Reuse of construction waste: performance under repeated loading

The use of recycled aggregates has increased greatly over the last decade owing to enhanced environmental sensitivities. The level of performance required by such materials is dependent upon the applications for which they are used. Many recycled construction wastes have adequate shear strength in relation to various geotechnical applications. However, a possible drawback of these materials is the risk of crushing during repeated loading. The work reported in this paper examined two waste materials: crushed concrete and building debris, both regarded as construction wastes. Tests were also performed on traditionally used crushed rock, in this case basalt. The materials were subjected to repeated loading in a large direct shear apparatus. The amount of crushing was quantified by performing particle size analysis of the tested material. The results have shown that both recycled construction wastes were susceptible to particle crushing. The amount of crushing was influenced by both the vertical pressure and the number of loading cycles. This leads to a marked decrease in peak friction angle

Query cost estimation through remote system contention states analysis over the Internet

Query processing over the Internet involving autonomous data sources is a major task in data integration. It requires the estimated costs of possible queries in order to select the best one that has the minimum cost. In this context, the cost of a query is affected by three factors: network congestion, server contention state, and complexity of the query. In this paper, we study the effects of both the network congestion and server contention state on the cost of a query. We refer to these two factors together as system contention states. We present a new approach to determining the system contention states by clustering the costs of a sample query. For each system contention state, we construct two cost formulas for unary and join queries respectively using the multiple regression process. When a new query is submitted, its system contention state is estimated first using either the time slides method or the statistical method. The cost of the query is then calculated using the corresponding cost formulas. The estimated cost of the query is further adjusted to improve its accuracy. Our experiments show that our methods can produce quite accurate cost estimates of the submitted queries to remote data sources over the Internet.

Ionic Liquid-Based Routes to Conversion or Reuse of Recycled Ammonium Perchlorate

New, potentially green, and efficient synthetic routes for the remediation and/or re-use of perchlorate-based energetic materials have been developed. Four simple organic imidazolium- and phosphonium-based perchlorate salts/ionic liquids have been synthesized by simple, inexpensive, and nonhazardous methods, using ammonium perchlorate as the perchlorate source. By appropriate choice of the cation, perchlorate can be incorporated into an ionic liquid which serves as its own electrolyte for the electrochemical reduction of the perchlorate anion, allowing for the regeneration of the chloride-based parent ionic liquid. The electrochemical degradation of the hazardous perchlorate ion and its conversion to harmless chloride during electrolysis was studied using IR and Cl-35 NMR spectroscopies.

Web Data Extraction from Query Result Pages Based on Visual and Content Features

A rapidly increasing number of Web databases are now become accessible via
their HTML form-based query interfaces. Query result pages are dynamically generated
in response to user queries, which encode structured data and are displayed for human
use. Query result pages usually contain other types of information in addition to query
results, e.g., advertisements, navigation bar etc. The problem of extracting structured data
from query result pages is critical for web data integration applications, such as comparison
shopping, meta-search engines etc, and has been intensively studied. A number of approaches
have been proposed. As the structures of Web pages become more and more complex, the
existing approaches start to fail, and most of them do not remove irrelevant contents which
may a®ect the accuracy of data record extraction. We propose an automated approach for
Web data extraction. First, it makes use of visual features and query terms to identify data
sections and extracts data records in these sections. We also represent several content and
visual features of visual blocks in a data section, and use them to ¯lter out noisy blocks.
Second, it measures similarity between data items in di®erent data records based on their
visual and content features, and aligns them into di®erent groups so that the data in the
same group have the same semantics. The results of our experiments with a large set of
Web query result pages in di®erent domains show that our proposed approaches are highly
e®ective.

Adaptive Dialogue Strategy Selection through Imprecise Probabilistic Query Answering

In a human-computer dialogue system, the dialogue strategy can range from very restrictive to highly flexible. Each specific dialogue style has its pros and cons and a dialogue system needs to select the most appropriate style for a given user. During the course of interaction, the dialogue style can change based on a user’s response and the system observation of the user. This allows a dialogue system to understand a user better and provide a more suitable way of communication. Since measures of the quality of the user’s interaction with the system can be incomplete and uncertain, frameworks for reasoning with uncertain and incomplete information can help the system make better decisions when it chooses a dialogue strategy. In this paper, we investigate how to select a dialogue strategy based on aggregating the factors detected during the interaction with the user. For this purpose, we use probabilistic logic programming (PLP) to model probabilistic knowledge about how these factors will affect the degree of freedom of a dialogue. When a dialogue system needs to know which strategy is more suitable, an appropriate query can be executed against the PLP and a probabilistic solution with a degree of satisfaction is returned. The degree of satisfaction reveals how much the system can trust the probability attached to the solution.

Extracting Query Interfaces Based on Form Structures and Semantic Similarity

Web databases are now pervasive. Such a database can be accessed via its query interface (usually HTML query form) only. Extracting Web query interfaces is a critical step in data integration across multiple Web databases, which creates a formal representation of a query form by extracting a set of query conditions in it. This paper presents a novel approach to extracting Web query interfaces. In this approach, a generic set of query condition rules are created to define query conditions that are semantically equivalent to SQL search conditions. Query condition rules represent the semantic roles that labels and form elements play in query conditions, and how they are hierarchically grouped into constructs of query conditions. To group labels and form elements in a query form, we explore both their structural proximity in the hierarchy of structures in the query form, which is captured by a tree of nested tags in the HTML codes of the form, and their semantic similarity, which is captured by various short texts used in labels, form elements and their properties. We have implemented the proposed approach and our experimental results show that the approach is highly effective.

WIQ:Work-intensive query scheduling for in-memory database systems

We propose a novel admission control policy for database queries. Our methodology uses system measurements of CPU utilization and query backlogs to determine interference between queries in execution on the same database server. Query interference may arise due to the concurrent access of hardware and software resources and can affect performance in positive and negative ways. Specifically our admission control considers the mix of jobs in service and prioritizes the query classes consuming CPU resources more efficiently. The policy ignores I/O subsystems and is therefore highly appropriate for in-memory databases. We validate our approach in trace-driven simulation and show performance increases of query slowdowns and throughputs compared to first-come first-served and shortest expected processing time first scheduling. Simulation experiments are parameterized from system traces of a SAP HANA in-memory database installation with TPC-H type workloads. © 2012 IEEE.