Systems and Communications Commons^™

Signature Pattern Recognition Using Kohonen Network, Nadia Roosmalita Sari, Mohammad Zoqi Sarwani, Yudha Alif Aulia, Wayan Firdaus Mahmudy

Knowledge Engineering and Data Science

A signature is a special form of handwriting that used for human identification process. The current identification process is extremely ineffective. People have to manually compare signatures with the previously stored data. This study proposed SOM Kohonen algorithm as the method of signature pattern recognition. This method has able to visualize high-dimensional data. The image processing method is used in this study in pre-processing data phase. The accuracy of SOM Kohonen was 70 %, indicated the method used was good enough for pattern recognition.

Digit Classification Of Majapahit Relic Inscriptionusing Glcm-Svm, Tri Septianto, Endang Setyati, Joan Santoso

Knowledge Engineering and Data Science

A higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition.Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In this paper, we propose the classification of the digit of the year of a relic inscription in the Kingdom of Majapahit using Support Vector Machine (SVM). This method is able to cope with very large feature dimensions and without reducing existing features extraction. While the method used for feature extraction using the Gray-Level Co-Occurrence Matrix (GLCM), special for texture …

Change Vulnerability Forecasting For Southeast Asiausing Deep Learning Algorithm, Amelia Ritahani Ismail, Nur 'Atikah Binti Mohd Ali, Junaida Sulaiman

Knowledge Engineering and Data Science

Climate change is expected to change people’s livelihood in significant ways. Several vulnerability factors and readiness factors used for measuring the prediction index of that particular country on how vulnerable of a country towards global change. Primary data was collected from University of Notre Dame Global Adaptation Index (NDGAIN). The data has been trained for the forecasting purpose with support from the validated statistical analysis. The summary of the predicted index is visualized using machine learning tools. The results developed the correlation between vulnerability and readiness factors and shows the stability of the country towards climate change. The framework is …

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 …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

Autoprov: An Automated File Provenance Collection Tool, Ryan A. Good

Theses and Dissertations

A file's provenance is a detailing of its origins and activities. There are tools available that are useful in maintaining the provenance of a file. Unfortunately for digital forensics, these tools require prior installation on the computer of interest while provenance generating events happen. The presented tool addresses this by reconstructing a file's provenance from several temporal artifacts. It identifies relevant temporal and user correlations between these artifacts, and presents them to the user. A variety of predefined use cases and real world data are tested against to demonstrate that this software allows examiners to draw useful conclusions about the …

System For Workout Information Management, Mark Archual, Ethan E. Schweinsberg

Williams Honors College, Honors Research Projects

Power racks are a weight machine used by swimmers to provide resistance while they swim away from a wall toward the center of the pool. The objective of this project is to build a modular data system that can be added to these machines to record and log quantitative information during their use. This information will be stored on a web server, and made available to the user for analysis and visualization through a web application. Workout data can also be downloaded and interpreted at a later time, independent of the web application. The data system should be water resistant, …

Optimizing Virtual Machine I/O Performance In Cloud Environments, Tao Lu

Theses and Dissertations

Maintaining closeness between data sources and data consumers is crucial for workload I/O performance. In cloud environments, this kind of closeness can be violated by system administrative events and storage architecture barriers. VM migration events are frequent in cloud environments. VM migration changes VM runtime inter-connection or cache contexts, significantly degrading VM I/O performance. Virtualization is the backbone of cloud platforms. I/O virtualization adds additional hops to workload data access path, prolonging I/O latencies. I/O virtualization overheads cap the throughput of high-speed storage devices and imposes high CPU utilizations and energy consumptions to cloud infrastructures. To maintain the closeness between …

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

Electrical and Computer Engineering Faculty Publications

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.

Comparing The Efficiency Of Heterogeneous And Homogeneous Data Center Workloads, Brandon Kimmons

College of Graduate Studies: Theses & Dissertations

Abstract

Information Technology, as an industry, is growing very quickly to keep pace with increased data storage and computing needs. Data growth, if not planned or managed correctly, can have larger efficiency implications on your data center as a whole. The long term reduction in efficiency will increase costs over time and increase operational overhead. Similarly, increases in processor efficiency have led to increased system density in data centers. This can increase cost and operational overhead in your data center infrastructure.

This paper proposes the idea that balanced data center workloads are more efficient in comparison to similar levels of …

Active Storage And Ssd Caching In An Object Storage Environment, Michael T. Runde

Master's Theses

The advancing performance and lowering costs required to implement additional processing power on system peripherals such as disk drives are increasingly allowing additional computing ability to be located directly on individual drives. Active Storage attempts to take advantage of this excess by moving some computationally intensive applications directly to the disk drives. This can remove the bottlenecks seen through interconnects between the drives and the CPU of an initiating system as well as remove the need for systems to handle these applications.

The contributions of this thesis are in two areas. The first is the development of a framework designed …

Calibration Of Complex System Dynamics Models: A Practioner's Report, Rod Walker, Wayne Wakeland

Complex Systems Faculty Publications and Presentations

This paper is not a typical academic paper that is solidly grounded in the literature. Instead, this paper reports practitioner’s experiences in rebuilding and calibrating a very large system dynamics model. A prior version of this model had been in use for over 10 years in an ongoing executive training simulation. That model had never worked correctly in several key areas, requiring the outputs to be manually adjusted by very experienced facilitators during the course of the simulation. The present project rebuilt the system dynamics model, redesigned the parts that weren’t working, and calibrated the resulting model to match the …

Scalable And Fault Tolerant Group Key Management, Nicholas A. Lupien

Theses and Dissertations

To address the group key management problem for modern networks this research proposes a lightweight group key management protocol with a gossip-based dissemination routine. Experiments show that by slightly increasing workload for the key update mechanism, this protocol is superior to currently available tree-based protocols with respect to reliability and fault tolerance, while remaining scalable to large groups. Java simulations show that the protocol efficiently distributes keys to large groups in the midst of up to 35 percent node failure rates. In addition, it eliminates the need for logical key hierarchy while preserving an overall reduction in rekey messages to …

Architecture For Intelligent Power Systems Management, Optimization, And Storage., J. Chris Foreman

Electronic Theses and Dissertations

The management of power and the optimization of systems generating and using power are critical technologies. A new architecture is developed to advance the current state of the art by providing an intelligent and autonomous solution for power systems management. The architecture is two-layered and implements a decentralized approach by defining software objects, similar to software agents, which provide for local optimization of power devices such as power generating, storage, and load devices. These software device objects also provide an interface to a higher level of optimization. This higher level of optimization implements the second layer in a centralized approach …

An Operational Model For Mobile Sensor Cloud Management, Indrajeet Kalyankar

Electrical & Computer Engineering Theses & Dissertations

Mobile sensors provide a safe, cost effective method for gathering information in hazardous environments. When the hazardous environment is either unexplored, such as the surface of Mars, or unanticipated, such as the result of chemical contamination, it is desirable for a system to gather information with a minimal amount of outside control (localization, decision control, etc.) and prepositioned sensors. If one takes a look at the number of the sensors deployed on a scale, at the lower end is the sole, multipurpose sensor unit. The upper end deals with hordes of inexpensive, expendable sensors. In the middle, a cluster of …

Compiling Unit Clauses For The Warren Abstract Machine, George D. Herbert

UNF Graduate Theses and Dissertations

This thesis describes the design, development, and installation of a computer program which compiles unit clauses generated in a Prolog-based environment at Argonne National Laboratories into Warren Abstract Machine (WAM) code. The program enhances the capabilities of the environment by providing rapid unification and subsumption tests for the very significant class of unit clauses. This should improve performance substantially for large programs that generate and use many unit clauses.