An improved residual frequency offset estimation scheme for OFDM based WLAN systems

Coarse frequency offset estimate and tracking of residual frequency offset are two crucial stages for frequency synchronization in OFDM based WLAN systems. An improved frequency offset estimation scheme is proposed for tracking residual offset. The estimation scheme is dependent on the position of an OFDM symbol in a frame.     

On burst rescheduling in OBS networks with partial wavelength conversion capability

The core nodes in an optical burst switching (OBS) network are normally equipped with wavelength converters (WCs) to reduce the burst loss probability. Since WCs are expensive and still immature technologically, it is desirable to reduce the number of WCs in the network and to have partial wavelength conversion capability at the core nodes. Nevertheless, a majority of algorithms in the literature are proposed under the full wavelength conversion assumption. As a result, they do not consider the burst loss caused by insufficient WCs, i.e., bursts dropped due to the unavailability of free WCs to convert them to unused wavelengths. In this paper, we demonstrate how to use burst rescheduling to decrease the burst loss due to insufficient WCs and hence cut down on the overall burst loss probability in OBS networks. Two burst rescheduling algorithms are proposed. Their effectiveness in reducing the overall burst loss probability is verified through simulation experiments.     

Concept-based near-duplicate video clip detection for novelty re-ranking of web video search results

State-of-the-art near-duplicate video clip (NDVC) detection for novelty re-ranking uses non-semantic low-level features (color/texture) to detect and eliminate “content-based NDVC” and increases content level novelty in the top results. However, humans may perceive a video as near duplicate from a semantic perspective as well. In this paper, we propose concept-based near-duplicate video clip (CBNDVC) detection technique for novelty re-ranking. We identify “semantic NDVC”, making use of the semantic features (events/concepts) and re-rank the top results to increase the content as well as semantic novelty. Videos are represented as a multivariate time series of confidence values of relevant concepts and thereafter discovery of CBNDVC clusters is achieved by conceptual clustering. Obtained results show higher precision and recall from the user’s perspective.     

Grounded discovery of symbols as concept–language pairs

In human designer usage, symbols have a rich semantics, grounded on experience, which permits flexible usage — e.g. design ideation is improved by meanings triggered by contrastive words. In computational usage however, symbols are syntactic tokens whose semantics is mostly left to the implementation, resulting in brittle failures in many knowledge-based systems. Here we ask if one may define symbols in computational design as {label,meaning} pairs, as opposed to merely the label. We consider three questions that must be answered to bootstrap a symbol learning process: (a) which concepts are most relevant in a given domain, (b) how to define the semantics of such symbols, and (c) how to learn labels for these so as to form a grounded symbol. We propose that relevant symbols may be discovered by learning patterns of functional viability. The stable patterns are information-conserving codes, also called chunks in cognitive science, which relate to the process of acquiring expertise in humans. Regions of a design space that contain functionally superior designs can be mapped to a lower-dimensional manifold; the inter-relations of the design variables discovered thus constitute the chunks. Using these as the initial semantics for symbols, we show how the system can acquire labels for them by communicating with human designers. We demonstrate the first steps in this process in our baby designer approach, by learning two early grounded symbols, tight and loose.     

Enablers That Help Foreign Architectural, Engineering, and Construction Firms Win Construction Contracts in China

With China’s fast economic growth and entry into the World Trade Organization (WTO), more foreign architectural, engineering, and construction (AEC) firms are expected to venture into this huge and attractive market. This paper explores the important strategies to help foreign AEC firms clinch construction projects in China. Using a questionnaire survey approach complemented by in-depth interviews, it was found that firms need to pay more attention to the market and working conditions in China and to strengthen their own capabilities. To win projects in China, foreign AEC firms should also be able to offer project financing services. The findings are useful to foreign AEC firms because it may help them win projects in the Chinese construction industry.     

Video arrays for real-time tracking of person,head, and face in an intelligent room

Real-time three-dimensional tracking of people is an important requirement for a growing number of applications. In this paper we describe two trackers; both of them use a network of video cameras for person tracking. These trackers are called a rectilinear video array tracker (R-VAT) and an omnidirectional video array tracker (O-VAT), indicating the two different ways of video capture. The specific objectives of this paper are twofold: (i) to present a systematic comparison of these two trackers using an extensive series of experiments conducted in an `intelligent' room; (ii) to develop a real-time system for tracking the head and face of a person, as an extension of the O-VAT approach. The comparative research indicates that O-VAT is more robust to the number of people, less complex and runs faster, needs manual camera calibration, and the integrated omnidirectional video network has better reconfigurability. The person head and face tracker study shows that such a system can serve as a most effective input stage for face recognition and facial expression analysis modules.     

Editorial

Machine Vision and Applications -     

A Scalable Asynchronous Cache Consistency Scheme (SACCS) for mobile environments

In the literature, there exit two types of cache consistency maintenance algorithms for mobile computing environments: stateless and stateful. In a stateless approach, the server is unaware of the cache contents at a mobile user (MU). Even though stateless approaches employ simple database management schemes, they lack scalability and ability to support user disconnectedness and mobility. On the other hand, a stateful approach is scalable for large database systems at the cost of nontrivial overhead due to server database management. We propose a novel algorithm, called Scalable Asynchronous Cache Consistency Scheme (SACCS), which inherits the positive features of both stateless and stateful approaches. SACCS provides a weak cache consistency for unreliable communication (e.g., wireless mobile) environments with small stale cache hit probability. It is also a highly scalable algorithm with minimum database management overhead. The properties are accomplished through the use of flag bits at the server cache (SC) and MU cache (MUC), an identifier (ID) in MUC for each entry after its invalidation, and estimated time-to-live (TTL) for each cached entry, as well as rendering of all valid entries of MUC to uncertain state when an MU wakes up. The stale cache hit probability is analyzed and also simulated under the Rayleigh fading model of error-prone wireless channels. Comprehensive simulation results show that the performance of SACCS is superior to those of other existing stateful and stateless algorithms in both single and multicell mobile environments.     

Performance analysis of tool electrode prepared through laser sintering process during electrical discharge machining of titanium

The International Journal of Advanced Manufacturing Technology - It is of great significance for intelligent manufacturing to study condition monitoring and diagnosis methods to realize early...