Conflict Scenarios Research Articles

Missing Persons of Post-Conflict Countries: Assessing Dental Identification through a Questionnaire-based Study in Syria

Locating and identifying missing persons is crucial to protecting human rights and rebuilding war-torn countries like Syria. Biological identity primarily relies on DNA, fingerprints, or dentition. However, post-conflict countries with high deaths, limited databases, insufficient resources, and a reduced or a lack of forensic expertise make this effort more challenging. Teeth are a practical and cost-effective means to identify human remains, particularly when acceptable dental records are available. Still, the application of comparative dental analysis in conflict scenarios needs to be more explored.A survey study in Syria examined whether post-conflict countries could employ comparative dental identification of missing individuals. The attitudes and perceptions of four groups (the public and dentists, forensic odontologists, dental schools, and the Syrian Dental Association) were determined using questionnaires and analysed for the first two groups. Most respondents (>90%) indicated that addressing disappearance is crucial for post-conflict reconstruction and considered it unachievable without international support and only 20% had confidence in this support. Issues hindering human identification reported by a high percentage of dentists and forensic odontologists and included education in Forensic Odontology (92%), expertise in the field (70%), awareness (90%), the availability of antemortem records (92.3%) and political and security influence (50%). Responses from over 80% of the public, 50% of the dentists and 92% of the forensic odontologists indicated that comparative dental identification in Syria may not be feasible.The results of this study provide strong evidence of the challenges in identifying missing persons using teeth in developing nations, particularly those affected by conflicts. They include the lack of antemortem records and forensic expertise. The international community is urged to support post-conflict nations including Syria.

Overtaking risk assessment based on extreme value theory and intelligent network information

In order to evaluate the overtaking risk level of intelligent connected vehicles when providing different connected information, and to make up for the neglect of driver factors in traditional risk assessment and the inadequate evaluation of complex traffic scenarios by a single traffic conflict indicator, this paper introduces the Block maxima (BM) and Peak over threshold (POT) methods to fit the extreme value distribution for two conflict scenarios involved in overtaking events (following vehicle conflict and frontal vehicle conflict), so as to evaluate the risk of following vehicle accidents and frontal collision accidents during overtaking. In each conflict scenario, a non-stationary extreme value model considering driver factors and a binary extreme value model considering different traffic conflict indicators are constructed, and the model is verified by the overtaking test data of intelligent connected vehicles in a two-way two-lane vehicle. Overtaking events were extracted from the original test data and conflict indicators were calculated: including the collision time GAP with the front vehicle at the beginning of the overtaking event, the collision time TTC_t1 with the oncoming vehicle, the deceleration DRAC, and the collision time TTC with the oncoming vehicle and the headway time THW with the front vehicle at the end of the overtaking event. The probability of the event with a negative time conflict indicator or DRAC greater than MADR was used to characterize the degree of collision risk. The results show that in the following vehicle conflict scenario, the binary extreme value model constructed with different conflict indicators has different error results, among which the binary extreme value model constructed with THW&DRAC has the most accurate evaluation result (standard error MAE = 0.00028); in the front vehicle conflict scenario, the binary extreme value model constructed with TTC&DRAC has the most accurate evaluation result ( MAE = 0.006 ). In different conflict scenarios, the non- stationary extreme value model considering the driver factor significantly improves the risk assessment accuracy compared with the model without considering the driver factor (small AIC and BIC values). In addition, different intelligent network information (real-time distance, overtaking advice, speed advice) brings different overtaking risks, and when the intelligent network information is speed advice, the vehicle's overtaking risk is the lowest. Therefore, the non- stationary extreme value model and binary extreme value model considering driver factors proposed in this paper can effectively evaluate driving risks through traffic conflict indicators. Secondly, the experimental data of intelligent networked vehicles show that the extreme value theory model proposed in this paper can accurately evaluate the overtaking risk level of intelligent networked vehicles when providing different network information.

Quantile via Moments Panel Data Analysis: Dissecting Political Regimes and the Spectrum of Internal Conflicts

AbstractThis study investigates whether the political regime affects internal conflicts and specific types (e.g., civil war, political violence, and civil disorder). The study reveals that even incremental movements toward democracy are associated with reduced internal conflict, challenging some elements of the inverted U hypothesis. Moreover, factors such as government stability are better indicators of smaller-scale forms of internal conflict than the political regime type. Finally, scenarios of acute internal conflict, cultural tension, and government instability serve as more reliable indicators, implying that these elements eclipse the stabilizing influence of a regime's progression toward a more inclusive government.

Hierarchical MPC-based authority allocation strategy for human–machine shared vehicles considering human–machine conflict

The uncertainty of driver behavior is an important factor affecting the safety of human–machine co-driving vehicles. Traditional rule-based models often fail to capture the nonlinear and complex characteristics of human steering behavior. To overcome this, we propose a data network-driven approach utilizing gated recurrent unit (GRU) neural networks to accurately predict driver steering behavior. The GRU-based driver model is integrated with vehicle dynamics to construct a control-oriented driver–vehicle model. Considering that human–machine conflict may cause vehicle instability, an exponential function combining proportional–integral–derivative is proposed to quantify the human–machine conflict level based on steering difference. To reasonably allocate human–computer permissions based on human–machine interaction, a hierarchical authority allocation framework is proposed. The upper layer provides a reference authority allocation via an exponential function, while the lower layer employs a real-time model predictive control (MPC) optimizer to track this reference, ensuring optimal vehicle path tracking and stability. The proposed system’s effectiveness is validated through driver-in-the-loop testing, demonstrating significant improvements in safety and performance. The results show that in the human–machine conflict scenario, the proposed authority allocation strategy can still ensure the path tracking and safety of the vehicle.

An Intelligent Decision-Making Approach for Multi-Ship Traffic Conflict Mitigation from the Perspective of Maritime Surveillance

Potential multi-ship conflict situations in coastal or near-shore port areas have always been one of the important factors affecting ship navigation safety and a key target of maritime traffic regulatory authorities. In recent years, with the continuous development and integration of various emerging technologies in the maritime field, maritime traffic supervision has also shown a trend of intelligent and autonomous development. The traditional supervision method dominated by human experience is evolving towards data and model-driven practices. In order to solve the problem of ship navigation safety supervision under multi-ship conflict scenarios, it is urgent to build an intelligent conflict mitigation decision-making model. Therefore, this paper designs a novel risk mitigation decision-making model for multi-ship conflict scenarios from the perspective of maritime supervision. The model proposed in this paper first extracts high-density ship clusters based on AIS (Automatic Identification System) data and uses the MCD (Mean Core Density) and PRM (Proportion of Relative Motion) as feature indicators to further mine potential multi-ship conflict scenarios. Finally, a global optimization decision-making model is constructed to effectively mitigate conflict risks. Experimental verification shows that the intelligent decision-making model for the mitigation of maritime traffic conflict proposed in this paper can autonomously identify conflict scenarios and make reasonable decisions in real time. It can effectively ensure the navigation safety of ships in multi-ship conflict scenarios and further improve the supervision level of maritime departments.

Investigation of Aircraft Conflict Resolution Trajectories under Uncertainties.

As air traffic intensity increases and stochastic uncertainties, such as wind direction and speed, continue to impact air traffic controllers' workload significantly, airlines are increasingly pressured to reduce costs by flying via straighter/more direct trajectories. Due to these changes, it is important to search for new means/solutions for aircraft conflict resolution to ensure the required level of safety and rational flight trajectory. Such a solution could be the implementation of Dubin's method of flight trajectories. This paper aims to propose and deeply analyze a new mathematical model for two-aircraft conflict resolution where the Dubins method is applied in a dynamic conflict scenario. In this model, at a certain moment, the flight trajectory of one aircraft follows a path similar to a moving circle's tangential line. Upon that, the conflict detection and resolution (CDR) model considers wind uncertainty. The proposed CDR method could be applied when uncertainty such as wind direction and speed are inconstant (stochastic) throughout the simulation.

The Narrative Construction of Peter in the Gospel of Mark in Light of the Reports of Displacement and Exile Due to the Armed Conflict in Colombia

A scenario of conflict, as in the Colombian case, may be related to the socio-political context in which the Gospel according to Mark may have been written, and therefore offers new insights for the understanding of the narrative phenomena presented. In effect, Mark could have been a response to the traumatic experiences of the followers of Jesus to whom the Gospel was addressed. Likewise, the experience of those displaced and exiled by the Colombian armed conflict has involved a series of traumatic events, but also bears witness to processes of resilient reparation. Against this background, it is proposed that in Mark, the figure of Peter, courageous and determined at the beginning but cowardly and flighty at the end, is analogous to that of many victims in the Colombian armed conflict who, faced with the imminent danger of losing their lives, were forced to abandon their deepest convictions and even their loved ones to end up fleeing into hiding and exile. Nevertheless, both Mark and the experience of those displaced and exiled because of the conflict in Colombia suggest the possibility of vindication of these victims and their respective narratives, helping them to recognize that their flight was not a betrayal and that, thanks to it, the memory of the events can be reconstructed to guarantee the truth and the non-repetition of the facts.

Wait or Pass? Promoting intersection’s cooperation via identifying vehicle’s social behavior

Lack of communication between road users can reduce traffic efficiency and cause safety issues like traffic accidents. Researchers are exploring how intelligent vehicles should communicate with the environment, other vehicles, and road users. This study explores the impact of social information communication on traffic safety and efficiency at intersections through vehicle-to-vehicle (V2V) communication. The research examines how these factors influence drivers’ decision-making and cooperative behavior by incorporating social value orientation (SVO) and driving agent identity into V2V systems and automated vehicle (AV) decision-support systems. An experimental platform simulating intersection conflict scenarios was developed, and three studies involving 334 participants were conducted. The findings reveal that providing drivers with social information about opposing vehicles significantly promotes cooperative behavior and safer driving strategies. Specifically, the waiting rate for people facing proself vehicles (Mean = 0.22) is significantly higher than when facing prosocial vehicles (Mean = 0.79). When SVO is unknown, the waiting rate is around 0.5. Participants behaved more waiting when confronted with an AV than human-driven vehicles. With AV recommendations based on SVO, participants’ final waiting rate increases as the recommended waiting rate increases. The optimal recommended waiting rate for AV is most acceptable when it matches the average waiting rate of the other vehicle. This research underscores the importance of integrating social information into V2V communication to improve road safety, aiding in designing automated decision-making strategies for AV and enhancing user satisfaction.

The web of conflict-related interactions in Colombia: exploring causal linkages between ecological and social variables by the qualitative loop analysis.

In Colombia, the long-lasting internal conflict heavily shaped the socio-ecological context and imposed relationships that persisted after the peace agreement was signed in 2016. One question of interest is whether policies or interventions conceived to attain desirable goals for the post-conflict society may be effective or, rather, if the constraints imposed by the conflict scenario might produce unintended effects, either on the environmental or the social side. To explore this issue, we envisaged the socio-ecological system as a parsimonious set of characteristic ecological and social variables within the conflict-related framework and reconstructed their interactions, exploiting elicitation-based information and the literature. We visualized the resulting interactive networks as signed digraphs. Applying the qualitative technique of loop analysis combined with numerical simulations, we predicted the response of the system to policies as drivers of change, such as subsidized credit to capital-intensive activities or policies that increase small farming competitiveness and access to markets. Highlighting causal linkages reveals that the persistence of conflict factors may produce unexpected interdependencies between licit and illicit activities and that, only in a few cases, the persistence of these mechanisms allows synergies between desirable goals.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Preparándose para la guerra: la Armada Argentina y sus hipótesis de conflicto en Sudamérica durante la década de 1920

As a result of the impacts and effects of the First World War, during the 1920s, the Argentine Navy was undergoing a pronounced process of material obsolescence. To reverse this situation, its authorities developed a series of studies, outlining possible acquisition and modernization programs that would respond, among other issues, to the existing conflict scenarios in the region. This article will analyze Comparative Study on South American Naval Power, a little-explored source found in the library of the National Naval Museum, which includes a set of memoirs and reports prepared by the General Staff of the Navy in 1923. It details the plans and deployments envisioned by the Navy in the event of war with Brazil, Chile, and Uruguay -nations perceived as rivals at the timealong with the various courses of action and the equipment that would need to be acquired to ensure the success of the operations.

The Legality of the Defensive Measures Taken by the USA and the UK in Response to the Houthi Attacks

The article delves into the legality of defensive actions taken by the USA and the UK in response to the Houthi attacks in the Red Sea. Despite assertions that such actions are justified under the right to self-defence, legal ambiguities persist in international law. The authors argue that while attacks on merchant vessels by non-state actors may constitute armed aggression, clarity is lacking on whether they meet the criteria for self-defence. The USA and UK stress that attacks on their warships validate their defensive measures, framing them as necessary responses to significant threats. However, the authors contend that the principle of proportionality may have been disregarded, urging restraint in the use of force to safeguard ships while respecting Yemen’s sovereignty. The article underscores the need for a nuanced approach to assessing the legality and necessity of military actions in complex conflict scenarios.

Game-theoretic agent-based modelling of micro-level conflict: Evidence from the ISIS-Kurdish war.

This article delves into the dynamics of a dyadic political violence case study in Rojava, Northern Syria, focusing on the conflict between Kurdish rebels and ISIS from January 1, 2017, to December 31, 2019. We employ agent-based modelling and a formalisation of the conflict as an Iterated Prisoner's Dilemma game. The study provides a nuanced understanding of conflict dynamics in a highly volatile region, focusing on microdynamics of an intense dyadic strategic interaction between two near-equally- powered actors. The choice of using a model based on the Iterated Prisoner's Dilemma, though a classical approach, offers substantial insights due to its ability to model dyadic, equally-matched strategic interactions in conflict scenarios effectively. The investigation primarily reveals that shifts in territorial control are more critical than geographical or temporal factors in determining the conflict's course. Further, the study observes that the conflict is characterised by periods of predominantly one-sided violence. This pattern underscores that the distribution of attacks, and target choices are a more telling indicator of the conflict nature than specific behavioural patterns of the actors involved. Such a conclusion aligns with the strategic implications of the underlying model, which emphasises the outcome of interactions based on differing aggression levels. This research not only sheds light on the conflict in Rojava but also reaffirms the relevance of this type of game-theoretical approach in contemporary conflict analysis.

China’s ‘Liquid’ Warfighting Shift and Its Implications for Possible Future Conflict

Some suggest that remote, precision strike warfare is a Western phenomenon motivated by aversion to high troop casualties among democratic leaders subject to re-election. Others contend that it is the result of a global transition in the way of modern war towards ‘liquid warfare’, centred around the disruption of adversary networks in the increasingly integrated and high-tech battlespace. This article advances the debate by applying the liquid warfare hypothesis to China’s post-1993 military reforms. It finds (a) that China’s development and embrace of its prevailing ‘systems destruction warfare’ concept constitutes a liquid shift in its warfighting approach, dispelling the contention that such transformations are necessarily linked with democratic political systems; and (b) that the liquidification of China’s warfighting approach has immediate implications for possible regional conflict scenarios, particularly those involving the United States, making them mutually costlier and susceptible to rapid escalation.

A game theoretic conflict analysis model with linguistic assessments and two levels of game play

In a conflict scenario, the domestic and international stake holders vye to safeguard their specific vested interests and objectives, like in the Syrian and Afghan conflicts. Knowledge about the position of domestic players can help both domestic and international players determine the root causes of conflict and work in groups to resolve the divergent issues. Due to complex nature of conflicts, it is pertinent to study conflict at domestic and international levels separately. For this purpose, we design a two-level conflict analysis model based on game theory and linguistic assessments of players. The first level deals with local players by playing a game between each of them in view of local issues and taking into account the local grouping. At the second level, game is played between local groups and international players regarding multiple issues. In this way, all the parties calculate the gains or losses of comparable actions of each other. Thus, the proposed model provides a comprehensive study of conflict. This paper studies Syrian conflict to validate the conflict analysis algorithm and explain the computations and results.

Trauma and resistance in Niger's emergency transit mechanism: A life narrative study

This qualitative exploratory research delves into the intricate life narratives of forcibly displaced individuals residing within the Emergency Transit Mechanism in Niger, employing a methodology grounded in life narrative analysis. The primary objective is to gain a comprehensive understanding of the potential stressors and traumatic experiences encountered by these individuals, encompassing both psychological and physiological dimensions, while also examining the dynamics of resilience and elements contributing to their overall well-being. The findings, derived through thematic content analysis, underscore the cumulative nature of traumatic events experienced by migrants throughout their lifetimes and across various stages of the migration continuum. The study, in alignment with extant scholarly literature, identifies thematic categories such as “A scenario of conflict and mourning, " everyday experience of violence and discrimination,” “health at risk”, and " Seeking security.” Refugees recount enduring multiple traumas, including familial bereavements and losses resulting from conflicts and militarized violence. Furthermore, the analysis elucidates a profound interplay between traumatic occurrences, subjective well-being, and resilience among the studied population. Despite confronting adverse living circumstances, refugees demonstrate indicators of subjective well-being, hinting at the potential for resilience and recovery. This challenges conventional diagnostic frameworks such as Post-Traumatic Stress Disorder (PTSD) and underscores the necessity for a nuanced understanding of trauma's multifaceted impacts. Nevertheless, the study underscores the urgent need for a more robust and contextually attuned mental health support infrastructure, advocating for a deeper exploration of the socio-political determinants underpinning forced migration. By comprehending the root causes of displacement through a socio-political lens, policymakers and practitioners can devise comprehensive strategies and interventions aimed at both prevention and mitigation of factors precipitating forced migration. This approach seeks to foster a global landscape wherein compassionate and well-informed interventions proactively address the underlying drivers of displacement.

Analyzing traffic conflict scenarios and safety assessment in the context of intelligent vehicles: A research review

The several internal disputes and various types of traffic accidents at an urban crossroads make for a complex traffic scenario. Because accident data and crash-based methodologies are limited, researchers are now examining other safety measures, including traffic conflicts that do not depend on crashes. To better assess road safety in the decades to come new real-time data is essential. The automobile industry is heading toward intelligent cars with the goal of enhancing road safety. Although there is a common failure mechanism between accidents and traffic conflicts during driving, which makes it possible to apply crash frequency and severity estimates to traffic conflict frequency and severity models, predicting traffic conflicts presents distinct difficulties. This study discusses conceptual and methodological concerns while reviewing research papers on traffic disputes as safety measures. It offers a thorough synopsis of previous research from the viewpoint of intelligent vehicles. It explains that there are three primary categories into which the perception technology of intelligent cars may be separated: perception technology, communication technology, and the combination of perception and communication technologies. The paper emphasizes the need of harmonizing international safety standards as well as the role that governments and regulatory agencies play in guaranteeing the security of intelligent vehicles. It highlights the need for additional research on transport conflict modeling techniques and offers practical recommendations for future study.

Enterprises’ response strategies towards a mission-oriented innovation initiative – a reflection on China’s indigenous innovation

ABSTRACT Mission-oriented innovation initiatives hold significant value for nations worldwide. Responses of innovative actors account for the final outcomes and achievements of these initiatives, while which are still unexplored. Based on the institutional logics perspective, we develop a framework to elucidate the response strategies of different kinds of enterprises towards the indigenous innovation proposed in the National Middle and Long-Term Program for Science and Technology Development 2006–2020 (MLP), the most influential mission-oriented innovation policy in China during the past 20 years. By combining primary interview materials with secondary data, we initially analyse the logic conflicts that enterprises face, the changes in logic conflict scenarios under this initiative (including the types and degrees of conflicts), and the potential benefits they can get from this initiative. We then delve deeper into investigating their response strategies. Our research provides a new lens for researchers and policymakers.

Conflict Detection and Separation Configuration Method Based on Uncertain Flight Trajectory

Aiming at two aircraft conflict scenario in the pre-tactical stage, by converting the uncertain flight trajectory of the target aircraft into a spatio-temporal trajectory under its performance constraints, a conflict detection model based on truncated normal distribution was proposed,and influencing factors affecting the overall conflict probability were analysed by numerical simulation. For the conflict scenario, nonlinear particle swarm optimisation (NPSO) algorithm was applied to solve the optimal separation configuration strategy for the ownship. The simulation results show that, in comparison to conventional PSO algorithm, the improved NPSO algorithm improves the optimal value by 14.88% and decreases the maximum velocity change by 19.84%. The simulation also shows that the algorithm can maintain the minimum interval requirements under different initial parameters, demonstrating its strong adaptability.

Research on AGV scheduling and potential conflict resolution in port scenarios: based on improved genetic algorithm

In the research of Automated Guided Vehicle (AGV) scheduling, the most critical issues are the optimization of task allocation to AGVs and the handling of conflict scenarios. To address these challenges, we propose a scheme for AGV scheduling optimization and conflict resolution. To begin with, we introduce a novel improved genetic algorithm grounded on a combination strategy that re-encodes tasks into compound groupings, effectively simplifying large-scale integer programing problems into smaller, more manageable ones. Subsequently, the simplified problem is solved using an improved genetic algorithm. Test results validate that this method not only quickens the pace of finding solutions but also significantly improves the quality of those solutions. This is particularly evident when it comes to managing larger-scale optimization challenges. Furthermore, within AGV system conflict scenarios, this paper divides them into two primary categories: navigational conflicts and task quantity changes. For navigational conflicts, three resolution approaches are designed to address four different types of conflict situations: head-on, crossing, occupation, and chasing conflicts. Considering the fluctuations in task quantity, we developed strategies for rescheduling, non-rescheduling, and insertion rescheduling. Their performances were experimentally compared across various scales of scheduling problems, providing data support and theoretical basis for the selection of scheduling strategies in practical applications.

On the importance of continuous development in the military domain

A significant percentage of modern products and systems purchased from the defense industry are difficult for the buyer to adapt or develop for new needs after lessons learned on the battlefield. This results in the procured systems having unnecessarily short lifespans. This paper contains a literature survey of the implementation and adaptation of military systems, combined with the authors’ own observations from real cases of procurement in the military domain. Furthermore,this paper presents concepts for continuous development in the military domain, addressing several of the issues observed with modern systems. The term “continuous development” is here defined as the continuous modification, improvement and enhancement of military equipment or a military technical system over the course of its life cycle. The paper outlines how compatibility, flexibility and interoperability relate to unmanned aerial vehicles, counter unmanned aerial systems operations and electronic warfare operations, their role in continuous development and why these concepts are important on the modern battlefield. We contend that the ability to modify equipment increases adaptability, and therefore survivability, in conflict scenarios where new threats continuously appear. The paper concludes with recommendations of practical value for the defense industry on how equipment can be adapted to facilitate continuous development.