See-Trend: Secure Traffic-Related Event Detection In Smart Communities,
2021
Old Dominion University
See-Trend: Secure Traffic-Related Event Detection In Smart Communities, Stephan Olariu, Dimitrie C. Popescu
Computer Science Faculty Publications
It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed …
Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations,
2021
Old Dominion University
Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox
Computer Science Faculty Publications
Electronic Theses and Dissertations (ETDs) contain domain knowledge that can be used for many digital library tasks, such as analyzing citation networks and predicting research trends. Automatic metadata extraction is important to build scalable digital library search engines. Most existing methods are designed for born-digital documents, so they often fail to extract metadata from scanned documents such as ETDs. Traditional sequence tagging methods mainly rely on text-based features. In this paper, we propose a conditional random field (CRF) model that combines text-based and visual features. To verify the robustness of our model, we extended an existing corpus and created a …
Deep Unsupervised Anomaly Detection,
2021
National University of Singapore
Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin
Research Collection School Of Computing and Information Systems
This paper proposes a novel method to detect anomalies in large datasets under a fully unsupervised setting. The key idea behind our algorithm is to learn the representation underlying normal data. To this end, we leverage the latest clustering technique suitable for handling high dimensional data. This hypothesis provides a reliable starting point for normal data selection. We train an autoencoder from the normal data subset, and iterate between hypothesizing normal candidate subset based on clustering and representation learning. The reconstruction error from the learned autoencoder serves as a scoring function to assess the normality of the data. Experimental results …
Coherence And Identity Learning For Arbitrary-Length Face Video Generation,
2021
Singapore Management University
Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
Face synthesis is an interesting yet challenging task in computer vision. It is even much harder to generate a portrait video than a single image. In this paper, we propose a novel video generation framework for synthesizing arbitrary-length face videos without any face exemplar or landmark. To overcome the synthesis ambiguity of face video, we propose a divide-and-conquer strategy to separately address the video face synthesis problem from two aspects, face identity synthesis and rearrangement. To this end, we design a cascaded network which contains three components, Identity-aware GAN (IA-GAN), Face Coherence Network, and Interpolation Network. IA-GAN is proposed to …
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials,
2021
ETH Zurich
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials, Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Van Gool Luc
Research Collection School Of Computing and Information Systems
There have been emerging a number of benchmarks and techniques for the detection of deepfakes. However, very few works study the detection of incrementally appearing deepfakes in the real-world scenarios. To simulate the wild scenes, this paper suggests a continual deepfake detection benchmark (CDDB) over a new collection of deepfakes from both known and unknown generative models. The suggested CDDB designs multiple evaluations on the detection over easy, hard, and long sequence of deepfake tasks, with a set of appropriate measures. In addition, we exploit multiple approaches to adapt multiclass incremental learning methods, commonly used in the continual visual recognition, …
Facial Emotion Recognition With Noisy Multi-Task Annotations,
2021
Singapore Management University
Facial Emotion Recognition With Noisy Multi-Task Annotations, S. Zhang, Zhiwu Huang, D.P. Paudel, Gool L. Van
Research Collection School Of Computing and Information Systems
Human emotions can be inferred from facial expressions. However, the annotations of facial expressions are often highly noisy in common emotion coding models, including categorical and dimensional ones. To reduce human labelling effort on multi-task labels, we introduce a new problem of facial emotion recognition with noisy multitask annotations. For this new problem, we suggest a formulation from the point of joint distribution match view, which aims at learning more reliable correlations among raw facial images and multi-task labels, resulting in the reduction of noise influence. In our formulation, we exploit a new method to enable the emotion prediction and …
Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction,
2021
Singapore Management University
Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction, Qiuyuan Chen, Xin Xia, Han Hu, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Code summarization aims at generating a code comment given a block of source code and it is normally performed by training machine learning algorithms on existing code block-comment pairs. Code comments in practice have different intentions. For example, some code comments might explain how the methods work, while others explain why some methods are written. Previous works have shown that a relationship exists between a code block and the category of a comment associated with it. In this article, we aim to investigate to which extent we can exploit this relationship to improve code summarization performance. We first classify comments …
Context-Aware Retrieval-Based Deep Commit Message Generation,
2021
Singapore Management University
Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy
Research Collection School Of Computing and Information Systems
Commit messages recorded in version control systems contain valuable information for software development, maintenance, and comprehension. Unfortunately, developers often commit code with empty or poor quality commit messages. To address this issue, several studies have proposed approaches to generate commit messages from commit diffs. Recent studies make use of neural machine translation algorithms to try and translate git diffs into commit messages and have achieved some promising results. However, these learning-based methods tend to generate high-frequency words but ignore low-frequency ones. In addition, they suffer from exposure bias issues, which leads to a gap between training phase and testing phase. …
Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction,
2021
Singapore Management University
Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman
Research Collection School Of Computing and Information Systems
Rewards-based crowdfunding presents an information asymmetry for participants due to the funding mechanism used. Campaign-backers trust creators to complete projects and deliver rewards as outlined prior to the fundraising process, but creators may discover better opportunities as they progress with a project. Despite this, the all-or-nothing (AON) mechanism on crowdfunding platforms incentivizes creators to set meager funding-targets that are easier to achieve but may offer limited slack when creators wish to simultaneously pursue emerging opportunities later in the project. We explore the related issues of how funding targets seem to be selected by the creators, and how dissatisfaction with the …
Three Stages Of Consumers’ Multi-Stage Dichotomic Switching Process: Pre-Switch, Switch, And Post-Switch,
2021
Singapore Management University
Three Stages Of Consumers’ Multi-Stage Dichotomic Switching Process: Pre-Switch, Switch, And Post-Switch, Jussi Nykanen, Virpi K. Tuunainen, Tuure Tuunanen, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This research examines why and how consumers switch their mobile phones. We propose a framework that is grounded on decision-making and motivational theories and draws on the findings from a multinational qualitative survey on consumers’ mobile phone switching process. We show that consumers’ pre-switching decisions are affected by push and pull factors, their mobile phone selections are based on utilitarian or hedonic values, and their justifications for switching are based on cognition or affect. Furthermore, we identify two archetypical routes (i.e., cognitive and affective routes) and three conjoint routes that explain the dichotomic switching processes in pre-switch, switch, and post-switch …
Enabling Efficient Spatial Keyword Queries On Encrypted Data With Strong Security Guarantees,
2021
Singapore Management University
Enabling Efficient Spatial Keyword Queries On Encrypted Data With Strong Security Guarantees, Xiangyu Wang, Jianfeng Ma, Feng Li, Ximeng Liu, Yinbin Miao, Robert H. Deng
Research Collection School Of Computing and Information Systems
Structured Encryption (STE), which allows a server to provide secure search services on encrypted data structures, has been widely investigated in recent years. To meet expressive search requirements in practical applications, a large number of STE constructions have been proposed either on textual keywords or spatial data. However, STE on spatio-textual data, which are widely used in location-based services, has not been fully investigated. In this paper, we formally define the notion of Spatial Keyword Structured Encryption (SKSE) and propose several concrete SKSE constructions with various efficiencysecurity trade-offs. Firstly, we propose a basic construction with linear search complexity, which only …
Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service,
2021
Singapore Management University
Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui
Research Collection School Of Computing and Information Systems
Despite that social media has become a promising alternative to traditional call centers, managers hesitate to fully harness its power because they worry that active service intervention may encourage excessive use of the channel by disgruntled customers. This paper sheds light on such a concern by examining the dynamics between brand-level customer complaints and service interventions on social media. Using details of customer-brand interactions of 40 airlines on Twitter, we find that more service interventions indeed cause more customer complaints, accounting for the online customer population and service quality. However, the increased complaints are primarily driven by the awareness enhancement …
Single And Differential Morph Attack Detection,
2021
West Virginia University
Single And Differential Morph Attack Detection, Baaria Chaudhary
Graduate Theses, Dissertations, and Problem Reports (ETD)
Face recognition systems operate on the assumption that a person's face serves as the unique link to their identity. In this thesis, we explore the problem of morph attacks, which have become a viable threat to face verification scenarios precisely because of their inherent ability to break this unique link. A morph attack occurs when two people who share similar facial features morph their faces together such that the resulting face image is recognized as either of two contributing individuals. Morphs inherit enough visual features from both individuals that both humans and automatic algorithms confuse them. The contributions of this …
Drone-Assisted Emergency Communications,
2020
New Jersey Institute of Technology
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,
2020
New Jersey Institute of Technology
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,
2020
Universitas Negeri Makassar, Indonesia
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,
2020
STMIK Nusa Mandiri, Indonesia
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 …
Penerapan Model Utaut 2 Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Penggunaan Siortu,
2020
Universitas Islam Indonesia, Indonesia
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 …
Optimalisasi Media Penyimpanan Pada Sistem Inventori Stok Barang Untuk Pt. Multi Usaha Sejahtera Jaya Menggunakan Metode Goldbach Codes,
2020
Akademi Komunitas Semen Indonesia Rembang, Indonesia
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 …
Traversal Struktur Data Bipartite Graph Dalam Graph Database Menggunakan Depth-First Search,
2020
Universitas Negeri Yogyakarta, Indonesia
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 …
