A Database Management System For Vision Applications

The Manchester Content Addressable Image Database is ageneric tool which has been designed for image informatics and computer vision problems. The system stores pre-compuied feature tokens, which are obtained by conventional processing of the input images, into a database which is accessed by a specialised query language (M VQL [1]). The M VQL is based on the creation and refinement of groups of features by computing attributes. We illustrate the system with an application concerned with the detection and classification of microfossil images. We use the MVQL to express a projective circular Hough Transform for microfossil detection. We also address the problem of classifying detected structures into six broad morphological groups. This is achieved using MVQL to define "structure " measures from the distribution of curve tokens in a circular region around each microfossil. 1. Introduction. The aim of this paper is to present a simple database management system (dbms), which includes a data entry system, query interface and some graphical capability, which has been specifically designed for vision research. The work is particularly motivated b

AmbientDB: P2P Data Management Middleware for Ambient Intelligence

The future generation of consumer electronics devices is envisioned to provide automatic cooperation between devices and run applications that are sensitive to people's likings, personalized to their requirements, anticipatory of their behavior and responsive to their presence. We see this `Ambient Intelligence' as a key feature of future pervasive computing. We focus here on one of the challenges in realizing this vision: information management. This entails integrating, querying, synchronizing and evolving structured data, on a heterogeneous and ad-hoc collection of (mobile) devices. Rather than hard-coding data management functionality in each individual application, we argue for adding highlevel data management functionalities to the distributed middleware layer. Our AmbientDB P2P database management system addresses this by providing a global database abstraction over an ad-hoc network of heterogeneous peers

Software Sharing Enables Smarter Content Management

In 2004, NASA established a technology partnership with Xerox Corporation to develop high-tech knowledge management systems while providing new tools and applications that support the Vision for Space Exploration. In return, NASA provides research and development assistance to Xerox to progress its product line. The first result of the technology partnership was a new system called the NX Knowledge Network (based on Xerox DocuShare CPX). Created specifically for NASA's purposes, this system combines Netmark-practical database content management software created by the Intelligent Systems Division of NASA's Ames Research Center-with complementary software from Xerox's global research centers and DocuShare. NX Knowledge Network was tested at the NASA Astrobiology Institute, and is widely used for document management at Ames, Langley Research Center, within the Mission Operations Directorate at Johnson Space Center, and at the Jet Propulsion Laboratory, for mission-related tasks

Data Sharing based on Facial Recognition Clusters

The evolution of computer vision technologies has led to the emergence of novel applications across various sectors, with face detection and recognition systems taking center stage. In this research paper, we present a comprehensive examination and implementation of a face detection project that harnesses the cutting-edge face recognition model. Our primary aim is to create a reliable and effective system that can be seamlessly integrated into functions allowing users to input their image to capture their facial features, subsequently retrieving all images linked to their identity from a database. Our strategy capitalizes on the dlib library and its face recognition model, which com- bines advanced deep learning methods with traditional computer vision techniques to attain highly accurate face detection and recognition. The essential elements of our system encompass face detection, face recognition, and image retrieval. Initially, we employ the face recognition model to detect and pinpoint faces within the captured image. Following that, we employ facial landmarks and feature embeddings to recognize and match the detected face with entries in a database. Finally, we retrieve and present all images connected to the recognized individual. To validate the effectiveness of our system, we conducted extensive experiments on a diverse dataset that encompasses various lighting conditions, poses, and facial expressions. Our findings demonstrate exceptional accuracy and efficiency in both face detection and recognition, rendering our approach suitable for real-world applications. We envision a broad spectrum of potential applications for our system, including access control, event management, and personal media organization

ART Neural Networks: Distributed Coding and ARTMAP Applications

ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial forecasting, machine tool monitoring, digital circuit design, chemical analysis, and robot vision. Supervised ART architectures, called ARTMAP systems, feature internal control mechanisms that create stable recognition categories of optimal size by maximizing code compression while minimizing predictive error in an on-line setting. Special-purpose requirements of various application domains have led to a number of ARTMAP variants, including fuzzy ARTMAP, ART-EMAP, Gaussian ARTMAP, and distributed ARTMAP. ARTMAP has been used for a variety of applications, including computer-assisted medical diagnosis. Medical databases present many of the challenges found in general information management settings where speed, efficiency, ease of use, and accuracy are at a premium. A direct goal of improved computer-assisted medicine is to help deliver quality emergency care in situations that may be less than ideal. Working with these problems has stimulated a number of ART architecture developments, including ARTMAP-IC [1]. This paper describes a recent collaborative effort, using a new cardiac care database for system development, has brought together medical statisticians and clinicians at the New England Medical Center with researchers developing expert systems and neural networks, in order to create a hybrid method for medical diagnosis. The paper also considers new neural network architectures, including distributed ART {dART), a real-time model of parallel distributed pattern learning that permits fast as well as slow adaptation, without catastrophic forgetting. Local synaptic computations in the dART model quantitatively match the paradoxical phenomenon of Markram-Tsodyks [2] redistribution of synaptic efficacy, as a consequence of global system hypotheses.Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

SPLICEcube Architecture: An Extensible Wi-Fi Monitoring Architecture for Smart-Home Networks

The vision of smart homes is rapidly becoming a reality, as the Internet of Things and other smart devices are deployed widely. Although smart devices offer convenience, they also create a significant management problem for home residents. With a large number and variety of devices in the home, residents may find it difficult to monitor, or even locate, devices. A central controller that brings all the home’s smart devices under secure management and a unified interface would help homeowners and residents track and manage their devices. We envision a solution called the SPLICEcube whose goal is to detect smart devices, locate them in three dimensions within the home, securely monitor their network traffic, and keep an inventory of devices and important device information throughout the device’s lifecycle. The SPLICEcube system consists of the following components: 1) a main cube, which is a centralized hub that incorporates and expands on the functionality of the home router, 2) a database that holds network data, and 3) a set of support cubelets that can be used to extend the range of the network and assist in gathering network data. To deliver this vision of identifying, securing, and managing smart devices, we introduce an architecture that facilitates intelligent research applications (such as network anomaly detection, intrusion detection, device localization, and device firmware updates) to be integrated into the SPLICEcube. In this thesis, we design a general-purpose Wi-Fi architecture that underpins the SPLICEcube. The architecture specifically showcases the functionality of the cubelets (Wi-Fi frame detection, Wi-Fi frame parsing, and transmission to cube), the functionality of the cube (routing, reception from cubelets, information storage, data disposal, and research application integration), and the functionality of the database (network data storage). We build and evaluate a prototype implementation to demonstrate our approach is scalable to accommodate new devices and extensible to support different applications. Specifically, we demonstrate a successful proof-of-concept use of the SPLICEcube architecture by integrating a security research application: an Inside-Outside detection system that classifies an observed Wi-Fi device as being inside or outside the home

A Manufacturing Execution System using Siemens\u27 PC Based Automation Technology

The focus of any manufacturing operation is to establish better yields, reduced cycle times, increase quality, and handle dynamic demand/resource fluctuations. Over the past few years many manufacturing companies have implemented Enterprise Resource Planning (ERP) systems and they have proved themselves to be successful in achieving these goals. However, real-time data is required in order to portray an accurate account of the day-to-day and/or hourly product manufacturing operations. Retrieval of this real-lime data is a challenging task. A Manufacturing Execution System (MES) is a real-time information system that improves the performance of the shop floor operations by linking business planning, order entry, material management, purchasing and accounting to the controls on the factory equipment. Siemens\u27 PC-based automation technology is an emerging technology that appears to provide a robust architecture for integrating all elements of the manufacturing environment. Applications that range from simple control to distributed control and full-fledged MES can be developed using Siemens\u27 architecture. The primary focus of this thesis is applied research to facilitate the development of a Manufacturing Execution System to control a flexible manufacturing system, CAMCELL, using Siemens\u27 PC-based automation technology and Microsoft\u27s database technology. CAMCELL contains two CNC machining centers, assembly robots, and a vision system, all of which are interlinked by a material handling system. The software architecture of the CAMCELL is based on NIST\u27s five level hierarchy. Specifically, it contains functional modules for order entry, scheduling, and routing. In addition to these functional modules, there are various support modules. In this study, we have developed software architecture to achieve vertical integration of the process control layer, the MES layer and the ERP layer. Using Siemens\u27 WinCC software, real-time process data was collected and integrated into an MES database. The study demonstrates how order information stored in a high-level database is converted into useful information for the control layer. The study also demonstrates the ability of WinCC and Visual FoxPro to update the production data into the MES database. Various Operator interface and database screens are proposed for CAMCELL

LEVEL OF COMPETENCY AND EXTENT OF TRAINING NEEDS ON TECHNOLOGY LITERACY AMONG THE STAFF OF GOVERNMENT OFFICES IN CATANDUNAES

 The study assessed the level of competency and the extent of training needs for technology literacy among the staff of the government offices in Catanduanes, Philippines. Along the areas of Computer Operation, WordProcessing, Spreadsheet, Database Management Systems, Internet Services, Computer Programming, Management Information Systems, Systems Analysis and Design (SAD) and Network Design and Management or Administration.  This study made use of a descriptive-survey method wherein a questionnaire was used to determine the level of competencies of the staff on computer literacy and the extent of their training needs on the specified technology literacy areas.   Level of Competency and Extent of Training Needs were measured using a 5-point Likert Scale. Result of the study showed that the staff of the government offices in Catanduanes evaluated themselves as “slightly competent†on the first four technology literacy skills that include: (a) computer operation skills, (b) word processing, (c) spreadsheet, (d) database management and “not competent†on the next five technology literacy skills that were: (a) using the Internet Services, (b) computer programming, (c) SAD/Software Engineering,  (d) MIS and (e) network design & management which means that the staff on the average, have a little knowledge and skills along technology  literacy needed by an office worker hence these staff felt they needed much training for technology literacy. The development and improvement of the knowledge and skills of the government staff in their literacy on the specified technology areas should be the done by the management of the government offices since office transactions nowadays are automated and dependent on information system applications and use of computing resources. Likewise, productivity is enhanced in employing technologies as tools in doing office transactions. Improvement of government staff’s performance would mean satisfied clientele and achievement of the mission, vision, goals and objectives of the organizatio

Crew and Display Concepts Evaluation for Synthetic / Enhanced Vision Systems

NASA s Synthetic Vision Systems (SVS) project is developing technologies with practical applications that strive to eliminate low-visibility conditions as a causal factor to civil aircraft accidents and replicate the operational benefits of clear day flight operations, regardless of the actual outside visibility condition. Enhanced Vision System (EVS) technologies are analogous and complementary in many respects to SVS, with the principle difference being that EVS is an imaging sensor presentation, as opposed to a database-derived image. The use of EVS in civil aircraft is projected to increase rapidly as the Federal Aviation Administration recently changed the aircraft operating rules under Part 91, revising the flight visibility requirements for conducting operations to civil airports. Operators conducting straight-in instrument approach procedures may now operate below the published approach minimums when using an approved EVS that shows the required visual references on the pilot s Head-Up Display. An experiment was conducted to evaluate the complementary use of SVS and EVS technologies, specifically focusing on new techniques for integration and/or fusion of synthetic and enhanced vision technologies and crew resource management while operating under the newly adopted FAA rules which provide operating credit for EVS. Overall, the experimental data showed that significant improvements in SA without concomitant increases in workload and display clutter could be provided by the integration and/or fusion of synthetic and enhanced vision technologies for the pilot-flying and the pilot-not-flying