Home audio consist of audio products and electronics such as speaker systems, players, and home theaters for home use. This is usually accessory equipment that enhances or supports standard equipment such as TVs, projectors, or music players. From the gramophone to cassette player and now to the latest DVD to Blu-ray players, the home audio scene worldwide has dramatically changed over the past decades.

2013年全球LTE手机终端销量超过2亿部，预计2018年全球LTE手机终端销量超过10亿部，以平均每部LTE手机2000元计算，2018年将实现超过2万亿元销售额。随着国内终端生产企业在全球竞争实力不断增强，产品在全球市场占有率逐年提升，届时中国厂商有望分享40%（即8000亿元）以上的市场商机。2004年LTE概念被正式提出，在LTE规范制定过程中来自全球不同国家和地区的众多企业提供了相关技术文稿，LTE已成为由全球多家企业共同参与制定的国际通用标准。

The Integrated Multi-Modal RF Sensing (IMMRF) effort performed basic research to examine key parameters of integrated multi-modal RF sensor design and algorithm development. A statistical framework for the program was developed, which ensured the overall statistical validity of the approaches. Dynamic waveform design for agile RF sensing, enhanced detection capabilities, and optimized tracking performance was investigated. Approaches were developed for using multiple, spatially distributed, adaptive multi-modal sensors for multiple target tracking and data association. Finally, a radar test bed was developed to support testing and refinement of theories and algorithms.

Flight tests of the National Aeronautics and Space Administration's Turbulence Prediction And Warning System (TPAWS) were conducted in the Fall of 2000 and Spring of 2002. TPAWS is a radar-based airborne turbulence detection system. During twelve flights, NASA's B-757 tallied 53 encounters with convectively induced turbulence. Analysis of data collected during 49 encounters in the Spring of 2002 showed that the TPAWS Airborne Turbulence Detection System (ATDS) successfully detected 80of the events at least 30 seconds prior to the encounter, achieving FAA recommended performance criteria. Details of the flights, the prevailing weather conditions, and each of the turbulence events are presented in this report. Sensor and environmental characterizations are also provided.

No abstract available.

The University of Memphis conducted basic research into techniques for advancing network-centric sensors for eventual deployment in Department of Defense (DoD) applications. This basic research included the following focus sub-areas: (i) feature fusion/feature-based sensor system design techniques; (ii) sensor ontologies for problemsolving architectures; (iii) profiling sensor improvement through the use of innovative classification algorithms and data visualization techniques; (iv) alternative sensing modalities; (v) turbulence mitigation techniques; and (vi) development of a feature sensing laboratory. Under the topic of feature fusion/feature-based sensor system design, techniques known as Lasso, Group Lasso, and Sparse Multiple Kernel Learning were applied to break beam profiling sensor design. The results indicate that the Group Lasso technique is effective for feature quality maximizing sensor design because of its ability to provide both intergroup and intra-group feature sparsity. Under the topic of sensor ontologies for problem-solving architectures, a framework that matches sensors to compatible algorithms to fonn synthesized systems was developed and applied to improved forms of the beam-break profiling sensor. This work resulted in several publications. Under the topic of profiling sensor improvement, various algorithms for improving the classification performance of a pyro-electric based profiling sensor were investigated and tested using data from field collections. Results indicated that Logistic regression with a simple height to width ratio provide good performance.

Cooperative localization is a useful way for nodes within a network to share location information in order to better arrive at a position estimate. This is handy in GPS contested environments (indoors and urban settings). Most systems exploring cooperative localization rely on special hardware, or extra devices to store the database or do the computations. Research also deals with specific localization techniques such as using Wi-Fi, ultra-wideband signals, or accelerometers independently opposed to fusing multiple sources together. This research brings cooperative localization to the smartphone platform, to take advantage of the multiple sensors that are available. The system is run on Android powered devices, including the wireless hotspot. In order to determine the merit of each sensor, analysis was completed to determine successes and failures. The accelerometer, compass, and received signal strength capability were examined to determine their usefulness in cooperative localization. Experiments at meter intervals show the system detected changes in location at each interval with an average standard deviation of 0.44m. The closest location estimates occurred at 3m, 4m and 6m with average errors of 0.15m, 0.11m, and 0.07m respectively. This indicates that very precise estimates can be achieved with an Android hotspot and mobile nodes.

The demonstration described in this report was conducted at the Former Camp Beale, California, under project ESTCP MR-201004 'Practical Strategies for UXO Discrimination.' It was performed under the umbrella of the ESTCP Live-Site Classification Study Program. The objective of the MR-201004 project is to demonstrate the application of feature extraction and statistical classification to the problem of UXO discrimination. At the Camp Beale site, the objective was to discriminate targets of interest (TOI) (including 37 mm, 60 mm, 81 mm targets, 105 mm and a small industry standard object (ISO)) from nonhazardous shrapnel, range and cultural debris. A number of fuses and fuse parts that were initially considered as a possible TOI was later found to be non-TOI, and labeled as clutter. In this report, we describe the performance of classification techniques that utilized full coverage, dynamically acquired, survey data acquired with a Geonics EM61 cart and static, cued interrogation style data acquired with advanced electromagnetic induction (EMI) sensors. Analysts from Sky Research and UBC-GIF processed (1) MetalMapper data acquired in a portion of the site amenable to vehicular towed systems (i.e. the 'Open Area'), and (2) man portable sensor data collected by the TEMTADS 2x2, BUD, and MPV in a treed section of the site (i.e. the 'Portable Area'). A small overlap of the Open and Portable Area allowed for a direct comparison of the MetalMapper and portable EMI sensors.

本刊以七大战略性新兴产业——节能环保、新一代信息技术、生物、高端装备制造、新能源、新材料、新能源汽车为研究重点，关注国家高层和各部委的动态，剖析国家和地方的新兴产业政策。本刊设有政策导读、领导讲话、七大战略性新兴产业本周国内外行业动态和重点企业新闻、投资专题四大板块，能够实时监测新兴产业和重点企业动态，把握新兴产业发展方向，研究发展重点，寻求发展机遇。