Data Storage Systems Commons^™

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in …

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents

The Relationship Between Organizational Resources And Green It/S Adoption: A Rbv Approach, Lutfus Sayeed, Alberto Onetti

Journal of International Technology and Information Management

ABSTRACT

The objective of the present study was to empirically explore the impact of the implementation of Green IT/S measures on organizational resources in the US and European firms. The study examined the influence of reconfiguration of resources within a firm while adopting various Green IT/S practices and technologies. Green IT/S implementation requires resource commitment from organizations (Bose and Luo, 2011). What are these resources and how do they affect the extent of Green IT/S measures adopted by businesses? Resource Based View (RBV) of the firm was used as the theoretical framework of the study. The relationship between the adoption …

Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla

Electronic Theses, Projects, and Dissertations

In a big organization there are many events organized every day. To know about the events, we typically need to check an events page, rely on flyers or on distributed pamphlets or through word of mouth. To register for an event a user now a days typically does this online which involves inputting user details. At the event, the user either signs a sheet of paper or enters credentials in a web page loaded on a tablet or other electronic device. Typically, this is a time-consuming process with many redundancies like entering user details every time the user wants to …

Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh

Purdue Journal of Service-Learning and International Engagement

Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.

Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.

Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto

Department of Anthropology: Faculty Publications

While digital technologies have been part of archaeology for more than fifty years, archaeologists still look for more efficient methodologies to integrate digital practices of fieldwork recording with data management, analysis, and ultimately interpretation.This Special Issue of the Journal of Field Archaeology gathers international scholars affiliated with universities, organizations, and commercial enterprises working in the field of Digital Archaeology. Our goal is to offer a discussion to the international academic community and practitioners. While the approach is interdisciplinary, our primary audience remains readers interested in web technology and collaborative platforms in archaeology

Is There Space For Violence?: A Data-Driven Approach To The Exploration Of Spatial-Temporal Dimensions Of Conflict, Tin Seong Kam, Vincent Zhi

Research Collection School Of Computing and Information Systems

With recent increases in incidences of political violence globally, the world has now become more uncertain and less predictable. Of particular concern is the case of violence against civilians, who are often caught in the crossfire between armed state or non-state actors. Classical methods of studying political violence and international relations need to be updated. Adopting the use of data analytic tools and techniques of studying big data would enable academics and policy makers to make sense of a rapidly changing world.

A New Framework For Securing, Extracting And Analyzing Big Forensic Data, Hitesh Sachdev, Hayden Wimmer, Lei Chen, Carl Rebman

Journal of Digital Forensics, Security and Law

Finding new methods to investigate criminal activities, behaviors, and responsibilities has always been a challenge for forensic research. Advances in big data, technology, and increased capabilities of smartphones has contributed to the demand for modern techniques of examination. Smartphones are ubiquitous, transformative, and have become a goldmine for forensics research. Given the right tools and research methods investigating agencies can help crack almost any illegal activity using smartphones. This paper focuses on conducting forensic analysis in exposing a terrorist or criminal network and introduces a new Big Forensic Data Framework model where different technologies of Hadoop and EnCase software are …

Simknn: A Scalable Method For In-Memory Knn Search Over Moving Objects In Road Networks, Bin Cao, Chenyu Hou, Suifei Li, Jing Fan, Jianwei Yin, Baihua Zheng, Jie Bao

Research Collection School Of Computing and Information Systems

Nowadays, many location-based applications require the ability of querying k-nearest neighbors over a very large scale of5 moving objects in road networks, e.g., taxi-calling and ride-sharing services. Traditional grid index with equal-sized cells can not adapt6 to the skewed distribution of moving objects in real scenarios. Thus, to obtain the fast querying response time, the grid needs to be split7 into more smaller cells which introduces the side-effect of higher memory cost, i.e., maintaining such a large volume of cells requires a8 much larger memory space at the server side. In this paper, we present SIMkNN, a scalable and in-memory …

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Deep learning methods have been successfully applied to fashion retrieval. However, the latent meaning of learned feature vectors hinders the explanation of retrieval results and integration of user feedback. Fortunately, there are many online shopping websites organizing fashion items into hierarchical structures based on product taxonomy and domain knowledge. Such structures help to reveal how human perceive the relatedness among fashion products. Nevertheless, incorporating structural knowledge for deep learning remains a challenging problem. This paper presents techniques for organizing and utilizing the fashion hierarchies in deep learning to facilitate the reasoning of search results and user intent. The novelty of …

Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As an attractive business model of cloud computing, outsourcing services usually involve online payment and security issues. The mutual distrust between users and outsourcing service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing payment solutions only consider a specific type of outsourcing service and rely on a trusted third-party to realize fairness. In this paper, in order to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or not, we introduce BCPay, a blockchain based fair payment framework for outsourcing services in cloud computing. We first present the …

Exact Processing Of Uncertain Top-K Queries In Multi-Criteria Settings, Kyriakos Mouratidis, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently uncertain due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we introduce the uncertain top-k query (UTK). Given uncertain preferences, that is, …

Learning Representations Of Ultrahigh-Dimensional Data For Random Distance-Based Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu

Research Collection School Of Computing and Information Systems

Learning expressive low-dimensional representations of ultrahigh-dimensional data, e.g., data with thousands/millions of features, has been a major way to enable learning methods to address the curse of dimensionality. However, existing unsupervised representation learning methods mainly focus on preserving the data regularity information and learning the representations independently of subsequent outlier detection methods, which can result in suboptimal and unstable performance of detecting irregularities (i.e., outliers).This paper introduces a ranking model-based framework, called RAMODO, to address this issue. RAMODO unifies representation learning and outlier detection to learn low-dimensional representations that are tailored for a state-of-the-art outlier detection approach - the random …

Retrieval Of Infotainment System Artifacts From Vehicles Using Ive, Celia J. Whelan, John Sammons, Brian Mcmanus, Terry W. Fenger

Journal of Applied Digital Evidence

The analysis of mobile devices and hard drives has been the focus of the digital forensics world for years, but there is another source of potential evidence not often considered: vehicles. Many of today’s “connected cars” have systems that function like computers, storing information they process including user data from devices synced to the system. There has been little to no research done regarding what types of user artifacts can be found on the system, how long these artifacts remain, whether or not the user can remove those artifacts, and whether certain systems provide more information than others. For this …

Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung

Research Collection School Of Computing and Information Systems

It has been widely recognized as a challenge to carry out data analysis and meanwhile preserve its privacy in the cloud. In this work, we mainly focus on a well-known data analysis approach namely association rule mining. We found that the data privacy in this mining approach have not been well considered so far. To address this problem, we propose a scheme for privacy-preserving association rule mining on outsourced cloud data which are uploaded from multiple parties in a twin-cloud architecture. In particular, we mainly consider the scenario where the data owners and miners have different encryption keys that are …

Network Traffic Time Series Performance Analysisusing Statistical Methods, Purnawansyah Purnawansyah, Haviluddin Haviluddin, Rayner Alfred, Achmad Fanany Onnlita Gaffar

Knowledge Engineering and Data Science

This paper presents an approach for a network traffic characterization by using statistical techniques. These techniques are obtained using the decomposition, winter’s exponential smoothing and autoregressive integrated moving average (ARIMA). In this paper, decomposition and winter’s exponential smoothing techniques were used additive and multiplicative model. Then, ARIMA based-on Box-Jenkins methodology. The results of ARIMA (1,0,2) was shown the best model that can be used to the internet network traffic forecasting

Decision Support System Determination Of Main Work Unitin Wpp-711 Using Fuzzy Topsis, Hozairi Hozairi, Yaser Krisnafi

Knowledge Engineering and Data Science

Decision-making to determine the working units for being prioritized to be developed in order to improve fishery monitoring in WPP-711 is imperative. The Ministry of Maritime Affairs and Fisheries should make no mismatch decision-making through long-term calculation and analysis. The problem of determining the priority of working units is a complex problem, thus it is required to find an appropriate method to avoid a mismatch decision. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a decision-making method capable of solving multi-criteria problems. TOPSIS working principle determines the alternative by considering the shortest distance from the positive …

Market Basket Analysis To Identify Customer Behaviorsby Way Of Transaction Data, Fachrul Kurniawan, Binti Umayah, Jihad Hammad, Supeno Mardi Susiki Nugroho, Mochammad Hariadi

Knowledge Engineering and Data Science

Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of …

Capital Letter Pattern Recognition In Text To Speechby Way Of Perceptron Algorithm, Novan Wijaya

Knowledge Engineering and Data Science

Computer vision is a data transformation retrieved or generated from webcam into another form in means of determining decision. All kinds of transformations are carried through to attain specific aims. One of the supporting techniques in implementing computer vision on a system is digital image processing as the objective of digital image processing is to transform digital-formatted picture so that it can be processed in computer. Computer vision and digital image processing can be implemented in a system of capital letter introduction and real-time handwriting reading on a whiteboard supported by artificial neural network mode “perceptron algorithm” used as a …

Sql Logic Error Detection Using Start End Mid Algorithm, Jevri Tri Ardiansyah, Aji Prasetya Wibawa, Triyanna Widiyaningtyas, Okazaki Yasuhisa

Knowledge Engineering and Data Science

Database is an important part of a system and it stores data to be manipulated. SQL (Structured Query Language) is used for manipulating those data to extract information and make decision. There are two types of error which make SQL is challenging to learn, namely syntax error and logic error. Compiler can detect syntax error, but it does not show error warning while logical error occurred. It makes logic error more difficult to understand than syntax error. A web based SQL compiler with errors detection ability by using Start End Mid algorithm is then developed, To help database's user to …