Web GIS to Identify the Problematic Mobile Signal Clusters

Mobile communications has become one of the fastest growing sectors in the world today. With the technological advancement, mobile communication has subjected to many upgrades such as 2G, 3G, 4G. The question of “Does a customer get the expected capabilities from it? ” is not answered yet. Even though, the subscribers of all operators pay almost equal charges per minute, most of the time, they do not get the real benefit from the service. At the moment there is no any location based system to capture the availability of signal receiving levels (specially 3G and 4G signal for Dongles), when a customer sit in front of the marketing person, asking to provide a new connection. What most of the customers do is to use the equipment for few days and return them with a complaint of malfunction in case of signal unavailability. In this study geostatistical analysis was carried out by the method of Inverse distance weighting and the interpolated maps were generated using ArcMap 10. Maps were uploaded to the map server, with standard color ramp. Thereby, the network users can get a better idea about the variation of mobile signal receiving level in a particular location. The developed web based GIS (Geographic Information Systems) system provides the capability of accessing the mobile signal levels remotely in an online manner prior to dealing with a particular customer. Analysis of receiving signal level variation helps to find clusters which have low signal levels than expected. Also, further investigation can be carried out to determine the frequently changing network clusters against a relevant time domain

Selection of surrogates to assess social resilience in disaster management using multi-criteria decision analysis

Purpose: The purpose of this paper is to present a framework for evaluation and ranking of potential surrogates to select the optimum surrogates and test it for five selected social resilience indicators in a disaster context. Innovative resilience assessment approaches are required to capture key facets of resilience indicators to deepen the understanding of social resilience. Surrogates can adequately represent the target indicator that is difficult to measure, as surrogates are defined as key facets of a target indicator. Design/methodology/approach: To optimize the selection of surrogates, five key evaluation criteria were used. Disaster management experts completed an online survey questionnaire and evaluated three potential surrogate options. Surrogates were then ranked using PROMETHEE, a multi-experts multi-criteria group decision analysis technique. Findings: A framework was devised to evaluate and rank potential surrogates to assess social resilience in a disaster context. The findings revealed that the first ranked surrogate can be the most critical facet of a resilience indicator of measure. In most instances, highly experienced cohort of practitioners and policy makers have aligned their preferences of surrogates with the overall ranking of surrogates obtained in this study. Research limitations/implications: The surrogate approach can also be tested in different disaster and geographic contexts. The resilience indicators used in this study to explore surrogates are largely applicable in all contexts. However, the preference of surrogates may also vary in different contexts. Practical implications: Once the surrogate is selected through an evaluation process proposed in this paper, the resilience status can be updated regularly with the help of the selected surrogate. The first ranked surrogate for each of the social resilience indicator can be applied, since the findings revealed that the first ranked surrogate can be the most critical facet in the context of the social resilience indicator being measured. Social implications: The framework and the selection of optimal surrogates will assist to overcome the conceptual and methodical challenges of social resilience assessment. The applicability of selected surrogates by practitioners and policymakers in disaster management will play a vital role in resilience investment decision-making at the community level. Originality/value: The surrogate approach has been used in the fields of ecology and clinical medicine to overcome the challenges in measuring difficult to measure indicators. The use of surrogates in this study to measure social resilience indicators in a disaster context is innovative, which was not yet explored in resilience measurement in disaster management. Graphical abstract: (Figure presented.).</p

Fuzzy based binary feature profiling for modus operandi analysis

It is a well-known fact that some criminals follow perpetual methods of operations known as modi operandi. Modus operandi is a commonly used term to describe the habits in committing crimes. These modi operandi are used in relating criminals to crimes for which the suspects have not yet been recognized. This paper presents the design, implementation and evaluation of a new method to find connections between crimes and criminals using modi operandi. The method involves generating a feature matrix for a particular criminal based on the flow of events of his/her previous convictions. Then, based on the feature matrix, two representative modi operandi are generated: complete modus operandi and dynamic modus operandi. These two representative modi operandi are compared with the flow of events of the crime at hand, in order to generate two other outputs: completeness probability (CP) and deviation probability (DP). CP and DP are used as inputs to a fuzzy inference system to generate a score which is used in providing a measurement for the similarity between the suspect and the crime at hand. The method was evaluated using actual crime data and ten other open data sets. In addition, comparison with nine other classification algorithms showed that the proposed method performs competitively with other related methods proving that the performance of the new method is at an acceptable level