LANDSAT data for state planning

The results of an effort to generate and apply automated classification of LANDSAT digital data to state of Georgia problems are presented. This phase centers on an analysis of the usefulness of LANDSAT digital data to provide land-use data for transportation planning. Hall County, Georgia was chosen as a test site because it is part of a seventeen county area for which the Georgia Department of Transportation is currently designing a Transportation Planning Land-Use Simulation Model. The land-cover information derived from this study was compared to several other existing sources of land-use data for Hall County and input into this simulation. The results indicate that there is difficulty comparing LANDSAT derived land-cover information with previous land-use information since the LANDSAT data are acquired on an acre by acre grid basis while all previous land-use surveys for Hall County used land-use data on a parcel basis

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

An Update on Analyzing Differences Between Public and Private Sector Information Resource Management: Strategic Information Challenges and Critical Technologies

Change is a constant within our contemporary IRM environment. The rapid development of information and communication technologies has been the most predominant among the many agents of change that are forcing a reevaluation of the role of the IRM professional. Few studies to date have compared public and private sector CIO perceptions concerning the IRM challenges and critical technologies faced by their organization. An earlier study concluded that the sectors CIOs do perceive to be faced with many of the same challenges and also view many of the same technologies as critical to the organization\u27s operations. A limiting factor identified in that study was the temporal separation of sector sampling. Any conclusions comparing the public and private sectors were based on survey responses separated by almost one year. The goal of this research is to validate if public and private sector senior IRM managers perceive to still be faced with the same challenges and view the same technologies as being critical to an organization\u27s IRM requirements. The results of a 2002 annual survey of public sector CIOs and senior IRM managers are compared with data collected from 2002 private sector CIOs. This research concluded that performing an analysis on datasets obtained from both sectors during the same time period provided a more appropriate comparison between sectors. Findings from this study provide sufficient evidence that both sectors have developed a closer correlation than was previously concluded

Corporate Codes of Conduct: Is Common Environmental Content Feasible?

In a developing country context, a policy to promote adoption of common environmental content for corporate codes of conduct (COCs) aspires to meaningful results on two fronts. First, adherence to COC provisions should offer economic benefits that exceed the costs of compliance; i.e., companies must receive a price premium, market expansion, efficiency gains, subsidized technical assistance, or some combination of these benefits in return for meeting the requirements. Second, compliance should produce significant improvements in environmental outcomes; i.e., the code must impose real requirements, and monitoring and enforcement must offer sufficient incentives to prevent evasion. With those goals in mind, we explore options for establishing common environmental content in voluntary COCs. Because the benefits of a COC rest on its ability to signal information, we ground our analysis in a review of experiences with a broad range of voluntary (and involuntary) information-based programs: not only existing corporate COCs, but also the International Organization for Standardization (ISO) family of standards, ecolabels, and information disclosure programs. We find some important tradeoffs between harmonization, applicability, feasibility, and efficacy.corporate social responsibility, codes of conduct, environmental management

Productive Development Policies and Supporting Institutions in Latin America and The Caribbean

This paper examines the evolution of productive development policies in Latin America in the last half century, with an emphasis on the post-reform period. The paper begins with a review of the import-substitution era and goes on to describe and make a preliminary assessment of the meaning and implications of productive development policies in the liberalization period.

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists