Computer Engineering Commons^™

Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv

Houbing Song

With the continuous development of information technology, enterprises, universities and governments are constantly stepping up the construction of electronic personnel information management system. The information of hundreds of thousands or even millions of people’s information are collected and stored into the system. So much information provides the cornerstone for the development of big data, if such data is tampered with or leaked, it will cause irreparable serious damage. However, in recent years, electronic archives have exposed a series of problems such as information leakage, information tampering, and information loss, which has made the reform of personnel information management more and …

Developing A Workflow To Integrate Tree Inventory Data Into Urban Energy Models, Farzad Hashemi, Breanna L. Marmur, Ulrike Passe, Janette R. Thompson

Farzad Hashemi

Building energy simulation is of considerable interest and benefit for architects, engineers, and urban planners. Only recently has it become possible to develop integrated energy models for clusters of buildings in urban areas. Simulating energy consumption of the built environment on a relatively large scale (e.g., such as a neighborhood) will be necessary to obtain more reliable results, since building energy parameters are influenced by characteristics of the nearby environment. Therefore, the construction of a 3-D model of urban built areas with detail of the near-building environment should enhance simulation approaches and provide more accurate results. This paper describes the …

Eliminating Data Redundancy: Our Solution For Database Discovery Using Alma/Primo, Jacob Kindle, Travis Clamon

Travis Clamon

East Tennessee State University recently adopted Alma & Primo and was suprised by the lack of an A-Z database discovery module. Frustrated by having to maintain electronic resources separately on our library website and in Alma, we embarked on a goal to eliminate redundancy and use Alma/Primo exclusively. This presentation will cover our entire workflow in both Alma & Primo and the issues we encountered along the way. I'll first go over our process in Alma including MARC record creation, electronic collection setup, and the top level collection module. Next, I'll cover our workflow in Primo including normalization rules, scoping, …

Building A Data “Deep State” @Gvsu, Matt Schultz

Matt Schultz

Maa & Mmdp: Fall Workshop 2016 With Mid-Michigan Digital Practitioners, Matt Schultz, Annie Benefiel

Matt Schultz

A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari

Vijayan K. Asari

This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames.

We anticipate that such key frame selection technique will have significant impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery. Three real-world datasets are used for evaluation and testing and the observed results are encouraging.

Data Provisioning For The Object Modeling System (Oms), Jack R. Carlson, Olaf David, Wes J. Lloyd, George H. Leavesley, Ken W. Rojas, Timothy R. Green, Mazdak Arabi, Lucas Yaege, Hom Kipka

Wes Lloyd

The Object Modelling System (OMS) platform supports initiatives to build or re-factor agro-environmental models and deploy them in different business contexts as model services on cloud computing platforms. Whether traditional desktop, client-server, or emerging cloud deployments, success especially at the enterprise level relies on stable and efficient data provisioning to the models. In this paper we describe recent experience and trends with tools and services deployed to cloud platforms. Also, systematic, sustained data stewardship and alignment with standards organizations impart stability to data provisioning efforts.

The Virtual Machine (Vm) Scaler: An Infrastructure Manager Supporting Environmental Modeling On Iaas Clouds, Wes J. Lloyd, Olaf David, Mazdak Arabi, James C. Ascough Ii, Timothy R. Green, Jack R. Carlson, Ken W. Rojas

Wes Lloyd

Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific modeling “as-a-service” requires dynamic scaling of server infrastructure to adapt to changing user workloads. This paper presents the Virtual Machine (VM) Scaler, an autonomic resource manager for IaaS Clouds. We have developed VM-Scaler, a REST/JSON-based web services application which supports infrastructure provisioning and management to support scientific modeling for the Cloud Services Innovation Platform (CSIP) [Lloyd et al. 2012]. VM-Scaler harnesses the Amazon Elastic Compute Cloud (EC2) …

Metadata For Describing Water Models, Mohamed M. Morsy, Jonathan L. Goodall, Christina Bandaragoda, Anthony M. Castronova, Jane Greenberg

Anthony Castronova

Computer models are widely used in hydrology and water resources management. A large variety of models exist, each tailored to address specific challenges related to hydrologic science and water resources management. When scientists and engineers apply one of these models to address a specific question, they must devote significant effort to set up, calibrate, and evaluate that model instance built for some place and time. In many cases, there is a benefit to sharing these computer models and associated datasets with the broader scientific community. Core to model reuse in any context is metadata describing the model. A standardized metadata …

Joining The Table: Advancing Digital Discussions At Gvsu, Matt Schultz, Kyle Felker

Matt Schultz

Data And Network Optimization Effect On Web Performance, Steven Rosenberg, Surbhi Dangi, Isuru Warnakulasooriya

Surbhi Dangi

In this study, we measure the effects of two software approaches to improving data and network performance: 1. Content optimization and compression; and 2. Optimizing network protocols. We achieve content optimization and compression by means of BoostEdge by ActivNetworks and employ the SPDY network protocol by Google to lower the round trip time for HTTP transactions. Since the data and transport layers are separate, we conclude our investigation by studying the combined effect of these two techniques on web performance. Using document mean load time as the measure, we found that with and without packet loss, both BoostEdge and SPDY …

Bridging Researchers’ Active Data Storage Needs, Matt Schultz

Matt Schultz

Gvsu Repository Migration Update, Matt Schultz

Matt Schultz

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Wilson A Higashino

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Hair-Oriented Data Model For Spatio-Temporal Data Mining, Abbas Madraky, Zulaiha Ali Othman, Razak Hamdan

Abbas Madraky

Spatio-temporal data are complex in terms of number of attributes for spatial and temporal values, and the data are changing towards time. Traditional method to mining the spatio-temporal data is the fact that the data is stored in data warehouse in un-normalization form as union of spatial and temporal data know as tabular data warehouse. A Hair-Oriented Data Model (HODM) has been proved as a suitable data model for spatio-temporal data. It has reduced the file size and decreased query execution time. The spatio-temporal data stored using the HODM known as Hair-Oriented Data warehouse. However, this paper aims to presents …

Analytic Methods For Spatio-Temporal Data In A Nature-Inspired Data Model, Abbas Madraky, Zulaiha Ali Othman, Abd Razak Hamdan

Abbas Madraky

We are surrounded by information and much of it needs to be stored and analyzed. Data analysis would be easier if the data storage structure were closer to that of a natural data structure. Many storage structures and related methods have been proposed in recent years due to the importance of understanding spatial-temporal information associated with a particular place and time. In this paper, some of the most important analytic methods for spatio-temporal data are considered and categorized in terms of their algorithms. We also describe the difficulties of knowledge representation when dealing with spatio-temporal data. In addition, three of …

Disaster Data Management In Cloud Environments, Katarina Grolinger

Katarina Grolinger

Facilitating decision-making in a vital discipline such as disaster management requires information gathering, sharing, and integration on a global scale and across governments, industries, communities, and academia. A large quantity of immensely heterogeneous disaster-related data is available; however, current data management solutions offer few or no integration capabilities and limited potential for collaboration. Moreover, recent advances in cloud computing, Big Data, and NoSQL have opened the door for new solutions in disaster data management. In this thesis, a Knowledge as a Service (KaaS) framework is proposed for disaster cloud data management (Disaster-CDM) with the objectives of 1) facilitating information gathering …

Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz

Katarina Grolinger

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …

Population Validity For Educational Data Mining Models: A Case Study In Affect Detection, Ryan Baker, Jaclyn Ocumpaugh, Sujith Gowda, Neil Heffermnan, Cristina Heffernan

Ryan S.J.d. Baker

ICT-enhanced research methods such as educational data mining (EDM) have allowed researchers to effectively model a broad range of constructs pertaining to the student, moving from traditional assessments of knowledge to assessment of engagement, meta-cognition, strategy, and affect. The automated detection of these constructs allows EDM researchers to develop intervention strategies that can be implemented either by the software or the teacher. It also allows for secondary analyses of the construct, where the detectors are applied to a data set that is much larger than one that could be analyzed by more traditional methods. However, in many cases, the data …

Research Data Management In The Curriculum: An Interdisciplinary Approach, Anna Maria Tammaro, Vittore Casarosa

Anna Maria Tammaro

The increase of digital content in the broad areas of Institutional and domain specific Repositories, Libraries, Archives and Museums and the increased interest in the sharing and preservation of "research data" have triggered the emergence of new roles such as Data Curator. The paper refers about the on-going investigation of current data curator education and training programs with regard to the role of information professionals and/or data scientists in the research lifecycle. The investigation has been based on a series of workshops and events discussing the concerns of researchers and teachers about digital library and digital curation. A first list …

Big Data, Predictive Analytics, And Data Visualization In The Construction Engineering, Joseph Shrestha

Joseph Shrestha

Rapport: Semantic-Sensitive Namespace Management In Large-Scale File Systems, Yu Hua, Hong Jiang, Yifeng Zhu, Dan Feng

Yifeng Zhu

Explosive growth in volume and complexity of data exacerbates the key challenge to effectively and efficiently manage data in a way that fundamentally improves the ease and efficacy of their use. Existing large-scale file systems rely on hierarchically structured namespace that leads to severe performance bottlenecks and renders it impossible to support real-time queries on multi-dimensional attributes. This paper proposes a novel semantic-sensitive scheme, called Rapport, to provide dynamic and adaptive namespace management and support complex queries. The basic idea is to build files’ namespace by utilizing their semantic correlation and exploiting dynamic evolution of attributes to support namespace management. …

The Smart Way To Manage Research Data, Craig Napier, Despina Clancy, Tim Davies, Katie Elcombe

Craig Napier

The University of Wollongongs' $62 million SMART (Simulation, Modelling, Analysis, Research, Teaching) Infrastructure Facility will become a research and development powerhouse with an unprecedented level of impact within the broader infrastructure sector nationally and overseas [1]. With a vision to be a world class intellectual leader and educator in 'integrated' infrastructure planning and management and the capacity to host 200 PhD students, comprising 30 integrated research laboratories, data demands and volume are increasing exponetially.

Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin L. Griss

Martin L Griss

This research addresses the use of mobile devices with both embedded and external sensors to provide contextualized help, advice, and remediation to learners engaged in real-world learn-by-doing tasks. This work is situated within the context of learning a complex procedure, in particular emergency responders learning to conduct urban search and rescue operations. Research issues include the design and delivery of contextualized performance support and the inferring of learner actions and intentions from sensor data to ensure that the right support is delivered just in time, as it is relevant to what the learner is doing.

Hair Data Model: A New Data Model For Spatio-Temporal Data Mining, Abbas Madraky, Zulaiha Ali Othman, Abdul Razak Hamdan

Abbas Madraky

Spatio-Temporal data is related to many of the issues around us such as satellite images, weather maps, transportation systems and so on. Furthermore, this information is commonly not static and can change over the time. Therefore the nature of this kind of data are huge, analysing data is a complex task. This research aims to propose an intermediate data model that can represented suitable for Spatio-Temporal data and performing data mining task easily while facing problem in frequently changing the data. In order to propose suitable data model, this research also investigate the analytical parameters, the structure and its specifications …

The Censsis Web-Accessible Image Database System, Furong Yang, David Kaeli

David Kaeli

The Gordon-CenSSIS Web accessible Image Database System (CenSSIS-DB) is a scientific database that enables effective collaborative scientific data sharing and accelerates fundamental research. We describe a state-of-the-art system using the Oracle RDBMS and J2EE technologies to provide remote, Internet based data management. The system incorporates efficient submission and retrieval of images and metadata, indexing of metadata for efficient searching, and complex relational query capabilities.

Digital Content Preservation Across Domain Verticals, Soha Maad, Borislav Dimitrov

Borislav D Dimitrov

The authors present a novel approach to develop scalable systems and services for preserving digital content generated from various application domains. The aim is to deliver an integrative scalable approach for digital content preservation across domain verticals. This would involve consolidating approaches for modeling document workflow, preserving the integrity of heterogeneous data, and developing robust and scalable tools for digital preservation ensuring interoperability across domains verticals. The authors consider various application domains including: healthcare, public, business and finance, media and performing art, and education. The authors focus on specific case studies of digital content preservation across the considered domain verticals. …

Naked Object File System (Nofs): A Framework To Expose An Object-Oriented Domain Model As A File System, Joseph P. Kaylor, Konstantin Läufer, George K. Thiruvathukal

Konstantin Läufer

We present Naked Objects File System (NOFS), a novel framework that allows a developer to expose a domain model as a file system by leveraging the Naked Objects design principle. NOFS allows a developer to construct a file system without having to understand or implement all details related to normal file systems development. In this paper we explore file systems frameworks and object-oriented frameworks in a historical context and present an example domain model using the framework. This paper is based on a fully-functional implementation that is distributed as free/open source software, including virtual machine images to demonstrate and study …

The Hydra Filesystem: A Distrbuted Storage Famework, Benjamin Gonzalez, George K. Thiruvathukal

George K. Thiruvathukal

Hydra File System (HFS) is an experimental framework for constructing parallel and distributed filesystems. While parallel and distributed applications requiring scalable and flexible access to storage and retrieval are becoming more commonplace, parallel and distributed filesystems remain difficult to deploy easily and configure for different needs. HFS aims to be different by being true to the tradition of high-performance computing while employing modern design patterns to allow various policies to be configured on a per instance basis (e.g. storage, communication, security, and indexing schemes). We describe a working prototype (available for public download) that has been implemented in the Python …

Scalable Implementations Of Mpi Atomicity For Concurrent Overlapping I/O, Wei-Keng Liao, Alok Choudhary, Kenin Coloma, George K. Thiruvathukal, Lee Ward, Eric Russell, Neil Pundit

George K. Thiruvathukal

For concurrent I/O operations, atomicity defines the results in the overlapping file regions simultaneously read/written by requesting processes. Atomicity has been well studied at the file system level, such as POSIX standard. In this paper, we investigate the problems arising from the implementation of MPI atomicity for concurrent overlapping write access and provide a few programming solutions. Since the MPI definition of atomicity differs from the POSIX one, an implementation that simply relies on the POSIX file systems does not guarantee correct MPI semantics. To have a correct implementation of atomic I/O in MPI, we examine the efficiency of three …