355 research outputs found
LTC-SUM: Lightweight Client-driven Personalized Video Summarization Framework Using 2D CNN
No full textFeature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba
No full textForensic autopsy focuses on revealing the cause of death (CoD) by examining a dead body. This process is performed by medical pathologists during the investigation of criminal and civil law cases. In forensic autopsy, pathologists examine corpses externally and anatomically to collect autopsy findings. Moreover, these experts collect the history of the deceased and death scene-related information from the deceased’s relatives and eyewitnesses. Afterward, the pathologists determine the CoD through their expert knowledge while correlating the current autopsy findings with previous autopsy reports. Therefore, determining the CoD from autopsy findings is laborious, time consuming, and subject to inconsistencies associated with any labor-intensive process. Hence, automated text classification (ATC) techniques must be employed to overcome the aforementioned issues in determining the CoD. This study aimed to employ ATC techniques to classify the CoD from forensic autopsy reports. In the ATC technique, feature engineering is a highly important step because the success or failure of any ATC model is heavily dependent on the quality of the features used in the classification task. In ATC, the traditional feature engineering techniques include bag of words (BoW) and n-gram. This study argues that BoW and its variant techniques are inadequate in determining the CoD from forensic autopsy reports because these techniques ignore word-order, word-context, and word-level synonymy and polysemy. To overcome the aforementioned issues of BoW and its variant techniques, this study aimed to achieve the following four main objectives. First, this work intended to investigate the existing feature engineering techniques to classify free-text clinical reports, including forensic autopsy reports. Second, this study aimed to develop semi-automated expert-driven feature engineering to overcome the issue of word-level synonymy and polysemy. Third, this research sought to propose a fully automated conceptual graph-based feature engineering technique to address issues in word-order and word-context. Finally, this work intended to evaluate the proposed techniques by comparing their performances with existing baseline techniques. For the experimental evaluation, forensic autopsy reports of 16 different CoDs were obtained from a very large hospital in Kuala Lumpur, Malaysia. These reports were preprocessed by applying various text preprocessing techniques. The discriminative features were then extracted from the preprocessed reports through the proposed feature engineering techniques and formed numeric master feature vectors. These master feature vectors were fed as input to six machine learning algorithms to construct and evaluate the classification models. Furthermore, to show the effectiveness of the proposed techniques, this study compared their performances with five state-of-the-art baseline feature engineering techniques. Experimental results showed that the proposed techniques outperformed the traditional BoW and its variant techniques. Moreover, support vector machines and random forest algorithms outperformed the four other algorithms. The proposed techniques are feasible and practical in determining the CoD from forensic autopsy reports and can assist pathologists to accurately and rapidly determine the CoD from autopsy findings. Finally, the proposed techniques are generally applicable to other kinds of free-text clinical reports
Does CEO guilt influence the adoption of employee welfare practices?
No full textThis study examines the role of CEOs' guilt in adopting employee welfare practices (EWP). Using the context of privatization that is associated with large-scale layoffs, we argue that witnessing the distress of laid-off workers and their families causes CEOs to experience guilt for not doing enough to alleviate their suffering. The guilt, in turn, drives CEOs to engage in remedial actions of restitution that reflect positively on employee-related practices. We find support for our idea in a sample of newly privatized firms from 31 countries. Our results show that CEOs' guilt positively influences the adoption of EWP among newly privatized firms. This effect is stronger in countries with collectivistic orientation and higher unemployment rates. Our findings suggest CEOs' values and emotions play an important role in business decisions concerning their employees. This perspective challenges the conventional view of business decisions as purely rational and profit-driven, highlighting the importance of ethical and emotional considerations in decision-making
كوفيد-19 خلق الفرص من الأزمات لطلاب الصيدلة: نقاش من حول العالم
No full textQatar University’s College of Pharmacy (QU-CPH) and Qatar Pharmacy Undergraduate Society (QPhUS) conducted a webinar entitled “ COVID-19 Creating Opportunities from a Crisis for Pharmacy Students: Discussion from Around the Globe”. The event was held successfully via WebEx platform with more than 100 attendees from around the world and more than 300 views on YouTube.
Speakers at the event included student leaders and members of pharmacy associations that are part of the International Pharmaceutical Students' Federation. They were: Hend Al-Naimi, QPhUS President and CPH fourth professional year student;. Ghulam Mujtaba, Member of Pakistan Pharmaceutical Students’ Federation (PPHSF);. Wafa Othman Member of Palestinian Pharmaceutical students’ federation An-Najah National University (PSFNNU); Melissa Kieley, Canadian Association of Pharmacy student and Interns Contact Person (CAPSI); and Ismail Jomha, Vice president chairperson of the Professional Development Committee at the Lebanese Pharmacy Students’ Association (LPSA). The webinar aimed to share the different experiences by pharmacy students around the world and how pharmacy students around the globe created new stories of success despite the unprecedented circumstances the world is facing
2023 Award Winner Bahaudin Mujtaba
No full textArts, Business, Humanities, Law, and Social Sciences
Professor Award
Bahaudin Mujtaba, H. Wayne Huizenga College of Business and Entrepreneurship, is a Professor of Human Resources and International Management. He is the author and coauthor of books dealing with diversity, ethics, and business management, and his contributions to his field are significant. During the past thirty years, he has worked with managers and human resource professionals in almost 20 countries, and this diverse exposure has provided him with many insights in cross-cultural management from the perspectives of different firms, people groups, and cultures. With an extensive publication record and thousands of citations covering topics such as business, change, culture, ethics, diversity, and others, his work is highly collaborative with over 50 different coauthors drawn from NSU, the United States, and abroad. His books and guidance are sought and frequently used by companies, professors, and the media. He served as a cultural consultant for the movie Kite Runner and in 2018 did pro bono training and development work in Afghanistan on topics of adult learning, leadership, and ethics.https://nsuworks.nova.edu/provost_research_award/1018/thumbnail.jp
Identification of networked tunnelled applications
No full textIn protocol tunnelling, one application protocol is encapsulated within another carrier protocol in an unusual way to circumvent firewall policy. Application-layer tunnels are a significant security and resource abuse threat for networks because those applications which are restricted by firewalls such as high data-rate games, peer-to-peer file sharing, video and audio streaming, and chat are carried through via allowed protocols like HTTP, HTTPS and the firewall security policy is thwarted. Protocols such as HTTP and HTTPS are indispensable today for any network which has to be connected to the Internet; hence these become a high value target for running restricted applications via tunnelling. The identification of the actual application running across a network is important for network management, optimization, security and abuse prevention. The existing techniques for identification of applications running across the network, for example port number based identification, and packet data analysis techniques are not always successful, especially for applications which use encrypted tunnels. This work describes a statistical approach to detect applications which are running using application layer tunnels. Previous work has shown the packet size distribution to be an effective metric for detecting most network applications, both UDP and TCP based applications. In this work it is shown how packet stream statistics including packet size distributions can be used to differentiate and identify networked tunnelled applications successfully. Tunnelled applications are identifiable using the traffic statistical parameters. Traffic trace files of the applications were captured, statistical parameters were derived from the trace files, and then these parameters were used for training machine learning algorithms. The trained machine learning algorithm is then able to classify the other packet trace data as belonging to an application. Five different machine learning algorithms have been applied, and their performance accuracy is discussed. The entropy distance based Nearest Neighbour machine learning algorithm and the Euclidean Distance based Nearest Neighbour classifier had better results than others. This method of identification of tunnelled applications can be complimentary to other network security systems such as firewalls and Intrusion Detection Systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic
No full textIn this study, we present the evidence of dramatic changes in the structure and time-varying patterns of volatility connectedness across equities and major commodities (oil, gold, silver and natural gas) in the US economy before and during the COVID-19 outbreak. We utilize high frequency 5-min trading data of most actively traded US ETFs to construct the volatility connectedness network. We compute the intraday volatility estimates using MCS-GARCH model and then employ Diebold and Yilmaz (2012) spillover index approach to approximate volatility spillovers between the financial markets. Our main findings showcase significant impact of COVID-19 pandemic on the volatility linkages of financial markets as the volatility connectedness among the different assets peaked during the outbreak. Other findings and implications of the study are further discussed
Muslim Public Opinion Toward the International Order [electronic resource] : Support for International and Regional Actors /
No full textThis book analyses the attitudes of Muslim citizens toward international and regional actors. In essence, the project examines whether Muslim public opinion is in favor of the current international order and if there is an ideal type of international governance perceived by Muslim citizens. The author connects the analysis to the literature of international public opinion and to the research on social legitimacy of international and global governance. It is ideal for scholarly audiences interested in Islamic, International and Global Governance Studies. Mujtaba Ali Isani is a Post-Doctoral Fellow at the Department of Political Science at the University of Muenster, Germany.1. Chapter 1 Introduction and Historical Context -- 2. Chapter 2 Literature Review, Theory and Methods -- 3. Chapter 3 Muslim Attitudes Toward the UN -- 4. Chapter 4 The Arab League and the GCC: Failures of Regional Organization in the Muslim World? -- 5. Chapter 5 Support for the Global Caliphate as Alternative -- 6. Chapter 6 Conclusion: ASEAN as a Successful Regional Organization? OIC as an Alternative to the Caliphate? Revisiting the Main Puzzles .This book analyses the attitudes of Muslim citizens toward international and regional actors. In essence, the project examines whether Muslim public opinion is in favor of the current international order and if there is an ideal type of international governance perceived by Muslim citizens. The author connects the analysis to the literature of international public opinion and to the research on social legitimacy of international and global governance. It is ideal for scholarly audiences interested in Islamic, International and Global Governance Studies. Mujtaba Ali Isani is a Post-Doctoral Fellow at the Department of Political Science at the University of Muenster, Germany
Effects of Basel equity and liquidity regulations on banking sector failure risk in emerging Asian economies
No full textWe study the effect of Basel equity requirements and liquidity creation measures on banking sector failure risk in case of emerging Asian economies for 2004-2017 by using dynamic panel GMM methodology. This study results show that a rise in equity requirements is likely to decrease in failure risk (as the higher z-score implies the reduced failure risk). The finding suggests that by an incremental increase in equity ratio, liquidity creation results a rise in bank default risk. The finding is consistent with the argument that liquidity generation function exposes banking industry towards risk of illiquidity. The findings also suggest the positive relationship amid bank capital structure and z-score, which implies a surge of equity in bank capital structure is likely to reduce the failure risk
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