Model Updating Technique Based on Modal Participation Factors for Beam Structures

This article proposes a model updating technique based on modal participation factors for a beam structure. In this model updating technique, the error functions of the dynamic characteristic differences between measurement and model are generated as the number of modes under consideration and minimized using the multiobjective optimization techniques. A modal influence factor defined by modal participation factors for each mode is presented for the selection of the best solution from among Pareto solutions. The selection rule represented in this article makes it possible to reflect the contributions of each mode on the behavior of a structure. The model is updated using natural frequencies measured in an impact hammer test of a beam structure and the validity of the updated model is confirmed by the strain responses measured from the test. It is found that the bending stiffness of the beam structure as the parameter for model updating can be identified by the proposed techniques. Furthermore, through comparing the models updated by the simple sum model updating and the technique in this research, it is verified that the proposed technique is more appropriate for the model updating.     

Ruthenium(II)‐ or Rhodium(III)‐Catalyzed Grignard‐Type Addition of Indolines and Indoles to Activated Carbonyl Compounds

The ruthenium(II)‐ or rhodium(III)‐catalyzed pyrimidinyl‐directed Grignard‐type C−H additions of N‐heterocycles with activated aldehydes and ketones are described. A cationic ruthenium catalyst and sodium acetate additive in dichloroethane as solvent were found to be optimal catalytic system for the construction of C‐7 alkylated indolines. In sharp contrast, a cationic rhodium complex allows the generation of C‐2 alkylated indoles and pyrroles as well as C‐1 alkylated carbazoles. The site‐selective C−H functionalization of these heterocyclic scaffolds could be an important asset towards the development of novel bioactive compounds.

     

Novel membrane bioreactor (MBR) coupled with a nonwoven fabric filter for household wastewater treatment

Conventional and modified membrane bioreactors (MBRs) are increasingly used in small-scale wastewater treatment. However, their widespread applications are hindered by their relatively high cost and operational complexity. In this study, we investigate a new concept of wastewater treatment using a nonwoven fabric filter bag (NFFB) as the membrane bioreactor. Activated sludge is charged in the nonwoven fabric filter bag and membrane filtration via the fabric is achieved under gravity flow without a suction pump. This study found that the biofilm layer formed inside the NFFB achieved 10 mg/L of suspended solids in the permeate within 20 min of initial operation. The dynamic biofilter layer showed good filterability and the specific membrane resistance consisted of 0.3-1.9 × 10¹² m/kg. Due to the low F/M ratio (0.04-0.10 kg BOD₅/m³/d) and the resultant low sludge yield, the reactor was operated without forming excess sludge. Although the reactor provided aerobic conditions, denitrification occurred in the biofilm layer to recover the alkalinity, thereby eliminating the need to supplement the alkalinity. This study indicates that the NFFB system provides a high potential of effective wastewater treatment with simple operation at reduced cost, and hence offer an attractive solution for widespread use in rural and sparsely populated areas.     

Meteorological effects on the levels of fecal indicator bacteria in an urban stream: A modeling approach

Gwangju Creek (GJC) in Korea, which drains a highly urbanized watershed, has suffered from substantial fecal contamination, thereby limiting the beneficial use of the water in addition to threatening public health. In this study, to quantitatively estimate the sinks and sources of fecal indicator bacteria (FIB) in GJC under varying meteorological conditions, two FIB (i.e., Escherichia coli and enterococci bacteria) were monitored hourly for 24 h periods during both wet and dry weather conditions at four sites along GJC, and the collected data was subsequently used to develop a spatiotemporal FIB prediction model. The monitoring data revealed that storm washoff and irradiational die-off by sunlight are the two key processes controlling FIB populations in wet and dry weather, respectively. FIB populations significantly increased during precipitation, with greater concentrations occurring at higher rainfall intensity. During dry weather, FIB populations decreased in the presence of sunlight in daytime but quickly recovered at nighttime due to continuous point-source inputs. In this way, the contributions of the key processes (i.e., irradiational die-off by sunlight, settling, storm washoff, and resuspension) to the FIB levels in GJC under different meteorological conditions were quantitatively estimated using the developed model. The modeling results showed that the die-off by sunlight is the major sink of FIB during the daytime in dry weather with a minor contribution from the settling process. During wet weather, storm washoff and resuspension are equally important processes that are responsible for the substantial increase of FIB populations.     

Bendable and Splitter-Integrated Optical Subassembly Based on a Flexible Optical Board

A bendable and splitter-integrated optical subassembly (OSA) is suggested as a short-distance board-to-board optical interconnection. This OSA was fabricated by simply packaging a vertical-cavity surface-emitting laser on a flexible optical board having an embedded 1 $times$ 8 optical splitter waveguide. Finally, we measured various optical characteristics of the OSA, including insertion, twist, and bending losses.      

Design of 24 GHz Radar with Subspace‐Based Digital Beam Forming for ACC Stop‐and‐Go System

For an adaptive cruise control (ACC) stop‐and‐go system in automotive applications, three radar sensors are needed because two 24 GHz short range radars are used for object detection in an adjacent lane, and one 77 GHz long‐range radar is used for object detection in the center lane. In this letter, we propose a single sensor‐based 24 GHz radar with a detection capability of up to 150 m and ±30° for an ACC stop‐and‐go system. The developed radar is highly integrated with a high gain patch antenna, four channel receivers with GaAs RF ICs, and back‐end processing board with subspace based digital beam forming algorithm.     

A Low‐Complexity 128‐Point Mixed‐Radix FFT Processor for MB‐OFDM UWB Systems

In this paper, we present a fast Fourier transform (FFT) processor with four parallel data paths for multiband orthogonal frequency‐division multiplexing ultra‐wideband systems. The proposed 128‐point FFT processor employs both a modified radix‐2⁴ algorithm and a radix‐2³ algorithm to significantly reduce the numbers of complex constant multipliers and complex booth multipliers. It also employs substructure‐sharing multiplication units instead of constant multipliers to efficiently conduct multiplication operations with only addition and shift operations. The proposed FFT processor is implemented and tested using 0.18 µm CMOS technology with a supply voltage of 1.8 V. The hardware‐ efficient 128‐point FFT processor with four data streams can support a data processing rate of up to 1 Gsample/s while consuming 112 mW. The implementation results show that the proposed 128‐point mixed‐radix FFT architecture significantly reduces the hardware cost and power consumption in comparison to existing 128‐point FFT architectures.     

Maximum Likelihood Training and Adaptation of Embedded Speech Recognizers for Mobile Environments

For the acoustic models of embedded speech recognition systems, hidden Markov models (HMMs) are usually quantized and the original full space distributions are represented by combinations of a few quantized distribution prototypes. We propose a maximum likelihood objective function to train the quantized distribution prototypes. The experimental results show that the new training algorithm and the link structure adaptation scheme for the quantized HMMs reduce the word recognition error rate by 20.0%.     

Predicting Protein Function by Frequent Functional Association Pattern Mining in Protein Interaction Networks

Predicting protein function from protein interaction networks has been challenging because of the complexity of functional relationships among proteins. Most previous function prediction methods depend on the neighborhood of or the connected paths to known proteins. However, their accuracy has been limited due to the functional inconsistency of interacting proteins. In this paper, we propose a novel approach for function prediction by identifying frequent patterns of functional associations in a protein interaction network. A set of functions that a protein performs is assigned into the corresponding node as a label. A functional association pattern is then represented as a labeled subgraph. Our frequent labeled subgraph mining algorithm efficiently searches the functional association patterns that occur frequently in the network. It iteratively increases the size of frequent patterns by one node at a time by selective joining, and simplifies the network by a priori pruning. Using the yeast protein interaction network, our algorithm found more than 1400 frequent functional association patterns. The function prediction is performed by matching the subgraph, including the unknown protein, with the frequent patterns analogous to it. By leave-one-out cross validation, we show that our approach has better performance than previous link-based methods in terms of prediction accuracy. The frequent functional association patterns generated in this study might become the foundations of advanced analysis for functional behaviors of proteins in a system level.      

Reducing Cr6+ emissions from gas tungsten arc welding using a silica precursor

Hexavalent chromium (Cr⁶⁺) emission from stainless steel welding operations poses a serious threat to worker safety and ambient air quality. In this study, tetraethyloxysilane (TEOS) was used as a silica precursor additive to welding shield gas during gas tungsten arc welding (GTAW) operations to determine the feasibility of using these chemicals for Cr⁶⁺ exposure reduction. Fume aerosol samples were analyzed for Cr⁶⁺ concentration using ion chromatography (IC) and for total Cr by inductively coupled plasma with atomic emission spectroscopy (ICP-AES).At high temperature, silica precursors are pyrolyzed to form amorphous silica (SiO₂) which can condense on the existing metal aerosols. The inert silica layer surrounding the aerosols can prevent further chromium oxidation by insulating chromium aerosols. Experimental results showed approximately 45% Cr⁶⁺ reductions when 3.0% TEOS was added to the shield gas. Nitrate concentration also decreased by 53%, indicating that reactive oxygen species were also reduced. Transmission electron microscopy (TEM) images of collected fume aerosols showed SiO₂ coating on metal particles, verifying the proposed mechanism.