Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Brigham Young University (632)
- Singapore Management University (183)
- California State University, San Bernardino (131)
- Universitas Negeri Malang (104)
- California Polytechnic State University, San Luis Obispo (52)
-
- Air Force Institute of Technology (18)
- San Jose State University (18)
- University of Arkansas, Fayetteville (17)
- University of Nebraska - Lincoln (17)
- Association of Arab Universities (16)
- University of Texas at Arlington (15)
- City University of New York (CUNY) (14)
- Old Dominion University (14)
- Portland State University (14)
- The University of Akron (14)
- Embry-Riddle Aeronautical University (13)
- University of Connecticut (12)
- University of New Mexico (12)
- Purdue University (11)
- University of South Florida (10)
- Clemson University (9)
- Louisiana State University (9)
- University of Kentucky (8)
- DePaul University (7)
- Georgia Southern University (7)
- Technological University Dublin (7)
- Kennesaw State University (6)
- University of Nevada, Las Vegas (6)
- University of North Florida (6)
- Department of Primary Industries and Regional Development, Western Australia (5)
- Keyword
-
- Database (20)
- Cloud computing (19)
- Blockchain (18)
- Data mining (18)
- Big data (17)
-
- Machine Learning (17)
- Machine learning (15)
- Security (14)
- Cloud Computing (13)
- Cybersecurity (13)
- Classification (12)
- Data management (12)
- Deep Learning (12)
- Technology (12)
- Artificial Intelligence (11)
- Climate change (11)
- Performance (10)
- Sustainability (10)
- ToC (10)
- Big Data (9)
- Data Mining (9)
- Education (9)
- Social media (9)
- Software (9)
- Computer science (8)
- Crowdsourcing (8)
- Data (8)
- Internet (8)
- Ontology (8)
- Privacy (8)
- Publication Year
- Publication
-
- International Congress on Environmental Modelling and Software (629)
- Research Collection School Of Computing and Information Systems (175)
- Journal of International Technology and Information Management (111)
- Knowledge Engineering and Data Science (104)
- Theses and Dissertations (24)
-
- Computer Engineering (20)
- Master's Theses (18)
- Future Computing and Informatics Journal (14)
- Williams Honors College, Honors Research Projects (14)
- Electronic Theses, Projects, and Dissertations (11)
- Branch Mathematics and Statistics Faculty and Staff Publications (9)
- Computer Science and Engineering Faculty Publications (9)
- Library Philosophy and Practice (e-journal) (9)
- Theses Digitization Project (9)
- All Theses (8)
- Electronic Theses and Dissertations (8)
- College of Graduate Studies: Theses & Dissertations (7)
- Graduate Theses and Dissertations (7)
- School of Computing: Technical Reports (7)
- Computer Science and Software Engineering (6)
- Dissertations and Theses (6)
- Dissertations and Theses Collection (Open Access) (6)
- Publications and Research (6)
- UNF Graduate Theses and Dissertations (6)
- CDM Annual Reports (5)
- Computer Science and Computer Engineering Undergraduate Honors Theses (5)
- Computer Science and Engineering Dissertations - Archive (5)
- Inaugural CSU IR Conference, 2015 (5)
- LSU Doctoral Dissertations (5)
- Published Works (5)
- Publication Type
- File Type
Articles 391 - 420 of 1552
Full-Text Articles in Computer Engineering
Auditing Database Systems Through Forensic Analysis, James Wagner
Auditing Database Systems Through Forensic Analysis, James Wagner
College of Computing and Digital Media Dissertations
The majority of sensitive and personal data is stored in a number of different Database Management Systems (DBMS). For example, Oracle is frequently used to store corporate data, MySQL serves as the back-end storage for many webstores, and SQLite stores personal data such as SMS messages or browser bookmarks. Consequently, the pervasive use of DBMSes has led to an increase in the rate at which they are exploited in cybercrimes. After a cybercrime occurs, investigators need forensic tools and methods to recreate a timeline of events and determine the extent of the security breach. When a breach involves a compromised …
Deep Learning For Real-World Object Detection, Xiongwei Wu
Deep Learning For Real-World Object Detection, Xiongwei Wu
Dissertations and Theses Collection (Open Access)
Despite achieving significant progresses, most existing detectors are designed to detect objects in academic contexts but consider little in real-world scenarios. In real-world applications, the scale variance of objects can be significantly higher than objects in academic contexts; In addition, existing methods are designed for achieving localization with relatively low precision, however more precise localization is demanded in real-world scenarios; Existing methods are optimized with huge amount of annotated data, but in certain real-world scenarios, only a few samples are available. In this dissertation, we aim to explore novel techniques to address these research challenges to make object detection algorithms …
Query Rewriting With Thesaurus-Based For Handling Semantic Heterogeneity In Database Integration, I Made Riyan Adi Nugroho, I Wayan Budi Sentana
Query Rewriting With Thesaurus-Based For Handling Semantic Heterogeneity In Database Integration, I Made Riyan Adi Nugroho, I Wayan Budi Sentana
Knowledge Engineering and Data Science
Nowadays, studies on handling semantic heterogeneity still become a challenge for researcher. Several methods have been used to solve these problems, one of which is query rewriting, implemented by rewriting a query into the latest one by using the selected schema. Semantic query rewriting needs a framework in order to identify the connection through the data schema sources. This line is used as a basis for scheme selection. Also, ontology is a model which often be used in these specific cases. The lack of ontology becomes a significant problem that usually seen. Therefore, this paper will describe an alternative framework …
Flood Prediction Using Artificial Neural Networks: Empirical Evidence From Mauritius As A Case Study, A. Z. Dhunny, Reena H. Seebocus, Z. Allam, Mohammad Yasser Chuttur
Flood Prediction Using Artificial Neural Networks: Empirical Evidence From Mauritius As A Case Study, A. Z. Dhunny, Reena H. Seebocus, Z. Allam, Mohammad Yasser Chuttur
Knowledge Engineering and Data Science
Artificial Neural Networks (ANN) has been well studied for flood prediction. However, there is not enough empirical evidence to generalize ANN applicability to small countries with microclimates prevailing in a small geographical space. In this paper, we focus on the climatic conditions of Mauritius for which we seek to investigate the accuracy of using ANN to predict flooding using locally collected data from 11 meteorological stations spread across the country. The ANN model for flood prediction presented in this work is trained using 20,000 climate data records, collected over a period of two years for Mauritius. Our input climate features …
Human Intestinal Condition Identification Based-On Blended Spatial And Morphological Feature Using Artificial Neural Network Classifier, Ummi Athiyah, Arif Wirawan Muhammad, Ahmad Azhari
Human Intestinal Condition Identification Based-On Blended Spatial And Morphological Feature Using Artificial Neural Network Classifier, Ummi Athiyah, Arif Wirawan Muhammad, Ahmad Azhari
Knowledge Engineering and Data Science
Colon cancer is a type of disease that attacks the intestinal walls cell of humans. Colorectal endoscopic screening technique is a common step carried out by the health expert/gynecologist to determine the condition of the human intestine. Manual interpretation requires quite a long time to reach a result. Along with the development of increasingly advanced digital computing techniques, then some of the weaknesses of the manually endoscopic image interpretation analysis model can be corrected by automating the detection process of the presence or absence of cancerous cells in the gut. Identification of human intestinal conditions using an artificial neural network …
Earthquake Magnitude And Grid-Based Location Prediction Using Backpropagation Neural Network, Bagus Priambodo, Wayan Firdaus Mahmudy, Muh Arif Rahman
Earthquake Magnitude And Grid-Based Location Prediction Using Backpropagation Neural Network, Bagus Priambodo, Wayan Firdaus Mahmudy, Muh Arif Rahman
Knowledge Engineering and Data Science
Earthquakes, a type of inevitable natural disaster, is responsible for the highest average death toll per year compared to other types of a natural disaster. Even though it is inevitable, but it can be anticipated to minimize damage and casualties, such as predicting the earthquake‘s magnitude using a neural network. In this study, a backpropagation algorithm is used to train the multilayer neural network to weekly predict the average magnitude of earthquakes in grid-based locations in Indonesia. Based on the findings in this research, the neural network is able to predict the magnitude of earthquakes in grid-based locations across Indonesia …
Parallelization Of Partitioning Around Medoids (Pam) In K-Medoids Clustering On Gpu, Adhi Prahara, Dewi Pramudi Ismi, Ahmad Azhari
Parallelization Of Partitioning Around Medoids (Pam) In K-Medoids Clustering On Gpu, Adhi Prahara, Dewi Pramudi Ismi, Ahmad Azhari
Knowledge Engineering and Data Science
K-medoids clustering is categorized as partitional clustering. K-medoids offers better result when dealing with outliers and arbitrary distance metric also in the situation when the mean or median does not exist within data. However, k-medoids suffers a high computational complexity. Partitioning Around Medoids (PAM) has been developed to improve k-medoids clustering, consists of build and swap steps and uses the entire dataset to find the best potential medoids. Thus, PAM produces better medoids than other algorithms. This research proposes the parallelization of PAM in k-medoids clustering on GPU to reduce computational time at the swap step of PAM. The parallelization …
Opinion Analysis For Emotional Classification On Emoji Tweets Using The Naïve Bayes Algorithm, Siti Sendari, Ilham Ari Elbaith Zaeni, Dian Candra Lestari, Hanny Prasetya Hariyadi
Opinion Analysis For Emotional Classification On Emoji Tweets Using The Naïve Bayes Algorithm, Siti Sendari, Ilham Ari Elbaith Zaeni, Dian Candra Lestari, Hanny Prasetya Hariyadi
Knowledge Engineering and Data Science
Opinion Analysis is a research study needed to social media, since the content could become a trending topic and has a significant impact on social life. One of the social media that have a big contribution to cyberspace and information development is Twitter. In the Twitter application, users can insert images that represent emotions, facial expressions, or icons. Emoji is a graphic symbol in the form of an image to express a thing, with the Emoji, a text can be read and understood according to its meaning because the image represents it. Of the several things that have been mentioned …
Wine Sampler, Lance L. Litten
Wine Sampler, Lance L. Litten
Computer Engineering
Quality testing is an important part of the wine industry. Without proper quality control, thousands of dollars could be wasted on bottling and recalling hundreds of gallons of wine. Due to this, labs are set up that collect wine samples from the tanks in a wine production plant and test them. A big part of this testing is determining exactly what tanks need to be tested and what tanks are at risk. My project aims to help automate this task by collecting data from the tanks wirelessly and keeping track of simple indicators such as pH and temperature. Automating this …
Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham
Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham
Asian Management Insights
Improving predictions and allocations to determine the optimal matching of demand and supply in a dynamic, uncertain future.
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Research Collection School Of Computing and Information Systems
Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the models trained on photo-realistic synthetic data (e.g., computer games) with computer-generated annotations can be adapted to real images. Despite this progress, without constraining the prediction on real images, the models will easily overfit on synthetic data due to severe domain mismatch. In this paper, we novelly exploit the intrinsic properties of semantic segmentation to alleviate such problem for model transfer. Specifically, we present a Regularizer of Prediction Transfer (RPT) that imposes the intrinsic properties …
Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad Al-Ramahi, Cherie Noteboom
Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad Al-Ramahi, Cherie Noteboom
Research & Publications
Patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. The incorporation of patient portals provides the promise to deliver excellent quality, at optimized costs, while improving the health of the population. This study extends the existing literature by extracting dimensions related to the Mobile Patient Portal Use. We use a topic modeling approach to systematically analyze users’ feedback from the actual use of a common mobile patient portal, Epic’s MyChart. Comparing results of Latent Dirichlet Allocation analysis with those of human analysis validated the extracted …
Trading Up: Exchanging Our Data For A Better Life, Nathan Turner
Trading Up: Exchanging Our Data For A Better Life, Nathan Turner
Marriott Student Review
We live in a data-driven economy. Many people feel like consumers are on the losing end of an economic data-battle with tech giants, but this is simply not true; our data can drive innovation. That’s right—personal data collected from you and me can influence new technologies that will improve our lives. This should excite us, but our fear of losing data privacy can quell our excitement for progress and even restrict innovation. Our quality of life has already begun to improve through data driven innovation, and technological progress is not slowing down. If we let our fear of losing data …
Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi
Multiplex Memory Network For Collaborative Filtering, Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi
Research Collection School Of Computing and Information Systems
Recommender systems play an important role in helping users discover items of interest from a large resource collection in various online services. Although current deep neural network-based collaborative filtering methods have achieved state-of-the-art performance in recommender systems, they still face a few major weaknesses. Most importantly, such deep methods usually focus on the direct interaction between users and items only, without explicitly modeling high-order co-occurrence contexts. Furthermore, they treat the observed data uniformly, without fine-grained differentiation of importance or relevance in the user-item interactions and high-order co-occurrence contexts. Inspired by recent progress in memory networks, we propose a novel multiplex …
Load Balancing Of Financial Data Using Machine Learning And Cloud Analytics, Dimple Jaiswal
Load Balancing Of Financial Data Using Machine Learning And Cloud Analytics, Dimple Jaiswal
Masters Theses & Specialist Projects
The rising use of technology for web applications, android applications, digital marketing, and e-application systems for financial investments benefits a large sector of stakeholders and common people. It allows investors to make an appropriate choice for investment and to increase their capital growth. This requires proper research of investment companies, their trends in price and analysis of historical and current information. In addition, prediction of prices makes the process of investment more comfortable and reliable for investors as shares are the most volatile type of investment. To offer this service to multiple users spread across the globe, there are certain …
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Research Collection School Of Computing and Information Systems
Outsourced storage such as cloud storage can significantly reduce the burden of data management of data owners. Despite of a long list of merits of cloud storage, it triggers many security risks at the same time. Data integrity, one of the most burning challenges in secure cloud storage, is a fundamental and pivotal element in outsourcing services. Outsourced data auditing protocols enable a verifier to efficiently check the integrity of the outsourced files without downloading the entire file from the cloud, which can dramatically reduce the communication overhead between the cloud server and the verifier. Existing protocols are mostly based …
How Data Became Part Of New Orleans’ Dna During The Katrina Recovery, Lamar Gardere, Allison Plyer, Denice Ross
How Data Became Part Of New Orleans’ Dna During The Katrina Recovery, Lamar Gardere, Allison Plyer, Denice Ross
New England Journal of Public Policy
Data intermediaries have a symbiotic relationship with government as the source of most of their information. The open-data movement in government and development of software-as-a-service technologies shaped the data landscape after Katrina. Through relationships and talent transfers with The Data Center, the City of New Orleans went from having its chief technology officer in federal prison and its data systems in shambles to being a nationally recognized leader in open and accountable government. To be effective during disasters, an intermediary should be (1) in place and widely respected before the event, (2) ready to respond immediately after the event and …
Does The Age Of An It Executive Impact Adoption Levels Of Cloud Computing Services?, Marcus L. Smith
Does The Age Of An It Executive Impact Adoption Levels Of Cloud Computing Services?, Marcus L. Smith
Faculty Publications
This author researched previously the personal decision factors considered by information technology (IT) executives when making the cloud computing services adoptionchoice. The conclusions in that work (Smith, Jr., 2016) supported four hypotheses, namely, (a) advancement, recognition and satisfaction from accomplishments, (b) top management support, (c) diminishment of personal image, and (d) a pattern of technology readiness have a positive influence on business intentions to adopt cloud computing services. Interestingly, a fifth hypothesis, diminishment of personal image, was found to have a negative influence on business intentions. The relationship between age of the survey respondents and adoption levels was highlighted in …
Using Knowledge Bases For Question Answering, Yunshi Lan
Using Knowledge Bases For Question Answering, Yunshi Lan
Dissertations and Theses Collection (Open Access)
A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.
In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …
Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu
Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu
Research Collection School Of Computing and Information Systems
Recent years have witnessed promising results of exploring deep convolutional neural network for face detection. Despite making remarkable progress, face detection in the wild remains challenging especially when detecting faces at vastly different scales and characteristics. In this paper, we propose a novel simple yet effective framework of “Feature Agglomeration Networks” (FANet) to build a new single-stage face detector, which not only achieves state-of-the-art performance but also runs efficiently. As inspired by Feature Pyramid Networks (FPN) (Lin et al., 2017), the key idea of our framework is to exploit inherent multi-scale features of a single convolutional neural network by aggregating …
Apps For Actionable Workflows: Tools To Stay In The Loop And On Top Of Tasks, Rachel S. Evans
Apps For Actionable Workflows: Tools To Stay In The Loop And On Top Of Tasks, Rachel S. Evans
Presentations
No matter what member of the team you are or what type of library you are in - be it electronic resources manager, cataloger, head of acquisitions, ILS or systems administrator, or even repository coordinator - getting things done and meeting goals depends largely on how you communicate with one another and how you handle your time. Meeting goals and deadlines on both big and small projects in addition to your personal tasks can be achieved less painfully by making effective use of a few on point tools. This session will use the presenter's preferred platforms to show specific examples …
Retrospective Study Of Fmol Health System Utilization Using Geospatial Information, Deekshith Mandala
Retrospective Study Of Fmol Health System Utilization Using Geospatial Information, Deekshith Mandala
LSU Master's Theses
Medicaid Expansion and closing of Emergency Departments (ED) like Earl K. Long, Baton Rouge General Mid-City ED, and Champion Medical Center changed the health care landscape in East Baton Rouge Parish (EBRP). In this research study, a Geographical Information System (GIS) is used to analyze the impact of the expansion of Medicaid and the inauguration of Our Lady of the Lake North Baton Rouge ED (OLOL NBR ED) over the utilization of Franciscan Missionaries of our Lady Health System (FMOLHS) for both emergency and non-emergency health care services. This study is performed across the 58 neighborhoods of EBRP. Overutilization of …
Annual Report 2019-2020, Depaul University College Of Computing And Digital Media
Annual Report 2019-2020, Depaul University College Of Computing And Digital Media
CDM Annual Reports
LETTER FROM THE DEAN
As I write this letter wrapping up the 2019-20 academic year, we remain in a global pandemic that has profoundly altered our lives. While many things have changed, some stayed the same: our CDM community worked hard, showed up for one another, and continued to advance their respective fields. A year that began like many others changed swiftly on March 11th when the University announced that spring classes would run remotely. By March 28th, the first day of spring quarter, we had moved 500 CDM courses online thanks to the diligent work of our faculty, staff, …
Determinants Of Startup Funding: The Interaction Between Web Attention And Culture, Jie Ren, Viju Raghupathi, Wullianallur Raghupathi
Determinants Of Startup Funding: The Interaction Between Web Attention And Culture, Jie Ren, Viju Raghupathi, Wullianallur Raghupathi
Journal of International Technology and Information Management
Technology empowers entrepreneurs to pursue alternative funding through platforms like crowdfunding. This research explores significant startup funding factors using Crunchbase. Controlling for common factors (acquisition/funding-rounds/IPO), the research uniquely focuses on web attention - the visibility on social media - and its impact on funding. It also examines the moderating influence of startup’s home country culture (individualism/collectivism). Findings show stronger positive impact of web attention on startup funding for collectivist countries. While individualistic investors value personal goals, collectivists value collaborative goals - inclinations that align with crowdfunding behavior. Therefore while increasing web attention, crowdfunding efforts can be targeted towards collectivist countries.
Evaluating Students Information System Success Using Delone And Mclean’S Model: Student’S Perspective, Majaliwa Mkinga, Herman Mandari
Evaluating Students Information System Success Using Delone And Mclean’S Model: Student’S Perspective, Majaliwa Mkinga, Herman Mandari
Journal of International Technology and Information Management
System success is considered to be an important element in accomplishing the goals of the organization; therefore evaluation of system success needs to be done in order to ensure that investment in Information System is successful. Most of Higher Learning Institutions (HLIs) in Tanzania have adopted the use of IS in providing service to their customers. Nevertheless, there is less evidence that system success evaluation has been done in order to identify the desired characteristics which could make IS more effective. Due to that, this study evaluates the effectiveness of Student Information System (SIS) used at the Institute of Finance …
An Integrated View Of Data: Application Of Knowledge Modeling To Data Management, Sung-Kwan Kim, Wenjun Wang
An Integrated View Of Data: Application Of Knowledge Modeling To Data Management, Sung-Kwan Kim, Wenjun Wang
Journal of International Technology and Information Management
Data management has become an important challenge. Good data management requires an effective approach to collecting, storing, and accessing data across the enterprise. In this paper, a knowledge modeling approach to data management is introduced with an emphasis on data requirements analysis. A knowledge model can provide a high-level view of organizational data by specifying the structure and relationships of the knowledge contents used in business processes. The proposed knowledge modeling approach is business process oriented and decision oriented. The description of the knowledge contents in the model is based on ontological specification. The model is comprised of five elements: …
Uga’S Alexander Campbell King Law Library: Phasing In Inclusive Usability Testing, Rachel S. Evans, Marie Mize, Jason Tubinis
Uga’S Alexander Campbell King Law Library: Phasing In Inclusive Usability Testing, Rachel S. Evans, Marie Mize, Jason Tubinis
Articles, Chapters and Online Publications
For years we have offered our EBSCO discovery layer service (EDS) as a secondary search tool in addition to our traditional online catalog (GAVEL) linking to both from the library website. However, the traditional catalog search, also known as “Classic GAVEL”, is always listed first while EDS, also known as “GAVEL & Beyond”, is listed second. Although maintenance has continued for populating EDS with library records on a daily basis, customization for this interface and sharing it with our users has not been prioritized. Before making any decisions related to changing the primary location our users experience when searching the …
Metadata Management For Clinical Data Integration, Ningzhou Zeng
Metadata Management For Clinical Data Integration, Ningzhou Zeng
Theses and Dissertations--Computer Science
Clinical data have been continuously collected and growing with the wide adoption of electronic health records (EHR). Clinical data have provided the foundation to facilitate state-of-art researches such as artificial intelligence in medicine. At the same time, it has become a challenge to integrate, access, and explore study-level patient data from large volumes of data from heterogeneous databases. Effective, fine-grained, cross-cohort data exploration, and semantically enabled approaches and systems are needed. To build semantically enabled systems, we need to leverage existing terminology systems and ontologies. Numerous ontologies have been developed recently and they play an important role in semantically enabled …
Algorithms For Achieving Fault-Tolerance And Ensuring Security In Cloud Computing Systems, Md. Tariqul Islam
Algorithms For Achieving Fault-Tolerance And Ensuring Security In Cloud Computing Systems, Md. Tariqul Islam
Theses and Dissertations--Computer Science
Security and fault tolerance are the two major areas in cloud computing systems that need careful attention for its widespread deployment. Unlike supercomputers, cloud clusters are mostly built on low cost, unreliable, commodity hardware. Therefore, large-scale cloud systems often suffer from performance degradation, service outages, and sometimes node and application failures. On the other hand, the multi-tenant shared architecture, dynamism, heterogeneity, and openness of cloud computing make it susceptible to various security threats and vulnerabilities. In this dissertation, we analyze these problems and propose algorithms for achieving fault tolerance and ensuring security in cloud computing systems.
First, we perform a …
Data Entry Voice Assistant For Healthcare Providers, Sajad Hussain M Alhamada
Data Entry Voice Assistant For Healthcare Providers, Sajad Hussain M Alhamada
EWU Masters Thesis Collection
No abstract provided.