Artificial Intelligence:International Security Challenges and Governance

Recently,the rapid development of artificial intelligence technology—and its application in the military field—has attracted extensive attention in the public,policy,and academic circles.However,different research paradigms and debates on the nature and aspects of AI challenges to international security exist in theory and policy.In the process of the international community’s exploration of AI global security governance,effectively integrating the views of all parties and constructing consensus international norms is difficult.This paper summarizes and analyzes the current debates on the challenges and governance of AI technology to international security,the multiple evolutions of international security governance norms in the era of AI,and the cooperation and competition between China and the United States in the field of AI international security.Sorting out and exploring these arguments can provide a new research direction and perspective for exploring the global governance path of artificial intelligence.

Hybrid Prediction Method for Solar Power Using Different Computational Intelligence Algorithms

Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicability of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Real life solar radiation data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart grid operation.

Seguin Form Board as an intelligence tool for young children in an Indian urban slum

Objective:The present study evaluates the concurrent and predictive validity of the Seguin Form Board Test(SFBT)as an intelligence tool for children in low-and middle-income countries.Methods:In a cohort of normal children,followed up in South India,two cross-sectional analyses were done at 3 and 7 years of age on 95 children.The SFBT and Vineland Social Matu-rity Scale(VSMS)were done at 3 years of age and Malin’s Intelligence Scale for Indian Children(MISIC)and the VSMS were done at 7 years of age,and the results were compared for concurrent and predictive validity for the SFBT.Results:Intelligence quotient and social quotient had positive correlations at 3 years of age,indicating fair concurrent validity.The SFBT done at around 3 years of age had good positive cor-relation with MISIC at 7 years of age,indicating good predictive validity.Conclusion:This study shows the utility of the SFBT as a community-based intelligence tool with acceptable concurrent and predictive validity.

Effect of mild head injury on intelligence in Zahedan, Iran

Objective： To investigate the effects of mild head injury （HI） on the victims＇ intelligence by measuring their intelligence quotient （IQ）.Methods： This cohort study was performed in Khatamol-Anbia Hospital, Zahedan, Iran and the IQs of 30 mild HI patients were measured right after the injury （IQ0） and six months later （IQ6）. The IQs of 90 close relatives of the patients were also measured at the same period of time as the non-exposure group. The IQs were measured with Wechsler adult intelligence scale-revised （WAIS-R）. The IQ0, IQ6 and their differences （IQ change） were compared in HI patients and their relatives using the Student＇s t test.Results： The mean IQ0 of the HI patients was similar to their relatives. The IQ6 of HI patients appeared to be less than those of their relatives. Moreover, the IQ6 of the HI patients appeared to be less than their initial scores. HI was associated with more decrease in IQ6 compared with IQ0and the female subjects showed more decrease in IQ6 compared with their IQ0.Conclusion： HI seems to be associated with decrease in IQ six months after the injury and it is more evident in female HI patients.

Cognitive impairment in patients with bipolar disorder alone versus those with bipolar disorder comorbid with borderline personality disorder

BACKGROUND Bipolar disorder(BD)is a severe mental illness.BD often coexists with borderline personality disorders,making the condition more complex.AIM To explore the differences in cognitive impairment between patients with BD and those with BD comorbid with borderline personality disorder.METHODS Eighty patients with BD and comorbid borderline personality disorder and 80 patients with BD alone were included in groups A and B,respectively,and 80 healthy volunteers were included as controls.Cognitive function in each group was evaluated using the Chinese version of the repeatable battery for the assess-ment of neuropsychological status(RBANS),the Stroop color-word test,and the Wechsler intelligence scale-revised(WAIS-RC).RESULTS The indices of the RBANS,Stroop color-word test,and WAIS-RC in groups A and B were significantly lower than those of the control group(P<0.05).Group A had significantly longer Stroop color-word test times for single-character,single-color,double-character,and double-color,lower scores of immediate memory,visual breadth,verbal function dimensions and total score of the RBANS,as well as lower scores of verbal IQ,performance IQ,and overall IQ of the WAIS-RC compared with group B(P<0.05).Compared to group B,group A exhibited significantly longer single-character time,single-color time,double-character time,and double-color time in the Stroop color-word test(P<0.05).CONCLUSION The cognitive function of patients with BD complicated with borderline personality disorder is lower than that of patients with BD.

Research on the intelligent internet nursing model based on the child respiratory and asthma control test scale for asthma management of preschool children

BACKGROUND Childhood asthma is a common respiratory ailment that significantly affects preschool children.Effective asthma management in this population is particularly challenging due to limited communication skills in children and the necessity for consistent involvement of a caregiver.With the rise of digital healthcare and the need for innovative interventions,Internet-based models can potentially offer relatively more efficient and patient-tailored care,especially in children.AIM To explore the impact of an intelligent Internet care model based on the child respiratory and asthma control test(TRACK)on asthma management in preschool children.METHODS The study group comprised preschoolers,aged 5 years or younger,that visited the hospital's pediatric outpatient and emergency departments between January 2021 and January 2022.Total of 200 children were evenly and randomly divided into the observation and control groups.The control group received standard treatment in accordance with the 2016 Guidelines for Pediatric Bronchial Asthma and the Global Initiative on Asthma.In addition to above treatment,the observation group was introduced to an intelligent internet nursing model,emphasizing the TRACK scale.Key measures monitored over a six-month period included the frequency of asthma attack,emergency visits,pulmonary function parameters(FEV1,FEV1/FVC,and PEF),monthly TRACK scores,and the SF-12 quality of life assessment.Post-intervention asthma control rates were assessed at six-month follow-up.RESULTS The observation group had fewer asthma attacks and emergency room visits than the control group(P<0.05).After six months of treatment,the children in both groups had higher FEV1,FEV1/FVC,and PEF(P<0.05).Statistically significant differences were observed between the two groups(P<0.05).For six months,children in the observation group had a higher monthly TRACK score than those in the control group(P<0.05).The PCS and MCSSF-12 quality of life scores were relatively higher than those before the nursing period(P<0.05).Furthermore,the groups showed statistically significant differences(P<0.05).The asthma control rate was higher in the observation group than in the control group(P<0.05).CONCLUSION TRACK based Intelligent Internet nursing model may reduce asthma attacks and emergency visits in asthmatic children,improve lung function,quality of life,and the TRACK score and asthma control rate.The effect of nursing was significant,allowing for development of an asthma management model.

面向智慧教育的技术伦理取向与风险规约

当前,智能技术与教育的全过程融合正推动教育方式发生深刻转变,同时衍生出算法歧视、技术滥用、隐私泄露和教育主体错位等技术伦理风险,如何规避风险以最大化享受智能技术红利成为智慧教育发展的重要议题。为此,文章首先分析技术伦理相关报告文件,刻画智慧教育在智能技术、教育主体、教育数据和教育监管四个向度的技术伦理取向;然后,文章剖析“教-学-管-评-练-研”六大智慧教育典型场景下的差异化技术伦理风险表征,将其产生根源归为技术工具失信、教育实践失范和师生素养不足三个层面;最后,文章从技术升级、风险管理、问责监管、数据流动和素养提升角度给出风险防范与治理建议,助力智慧教育健康可持续发展。

大模型融入云平台,信息化走向数智化

随着人工智能的快速发展,大模型已逐渐发挥其关键作用,成为驱动企业数字化转型的重要力量。主要探寻了大模型崛起引发的众多变革,回溯了人工智能的发展轨迹,分析了自建基础大模型所面临的挑战,强调引入基础大模型提供方需要与垂直行业企业联手,合作开发行业大模型。针对中小型企业在开发行业大模型时所面临的困扰,提出“模型即服务”及其相关工具链可以通过协助微调形成专有企业模型的观点;探讨了大模型兴起对云服务产生的变革;对云网协同、算网融合以及人工智能加速数智化发展进行了深入分析。在数字经济时代的背景下,进一步分析了人工智能如何赋能新一代信息技术创新。目前正处于国际经济发展调整期、信息化向数字化的演进期及网络技术创新的加速期,大宽带、大连接、大数据、大平台、大模型、大智能正在快速地融合发展。

页岩气勘探开发实验技术研究进展与发展方向

页岩气开发的成功得益于全新地质理论的建立及工程技术的进步,其中地质理论的创新离不开实验技术的突破与发展,但随着页岩气进入全面开发的新阶段,对实验方法、基础理论等方面提出了更高要求和技术挑战。为此,针对页岩气勘探开发过程中的关键问题,从页岩矿物组成、岩石物性、孔隙结构、含气性及可压性等5个方面展示了地质实验研究的进展和应用实例,分析了页岩气勘探开发实验研究面临的问题和挑战,并展望了其未来的发展方向和趋势。研究结果表明:①薄片鉴定和X射线衍射是页岩矿物分析最有效的定性定量方法,开展矿物成因实验研究对于揭示页岩成储规律及地质工程甜点段优选有着更重要的指导意义;②页岩物性测试方法多且标准不统一,需要根据研究目的选择适用的测试方法,开展地层条件下的物性测试对储量计算及开发效果评价更有帮助;③页岩孔隙结构表征已形成了从宏观到微观、从定性到定量、从二维到三维的综合评价方法,可指导开发层系划分和水平井靶窗优选;④页岩含气性评价已形成了现场含气量测试、等温吸附、气体碳同位素监测等实验方法,揭示了页岩气赋存状态和解吸规律,可有效指导气井生产制度制订和采收率提高;⑤页岩可压性评价已形成了X射线衍射、多尺度的裂缝网络刻画、三轴力学、差应变法、声波各向异性法及声发射法等实验方法,可指导水平井设计和压裂工艺优化。结论认为,建立跨尺度多方法深度融合的实验体系、加强原位条件下的页岩气储层评价、开展关键参数的动态演化和基于大数据模型的人工智能实验评价等是下一步研究方向,持续完善页岩气实验地质技术体系方可为页岩气高效勘探开发提供更好的理论基础和技术支撑。

水凝胶多场耦合计算力学

作为一种具有多场耦合特性的智能柔体材料,水凝胶的制备技术、性能表征与结构应用得到迅速发展。本文在分析水凝胶本构理论和结构设计的基础上,提出了水凝胶多场耦合计算力学的基本方法和范式,包括微观粗粒化分子动力学模拟和宏观耦合有限元方法等,计算了化学-力学耦合作用下水凝胶材料与结构的变形和应力,给出了多个数值算例与结果比较。研究指出多场耦合计算力学将成为水凝胶材料和结构分析的主要手段,并推动水凝胶等这类智柔材料的性能设计与工程应用。

Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

拉普拉斯卷积的双路径特征融合遥感图像智能解译方法

由于遥感图像存在多尺度变化和目标边缘模糊等问题,对其进行智能解译仍然是一项极具挑战性的工作。传统的语义分割方法在处理这些问题时存在局限性,难以有效捕捉全局和局部信息。针对上述问题,文中提出一种双路径特征融合分割方法 DFNet。首先,使用Swin Transformer作为主干提取全局语义特征,以处理像素之间的长距离依赖关系,从而促进对图像中不同区域相关性的理解;其次,将拉普拉斯卷积嵌入到空间分支,以捕获局部细节信息,加强目标地物边缘信息表达;最后,引入多尺度双向特征融合模块,充分利用图像中的全局和局部信息,以增强多尺度信息的获取能力。在实验中,使用了三个公开的高分辨率遥感图像数据集进行验证,并通过消融实验验证了所提模型不同模块的作用。实验结果表明,所提方法在Uavid数据集、Potsdam数据集、LoveDA数据集的mIoU达到了71.32%、85.58%、54.01%,提高了语义分割的性能,使分割结果更为精细。

无人机高空航拍视角下小尺度车辆精确检测方法

无人机高空航拍图像中车辆像素占比极低,目标可视化信息较少,在目标检测任务中容易漏检和误检。因此,本文提出一种基于改进YOLOX(You Only Look Once X)的无人机高空航拍视角下小尺度车辆精确检测方法。首先,为增强网络对低级特征的提取能力,在原始YOLOX预测头部增加一个160 pixel×160 pixel的浅层特征提取网络;其次,在骨干网络后端嵌入基于归一化的注意力机制模块(Normalization-based Attention Module,NAM),以抑制冗余的非显著特征表达;最后,为了增大小尺度车辆的相对像素比,提升网络捕捉有效特征信息的能力,提出一种基于滑动窗口的图像切分检测方法。试验结果表明,改进YOLOX网络表现出良好的检测效能,检测精度达到了84.58%,优于典型的目标检测网络Faster R-CNN(79.95%)、YOLOv3(83.69%)、YOLOv5(84.31%)及YOLOX(83.10%)。此外,改进YOLOX能够有效解决无人机高空航拍图像中小尺度车辆的漏检和误检问题,且预测框更贴合车辆的实际轮廓;同时,在不同航拍高度的目标检测任务中具有较高的鲁棒性。

Evaluating Pharmacological and Rehabilitation Strategies for Effective Management of Bipolar Disorder: A Comprehensive Clinical Study

Bipolar disorder presents significant challenges in clinical management, characterized by recurrent episodes of depression and mania often accompanied by impairment in functioning. This study investigates the efficacy of pharmacological interventions and rehabilitation strategies to improve patient outcomes and quality of life. Utilizing a randomized controlled trial with multiple treatment arms, participants will receive pharmacotherapy, polypharmacotherapy, rehabilitation interventions, or combination treatments. Outcome measures will be assessed using standardized scales, including the Hamilton Depression Scale, Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and Mania Scale. Preliminary data suggest improvements in symptom severity and functional outcomes with combination treatments. This research aims to inform clinical practice, guide treatment decisions, and ultimately enhance the quality of care for individuals living with bipolar disorder. Findings will be disseminated through peer-reviewed journals and scientific conferences to advance knowledge in this field.

AIGC出版背景下知识生产合规化困境与调适

AIGC技术凭借强大的内容生成能力迅速渗透到知识生产领域,在成为知识生产有力工具的同时也引发诸多合规化问题。出版界早已敏锐地认识到问题的严重性,却因缺乏应对能力而陷入了知识生产合规化治理的困境。文章对AIGC技术可能违反的知识生产规范进行详细梳理,包括独立性规范、知识产权规范、权责明确规范、科学性规范和创新性规范,剖析知识生产合规化困境的结构化成因,提出以构建知识核验机制为核心的调适思路,并设计知识核验机制的具体方案,以期为破解AIGC出版背景下知识生产的合规化困境,维护知识生产秩序提供有效的参考。

基于改进YOLOv5算法的无人机巡检图像智能识别方法

提出一种基于改进YOLOv5算法的无人机巡检图像智能识别方法。该方法构建无人机巡检图像的相邻图像独立坐标系,并利用相对定向法确定图像中共同目标的位置关系。将巡检目标统一转换至同一坐标系下,采用先进的分割技术提取目标纹理特征向量,为后续的图像识别提供了有力支持。在改进YOLOv5算法的过程中,特别注重多尺度网络的选择与融合激活函数及损失函数的优化组合。采用大疆无人机获取建筑裂缝巡检图像进行实验。结果表明,该方法能够在高效率下实现不同类型建筑裂缝的高精度识别,展现出优异的稳定性能。这一研究成果为无人机巡检图像的智能识别提供了新的思路和方法,具有广泛的应用前景和实际价值。

智能人文研究及其未来发展

智能人文是一个新兴的人文研究领域,涵盖了人类文化、语言研究、历史研究、文化遗产保护、艺术创作和哲学反思等多个智能化发展方面。现阶段,在人文学科领域,人工智能技术的引入正逐渐成为一把双刃剑。一方面,人工智能为人文研究提供了前所未有的高效工具和方法;另一方面,人工智能技术的引入也带来了一系列风险和挑战。因此,人工智能技术适配人文学科的关键在于跨学科合作和交流、确保数据的多样性和代表性、重视人工智能系统给出结果的可解释性和批判性分析。

基于5G技术的大规模在线智慧考试体系构建

随着社会对基于互联网的大规模考试需求不断增加,新的形势对考试场景智能化水平、考务管理能力、考试评价改革都提出了更高的要求。基于此,本研究构建出一套适合大规模、跨地域、多层级办学体系的智慧考试体系,创新性提出适合大规模考试场景的5G多级混合组网架构,同时,融合前沿智能技术实现考前、考中、考后全流程的智能化提升,并基于国家开放大学的组考实践进行了验证,为未来大规模、社会化考试的组织和管理提供路径参考。

新纯粹主义:逻辑美学与语义驱动

提出并定义了新纯粹主义美学的基本理论框架,指出美作为一种逻辑存在,必须是在共同逻辑基础、共同逻辑范式基础上形成的逻辑共鸣。通过理性控制与认知引导等方式构建美的逻辑存在是新纯粹主义美学管理的主要路径,并以朗香教堂为例做了论证。新纯粹主义美学的内核可以归纳为逻辑美学,这是纯粹主义美学的必然趋势,也是人工智能大模型进行艺术创作的理论依据。从分析哲学角度讨论了新纯粹主义美学的语义驱动原理,重点分析了人工智能如何通过逻辑分析驱动大模型的艺术创作,指出新纯粹主义美学通过对审美乃至情感的逻辑表达,为数字时代的艺术创造提供了新的方向。

制造企业数智化能力:维度探索与量表开发

随着数智技术的飞速发展,数智化转型已成为数字经济时代制造企业发展的必然选择。数智化推动制造企业重构竞争优势,数智化能力成为制造企业创新发展的关键驱动力。然而,部分制造企业在转型过程中陷入“不转型等死、转型找死”的两难困境,数智化能力建设缺乏方向指引,亟待对数智化能力的内涵和构面进行深入研究。在文献分析和扎根理论的基础上,基于动态资源基础观,归纳并提取企业数智化能力构成维度,包括生产智造能力、数智化运营能力和数智连接能力,开发各维度测量量表,利用SPSS和Amos软件对290份有效问卷进行实证检验,结果表明开发的数智化能力测量量表信效度较高。研究结论有助于加深对数智化能力这一概念构成的理解,为数智化能力水平测度提供有效的量化分析工具。