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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 2020 Departement of Electrical Engineering, Universitas Negeri Malang, Indonesia

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 …


Earthquake Magnitude And Grid-Based Location Prediction Using Backpropagation Neural Network, Bagus Priambodo, Wayan Firdaus Mahmudy, Muh Arif Rahman 2020 Faculty of Computer Science, Brawijaya University, Indonesia

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 …


Query Rewriting With Thesaurus-Based For Handling Semantic Heterogeneity In Database Integration, I Made Riyan Adi Nugroho, I Wayan Budi Sentana 2020 Jurusan Teknik Elektro, Politeknik Negeri Bali, Indonesia

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 …


Human Intestinal Condition Identification Based-On Blended Spatial And Morphological Feature Using Artificial Neural Network Classifier, Ummi Athiyah, Arif Wirawan Muhammad, Ahmad Azhari 2020 Department of Data Science, Institut Teknologi Telkom Purwokerto

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 …


Parallelization Of Partitioning Around Medoids (Pam) In K-Medoids Clustering On Gpu, Adhi Prahara, Dewi Pramudi Ismi, Ahmad Azhari 2020 Informatics Department, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Indonesia

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 …


Wine Sampler, Lance L. Litten 2020 California Polytechnic State University, San Luis Obispo

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 2020 Singapore Management University

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.


Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad al-Ramahi, Cherie Noteboom 2020 Texas A&M - San Antonio

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 …


Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng ZHANG, Zhaofan QIU, Ting YAO, Chong-wah NGO, Dong LIU, Tao MEI 2020 Singapore Management University

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 …


Trading Up: Exchanging Our Data For A Better Life, Nathan Turner 2020 Brigham Young University

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 2020 Singapore Management University

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 2020 Western Kentucky University

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 2020 Singapore Management University

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 2020 The Data Center of Southeast Louisiana

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 …


Feature Agglomeration Networks For Single Stage Face Detection, Jialiang ZHANG, Xiongwei WU, Steven C. H. HOI, Jianke ZHU 2020 Singapore Management University

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 …


Does The Age Of An It Executive Impact Adoption Levels Of Cloud Computing Services?, Marcus L. Smith 2020 Texas A&M University-Commerce

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 2020 Singapore Management University

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 …


Apps For Actionable Workflows: Tools To Stay In The Loop And On Top Of Tasks, Rachel S. Evans 2020 University of Georgia School of Law

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 2020 Louisiana State University and Agricultural and Mechanical College

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 2020 DePaul University

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, …


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