DEEP LEARNING-GUIDED GENOMIC PROFILING FOR BRAIN TUMOR SUBTYPING USING HYBRID FEATURE SELECTION AND ENSEMBLE CLASSIFICATION
The problem of brain tumors is a range of different subtypes, which have a variety of clinical forms, and the diagnosis and treatment of tumors is a challenging task. This paper introduces a hybrid deep learning system that combines genomic profiling with MRI image analysis to provide an effective brain tumor subtyping. The framework is initiated b...
By M. Yuvaraja, S. Sureshkumar, J. Dhanasekar, Vilas Namdeo Nitnaware, M. Sowmya, D. Kumar
INTEGRATION OF GNSS AND REMOTE SENSING TECHNIQUES FOR HIGH PRECISION GEODETIC APPLICATIONS
Geodesy is dependent on proper positioning and spatial information, and this is usually determined by GNSS and remote sensing techniques. Nevertheless, the conventional techniques are usually limited in terms of accuracy, particularly where the environment is complex. This paper explores the use of GNSS data in conjunction with remote sensing in or...
By Ankita Nihlani, Nishtha Sharma
ENHANCED U-NET ARCHITECTURE METHOD FOR SEGMENTATION OF BRAIN TUMOR FROM MRI IMAGES
Proper brain tumor segmentation is of great importance in the diagnosis and treatment planning. In this paper, the author presents an EfficientNet-modified U-Net-based system to segment the glioma in the pre-operative MRI scans using the BraTS 2018 dataset. This data consists of four types of MRI (T1, T2, T1Gd, and FLAIR). The model uses the Effici...
By P.A. Monisha, S. Sukumaran, G. Karthikeyan
SLOPE STABILITY IN UNSATURATED LOW PLASTICITY SOILS USING THE BARCELONA BASIC MODEL (BBM) AND CALIBRATION OF TRIAXIAL TEST DATA
The stability of slope in unsaturated low plasticity soils is also a major issue particularly in areas where the level of water changes. This paper looks into how the Barcelona Basic Model (BBM) applies to the evaluation of the stability of a real slope that consists of low plasticity silt in the Chilca region, Peru. There was a complete characteri...
By Luis Roberto Valderrama Moscoso, Juan Antonio Gaona Rojas, Neicer Campos Vasquez, Enzo Luigui Pacahuala Rojas, Ruben Kevin Manturano Chipana
A ROBUST FEATURE ENGINEERING ARCHITECTURE INCORPORATING HYBRID SAMPLING AND SEMANTIC-STRUCTURAL CODE AUGMENTATION
The sophistication of the contemporary code has augmented defect prediction (SDP) with vital concerns like severe imbalance in classes, high redundancy of features and failure of conventional techniques to gain the rich semantic and structural context of a source code. The model suggested within the current paper is HDA-SE-GFF that has Semantic-Enr...
By P. Bhavani, N. Danapaquiame
DIGITAL TWIN–BASED INTELLIGENT MONITORING OF INDUSTRIAL SYSTEMS USING EXPLAINABLE AI
Industrial systems increasingly rely on Industrial Internet of Things (IIoT) sensors for real-time monitoring and predictive maintenance. However, most existing digital twin–based monitoring solutions depend on static or black-box machine learning models, limiting interpretability, operator trust, and safe deployment in safety-critical enviro...
By R. Kousalya, V. Radhika, C. Thangamani, V. Deepa, Laxmi Basappa Dharmannavar
LEVERAGING NANOMATERIALS IN CHEMICAL ENGINEERING TO OPTIMIZE EFFICIENCY AND SUSTAINABILITY ACROSS MODERN INDUSTRIAL PROCESSES
Nanomaterials have distinct physicochemical characteristics of high surface area, controllable surface chemistry, and size-dependent reactivity, which can be used to fine-tune industrial chemical reactions to maximize efficiency and sustainability. The paper examines the incorporation of the following nanomaterials, namely carbon nanotubes, graphen...
By Sandeep Soni, Rajvir Saini
FRAGMENTATION-ENABLED VM MIGRATION AND ENHANCED DATA SEARCHING IN BIG DATA SERVER ENVIRONMENT
The proposed research paper suggests a hybrid system to improve speed and data extraction in a large data server setup, but the focus will be on how to maximize the use of resources and provide actionable information on the unstructured data. The architecture also incorporates fragmentation-enabled virtual machine (VM) migration and high-end data s...
By G.S. Manjula, T. Meyyappan
EXPERIMENTAL INVESTIGATION ON MECHANICAL AND FLEXURAL BEHAVIOUR OF CONCRETE WITH FOUNDRY SAND AS PARTIAL FINE AGGREGATE REPLACEMENT
Waste Foundry Sand (WFS) is the disposal that has been of great concern to the environment and this is as a result of high volumes generated in the process of metal casting. The building sector is developing eco-friendly alternatives to the natural aggregates in order to minimize environmental degradation and save natural resources. In this paper, ...
By John Sundarraj, Kesavan Govindaraj
RULE-BASED ITERATIVE PREPROCESSING WITH DEEP SIAMESE GRU–BILSTM FOR EFFICIENT DOCUMENT STREAMING
Efficient document streaming requires robust preprocessing and semantic modeling to handle noise, redundancy, and morphological variations in large-scale text data. Existing stemming and document processing techniques often fail to preserve contextual relevance, leading to reduced classification and retrieval performance. In a bid to overcome this ...
By K. Ranjit Kumar, S. Thirumaran