Comparison of stationary acoustic monitoring and visual observation of finless porpoises

The detection performance regarding stationary acoustic monitoring of Yangtze finless porpoises Neophocaena phocaenoides asiaeorientalis was compared to visual observations. Three stereo acoustic data loggers (A-tag) were placed at different locations near the confluence of Poyang Lake and the Yangtze River, China. The presence and number of porpoises were determined acoustically and visually during each 1-min time bin. On average, porpoises were acoustically detected 81.7 +/- 9.7% of the entire effective observation time, while the presence of animals was confirmed visually 12.7 +/- 11.0% of the entire time. Acoustic monitoring indicated areas of high and low porpoise densities that were consistent with visual observations. The direction of porpoise movement was monitored using stereo beams, which agreed with visual observations at all monitoring locations. Acoustic and visual methods could determine group sizes up to five and ten individuals, respectively. While the acoustic monitoring method had the advantage of high detection probability, it tended to underestimate group size due to the limited resolution of sound source bearing angles. The stationary acoustic monitoring method proved to be a practical and useful alternative to visual observations, especially in areas of low porpoise density for long-term monitoring.

A dedicated binding mechanism for the visual control of movement.

The human motor system is remarkably proficient in the online control of visually guided movements, adjusting to changes in the visual scene within 100 ms [1-3]. This is achieved through a set of highly automatic processes [4] translating visual information into representations suitable for motor control [5, 6]. For this to be accomplished, visual information pertaining to target and hand need to be identified and linked to the appropriate internal representations during the movement. Meanwhile, other visual information must be filtered out, which is especially demanding in visually cluttered natural environments. If selection of relevant sensory information for online control was achieved by visual attention, its limited capacity [7] would substantially constrain the efficiency of visuomotor feedback control. Here we demonstrate that both exogenously and endogenously cued attention facilitate the processing of visual target information [8], but not of visual hand information. Moreover, distracting visual information is more efficiently filtered out during the extraction of hand compared to target information. Our results therefore suggest the existence of a dedicated visuomotor binding mechanism that links the hand representation in visual and motor systems.

Revised diagnosis of the genus Bangana Hamilton, 1822 (Pisces : Cyprinidae), with taxonomic and nomenclatural notes on the Chinese species

Most morphological characters diagnostic of the 13 Chinese species of the cyprinid genus Sinilabeo Rendahl, 1932, are identical to those of the genus Bangana Hamilton, 1822. Consequently, these 13 species are transferred to Bangana. A revised diagnosis is provided for the now-expanded genus Bangana, and a dichotomous key and taxonomic and nomenclatural notes are included for the following valid Chinese species: B. decora, B. dero, B. devdevi, B. discognathoides, B. lemassoni, B. lippa, B. rendahli, B. tonkinensis, B. tungting, B. wui, B. xanthogenys, B. yunnanensis, and B. zhui. Literature reports, by Chinese authors, of Sinilabeo dero from the upper Irrawady River basin, in Yunnan, are based on misidentifcations of B. devdevi. Sinilabeo cirrhinoides Wu and Lin in Wu, Lin, Chen, Chen and He, 1977, and S. laticeps Wu and Lin in Wu, Lin, Chen, Chen and He, 1977, are junior subjective synonyms of B. devdevi and B. lippa, respectively. Sinilabeo yunnanensis Wu, Lin, Chen, Chen and He, 1977, is an available name, and a lectotype is designated for the species. Bangana zhui ( Zheng and Chen, 1983) is a valid species distinct from B. yunnanensis.

Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.

Biologically inspired visual odometer for navigation of a flying robot

Experimental research in biology has uncovered a number of different ways in which flying insects use cues derived from optical flow for navigational purposes, such as safe landing, obstacle avoidance and dead reckoning. In this study, we use a synthetic methodology to gain additional insights into the navigation behavior of bees. Specifically, we focus on the mechanisms of course stabilization behavior and visually mediated odometer by using a biological model of motion detector for the purpose of long-range goal-directed navigation in 3D environment. The performance tests of the proposed navigation method are conducted by using a blimp-type flying robot platform in uncontrolled indoor environments. The result shows that the proposed mechanism can be used for goal-directed navigation. Further analysis is also conducted in order to enhance the navigation performance of autonomous aerial vehicles. © 2003 Elsevier B.V. All rights reserved.

Comparison between visual and passive acoustic detection of finless porpoises in the Yangtze river, China

Recently, sonar signals and other sounds produced by cetaceans have been used for acoustic detection of individuals and groups in the wild. However, the detection probability ascertained by concomitant visual survey has not been demonstrated extensively. The finless porpoises (Neophocaena phocaenoides) have narrow band and high-frequency sonar signals, which are distinctive from background noises. Underwater sound monitoring with hydrophones (B&K8103) placed along the sides of a research vessel, concurrent with visual observations was conducted in the Yangtze River from Wuhan to Poyang Lake in 1998 in China. The peak to peak detection threshold was set at 133 dB re 1 mu Pa. With this threshold level, porpoises could be detected reliably within 300 m of the hydrophone. In a total of 774-km cruise, 588 finless porpoises were sighted by visual observation and 44 864 ultrasonic pulses were recorded by the acoustical observation system. The acoustic monitoring system could detect the presence of the finless porpoises 82% of the time. A false alarm in the system occurred with a frequency of 0.9%. The high-frequency acoustical observation is suggested as an effective method for field surveys of small cetaceans, which produce high-frequency sonar signals. (C) 2001 Acoustical Society of America.

HIRFL 束流诊断系统软件的设计

本论文根据兰州重离子加速器（HIRFL）束流诊断系统的现状及改造要求，开发了多任务的束流诊断系统应用软件，它能够通过计算机网络进行测量。该软件的设计采用了面向对象程序设计技术；论文还完成了荧光靶图像获取与处理系统应用软件的开发。这两个应用软件都是由Visual C++编译器来实现，并运行于Windows 95/98操作系统中。论文包括三个部分。第一部分综述了目前国际上加速器束流诊断技术的现状及其发展的新动向，并扼要地介绍了一些重要束流参数的测量方法。第二部分简单介绍了数字图像处理技术的基本内容，比较系统地介绍了荧光靶图像获取及处时系统软件的设计过程，并给出了用该系统测量ECR源束线上束流横向发射度的结果。第三部分首先介绍了Windows操作系统的多任务机制以及计算机网络的通信机制，其中包括TCP/IP协议的有关特性以及如何利用MFC中的CSocket类实现Windows 95/NT系统中网络通信的方法；然后详细介绍了多任务束流诊断系统软件的设计方法及实现过程；最后给出它的现场测试结果以及作者对仿后该软件的升级和维护的设想及展望。

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.