Transforming One‐Dimensional Nanowalls to Long‐Range Ordered Two‐Dimensional Nanowaves: Exploiting Buckling Instability and Nanofibers Effect in Holographic Lithography

Two‐dimensional nanowaves with long‐range order are fabricated by exploiting swelling‐induced buckling of one‐dimensional (1D) nanowalls with nanofibers formed in‐between during holographic lithography of the negative‐tone photoresist SU‐8. The 1D film goes through a constrained swelling in the development stage, and becomes buckled above the critical threshold. The degree of lateral undulation can be controlled by tuning the pattern aspect ratio (height/width) and exposure dosage. At a high aspect ratio (e.g., 6) and a high exposure dosage, nanofibers (30–50 nm in diameter) are formed between the nanowalls as a result of overlapping of low crosslinking density regions. By comparing experimental results with finite‐element analysis, the buckling mechanism is investigated, which confirms that the nanofibers prevent the deformed nanowalls from recovery to their original state, thus, leading to long‐range ordered two‐dimensional (2D) wavy structures. The film with nanowaves show weaker reflecting color under an ambient light and lower transmittance compared to the straight nanowalls. Using double exposure through a photomask, patterns consisting of both nanowaves and nanowalls for optical display are created.     

Variable length signal detection framework for cognitive radio systems

The cognitive radio (CR) system opportunistically utilizes the frequency bands temporally unoccupied by the primary user. In the CR system, the energy or cyclostationary detector is used to detect the primary user signal. For protecting the primary user tightly, the signal detection time can be very long, which leads to inefficiency in the CR system. Thus, we propose a novel signal detector that greatly reduces the average detection time. The proposed detector periodically decides whether it terminates the detection process or receives more input signal for more information. Therefore, the proposed detector has variable detection time. We will call the proposed detector the variable length signal detector (VLSD). The VLSD is designed by using a partially observable Markov decision process framework for optimal performance. We present the numerical results showing that the VLSD requires much smaller average detection time compared with the traditional fixed length signal detector to achieve a given detection error probability. Copyright © 2012 John Wiley & Sons, Ltd.     

A moving-actuator type electromechanical total artificial heart.II. Circular type and animal experiment

A new type of electromechanical total artificial heart (TAH) based on circular rolling-cylinder mechanism was developed to overcome critical problems in motor-driven artificial hearts such as large size and difficulties in fitting the heart to atrial remnants and arterial vessels. Its performance and reliability were evaluated in mock circulation and in an animal implant experiment. The total weight and volume of the pump is 650 g and 600 mL, respectively. This new pump was implanted in a calf for total heart replacement and 96 h of survival was achieved. The whole system, including pump, controller, and control algorithm performed well enough to improve the prospect of eventual clinical application of our TAH system.     

Understanding social viewing through discussion network and emotion: A focus on South Korean presidential debates

With the development of social media, television viewing is perceived no longer as an isolated activity. This study explores the underlying mechanism of the effects of social viewing discussion networks (i.e., bridging and bonding social viewing networks) on emotions (i.e., anger, fear, and enthusiasm), and moreover on opinion consolidation as well as opinion weakening in the context of the 2017 South Korean presidential debates. Overall, the main results are: a) Social viewing discussion networks influenced emotional states of social viewers, b) Emotions influenced attitude formation during social viewing, and c) Enthusiasm served as a catalyst that links bonding and bridging social viewing, and opinion consolidation. Implications and theoretical contributions are discussed.     

Lowering customer’s switching cost using B2B services for telecommunication companies

A B2B transaction is a transaction between organizations. However, the ripple effects of a B2B transaction can reach the members of the organization and generate additional economic impact. Enterprise LTE (Long term evolution) is a newly introduced B2B service in the South Korean telecommunications market. While it provides secure and fast telecommunications services to businesses, it can also affect the employees’ utility in the business, since the service provider can provide a variety of additional services to employees who use the same telecommunications provider for their mobile devices. In this study, we empirically analyze how B2B and Enterprise LTE services affect consumer churn-in in the telecommunications market. We estimate consumer benefit based on the additional services provided after the introduction of the B2B service using conjoint analysis. We also estimate consumer switching cost for changing one’s mobile telecommunications service provider using contingent valuation method. By comparing these values, we analyze the switching probability of employees when B2B services are introduced at their workplace. The results show that in order to maximize revenue, considering the revenue gained from new subscribers and from fees for providing additional services, lowering service fees for additional services and maximizing market share are advisable.     

Dynamic programming approach to optimal vertex selection for polygon-based shape approximation

A new vertex selection scheme for polygon-based contour coders is presented. In the proposed method, final vertex points are determined by a 'two-step procedure'. In the first step, the initial vertices are simply selected from the contour, thereby constituting a subset of the original contour, using conventional methods such as the iterated refinement method (IRM) or progressive vertex selection (PVS) method. In the second step, a vertex adjustment process is incorporated to generate final vertices that are no longer confined to the contour and are optimal in view of the given distortion measure. For the optimality of the final vertices, a dynamic programming (DP)-based solution for the adjustment of the vertices is proposed. Consequently, the authors offer two main contributions. First, it is shown that DP can be successfully applied to vertex adjustment. Secondly, the use of DP enables global optimality to be achieved in vertex selection without any iterative processes. Experimental results are presented to demonstrate the superiority of the proposed method over traditional methods     

A novel hidden station detection mechanism in IEEE 802.11 WLAN

The popular IEEE 802.11 wireless local area network (WLAN) is based on a carrier sense multiple access with collision avoidance (CSMA/CA), where a station listens to the medium before transmission in order to avoid collision. If there exist stations which can not hear each other, i.e., hidden stations, the potential collision probability increases, thus dramatically degrading the network throughput. The RTS/CTS (request-to-send/clear-to-send) frame exchange is a solution for the hidden station problem, but the RTS/CTS exchange itself consumes the network resources by transmitting the control frames. In order to maximize the network throughput, we need to use the RTS/CTS exchange adaptively only when hidden stations exist in the network. In this letter, a simple but very effective hidden station detection mechanism is proposed. Once a station detects the hidden stations via the proposed detection mechanism, it can trigger the usage of the RTS/CTS exchange. The simulation results demonstrate that the proposed mechanism can provide the maximum system throughput performance.     

Uniaxial-process-induced strained-Si: extending the CMOS roadmap

This paper reviews the history of strained-silicon and the adoption of uniaxial-process-induced strain in nearly all high-performance 90-, 65-, and 45-nm logic technologies to date. A more complete data set of n- and p-channel MOSFET piezoresistance and strain-altered gate tunneling is presented along with new insight into the physical mechanisms responsible for hole mobility enhancement. Strained-Si hole mobility data are analyzed using six band k/spl middot/p calculations for stresses of technological importance: uniaxial longitudinal compressive and biaxial stress on [001] and [110] wafers. The calculations and experimental data show that low in-plane and large out-of-plane conductivity effective masses and a high density of states in the top band are all important for large hole mobility enhancement. This work suggests longitudinal compressive stress on [001] or [110] wafers and <110> channel direction offers the most favorable band structure for holes. The maximum Si inversion-layer hole mobility enhancement is estimated to be /spl sim/ 4 times higher for uniaxial stress on (100) wafer and /spl sim/ 2 times higher for biaxial stress on (100) wafer and for uniaxial stress on a [110] wafer.     

Adaptive processing using real weights based on a direct data domain least squares approach

In traditional, adaptive signal processing algorithms one change both the amplitude and phase of the weight vectors associated with an array at each of the antenna elements. The use of complex weights offers greater control over the array response at the expense of system complexity. However, it is easier if one requires only amplitude variation with a fixed phase for all the weight vectors associated with all the antenna elements. Because one uses only real arithmetic operations to find the amplitude of the weights connected to the antenna, the computational complexity is reduced considerably. Hence, this paper addresses the use of real weights in an adaptive system. In this paper we describe a new direct data domain least squares (D/sup 3/LS) method using real weights, which utilizes only a single snapshot of the data for adaptive processing. This technique may be useful for real time implementation of the D/sup 3/LS method on a chip.     

A learning approach of wafer temperature control in a rapid thermalprocessing system

This paper presents a learning approach for wafer temperature control in a rapid thermal processing system (RTP). RTP is very important for semiconductor processing system and requires an accurate trajectory following. Numerous studies have addressed this problem and most research on this problem requires exact knowledge of the system dynamics. The various approaches do not guarantee the desired performance in practical applications when there exist some modeling errors between the model and the actual system. In this paper, iterative learning control scheme is applied to RTP without exact information on the dynamics. The learning gain of the iterative learning law is estimated by neural networks instead of a mathematical model. In addition, the control information obtained by the iterative learning controller (ILC) is accumulated in the feedforward neuro controller (FNC) for generalization to various reference profiles. Through numerical simulations, it is demonstrated that the proposed method can achieve an accurate output tracking even without an exact RTP model. The output errors decrease rapidly through iterations when using the learning gain estimated and the FNC yields a reduced initial error, and so requires small iterations