Monte Carlo Studies of the GCT Telescope for the Cherenkov Telescope Array

The GCT is an innovative dual-mirror solution proposed for the small-size telescopes for CTA, capable of imaging primary cosmic gamma-rays from below a TeV to hundreds of TeV. The reduced plate scale resulting from the secondary optics allows the use of compact photosensors, including multi-anode photomultiplier tubes or silicon photomultipliers. We show preliminary results of Monte Carlo simulations using the packages CORSIKA and Sim_telarray, comparing the relative performance of each photosensor type. We also investigate the effect of the secondary optics in terms of optical performance, image resolution and camera response. With the ongoing commissioning of the prototype structure and camera, we present the preliminary expected performance of GCT.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Correspondence - Members of The Writer\u27s Club, Inc. from Victor B. Daly

Letter to the Members of The Writer\u27s Club, Inc. from the Former President, Victor B. Daly regarding a farewell party to the Club nd Madeline.https://dh.howard.edu/wci_docs/1011/thumbnail.jp

Newsclippings - D.C. Employment Trends

https://dh.howard.edu/wci_docs/1024/thumbnail.jp

IMPLEMENTATION OF FACE RECOGNITION ATTENDANCE SYSTEM FOR PT. SUMBER KURNIA ALAM WITH MTCNN AND FACENET ALGORITHM

Attendance taking is an essential and recurring task in many organizations. Traditionally, ttendance is recorded manually using pen and paper, which can be time-consuming, prone to erros, and inefficient. With advancements in computer vision and machine learning, the process of attendance taking can be automated using face recognition technology. This project presents the implementation of a face recognition attendance system for PT. Sumber Kurnia Alam. The system is designed to replace the traditional manual method for attendance taking and to improve the accuracy and efficiency of the attendance recording process. The face recognition attendance system uses MTCNN and FaceNet algorithms, which are widely used in the field of computer vision and machine learning for face detection and recognition. The implementation of the system involves gathering a dataset of employee faces. To provide accurate detection, dataset needs to be preprocess using whitening and EXIF transformation methods. Preprocessed dataset then being used to train the smart attendance system to generate facial embeddings. The attendance recording process works by comparing facial input that has been captured using webcam by the help of OpenCV library with facial embeddings generated earlier when the training process occured. This project will provide a faster and more accurate attendance recording system with average time of 6,57 seconds difference from real time

Promoting VCU Community Solutions

This promotional project focuses on VCU Community Solutions — the new interdisciplinary initiative for education, research, and service. Since this initiative demonstrates the synergy that students, faculty, and community members can create by working together, the promotional video captures their perspectives. Through interviews and footage of community programs, the video shows how VCU Community Solutions engages university and community partners in addressing critical social issues — creating more imovative approaches by working together

The effectiveness of long-term rehabilitation programmes

As the consequences of illicit drug use become more widespread amongst all sectors of our society, the relevance of long term rehabilitation continues to grow. A review of the literature reveals that although there has been considerable debate over the last decade surrounding the effectiveness of longterm rehabilitation, especially that involving residential TCs, research still predicts better outcomes for this treatment modality. This paper will explore some of the principle reasons why long-term rehabilitation has remained so effective. It will also examine how, 12 years after its inception, the Caritas New Hope Programme in Malta is evolving into a holistic and biopsychosocial project offering a range of services to drug users in rehabilitation.peer-reviewe

The effects of a college preparatory program on social capital, student achievement, and college matriculation

With an unstable economy and non-diverse populations in STEM-related majors and fields, the United States of America is faced with unprecedented challenges in meeting the growing demands of a technical society. The lack of minorities in STEM- related fields yields untapped human resources for solving many of society’s challenges. Diversity in the workforce provides different perspectives, methods, and cognitive abilities for addressing many cultural, social, economic, and technical challenges that are present in today’s global world. Social capital represents a convergence of social networks and resources that is a worthy paradigm of continued exploration within the context of STEM educational outcomes. The purpose of this study was to examine the impact of a college preparatory program on social capital and student achievement as secondary students prepare for college. This study investigated the following: the reliability and validity of the survey used to collect social capital and demographic data; whether there was a difference in social capital for students who participate in a pre- college program versus students with similar backgrounds who do not participate in the program; and if there is a relationship between social capital and student achievement. The findings supported the literature. The survey was a reliable and valid instrument. Students who participated in a pre-college program had higher levels of social capital than non-participants. No significant results were found linking social capital and student achievement