Effects of User Request Patterns on a Multimedia Delivery System

Because of their size, service times, and drain on server resources, multimedia objects require specialized replication systems in order to meet demand and ensure content availability. We present a novel method for creating replication systems where the replicated objects' sizes and/or per-object service times are large. Such replication systems are well-suited to delivering multimedia objects on the Internet. Assuming that user request patterns to the system are known, we show how to create replication systems that distribute read load to servers in proportion to their contribution to system capacity and experimentally show the positive load distribution properties of such systems. However, when user request patterns differ from what the system was designed for, system performance will be affected. Therefore, we also report on results that reveal (i) how server loads are affected and (ii) the impact two system design parameters (indicators of a system's load distribution qualities) have on server load when request patterns differ from that for which a system was designed.     

Role of Insulation Effectiveness on Fire Resistance of Steel Structures under Extreme Loading Events

Fire performance of steel structures is highly dependent on the effectiveness of applied fire insulation. However, insulation materials are susceptible to damage under extreme loading events. A state-of-the-art review on the role of insulation damage on fire resistance of steel structures is presented. Parametric studies on a six-story steel-framed building were carried out to illustrate the effect of insulation damage on fire response of a steel structure. In the analysis, realistic fire scenarios, loading, and failure criteria were taken into consideration. Analysis results indicate that the fire resistance of a steel-framed structure is significantly influenced by the extent of insulation loss, type of fire scenario, and level of lateral load. Insulation damage causes faster deterioration in the structural response of framed buildings under the combined effect of fire and lateral loading. The need for accounting for any insulation damage, arising under extreme loading events, in fire design of steel-framed structures is highlighted, and a performance-based design strategy incorporating fire resistance analysis is discussed.     

Pattern identification in dynamical systems via symbolic time series analysis

This paper presents symbolic time series analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the time series patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from raw data through partitioning of the data space. The maximum entropy method of partitioning is extended to multi-dimensional space. The resulting symbol sequences, generated from time series data, are used to model the dynamical information as finite state automata and the patterns are represented by the stationary state probability distributions. A novel procedure for determining the structure of the finite state automata, based on entropy rate, is introduced. The diversity among the observed patterns is quantified by a suitable measure. The efficacy of the STSA technique for pattern identification is demonstrated via laboratory experimentation on nonlinear systems.     

Regularized nonnegative shared subspace learning

Joint modeling of related data sources has the potential to improve various data mining tasks such as transfer learning, multitask clustering, information retrieval etc. However, diversity among various data sources might outweigh the advantages of the joint modeling, and thus may result in performance degradations. To this end, we propose a regularized shared subspace learning framework, which can exploit the mutual strengths of related data sources while being immune to the effects of the variabilities of each source. This is achieved by further imposing a mutual orthogonality constraint on the constituent subspaces which segregates the common patterns from the source specific patterns, and thus, avoids performance degradations. Our approach is rooted in nonnegative matrix factorization and extends it further to enable joint analysis of related data sources. Experiments performed using three real world data sets for both retrieval and clustering applications demonstrate the benefits of regularization and validate the effectiveness of the model. Our proposed solution provides a formal framework appropriate for jointly analyzing related data sources and therefore, it is applicable to a wider context in data mining.     

Detection of cross-channel anomalies

The data deluge has created a great challenge for data mining applications wherein the rare topics of interest are often buried in the flood of major headlines. We identify and formulate a novel problem: cross-channel anomaly detection from multiple data channels. Cross-channel anomalies are common among the individual channel anomalies and are often portent of significant events. Central to this new problem is a development of theoretical foundation and methodology. Using the spectral approach, we propose a two-stage detection method: anomaly detection at a single-channel level, followed by the detection of cross-channel anomalies from the amalgamation of single-channel anomalies. We also derive the extension of the proposed detection method to an online settings, which automatically adapts to changes in the data over time at low computational complexity using incremental algorithms. Our mathematical analysis shows that our method is likely to reduce the false alarm rate by establishing theoretical results on the reduction of an impurity index. We demonstrate our method in two applications: document understanding with multiple text corpora and detection of repeated anomalies in large-scale video surveillance. The experimental results consistently demonstrate the superior performance of our method compared with related state-of-art methods, including the one-class SVM and principal component pursuit. In addition, our framework can be deployed in a decentralized manner, lending itself for large-scale data stream analysis.     

Reuse potential of municipal wastewater treatment facility effluents for sustainable water resource management in Ulsan,Korea

Effluent qualities of five municipal wastewater treatment facilities (MWWTFs) in Ulsan were evaluated to examine their reuse potential. Effluent from Yongyeon (Y) MWWTF, Onsan (O) MWWTF and Bangeojin (B) MWWTFs can be used as cooling water without further treatment. As evident from Langelier saturation index and Ryzner index values, reuse of treated effluent from OMWWTF and BMWWTFs is recommended by controlling the pH to reduce the scale-forming potential of effluent. However, effluents from these MWWTFs need additional treatment to remove residual dissolved constituents before reuse as boiler water. Besides, effluent from Hoiya (H) MWWTF and Unyang (U) MWWTFs can be reused for agricultural irrigation without any additional treatment. Based on the scientific results obtained from this investigation, proper application of technology and promotion of public awareness to change the traditional mindset for treated effluent reuse could immensely contribute towards conserving local water resources and addressing global environmental problems on a regional basis.     

The effects of xanthan and guar gums on staling of gluten-free rice cakes baked in different ovens

The objective of this study was to determine the effects of different concentrations of xanthan and guar gums and their blends on staling of gluten-free rice cakes baked in microwave-infrared combination oven (MW–IR) and to compare the cakes with conventionally baked ones. Gums were added at concentrations of 0.3% and 1.0%. For preparation of gum blend, 0.5% xanthan gum was mixed with 0.5% guar gum. In order to understand the staling behaviour of cakes, cakes were stored at 22 ± 2 °C for 120 h. Xanthan-guar gum blend decreased hardness, weight loss, retrogradation enthalpy and the change in setback viscosity values of cakes during storage for both types of ovens as compared to control formulation. It was found that oven type was a significant factor in affecting staling parameters of gluten-free cakes.     

Performance of insulated FRP-strengthened concrete flexural members under fire conditions

This paper presents the results of fire resistance tests on carbon fiber-reinforced polymer (CFRP) strengthened concrete flexural members, i.e., T-beams and slabs. The strengthened members were protected with fire insulation and tested under the combined effects of thermal and structural loading. The variables considered in the tests include the applied load level, extent of strengthening, and thickness of the fire insulation applied to the beams and slabs. Furthermore, a previously developed numerical model was validated against the data generated from the fire tests; subsequently, it was utilized to undertake a case study. Results from fire tests and numerical studies indicate that owing to the protection provided by the fire insulation, the insulated CFRP-strengthened beams and slabs can withstand four and three hours of standard fire exposure, respectively, under service load conditions. The insulation layer impedes the temperature rise in the member; therefore, the CFRP–concrete composite action remains active for a longer duration and the steel reinforcement temperature remains below 400°C, which in turn enhances the capacity of the beams and slabs.     

Numerical and experimental study of a shell and tube heat exchanger for different baffles

In the present work, the shell and tube heat exchanger (STHX) is designed based on The Tubular Exchanger Manufacturers Association standards with hot fluid (water) flowing on the shell side and cold fluid on the tube side. A comparison is made between the Nusselt number and friction factor obtained from numerical and experimental results of segmental baffles (SBs) and helical baffles (HB) with different baffle inclinations. The results show that SB provided a higher Colburn factor (j_s) when compared with HBs STHXs (20°, 30°, 40°, and 50°), but shell side pressure drop is lower for 40° HBs STHXs for the same shell side fluid flow rates.     

Smart utilization of renewable energy sources in a microgrid system integrated with plug‐in hybrid electric vehicles

Mass roll‐out of plug‐in hybrid electric vehicles (PHEVs) and significant penetration of renewable energy sources in distribution system play a major role in delivering low carbon environment. However, placing and utilizing these units randomly result in overloading, increased power loss, and reduced voltage profile. This paper responds to these technical challenges by using a strategic placement method for locating the distributed generation (DG) and the charging station (CS) of PHEVs in a multi‐zone distribution system. For simultaneously scheduling of these units in each zone, the smart energy management framework is proposed in this paper. Apart from usual energy management constraints, this paper also incorporates the real‐time constraints involving the capacity of PHEV batteries, the mobility pattern, and the power level of the charging infrastructure. The simulation studies are carried out for each hour of a day. To cope with this time constraint execution, particle swarm optimization algorithm‐based approach is used. The proposed framework is tested in IEEE 33 and IEEE 69 bus radial distribution system. The obtained results imply that the presented energy management framework provides maximum profits for the vehicle owner, and meanwhile it fulfills preferences of the user in each zone simultaneously.