Performance evaluation and optimization design of photoelectric pyrometer detection optical system

The measurement and control of high temperature play very important roles in national defense, military, scientific experiments, industrial and agricultural production. Photoelectric pyrometer is one of the important radiation thermometers for non-contact temperature measurement. It has an important application in the field of high temperature measurement, and its performance directly affects the accuracy of temperature measurement. By improving the design of the detection optical system of the photoelectric pyrometer, the imaging performance of the photoelectric pyrometer can be improved effectively, and the temperature measurement accuracy can be improved. In this paper, the temperature measurement principle of photoelectric pyrometer, the working principle of the detection optical system and the composition of the system are introduced. The optical components that affect the imaging of the optical system of the photoelectric pyrometer are analyzed. The optical pyrometer detection optical system is simulated by ZEMAX software, based on the analysis results, the Modulation Transfer Function (MTF) and the spot Diagram are used as the main evaluation criteria to optimize the design of the objective lens of the photoelectric pyrometer detection optical system. The imaging performance of the photoelectric pyrometer detection optical system and the accuracy of temperature measurement of the photoelectric pyrometer are improved by optimization design of the detection optical system.     

新一代人工智能在国防科技领域发展探讨

新一代人工智能技术已经成为当前研究的重点和热点,并逐渐成为提升国防力量、军事能力和国家竞争力的有效途径。本文在总结人工智能概念的基础上,给出了新一代人工智能的定义和发展的重要意义,从掌握未来战争主动权、支撑军工装备研制生产模式转型和保障国防科技先进性三个方面梳理了国防科技领域发展新一代人工智能的必要性,并从基础技术支撑和国防特色应用两个方向提出了国防科技领域发展新一代人工智能涉及的基础软硬件、标准规范、智能装备/系统、辅助作战指挥、智能研发等重点内容,在此基础上给出了相关的发展建议。以上研究可为新一代人工智能技术在国防科技领域的研究、应用和发展提供参考。     

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment, the evaluation information of alternatives given by decision makers is often fuzzy and uncertain. As a generalization of intuitionistic fuzzy set (IFSs) and Pythagoras fuzzy set (PFSs), q-rung orthopair fuzzy set (q-ROFS) is more suitable for expressing fuzzy and uncertain information. But, in actual multiple attribute decision making (MADM) problems, the weights of DMs and attributes are always completely unknown or partly known, to date, the maximizing deviation method is a good tool to deal with such issues. Thus, combine the q-ROFS and conventional maximizing deviation method, we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper. Firstly, we briefly introduce the basic concept of q-rung orthopair fuzzy sets (q-ROFSs) and q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs). Then, combine the maximizing deviation method with q-rung orthopair fuzzy information, we establish two new decision making models. On this basis, the proposed models are applied to MADM problems with q-rung orthopair fuzzy information. Compared with existing methods, the effectiveness and superiority of the new model are analyzed. This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers (q-ROFNs) and whose attributes are incomplete.     

Sensor radiation interception risk control in target tracking

This paper is mainly on the problem of radiation interception risk control in sensor network for target tracking. Firstly, the sensor radiation interception risk is defined as the product of the interception probability and the cost caused by the interception. Secondly, the radiation interception probability model and cost model are established, based on which the calculation method of interception risk can be obtained. Thirdly, a sensor scheduling model of radiation risk control is established, taking the minimum interception risk as the objective function. Then the Hungarian algorithm is proposed to obtain sensor scheduling scheme. Finally, simulation experiments are mad to prove the effectiveness of the methods proposed in this paper, which shows that compared with the sensor radiation interception probability control method, the interception risk control method can keep the sensor scheduling scheme in low risk as well as protect sensors of importance in the sensor network.     

Military Spending,Conflict and External Debt in Sub-Saharan Africa

The damaging economic effects of the debt crises on Africa in the late 1980s encouraged considerable research on the determinants of external debt in developing economies. Although sub-Saharan Africa's (SSA) debt was cut by two-thirds by 2008, through two debt relief programmes, debt in the region has since been rising at an increasingly rapid pace. This study provides an empirical analysis of the determinants of external debt in SSA over the period 1960–2016, using dynamic panel methods. It also considers two potentially important factors that have received relatively little attention. One is military spending, rarely considered, despite a number of well-publicised scandals over the procurement of unnecessary and expensive high-tech weapons systems. A second, is the possibility that the countries studied have been involved in conflict. The empirical results point to a positive impact of military spending on external debt, but with some evidence of heterogeneity across the countries. Furthermore, findings indicate that the positive effect of military expenditure on debt becomes more marked in countries that have been affected by conflict. These results imply that policies to improve security and reduce military spending could be beneficial in reducing external debt and, potentially, improving economic performance in the region.     

Dynamic institutionalization: the foundations of Japan’s radioactive problem

Many have suggested that the true purpose behind Japan’s development of a closed nuclear-fuel cycle is to maintain the technical potential to develop nuclear weapons. However, closer examination of the development of Japan’s nuclear industry shows that, although Japan possesses advanced nuclear technologies, there has been no deliberate strategy to create a nuclear-weapon option. There is no “nuclear hedge.” To illustrate this point, this article presents a framework called “dynamic institutionalization” to explain the origins of Japan’s nuclear policies and the different sets of institutionalized pressures and constraints that have perpetuated these policies over time. Japan’s continued development of closed fuel-cycle technologies is primarily driven by domestic politics and the lack of a permanent spent-fuel management solution. On the other hand, Japan’s institutionalized nuclear forbearance is driven by the calculation that, as long as US extended deterrence remains credible, Japan’s security is best guaranteed through reliance on the US nuclear umbrella. By analytically untangling the policy of closed fuel-cycle development from the rationale for nuclear forbearance, this article provides a more nuanced view of the relationships between the domestic and international variables shaping Japan’s nuclear policies.     

Optimal allocation of minimal repairs in parallel and series systems

In reliability engineering, the concept of minimal repair describes that the repair brings the failed unit (eg, system or component) to the situation which is same as it was just before the failure. With the help of the well‐known Gamma‐Poisson relationship, this paper investigates optimal allocation strategies of minimal repairs for parallel and series systems through implementing stochastic comparisons of various allocation policies in terms of the hazard rate, the reversed hazard rate, and the likelihood ratio orderings. Numerical examples are presented to illustrate these findings as well. These results not only strengthen and generalize some known ones in the seminal work of Shaked and Shanthikumar, but also solve the open problems proposed by Chahkandi et al.'s study and Arriaza et al.'s study.     

智能化作战指挥模式需求

智能装备已经走入军队、走向战场,创建智能化作战指挥模式是智能化时代作战指挥的必然发展趋势,智能化作战指挥模式需求分析可为智能作战问题研究提供有效的信息。智能化作战指挥模式的需求分析已经具备了一定的物质、理论和技术基础,同时,也具有了一定的构建思路、实践条件和实验平台。在此基础上,本文从军事需求、功能需求和技术需求以及构建要求四个不同角度进行需求分析,以找准创建需求,为后续工作进一步展开奠定基础。     

An evolving state of play? Exploring competitive advantages of state assets in proliferation networks

Illicit procurement networks often target industry in developed economies to acquire materials and components of use in WMD and military programs. These procurement networks are ultimately directed by elements of the proliferating state and utilize state resources to undertake their activities: diplomats and missions, state intelligence networks, and state-connected logistical assets. These state assets have also been utilized to facilitate the export of WMD and military technologies in breach of sanctions. While used in most historic proliferation cases, their role has seen limited consideration in the scholarly literature. This article seeks to systematically contextualize state resources in proliferation networks, arguing that their use lies between state criminality and routine activity in support of national security. Considering the competitive advantages of these assets compared to similar resources available in the private sector, the article argues that nonproliferation efforts have caused states to change how they use these resources through an ongoing process of competitive adaptation.     

适用于北斗混合星座的相对定位随机模型建模策略

为提高模糊度解算成功率和基线解精度,提出适用于北斗的相对定位随机模型建模策略,即混合随机建模策略。采用最小二乘方差分量估计方法对北斗单差观测量方差进行估计。对处于不同高度的三轨道卫星观测量方差分别建模:对地球静止轨道卫星观测量方差采用载噪比模型建模,对倾斜地球同步轨道卫星和中地球轨道卫星观测量方差均采用仰角模型建模。根据不同模型实时组建观测量的随机模型。试验结果表明:相比于采用传统简化模型和单一的仰角或载噪比模型,混合随机模型能更加真实地反映不同卫星观测量的随机噪声特性,模糊度解算成功率和相对定位精度均有提高,总体性能最优,因而能更好地适用于北斗系统。