Optimization and Performance Analysis of Intelligent Video AI Dynamic

In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.

RELATIONSHIP OF TARGET RECOGNITION PERFORMANCE AND RADAR WAVEFORM PARAMETERS

Target recognition performance can be affected by radar waveform parameters.In this paper,we established rigorous relationship between target recognition efficiency and the parameters of a repeatedly transmitted waveform.It is based on Kullback-Leibler Information Number of single observation(KLINs),which measures the dissimilarity between targets depicted by a range-velocity double spread density function in frequency domain.We considered two signal models which are different in the coherence of the observations.The method we proposed takes advantage of the methodology of sequential hypothesis test,and then the recognition performance in terms of correct classification rate is expressed by Receiver Operating Characteristic(ROC).Simulation results about the parameters of LFM signal show the validity of the method.

Recognition and Appreciation and the Moderating Role of Self-esteem on Job Satisfaction and Performance among IT Employees in Melaka

The purpose of this study is to explore and examine employees＇ perceptions of recognition and appreciation among Telekom Malaysia （TM） employees in Melaka and the psychological influence it has on their job satisfaction, performance, productivity, and commitment towards the organizational goals. According to one of the laws of psychology which ＂says if you want someone to repeat a behavior, you should positively recognize the behavior immediately＂. Thus, it has been positively affirmed that every human being like to be recognized and appreciated because it is an innate aspiration. Conversely, even though there is nothing complex about recognition and appreciation, studies has found that these items consistently receive the lowest ratings from employees. Furthermore, research conducted over so many eras constantly and consistently discovered that people care about fair treatment, thus, recognition and appreciation of employees must be done appropriately and timely in order for the program to be effective and efficient and achieve its full objective and set goal of motivation. The constructs that will be used in this study will be operationalized using previously-validated and originally developed measures with little or no modifications where necessary to suit the present research context while the primary data of this research will be analyzed using AMOS software.

Promotion of structural plasticity in area V2 of visual cortex prevents against object recognition memory deficits in aging and Alzheimer's disease rodents

Memory deficit,which is often associated with aging and many psychiatric,neurological,and neurodegenerative diseases,has been a challenging issue for treatment.Up till now,all potential drug candidates have failed to produce satisfa ctory effects.Therefore,in the search for a solution,we found that a treatment with the gene corresponding to the RGS14414protein in visual area V2,a brain area connected with brain circuits of the ventral stream and the medial temporal lobe,which is crucial for object recognition memory(ORM),can induce enhancement of ORM.In this study,we demonstrated that the same treatment with RGS14414in visual area V2,which is relatively unaffected in neurodegenerative diseases such as Alzheimer s disease,produced longlasting enhancement of ORM in young animals and prevent ORM deficits in rodent models of aging and Alzheimer’s disease.Furthermore,we found that the prevention of memory deficits was mediated through the upregulation of neuronal arbo rization and spine density,as well as an increase in brain-derived neurotrophic factor(BDNF).A knockdown of BDNF gene in RGS14414-treated aging rats and Alzheimer s disease model mice caused complete loss in the upregulation of neuronal structural plasticity and in the prevention of ORM deficits.These findings suggest that BDNF-mediated neuronal structural plasticity in area V2 is crucial in the prevention of memory deficits in RGS14414-treated rodent models of aging and Alzheimer’s disease.Therefore,our findings of RGS14414gene-mediated activation of neuronal circuits in visual area V2 have therapeutic relevance in the treatment of memory deficits.

Design and implementation of railway green performance basic data collection system

This study addressed the issues related to the collection and management of basic data for railway green performance. A railway green performance basic database has been constructed based on metadata and data exchange schemas. A data classification system has been established from the perspectives of businesses, processes,and entities. A BIM(Building Information Modelling) model data extraction scheme is proposed based on field similarity matching and a document content extraction scheme is proposed based on image recognition. A railway green performance basic data collection system has been developed, achieving efficient collection and integrated management of railway green performance basic data. This system can provide data support for applications such as railway carbon emissions accounting, green cost-benefit analysis, and evaluation of green design solutions.

A TOTAL QUALITY PROCESS FOR DESIGN OF A PERFORMANCE APPRAISAL SYSTEM

This paper proposes an improved performance appraisal system (PAS) that is based on the philosophy of total quality management(TQM). It focuses on understanding the customer′s (both management and employees) requirements for the PAS in order to prioritize and simplify the basic elements of the appraisal system and implementation process. The improved process is defined by performance planning, counseling and evaluation with assessments for individual, team and management contributions. In addition, reducing the rating scale to three categories should facilitate a very positive evaluation process for most employees and still allow a constructive focus on those individuals that must be improved. Finally, if people come first in the TQM organization, then the personnel systems must reflect this philosophy.

Application of support vector machine in trip chaining pattern recognition and analysis of explanatory variable effects

In order to improve the accuracy of travel demand forecast and considering the distribution of travel behaviors within time dimension, a trip chaining pattern recognition model was established based on activity purposes by applying three methods： the support vector machine （SVM） model, the radial basis function neural network （RBFNN） model and the multinomial logit （MNL） model. The effect of explanatory factors on trip chaining behaviors and their contribution to model performace were investigated by sensitivity analysis. Results show that the SVM model has a better performance than the RBFNN model and the MNL model due to its higher overall and partial accuracy, indicating its recognition advantage under a smai sample size scenario. It is also proved that the SVM model is capable of estimating the effect of multi-category factors on trip chaining behaviors more accurately. The different contribution of explanatory, factors to trip chaining pattern recognition reflects the importance of refining trip chaining patterns ad exploring factors that are specific to each pattern. It is shown that the SVM technology in travel demand forecast modeling and analysis of explanatory variable effects is practical.

Comparing Online Performance of EMG Pattern Recognition with and Without Joint Movements

Our previous study suggested that the subcutaneous muscle displacement caused by joint movements might alter muscle activation patterns and thus affect the classification performance.To further analyze the effect of joint movements on the online performance of Electromyography(EMG)Pattern Recognition(PR),this study assessed online classification performance with and without joint movements.EMG signals were recorded from the dominant forearm of 10 able-bodied subjects under two motion scenarios:Hand and Wrist Joints Unconstrained(HAWJU)and Constrained(HAWJC).Sixth-order autoregressive coefficients and four time-domain features were extracted from EMG signals.Linear Discriminant Analysis(LDA)models were trained to perform an online performance evaluation of the limb motions.The experimental results showed that the four online performance metrics:Motion Selection Time(MST),Motion Completion Time(MCT),Motion Completion Rate(MCR),and Online Classification Accuracy(ONCA)were 0.35 s,1.44 s,97.40%,and 82.61%for HAWJU and 0.37 s,1.47 s,89.70%,and 73.57%for HAWJC,respectively.The outcomes of this study indicated that subcutaneous muscle displacement due to joint movements has a positive effect on online classification performance.The absence of joint movements may be a physiological factor contributing to the poor online performance of the EMG-PR of transradial amputees.This study can provide a new perspective for improving the online performance of EMG-PR for transradial amputees.

Authentication and distinction of Shenmai injection with HPLC fingerprint analysis assisted by pattern recognition techniques

In this paper, the feasibility and advantages of employing high performance liquid chromatographic （HPLC） fingerprints combined with pattern recognition techniques for quality control of Shenmai injection were investigated and demonstrated. The Similarity Evaluation System was employed to evaluate the similarities of samples of Shenmai injection, and the HPLC generated chromatographic data were analyzed using hierarchical clustering analysis （HCA） and soft independent modeling of class analogy （SIMCA）. Consistent results were obtained to show that the authentic samples and the blended samples were successfully classified by SIMCA, which could be applied to accurate discrimination and quality control of Shenmai injection. Furthermore, samples could also be grouped in accordance with manufacturers. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of Shenmai injection.

Posterior probability calculation procedure for recognition rate comparison

This paper focuses on the recognition rate comparison for competing recognition algorithms, which is a common problem of many pattern recognition research areas. The paper firstly reviews some traditional recognition rate comparison procedures and discusses their limitations. A new method, the posterior probability calculation（PPC） procedure is then proposed based on Bayesian technique. The paper analyzes the basic principle, process steps and computational complexity of the PPC procedure. In the Bayesian view, the posterior probability represents the credible degree（equal to confidence level） of the comparison results. The posterior probability of correctly selecting or sorting the competing recognition algorithms is derived, and the minimum sample size requirement is also pre-estimated and given out by the form of tables. To further illustrate how to use our method, the PPC procedure is used to prove the rationality of the experiential choice in one application and then to calculate the confidence level with the fixed-size datasets in another application. These applications reveal the superiority of the PPC procedure, and the discussions about the stopping rule further explain the underlying statistical causes. Finally we conclude that the PPC procedure achieves all the expected functions and be superior to the traditional methods.

商品房消费者执行异议的规则适用——基于最高人民法院裁判分歧的分析与展开

我国实定法优先保护商品房消费者的权利,但基于生存权的考量,这一规则不会导致实践中相冲突利益间的严重失衡。为稳定交易预期,这一规则的适用应予严格把握:首先,只要具备商品房买卖合同必要条款的书面合同均可被认定为“买卖合同”;其次,商住两用房、车位等不动产只要满足当事人及其配偶、未成年子女或其监护人的居住需要,则在保护范围之内;再次,买受人尚须证明已实际支付不动产买卖价金。另外,为提供高效完整的权利保护体系,商品房消费者在排除申请人对不动产的执行后,可以选择继续履行合同,亦可选择参与拍卖不动产的价金分配,如商品房消费者不能继续履行合同,债权人可再次提起诉讼,以争议标的实现债权。

应用于人脸识别的多任务卷积神经网络性能优化

对一种多任务卷积神经网络的人脸识别性能进行研究与优化。该神经网络采用3个独立的任务网络分别进行人脸检测、关键点定位和人脸识别。让3个任务网络在训练过程中共享底层卷积层的特征表示,使得模型能针对多个任务同时进行学习,进而提高其泛化能力和识别精度。为了增强模型对图像的学习能力,采用一种数据增强和迁移学习技术,使人脸识别系统的准确性、鲁棒性和可靠性均得到了显著提升。研究结果为发展人脸识别技术提供了新的思路,尤其在处理复杂场景和多样化人脸图像方面具有一定的应用前景。

Improving iris recognition performance via multi-instance fusion at the score level

Fusion of multiple instances within a modality for biometric verification performance improvement has received considerable attention. In this letter, we present an iris recognition method based on multiinstance fusion, which combines the left and right irises of an individual at the matching score level. When fusing, a novel fusion strategy using minimax probability machine （MPM） is applied to generate a fused score for the final decision. The experimental results on CASIA and UBIRIS databases show that the proposed method can bring obvious performance improvement compared with the single-instance method. The comparison among different fusion strategies demonstrates the superiority of the fusion strategy based on MPM.

基于视线角速度精度的导引系统抗干扰性能评估指标研究

针对传统抗干扰性能评估指标集中在导弹制导系统层面,无法满足导引系统抗干扰性能评估的问题,本文在分析抗干扰过程中制导系统内部误差传递原理的基础上,基于导引系统的测量误差,提出了基于视线角速度精度的导引系统抗干扰性能评估指标,从而在导引系统研制过程中,能够及时对其抗干扰性能进行评估。由于视线角速度精度在外场试验中不易测量,为了提高该指标的测试效率,基于比例导引制导原理,给出了视线角速度精度的简化计算方法,并针对非比例导引制导场景,给出了利用识别时间对视线角速度精度进行等效测试的方法。外场数据测试结果表明,该指标能够反映导弹在不同场景下的抗干扰性能,具有一定合理性。

麻石清肺合剂HPLC指纹图谱的建立及7种成分含量测定

目的建立麻石清肺合剂HPLC指纹图谱及测定盐酸麻黄碱等7种成分的含量。方法应用HPLC法构建12批麻石清肺合剂的指纹图谱同时进行了相似度评价,通过模式识别筛选差异性成分,对盐酸麻黄碱等7种成分进行含量测定。结果12批麻石清肺合剂样品中标定16个共有峰,相似度均>0.900,指认7个化学成分。12批样品被分为4类,筛选出8、7(苦杏仁苷)、3(盐酸麻黄碱)、9、10(甘草苷)、4(盐酸伪麻黄碱)、6号峰为差异性成分。12批麻石清肺合剂中盐酸麻黄碱、盐酸伪麻黄碱、苦杏仁苷、甘草苷、甘草酸、和厚朴酚、厚朴酚的含量分别为29.620~156.274、12.504~85.355、245.089~643.440、20.357~79.625、35.117~108.893、0.310~5.556、1.777~10.382μg·mL^(-1)。结论建立的指纹图谱和含量测定方法能够更加全面地评价麻石清肺合剂的品质。

基于深度卷积自编码器和多尺度残差收缩网络的滚动轴承寿命状态识别

针对滚动轴承早期故障识别困难、退化性能难以准确评估的问题,提出了基于深度卷积自编码器(DCAE)和多尺度残差收缩网络(MSRSN)的滚动轴承寿命状态识别方法。首先,为获得清晰的故障特征频率及倍频,将原始数据样本转换为包络谱输入深度卷积自编码器中,实现轴承寿命状态特征的自动提取与表达,并基于多维尺度分析(MDS)算法约简寿命状态特征获得低维特征,然后计算低维特征空间内样本间的欧几里得距离(ED),即为轴承性能衰退评估指标;其次,为全面提取轴承性能衰退特征,提出了改进的多尺度残差收缩网络识别模型,并开发了ReLU与DropBlock正则化相结合的新激活策略增强模型的抗噪性;最后,将所提方法及对比方法应用于轴承全寿命实验数据。实验结果表明:笔者提出的性能衰退评估指标能够精准地识别轴承性能退化起始点以及刻画轴承的退化趋势,所提出的改进的多尺度残差收缩网络识别模型在S SNR=-4~6 dB环境中平均识别正确率为91.75%,能够准确识别轴承寿命状态,验证了方法的实用性以及有效性。

Retention and chiral recognition mechanism of organo-phosphorus compounds in high-performance liquid chromatography

In normal phase condition, a series of chiral phosphorus organic compounds have been separated by high-performance liquid chromatography. In order to study the retention and chiral recognition mechanism, the method of quantitative structure-enantioselectivity retention relationships (QSERRs) has been investigated from the quantitative equations established between the chromatographic retention of enantiomers and their molecular descriptors of physicochemical properties. The results show that on the Pirkle-type chiral stationary phase (CSP) of Sumichiral OA4700, it is the parameter of LUMO that gives the most contribution to the chromatographic retention of O-ethyl O-(substituted) phenyl N-isopropyl phosphoroamidothioates resulting from the interaction of hydrogen bond and (or) π-π interaction. Meanwhile, the chiral recognition is formed from the contribution of logP and LUMO.

UPLC-Q-Exactive-Orbitrap-MS法同时测定牛黄上清片中18种胆汁酸的含量

目的 建立超高效液相色谱-四极杆-静电场轨道阱高分辨质谱(UPLC-Q-Exactive-Orbitrap-MS)法同时测定牛黄上清片中牛磺胆酸、7-酮-3α,12-α-羟基胆烷酸、甘氨猪去氧胆酸、12-脱氢胆酸、甘氨胆酸、3-酮-7α,12α-二羟基-5β-胆烷酸、牛磺鹅去氧胆酸、3α-羟基-7-氧代-5β-胆烷酸、猪胆酸、牛磺脱氧胆酸钠、猪去氧胆酸、胆酸、甘氨鹅脱氧胆酸、甘氨脱氧胆酸、牛磺石胆酸钠、鹅去氧胆酸、去氧胆酸、石胆酸的含量。方法 分析采用Thermo Fisher Scientfic Bremen HYPERSIL GOLD色谱柱(2.1 mm×100 mm, 1.9μm);流动相0.1%甲酸-甲醇,梯度洗脱;体积流量0.2 mL/min;柱温40℃;加热电喷雾离子源;负离子扫描;平行反应监测模式。再进行化学模式识别。结果 18种胆汁酸在各自范围内线性关系良好(r≥0.999 5),平均加样回收率96.73%~104.07%,RSD 2.10%~4.07%。不同厂家样品中各胆汁酸在种类和含量上存在一定差异。结论 该方法灵敏可靠,专属性好,可用于牛黄上清片的质量控制。

一种综合赋权的算法性能评价体系

针对当前自动目标识别算法的性能评价指标过于单一的问题,以行人检测作为应用背景下进行了相关研究。论文设计了一套基于AHP(层次分析法)与CRITIC赋权法的目标识别算法性能评价指标体系。该指标体系针对目标识别算法的准确性、时效性、适应性设计了多个性能评价指标,并综合主观赋权法与客观赋权法对评价指标进行赋权。实验测试结果与ImageNet等计算机视觉挑战赛中person类别的检测排名基本吻合,证实论文提出的性能评价体系可靠。

表现性评价何以甄别高质量的教师——以美国加州PACT模式为例

美国加州教师表现性评价(PACT)模式关注真实的课堂情境,基于多元表现性证据,注重教学实践反思,通过精通表现性评价的专业化评价人员,采取公正科学的表现性评价原则和标准来甄别高质量的、具有教学表现力的教师。该模式已经证实具有一定的优越性,但对于如何甄别高质量的教师仍存在理论和实践的争议,包括教师选拔的专业化和地方控制、边缘化和特权化、形成性和总结性等方面。基于PACT模式的优势和争议分析,对于如何重新构想我国高素质、专业化、创新型教师的遴选和甄别模式具有重要的参考价值,包括精准关切教师的过程性评价,完善教师甄别的制度衔接,预见可能的表现性评价的挑战等。