1,722,939 research outputs found
Spiral Fishbone Network Performance Dataset
No full textAny Author wants to use these dataset for research purpose must take permission from Sayed Asaduzzaman .THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Spiral Fishbone Network Performance Dataset
No full textAny Author wants to use these dataset for research purpose must take permission from Sayed Asaduzzaman .THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Spiral Fishbone Routing Network with Performance (Dataset)
No full textNetwork Performance Dataset for Spiral Fishbone Networ
Financial performance analysis of LP Gas Ltd. with special reference to govt. restriction on new piped gas connection to households
No full textLink to publisher's homepage at http://ijbt.unimap.edu.my/This paper examines the financial performance of LP Gas Ltd. and impact on sales
resulting from the Govt. restriction on new piped gas connection to households. The
existing literature was reviewed to establish the financial performance framework of
the company and at the same time to examine the sales (m. ton) of LP Gas Ltd before
and after the Govt. proscription of Gas connection to the households. The
performance of the company has been measured through various financial ratios i.e.
liquidity ratios, activity ratios, leverage ratios, and profitability ratios with an
analysis of market value ratios. SPSS software package is used for descriptive
statistics and to predict the sales trend linear regression method is used. To examine
the impact of Govt. restriction on piped gas connection on the sales of LP Gas: t-test
has been resorted. The analysis brings to the fore that the financial position and
operational performance of LP Gas ltd. in most cases are not satisfactory. Sales trend
shows huge incongruities over the 23 years period. Sales (m.ton) of LP Gas Ltd. have
not been significantly increased since the time after the Govt. restrictions of new gas
connection to households
Machine Learning Approaches for Skin Neoplasm Diagnosis
No full textApproaches for skin neoplasm diagnosis include physical exam, skin biopsy, lab tests of biopsy samples, and image analyses. These approaches often involve error-prone and time-consuming processes. Recent studies show that machine learning shows promise in effectively classifying skin images into different categories such as melanoma and melanocytic nevi. In this work, we investigate machine learning approaches to enhance the performance of computer-aided diagnosis (CADx) systems to diagnose skin diseases. In the proposed CADx system, generative adversarial network (GAN) discriminator is used to identify (and remove) fake images. Exploratory data analysis (EDA) is applied to normalize the original data set for preventing model overfitting. Synthetic minority oversampling technique (SMOTE) is employed to rectify class imbalances in the original data set. To accurately classify skin images, the following machine learning models are utilized: linear discriminant analysis (LDA), support vector machine (SVM), convolutional neural network (CNN), and an ensemble CNN-SVM. Experimental results using the HAM10000 data set demonstrate the ability of the machine learning models to improve CADx performance in treating skin neoplasm. Initially, the LDA, SVM, CNN, and ensemble CNN-SVM show 49%, 72%, 77%, and 79% accuracy, respectively. After applying GAN (discriminator) and SMOTE, the LDA, SVM, CNN, and ensemble CNN-SVM show 76%, 83%, 87%, and 94% accuracy, respectively. We plan to explore other machine learning models and data sets in our next endeavor
Dynamic job scheduling using the least utilized cores for enhanced performance and thermal management in WNoC
No full texte-Prints posted on TechRxiv are preliminary reports that are not peer reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in the media as established information.Multicore architecture featuring wireless network-on-chip (WNoC) has emerged as a promising solution to meet the increasing demand for performance and power efficiency. However, the frequent utilization of cores to accomplish computational and communication objectives often leads to significant heat generation within multicore processors. This excessive heat poses the risk of overheating and potential malfunction of the processor chip. Multicore WNoC systems, whether with uniform or non-uniform subnets, often suffer from inefficient core utilization, which can result in decreased performance, localized overheating, and reduced processor chip lifespan. In this study, we propose a dynamic job scheduling methodology combined with the least used core selection to enhance performance and achieve even heat distribution across multicore WNoC chips. The proposed method employs the shortest remaining job first (SRJF) algorithm to select jobs and the least recently used (LRU) algorithm to select cores for ensuring even time distribution for equal heat dissipation while maximizing resource utilization. We simulate a 49-core 7x7 WNoC utilizing 1-hop (where a core needs only one hop to reach the nearest wireless router), 2-hop, and 3-hop organizations. Simulation programs are executed using a representative workload consisting of 92 jobs to evaluate the effectiveness of the proposed method. Our simulation results demonstrate how the communication latency and power consumption are impacted by the number of wireless routers. Also, it is observed that the proposed method effectively achieves balanced heat distribution across the WNoC. The 2-hop WNoC emerges as the optimal WNoC, achieving a 57% reduction in wireless routers compared to the 1-hop architecture, along with latency reductions of 9% and 14%, and power consumption reductions of 18% and 25% compared to the 3-hop and non-uniform configurations, respectively
Dr. Mohammed Asaduzzaman on agriculture and climate change in Bangladesh
No full textClimate change has become a major component of government plans for dealing with food security as nations see unprecedented changes in growing conditions. How are climate change concerns influencing agriculture policies in Bangladesh
Post-resettlement Health Realities of Rohingya Refugees: An Ethnographic Study in the Context of U.S. Health Care System in the Atlanta Metropolitan Area
Full text linkHealth is a significant part of human life. To keep good health, people seek the best option in the settings of their social, cultural, and economic circumstances. This study aims to examine to understand how Rohingya refugees consider their health perception and post-resettlement health realities in the Atlanta metropolitan area, USA. Through the theoretical lens of medical pluralism, practice theory, therapy management network, this study determines what factors facilitate them to seek health-care in the USA. In this study, data was gained by interview, key informant interview, observation, case study, and Autoethnography methods
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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