Improved Scalar Multiplication on Elliptic Curves Defined over F2mn

We propose two improved scalar multiplication methods on elliptic curves over F_qn where q = 2^m using Frobenius expansion. The scalar multiplication of elliptic curves defined over subfield F_q can be sped up by Frobenius expansion. Previous methods are restricted to the case of a small m. However, when m is small, it is hard to find curves having good cryptographic properties. Our methods are suitable for curves defined over medium‐sized fields, that is, 10 ≤ m ≤ 20. These methods are variants of the conventional multiple‐base binary (MBB) method combined with the window method. One of our methods is for a polynomial basis representation with software implementation, and the other is for a normal basis representation with hardware implementation. Our software experiment shows that it is about 10% faster than the MBB method, which also uses Frobenius expansion, and about 20% faster than the Montgomery method, which is the fastest general method in polynomial basis implementation.     

Exhaustive Output Arbitration of Input Buffered Switch with Buffered Crossbar

We propose a new arbitration method for an input buffered switch with a buffered crossbar. In the proposed method, an exhaustive polling method is used to decrease the synchronization. Using an approximate analysis, we explain how the proposed method improves the switch performance. Also, using computer simulations, we show the proposed method outperforms the previous methods under burst traffic.     

Performance comparison of integrated fully-differential filterless class-D amplifiers with different feedback techniques

Two integrated stereo fully differential filterless class-D amplifiers are presented in this paper. The object is to develop a modulation of a class-D audio amplifier with high power efficiency in this paper. The traditional H-bridge class-D audio amplifier has a shortcoming of large signal distortion which is worse than realized. However, the proposed circuit improves the drawback and provides high power efficiency at the same time. The circuit implements a modified scheme of pulse-width modulation. In this paper, we presented two class-D amplifiers, compared their differences and explained why the efficiency and distortion performance can be modified. The increase in total harmonic distortion (THD) is due to non-linearity in the triangle wave. To overcome this problem, a negative feedback from the output of the switching power stage is adopted to reduce the THD. When a 0.7-V_PP and 1 kHz sine wave is used as an input signal, the minimum THD is 0.029 % and the maximum power efficiency is 83 %. The fully differential class-D audio amplifier is implemented with a TSMC 0.35-μm 2P4M CMOS process, and the chip area is 2.57 × 2.57 mm² (with PADs).     

A novel dynamic Multiple Ring-based Local Restoration for point-to-multipoint multicast traffic in WDM mesh networks

Optical networks with DWDM (Dense Wavelength Division Multiplex) can provide multiple data channels to supply high speed, high capacity to perform bandwidth-intensive multicast transmission service. Light-tree is a popular technique applied to support point-to-multipoint multicast services. Any failure during a multicast session would cause severe service loss or disruptions, especially when the faults occur near the source node. A novel ring-based local fault recovery mechanism, Multiple Ring-based Local Restoration (MRLR), for point-to-multipoint multicast traffic based on the minimum spanning tree (MST) in WDM mesh networks is proposed in this article. The MRLR mechanism dismembers the multicast tree into several disjoint segment-blocks (sub-trees) and reserves preplanned spare capacity to set up multiple protection rings in each segment-block for providing rapid local recovery. The MRLR scheme outperforms other methodologies in terms of the blocking probability, recovery time, and average hop count of protection path per session for different network topologies.     

Study of Intrusion Detection Systems

Modern network systems have much trouble in security vulnerabilities such as buffer overflow, bugs in Microsoft Internet, sensor network routing protocol too simple, security flaws of applications, and operating systems. Moreover, wireless devices such as smart phones, personal digital assistants （PDAs）, and sensors have become economically feasible because of technological advances in wireless communication and manufacturing of small and low-cost sensors. There are typologies of vulnerabilities to be exploited in these devices. In order to improve securities, many mechanisms are adopted, including authentication, cryptography, access control, and intrusion detection systems （IDS）. In general, intrusion detection techniques can be categorized into two groups： misuse detection and anomaly detection. The misuse detection systems use patterns of weB-known attacks or weak spots of the systems to identify intrusions. The weakness of misuse detection systems is unable to detect any future （unknown） intrusion until corresponding attack signatures are intruded into the signature database. Anomaly detection methods try to determine whether the deviation is from the established normal usage patterns or not. The critical success of anomaly detection relies on the model of normal behaviors.     

A Multi‐Strategic Concept‐Spotting Approach for Robust Understanding of Spoken Korean

We propose a multi‐strategic concept‐spotting approach for robust spoken language understanding of conversational Korean in a hostile recognition environment such as in‐car navigation and telebanking services. Our concept‐spotting method adopts a partial semantic understanding strategy within a given specific domain since the method tries to directly extract pre‐defined meaning representation slot values from spoken language inputs. In spite of partial understanding, we can efficiently acquire the necessary information to compose interesting applications because the meaning representation slots are properly designed for specific domain‐oriented understanding tasks. We also propose a multi‐strategic method based on this concept‐spotting approach such as a voting method. We present experiments conducted to verify the feasibility of these methods using a variety of spoken Korean data.     

Improved Yen-Joye's authenticated multiple-key agreement protocol

An authenticated multiple-key agreement protocol is proposed. The protocol is not only secure against the unknown-key attack but also more efficient than other protocols.     

Enhancing Representation of Deep Features for Sensor-Based Activity Recognition

Sensor-based activity recognition (AR) depends on effective feature representation and classification. However, many recent studies focus on recognition methods, but largely ignore feature representation. Benefitting from the success of Convolutional Neural Networks (CNN) in feature extraction, we propose to improve the feature representation of activities. Specifically, we use a reversed CNN to generate the significant data based on the original features and combine the raw training data with significant data to obtain to enhanced training data. The proposed method can not only train better feature extractors but also help better understand the abstract features of sensor-based activity data. To demonstrate the effectiveness of our proposed method, we conduct comparative experiments with CNN Classifier and CNN-LSTM Classifier on five public datasets, namely the UCIHAR, UniMiB SHAR, OPPORTUNITY, WISDM, and PAMAP2. In addition, we evaluate our proposed method in comparison with traditional methods such as Decision Tree, Multi-layer Perceptron, Extremely randomized trees, Random Forest, and k-Nearest Neighbour on a specific dataset, WISDM. The results show our proposed method consistently outperforms the state-of-the-art methods.

     

Digital Laser Micropainting for Reprogrammable Optoelectronic Applications

Structural coloration is closely related to the progress of innovative optoelectronic applications, but the absence of direct, on-demand, and rewritable coloration schemes has impeded advances in the relevant area, particularly including the development of customized, reprogrammable optoelectronic devices. To overcome these limitations, a digital laser micropainting technique, based on controlled thin-film interference, is proposed through direct growth of the absorbing metal oxide layer on a metallic reflector in the solution environment via a laser. A continuous-wave laser simultaneously performs two functions—a photothermal reaction for site-selective metal oxide layer growth and in situ real-time monitoring of its thickness—while the reflection spectrum is tuned in a broad visible spectrum according to the laser fluence. The scalability and controllability of the proposed scheme is verified by laser-printed painting, while altering the thickness via supplementary irradiation of the identical laser in the homogeneous and heterogeneous solutions facilitates the modification of the original coloration. Finally, the proof-of-concept bolometer device verifies that specific wavelength-dependent photoresponsivity can be assigned, erased, and reassigned by the successive application of the proposed digital laser micropainting technique, which substantiates its potential to offer a new route for reprogrammable optoelectronic applications.     

Rapid Generation of Biologically Relevant Hydrogels Containing Long‐Range Chemical Gradients

Many biological processes are regulated by gradients of bioactive chemicals. Thus, the generation of materials with embedded chemical gradients may be beneficial for understanding biological phenomena and generating tissue‐mimetic constructs. Here a simple and versatile method to rapidly generate materials containing centimeter‐long gradients of chemical properties in a microfluidic channel is described. The formation of a chemical gradient is initiated by a passive‐pump‐induced forward flow and further developed during an evaporation‐induced backward flow. The gradient is spatially controlled by the backward flow time and the hydrogel material containing the gradient is synthesized via photopolymerization. Gradients of a cell‐adhesion ligand, Arg‐Gly‐Asp‐Ser (RGDS), are incorporated in poly(ethylene glycol)‐diacrylate (PEG‐DA) hydrogels to test the response of endothelial cells. The cells attach and spread along the hydrogel material in a manner consistent with the RGDS‐gradient profile. A hydrogel containing a PEG‐DA concentration gradient and constant RGDS concentration is also shown. The morphology of cells cultured on such hydrogel changes from round in the lower PEG‐DA concentration regions to well‐spread in the higher PEG‐DA concentration regions. This approach is expected to be a valuable tool to investigate the cell–material interactions in a simple and high‐throughput manner and to design graded biomimetic materials for tissue engineering applications.