12,901 research outputs found
MR Elastography and MR Imaging for the Evaluation of TE Construct
No full textUniversity of the Pacific Graduate School Three Minute Thesis Competition MR Elastography and MR Imaging for the Evaluation of TE Construct by Muhammad Waqas, MS in Engineering Science student, School of Engineering & Computer Scienc
Ottimizzazione delle Prestazioni del Cloud Computing: Simulazione di Sistemi di Accodamento Multi-Server a Capacità Finita Optimizing Cloud Computing Performance: Simulation of Finite-Capacity Multi-Server Queueing Systems
No full textIl concetto di cloud computing nasce dall’architettura software distribuita con l’obiettivo di fornire servizi tramite Internet. Ha rivoluzionato l’accesso e l’utilizzo delle risorse computazionali, offrendo notevole flessibilità e scalabilità. Tuttavia, la natura dinamica degli ambienti cloud, accentuata dalle crescenti esigenze dei carichi di lavoro basati sull’Intelligenza Artificiale, che richiedono un vasto numero di risorse e funzionalità, comporta sfide significative nella gestione delle risorse, nella garanzia della qualità del servizio e nell’ottimizzazione delle prestazioni. Questo lavoro affronta le problematiche legate all’allocazione delle risorse dovute alla diversità delle tipologie (es. memoria, CPU, banda, I/O), concentrandosi sulla simulazione e analisi di sistemi di accodamento multi-server a capacità finita all'interno degli ambienti cloud, utilizzando il framework OMNeT++.
La prima parte della tesi ha riguardato lo sviluppo di una libreria di simulazione dettagliata per l’implementazione di sistemi di accodamento multi-server. Il lavoro si è concentrato sugli aspetti pratici della simulazione di ambienti cloud con risorse finite, in particolare attraverso la realizzazione di un simulatore open-source per analizzare modelli di accodamento su OMNeT++. Configurando diverse discipline di accodamento, come le politiche First-In First-Out (FIFO) e quelle basate sulla priorità, è stato possibile modellare dinamicamente l’allocazione delle risorse, simulare la pianificazione dei job e analizzare le metriche prestazionali, fornendo uno strumento solido per l’esame di scenari realistici nel cloud computing. L’importanza del simulatore è giustificata dalla mancanza di risultati analitici generali che permettano di prevedere efficacemente le metriche prestazionali.
Nella seconda parte, il lavoro è stato esteso con uno studio di simulazione approfondito dei sistemi di accodamento multi-server a capacità finita. Questo studio ha esplorato l’impatto delle diverse politiche di accodamento sulle metriche prestazionali in ambiente cloud. I risultati hanno evidenziato che assegnare priorità ai job con tempi di servizio più lunghi e maggiori richieste di risorse può migliorare le prestazioni complessive del sistema, beneficiando sia i job piccoli che quelli grandi.
Come prosecuzione di questa tesi, è stato analizzato l’effetto delle politiche di scheduling, in particolare quelle preemptive e non preemptive. Lo studio ha dimostrato che le politiche preemptive, incluso un approccio greedy in cui le risorse vengono liberate preemptando prima i job più piccoli e proseguendo progressivamente verso quelli più grandi fino al raggiungimento della soglia di risorse necessarie, migliorano le metriche come la probabilità di perdita, il tempo di attesa e l’utilizzo delle risorse. Tuttavia, queste politiche introducono anche sprechi computazionali, poiché i job attivi vengono interrotti durante il servizio. Questo compromesso mette in evidenza la complessità e l’eterogeneità nell’ottimizzazione degli ambienti cloud e la necessità di considerare attentamente sia le prestazioni sia l’efficienza delle risorse.
In generale, questo lavoro contribuisce a una migliore comprensione della relazione tra discipline di accodamento, allocazione delle risorse e prestazioni del sistema nei contesti di cloud computing. I risultati della ricerca sono di grande utilità non solo per i fornitori di servizi cloud, ma anche per i consumatori, per una progettazione ottimale dei sistemi cloud-based, grazie agli strumenti di simulazione sviluppati e alle conoscenze analitiche ottenute dagli esperimenti condotti.The concept of cloud computing has emerged from the distributed software architecture with the aim of providing services over the Internet. It has revolutionized the access and use of computational resources with remarkable flexibility and scalability. However, the dynamic nature of cloud environments, intensified by the growing demands of Artificial Intelligence-driven workloads that require a vast number of resources and capabilities, introduces serious challenges in resource allocation, service quality assurance, and performance optimization. This work addresses the challenges of resource allocation due to diverse resource types (e.g. memory, cores, bandwidth, input/output) by focusing on the simulation and analysis of finite-capacity multi-server job queueing systems within cloud computing environments, using the OMNeT++ framework. Specifically, we investigate the impact of scheduling policies on the performance metrics of a multi-server job system to contribute to a deeper understanding and provide solutions to optimize cloud resource allocation due to diverse resource types required by jobs from different types of sources.
The first part of this thesis involved developing a detailed simulation library for implementing multi-server job queueing systems. This work focused on the practical aspects of simulating cloud environments with finite resources, specifically developing an open-source simulator to analyze queueing models on the top of OMNeT++. By configuring various queueing disciplines such as First-In, First-Out and Priority-based scheduling algorithms, we were able to dynamically model resource allocation, simulate job scheduling, and analyze performance metrics, providing a robust tool for examining real-world scenarios in cloud computing. The importance of the simulator is justified by the lack of general analytical results that can predict the performance metrics efficiently.
In the second part, we extended our work by conducting a detailed simulation study of finite-capacity multi-server job systems. This study focused on understanding the impact of different queueing policies on performance metrics in the cloud environment. Our findings revealed that assigning priority to jobs with longer service times and higher resource demands can positively impact both smaller jobs with shorter service times and big jobs, and thus enhance overall system performance.
As a follow-up to this thesis, we further investigate the performance implications of scheduling policies, particularly preemptive and non-preemptive approaches. The study demonstrated that preemptive policies, including a greedy approach in which resources are freed by first preempting smaller jobs and gradually progressing to big ones until the required resource threshold is met, improved performance metrics such as the probability of dropping, waiting time and resource utilization. However, these policies also introduce computational waste as the active jobs are disrupted during their service in this model. This trade-off emphasizes the heterogeneity of optimizing cloud computing environments and the need for careful consideration of both performance and resource efficiency.
In general, our work contributes to a better understanding of the relationship between queueing disciplines, resource allocation, and system performance in cloud computing environments. These research findings are of great help not only to cloud service providers, but also to cloud consumers for the optimal design of cloud-based systems, which is achieved by simulation tools developed during the study and the analytical insight from the experiments conducted as part of the work
Pioneers of Library Movement in Pakistan
Full text linkThe paper aims to describe in brief the contribution of seven leaders of Pakistan librarianship, viz. K.B. Khalifa M. Asadullah, Prof. Dr. Abdul Moid, Dr. Abdus Subuh Qasimi, Muhammad Shafi, Fazal Elahi, Khawaja Nur Elahi and S. V. Hussain. The early library developments are given for better understanding of the role of these leaders
sj-tiff-1-tdo-10.1177_00494755221127355 - Supplemental material for Respiratory sequelae of dengue fever
No full textSupplemental material, sj-tiff-1-tdo-10.1177_00494755221127355 for Respiratory sequelae of dengue fever by Asad Mehmood, Muhammad Waqas Afzal, Muhammad Ahmad, Mahreen Mufti, Jahanzeb Malik and Syed Muhammad Jawad Zaidi in Tropical Doctor</p
sj-docx-2-tdo-10.1177_00494755221127355 - Supplemental material for Respiratory sequelae of dengue fever
No full textSupplemental material, sj-docx-2-tdo-10.1177_00494755221127355 for Respiratory sequelae of dengue fever by Asad Mehmood, Muhammad Waqas Afzal, Muhammad Ahmad, Mahreen Mufti, Jahanzeb Malik and Syed Muhammad Jawad Zaidi in Tropical Doctor</p
sj-pdf-3-tdo-10.1177_00494755221127355 - Supplemental material for Respiratory sequelae of dengue fever
No full textSupplemental material, sj-pdf-3-tdo-10.1177_00494755221127355 for Respiratory sequelae of dengue fever by Asad Mehmood, Muhammad Waqas Afzal, Muhammad Ahmad, Mahreen Mufti, Jahanzeb Malik and Syed Muhammad Jawad Zaidi in Tropical Doctor</p
The fourth industrial revolution and environmental efficiency: The role of fintech industry
No full textIn the recent years, fintech industry of the fourth industrial revolution has grown multifold, which raised the concerns of scholars over the excessive usage of electricity. This paper places contribution to the existing literature by analyzing the impact of fintech industry on environmental efficiency across selected EU countries. We also utilized indicators like high-tech industry and e-commerce along with fintech industry to better understand the relationship between fourth industrial revolution and environmental efficiency. This study used Data Envelopment Analysis (DEA) to evaluate environmental efficiency using two different techniques i.e., Slack-Base Measure (SBM) and Epsilon-Based Measure (EBM). Method of Moments Quantile (MMQ) regression is employed as a basic regression technique, while instrumental variables Generalized method of Moments (IV-GMM) is used for robust analysis. The results show that, the overall environmental efficiency of EU countries have improved over the years. As the indicators of the fourth industrial revolution, fintech industry and e-commerce exert a positive effect and improve environmental efficiency; however, high-tech industry reduces environmental efficiency. The results further show that, economic growth and green finance investment promote environmental efficiency, while industrialization and R&D deteriorates it. The results can be of special interest for the policy makers of technological world
Decoding Informal Settlements in Core Urban Areas of Karachi: Leveraging Machine Learning Algorithms for Classification and Analysis
No full textThe proliferation of informal settlements in developing countries marks a significant byproduct of unchecked urbanization and economic expansion, posing substantial sustainability challenges within urban systems. This complexity stresses the urgency of dissecting the nature and forces associated with such settlements to forge effective intervention strategies. Focused on Karachi’s primary urban sectors, this research enlightens the dynamics of informal settlements and their contributing factors. By utilizing published public datasets, the study evaluates the efficacy of five machine learning algorithms—K Nearest Neighbors (KNN), Neural Networks (NN), Random Forest (RF), Random Trees (RT), and XGBoost Tree—in predictive modelling of the spatial patterns and associated elements of these settlements. Random Forest distinguished itself among the assessed algorithms by delivering unparalleled precision across critical performance metrics, reaching an F1-Score of 0.80. This investigation further illuminates the critical role of several determinants, such as proximity to the central business district (CBD), railway lines, waterways, commercial zones, health facilities, educational institutions, and poverty markers, in accumulating informal settlements. The insights from this study are instrumental in predictive modeling for informed urban planning and policymaking, aiming to develop a systematic resolution of the challenges posed by informal settlements in Karachi
Business Applications of Cargo Drones in the EU
No full textDrones have become ubiquitous in various industries due to their versatility and efficiency in performing various tasks, from agricultural operations to search and rescue missions. This paper explores the use of drones, particularly cargo drones, in revolutionizing logistics and transportation systems. Medium-range cargo drones offer the potential to transform freight transportation by offering independence from traditional infrastructure and potentially reducing environmental impact. However, the integration of UAVs into existing logistical operations faces several challenges, including regulatory hurdles, technological limitations, and public perception issues. Drones can become a viable form of cargo transportation given that the regulatory challenges are addressed and can be efficiently integrated into the existing logistic operations. It would ultimately result in an efficient last-mile delivery option and will revolutionize the logistics industry
The impact of M&A on bank's financial performance: evidence from emerging economy.
Full text linkThe proliferation of bank M&A has been a global phenomenon. In many emerging economies, bank M&A has often been driven by policies for restructuring the banking industry in the hope of improving stability in the financial system. The Pakistan M&A market is relatively new and is characterized by several unique features. In this regards, our study aim is to examine the impact of pre and post M&A on the bank’s financial performance in Pakistan during the period (2004-2015). Our results reveal that liquidity, profitability and investment ratios of the banks are positively and significantly increased the performance after M&A. Nevertheless, the solvency ratios indicate negative effects which are mainly based on the fact that after undergoing M&A the acquiring bank has to deal with the greater amount of debt burden as compared to pre-M&A. In light of these results, this study suggests implications for both theory and practice and also recommends ideas for future research
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