Deep smarts

Deep smarts are not philosophical-they are not "wisdom" in that sense-but they are as close to wisdom as business gets. Throughout your organization, there are people with deep smarts. Their judgment and knowledge-both explicit and tacit-are stored in their heads and hands. Their knowledge is essential. The organization cannot progress without it. You will be a more effective manager if you understand what deep smarts are, how they are cultivated, and how they can be transferred from one person to another. Very few organizations manage this asset well, perhaps because it's difficult to pin down and measure. Such neglect is risky.     

深亚微米光刻技术

超大规模集成电路（ＶＬＳＩ）线宽的不断缩小,促进了光刻技术的发展和分辨率的提高,使分辨率已进入到深亚微米区域。光学光刻分辨率的提高是依靠缩短曝光波长、增大透镜系统的数值孔径（ＮＡ）、采用新技术改进掩模和光学系统的设计以及提高光致抗蚀剂的性能来实现的。在简要的介绍了ＶＬＳＩ发展趋势的基础上,论述了深紫外光刻（ＤＵＶＬ）、极紫外光刻（ＥＵＶＬ）和Ｘ射线光刻技术取得的重要成果及面临的问题和可能解决的途径。     

用深能级瞬态谱法测量GaAS MESFET中的深能级

本文介绍了用深能级瞬态谱(DLTS)法测量GaAs MESFET的深能级杂质和缺陷。在有源层中一般没有测到深能级杂质和缺陷,但在有源层与缓冲层界面附近测到了多个空穴陷阱和电子陷阱。其中空穴陷阱的能级有0.41eV、0.53eV、0.68eV、0.91eV;电子陷阱的能级有0.30eV、0.44eV、0.84eV。并对部分陷阱的性质作了初步的讨论。     

Deep levels in superlattices

The physics governing deep levels in superlattices and quantum wells is elucidated, with emphasis on the importance of shallow-deep transitions caused by a band edge passing through a deep level, and the accompanying change in doping character of the impurity.     

Deep multi-query video retrieval

Video retrieval methods have been developed for a single query. Multi-query video retrieval problem has not been investigated yet. In this study, an efficient and fast multi-query video retrieval framework is developed. Query videos are assumed to be related to more than one semantic. The framework supports an arbitrary number of video queries. The method is built upon using binary video hash codes. As a result, it is fast and requires a lower storage space. Database and query hash codes are generated by a deep hashing method that not only generates hash codes but also predicts query labels when they are chosen outside the database. The retrieval is based on the Pareto front multi-objective optimization method. Re-ranking performed on the retrieved videos by using non-binary deep features increases the retrieval accuracy considerably. Simulations carried out on two multi-label video databases show that the proposed method is efficient and fast in terms of retrieval accuracy and time.     

Deep space communications

Discusses communications with spacecraft in deep space from the point of view of: signal strength, the role of the DSN (Deep Space Network), the various missions, and the work of ESA/ESOC (European Space Operations Centre)     

皮基站深度覆盖应用

随着VoLTE规模商用和移动支付业务的高速发展,用户对无线网络深度覆盖提出了更高要求。目前,深度覆盖主要采用小区点射、新建微站或新型室分等方式解决,但受物业协调、配套建设等多方面制约,实施难度不断加大。皮基站微形化、低功率,可采用光纤宽带回传,基本无需物业协调和配套工程建设,部署快、成本低,可快速提升4G网络深度覆盖水平。无线人员深入开展皮基站应用场景分析,详细总结应用和优化方法,提升皮基站应用能力和水平,为网络质量和用户感知保驾护航。     

基于深度学习的单载波频域均衡算法研究

单载波频域均衡(Single-Carrier Frequency-Domain Equalization,SC-FDE)是一种有效的抗码间干扰的算法,在无线通信系统中得到了广泛的应用.传统线性SC-FDE算法主要包括信道估计、噪声功率估计和信道均衡三个模块,其中每个模块都是单独优化的.为了联合优化这三个模块,本文提出了...     

基于深度报文检测和深度流检测的骨干网流量特征分析

Based on the massive data collected with a passive network monitoring equipment placed in China's backbone, we present a deep insight into the network backbone traffic and evaluate various ways for improving traffic classifying efficiency in this paper. In particular, the study has scrutinized the network traffic in terms of protocol types and signatures, flow length, and port distribution, from which meaningful and interesting insights on the current Internet of China from the perspective of both the packet and flow levels are derived. We show that the classification efficiency can be greatly improved by using the information of preferred ports of the network applications. Quantitatively, we find two traffic duration thresholds, with which 40% of TCP flows and 70% of UDP flows can be excluded from classification processing while the impact on classification accuracy is trivial, i.e., the classification accuracy can still reach a high level by saving 85% of the resources.     

Deep multi query image retrieval

There exist few studies investigating the multi-query image retrieval problem. Existing methods are not based on hash codes. As a result, they are not efficient and fast. In this study, we develop an efficient and fast multi-query image retrieval method when the queries are related to more than one semantic. Image hash codes are generated by a deep hashing method. Consequently, the method requires lower storage space, and it is faster compared to the existing methods. The retrieval is based on the Pareto front method. Reranking performed on the retrieved images by using non-binary deep-convolutional features increase retrieval accuracy considerably. Unlike previous studies, the method supports an arbitrary number of queries. It outperforms similar multi-query image retrieval studies in terms of retrieval time and retrieval accuracy.     

Deep metal-related centres in germanium

The deep centres introduced by Au, Ag, Ni, Pt and Pd diffusion in n-and p-type germanium have been investigated by deep level transient spectroscopy. Broad similarities in emission and capture data for donor states measured for these metals indicate that they may have the same underlying complex structure. Lithium is shown to form defect complexes with the metal ions; these Li-related centres also have similar emission rates and capture cross sections.     

深亚微米pHEMT器件的建模

针对0.25μmpHEMT器件,建立了其小信号和非线性等效电路模型,采用窄脉冲测试技术提高了深亚微米器件的测试精度,采用改进的Materka模型提高了模型的模拟精度。已建立的两种0.25μmpHEMT模型已用于毫米波VCO和PA的设计中。     

深空探测与测控通信技术

本文简述了深空探测的重要意义,深空探测对测控通信的挑战以及人类在近30年来为解决矛盾而研究应用的各项措施和所达到的水平。提出了我们应当跟踪研究的深空测控通信领域的新体制、新技术和新设备。     

利用无监督预训练的轨迹深度关联

针对时空相似度算法关联轨迹的局限性,采用深度学习方法进行轨迹关联,并提出了一种基于无监督预训练的匹配神经网络训练方式。利用Geohash向量嵌入对轨迹信号做特征工程处理,构建自注意力机制神经网络结构,使用无标注轨迹数据基于遮蔽预测任务进行模型预训练;然后构建孪生匹配网络结构,加载预训练模型参数;最后使用标注轨迹对数据基于均方差损失函数微调预训练模型参数得到轨迹对匹配模型。采用Geolife GPS轨迹数据集作为评估数据集进行模型训练与测试,实验结果显示,利用无监督预训练的轨迹关联方法较现有最优算法匹配准确率提高了5个百分点,达到了96.3%,充分证明了该方法的有效性。目前轨迹关联领域基于深度学习预训练模型的研究较少,该方法具有重要的参考意义。     

深度学习在雷达中的研究综述

雷达通过发射天线发射电磁波,经过不同物体反射接收到相应的反射波,对其接收结果进行分析,能得到物体距雷达的位置,径向运动速度等信息,所以对雷达信号的分析具有重要的研究意义。近些年深度学习成为各个领域的研究热点,而在雷达领域同样可通过深度学习算法实现对信号的相应的信息处理。与传统方法相比,深度学习算法具有自动提取深层特征、获取较高准确率等优势。该文具体介绍了近期典型的深度学习算法在雷达信号处理中的应用及研究情况。此外,该文介绍了两个在雷达领域中应用深度学习亟待解决的问题,即过拟合和可解译性。      

Deep submicron PDSOI thermal resistance extraction

Deep submicron partially depleted silicon on insulator (PDSOI) MOSFETs with H-gate were fabricated based on the 0.35μm SOI process developed by the Institute of Microelectronics of the Chinese Academy of Sciences. Because the self-heating effect (SHE) has a great influence on SOI, extractions of thermal resistance were done for accurate circuit simulation by using the body-source diode as a thermometer. The results show that the thermal resistance in an SOI NMOSFET is lower than that in an SOI PMOSFET; and the thermal resistance in an SOI NMOSFET with a long channel is lower than that with a short channel. This offers a great help to SHE modeling and parameter extraction.     

Deep centers in undoped semi-insulating InP

Undoped semi-insulating (SI) InP samples, subjected to one-step and multi-step wafer annealing, and lightly and normally Fe-doped SI InP samples without annealing have been characterized by thermally stimulated current (TSC) spectroscopy. A dominant deep center at 0.63 eV is found in all samples and is undoubtedly due to iron. Two prominent TSC traps, T_b (0.44 eV) and T_d (0.33 eV), found in undoped SI InP, are thought to be related to the phosphorus antisite P_In, and traps at low temperatures, like T_e* (0.19 eV), to the phosphrus vacancy V_P.     

Deep image compression with multi-stage representation

While deep learning-based image compression methods have shown impressive coding performance, most existing methods are still in the mire of two limitations: (1) unpredictable compression efficiency gain when adopting convolutional neural networks with different depths, and (2) lack of an accurate model to estimate the entropy during the training process. To address these two problems, in this paper, a deep multi-stage representation based image compression (MSRIC) method is proposed. Owing to this architecture, the detail information of shallow stages and the compact information of deep stages can be utilized for image reconstruction. Furthermore, a data-dependent channel-wised factorized probability model (DCFPM) is adopted to increase the accuracy of entropy estimation. Experimental results indicate that the proposed method guarantees better perceptual performance at a wide range of bit-rates. Also, ablation studies are carried out to validate the above mentioned technologies.     

深亚微米MOS器件的热载流子效应

对深亚微米器件中热载流子效应 (HCE)进行了研究 .还研究了沟道热载流子的产生和注入以及与器件工作在高栅压、中栅压和低栅压三种典型的偏置条件的关系 .在分析热载流子失效机理的基础上 ,讨论了热载流子效应对电路性能的影响 .提出影响晶体管热载流子效应的因素有 :晶体管的几何尺寸、开关频率、负载电容、输入速率及晶体管在电路中的位置 .通过对这些失效因素的研究并通过一定的再设计手段 ,可以减少热载流子效应导致的器件退化 .     

InP中的深能级杂质与缺陷

综述了近年来关于InP中深能级缺陷和杂质的研究工作。讨论了深能级杂质及缺陷对InP材料性能的重要影响;介绍了深能级瞬态谱(DLTS)、光致发光谱(PL)、热激电流谱(TSC)、正电子寿命谱(PAS)、正电子深能级瞬态谱(PDLTS)等几种研究深中心的方法在研究InP时的某些特点;综合深能级缺陷和电学性质的测试结果,证明了半绝缘InP单晶材料的电学性能、热稳定性、均匀性等与材料中一些深能级缺陷的含量密切相关;分析了对掺铁和非掺退火两种半绝缘InP材料中深能级缺陷对电学补偿的影响;评述了对InP中的一些深中心所取得的研究成果和半绝缘InP的形成机理。