Scalable semantic brokering over dynamic heterogeneous data sources in InfoSleuth/spl trade/

InfoSleuth is an agent-based system for information discovery and retrieval in a dynamic, open environment. Brokering in InfoSleuth is a matchmaking process, recommending agents that provide services to agents requesting services. This paper discusses InfoSleuth's distributed multibroker design and implementation. InfoSleuth's brokering function combines reasoning over both the syntax and semantics of agents in the domain. This means the broker must reason over explicitly advertised information about agent capabilities to determine which agent can best provide the requested services. Robustness and scalability issues dictate that brokering must be distributable across collaborating agents. Our multibroker design is a peer-to-peer system that requires brokers to advertise to and receive advertisements from other brokers. Brokers collaborate during matchmaking to give a collective response to requests initiated by nonbroker agents. This results in a robust, scalable brokering system.     

Multi-label classification via learning a unified object-label graph with sparse representation

Automatic annotation is an essential technique for effectively handling and organizing Web objects (e.g., Web pages), which have experienced an unprecedented growth over the last few years. Automatic annotation is usually formulated as a multi-label classification problem. Unfortunately, labeled data are often time-consuming and expensive to obtain. Web data also accommodate much richer feature space. This calls for new semi-supervised approaches that are less demanding on labeled data to be effective in classification. In this paper, we propose a graph-based semi-supervised learning approach that leverages random walks and ? ₁ sparse reconstruction on a mixed object-label graph with both attribute and structure information for effective multi-label classification. The mixed graph contains an object-affinity subgraph, a label-correlation subgraph, and object-label edges with adaptive weight assignments indicating the assignment relationships. The object-affinity subgraph is constructed using ? ₁ sparse graph reconstruction with extracted structural meta-text, while the label-correlation subgraph captures pairwise correlations among labels via linear combination of their co-occurrence similarity and kernel-based similarity. A random walk with adaptive weight assignment is then performed on the constructed mixed graph to infer probabilistic assignment relationships between labels and objects. Extensive experiments on real Yahoo! Web datasets demonstrate the effectiveness of our approach.     

Dynamic composition and optimization of Web services

Process-based composition of Web services has recently gained significant momentum for the implementation of inter-organizational business collaborations. In this approach, individual Web services are choreographed into composite Web services whose integration logics are expressed as composition schema. In this paper, we present a goal-directed composition framework to support on-demand business processes. Composition schemas are generated incrementally by a rule inference mechanism based on a set of domain-specific business rules enriched with contextual information. In situations where multiple composition schemas can achieve the same goal, we must first select the best composition schema, wherein the best schema is selected based on the combination of its estimated execution quality and schema quality. By coupling the dynamic schema creation and quality-driven selection strategy in one single framework, we ensure that the generated composite service comply with business rules when being adapted and optimized.     

Modeling and Retrieval of Moving Objects

This paper presents a symbolic formalism for modeling and retrieving video data via the moving objects contained in the video images. The model integrates the representations of individual moving objects in a scene with the time-varying relationships between them by incorporating both the notions of object tracks and temporal sequences of PIRs (projection interval relationships). The model is supported by a set of operations which form the basis of a moving object algebra. This algebra allows one to retrieve scenes and information from scenes by specifying both spatial and temporal properties of the objects involved. It also provides operations to create new scenes from existing ones. A prototype implementation is described which allows queries to be specified either via an animation sketch or using the moving object algebra.     

Optimal training signals for MIMO OFDM channel estimation

This paper presents general classes of optimal training signals for the estimation of frequency-selective channels in MIMO OFDM systems. Basic properties of the discrete Fourier transform are used to derive the optimal training signals which minimize the channel estimation mean square error. Both single and multiple OFDM training symbols are considered. Several optimal pilot tone allocations across the transmit antennas are presented and classified as frequency-division multiplexing, time-division multiplexing, code-division multiplexing in the frequency-domain, code-division multiplexing in the time-domain, and combinations thereof. All existing optimal training signals in the literature are special cases of the presented optimal training signals and our designs can be applied to pilot-only schemes as well as pilot-data-multiplexed schemes.     

A study on physical and mechanical properties for soft to firm clays in Yangon area – Properties of clays deposit at the sedimentary basins in Myanmar

Recently, a great deal of foreign investment has been entered into construction of the social infrastructure of Myanmar. Many construction projects are therefore on-going, and these are especially planned in the Yangon area. While these construction booms are increasing, existing studies on the geotechnical problems in the Yangon area such as problematic soils like soft clays are limited at present. Information on soil properties has also not been shared and has been confined to individual projects. In this paper, the boring and laboratory tests carried out in the Yangon area are selected and focused upon among the tests carried out in Myanmar. Laboratory test results for clay deposits in the Yangon area are analyzed and the differences in soil properties between different sedimentary basins and sub-areas divided by the Tertiary sediment ridge that runs from north to south at the center of Yangon are clarified together with a comparison to the clays found in other countries, which have been previously investigated.     

PIC-based iterative SDR detector for OFDM systems in doubly-selective fading channels

OFDM data detection in doubly-selective fading channels requires high complexity due to intercarrier interferences (ICI). We present a low-complexity receiver consisting of a semidefinite relaxation (SDR) based detector and parallel interference cancellation (PIC). The entire band is divided into clusters of adjacent subcarriers. SDR is applied on each cluster while PIC tackles ICI from other clusters. An upper bound of ICI power is derived and used to omit far-away clusters in performing PIC. Finally, an adaptive detector based on PIC, PIC-based SDR and the snap-shot SNR in channel is proposed to achieve a better tradeoff between complexity and performance.     

A Complete Model for Simulating Magnitude and Phase of Emissions from a DUT Placed Inside a GTEM Cell

Since the publication of IEC 61000-4-20, the gigahertz transverse electromagnetic (GTEM) cell has gained popularity in radiated emission and immunity electromagnetic compatibility tests. Various numerical methods such as finite-difference time-domain, finite element method, and method of moments have been used to model the GTEM cell in the pursuit of getting to know the characteristic of the GTEM cell with varying degrees of verification. In this paper, the time-domain transmission line model will be used to model the GTEM cell. The advantages of this method include high accuracy and the ability to model different materials. Thus, the GTEM is realistically modeled including radio absorbing material (RAM) and lumped terminations. In addition, the model of a realistic device under test (DUT) was also included in the GTEM model. The DUT consists of a standard sized box with an aperture, placed in different orientations inside the GTEM for power and phase measurements. The particular features of this paper are: 1) the inclusion of a realistic numerical model of RAM, 2) the inclusion of a realistic DUT model, 3) systematic verification of the model against measurements, and 4) the method of phase measurement in a GTEM cell. Good agreement between the experimental results and simulations is obtained.     

Prevalence and demographic determinants of metronidazole resistance by Helicobacter pylori in a large cosmopolitan cohort of Australian dyspeptic patients

1. Heterozygous naked neck birds were raised under natural spring (average 21.2 degrees C) and summer temperatures (average 27.1 degrees C) to investigate the influence of dietary energy on broiler performance, carcase yield and nutrient composition of breast meat. 2. Birds were fed on a low energy diet of 12.12 MJ ME/kg, a medium energy diet of 12.96 MJ ME/kg and a high energy diet of 13.79 MJ ME/kg with 2 protein concentrations per energy treatment, 230 and 200 g/kg, from 0 to 3 and 3 to 7 weeks of age, respectively. 3. Summer rearing resulted in a decrease in body weight, body weight gain, carcase weight and carcase part yields of birds. 4. Increasing dietary energy from 12.12 to 13.79 MJ ME/kg increased body weight at 3 and 7 weeks, body weight gains from 0 to 3 and 3 to 7 weeks, carcase weights and relative abdominal fat weights of birds in a linear manner. There was no effect of dietary energy on the nutrient composition of breast meat. 5. It was concluded that there was no differences in dietary energy requirements of heterozygous naked neck birds when grown under natural optimum (21.2 degrees C) and summer temperatures (27.1 degrees C).