A CPM-Based Construction Quality Inspection and Decision-Aid System

This article adopted the concept of decision support to establish a CPM-based construction quality inspection and decision-aid system (CQIDS) to improve ineffective field quality inspection processes. The system consists of two main subsystems: the database subsystem and the decision subsystem. The database subsystem contains information about quality specifications, shop drawings, checklists, and corrective actions that comprises a multimedia network. The decision subsystem contains statistical algorithms to facilitate in situ quality data analysis. Moreover, in order to execute quality management in a timely fashion, quality management timetables are generated automatically from the CQIDS and sent to field quality supervisors by integrating quality management activities within the project's own CPM network.     

Social factors, allergen, endotoxin, and dust mass in mattress

Indoor environment has been associated with allergic disease. Further, it has been observed that the prevalences of allergic sensitization are different in different social groups. We therefore investigated the association between socioeconomic status (SES) and indoor bio-contaminants. House dust samples were collected from parents' and infants' mattress from 2166 families in Munich (62.2%) and Leipzig (37.8%), Germany. Major mite allergen Der p 1 and Der f 1, cat allergen Fel d 1, and endotoxin were extracted and quantified. Parental educational level and family equivalent income were used independently as socioeconomic indicators. Indoor endotoxin, mite allergen Der p 1, and the amount of sampled dust were not associated with the social factors. Mite allergen Der f 1 was slightly associated by family SES but without a consistent pattern. In families who are not cat owners, however, a negative association between the amount of cat allergen and family SES were observed. The observed negative association between cat allergen loads and concentrations in mattress and family SES in non-cat owners' homes indicated that community is an important source of cat allergen exposure. PRACTICAL IMPLICATIONS: The study indicated that community is a major source of cat allergen exposure especially in communities of low SES.     

Code-modulated path-sharing multi-antenna receivers: theory and analysis

Conventional multi-antenna receiver front-ends require multiple RF/baseband chains and analog-to-digital converters (ADC). This increases power consumption and chip area substantially. In this letter, we introduce a new Code-Modulated Path-Sharing Multi-Antenna (CPMA) receiver architecture suitable for any multi-antenna scheme including spatial multiplexing, spatial diversity, and beamforming. The receiver uses code modulation to distinguish the antenna signals before combining them in the analog domain. The combined signal propagates through shared-path blocks and all the original signals are later recovered in the digital domain for further processing. Due to the spread spectrum nature of code modulation, a larger bandwidth is needed for the blocks in the shared path. To alleviate this effect, the use of non-orthogonal coding is examined. An effective channel matrix is derived and the system capacity is evaluated in terms of the cross-correlation between signature codes. Implementation and code selection issues are discussed. Analysis and simulation results indicate that by properly selecting non-orthogonal code sets, the spreading factor, and therefore, the overall analog signal bandwidth is reduced while incurring minimal performance degradation.     

Improvement of CSO/CTB performances employing up-converted and polarization modulation techniques

A two-wavelength wavelength-division multiplexing (WDM) community antenna television (CATV) transport system that employed up-converted and polarization modulation techniques to reduce the composite second-order (CSO) distortion and optical nonlinearities is proposed and demonstrated. In contrast to a two-wavelength WDM CATV transport system using the intensity modulation technique, good performances of CSO and composite triple beat were obtained, accompanied by acceptable carrier-to-noise ratio value in our proposed system over a 100-km single-mode fiber transmission.     

Influence of number of simulated particles on DSMC modeling of micro-scale Rayleigh-Bénard flows

Two-dimensional micro-scale Rayleigh-Bénard flows are investigated numerically using direct simulation Monte Carlo method. An enclosure of length-to-height aspect ratio of AS = 4 is taken to explore the influence of initial setting of simulated molecules. The simulation domain is divided into 81 × 21 sampling cells and the range of Rayleigh number from 3000 to 10 000 corresponds to the convection state. Cases of 8, 10, 12, 14, 16 and 24 simulated particles in each collision cell are examined. It is shown that flow patterns with three-, four- or five-roll modes may appear depending on the number of simulated particles.     

Backhaul and Routing Assignments with End-to-End QoS Constraints for Wireless Mesh Networks

In scalable last-mile broadband networks such as wireless mesh networks (WMNs), quality-of-service (QoS) concerns are vital to multimedia applications such as video-conferencing and voice over IP (VoIP). Crucial decisions involve the number of backhauls that are to be deployed as well as the optimal assignment of paths and bandwidths. We focus on cost effectiveness and QoS requirements to develop a solution based on Lagrangean Relaxation and the subgradient method. Our approach satisfies QoS demands and minimizes costs more effectively than general algorithms, as demonstrated by our experimental results.     

Routing table partitioning for speedy packet lookups in scalable routers

Most of the high-performance routers available commercially these days equip each of their line cards (LCs) with a forwarding engine (FE) to perform table lookups locally. This work introduces and evaluates a technique for speedy packet lookups, called SPAL, in such routers. The BGP routing table under SPAL is fragmented into subsets which constitute forwarding tables for different FEs so that the number of table entries in each FE drops as the router grows. This reduction in the forwarding table size drastically lowers the amount of SRAM (e.g., L3 data cache) required in each LC to hold the trie constructed according to the prefix matching algorithm. SPAL calls for caching the lookup result of a given IP address at its home LC (denoted by LC/sub ho/, using the LR-cache), such that the result can satisfy the lookup requests for the same address from not only LC/sub ho/, but also other LCs quickly. Our trace-driven simulation reveals that SPAL leads to improved mean lookup performance by a factor of at least 2.5 (or 4.3) for a router with three (or 16) LCs, if the LR-cache contains 4K blocks. SPAL achieves this significant improvement, while greatly lowering the SRAM (i.e., the L3 data cache plus the LR-cache combined) requirement in each LC and possibly shortening the worst-case lookup time (thanks to fewer memory accesses during longest-prefix matching search) when compared with a current router without partitioning the routing table. It promises good scalability (with respect to routing table growth) and exhibits a small mean lookup time per packet. With its ability to speed up packet lookup performance while lowering overall SRAM substantially, SPAL is ideally applicable to the new generation of scalable high-performance routers.     

The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping

When students learn a new and challenging task, for which they have very limited corresponding personal or vicarious experiences to refer, it is important to understand how their self-efficacy beliefs evolve during the course of sequential lessons; how they differ in the way their general learning performance and self-efficacy influence their ratings of task-specific self-efficacy and performance; and, how such differences may result in different learning outcomes and motivations for learning. By examining a group of 66 students engaged in learning to construct good concept maps with computer software, this study revealed several important findings on these questions. Students generally tended to initially overestimate their ability to successfully carry out the required task. They also varied in the way their general self-efficacy and performance were associated with their task-specific self-efficacy and performance. And, these differences did appear to be associated with different learning outcomes and motivations for learning. These results indicate that investigating individual differences in students’ patterns of association between general and specific performance and their self-efficacy may lead to a better understanding of how students differ in their levels of motivation and outcomes when learning a new and challenging task.     

Identification of general fuzzy measures by genetic algorithmsbased on partial information

This study develops an identification procedure for general fuzzy measures using genetic algorithms. In view of the difficulty in data collection in practice, the amount of input data is simplified through a sampling procedure concerning attribute subsets, and the corresponding detail design is adapted to the partial information acquired by the procedure. A specially designed genetic algorithm is proposed for better identification, including the development of the initialization procedure, fitness function, and three genetic operations. To show the applicability of the proposed method, this study simulates a set of experimental data that are representative of several typical classes. The experimental analysis indicates that using genetic algorithms to determine general fuzzy measures can obtain satisfactory results under the framework of partial information.