Nanotextured superhydrophobic micromesh

A superhydrophobic micromesh covered with nanoprotrusions has been introduced and its applicability to a waterproof mobile phone speaker has been evaluated. The nanotextured superhydrophobic micromesh showed excellent water repellency, self-cleaning and waterproofing performances. In a waterproof speaker test using the fabricated nanotextured micromesh, the micromesh did not lose its waterproof function at 2 m water depth and did not form a remnant water film after being removed from the water. The packaged speaker showed almost the same sound quality before and after dipping at a 2 m water depth. These results demonstrate that the superhydrophobic nanotextured micromesh could be directly applicable for various products that need to resist water penetration, yet allow the transmission of gases and sound/light waves.     

Autonomous topological modeling of a home environment and topological localization using a sonar grid map

This paper presents a method of autonomous topological modeling and localization in a home environment using only low-cost sonar sensors. The topological model is extracted from a grid map using cell decomposition and normalized graph cut. The autonomous topological modeling involves the incremental extraction of a subregion without predefining the number of subregions. A method of topological localization based on this topological model is proposed wherein a current local grid map is compared with the original grid map. The localization is accomplished by obtaining a node probability from a relative motion model and rotational invariant grid-map matching. The proposed method extracts a well-structured topological model of the environment, and the localization provides reliable node probability even when presented with sparse and uncertain sonar data. Experimental results demonstrate the performance of the proposed topological modeling and localization in a real home environment.     

BSPNN: boosted subspace probabilistic neural network for email security

In the modern age of Internet connectivity, advanced information systems have accumulated huge volumes of data. Such fast growing, tremendous amount of data, collected and stored in large databases has far exceeded our human ability to comprehend without proper tools. There has been a great deal of research conducted to explore the potential applications of Machine Learning technologies in Security Informatics. This article studies the Network Security Detection problems in which predictive models are constructed to detect network security breaches such as spamming. Due to overwhelming volume of data, complexity and dynamics of computer networks and evolving cyber threats, current security systems suffer limited performance with low detection accuracy and high number of false alarms. To address such performance issues, a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), has been proposed which combines a Radial Basis Function Neural Network with an innovative diversity-based ensemble learning framework. Extensive empirical analyses suggested that BSPNN achieved high detection accuracy with relatively small computational complexity compared with other conventional detection methods.     

Preparation of bao-pbo-nd2o3-tio2 powders by hydrothermal synthesis

Homogeneous and nano-sized BPNT [(Ba_1-xPb_x)Nd₂Ti₅O₁₄] powders were prepared under various hydrothermal conditions. Crystallinity and homogeneity of the synthetic powders were investigated. The microwave dielectric properties of the filters prepared with hydrothermal powders were compared with those of the filters prepared with conventional powders. The microwave dielectric properties of the filter prepared with the hydrothermal powders were also better than those of the filter manufactured with the conventional powders. The dielectric constant, quality constant and temperature coefficient of resonance frequency of hydrothermally prepared filter under optimum condition and measured at 3.5 GHz around were about 93, 6067 and 0 ppm/°C, respectively.     

Localizing slab identification numbers in factory scene images

This paper deals with algorithms for text localization and character segmentation in images for process automation in the steel-making industry. Each character which comprises slab identification numbers may be corrupted severely before it is captured by network cameras. Therefore, proper processing is required to localize the target texts successfully. In this paper, we propose (1) a method to evaluate the closeness of an edge patch to the form of a closed contour, (2) an edge inspection method to determine character colors and estimate font thickness, and (3) three reasonable binarization methods to increase the performance of the algorithm for the detection of the left and right boundaries of the text rectangle. The experimental results show that the proposed algorithms are reliable.     

Challenges of Raman Amplification

Raman amplifiers are often regarded as a typical example of technologies rapidly developed in the midst of turmoil created by the so-called wavelength division multiplexing (WDM) bubble. Indeed, Raman amplifiers turned out to be technically very attractive in all the aspects of capacity, reach, and bit rate. Even though Raman amplifiers are actually being deployed into systems in commercial service, the practical issues, such as cost, reliability and safety, are yet to be further discussed, particularly for the configuration of distributed amplification. After summarizing the advantages of Raman amplification and reviewing pump laser technologies, this paper will highlight ongoing efforts on practical issues, which include reliability and safety issues of fiber under high-power operations. Finally, it is concluded that by overcoming the above-mentioned practical issues, Raman amplification will stay as a key technology for future optical communications because of its compelling unique advantages.     

Dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing

The dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing (ECAP) was investigated in this study. Dynamic torsional tests, using a torsional Kolsky bar, were conducted on four steel specimens, two of which were annealed at 480 °C after ECAP, and then the test data were compared in terms of microstructures, tensile properties, and adiabatic shear-band formation. The equal-channel angular pressed specimen consisted of very fine, equiaxed grains of 0.2 to 0.3 μm in size, which were slightly coarsened after annealing. The dynamic torsional test results indicated that maximum shear stress decreased with increasing annealing time, whereas fracture shear strain increased. Some adiabatic shear bands were observed at the gage center of the dynamically deformed torsional specimen. Their width was smaller in the equal-channel angular pressed specimen than in the 1-hour-annealed specimen, but they were not found in the 24-hour-annealed specimen. Ultrafine, equiaxed grains of 0.05 to 0.2 μm in size were formed inside the adiabatic shear band, and their boundaries had characteristics of high-angle grain boundaries. These phenomena were explained by dynamic recrystallization due to a highly localized plastic strain and temperature rise during dynamic deformation.     

Recursive nonlinear observer design: beyond the uniform observability

We propose a recursive design scheme of a state observer for multiple-input-multiple-output, partly lower triangular nonlinear systems. The design begins from the subdynamics far from the output and propagates to the subdynamics close to the output, recalling the backstepping scheme for nonlinear control. The proposed class of systems is fairly general since it includes nonuniformly observable and/or detectable multioutput systems. Error convergence to zero is proved assuming boundedness of inputs a posteriori (i.e., after the design), which is preferable whereas most results in the literature assume the boundedness; a priori (i.e., before the design). A global observer is proposed with the global Lipschitz condition of the system, but without any restriction on the size of Lipschitz coefficient. The Lipschitz condition can be removed when a semiglobal observer is of interest.     

Development of a prototype customer-oriented virtual factory system

Current Computer integrated manufacturing/Enterprise Resource Planning (CIM/ERP) systems require harmony and communication between humans and facilities. A user’s preferences should also be considered in CIM/ERP systems. Virtual factory (VF), also known as virtual manufacturing (VM), systems can fulfill the requirements of current CIM/ERP systems. A VF system simulates virtual production in a virtual factory environment on the computer system which allows optimization prior to going into production. In this paper, we defined a VF system as a pre-analyzing system for designing, engineering and manufacturing a product in the enterprise system of the real world. The objective of this paper is to design a VF system and to develop a prototype system that the customer can participate in and be satisfied with. We selected a telephone as a sample product for the VF system. The VF system consists of four subsystems: virtual product ordering, design, manufacturing, and CIM/ERP interface. The prototype system aims to develop a virtual product ordering and design system.