Spatial Network k-Nearest Neighbor: A Survey and Future Directives

Nearest neighbor algorithms play many roles in our daily lives. From facial recognition to networking applications, many of these are constantly improved for faster processing time and reliable memory management. There are many types of nearest neighbor algorithms. One of them is called k-nearest neighbor (k-NN), a technique that helps to find number of k closest objects from a user location within a specified range of area. k-NN road network algorithm studies have been through various query performance discussions. Each algorithm is usually judged based on query time over few selected parameters which are; number of k, network density and network size. Many studies have claimed different opinions over their techniques and with many results to prove better query performance than others. However, among these techniques, which k-NN road network algorithm has the highest rate of query performance based on the selected parameters? In this paper, reviews on several k nearest neighbor algorithms were made through series of journal extractions and experimentation in order to identify the algorithm that achieves highest query performance. It was found that with the experimentation method, we can identify not only the algorithm’s performance, but also its design flaws and possible future improvement. All methods were tested with some parameters such as varying number of k, road network density and network size. With the results collected, Incremental Expansion Restriction – Pruned Highway Labeling method (IER-PHL) proves to have the best query performance than other methods for most cases

Preventing Incomplete/Hidden Requirements: Reflections on Survey Data from Austria and Brazil

Many software projects fail due to problems in requirements engineering (RE). The goal of this paper is analyzing a specific and relevant RE problem in detail: incomplete/hidden requirements. We replicated a global family of RE surveys with representatives of software organizations in Austria and Brazil. We used the data to (a) characterize the criticality of the selected RE problem, and to (b) analyze the reported main causes and mitigation actions. Based on the analysis, we discuss how to prevent the problem. The survey includes 14 different organizations in Austria and 74 in Brazil, including small, medium and large sized companies, conducting both, plan-driven and agile development processes. Respondents from both countries cited the incomplete/hidden requirements problem as one of the most critical RE problems. We identified and graphically represented the main causes and documented solution options to address these causes. Further, we compiled a list of reported mitigation actions. From a practical point of view, this paper provides further insights into common causes of incomplete/hidden requirements and on how to prevent this problem.Comment: in Proceedings of the Software Quality Days, 201

Requirements engineering process improvement and related models

Requirements Engineering (RE) is a key discipline in software development, and several standards and models are available to help assess and improve RE processes. However, different standards and models can also help achieve different improvement goals. Thus, organizations are challenged to select these standards and models to best suit their specific context and available resources. This chapter presents a review of selected RE-specific and generic process improvement models that are available in the public domain. The review aims to provide preliminary information that might be needed by organizations in selecting these models. The chapter begins with analyses of how RE maturity is addressed in the Capability Maturity Model Integration (CMMI) for Development. Then, it describes the principal characteristics of, and the assessment and improvement framework applied in four RE-specific process assessment and improvement models: the Requirements Engineering Good Practice Guide (REGPG), the Requirements Engineering Process Maturity(REPM), the Requirements Capability Maturity Model (R-CMM), and the Market-Driven Requirements Engineering Process Model (MDREPM). This chapter also examines the utility and lesson learned of these models

Flood insurance rate map for non-structural mitigation

December 2014 flooding in Kelantan river basin caused severe damage to economic and social infrastructure and dealt a serious blow to Kelantan state economies. Mitigation of flood disaster can be successful only when detailed knowledge is obtained about the vulnerability of the people, buildings, infrastructure and economic activities in a flood risk area. Therefore, to identify a community's flood risk, pre-disaster financial instrument will be introduced as non-structural mitigation measures know as flood insurance rate map. This instrument will be developed based on geospatial technology using satellite images, topographic surveys, cadastral map, type of community building such as residential or commercial and households’ income. Flood hazard maps and flood insurance rate map will provide the flood risk zone and flood insurance rate and premium coverage for the affected community. In additions it helps to determine the type of flood insurance coverage is needed since standard homeowners’ insurance doesn't cover flooding. Flood insurance rate map will provide affordable insurance for property owners, based on the lower the degree of risk state in flood hazard map, the lower the flood insurance premium. These insurance rate map are valuable to communities because it creates safer environments by reducing loss of life and decreasing property damage, allows individuals to minimize post-flood disaster disruptions and to recover quicker

Is Crowdfunding Suitable for Financing German Public Research Organization (PRO) Projects?

So far, public research organizations (PROs) and universities in Germany are not benefiting from the manifold opportunities of crowdsourcing platforms and crowdfunding in particular. Crowdfunding may not only provide complementary financial resources for scientific projects, but it can also enhance the spectrum of science communication and facilitate the knowledge and technology transfer process. Consequently, scientists can use crowdfunding activities to stimulate the transfer of their knowledge to business and/or society to stimulate innovation. Nevertheless, it is a challenging task to apply the full spectrum of crowdsourcing instruments in PROs and universities. The crowdfunding literature rarely covers the untapped potential and challenges associated with crowdfunding for scientific institutions. In this conceptual paper, we provide approaches how PROs and universities can successfully acquire alternative financing, in particular from crowdfunding, and use it strategically. The aim is to provide solutions to pitfalls that may prevent researchers from exploiting crowdfunding in their “funding journey.” We introduce a model called “scientific cooperative crowdfunding” as a field for further research to explore how PROs and universities can use crowdfunding in a more comprehensive way during different stages of the knowledge and technology transfer process