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All Journal Journal of Applied Data Sciences
R., Karthick Manoj
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Design of multiband antenna for full screen smartphone using ANSYS HFSS R., Karthick Manoj; K., Suresh Kumar; T., Ananth kumar; R., Nishanth; Joseph, Abin John; Batumalay, Malathy
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.718

Abstract

The current scenario and the global trend are rapidly growing in terms of technology and connected through communication. The term communication is an extensive link and has an enormous number of inventions and technologies booming in this field. In mobile communication, numerous antennas are worked and fabricated in mobile phones. Here, in this paper, we focus on communication through mobile phones. It deals with simulating a multi-band slotted microstrip patch antenna for mobile phones with 6 GHz as the operating frequency using FR4 substrate material. This proposed antenna has resonating frequencies such as 2.732 GHz, 3.311 GHz,4.792 GHz,5.373 GHz, 6.462 GHz, 7.476 GHz, and 9.156 GHz. The parameters to be performed are VSWR, gain, directivity, return loss, and radiation pattern with the inputs as dimen-sion and frequency. The FR4 material might be used as the base substrate because flexi-bility is better, easily used for thin substrates and patch antennas, and the cost is meagre. The simulation is performed with the help of the ANSYS HFSS tool. When implemented in real-time in smartphones, the simulated output will be compatible in means of low power consumption and utilizes low area when fabricated. It is very efficient and has good performance. The antenna, thus simulated in this paper, will be proficient in a great way for the fifth-generation telecommunication field when designed further for process innovation
Automated Brain Tumor Analysis with Multimodal Fusion and Augmented Intelligence R., Karthick Manoj; S., Aasha Nandhini; Batumalay, Malathy
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.719

Abstract

Brain tumor segmentation and classification are critical tasks in medical imaging, having a major impact on spotting and treating brain tumors. In the medical field, augmented intelligence has garnered a lot of attention lately since it emphasizes how human knowledge and artificial intelligence can be combined to enhance efficiency and decision-making in applications like brain tumor identification. This research concentrates on developing a novel approach utilizing Attention U-Net and Multimodal Transformers to assist doctors with precise tumor segmentation and classification while maintaining their critical clinical judgment. Attention U-Net is used to segment brain tumor because it efficiently collects detailed spatial data while focusing on key locations compared with traditional U-Net models. Multimodal Transformers provide reliable as well as effective feature extraction when utilized for early fusion to merge data from many modalities, such as T1, T2, and FLAIR This work utilizes CycleGAN-based data augmentation to supplement limited training data, thus improving the variety and quality of the dataset. The fused multimodal features are then utilized for the segmentation of the tumor and further classified as benign and malignant using hybrid transformer. The performance of the proposed system is assessed using standard metrics like accuracy for classification and Dice Similarity Coefficient and Intersection Over Union for segmentation. The proposed approach demonstrates high effectiveness in both segmentation and classification tasks, achieving 98 % accuracy showcasing its potential as a process innovation for clinical applications.
Co-Authors Batumalay, Malathy Joseph, Abin John K., Suresh Kumar R., Nishanth S., Aasha Nandhini T., Ananth kumar