Daily Archives: August 29, 2025

Authors: Lalita Chouhan, Mr. Divyanshu Wagh

Abstract: Recently, the use of RF mixers has grown substantially. The Gilbert cell remains the de-facto core thanks to its high conversion gain, strong port-to-port isolation, and suppression of even-order distortion. Multi-tanh linearization implemented with multiple parallel differential transconductance stages offers excellent linearity but typically yields very low conversion gain. In contrast, current-bleeding improves both linearity and conversion gain by injecting additional bias current, at the cost of increased power consumption. Leveraging CMOS for its low cost, low static power, and compact area, we designed single-ended and differential low-noise amplifiers (LNAs) for WCDMA reception using the BSIM3v2 (Level-49) UMC 0.18-µm process in the Xcircuit open-source EDA tool. The designs prioritize high gain, low noise, good linearity, and input matching to a 50-ohm RF system.

Published by: vikaspatanker

Authors: Adesina Toheeb Damilola

Abstract: Customer Relationship Management (CRM) has become an essential strategy for large-scale organizations seeking to enhance their interactions with customers, improve satisfaction, and foster long-term loyalty. As competitive pressures increase and customer expectations evolve, enterprises recognize the vital role of CRM systems in managing vast amounts of customer data, streamlining communication, and facilitating personalized marketing strategies. This review explores the implementation of CRM in large-scale organizations, focusing on key strategies, challenges, benefits, and best practices. The integration of CRM systems involves technological, organizational, and human factors that must be comprehensively addressed to ensure successful deployment and adoption. Studies have shown that CRM implementation can lead to improved customer retention, increased revenue, and operational efficiencies, but these outcomes depend significantly on how organizations align CRM initiatives with their business goals and culture. This paper synthesizes findings from various research efforts and case studies, emphasizing the importance of strategic planning, employee involvement, and technological customization in CRM projects. Additionally, the review highlights the roles of data quality management, user training, and continuous performance evaluation as critical success factors. By offering a detailed understanding of CRM implementation dynamics, this paper provides valuable insights for practitioners and researchers interested in optimizing CRM applications within extensive organizational settings.

DOI: http://doi.org/10.5281/zenodo.16993788

Published by: vikaspatanker

Authors: Ronnel C. Mesia, Dr. John Lenon E. Agatep

Abstract: Scoliosis is a condition where the spine curves abnormally, which can cause discomfort, pain, and difficulties with movement. It is essential to detect and diagnose scoliosis as early as possible to prevent further complications and improve treatment outcomes (Brackett, 2023). The main goal of this study was to improve classification accuracy of ResNet-50 architecture in detecting scoliosis on unclothed human back images, enabling early detection and intervention to prevent the progress of the spine curvature. The modified ResNet-50 architecture in this study incorporates global average pooling and reduces the size of the fully connected layers in the original ResNet-50 architecture. The data used in this study consists of images of normal and with scoliosis unclothed human back images. The dataset was sourced from public repositories, private individuals and patients at President Ramon Magsaysay Memorial Hospital Iba, Zambales. These images were annotated and validated by medical experts from PRMMH. The Modified ResNet-50 model showed outstanding performance with slight fluctuation in validation loss similar to the findings in the study of Artates et. al (2024) that despite of minimal validation loss fluctuations the model can still be more robust and reliable. The Modified ResNet-50 model achieved impressive results and outperformed the baseline ResNet-50 across multiple evaluation metrics. The Modified ResNet-50 model reached an accuracy of ninety-seven percent (97%), both precision and recall values of ninety-six-point five percent (96.5), and F1-Score, Macro & Weighted Average of ninety-seven percent (97%). These results indicate that the model is highly effective in accurately classifying unclothed human back images.

DOI: http://doi.org/10.5281/zenodo.16992430

Published by: vikaspatanker