mapreduce and LSQN3 Techniques

    R. Gopi1,*, S. Veena2, S. Balasubramanian3, D. Ramya4, P. Ilanchezhian5, A. Harshavardhan6, Zatin Gupta7

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1215-1230, 2022, DOI:10.32604/iasc.2022.025792

    Abstract In this modern era, the transformation of conventional objects into smart ones via internet vitality, data management, together with many more are the main aim of the Internet of Things (IoT) centered Big Data (BD) analysis. In the past few years, significant augmentation in the IoT-centered Healthcare (HC) monitoring can be seen. Nevertheless, the merging of health-specific parameters along with IoT-centric Health Monitoring (HM) systems with BD handling ability is turned out to be a complicated research scope. With the aid of Map-Reduce and LSQN3 techniques, this paper proposed IoT devices in Wireless Sensors Networks (WSN) centered BD Mining (BDM)… More >

  • Open Access

    ARTICLE

    Class Imbalance Handling with Deep Learning Enabled IoT Healthcare Diagnosis Model

    T. Ragupathi1,*, M. Govindarajan1, T. Priyaradhikadevi2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1351-1366, 2022, DOI:10.32604/iasc.2022.025756

    Abstract The rapid advancements in the field of big data, wearables, Internet of Things (IoT), connected devices, and cloud environment find useful to improve the quality of healthcare services. Medical data classification using the data collected by the wearables and IoT devices can be used to determine the presence or absence of disease. The recently developed deep learning (DL) models can be used for several processes such as classification, natural language processing, etc. This study presents a bacterial foraging optimization (BFO) based convolutional neural network-gated recurrent unit (CNN-GRU) with class imbalance handling (CIH) model, named BFO-CNN-GRU-CIH for medical data classification in… More >

  • Open Access

    ARTICLE

    Aggregated PSO for Secure Data Transmission in WSN Using Fog Server

    M. Manicka Raja1,*, S. Manoj Kumar2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1017-1032, 2022, DOI:10.32604/iasc.2022.025665

    Abstract Privacy of data in Internet of Things (IoT) over fog networks is the biggest challenge in security of Wireless communication networks. In Wireless Sensor Network (WSN), current research on fog computing with IoT is gaining popularity among IoT devices over network. Moreover, the data aggregation will reduce the energy consumption in WSN. Due to the open and hostile nature of WSN, secure data aggregation is the major issue. The existing data aggregation methods in IoT and its associated approaches are lack of limited aggregation functions, heavyweight, issues related to the performance overhead. Besides, the overload on fog node will result… More >

  • Open Access

    ARTICLE

    Performance Analysis of PTS PAPR Reduction Method for NOMA Waveform

    Himanshu Sharma1, Nidhi Gour1, Sumit Chakravarty2, Fahad Alraddady3, Mehedi Masud4, Rajneesh Pareek1, Arun Kumar5,*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1367-1375, 2022, DOI:10.32604/iasc.2022.025655

    Abstract Cellular systems utilize single and multicarrier waveforms for high-speed data transmission. The Fifth-Generation (5G) system proposes several techniques based on multicarrier waveforms. However, the Peak to Average Power Ratio (PAPR) is one of the significant concerns in advanced waveforms as it degrades the framework's efficiency. Non Orthogonal Multiple Access (NOMA) can provide massive connectivity, which is the crucial requirement of the Internet of Things (IoT). The 3rd generation tested NOMA applications in downlink and uplink transmission. However, NOMA uplink transmission in the power domain has performance degradation and is not considered a possible technique in 3rd generation power projects (3GPP).… More >

  • Open Access

    ARTICLE

    Control and Automation of Hybrid Renewable Energy Harvesting System

    R. S. Jothilakshmi*, S. Chitra Selvi

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 865-876, 2022, DOI:10.32604/iasc.2022.025643

    Abstract The hybrid renewable energy harvesting and grid integration system has been proposed and validated in this work. The proposed system uses a Wind Energy Conversion System (WECS) and a Solar Photo Voltaic Energy Conversion System (SPVECS). The WECS uses Permanent Magnet Synchronous Generator (PMSG) driven by a wind turbine. The variable frequency and variable voltage output of PMSG is rectified by Diode Bridge Rectifier (DBR) and stepped up by Super Lift Luo Converter (SLLC 1), and finally, the harvested wind energy is delivered to the Direct Current (DC) link of a Distributed Static Synchronous Compensator (DSTATCOM). Further, SPV energy is… More >

  • Open Access

    ARTICLE

    Secured Medical Data Transfer Using Reverse Data Hiding System Through Steganography

    S. Aiswarya*, R. Gomathi

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 969-982, 2022, DOI:10.32604/iasc.2022.025475

    Abstract Reversible Data Hiding (RDH) is the process of transferring secret data hidden inside cover media to the recipient so the recipient can securely retrieve both the secret data and cover media. The RDH approach is applied in this study in the field of telemedicine, and medical-secret data is conveyed privately via medical cover video. Morse code-based data encryption technique tends to encrypt the medical-secret data by compression using the Arithmetic coding technique. Discrete Shearlet transform (DST) compresses the selected frame from the medical cover video and the compressed secret data is embedded into the compressed frame using logical operations. On… More >

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