Boron distribution in a low-alloy steel

Boron distribution in a low-alloy steel (15B26:0.25C-0.29Cr-0.03Ti-0.028Al-0.0016B) has been characterized employing Fission Track Etching (FTE) method. The characteristics of boron distribution with variation of cooling rate after austenitization and through case-hardened depth after carburization were analyzed. Hardenability of 15B26 steel was also evaluated through Jominy-end-quench test and the results are as follows: It was observed that, in austenitized 15B26 steel, boron was distributed uniformly over the whole area of specimen with a little segregation along the austenite grain boundaries at higher cooling rates and boron precipitates were formed in the intergranular as well as transgranular regions at lower cooling rates. Jominy equivalents (HRC 35) of 15B26 steel were fairly increased between the Jominy temperatures of 820°C and 850°C, which might result from the increase of the amount of soluble boron in austenite due to the dissolution of borocarbides between 820°C and 850°C. In carburized 15B26 steel, the different through thickness features of boron distribution from the carburized surface were found; coarse nodular boron precipitates up to the depth of 150 μm; uniform distribution of dissolved boron between 150~650 μm; and segregation of boron atoms along grain boundaries in the regions deeper than 650 μm.     

A timing controller embedded driver IC with 3.24‐Gbps eDP interface for chip‐on‐glass TFT‐LCD applications

This paper presents a timing controller embedded driver (TED) IC with 3.24‐Gbps embedded display port (eDP), which is implemented using a 45‐nm high‐voltage CMOS process for the chip‐on‐glass (COG) TFT‐LCD applications. The proposed TED‐IC employs the input offset calibration scheme, the zero‐adjustable equalizer, and the phase locked loop‐based bang‐bang clock and data recovery to enhance the maximum data rate. Also, the proposed TED‐IC provides efficient power management by supporting advanced link power management feature of eDP standard v1.4. Additionally, the smart charge sharing is proposed to reduce the dynamic power consumption of output buffers. Measured result demonstrates the maximum data rate of 3.24 Gbps from a 1.1 V supply voltage with a 7.9‐inch QXGA 60‐Hz COG‐LCD prototype panel and 44% power saving from the display system.     

Rendering of HDR images to improve brightness discrimination

The impression of quality of images can be enhanced on a high dynamic range (HDR) displays. Generally, a conventional 8‐bit image can be processed to an HDR image by inverse tone mapping operators. Among the operators, brightness discrimination mapping by applying brightness adaptation model attempted to mimic the human visual system. In this paper, we use a brightness adaptation model to derive a brightness discrimination mapping algorithm for HDR displays. The proposed algorithm maximizes a function, which represents the local and global brightness discrimination range by exploiting characteristics of the human visual system. Enhancement of details is verified by visualizing HDR images from dark to bright regions. Improvement of dynamic range is quantified by measuring increased discrimination ratio.     

Key-dependent 3D model hashing for authentication using heat kernel signature

Multimedia-based hashing is considered an important technique for achieving authentication and copy detection in digital contents. However, 3D model hashing has not been as widely used as image or video hashing. In this study, we develop a robust 3D mesh-model hashing scheme based on a heat kernel signature (HKS) that can describe a multi-scale shape curve and is robust against isometric modifications. We further discuss the robustness, uniqueness, security, and spaciousness of the method for 3D model hashing. In the proposed hashing scheme, we calculate the local and global HKS coefficients of vertices through time scales and 2D cell coefficients by clustering HKS coefficients with variable bin sizes based on an estimated L² risk function, and generate the binary hash through binarization of the intermediate hash values by combining the cell values and the random values. In addition, we use two parameters, bin center points and cell amplitudes, which are obtained through an iterative refinement process, to improve the robustness, uniqueness, security, and spaciousness further, and combine them in a hash with a key. By evaluating the robustness, uniqueness, and spaciousness experimentally, and through a security analysis based on the differential entropy, we verify that our hashing scheme outperforms conventional hashing schemes.     

A hybrid user authentication protocol for mobile IPTV service

IPTV, a technological convergence that combines communication and broadcasting technologies, delivers customized, interactive TV content and other multimedia information over wired and wireless connections. Providing secure access to IPTV services calls for authentication, without proper and secure authentication mechanisms, an individual impersonating a subscriber could steal a service. This paper proposes a new authentication protocol to authenticate IPTV users. The authors based the proposed protocol, a hybrid authentication protocol providing lightweight, personalized user authentication, on RFID (radio-frequency identification) and USIM (Universal Subscriber Identity Module) technologies. In the proposed protocol, USIM performs highly personalized authentication, and the authenticated subscriber’s RFID tags can have a temporary authority to execute authentication. These RFID tags become Agent Tags authorized to authenticate subscribers. Agent Tags identify and authenticate themselves to RFID readers in the set-top box, thus, simplifying the authentication process.     

Oscillating bubbles in teardrop cavities for microflow control

Microstreaming generated from oscillating microbubbles has great potential in microfluidic applications for localized flow control. In this study, we explore the use of teardrop-shaped cavities for trapping microbubbles. Upon acoustic actuation, these microbubbles confined in teardrop cavities can be utilized to generate a directional microstreaming flow. We further show that by altering the acoustic excitation frequency, a flow-switch for altering flow direction in microfluidic environments can be achieved using two oppositely arranged teardrop cavities with different sizes. In the end, we show that an array of such bubble-filled teardrop cavities can act as a fixated microfluidic transport system allowing for on-chip particle manipulation in complex flow patterns. This inexpensive method to create flows to switch and transport elements based on teardrop cavities can be widely employed for microfluidic applications such as drug delivery systems.     

Exaggerating Character Motions Using Sub‐Joint Hierarchy

Motion capture cannot generate cartoon‐style animation directly. We emulate the rubber‐like exaggerations common in traditional character animation as a means of converting motion capture data into cartoon‐like movement. We achieve this using trajectory‐based motion exaggeration while allowing the violation of link‐length constraints. We extend this technique to obtain smooth, rubber‐like motion by dividing the original links into shorter sub‐links and computing the positions of joints using Bézier curve interpolation and a mass‐spring simulation. This method is fast enough to be used in real time.     

A Hidden‐picture Puzzles Generator

A hidden‐picture puzzle contains objects hidden in a background image, in such a way that each object fits closely into a local region of the background. Our system converts image of the background and objects into line drawing, and then finds places in which to hide transformed versions of the objects using rotation‐invariant shape context matching. During the hiding process, each object is subjected to a slight deformation to enhance its similarity to the background. The results were assessed by a panel of puzzle‐solvers.     

Asynchronous action-reward learning for nonstationary serial supply chain inventory control

Action-reward learning is a reinforcement learning method. In this machine learning approach, an agent interacts with non-deterministic control domain. The agent selects actions at decision epochs and the control domain gives rise to rewards with which the performance measures of the actions are updated. The objective of the agent is to select the future best actions based on the updated performance measures. In this paper, we develop an asynchronous action-reward learning model which updates the performance measures of actions faster than conventional action-reward learning. This learning model is suitable to apply to nonstationary control domain where the rewards for actions vary over time. Based on the asynchronous action-reward learning, two situation reactive inventory control models (centralized and decentralized models) are proposed for a two-stage serial supply chain with nonstationary customer demand. A simulation based experiment was performed to evaluate the performance of the proposed two models. Chang Ouk Kim received his Ph.D. in industrial engineering from Purdue University in 1996 and his B.S. and M.S. degrees from Korea University, Republic of Korea in 1988 and 1990, respectively. From 1998--2001, he was an assistant professor in the Department of Industrial Systems Engineering at Myongji University, Republic of Korea. In 2002, he joined the Department of Information and Industrial Engineering at Yonsei University, Republic of Korea and is now an associate professor. He has published more than 30 articles at international journals. He is currently working on applications of artificial intelligence and adaptive control theory in supply chain management, RFID based logistics information system design, and advanced process control in semiconductor manufacturing. Ick-Hyun Kwon is a postdoctoral researcher in the Department of Civil and Environmental Engineering at University of Illinois at Urbana-Champaign. Previous to this position, Dr. Kwon was a research assistant professor in the Research Institute for Information and Communication Technology at Korea University, Seoul, Republic of Korea. He received his B.S., M.S., and Ph.D. degrees in Industrial Engineering from Korea University, in 1998, 2000, and 2006, respectively. His current research interests are supply chain management, inventory control, production planning and scheduling. Jun-Geol Baek is an assistant professor in the Department of Business Administration at Kwangwoon University, Seoul, Korea. He received his B.S., M.S., and Ph.D. degrees in Industrial Engineering from Korea University, Seoul, Korea, in 1993, 1995, and 2001 respectively. From March 2002 to February 2007, he was an assistant professor in the Department of Industrial Systems Engineering at Induk Institute of Technology, Seoul, Korea. His research interests include machine learning, data mining, intelligent machine diagnosis, and ubiquitous logistics information systems. An erratum to this article can be found at     

Replication of nanostructures on microstructures by intermediate film mold inserted hot embossing process

The present study proposes a simple method to replicate nano/micro combined multiscale structures using an intermediate film mold and anodic aluminum oxide (AAO) nanomold in hot embossing process. The proposed method is simply to add an intermediate film mold with microscale thru-hole patterns to the ordinary mold system, on which nanostructures are patterned, in the hot embossing process. The intermediate film mold is inserted between polymer substrate and AAO nanomold. During the hot embossing process, the polymer first fills microscale thru-hole patterns in the intermediate film mold and subsequently fills nanopores in AAO nanomold, resulting in the nano/micro combined structures. The intermediate film molds, which have microscale thru-hole patterns were fabricated by micro-milling, laser ablation, etching methods and/or LIGA process. The nano/micro combined structures were successfully replicated by the proposed method.