Enemy Threats Research Articles

Robust convoy movement problem under travel time uncertainty

A convoy represents a collection of vehicles traveling with a spacing of 50–100 m between them for tactical purposes. The convoy movement problem is a variant of the vehicle routing problem, an NP-hard problem aimed at determining the paths and schedules of convoys. Given the uncertainties in travel times during wartime, attributable to various factors such as road conditions and enemy threats, it is essential to consider uncertain travel times when determining convoy paths and schedules. Therefore, this study introduces a robust convoy movement problem under travel time uncertainty. A polyhedral set for uncertain travel times is used to derive a robust counterpart for the problem. To solve the proposed problem, we establish an exact algorithm that determines optimal solutions by iteratively generating and integrating multiple paths of convoys. This algorithm involves four steps: generation of k-th robust shortest paths, construction of path combinations, adjustment of departure times, and conduction of optimality check. These steps are iterated sequentially until the optimal solution is obtained. In computational experiments, the exact algorithm demonstrates superior performance and reduced computation time compared with the commercial solver CPLEX on both real instances and randomly generated instances. In addition, we conduct a sensitivity analysis for several parameters related to the problem, providing valuable managerial insights for decision-makers.

A hospitalization mechanism based immune plasma algorithm for path planning of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) and their specialized variants known as unmanned combat aerial vehicles (UCAVs) have triggered a profound change in the well-known military concepts and researchers from different disciplines tried to solve challenging problems of the mentioned vehicles. Path planning is one of these challenging problems about the UAV or UCAV systems and should be solved carefully by considering some optimization requirements defined for the enemy threats, fuel or battery usage, kinematic limitations on the turning and climbing angles in order to further improving the task success and safety of autonomous flight. Immune plasma algorithm (IP algorithm or IPA) modeling the details of a medical method gained popularity with the COVID-19 pandemic has been introduced recently and showed promising performance on solving a set of engineering problems. However, IPA requires setting the control parameters appropriately for maintaining a balance between the exploration and exploitation characteristics and does not design the particular treatment and hospitalization procedures by taking into account the implementation simplicity. In this study, IP algorithm was supported with a newly designed and realistic hospitalization mechanism that manages when an infected population member enters and discharges from the hospital. Moreover, the existing treatment schema of the algorithm was changed completely for improving the efficiency of the plasma transfer operations and removing the necessity of IPA specific control parameters and then a novel path planner called hospital IPA (hospIPA) was presented. For investigating the performance of hospIPA on solving path planning problem, a set of detailed experiments was carried out over twenty test cases belonging to both two and three-dimensional battlefield environments. The paths calculated by hospIPA were also compared with the calculated paths of other fourteen meta-heuristic based path planners. Comparative studies proved that the hospitalization mechanism making an exact discrimination between the poor and qualified solutions and modified treatment schema collecting the plasma being transferred by guiding the best solution give a tremendous contribution and allow hospIPA to obtain more safe and robust paths than other meta-heuristics for almost all test cases.

En los ríos, bajo la sombra de los árboles y al cobijo del quepis: representaciones gráficas del aseo y del descanso militar durante la Intervención Francesa en México

This article examines some representations of military cleanliness and rest during the French Intervention in Mexico, based on the iconographic and icono-textual analysis of images and reports published in three of the most widely circulated French prints of the time: the illustrated weeklies “L'Illustration Journal Universel” and “Le Monde Illustré”, and the satirical newspaper “Le Charivari”. The two engravings and lithograph were compared with letters, memoirs, manuals, and journalistic pieces by Mexican and French authors in order to observe the graphic expression of the concepts of hygiene and privacy that began to take root socially in both countries from the second half of the 19th century. It is proposed that, despite protocolization, combatants on both sides had to adapt to the harsh conditions of war to recover from it amidst snoring, heat, the anxiety of enemy threat, and dreams of conquest.

Floods- suffering fauna and remedies

Climatic changes are occurring at a faster pace than ever before and Natural disasters are occurring now more frequently. Floods, as one of the Natural disaster is causing heavy losses to human beings as well as to animals, especially livestock and wildlife. Fast and large volumes of water present in the floods, destroy vegetation and other habitat structures of the wild and domestic animals, in minutes, but it can take many years or decades to return, if ever possible. Animals that can fly, may be able to escape, depending upon the severity of weather system. Wild fauna have to face the challenge of finding food in extreme conditions, some may even compromise by reducing their energy requirements, or by ?sleeping? for extended periods. The extent to which wild animals are affected by floods will also depend upon their sensing ability of what?s going to happen and how to respond. Animals, which are having dependent young in burrows, may by the worst sufferers, animals facing flood may be trapped far away from their homes, facing panic and more enemy threats on return. Fast and huge volumes of water from floods can also carry high levels of pollution leading to killing or diseased condition of aquatic animals. Livestock impacted by floods, is mostly fatigued and stressed, upon approaching these animals, they may become aggressive and cause nuisance. Emergency plan should be ready all the time to save livestock. Advance planning for domestic and wild animals (which is mostly not paid attention) is needed in flood prone areas well in time to save them especially in developing countries. When flood comes, animals should be moved to safety, by opening gates and removing fencing. Local authorities and state as well as Centre Government can play an important role to reduce mortality and disease consequences. . KEYWORDS :Floods, Livestock, Climate change, Suffering fauna, Emergency plan

A Multimodal Data Harness Approach of Mobile Sensors Trajectory Planning for Target Tracking

The future Internet comprising multimodal mobile wireless sensors (MMWSs) dramatically increases the data dimension and complexity compared to the traditional homogeneous networks. It consists of various types of nodes that can be deployed in different spatial domains to form the space, air, ground, and ocean integrated network (SAGOI-Net). A key challenge to IoT with SAGOI-Net is harnessing the real-time data from these sensors to obtain target characteristics and realize target tracking, especially in rough environment with obstacles and enemy threats. In this paper, we propose an approach -fuzzy logic and flocking control under extended kalman filter (EKFFL) to provide sensor nodes trajectory formation. With the tools from control systems and signal processing, this approach improves the commonly-adopted flocking control algorithm and fully employs multi modality of data. Compared with the modified kalman consistency filter (KCF) approach, the proposed EKFFL achieves higher target tracking accuracy with a shorter time period of trajectory formation. The trade-off between the data delay and tracking accuracy is also analysed. Based on its advantages, the EKFFL approach can be applied in broad scenarios, such as unmanned border awareness systems, environmental monitoring and intelligent transportation.

Path Planning of an Unmanned Combat Aerial Vehicle with an Extended-Treatment-Approach-Based Immune Plasma Algorithm

The increasing usage of unmanned aerial vehicles (UAVs) and their variants carrying complex weapon systems, known as unmanned combat aerial vehicles (UCAVs), has triggered a global revolution in complex military and commercial operations and has attracted researcher attention from different engineering disciplines in order to solve challenging problems regarding these modern vehicles. Path planning is a challenging problem for UAV and UCAV systems that requires the calculation of an optimal solution by considering enemy threats, total flight length, fuel or battery consumption, and some kinematic properties such as turning or climbing angles. In this study, the immune plasma (IP or IPA) algorithm, one of the most recent nature-inspired intelligent optimization methods, was modified by changing the default plasma transfer operations with a newly proposed technique called the extended treatment approach; extended IPA (ExtIPA) was then introduced as a path planner. To analyze the solving capabilities of the ExtIPA, 16 cases from five battlefield scenarios were tested by assigning different values to the algorithm-specific control parameters. The paths calculated with ExtIPA were compared with the paths found by planners on the basis of other intelligent optimization techniques. Comparative studies between ExtIPA and other techniques allowed for stating that the extended treatment approach significantly contributes to both the convergence speed and qualities of the obtained solutions and helps ExtIPA in performing better than its rivals in most cases.

BUILDINGOF THE MUGHAL NAVAL FORCES

The military was a major element of the Mughal Empires strength and integrity. Beginning with the formation and mobility of the Mughal land army which led to their victory in the First Battle of Panipat in 1526, the Mughal military power grew rapidly alongside the development of the Mughal Empire itself. In compatibility with the position of the Mughal Empire which also controlled the Indian Ocean, Mughal rulers paid attention to the building of the naval force. Commencing with the onset of that statement, the purpose of this article is to examine the purpose of and approaches undertaken by the Mughals in building their naval strength, especially in dealing with enemy threats and consolidating their dominance in the Indian Ocean. This study applied a qualitative approach through historical research and content analysis when collecting and analyzing data from primary and secondary sources. Research findings show that the Mughal navy was built during the era of Akbars reign with the aim of reinforcing the position of the Mughal Empire in several key regions, Gujarat and Bengal being among them, which contributed to economic development within the kingdom. The naval force was given full attention by post-Akbar rulers for the purpose of providing movement support to the land army and dealing with the presence of European powers in India, such as the Portuguese and the British.

An Efficient Path Planning Algorithm Using a Potential Field for Ground Forces

With the development and proliferation of unmanned weapons systems, path planning is becoming increasingly important. Existing path-planning algorithms mainly assume a well-known environment, and thus pre-planning is desirable, but the actual ground battlefield is uncertain, and numerous contingencies occur. In this study, we present a novel, efficient path-planning algorithm based on a potential field that quickly changes the path in a constantly changing environment. The potential field is composed of a set of functions representing enemy threats and a penalty term representing distance to the target area. We also introduce a new threat function using a multivariate skew-normal distribution that accurately expresses the enemy threat in ground combat.

A multi-population immune plasma algorithm for path planning of unmanned combat aerial vehicle

Autonomous flight of an unmanned aerial vehicle (UAV) or its weaponized variant named unmanned combat aerial vehicle (UCAV) requires a route or path determined carefully by considering the optimization objectives about the enemy threats and fuel consumption of the system being operated. Immune Plasma algorithm (IP algorithm or IPA) is one of the most recent optimization techniques and directly models the fundamental steps of a medical method also used for the COVID-19 disease and known as convalescent or immune plasma treatment. In this study, IP algorithm for which a promising performance has already been validated with a single population was first extended to a multi-population domain supported by a migration schema. Moreover, the usage of the donor as a source of plasma for the treatment operations of a receiver was remodeled. The new variant of the IPA empowered with the multi-population and modified donor usage approach was called Multi-IP algorithm or MULIPA. For investigating the solving capabilities of the MULIPA as a UCAV path planner, different battlefield scenarios and algorithm specific parameter configurations were used. The results obtained by the MULIPA were compared with the results of other meta-heuristic based path planners. The comparative studies between MULIPA and other techniques showed that newly proposed IPA variant is capable of finding more secure and fuel efficient paths for a UCAV system.

Menanamkan Nilai-Nilai Pendidikan Patriotisme pada Mahasiswa

The purpose of this study was to determine the educational values of patriotism in students of the PPKn Study Program at Labuhanbatu University. The approach used in this research is a qualitative research type, with a descriptive approach because this research is to describe and explain about the education of patriotism character values that are obtained directly and in real terms through interviews. structured towards students of the 1st (one) semester PPKn Study Program which is carried out for one month. Data collection methods used in the research included observation, interviews and documentation. The results of the study concluded regarding the process of instilling patriotism educational values obtained during structured interviews with material that had been prepared beforehand, many students did not understand the material. Such as material about (1) Willing to sacrifice which is interpreted as a form of fighting spirit to defend the country from enemy threats, (2) Defending the country such as national defense reserves or conscription for every citizen if needed for the integrity of the Indonesian nation, (3) love of the motherland such as commemorating the independence day of the Indonesian nation, maintaining the unity of the Indonesian republic and not being divided, and (4) Pancasila as the state ideology in which there are five precepts that must be carried out in every joint of the country. Pancasila as a unifying nation and the foundation of a country to maintain the integrity of a nation and instill nationalism and patriotism of the nation.

The Effects of Blackcurrant and Berry Extracts on Oxidative Stress in Cultured Cardiomyocytes and Microglial Cells

BackgroundCardiovascular disease (CVD) is the number one cause of morbidity and mortality for both men and women in the U.S; to include our military. Warfighters consistently serve in harm’s way due to their national security mission to deter the enemy’s threats and protect our homeland security. With these high stakes, operational demands impose stressors related to military deployment, and consequently physiological changes related to brain and heart health. All together these processes may also impact operational readiness. Oxidative stress is an key underlying factor in atherosclerosis and cognitive decline. It occurs at the cellular level with an imbalance between reactive oxygen species and reactive nitrogen species, and/or a deficiency in antioxidant systems. Mounting evidence suggests flavonoids, in the form of berry extracts, may promote cell health by exerting antioxidant properties.MethodsThe effects of blackcurrant and various berry extracts were tested in two different cultured cell lines ‐ cardiomyocyte (HL‐1) and microglia (BV‐2) cells ‐ to study their biological effects. The principal ingredients in blackcurrant and cranberry extract – delphinidin 3‐rutinoside (D3R) and cyanidin 3‐glucoside (C3G), respectively—were also assessed. Our primary outcome was oxidative stress. A menadione‐induced oxidative stressor was used and its output was quantified using a green fluorogenic probe to detect oxidative stress (CellROXTM). Control substances included N‐acetyl‐cysteine (NAC).ResultsBlackcurrant extracts had similar antioxidant effects as N‐acetyl‐cysteine (NAC) in HL‐1 cells with regard to cellular protection and antioxidant protection, whereas cranberry extract was ineffective. In contrast, cranberry extract was comparable to blackcurrant extract in BV‐2 cells. As for the bioactive ingredients, results showed that D3R and C3G reduced oxidative stress, which were similar to whole berry extracts. This indicates that these ingredients likely contribute to the antioxidant properties of berries.ConclusionIn summary, we demonstrated that both blackcurrant and cranberry extracts can reduce oxidative stress. Overall, blackcurrant extract was more effective in reducing oxidative stress in the HL‐1 cells, whereas cranberry extract was more effective in reducing oxidative stress in the BV‐2 cells. These results suggest specific cardio and neuroprotective benefits of berry flavonoids. Berry flavonoids also demonstrated promising effects as potent antioxidants. Future research should explore dose response, cell viability, and bioavailability in cellular and human models.DisclaimerThe opinions and assertions expressed herein are those of the author(s) and do not necessarily reflect the official policy or position of the Uniformed Services University or the Department of Defense.Conflict of InterestNeither I nor my family members have a financial interest in any commercial product, service, or organization providing financial support for this research.

Three Dimensional Volume Coverage in Multistatic Sonar Sensor Networks

Recent changes in the design of enemy threats such as submarines and the technological achievements in sensor development have paved the way for multistatic sonar applications, which increase security and situational awareness in underwater tactical operations. Previously, coverage in multistatic sonar sensor networks (MSSN) was studied using Cassini ovals and the traditional sonar detection model in two dimensions without any discussion of the practicability and feasibility in terms of conditions related to the underwater acoustic propagation environment. In this study, a practical three-dimensional MSSN channel model is proposed. The proposed model covers a spectral variation of absorption loss, ambient noise, sound speed profile, and shadow zones. The realistic effects of sound propagation and environmental conditions are modeled and evaluated using Lybin, which is a well-known sonar performance prediction tool. Using the practical MSSN channel model, the number of source-receiver pairs required to cover a three-dimensional MSSN volume is calculated. The impacts of frequency, source-to-receiver distance, and source level are investigated. The results are compared to the Cassini oval and traditional sonar detection models via an error expression derived according to our verified practical model. The results reveal that the inclusion of ambient conditions and sound propagation characteristics in the channel model leads to huge error levels of 4700000% in the Cassini oval model and 170000% in the traditional sonar detection model, depending on frequency. Thus, the applicability of these models in realistic MSSN deployment scenarios is limited.

함정용 고장력 판재의 방호한계속도 추정을 위한 간이 실험식

Naval ships are designed to have a variety of active and passive systems to defend against enemy threats. One of the passive defense systems is to protect crew members and core equipment against the threat by using the outer plate of the equipment. This study was intended to deal with design methods against small arms ammunition and fragments. The Korea Institute of Machinery and Materials has measured the ballistic limit velocity of two types of high-tensile plate materials (AH36 and EH36) widely used in ships and offshore structures through tests in cooperation with various related organizations, and the result data is continuousy accumulated. Based on the accumulated test results and data, such as mil test certificates of plate materials, it is intended to estimate the protection limit speed of high-tensile plates and to develop a simple calculating formula that can be used in the early design stage.

Behavior modeling method and its application in combat simulation

Behavior Modeling and Simulation is an important method to analyze macro-and micro-behaviors of groups and individuals. It can predict and analyze the law of crowd activity under a certain density and provide important support for the study of social and economic activities and war and military activities. It has been widely used in emergency response, combat simulation and many other fields. This paper reviews behavioral modeling and simulation, mainly from the current situation of behavioral simulation applications, the main methods of behavioral modeling and the needs of future development direction. Firstly, the application status of behavior simulation is analyzed from both military and social aspects. In the aspect of social behavior simulation, it mainly analyses several aspects, such as safe evacuation, automatic driving, road traffic planning, intelligent robots and so on. In the aspect of military behavior simulation, it mainly analyses individual combat behavior simulation, battlefield element model construction, combat action combination model, multi-agent coupling simulation and so on. Secondly, the method of behavior modeling is deeply analyzed, and the main models of behavior modeling are summarized, including social force model, cellular automata model, agent model, etc. At the same time, the behavior model of individual’s multiple forces in a certain environment and the emergence effect model of group are deeply analyzed. Finally, based on the above two aspects of research and analysis results, this paper aims at the simulation of multi-person cooperative attack and defense, which is a military behavior simulation problem. From the four aspects of dynamic environmental factors, operational rules constraints, enemy threat factors and multi-agent cooperative control, this paper puts forward several problems that need to be further improved in cooperative attack and defense.

A Solution to VRPTW Based on Improved GA-AMMAS Algorithm

Vehicle routing problem with time windows (VRPTW) is a NP difficult problem, and it has important applications in military logistics, especially the distribution of wartime military equipment, materials and spare parts. In the last decade, numerous new methods for VRPTW have sprung up. However, few researches have been made in the study of VRPTW of wartime distribution. Hence, a two-stage solution is proposed in this paper to solve the VRPTW in complex dynamic environment during the war. That is, static route optimization in the pre-planning stage and dynamic route re-planning in the execution stage for sudden or changing enemy threats. An improved hybrid algorithm of Genetic algorithm and adaptive maximum-minimum ant system (GA-AMMAS) is designed in this paper for the solution of the model above.

Estimation of damage probability of combat vehicle components based on modeling and simulation

Many functions are considered for the design of GCV (ground combat vehicles), which are carried out to increase the survivability of GCV from enemy threats. By improving survivability, the interior of the GCV can be protected and the continuity of mission performance can be improved. The vulnerability assessment is calculated from the damage probability of the components of the target. The damage probability of the component is calculated by the damage probability of the sub-components. For the accuracy of the vulnerability assessment, it is important to accurately calculate the damage probability of sub-components. The damage probability of sub-components is usually calculated only by the penetration. However, it is difficult to calculate the exact damage probability by penetration alone. In this study, damage scenarios of sub-components are created and classified according to damage types such as a type of components, hit position, damage cause and result, etc., and damage rule is calculated and the damage probability of the sub-components is calculated. In order to improve the accuracy of the analysis of the shot line, which was used only to identify the penetration, we conducted the shot line analysis for the ricochet and deflection to enhance the accuracy of the vulnerability assessment.

Robust Optimization Approach Using Scenario Concepts for Artillery Firing Scheduling Under Uncertainty

Real wars involve a considerable number of uncertainties when determining firing scheduling. This study proposes a robust optimization model that considers uncertainties in wars. In this model, parameters that are affected by enemy’s behavior and will, i.e., threats from enemy targets and threat time from enemy targets, are assumed as uncertain parameters. The robust optimization model considering these parameters is an intractable model with semi-infinite constraints. Thus, this study proposes an approach to obtain a solution by reformulating this model into a tractable problem; the approach involves developing a robust optimization model using the scenario concept and finding a solution in that model. Here, the combinations that express uncertain parameters are assumed by scenarios. This approach divides problems into master and subproblems to find a robust solution. A genetic algorithm is utilized in the master problem to overcome the complexity of global searches, thereby obtaining a solution within a reasonable time. In the subproblem, the worst scenarios for any solution are searched to find the robust solution even in cases where all scenarios have been expressed. Numerical experiments are conducted to compare robust and nominal solutions for various uncertainty levels to verify the superiority of the robust solution.

Assessing the vulnerability of military theater distribution routes

Purpose This paper introduces a new heuristic algorithm that aims to solve the military route vulnerability problem, which involves assessing the vulnerability of military cargo flowing over roads and railways subject to enemy interdiction. Design/methodology/approach Graph theory, a heuristic and a binary integer program are used in this paper. Findings This work allows transportation analysts at the United States Transportation Command to identify a relatively small number of roads or railways that, if interdicted by an enemy, could disrupt the flow of military cargo within any theater of operation. Research limitations/implications This research does not capture aspects of time, such as the reality that cargo requirements and enemy threats may fluctuate each day of the contingency. Practical implications This work provides military logistics planners and decision-makers with a vulnerability assessment of theater distribution routes, including insights into which specific roads and railways may require protection to ensure the successful delivery of cargo from ports of debarkation to final destinations. Originality/value This work merges network connectivity and flow characteristics with enemy threat assessments to identify militarily-useful roads and railways most vulnerable to enemy interdictions. A geographic combatant command recently used this specific research approach to support their request for rapid rail repair capability.

Optimal manoeuvre for two cooperative military elements under uncertain enemy threat

Consider an armed military group of two friendly elements that need to move between two given locations - a starting point and an end point - in an environment with the possible presence of armed enemy elements. The potential positions of the enemy may or may not be known in advance. Therefore, we capture the possible threat by identifying the locations that are advantageous from the enemy's perspective. We model the problem using a stochastic programming approach. We then provide a deterministic reformulation of the problem in consideration of this possible threat and, through the use of cooperation, we minimise the total predicted threat as well as the suitability of the terrain for movement (or total length). Finally, we provide concrete experimental calculations and visualisations in our tactical information system, which serves as a tool for commanders to support their decision-making processes, and compare the obtained results to a selection of different approaches.

A robust optimization approach for an artillery fire-scheduling problem under uncertain threat

Abstract In this study, the determination of an artillery firing sequence is considered in order to minimize the enemy threat to friendly forces prior to the conclusion of the firing operation. A deterministic model and robust counterpart are developed to deal with the deterministic and uncertain enemy threat levels, respectively. In both cases, the optimal strategy is demonstrated to be firing based on the threat removal rate per unit time. Moreover, a two-phase approach is developed based on the concept of cardinality-constrained uncertainty. In this approach, the firing sequence is determined in the first phase and then, in the second phase, the robustness of the uncertain factors is adjusted by using the modified problem to evaluate the total threat exposure of friendly units to the enemy. A set of problems is generated and tested using the proposed model and strategy. The results of numerical experiments demonstrate that the proposed strategy outperforms conventional fire-scheduling approaches. Additionally, the price of robustness is considered by adjusting the value of uncertain factors.