The human-elephant conflict: mapping the elephant area and the level of conflict vulnerability in the Mila Landscape, Pidie District, Aceh, Indonesia

Elephants are designated as endangered animals because their population in the wild continues to decline. One of the causes of its extinction is the threat of conflict between elephants and humans. The conflict between Sumatran elephants and humans in Aceh continues to increase every year, but there is no resolution to this conflict. This study was aimed to analyse the level of risk of elephant-human conflict in the Mila area and map the conflict areas. The method used was the observation method with the purposive sampling technique. The data was analysed using the disaster risk formula. The results of the analysis of the risk level of elephant-human conflict in Mila District showed that the high-risk level was in Tuha Lala Village (35.24%), Babah Jurong Village (35.22%) and Kumbang Village (35.04%). The level of risk was moderate in Krueng Lala Village (27.64%), Andeue Mosque Village (30.38%) and Dayah Andeue Village (33.38%). Meanwhile, areas with a low-risk level were Kulu Village (21.65%) and Dayah Sinthop Village (20.32%). The mapping of conflict risk areas was coloured red for high risk, yellow for medium risk and green for low risk. The conclusion in this study is that Tula Lala Village, Babah Jurong Village and Kumbang Village are areas with high conflict marked in red. Krueng Lala Village, Andeu Mosque Village and Andeue Dayah Village are areas with moderate conflict which are marked in yellow. Meanwhile, Kulu Village and Dayah Sinthop Village are areas with low conflict marked in green.

Simulation-Based Evaluation of Variation in Left-Turn Paths in the Coordinated Intersection Management

Coordinated intersection management (CIM) has gained more attention with the advance of connected and autonomous vehicle technology. The optimization of passing schedules and conflict separation between conflicting vehicles are usually conducted based on the predefined travelling paths through the intersection area in the CIM. In real-world implementation, however, the diversity of turn paths exists due to multiple factors such as various vehicle sizes and automation control algorithms. The aim of this paper is to investigate how the variation in left-turn paths affects the feasibility and viability of optimal passing schedules, as well as the safety and efficiency of intersection operation. To do this, we start with identifying six typical left-turn paths to represent the variation. A scenario-based simulation is first conducted by using each of the paths as the nominal path. The optimal schedules and the corresponding alternative schedules are generated to calculate indicators for nominal performance, average performance, and robustness. The best path is selected in terms of schedule optimality and robustness. With schedules obtained by solving CIM models using the selected path, the left-turning CAVs are assumed to travel along one of the six paths randomly to simulate the path divergence. A surrogate safety measure, PET, is utilized to assess the safety of the intersection under CIM. The theoretical PET with the nominal path and the actual PET with the random path are calculated for each conflict event. Comparisons of two PET sets show the increase in conflict risk and vehicle delay. The conclusion can be drawn that the variation in left-turn paths causes the decline in safety level and travelling efficiency and should be considered in the CIM model to ensure safe and efficient implementation in the intersection.

Projecting armed conflict risk in Africa towards 2050 along the SSP-RCP scenarios: a machine learning approach

In the past decade, several efforts have been made to project armed conflict risk into the future. This study broadens current approaches by presenting a first-of-its-kind application of machine learning (ML) methods to project sub-national armed conflict risk over the African continent along three Shared Socioeconomic Pathway (SSP) scenarios and three Representative Concentration Pathways (RCPs) towards 2050. Results of the open-source ML framework CoPro are consistent with the underlying socioeconomic storylines of the SSPs, and the resulting out-of-sample armed conflict projections obtained with Random Forest classifiers agree with the patterns observed in comparable studies. In SSP1-RCP2.6, conflict risk is low in most regions although the Horn of Africa and parts of East Africa continue to be conflict-prone. Conflict risk increases in the more adverse SSP3-RCP6.0 scenario, especially in Central Africa and large parts of Western Africa. We specifically assessed the role of hydro-climatic indicators as drivers of armed conflict. Overall, their importance is limited compared to main conflict predictors but results suggest that changing climatic conditions may both increase and decrease conflict risk, depending on the location: in Northern Africa and large parts of Eastern Africa climate change increases projected conflict risk whereas for areas in the West and northern part of the Sahel shifting climatic conditions may reduce conflict risk. With our study being at the forefront of machine learning (ML) applications for conflict risk projections, we identify various challenges for this arising scientific field. A major concern is the limited selection of relevant quantified indicators for the SSPs at present. Nevertheless, ML models such as the one presented here are a viable and scalable way forward in the field of armed conflict risk projections, and can help to inform the policy-making process with respect to climate security.

Arming for conflict, arming for peace? How small arms imports affect intrastate conflict risk

Although a prevalent technology of conflict, the impact of small arms imports on the risk of intrastate conflict outbreak has not been examined so far. This article argues that small arms not only enhance general military capabilities, but also contribute to state capacities necessary for conflict prevention. These two mechanisms are incorporated in a formal model of power shifts. The derived hypotheses are tested on 146 countries for the period 1993–2014. Using split-population and penalized fixed-effects logit models as innovative estimation methods for rare-events data, small arms imports are found to have no or even a risk-reducing impact.

A Conflict Risk Analysis of MAV\UAV Flight in Shared Airspace

The intelligent auxiliary decision-making (IADM) is emerging as a feasible solution for air traffic control (ATC) to reduce undesirable conflicts in shared airspace; meanwhile, unmanned aerial vehicles (UAVs) can be operated with enhanced efficiency and safety using IADM. This paper presents the conflict risk framework of the MAV\UAV flight that improves flight safety of MAVs and UAVs in shared airspace. This is accomplished by focusing on two steps: First, determine the minimum safety communication interval between the UAV and controller; second, build a conflict risk model to detect which decision mechanism will minimize risk. Our approach provides a standard model to start with to improve IADM and allow engineers to focus on the operational purpose of MAV/UAV. Results show that our work presented here is practical and straightforward, and it brings an evident engineering application prospect.

Real-Time Evaluation Method of Vehicle Conflict Risk on Urban Expressway Based on Smartphone GPS Data

To effectively evaluate the traffic safety risk of urban expressways in real time and ensure their traffic safety and smoothness, a real-time evaluation method of vehicle conflict risk of an urban expressway based on smartphone GPS data was proposed. We screened and processed smartphone GPS data to obtain vehicle behavior data, including acceleration and angular acceleration, and road state data, including average vehicle speed. Urban expressways were divided into four categories, closed straight section, closed curve section, vehicle entry section, and vehicle exit section; the evaluation indexes of abnormal vehicle behavior were established. Based on the improved entropy weight method, the vehicle conflict risk entropy was established to distribute the weight of different types of abnormal behaviors of vehicles. The evaluation system of vehicle conflict risk entropy was applied to the vehicle behavior data. Urban Expressways with more abnormal vehicle behavior were obtained to evaluate the risk of vehicle conflict in real time. The results showed that the easily obtained smartphone GPS data may be effectively used to analyze the abnormal behavior of vehicles, identify vehicle conflict risk points hidden in urban expressways in real time to provide effective methods for batch and dynamic real-time evaluations of vehicle conflict risks on urban expressways, and improve the traffic safety service level of urban expressways.

A conceptual framework for effective management of conflict risk within Agile software development environments

Background: Whenever teams obtain together to work towards a common goal, the lingering of an inherent conflict risk is always a possibility. This applies to software development teams as well. Researchers even argue this inherent conflict existence as necessary. Agile development environment is no exception. The main purpose for adopting Agile is to improve the technology adequacy to facilitate organisation competitiveness. Agile manages the achievement of this through its advocacy for change, adaptability and constant satisfaction of market demands. This is because Agile enables organisations to create software of quality standard that allows for quicker response to the continuously changing market needs of todays’ world.Objectives: Henceforth, this article investigates this topic to develop a conceptual framework for effectively managing conflict risk in Agile teams, to improve the organisation technology adequacy.Method: This article employed quantitative methods for data collection and analysis. A structured online questionnaire was used for data collection and Statistical Package for the Social Sciences was used for data analysis. Pearson’s correlation was used to test the relationships among variables.Results: The findings show affirming results on the existence of conflict risk among Agile software development teams. The results indicate that there is a strong positive significant correlation between effective interaction, discussions and quality software application. Moreover, the findings demonstrate a strong relation between effective conflict management and achievement of set agile project goals.Conclusion: Agile allows companies to address the market requirements while still being adaptive to constant change. However, the literature identifies conflict risk as one of the hindrances to realising this purpose.