群检铅防护屏的制作与应用

1．1两块高60cm、宽100cm的铅百叶裙（自制）。其中一个制成带有底座并且能竖立于地面上，（如图1，表示为裙①）。一根直径约1cm、长约100cm的不锈钢棍，另一百业裙与不锈钢棍相固定，（如图2，表示为裙②）。

机械定时器单片机群检系统

本文介绍了一种专门用于检测家电产品上所用机械定时器的群检系统。该系统以８０３１单片机为核心，用８２５５Ａ扩展了三个并行接口，外接ＥＰＲＯＭ和ＲＡＭ，键盘，ＬＥＤ显示器等元器件构成。文中给出了系统硬件框图和部分软件框图。

胸部X射线群检剂量的测定

本文给出历年来在胸部X射线群检中医务工作者和受检者所接受的体表吸收剂量的测定结果。在一次胸部X射线摄片检查中医务工作者和受检者所接受的平均体表吸收剂量分别为:7.9×10^(-12)Gy和2.02×10^(-4)Gy;变化范围分别为(3.0-11.9)×10^(-12)Gy和(1.61-2.31)×10^(-4)Gy。在一次胸部X射线透视检查中医务工作者和受检查所接受的平均体表吸收剂量分别为:6.5×10^(-10)Gy和12.7×10^(-4)Gy;变化范围分别为(1.7-17.2)×10^(-10)Gy和(7.2-24.6)×10^(-4)Gy。本文还给出受检者在检查前等待时由散射X射线所产生的体表吸收剂量的测量结果。

无人机集群协同巡检在超高压和特高压输电线路运维中的实践

文章主要研究了超、特高压输电线路运维面临的挑战与需求,探讨了无人机集群协同巡检技术的原理和优势。通过实际的实验和应用案例,验证了无人机集群协同巡检在超、特高压输电线路运维中的可行性和效果。研究结果表明,无人机集群协同巡检方法可提高线路巡检效率,降低运维成本,同时减少人员安全风险。该研究有助于推动超、特高压输电线路运维的现代化进程,具有重要的研究意义和实际应用价值。

汽车检测与维修技术专业群人才培养模式的研究

文章介绍了汽车检测与维修技术专业群的建设基础和建设思路。首先强调了专业群的定位和人才培养目标,强调培养具有创新意识、创业能力、工匠精神的复合型高素质技术技能人才。其次,介绍了专业群与区域产业的紧密结合,以校企合作和订单培养为基础,完善双元育人模式。然后,探讨了课证融合体系和多样化的课程学习模式,包括线上线下混合式教学和项目教学等方法,阐述了专业群的建设思路,包括明确人才培养定位、与产业链对应、协调共建等方面。最后,强调了专业群内专业的协同发展和与社会职业、行业和产业发展的对应关系。

体育科学研究中有中介的调节和有调节的中介潜变量模型检定

体育科学研究中,中介变量和调节变量2个第三变量同时出现的检定情形越来越多。有调节的中介和有中介的调节模型检定,关注自变量与因变量关系的机制和边界条件,极大促进了体育科学研究的深入发展。随着统计技术和软件开发的长足进步,则更有裨益。就体育科学研究中,存在的有调节的中介和有中介的调节潜变量模型检定问题进行整理和分析,并参照目前检定力较强、学界一致推崇的偏差校正非参数百分位Bootstrapping法(Bias-corrected non-parametric percentile Bootstrap method)进行案例检定分析。结论:(1)体育科学研究中,有中介的调节和有调节的中介潜变量检定存在的主要问题是变量关系利用不充分、理解及表述不规范、调节变量拉入时机缺乏理论支撑、采用标准化值检定、检定方法失当等问题;(2)Bootstrapping法的实用性、易用性和可读性,有利于满足体育科学研究中自变量与因变量关系机制和边界条件的检定需求;(3)有调节的中介和有中介的调节潜变量模型的检定程序和方法包括检定中介效果跨群组特性、检定中介效果改变的强度与方向和检定中介效果的差异(异质性检定)3个步骤。

Driving fatigue fusion detection based on T-S fuzzy neural network evolved by subtractive clustering and particle swarm optimization

In order to improve the accuracy and reliability of the driving fatigue detection based on a single feature, a new detection algorithm based on multiple features is proposed. Two direct driver＇s facial features reflecting fatigue and one indirect vehicle behavior feature indicating fatigue are considered. Meanwhile, T-S fuzzy neural network（TSFNN）is adopted to recognize the driving fatigue of drivers. For the structure identification of the TSFNN, subtractive clustering（SC） is used to confirm the fuzzy rules and their correlative parameters. Moreover, the particle swarm optimization （PSO）algorithm is improved to train the TSFNN. Simulation results and experiments on vehicles show that the proposed algorithm can effectively improve the convergence speed and the recognition accuracy of the TSFNN, as well as enhance the correct rate of driving fatigue detection.

Low complexity iterative differential decoding algorithm for multiband UWB communication systems

Due to not requiring channel state information （CSI） at both the transmitter and the receiver, noncoherent ultra-wideband （UWB） incurs a performance penalty of approximately 3 dB in the required signal to noise ratio （SNR） compared to the coherent case. To overcome the gap, an effective differential encoding and decoding scheme for multiband UWB systems is proposed. The proposed scheme employs the parallel concatenation of two recursive differential unitary space-frequency encoders at the transmitter. At the receiver, two component decoders iteratively decode information bits by interchanging soft metric values between each other. To reduce the computation complexity, a decoding algorithm which only uses transition probability to calculate the log likelihood ratios （LLRs） for the decoded bits is given. Simulation results show that the proposed scheme can dramatically outperform the conventional differential and even coherent detection at high SNR with a few iterations.

GNSS spoofing detection based on uncultivated wolf pack algorithm

In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.

Barrier-focused intervention to increase colonoscopy attendance among nonadherent high-risk populations

AIM： To increase attendance tor colonoscopy among nonadherent high-risk individuals for colorectal cancer （CRC） screening in China. METHODS： During the first 12 mo without intervention, only 428 of the 2398 high-risk subjects attended a scheduled colonoscopy examination. The 1970 subjects who did not attend for CRC screening were enrolled in the present study. Prior barrier investigation was performed to ascertain the reasons for nonadherence. A barrier-focused intervention program was then established and implemented among eligible nonadherent subjects by telephone interviews and on-site consultations. The completion rates of colonoscopy during the first 12 mo without intervention and the second 12 mo with intervention were compared. Variations in the effect of the intervention on some high-risk factors and barrier characteristics were analyzed using logistic regression. RESULTS： 540 subjects who were not eligible were excluded from the study. The colonoscopy attendance rate was 23.04% （428/1858） during the first 12 mo without intervention, and 37.69% （539/1430） during the second 12 mo with intervention （P 〈 0.001）. Logistic regression analysis showed that the intervention was more effective among subjects with only objective barriers （OR： 34.590, 95% CI： 23.204-51.563） or subjects with some specific highrisk characteristics： first-degree relatives diagnosed with CRC （OR： 1.778, 95% CI： 1.010-3.131）, personal history of intestinal polyps （OR： 3.815, 95% CI： 1.994-7.300） and positive result for immunochemical fecal occult blood testing （OR： 2.718, 95% CI： 1.479-4.996）. CONCLUSION： The barrier-focused telephone or on- site consultation intervention appears to be a feasible means to improve colonoscopy attendance among nonadherent high-risk subjects for CRC screening in China.

Packet Cache-Forward Method Based on Improved Bayesian Outlier Detection for Mobile Handover in Satellite Networks

In this paper, we propose a Packet Cache-Forward(PCF) method based on improved Bayesian outlier detection to eliminate out-of-order packets caused by transmission path drastically degradation during handover events in the moving satellite networks, for improving the performance of TCP. The proposed method uses an access node satellite to cache all received packets in a short time when handover occurs and forward them out in order. To calculate the cache time accurately, this paper establishes the Bayesian based mixture model for detecting delay outliers of the entire handover scheme. In view of the outliers' misjudgment, an updated classification threshold and the sliding window has been suggested to correct category collections and model parameters for the purpose of quickly identifying exact compensation delay in the varied network load statuses. Simulation shows that, comparing to average processing delay detection method, the average accuracy rate was scaled up by about 4.0%, and there is about 5.5% cut in error rate in the meantime. It also behaves well even though testing with big dataset. Benefiting from the advantage of the proposed scheme in terms of performance, comparing to conventional independent handover and network controlled synchronizedhandover in simulated LEO satellite networks, the proposed independent handover with PCF eliminates packet out-of-order issue to get better improvement on congestion window. Eventually the average delay decreases more than 70% and TCP performance has improved more than 300%.

On-line outlier and change point detection for time series

The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.

A Modified Outlier Detection Method in Dynamic Data Reconciliation

Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.

Correlativity of lymph node micrometastases detection in follicular carcinoma of thyroid in different risk groups

Objective:The aim of this study was to explore the relationship between follicular carcinoma of thyroid in different risk groups and lymph node micrometastases.Methods:The keratin-19 of negative neck lymph nodes in 83 cases in routine pathological examination,was detected by SP immunohistochemistry using keratin-19 monoclonal antibody to confirm lymph node micrometastases.All of cases are divided into high risk group,middle risk group and low risk group according to factors related prognosis,the relationship between lymph node micrometastases and different risk groups and follow-up visit documents were analyzed.Results:Fifty-eight neck lymph nodes in 16 cases of 83 cases(19.3%) showed positive lymph node micrometastases,and incidence of lymph node micrometastases was 4/39 in low risk group,5/32 in middle risk group and 7/12 in high risk group,respectively.it showed remarkable difference during 3 groups(P < 0.001).Nine patients in 16 cases with positive lymph node micrometastases showed local recurrence and distant metastases,6 patients in 67 cases with negative lymph node micrometastases showed same result(P < 0.001).Conclusion:Lymph node micrometastases in follicular thyroid carcinoma closely correlated to factors related to prognosis.The detection of lymph node micrometastases can directly assistant postoperative treatment and prognosis evaluation to some extent for follicular thyroid carcinoma.

Application of heat shock protein expression for detecting natural adaptation and exposure to stress in natural populations

Heat-shock proteins （HSPs） play an undisputed role for maintaining cellular functioning under environmental challenges and protein denaturing conditions. Compelling evidence points to an evolutionary important role of HSPs and a strict evolutionary control of these proteins as a balance between benefits and costs. While there is a great potential for using HSP expression for detecting natural adaptation and exposure to stress in natural populations, some obstacles and key issues await investigation. From an ecological perspective these key issues needs to be resolved in order to fully appreciate the complex responses and adaptations to stress and to increase our understanding of HSPs and other molecular chaperones for stress adaptation and potential use as biomarkers. Here, the current knowledge and understanding of HSPs is reviewed and a number of key issues including the interpretation of elevated HSP levels, the complications of extrapolating between laboratory and field conditions, the effects of choice of traits and methodology and the larger intra-and extracellular networks of interactions that HSPs participate in are discussed [Current Zoology 56 （6）： 703-713, 2010].

Distribution Pattern Scale of Natural Toona ciliata Population

In order to research the population distribution pattern of endangered species Toona ciliata Roem., the sampling quadrats of 5 mx5 m and 3 m×3 m in size, accurate to 1 mxl m, were established in 2 newly-found only existing T. cili- ata Roem. communities （T1 and T2） with contiguous grid quadrate method, in the Nanhe River valley, Gucheng County. By X2 test, t-test of distribution coefficient Cx method, and F test of Morisita pattern index Iδ whether the distribution patterns of the T. ciliata Roem. populations conformed to Poisson distribution were checked. The results indicated that, population T1 was in Poisson distribution under 5 m×5 m and 3 m×3 m in size by Cx and 16 methods, but in clumped distribution pattern un- der 5 m×5 m in size by the Chi-square test; however, the population was in Pois- son distribution under the dimension of 3 m×3 m. Population T2 under human dis- turbance had higher population density, indicating clumped distribution under 3 above-mentioned tests. If Chi-square test is satisfied, a distribution pattern is in Poisson distribution, and size and quantity of sampling quadrats should be given pri- ority to; and if df is greater, both theoretical values and observed values tend to- wards normal distribution more probably, and the test of distribution pattern, there- fore will be more dependable.

FAST DETECTING TARGET GROUPS IN SAR IMAGES

A successful algorithm for detecting target groups is presented. Firstly, A global Constant False Alarm Rate (CFAR) detector is utilized to locate the potential target regions, and then the features are com- puted for target discrimination based on voting mechanism. Finally, Target groups are extracted. The results of experiments show the validity of this algorithm.

New Technology Usage for Sustaniable Dairy Cow Reproductive Perfomances

Technology gives many oppurtunites for cattle farmers for easier and effective herd management possibilities. New era provides many realistic applications using smart applications for farmers. Especially milking is very popular for engineering applications. Reproductive technologies can be seen as frontier applications. Reproductive performances of the dairy farms can be defined as number of calves for cows in a year. It means new material for meat and milk production. Because new female calf means new cow for her while male calf means new material for beef. If meat and milk production are to be increased, cow productivity, i.e. the number of calves produced lifetime must be improved and increased. Although varying among herds, annual average herd incidences of reproductive disorders and reproductive performance were similar to those reported. Managerial practices influenced incidences of retained placenta and uterine infection, days open of cows not bred and of all cows, services per conception and percentages of herd open more than 100 days and culled for low production. Good heat detection programs can have a major impact on overall herd reproductive performance. The best heat detection programs start with careful timing, good observation and the effective use of detection aids. Being able to distinguish and interpret cow behaviour and other signs is critical, so are good record keeping and training for the people responsible for heat detection. Generaly, farmers with the best heat detection results use a combination of observation and heat detection aids. Several options are available to aid heat detection and increase heat detection rates. Although a rich variety of methods have been introduced for the detection of oestrus, a more accurate and practical method is still required.

Indication of Bacteria in Water Marshes （Southern Iraq）

The study was conducted in water marshes for five major marshes during the months of January, April and September of each region （Hawizeh, Hammer and the central marsh） in southern Iraq. Bacteriological analysis that some of the default pathological bacteria, including TC （Total bacterial count）, FCB （faecal coliform bacteria）, MPN （coliform bacteria） and FS （faecal streptococcus） can evidence to indicate of pollution. The results showed that most of the water samples examined pathological contain bacteria which indicates that the water is unfit for human consumption and the waters as basal （more hydrogen than No. 7）. There was a high salinity more than the permissible limits for human consumption and even to irrigate crops, and the same case for dissolve oxygen which exceeded are other limits as drinking water.