Continuous Flash Suppression Inhibits Semantic Processing of Chinese Characters with Unawareness: An Event-Related Potential Study

Semantic processing is a high level cognition function of the human brain. It has been argued intensively whether this process could be accomplished in the absence of awareness. Continuous flash suppression (CFS) is a powerful approach to create stable unconscious state. In this study, subjects were required to observe a series of paired Chinese words and judge the correlation between them in CFS paradigm. A negative component of event related potential, N400, and a Brain symmetry index were used to measure whether the meaning of the paired stimulus was registered in subliminal semantic processing. Analysis didn’t detect a significant difference in N400 response and EEG signal symmetry between correlated and uncorrelated pairs under unconscious condition. These results support the view that semantic information of Chinese character processing is absent without consciousness created by CFS.

Cultural Awareness＇ Functions in Chinese Learners＇ English Acquisition --An Analysis through the Way of Signal-processing

The significance of cultural awareness in foreign language learning is an issue that earns hot discussion in the both fields of linguistics and instructional science. Being different from others, the observing angle in this paper lies in how the signal is processed. The four skills of listening, speaking, reading and writing are classified, by ways of signal processing, into two categorizes, namely receptive skills to which listening and reading belong, and productive skills to which speaking and writing belong. By analyzing the signal processing progress occurred in each of the four skills, the author is to argue the functions of cultural awareness in each of these four skills, in order to reinforce the importance of emphasizing cultural awareness in the new standards for English in China.

A hierarchical algorithm for cyberspace situational awareness based on analytic hierarchy process

The existing network security management systems are unable either to provide users with useful security situation and risk assessment, or to aid administrators to make right and timely decisions based on the current state of network. These disadvantages always put the whole network security management at high risk. This paper establishes a simulation environment, captures the alerts as the experimental data and adopts statistical analysis to seek the vulnerabilities of the services provided by the hosts in the network. According to the factors of the network, the paper introduces the two concepts： Situational Meta and Situational Weight to depict the total security situation. A novel hierarchical algorithm based on analytic hierarchy process （AHP） is proposed to analyze the hierarchy of network and confirm the weighting coefficients. The algorithm can be utilized for modeling security situation, and determining its mathematical expression. Coupled with the statistical results, this paper simulates the security situational trends. Finally, the analysis of the simulation results proves the algorithm efficient and applicable, and provides us with an academic foundation for the implementation in the security situation

Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries

Introduction: The present work was devoted to assess the awareness and usage of quality control tools with the emphasis on statistical process control in Ethiopian manufacturing industries. Semi structured questionnaire has been employed to executive and technical managers of manufacturing industries of various size and specialism across the country. Stratified random sample method by region was used to select sample industries for the study. The samples used for this study are industries mainly from Oromiya, Addis Ababa, Tigray, Amara, SNNP and Diredawa regions proportional to their size of the available industries. Methods: Exploratory method and descriptive statistics was used for data analysis. Available documents and reports related to quality control policy of the selected companies were investigated. Results and Discussions: The number of manufacturing industries involved in this study was 44. Of the sampled manufacturing industries about 60% are from Oromiya and Addis Ababa regions. It has been reported that 100% of the respondents said that the importance of quality control tools is very important to their organizations’ productivity and quality improvement (Figure 3). Quality control professionals were also asked the extent to which quality control system is working in their industry and majority of the respondents (45%) have indicated that quality control system is working to some extent in their respective industries (Figure 18). Conclusions and Recommendations: Most of the quality department of the industries did not fully recognize the importance of statistical process control as quality control tools. This is mainly due to lack of awareness and motivation of the top managements, shortage of man power in the area, and others together would make it difficult to apply quality control tools in their organization. In general, the industries in Ethiopia are deficient in vigor and found to be stagnant hence less exposed to a highly competitive market and don’t adopt the latest quality control techniques in order to gain knowledge about systems to improve quality and operational performance. We conclude that quality management system has to be established as an independent entity with a real power and hence the quality control department which is responsible for quality can make an irreversible decision with respect to quality of any given product. Moreover, the concerned bodies (government and ministry of industries) should give attention and work together with universities to ensure how these statistical process control techniques could be incorporated in a curriculum of the universities at higher levels in degree and masters programs. Furthermore, different trainings which could improve quality and efficiency of their respective management system should be given as short and long term to the employees including top and middle managers found in various industries relevant to their process.

Simulation of Cyber-Physical Systems of Systems： Some Research Areas-Computational Understanding, Awareness, and Wisdom

After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.

Unmanned Aerial Vehicles Flight Safety Improvement Using In-Flight Awareness

This paper presents a novel onboard system called In-Flight Awareness Augmentation System (IFA2S) to improve flight safety. IFA2S is designed to semi-automatically (with human supervision) avoid hazards and accidents due to either internal or external causal factors. The requirements were defined in an innovative way using Systems-Theoretic Process Analysis (STPA) method and applied next to model the system. IFA2S increases aircraft awareness regarding both itself and its environment and, at the same time, recognizes platform and operational constraints to act in accordance to predefined decision algorithms. Results are presented through simulations and flight tests using state machines designed to allow the adoption of appropriate actions for the identified hazards. The different decision algorithms are evaluated over as many as possible hazard situations by simulations conducted with software Labview and XPlane flight simulator. Flight tests are performed in a small fixed wing aircraft and make use of a limited version IFA2S, partially attending identified requirements. Results support the conclusion that IFA2S is capable of improving flight safety.

SCP-Trust Reasoning Strategy Based on Preference and Its Service Composition Process of Context-Aware Process

Before providing services to the user, user preference considerations are the key conditions to achieve the self-adaptive decision-making about service selection and composition process, which is the flexible concerned aspect provided by massive cloud computing environment data. Meanwhile, during the whole services’ providing process, achieving the capturing and forming of service aggregation units’ topology logic, building the context environment’s process-aware of service composition, ensuring the trust and adaptation among service aggregation units, which are the important reasons to express timely requirement preference. This paper designs SCP-Trust Reasoning strategy about the integration of user preference and trust, with process algebra, it is to achieve the context process-aware logic for service composition process, in order to improve the autonomous optimization and evolution of service implementation system.

高校大学生实验室安全意识评价模型的构建

为减少实验室安全事故的发生和提高大学生的实验室安全意识,设计了实验室安全意识影响因素调查问卷和大学生实验室安全意识评价调查问卷,利用层次分析法—熵权法(AHP-EWM)主客观相结合的方法建立高校大学生实验室安全意识评价体系。通过主成分分析法(PCA)处理,再选取累计贡献率超过95%的评价指标进行布谷鸟搜索(Cuckoo Search, CS),最后结合混合优化支持向量机(SVM)建立PCA-CS-SVM大学生实验室安全意识评价模型。验证结果表明,与PCA-LS-SVM和PCA-GA-SVM模型相比,PCA-CS-SVM模型的预测值与实际值的误差较小且评价等级与实际值保持一致,具有较高的准确性和可靠性,可用于高校大学生实验室安全意识评价。

基于霍克斯过程和图神经网络的会话推荐

针对传统会话推荐系统(Session-Based Recommendation System, SBRS)往往忽略了项目点击量之间的交互,以及遗漏了会话内项目之间的相对顺序的问题,本文提出了一种基于霍克斯过程和图神经网络(Hawkes Process and Graph Neural Network, HPGNN)的会话推荐方法。该方法提出了包含图神经位置感知层和图神经霍克斯层的双流结构,分别学习用户的长期和短期偏好。图神经位置感知层通过门控图神经网络(Gated Graph Neural Network, GGNN)来捕捉各个节点之间的交互关系,得到会话中每个项目的隐向量表示,并引入逐次递减的残差网络,有效地将之前的编码信息与当前网络融合,然后通过位置感知注意力网络来捕捉项目节点在会话中的位置信息,用于学习用户的长期偏好表示。图神经霍克斯层通过将霍克斯过程和GGNN相结合来捕捉连续时间的项目点击量之间的关系,用于更准确的表示用户的短期偏好。最后将两者进行线性组合,来更好地描述用户意图。实验结果表明,提出的HPGNN在Diginetica和Yoochoose1/64两个基准会话推荐数据集上的推荐性能均优于其他会话推荐模型。

面对分布式多域电磁态势感知的射频传感器设计

射频传感器是电磁态势感知的一种重要手段,通过对射频信号进行探测和分析,为电磁态势感知提供必要的数据支撑。针对现有射频传感器存在的获取信息不全面、集成度差等问题,提出基于分布式架构,以时、频、空、能等多域为切入点,设计一款分布式的多域电磁态势感知射频传感器,对射频信号进行多域协同侦测,为分析和评估战场电磁态势提供重要参考。首先基于Zynq多进程(Zynq multi-processor,ZynqMP)处理器和ADRV9009射频收发芯片,设计了传感器的硬件方案,并完成了系统实物制作与测试,然后在软件算法方面,从时、频、空、能四个方面入手,分别就各域的关键特征指标,设计了相应的提取算法,最后设计了相应的功能和性能对比测试内外场实验。实测结果表明,传感器在时域所获得波形的震荡次数的误差小于1.92%,频域中对信号带宽和中心频率的测量误差分别小于3.2%和0.04%,能域中对能量的计算存在小于5.6%的误差,空域中来波方向角的测量误差小于2.7%,达到了预期设计要求。

基于Wi-Fi Sensing的无感检测技术

随着智能家居的推广普及,对于移动物体的行为感知成为热点技术。相比于传统的信息检测技术,新型的基于Wi-Fi信号的设备无关被动入侵检测,能够在无需用户做任何干预也不影响人员隐私安全的情况下实现对于行为的检测判断,这和使用摄像头或红外检测形成显著差异,成为研究热点。该文基于Wi-Fi芯片平台采集物理层信道状态信息,构建与移动载体信息相关的检测模型,结合大数据分析和智能算法,给出相关的实现方案,并基于实验验证实现从无线信道中捕捉波形特征,验证方案的有效性,结合结果分析也为后续精度的进一步提升提供改进方向。

基于Qt的遥操作GIS维护机器人监控系统设计与实现

在电力系统中,为了更好、更方便地遥控操作机器人清理气体绝缘开关设备(Gas Insulated Switchgear,GIS)腔体内的螺栓、螺母等异物,研发GIS维护机器人监控系统。采用Qt平台开发,结合FFMPEG和OpenCV采集RTMP网络视频流并进行图像处理,实现对腔体内异物的检测识别与精准定位;以SLAM点云进行环境感知,还原出机器人在腔体内的实际场景。测试结果表明,在无线环境下,该系统可高效实现与机器人的数据交互和有效地实时监控,较好地完成GIS腔体内遗留物的识别与清理。

基于时间序列的大型核电厂设备异动态势感知系统设计

为了准确感知核电厂设备设备异动态势,防止负荷电压、负荷电流数值异常增大,设计基于时间序列的大型核电厂设备异动态势感知系统;在系统硬件设计上,完善设备数据自动处理模块、设备异动信号采集器、态势感知装置之间的实时连接关系;系统软件设计上,构建时间序列模型,实现对核电厂设备异动数据的处理;选取核心异动态势指标,按照标量化处理流程,通过阈值方法实现对核电设备异动态势的感知,完成大型核电厂设备异动态势感知;实验结果表明,上述系统通过准确感知核电厂设备异动态势,将设备负荷电压、负荷电流数值控制在阈值之内,能够维护核电厂设备的稳定运行。

智慧医院网络安全攻防实战体系的构建与思考

目的:针对医疗行业网络安全事件只能事后补救而无法事前预警,解决存在的投入产出比低、绩效难以量化等问题,构建可见、可知、可管、可控的智慧医院网络安全攻防实战体系。方法:通过态势感知平台、安全运行队伍、安全管理方法、安全操作流程等多个维度的技术或管理方法构建网络安全攻防实战体系,将技术手段与管理机制有机结合以实现安全保护。结果:在安全管理制度的指导下,规范安全操作流程,结合实战化态势感知平台对安全事件的精准定位,依托高素质的安全运营队伍,高效处置,快速应急响应,使智慧医院的网络实战能力得到真正体现。结论:通过网络安全攻防实战体系的建设和实践,形成对医疗业务系统安全运营全过程的有效感知,为医疗业务开展创造更加可靠的网络环境。

大语言模型驱动的立场感知事实核查

为解决事实核查领域的证据立场不平衡和忽略立场信息的问题,提出一种大语言模型(LLM)驱动的立场感知事实核查(LLM-SA)方法。首先,使用LLM推理并生成一系列与原始声明立场不同的辩证声明,使事实核查任务能够获取不同立场的视角;其次,通过语义相似度计算衡量每个证据句子与原始声明及辩证声明之间的相关性,并从证据句子中分别选择与两者语义上最相近的k个句子,作为支持或反对原始声明的证据,从而获得代表不同立场的证据,有助于事实核查模型综合多角度的信息,更准确地评估声明的真实性;最后,引入BERT-StuSE(Bidirectional Encoder Representations from Transformers-based Stance-infused Semantic Encoding network)模型,利用多头注意力机制充分融合证据的语义和立场信息,并更全面、客观地判断声明和证据的关系。在CHEF数据集上的实验结果表明,与BERT方法相比,所提方法在测试集上的Micro F1值和Macro F1值分别提高了3.52、3.90个百分点,达到较好的水平。验证了所提方法的有效性,以及考虑不同立场的证据和充分利用证据的立场信息对事实核查的性能提升具有重要意义。

方向感知增强的轻量级自监督单目深度估计方法

为解决现有单目深度估计网络复杂度高、在弱纹理区域精度低等问题,该文提出一种基于方向感知增强的轻量级自监督单目深度估计方法(DAEN)。首先,引入迭代扩展卷积模块(IDC)作为编码器的主体,提取远距离像素的相关性;其次,设计方向感知增强模块(DAE)增强垂直方向的特征提取,为深度估计模型提供更多的深度线索;此外,通过聚合视差图特征改善解码器上采样过程中的细节丢失问题;最后,采用特征注意力模块(FAM)连接编解码器,有效利用全局上下文信息解决弱纹理区域的不适应问题。在KITTI数据集上的实验结果表明,该文模型参数量仅2.9M,取得δ指标89.2%的先进性能。在Make3D数据集上验证DAEN的泛化性,结果表明,该文模型各项指标均优于目前主流的方法,在弱纹理区域具有更好的深度预测性能。

基于情境感知的经期健康管理产品设计研究

探索在女性经期健康管理产品设计中情境感知理论的介入点,以期改善目前经期健康管理产品所供服务的同质化问题,从而提升产品的实际使用效果和用户体验。概述情境感知理论,提取女性经期健康管理的四类情境要素,采用桌面调研、问卷和访谈等方法进行定量和定性分析,运用层次分析法确定功能需求的权重,匹配情境要素,得出针对不同情境感知要素的设计策略。情境感知理论的运用,加强了经期健康管理产品对于情境信息的感知能力,有助于深度挖掘用户需求,为用户提供更具针对性的服务,提升使用效果和体验。

中国英语学习者对粘着词根的识别加工研究

英语派生词的词根可分为自由词根和粘着词根,前者可独立成词,后者不能。实验1采用词汇判断任务,探索汉语为母语的英语学习者是否具有粘着词根意识。实验比较了英语学习者对粘着词根(如clude)和仅一个字母之差的非词(如blude)的反应是否不同。实验2旨在探查英语学习者对自由词根与粘着词根的加工是否存在差异。相比无关的非词启动词(如breffer),含粘着词根的启动非词(如breclude)是否能促进目标词(如CONCLUDE)的识别;与自由词根(如relegal-ILLEGAL)条件相比,两者是否存在差异。两个实验结果均表明英语学习者与母语者相似,存在粘着词根表征,英语学习者对粘着词根的加工与对自由词根的加工没有显著差异。

基于方面感知注意力增强的方面情感三元组抽取

在自然语言处理(NLP)的细粒度情感分析问题中,为探索携带结构偏差的预训练语言模型(PLM)对端到端式情感三元组抽取任务的影响,解决方面语义特征依赖容错率低的问题,结合方面感知注意力机制和图卷积网络(GCN),提出用于方面情感三元组抽取任务的方面感知注意力增强图卷积网络(AE-GCN)模型。首先,在方面情感三元组抽取任务中引入多种类型的关系;其次,采用双仿射注意力机制将这些关系嵌入句子中单词之间的相邻张量,并引入方面感知注意力机制以获取句子注意力评分矩阵,深入挖掘与方面相关的语义特征;再次,GCN通过将单词和关系相邻张量分别视为边和节点,将句子转换为多通道图以学习关系感知节点表示;最后,使用一种有效的词对表示细化策略确定词对是否匹配,以考虑方面和意见抽取的隐含结果。在ASTE-D1基准数据集上的实验结果表明,所提模型在14res、14lap、15res和16res子数据集上的F1值相较于增强型多通道图卷积网络(EMC-GCN)模型提升了0.20、0.21、1.25和0.26个百分点;在ASTE-D2基准数据集上,所提模型在14lap、15res和16res子数据集上的F1值相较于EMC-GCN模型提升了0.42、0.31和2.01个百分点。可见所提模型相较于EMC-GCN模型在精确率和有效性方面有较大改进。

文化自觉视域下文化产业发展评价研究——以安徽省为例

在文化自觉视域下,安徽省文化产业迎来了高质量发展与产业升级的新机遇,但同时也面临着创意人才短缺、文化科研支持力度不够等一系列挑战。基于文化自觉理念和新发展理念,构建符合文化自觉理念内涵的安徽省文化产业发展评价指标体系,运用层次分析法和熵值法相结合的组合权重方法,对安徽省2010—2020年文化产业在文化自觉理念指导下的发展能力进行评估。结果显示2010—2020年安徽省文化继承性总体呈上升趋势,但文化创新能力不显著。有鉴于此,建议安徽省在继承优秀传统文化的基础上,增强文化创新的核心能力,增加对文化科技研究院所的机构支出,加大文化创新与技术性人才的培养力度,促进安徽省文化产业文化创新能力的提升。