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Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat 2020 Department of Electrical Engineering, Politeknik Negeri Padang, Indonesia

Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat

Knowledge Engineering and Data Science

Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast Region Based Convolutional Neural Networks (RCNN), Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was …


Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski 2020 Electrical Engineering Department, Universitas Negeri Malang, Indonesia

Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski

Knowledge Engineering and Data Science

Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created …


Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman 2020 Faculty of Computer Science, Brawijaya University, Indonesia

Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman

Knowledge Engineering and Data Science

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one …


Docs_On_Blocks – A Defense In Depth Strategy For E-Healthcare, Saad Mohammed 2020 California State University - San Bernardino

Docs_On_Blocks – A Defense In Depth Strategy For E-Healthcare, Saad Mohammed

Electronic Theses, Projects, and Dissertations

With the increase in the data breaches and cyber hacks, organizations have come to realize that cyber security alone would not help as the attacks are becoming more sophisticated and complex than ever. E-Healthcare industry has shown a promising improvement in terms of security over the past, but the threat remains. Thus, the E-Healthcare industries are aiming towards a Defense in Depth Strategy approach.

The project here describes how a Defense in Depth Strategy for E-Healthcare system can provide an environment for better security of the data and peer-to-peer interaction with stakeholders. The legacy systems have at some point failed …


Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari 2020 Department of Informatics, Universitas Ahmad Dahlan, Indonesia

Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari

Knowledge Engineering and Data Science

Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is …


Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani 2020 Department of Information Technology, Universitas Pendidikan Nasional, Indonesia

Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani

Knowledge Engineering and Data Science

Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are …


A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad 2020 Department of Computer Information Systems, Al-Quds Open University, Palestine

A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad

Knowledge Engineering and Data Science

Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new …


The Effect Of Information Technology Audit For E-Health Of Indonesia Using Itil Framework V.3 Domain Service Design, Eva Mufidah, Ilham M, Anis Eliyana, Tanti Handriana, Indrianawati Usman 2020 Airlangga University Of Surabaya, Indonesia

The Effect Of Information Technology Audit For E-Health Of Indonesia Using Itil Framework V.3 Domain Service Design, Eva Mufidah, Ilham M, Anis Eliyana, Tanti Handriana, Indrianawati Usman

Library Philosophy and Practice (e-journal)

This study explain about E-Health Surabaya is a web-based health service technology application that is used to help people register as patients in hospitals and health centers. Although its function is very useful, there are also people who still do not understand how to use this application, there are also some shortcomings that cause inconvenience in its use. So that research is conducted in which the application uses ITIL V.3 framework with Domain Service Design to conduct an audit of the maturity level of this E-Health Surabaya Web Application. ITIL (Information Technology Infrastructure Technology) is a framework used to manage …


Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle 2020 University of New Mexico

Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle

Computer Science ETDs

Existing communication protocols in security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing visual imagers and microwave sensor information. These data types are ubiquitous in perimeter security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm …


Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao LIU, Guomin YANG, Guomin YANG 2020 Singapore Management University

Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang

Research Collection School Of Computing and Information Systems

In a cloud data storage system, symmetric key encryption is usually used to encrypt files due to its high efficiency. In order allow the untrusted/semi-trusted cloud storage server to perform searching over encrypted data while maintaining data confidentiality, searchable symmetric encryption (SSE) has been proposed. In a typical SSE scheme, a users stores encrypted files on a cloud storage server and later can retrieve the encrypted files containing specific keywords. The basic security requirement of SSE is that the cloud server learns no information about the files or the keywords during the searching process. Some SSE schemes also offer additional …


Dbknot: A Transparent And Seamless, Pluggable Tamper Evident Database, Islam Khalil 2020 American University in Cairo

Dbknot: A Transparent And Seamless, Pluggable Tamper Evident Database, Islam Khalil

Theses and Dissertations

Database integrity is crucial to organizations that rely on databases of important data. They suffer from the vulnerability to internal fraud. Database tampering by internal malicious employees with high technical authorization to their infrastructure or even compromised by externals is one of the important attack vectors.

This thesis addresses such challenge in a class of problems where data is appended only and is immutable. Examples of operations where data does not change is a) financial institutions (banks, accounting systems, stock market, etc., b) registries and notary systems where important data is kept but is never subject to change, and c) …


Supply Chain Analysis To Determine E-Commerce Distribution Center Locations, Fatima Chebchoub 2020 Western Kentucky University

Supply Chain Analysis To Determine E-Commerce Distribution Center Locations, Fatima Chebchoub

Masters Theses & Specialist Projects

Supply chain management is the key success for each business. Having a robust supply chain will help the business to improve service, quality, reduce the costs, improve the speed, and be more flexible. Organizations need to look at data and deploy plans to move the product from operation to logistics to manage a global chain. In this paper we will use E-Comm shipment data to identify the best locations to build a new distribution center (DC).


A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B. 2020 University of New Mexico

A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.

Branch Mathematics and Statistics Faculty and Staff Publications

With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a …


Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene YADAMJAV, Zhifeng BAO, Baihua ZHENG, Farhana M. CHOUDHURY, Hanan SAMET 2020 Royal Melbourne Institute of Technology

Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet

Research Collection School Of Computing and Information Systems

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on …


Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui MA, Rui ZHANG, Guomin YANG, Zishuai ZONG, Kai HE, Yuting XIAO 2020 Singapore Management University

Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao

Research Collection School Of Computing and Information Systems

Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …


Tech Policy And Legal Theory Syllabus, Yafit Lev-Aretz, Nizan Packin 2020 CUNY Bernard M Baruch College

Tech Policy And Legal Theory Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Technology has changed dramatically over the last couple of decades. Currently, virtually all business industries are powered by large quantities of data. The potential as well as actual uses of business data, which oftentimes includes personal user data, raise complex issues of informed consent and data protection. This course will explore many of these complex issues, with the goal of guiding students into thinking about tech policy from a broad ethical perspective as well as preparing students to responsibly conduct themselves in different areas and industries in a world growingly dominated by technology.


Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen YIN, Chenghao LIU, Weiqing WANG, Jianling SUN, Steven C. H. HOI 2020 Zhejiang University

Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance of sequential modeling heavily depends on the scale and quality of historical behaviors. However, the number of user behaviors inherently follows a long-tailed distribution, which has been seldom explored. In this work, we argue that focusing on tail users could bring more benefits and address the long tails issue by learning transferrable parameters from both optimization and feature perspectives. Specifically, we propose a gradient alignment optimizer and adopt an adversarial training scheme to facilitate knowledge transfer …


Auditing Database Systems Through Forensic Analysis, James Wagner 2020 DePaul University

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 2020 Singapore Management University

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 …


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 2020 Cyberange Global Holdings PTE, Singapore

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 …


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