http://hdl.handle.net/2080/568 Thu, 09 Apr 2026 15:19:29 GMT 2026-04-09T15:19:29Z http://hdl.handle.net/2080/4701 Title: Raindrop Size Distribution Analysis in Active vs. Break Spells of Summer Monsoon from 2018 to 2021 over Rourkela Authors: Tharun, Dola; Seela, Balaji Kumar; Tyagi, Bhishma; Lin, Pay-Liam Abstract: This study analyzed Raindrop Size Distributions (RSD) of summer monsoon rainfall over eastern India from 2018 to 2021. Raindrops were divided into small, medium-sized drops, and large-sized drops. The findings reveal that all-sized drops were more prevalent during active spells than break spells. The Probability Distribution Function (PDF) of rain rate (R) and liquid water content (log10W), mass-weighted mean diameter (Dm), and Normalized intercept parameter (log10Nw) were analyzed. PDF of R and log10W showed a higher frequency during break spells but higher values during active spells. Conversely, the Dm and the log10Nw exhibited higher frequency and values during active spells. Convective precipitation was higher than stratiform precipitation in both active and break spells. Distinct differences between active and break spells were observed in the radar reflectivity-rainfall rate (Z–R) relation and the shape and slope (μ–Λ) relation. The presence of higher concentrations of raindrops of all sizes and the dominance of convective precipitation during active spells can be attributed to the increased Convective Available Potential Energy (CAPE) and greater liquid water content during active spells. Description: Copyright belongs to proceeding publisher Sun, 01 Sep 2024 00:00:00 GMT http://hdl.handle.net/2080/4701 2024-09-01T00:00:00Z http://hdl.handle.net/2080/4631 Title: Engineering and Resilient Properties of Local Clayey Soil Improved by Fly Ash and Cement for Pavement Subgrade Authors: Panda, Mahabir; Sahoo, Subhendu Sekhar; Naik, Niyati; Das, Aditya Kumar; Bhuyan, Prasanta Kumar Abstract: Soil for the subgrade of a pavement as represented by satisfactory engineering and strength properties, is usually preferred. Generally, poor soil for subgrade is improved by use of additives like lime, cement, etc. However, cost being a concern, locally available or waste materials like fly ash are chosen for soil improvement in the subgrade layer. This also helps in minimizing the concerns of pollution, besides reducing the cost. This motivates the authors to use fly ash with clayey soil, each locally available to reduce the plasticity and make it suitable for subgrade. This paper encompasses a systematic laboratory study of use of fly ash and ordinary Portland cement (OPC), from improvement of consistency properties to strength characteristics including resilient modulus. The present study concluded that the clayey soil modified with 30% fly ash and 2% cement (each material available locally) results in a considerably improved soil for use in the subgrade of a pavement subjected to high volume traffic. Description: Copyright belongs to proceeding publisher Sat, 01 Jun 2024 00:00:00 GMT http://hdl.handle.net/2080/4631 2024-06-01T00:00:00Z http://hdl.handle.net/2080/3737 Title: EEG Classification For Stroke Detection Using Deep Learning Networks Authors: Kumar, Suranjan; Sengupta, Anwesha Abstract: Stroke is currently a major public health concern. Hence more accurate and objective methods for diagnosis and prognosis are required to enable better clinical decision making. Electroencephalogram (EEG) is a non-invasive, low-cost method that can provide information regarding changes in the cerebral cortex throughout the recovery process following a stroke. EEG gives information on the progression of brain activity patterns. Many strategies have recently been developed to improve detection accuracy such as Support Vector Machine(SVM), Artificial Neural Network (RNN), Logistic Regression (LR), etc. VGG-16 and RESNET-50 are two non-invasive, low- cost transfer learning methods compared in this study. The results show that the proposed models can correctly classify EEG signals as stroke or not-stroke with 90% accuracy and 100% sensitivity for RESNET-50 while VGG-16 has a 90% accuracy, 100% specificity, and 100% precision. The work also compares other parameter i.e., F1-score between VGG-16 and RESNET-50 for this purpose. RESNET-50 is a major improvement over VGG-16 in terms of speed. Based on the results, this work appears to have been a success in terms of deep learning. Automation and great accuracy are achievable with this technique, which may be used in instances where Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI) examinations are not accessible. Description: Copyright belongs to proceeding publisher Wed, 01 Jun 2022 00:00:00 GMT http://hdl.handle.net/2080/3737 2022-06-01T00:00:00Z http://hdl.handle.net/2080/3351 Title: High Density Polyethylene (HDPE) and Polypropylene (PP) Polyblend: An Experimental Approach Authors: Sutar, Harekrushna; Murmu, Rabiranjan; Dutta, Chiranjit; Ozcan, Mutlu; Mishra, Subash Chandra Abstract: The present research focuses to evaluate a complete outlook of virgin high density polyethylene (HDPE) and polypropylene (PP) polyblends. Virgin PP of 10, 20, 30, 40 and 50 weight % is compounded with virgin HDPE. Tensile, Flexural and impact test specimens of virgin HDPE, Virgin PP and HDPE-PP composites are prepared via twin screw extruder and injection moulding methods as per ASTM D638-02a (Type-I), ASTM D790 and ASTM D256-A standards respectively. The mechanical properties like tensile strength, flexural strength, Izod impact strength are examined. Polymer sheets are fabricated using a two roll milling machine and compression moulding; and its electrical properties like dielectric strength, surface resistivity, volume resistivity are examined according to ASTM-D 257 standard. The study also includes effect of strain rate on tensile properties of the prepared composite at a cross head speed of 30, 40, 50, 60 and 70 mm/min. Design of experiment is conducted to find parameters dominating the tensile strength. All experiments are carried out at room temperature of 23°C and absolute humidity of 54%. Scanning electron microscopy (SEM), Atomic force microscopy (AFM) and polarised light microscopy (PLM) are used to observe the surface and crystal morphology. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) tests verify the non compatibility of both polymers. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) techniques are used to study the thermal behaviour of composites. The results manifest dielectric strength and volume resistivity decreases with addition of PP to HDPE; whereas surface resistivity increases. Co-occurring spherulites are seen for polyblends; indicating the composite to be a physical blend of continuous and dispersed phases, but on the other hand PP improves the tensile and flexural properties of HDPE. Sun, 01 Sep 2019 00:00:00 GMT http://hdl.handle.net/2080/3351 2019-09-01T00:00:00Z