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Articles 1 - 30 of 375
Full-Text Articles in Physical Sciences and Mathematics
Drone-Assisted Emergency Communications, Di Wu
Drone-Assisted Emergency Communications, Di Wu
Dissertations
Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area …
Supporting User Interaction And Social Relationship Formation In A Collaborative Online Shopping Context, Yu Xu
Dissertations
The combination of online shopping and social media allow people with similar shopping interests and experiences to share, comment, and discuss about shopping from anywhere and at any time, which also leads to the emergence of online shopping communities. Today, more people turn to online platforms to share their opinions about products, solicit various opinions from their friends, family members, and other customers, and have fun through interactions with others with similar interests. This dissertation explores how collaborative online shopping presents itself as a context and platform for users' interpersonal interactions and social relationship formation through a series of studies. …
Pengembangan Sistem Informasi Pemasaran Produk Pertanian Berbasis Website, Veronika Asri Tandirerung, Syahrul Syahrul, Achmad Padil
Pengembangan Sistem Informasi Pemasaran Produk Pertanian Berbasis Website, Veronika Asri Tandirerung, Syahrul Syahrul, Achmad Padil
Elinvo (Electronics, Informatics, and Vocational Education)
Pengembangan sistem informasi pemasaran produk pertanian (SIPTANI) dibutuhkan untuk membantu para petani dalam memasarkan produk-produk pertanian khususnya di era pandemic Covid-19. Penelitian ini merupakan penelitian pengembangan sistem dengan model pengembangan prototype dengan studi kelayakan menggunakan standar ISO 9126. Data penelitian diperoleh dari hasil observasi dan pengisian kuesioner oleh responden. Hasil pengujian aplikasi diperoleh dengan menganalisis aspek-aspek pada functional suitability, usability, compatibility, dan portability. Pada aspek functional suitability berada pada kategori layak diterima. Pada aspek usability, kategori sangat setuju memiliki dengan persentase 90%, sehingga aplikasi dinyatakan layak dan ditanggapi baik oleh pengguna. Pada aspek compatibility, sistem pemasaran pertanian ini dapat …
Penggunaan Analytical Hierarchy Process (Ahp) Pada Penentuan Prioritas Supplier Food Chemical Di Pt. Garuda Hidrotive Internasional, Nehemia Hadiwijaya, Jenie Sundari
Penggunaan Analytical Hierarchy Process (Ahp) Pada Penentuan Prioritas Supplier Food Chemical Di Pt. Garuda Hidrotive Internasional, Nehemia Hadiwijaya, Jenie Sundari
Elinvo (Electronics, Informatics, and Vocational Education)
Abstract-Supplier selection is one of the important things in purchasing activities for companies. Supplier selection is a multi-criteria problem which includes quantitative and qualitative factors. One method that can be used for supplier selection is the AHP (Analytical Hierarchy Process) method. The problems that will be discussed in this study are: (1) how is the order of priority criteria and sub-criteria in the selection of suppliers at PT Garuda Hidrotive International? (2) which supplier / supplier should PT Garuda Hidrotive International choose based on the AHP method? The sampling technique uses judgment sampling because the AHP method requires dependence on …
Traversal Struktur Data Bipartite Graph Dalam Graph Database Menggunakan Depth-First Search, Pradana Setialana, Muhammad Nurwidya Ardiansyah
Traversal Struktur Data Bipartite Graph Dalam Graph Database Menggunakan Depth-First Search, Pradana Setialana, Muhammad Nurwidya Ardiansyah
Elinvo (Electronics, Informatics, and Vocational Education)
Bipartite graph merupakan satu bentuk graph yang dapat digunakan dalam membentuk sebuah strukur data yang saling berelasi namun memiliki karakteristik dengan dua jenis node yang berbeda seperti data hubungan keluarga atau data pohon keluarga. Dalam menyimpan struktur data bipartite graph ke sebuah database dapat digunakan graph database dengan konsep dimana node saling saling terhubung dengan node lainnya. Bipartite graph yang dikombinasikan dengan graph database menghasilkan solusi yang tepat dalam menyimpan data berelasi dengan dua jenis node yang berbeda. Namun dalam solusi tersebut menimbulkan permasalahan baru mengenai pencarian atau penelusuran (traversal) terhadap data yang terdapat dalam struktur data tersebut. Tujuan dari …
Optimalisasi Media Penyimpanan Pada Sistem Inventori Stok Barang Untuk Pt. Multi Usaha Sejahtera Jaya Menggunakan Metode Goldbach Codes, Angga Debby Frayudha, Siti Purwanti
Optimalisasi Media Penyimpanan Pada Sistem Inventori Stok Barang Untuk Pt. Multi Usaha Sejahtera Jaya Menggunakan Metode Goldbach Codes, Angga Debby Frayudha, Siti Purwanti
Elinvo (Electronics, Informatics, and Vocational Education)
Pengelolaan data secara konvensional, baik manual pada buku maupun penggunaan aplikasi pengolah data (kata atau angka) dinilai masih memiliki keterbatasan terutama dalam hal keterjangkauan akses dan pengelolaan. Sistem informasi inventori mampu menyajikan pengelolaan data berupa informasi-informasi yang dibutuhkan untuk produktivitas tempat usaha sesuai karakteristik pengguna informasi pada tempat usaha tersebut. Lebih lanjut untuk proses transmisi data yang lebih baik, diperlukan optimalisasi media penyimpanan melalui teknik kompresi data tertentu. Salah satu algoritma kompresi data teks yang memiliki keunggulan pada optimalisasi ukuran hasil kompresi adalah Goldbach Codes. Artikel ini mendeskripsikan pengembangan sistem pengelolaan inventori dengan kemampuan dapat menyimpan maupun mengubah data stok …
Penerapan Model Utaut 2 Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Penggunaan Siortu, Nur Azmi Ainul Bashir
Penerapan Model Utaut 2 Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Penggunaan Siortu, Nur Azmi Ainul Bashir
Elinvo (Electronics, Informatics, and Vocational Education)
Layanan sistem informasi akademik untuk orang tua (SIORTU) telah banyak diterapkan di kampus-kampus, salah satunya adalah Universitas Islam Indonesia (UII). Nama resmi SIORTU UII yaitu UNISYS untuk orang tua. Belum banyak orang tua atau wali mahasiswa yang menggunakan SIORTU. Tercatat hanya 7.361 akun SIORTU yang aktif pada rentang April 2018 s.d Maret 2019. Jumlah tersebut hanya 36.68% dari jumlah akun yang disediakan untuk orang tua mahasiswa angkatan 2015-2018 yaitu 20.068 akun. Penelitian ini merupakan pengembangan penelitian yang telah dilakukan sebelumnya. Penelitian ini merupakan penelitian kuantitatif. Data yang dianalisis diperoleh dari data penelitian yang dikembangkan. Tujuan penelitian ini adalah mengetahui pengaruh …
Cat Tracks – Tracking Wildlife Through Crowdsourcing Using Firebase, Tracy Ho
Cat Tracks – Tracking Wildlife Through Crowdsourcing Using Firebase, Tracy Ho
Master's Projects
Many mountain lions are killed in the state of California every year from roadkill. To reduce these numbers, it is important that a system be built to track where these mountain lions have been around. One such system could be built using the platform-as-a-service, Firebase. Firebase is a platform service that collects and manages data that comes in through a mobile application. For the development of cross-platform mobile applications, Flutter is used as a toolkit for developers for both iOS and Android. This entire system, Cat Tracks is proposed as a crowdsource platform to track wildlife, with the current focus …
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Articles
It is often the case with new technologies that it is very hard to predict their long-term impacts and as a result, although new technology may be beneficial in the short term, it can still cause problems in the longer term. This is what happened with oil by-products in different areas: the use of plastic as a disposable material did not take into account the hundreds of years necessary for its decomposition and its related long-term environmental damage. Data is said to be the new oil. The message to be conveyed is associated with its intrinsic value. But as in …
The Algorithm Project Research And Modeling Of Information Systems, Victoria Kuznetsova, S.B. Dovletova, Mixriddin Raximov, Gulnora Muxtorova, Kim Yelena
The Algorithm Project Research And Modeling Of Information Systems, Victoria Kuznetsova, S.B. Dovletova, Mixriddin Raximov, Gulnora Muxtorova, Kim Yelena
Bulletin of TUIT: Management and Communication Technologies
Pre-project research is a strategic stage of the object design process, based on the results of which a decision is made on the level of competitiveness, development prospects, setting a task for the project, labor intensity and feasibilityof creating a system in general.
The existing methods of pre-project research have a high degree of generalization and are practically not formalized in any way. The disadvantage of these methods is that they consider only specific individual prototypes and are aimed at finding solutions to current problems and eliminating individual shortcomings of a particular prototype. Thus, it Is Concluded that It Is …
Regional Integration: Physician Perceptions On Electronic Medical Record Use And Impact In South West Ontario, Sadiq Raji
Electronic Thesis and Dissertation Repository
Regional initiatives in the health care context in Canada are typically organized and administered along geographic boundaries or operational units. Regional integration of Electronic Medical Records (EMR) has been continuing across Canadian provinces in recent years, yet the use and impact of regionally integrated EMRs are not routinely assessed and questions remain about their impact on and use in physicians’ practices. Are stated goals of simplifying connections and sharing of electronic health information collected and managed by many health services providers being met? What are physicians’ perspectives on the use and impact of regionally integrated EMR? In this thesis, I …
School District Boundaries Map, Nick Huffman
School District Boundaries Map, Nick Huffman
Honors Theses
The purpose of this project is to provide a school district boundary mapping feature to a product sold by Level Data called SDVS, which is a plugin used by districts inside of PowerSchool. Using primarily the features offered by Mapbox, We have implemented a React component that is capable of plotting useful data points related to a student and their school district on a map. The tool is designed to be used primarily by school administrators to determine whether or not a student lives within their district boundaries. The application uses a dataset that is provided by the NCES to …
Stem Teacher Database, Veronica Buss
Stem Teacher Database, Veronica Buss
Honors Theses
The College of Engineering and Applied Sciences (CEAS) Recruitment web application provides access to recruitment information for the Manager of Recruitment and Outreach and those who also use the spreadsheet file with their current data. This database is a functional database for the WMU college of engineering and applied sciences’ recruiters to organize their data on STEM teachers from the feeder high schools of WMU. The app provides an interface for its users to filter and search the data they have compiled to create recruitment mailing reports. The main purpose of this app was to facilitate the retrieval and upkeep …
Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott
Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott
Master's Theses
The endemic eelgrass (Zostera marina) community of Morro Bay Estuary, located on the central coast of California, has experienced an estimated decline of 95% in occupied area (reduction of 344 acres to 20 acres) from 2008 to 2017 for reasons that are not yet definitively clear. One possible driver of degradation that has yet to be investigated is the role of herbicides from agricultural fields in the watershed that feeds into the estuary. Thus, the primary research goal of this project was to better understand temporal and spatial trends of herbicide use within the context of San Luis …
Cross Dataset Evaluation For Iot Network Intrusion Detection, Anjum Farah
Cross Dataset Evaluation For Iot Network Intrusion Detection, Anjum Farah
Theses and Dissertations
With the advent of Internet of Things (IOT) technology, the need to ensure the security of an IOT network has become important. There are several intrusion detection systems (IDS) that are available for analyzing and predicting network anomalies and threats. However, it is challenging to evaluate them to realistically estimate their performance when deployed. A lot of research has been conducted where the training and testing is done using the same simulated dataset. However, realistically, a network on which an intrusion detection model is deployed will be very different from the network on which it was trained. The aim of …
Deep Multi-Task Learning For Depression Detection And Prediction In Longitudinal Data, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel
Deep Multi-Task Learning For Depression Detection And Prediction In Longitudinal Data, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel
Research Collection School Of Computing and Information Systems
Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model's generalizability on small depression …
Design Of A Two-Echelon Freight Distribution System In An Urban Area Considering Third-Party Logistics And Loading-Unloading Zones, Vincent F. Yu, Winarno, Shih-Wei Lin, Aldy Gunawan
Design Of A Two-Echelon Freight Distribution System In An Urban Area Considering Third-Party Logistics And Loading-Unloading Zones, Vincent F. Yu, Winarno, Shih-Wei Lin, Aldy Gunawan
Research Collection School Of Computing and Information Systems
This research examines the problem of designing a two-echelon freight distribution system in a dense urban area that considers third-party logistics (TPL) and loading–unloading zones (LUZs). The proposed system takes advantage of outsourcing the last mile deliveries to a TPL provider and utilizing LUZs as temporary intermediate facilities instead of using permanent intermediate facilities to consolidate freight. A mathematical model and a simulated annealing (SA) algorithm are developed to solve the problem. The efficiency and effectiveness of the proposed SA heuristic are verified by testing it on existing benchmark instances. Computational results show that the performance of the proposed SA …
Sharper Generalisation Bounds For Pairwise Learning, Yunwen Lei, Antoine Ledent, Marius Kloft
Sharper Generalisation Bounds For Pairwise Learning, Yunwen Lei, Antoine Ledent, Marius Kloft
Research Collection School Of Computing and Information Systems
Pairwise learning refers to learning tasks with loss functions depending on a pair of training examples, which includes ranking and metric learning as specific examples. Recently, there has been an increasing amount of attention on the generalization analysis of pairwise learning to understand its practical behavior. However, the existing stability analysis provides suboptimal high-probability generalization bounds. In this paper, we provide a refined stability analysis by developing generalization bounds which can be √nn-times faster than the existing results, where nn is the sample size. This implies excess risk bounds of the order O(n−1/2) (up to a logarithmic factor) for both …
Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas
Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of …
Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun
Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks to the confounding context, e.g., the correct image-level classification of "horse'' and "person'' may be not only due to the recognition of each instance, but also their co-occurrence context, making the model inspection (e.g., CAM) hard to distinguish between the boundaries. Inspired by this, we propose a structural causal model to analyze the causalities among images, contexts, and …
A Social Network Analysis Of Jobs And Skills, Derrick Ming Yang Lee, Dion Wei Xuan Ang, Grace Mei Ching Pua, Lee Ning Ng, Sharon Purbowo, Eugene Wen Jia Choy, Kyong Jin Shim
A Social Network Analysis Of Jobs And Skills, Derrick Ming Yang Lee, Dion Wei Xuan Ang, Grace Mei Ching Pua, Lee Ning Ng, Sharon Purbowo, Eugene Wen Jia Choy, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In this study, we analyzed job roles and skills across industries in Singapore. Using social network analysis, we identified job roles with similar required skills, and we also identified relationships between job skills. Our analysis visualizes such relationships in an intuitive way. Insights derived from our analyses are expected to assist job seekers, employers as well as recruitment agencies wanting to understand trending and required job roles and skills in today’s fast changing world.
Social Media Analytics: A Case Study Of Singapore General Election 2020, Sebastian Zhi Tao Khoo, Leong Hock Ho, Ee Hong Lee, Danston Kheng Boon Goh, Zehao Zhang, Swee Hong Ng, Haodi Qi, Kyong Jin Shim
Social Media Analytics: A Case Study Of Singapore General Election 2020, Sebastian Zhi Tao Khoo, Leong Hock Ho, Ee Hong Lee, Danston Kheng Boon Goh, Zehao Zhang, Swee Hong Ng, Haodi Qi, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
The 2020 Singaporean General Election (GE2020) was a general election held in Singapore on July 10, 2020. In this study, we present an analysis on social conversations about GE2020 during the election period. We analyzed social conversations from popular platforms such as Twitter, HardwareZone, and TR Emeritus.
Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim
Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In light of the #MeToo movement and publicized sexual harassment incidents in Singapore in recent years, we built an analytics pipeline for performing digital social listening on conversations about sexual harassment for AWARE (Association of Women for Action and Research). Our social network analysis results identified key influencers that AWARE can engage for sexual harassment awareness campaigns. Further, our analysis results suggest new hashtags that AWARE can use to run social media campaigns and achieve greater reach.
A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua
A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Modeling the structure of culinary recipes is the core of recipe representation learning. Current approaches mostly focus on extracting the workflow graph from recipes based on text descriptions. Process images, which constitute an important part of cooking recipes, has rarely been investigated in recipe structure modeling. We study this recipe structure problem from a multi-modal learning perspective, by proposing a prerequisite tree to represent recipes with cooking images at a step-level granularity. We propose a simple-yet-effective two-stage framework to automatically construct the prerequisite tree for a recipe by (1) utilizing a trained classifier to detect pairwise prerequisite relations that fuses …
Learning To Dispatch For Job Shop Scheduling Via Deep Reinforcement Learning, Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang, Puay Siew Tan, Xu Chi
Learning To Dispatch For Job Shop Scheduling Via Deep Reinforcement Learning, Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang, Puay Siew Tan, Xu Chi
Research Collection School Of Computing and Information Systems
Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad of specialized knowledge and often delivering limited performance. In this paper, we propose to automatically learn PDRs via an end-to-end deep reinforcement learning agent. We exploit the disjunctive graph representation of JSSP, and propose a Graph Neural Network based scheme to embed the states encountered during solving. The resulting policy network is size-agnostic, effectively enabling generalization on large-scale instances. Experiments show that the agent can learn high-quality PDRs from scratch with elementary raw …
Vision-Based Analytics For Improved Ai-Driven Iot Applications, Amit Sharma
Vision-Based Analytics For Improved Ai-Driven Iot Applications, Amit Sharma
Dissertations and Theses Collection (Open Access)
Proliferation of Internet of Things (IoT) sensor systems, primarily driven by cheaper embedded hardware platforms and wide availability of light-weight software platforms, has opened up doors for large-scale data collection opportunities. The availability of massive amount of data has in-turn given way to rapidly growing machine learning models e.g. You Only Look Once (YOLO), Single-Shot-Detectors (SSD) and so on. There has been a growing trend of applying machine learning techniques, e.g., object detection, image classification, face detection etc., on data collected from camera sensors and therefore enabling plethora of vision-sensing applications namely self-driving cars, automatic crowd monitoring, traffic-flow analysis, occupancy …
Security Analysis Of Permission Re-Delegation Vulnerabilities In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar
Security Analysis Of Permission Re-Delegation Vulnerabilities In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar
Research Collection School Of Computing and Information Systems
The Android platform facilitates reuse of app functionalities by allowing an app to request an action from another app through inter-process communication mechanism. This feature is one of the reasons for the popularity of Android, but it also poses security risks to the end users because malicious, unprivileged apps could exploit this feature to make privileged apps perform privileged actions on behalf of them. In this paper, we investigate the hybrid use of program analysis, genetic algorithm based test generation, natural language processing, machine learning techniques for precise detection of permission re-delegation vulnerabilities in Android apps. Our approach first groups …
Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu
Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only …
Ppmexplorer: Using Information Retrieval, Computer Vision And Transfer Learning Methods To Index And Explore Images Of Pompeii, Cindy Roullet
Ppmexplorer: Using Information Retrieval, Computer Vision And Transfer Learning Methods To Index And Explore Images Of Pompeii, Cindy Roullet
Graduate Theses and Dissertations
In this dissertation, we present and analyze the technology used in the making of PPMExplorer: Search, Find, and Explore Pompeii. PPMExplorer is a software tool made with data extracted from the Pompei: Pitture e Mosaic (PPM) volumes. PPM is a valuable set of volumes containing 20,000 historical annotated images of the archaeological site of Pompeii, Italy accompanied by extensive captions. We transformed the volumes from paper, to digital, to searchable. PPMExplorer enables archaeologist researchers to conduct and check hypotheses on historical findings. We present a theory that such a concept is possible by leveraging computer generated correlations between artifacts using …
Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates
Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates
Information Systems and Analytics Department Faculty Journal Articles
This paper presents student projects analyzing or using blockchain technologies, created by students enrolled in courses dedicated to teaching blockchain, at two different universities during the 2018-2019 academic year. Students explored perceptions related to storing private healthcare information on a blockchain, managing the security of Internet of Things devices, maintaining public governmental records, and creating smart contracts. The course designs, which were centered around project-based learning, include self-regulated learning and peer feedback as ways to improve student learning. Students either wrote a research paper or worked in teams on a programming project to build and deploy a blockchain-based application using …