Assess program: Interactive data management systems for airborne research

Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition

ERP System Audit a Control Support For Knowledge Management

The ERP system supports most of the business system that maintains in a single database the data needed for a variety of business functions such as Manufacturing, SCM, Financials, Projects, Human Resources and CRM; the audit of this systems is necessary in order to give reasonable assurance to the company on its core system. Obtained evidence evaluation can ensure whether the organization's IT&C system safeguard assets, maintains data integrity, and is operating effectively and efficiently to achieve the organization's goals or objectives. The audit process respecting the methodology based on: gathering information and plan; obtaining an understanding of internal controls; performing test of controls and substantive tests, develop a control support on quality of flow of information and knowledge from formal perspective, for Knowledge Management in large enterprises.ERP systems, IT audit, information quality, knowledge management

An Extended Data Management Facility for a General Purpose Time-Sharing System

Contemporary software forces users to choose between general purpose operating systems with primitive data management facilities, and special-purpose data management systems with little support of programing languages and interactive computation. This is because integrated systems combining these two features have not been available. This report presents the design of an integrated system known as the Extended Data Management Facility (EDMF) which combines the facilities of the RCA Time Sharing Operating System (TSOS) with novel data-handling and access-control capabilities. The novelties of the EDMF include a generalized file structure, a generalized record organization, an efficient record retrieval algorithm, and access control to files, records within files, and fields within records. A comprehensive set of on-line commands and system macroinstructions are provided for defining and processing files, records, and fields, and for access control. Special programming aids are also provided for defining blocks of commands, called procedures, for later execution

A study of System Interface Sets (SIS) for the host, target and integration environments of the Space Station Program (SSP)

System interface sets (SIS) for large, complex, non-stop, distributed systems are examined. The SIS of the Space Station Program (SSP) was selected as the focus of this study because an appropriate virtual interface specification of the SIS is believed to have the most potential to free the project from four life cycle tyrannies which are rooted in a dependance on either a proprietary or particular instance of: operating systems, data management systems, communications systems, and instruction set architectures. The static perspective of the common Ada programming support environment interface set (CAIS) and the portable common execution environment (PCEE) activities are discussed. Also, the dynamic perspective of the PCEE is addressed

Trends in metering potable water

Abstract Sustainable management of drinking water distribution systems requires information on the operating status of system components to identify the best operational management measures. The ability to acquire information on tank levels, pipeline flow and real-time pressure offers an efficient and cost-effective management perspective, and enables wider monitoring, which can improve (physical) security as well. The technology of measuring instruments for hydrodynamic variables, used to monitor potable water systems, differs in their independence from electronic data acquisition components and ability to connect to remote data communication systems. Advanced water measurement infrastructure is characterized by the ability to capture data with measurable errors from anywhere in the system, without restrictions on communication type. This paper deals with the measurement of hydrodynamic parameters and a proposal for water meter classification. It includes analysis of the main water meter and data tele-acquisition infrastructure. Several selection criteria are evaluated with respect to their ability to support mathematical hydraulic models and expert systems for water distribution system management

New Data Protection Abstractions for Emerging Mobile and Big Data Workloads

Two recent shifts in computing are challenging the effectiveness of traditional approaches to data protection. Emerging machine learning workloads have complex access patterns and unique leakage characteristics that are not well supported by existing protection approaches. Second, mobile operating systems do not provide sufficient support for fine grained data protection tools forcing users to rely on individual applications to correctly manage and protect data. My thesis is that these emerging workloads have unique characteristics that we can leverage to build new, more effective data protection abstractions. This dissertation presents two new data protection systems for machine learning work-loads and a new system for fine grained data management and protection on mobile devices. First is Sage, a differentially private machine learning platform addressing the two primary challenges of differential privacy: running out of budget and the privacy utility tradeoff. The second system, Pyramid, is the first selective data system. Pyramid leverages count featurization to reduce the amount of data exposed while training classification models by two orders of magnitude. The final system, Pebbles, provides users with logical data objects as a new fine grained data management and protection primitive allowing data management at a higher level of abstraction. Pebbles, leverages high level storage abstractions in mobile operating systems to discover user recognizable application level data objects in unmodified mobile applications

Support Vector Machine in Prediction of Building Energy Demand Using Pseudo Dynamic Approach

Building's energy consumption prediction is a major concern in the recent years and many efforts have been achieved in order to improve the energy management of buildings. In particular, the prediction of energy consumption in building is essential for the energy operator to build an optimal operating strategy, which could be integrated to building's energy management system (BEMS). This paper proposes a prediction model for building energy consumption using support vector machine (SVM). Data-driven model, for instance, SVM is very sensitive to the selection of training data. Thus the relevant days data selection method based on Dynamic Time Warping is used to train SVM model. In addition, to encompass thermal inertia of building, pseudo dynamic model is applied since it takes into account information of transition of energy consumption effects and occupancy profile. Relevant days data selection and whole training data model is applied to the case studies of Ecole des Mines de Nantes, France Office building. The results showed that support vector machine based on relevant data selection method is able to predict the energy consumption of building with a high accuracy in compare to whole data training. In addition, relevant data selection method is computationally cheaper (around 8 minute training time) in contrast to whole data training (around 31 hour for weekend and 116 hour for working days) and reveals realistic control implementation for online system as well.Comment: Proceedings of ECOS 2015-The 28th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems , Jun 2015, Pau, Franc

Polio Eradication Initiative contribution in strengthening immunization and integrated disease surveillance data management in WHO African region, 2014

AbstractIntroductionThe PEI Programme in the WHO African region invested in recruitment of qualified staff in data management, developing data management system and standards operating systems since the revamp of the Polio Eradication Initiative in 1997 to cater for data management support needs in the Region. This support went beyond polio and was expanded to routine immunization and integrated surveillance of priority diseases. But the impact of the polio data management support to other programmes such as routine immunization and disease surveillance has not yet been fully documented. This is what this article seeks to demonstrate.MethodsWe reviewed how Polio data management area of work evolved progressively along with the expansion of the data management team capacity and the evolution of the data management systems from initiation of the AFP case-based to routine immunization, other case based disease surveillance and Supplementary immunization activities.ResultsIDSR has improved the data availability with support from IST Polio funded data managers who were collecting them from countries. The data management system developed by the polio team was used by countries to record information related to not only polio SIAs but also for other interventions. From the time when routine immunization data started to be part of polio data management team responsibility, the number of reports received went from around 4000 the first year (2005) to >30,000 the second year and to >47,000 in 2014.ConclusionPolio data management has helped to improve the overall VPD, IDSR and routine data management as well as emergency response in the Region. As we approach the polio end game, the African Region would benefit in using the already set infrastructure for other public health initiative in the Region

Modeling the growth dynamics of four candidate crops for Controlled Ecological Life Support Systems (CELSS)

The production of food for human life support for advanced space missions will require the management of many different crops. The research to design these food production capabilities along with the waste management to recycle human metabolic wastes and inedible plant components are parts of Controlled Ecological Life Support Systems (CELSS). Since complete operating CELSS were not yet built, a useful adjunct to the research developing the various pieces of a CELSS are system simulation models that can examine what is currently known about the possible assembly of subsystems into a full CELSS. The growth dynamics of four crops (wheat, soybeans, potatoes, and lettuce) are examined for their general similarities and differences within the context of their important effects upon the dynamics of the gases, liquids, and solids in the CELSS. Data for the four crops currently under active research in the CELSS program using high-production hydroponics are presented. Two differential equations are developed and applied to the general characteristics of each crop growth pattern. Model parameters are determined by closely approximating each crop's data