Finite sample size effect on minimum variance beamformers: optimum diagonal loading factor for large arrays

Minimum variance beamformers are usually complemented with diagonal loading techniques in order to provide robustness against several impairments such as imprecise knowledge of the steering vector or finite sample size effects. This paper concentrates on this last application of diagonal loading techniques, i.e., it is assumed that the steering vector is perfectly known and that diagonal loading is used to alleviate the finite sample size impairments. The analysis herein is asymptotic in the sense that it is assumed that both the number of antennas and the number of samples are high but have the same order of magnitude. Borrowing some results of random matrix theory, the authors first derive a deterministic expression that describes the asymptotic signal-to-noise-plus-interference ratio (SINR) at the output of the diagonally loaded beamformer. Then, making use of the statistical theory of large observations (also known as general statistical analysis or G-analysis), the authors derive an estimator of the optimum loading factor that is consistent when both the number of antennas and the sample size increase without bound at the same rate. Because of that, the estimator has an excellent performance even in situations where the quotient between the number of observations is low relative to the number of elements of the array.     

500kW／380V国产大功率变频器在钻机上的应用

针对国外变频器价格昂贵、调试周期和维修周期长等特点，我公司自主研发了可替代进口机的高性能钻机国产专用变频器。该变频器能够从零开始调速。当钻井卡钻时，能及时断开电动机，在低速提升时，能最大限度地发挥电动机的动力特性，提供220％的转矩输出。变频器具有易安装、调试、维护，性能稳定。应用中据实测数据显示，采用变频改造后，打1口井可节省柴油15t。     

Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.     

A new detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection.

White blood cell detection is one of the most basic and key steps in the automatic recognition system of white blood cells in microscopic blood images. Its accuracy and stability greatly affect the operating speed and recognition accuracy of the whole system. But there are only a few methods available for cell detection or segmentation due to the complexity of the microscopic images. This paper focuses on this issue. Based on the detailed analysis of the existing two methods--threshold segmentation followed by mathematical morphology (TSMM), and the fuzzy logic method--a new detection algorithm (NDA) based on fuzzy cellular neural networks is proposed. NDA combines the advantages of TSMM and the fuzzy logic method, and overcomes their drawbacks. With NDA, we can detect almost all white blood cells, and the contour of each detected cell is nearly complete. Its adaptability is strong and the running speed is expected to be comparatively high due to the easy hardware implementation of FCN. Experimental results show good performance.     

Operating Penalties in Single-Fiber Operation 10-Gb/s, 1024-Way Split, 110-km Long-Reach Optical Access Networks

We report for the first time optical signal-to-noise penalties which lead to performance degradations in single-fiber long-reach optical access networks when compared to identical dual-fiber systems. A simplified architecture, with reduced optical amplifier count compared to previous work, for single-fiber operation of a symmetrical 10-Gb/s, 1024-way split, 110-km long-reach optical access network is presented and demonstrated. In addition, a possible solution to remove the optical signal-to-noise penalty is suggested     

Multi-level attention model for tracking and segmentation of objects under complex occlusion

A multi-level attention framework for tracking and segmentation of humans and objects under complex occlusions is investigated, featuring an effective probabilistic appearance-based technique for pixel reclassification during object grouping and splitting. A novel ’spatial-depth affinity metric’ is introduced in the conventional likelihood function, utilising information of both spatial locations of pixels and dynamic depth ordering of the component objects in grouping. Depth ordering estimation is achieved through a combination of top-down and bottom-up approach. Experiments on some realworld difficult scenarios of low quality and highly compressed videos demonstrate the very promising results achieved.     

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

Co-digestion of manure and biowaste according to the EC animal by-products regulation and Finnish national regulations.

The objective of this study was to compare methane production and characteristics of digested material in anaerobic digestion concepts according to the Animal By-Products Regulation (ABP-Regulation) of the EC (hygienisation of biowaste for 1 hour at 70 degrees C, particle size < 12 mm) and Finnish national regulations (treatment temperature 55 degrees C, feeding interval 24 h, hydraulic retention time (HRT) 20 d, particle size < 40 mm) and with small variations in treatment methods for treating manure and biowaste. Moreover, the survival of three different salmonella bacteria in these processes was studied. Hygienisation of biowaste prior to digestion at 35 degrees C enhanced methane production by 14-18% compared to similar treatment without hygienisation. The differences in treatment temperature, HRT and hygienisation of biowaste prior to digestion did not significantly affect the characteristics of digested material. The concepts according to the ABP-Regulation and Finnish national regulations were effective in destroying salmonella bacteria to an undetectable level.     

Photocatalytic oxidation of low concentration 2,4-D solution with new TiO2 fiber catalyst in a continuous flow reactor.

Environmental pollution by low concentrations of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a concern these days due to ever increasingly stringent regulations. Photocatalysis with immobilized TiO2 fiber is a promising oxidation method. Laboratory experiments on photocatalytic degradation of 0.045 mmol l(-1) 2,4-D with the world's first high-strength TiO2 fiber catalyst were carried out in a continuous flow reactor in which the degradations were, in general, similar to those with high 2,4-D concentrations investigated elsewhere. Degradation and mineralization of 2,4-D were significantly enhanced with no initial pH adjustments. The rate constants for total organic carbon (TOC) without pH adjustment were about two-fold bigger than the pH adjustment cases. CO2 gas measurement and carbon mass-balance were carried out for the first time, where about 34% organic carbon converted into CO2 gas during four-hour oxidation. 2,4-Dichlorophenol (2,4-DCP), phenol, benzyl alcohol and two unknowns (RT = 2.65 and 3.78 min.) were detected as aromatic intermediates while Phenol was the new aromatic in HPLC analysis. Dechlorination efficiencies were high (> 70%) in all the cases, and more than 90% efficiencies were observed in chloride mass balance. Bigger flow rates and solution temperature fixed at 20 degrees C without pH adjustment greatly enhanced 2,4-D mineralization. These results can be an important basis in applying the treatment method for dioxin-contaminated water and wastewater.     

县区电网电压无功控制系统设计

针对目前地区电网电压无功控制的现状,提出了电网电压无功监控系统的设计方案。说明优化控制系统应该实现的功能,选用线性规划(LP)算法为核心程序,正常状态下以有功网损最小为目标函数。依据分离原理提出两层分级控制的系统结构,分析优化控制系统的工作流程及特点。