Geospatial Technologies Applied to International Boundaries – the Case Study of Guinea Bissau

Modern geospatial technologies applied to frontiers involve remote sensing data, namely satellite imagery, orthophoto or orthoimages, global navigation technology (GPS/GNSS), as well as Geographical Information System (GIS) tools, which have been used during the last decade for boundary delimitation, demarcation or revision. This paper intends to present the case study of Guinea Bissau boundary which was the first African Portuguese colonies to settle its boundaries. It was delimitated by a Franco– Portuguese convention signed in Paris on May 12, 1886, and ratified later in Lisbon, on August 31, 1887. The demarcation was completed between 1900 and 1905 and recorded in memoranda prepared by the commissioners. For historical reasons Tropical Research Institute (IICT) concentrates a unique, vast and diverse amount of information concerning the borders of those countries. The scope of this research is to explore new methodologies and approaches to study frontiers, making use of geospatial technologies. A Boundary Geographical Information System (BGIS) is being developed based on GIS technology which is a powerful tool to integrate various datasets, visualize, analyze and model spatial and territorial specificities. Historicaldiplomatic information will be articulated with the geospatial data, in order to be included into the geodatabase and to recover the location of the borderlines. The original analogue data was converted into digital format, and image processing techniques were applied to remove residual artifacts, improving the appearance of the documents and reducing storage volume. These methodologies prepared the images for the application of optical character recognition (OCR) before integrating them into the geodatabase. The main objective is to make this information useful and accessible, in a digital platform, to support local authorities, thus promoting cooperation and facilitating public access. The BGIS will be used for present and future management of Guinea Bissau boundaries and as an instrument for policy making

Developing an Efficient DMCIS with Next-Generation Wireless Networks

The impact of extreme events across the globe is extraordinary which continues to handicap the advancement of the struggling developing societies and threatens most of the industrialized countries in the globe. Various fields of Information and Communication Technology have widely been used for efficient disaster management; but only to a limited extent though, there is a tremendous potential for increasing efficiency and effectiveness in coping with disasters with the utilization of emerging wireless network technologies. Early warning, response to the particular situation and proper recovery are among the main focuses of an efficient disaster management system today. Considering these aspects, in this paper we propose a framework for developing an efficient Disaster Management Communications and Information System (DMCIS) which is basically benefited by the exploitation of the emerging wireless network technologies combined with other networking and data processing technologies.Comment: 6 page

A Secure Lightweight Approach of Node Membership Verification in Dense HDSN

In this paper, we consider a particular type of deployment scenario of a distributed sensor network (DSN), where sensors of different types and categories are densely deployed in the same target area. In this network, the sensors are associated with different groups, based on their functional types and after deployment they collaborate with one another in the same group for doing any assigned task for that particular group. We term this sort of DSN as a heterogeneous distributed sensor network (HDSN). Considering this scenario, we propose a secure membership verification mechanism using one-way accumulator (OWA) which ensures that, before collaborating for a particular task, any pair of nodes in the same deployment group can verify each other-s legitimacy of membership. Our scheme also supports addition and deletion of members (nodes) in a particular group in the HDSN. Our analysis shows that, the proposed scheme could work well in conjunction with other security mechanisms for sensor networks and is very effective to resist any adversary-s attempt to be included in a legitimate group in the network.Comment: 6 page

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges--management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu

Data protection: the challenges facing social networking

The popularity of social networking sites has increased dramatically over the past decade. A recent report indicated that thirty-eight percent of online users have a social networking profile. Many of these social networking site users (SNS users) post or provide personal information over the internet every day. According to the latest OfCom study, the average adult SNS user has profiles on 1.6 sites and most check their profiles at least once every other day. However, the recent rise in social networking activity has opened the door to the misuse and abuse of personal information through identity theft, cyber stalking, and undesirable screenings by prospective employers. Behavioral advertising programs have also misused personal information available on social networking sites. Society is now facing an important question: what level of privacy should be expected and required within the social networking environment

A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes

Identification and Mapping of Readiness of Micro and Small Coffee Industry Cluster Development

Cluster development of micro and small-scaled coffee industry is an effortto improve the economy of community by utilizing local resources. This studywas aimed to identify phase of cluster growth through determinant factors ofindustrial cluster growth; to assess a linkage between economy players in theindustrial cluster; and to identify strength, weakness, opportunity, and threat incoffee industry development. This research was carried out in Sumberwringin,Bondowoso District, East Java. Survey method through direct observation andinterviews were conducted in this study. Data collected included primary andsecondary data. Number of respondents were 25 industry players selected byjudgement sampling method. The data were analyzed by exploratory descriptivewith content analysis method. This research concluded that industrial clusterstudied was still in phase of formation and initiative (embryo) and its growthpattern followed Pattern III. Interrelationship between core industries has notbeen established, while linkage between core industries and supporting industrieshad already well-established. Strength and opportunity in coffee industrydevelopment included raw materials availability, market segment growth. Smalland micro enterprises credit facility, supporting facility, and labor availability.Constraints and threat faced by coffee industry included limited market access,in adequate machineries, limited working capital, raw materials quality, inconsistentproduct quality, credit claim, and competitors