Identification of early aspects is the critical problem in aspect-oriented requirement engineering. But the representation of crosscutting concerns is various, which makes the identification difficult. To address the problem, this paper proposes the AspectQuery method based on goal model. We analyze four kinds of goal decomposition models, then summarize the main factors about identification of crosscutting concerns and conclude the identification rules based on a goal model. A goal is crosscutting concern when it satisfies one of the following conditions: i) the goal is contributed to realize one soft-goal; ii) parent goal of the goal is candidate crosscutting concern; iii) the goal has at least two parent goals. AspectQuery includes four steps: building the goal model, transforming the goal model, identifying the crosscutting concerns by identification rules, and composing the crosscutting concerns with the goals affected by them. We illustrate the AspectQuery method through a case study (a ticket booking management system). The results show the effectiveness of AspectQuery in identifying crosscutting concerns in the requirement phase.

In situ UV-vis. absorption spectra of cytochrome c adsorbed on ITO electrode was observed with slab optical waveguide spectroscopy combining pulse potential step (PPS) between 0.3 and -0.45 V vs. Ag/AgCl. The amount of cytochrome c adsorbed on ITO electrode was estimated from the amount of coulomb of the peaks in cyclic voltammogram to be about a monolayer coverage in this experimental condition. Spectral change between oxidized and reduced cytochrome c by PPS was finished in about 20 msec with phosphate buffer solution. The results strongly proved that SOWG spectroscopy should be effective for in situ observation of ET reaction kinetics of surface adsorbed molecules.

Among the cognitive radio technologies, cooperative spectrum sensing has been corroborated to be an effective approach to counter channel fading. Recent research about it is mainly with the assumption that secondary users (SUs) are synchronous with primary users (PUs). In this letter, we discuss the asynchronous situation for the first time, which means SUs have no idea about the communication time table of PUs' network. Based on the ON/OFF channel model, we derive the detection and false alarm probabilities, and the optimal sensing parameters under such asynchronous scenario. Simulation results are shown in the end.

For opportunistic spectrum access (OSA), spectrum management is a key function to effectively utilize white space without causing harmful interference to incumbent receivers. Geo-location database approaches using radio propagation estimation have been regarded as practical spectrum management methods. However, propagation models inevitably fail to accurately estimate the path loss in actual radio environments, resulting in estimation error of carrier to interference ratio (CIR) of the incumbent receivers. This could prevent white space from being efficiently utilized, because the allowable transmit power of the opportunistic system has to be limited to keep the CIR at the required level. To improve the accuracy of CIR estimation, we propose the new concept of Interference Monitoring which works in combination with spectrum management. In this method, a monitoring node located near the incumbent receivers actually measures both the interference signals and the incumbent signals. Using the measurement results, the CIR estimates are corrected based on the minimum mean square error (MMSE) criterion. The proposed Interference Monitoring can be extended to establish cooperation among multiple monitoring nodes and thus spatial diversity. Analytical evaluations assuming a simple cellular system model show that Interference Monitoring can more accurately estimate CIR, and thus it can significantly increase the allowable transmit power. For an urban macro cell, Interference Monitoring with a single node achieved about a 6.5 dB increase in the transmit power; Cooperative Interference Monitoring with 4 nodes achieved about a 13.5 dB increase. Thus, Interference Monitoring-based spectrum management can maximize opportunities for white space utilization without imposing additional interference to the incumbent system.

After brief introduction of our new microscope unit with an immersion objective and ionic liquid used as a refractive index matching medium, in this paper, we describe the studies on dipole orientation imaging of single molecules under high vacuum conditions as one of the important applications of our microscope.

In this paper, we propose a new method for wideband spectrum sensing using compressed measurements of the received wideband signal; we can directly separate information of the sub-channels and perform detection in each. Wideband spectrum sensing empowers us to rapidly access the vacant sub-channels in high utilization regime. Regarding the fact that at each time instant some sub-channels are vacant, the received signal is sparse in some bases. Then we could apply the Compressive Sensing (CS) algorithms and take the compressed measurements. On the other hand, the primary user signals in different sub-channels could have different modulation types; therefore, the signal in each sub-channel is chosen among a signal space. Knowing these signal spaces, the secondary user could separate information of different sub-channels employing the compressed measurements. We perform filtering and detection based on these compressed measurements; this decreases the computational complexity of the wideband spectrum sensing. In addition, we model the received wideband signal as a vector which has a block-sparse representation on a basis consisting of all sub-channel bases whose elements occur in clusters. Based on this feature of the received signal, we propose another wideband spectrum sensing method with lower computational complexity. In order to evaluate the performance of the proposed method, we employ the Monte-Carlo simulation. According to simulations if the compression rate is selected appropriately according to the CS theorems and the problem model, the detection performance of our method leads to the performance of the ideal filter bank-based method, which uses the ideal and impractical narrow band filters.

We report a trial of 100-GS/s optical quantization with 5-bit resolution using soliton self-frequency shift (SSFS) and spectral compression. We confirm that 100-GS/s 5-bit optical quantization is realized to quantize a 5.0-GHz sinusoid electrical signal in simulation. In order to experimentally verify the possibility of 100-GS/s 5-bit optical quantization, we execute 5-bit optical quantization by using two sampled signals with 10-ps intervals.

In spectrum sharing cognitive radio (CR) networks, secondary user (SU) is allowed to share the same spectrum band concurrently with primary user (PU), with the condition that the SU causes no harmful interference to the PU. In this letter, the ergodic and outage capacity loss constraints are proposed to protect the PU according to its service types. We investigate the performance of the SU in terms of ergodic capacity under various power allocation policies of the PU. Specifically, three PU power allocation policies are considered, namely waterfilling, truncated channel inversion with fixed rate (TIFR) and constant power allocation. We obtain the ergodic capacities of the SU under the three PU power allocation policies. The numerical results show that the PU waterfilling and TIFR power allocation policies are superior to the PU constant power allocation in terms of the capacity of the PU. In particular, it is shown that, with respect to the ergodic capacity of the SU, the PU waterfilling power allocation is superior to the PU constant power allocation, while the PU TIFR power allocation is inferior to the PU constant power allocation.

Probabilistic Packet Marking (PPM) is a scheme for IP traceback where each packet is marked randomly with an IP address of one router on the attack path in order for the victim to trace the source of attacks. In previous work, a network coding approach to PPM (PPM+NC) where each packet is marked with a random linear combination of router IP addresses was introduced to reduce number of packets required to infer the attack path. However, the previous work lacks a formal proof for benefit of network coding to PPM and its proposed scheme is restricted. In this paper, we propose a novel method to prove a strong theorem for benefit of network coding to PPM in the general case, which compares different perspectives (interests of collecting) at the collector in PPM+NC scheme. Then we propose Core PPM+NC schemes based on our core network coding approach to PPM. From experiments, we show that our Core PPM+NC schemes actually require less number of packets than previous schemes to infer the attack path. In addition, based on the relationship between Coupon Collector's Problem (CCP) and PPM, we prove that there exists numerous designs that CCP still benefits from network coding.

We have investigated on a random-texturing process for multi-crystalline Si solar cells by plasmaless dry etching, with chlorine trifluoride (ClF3) gas treatments. The reflectance of textured surfaces was reduced to below 20% at a wavelength of 600 nm. In this study, we tried to improve the electrical characteristics by modifying the fabrication process. The substrate surfaces were dry etched by chlorine trifluoride gas and subsequently etched with an acid solution to form appropriate textured structures. The improved electrical characteristics were demonstrated.

Fast string matching is essential for deep packet inspection (DPI). Traditional string matchers cannot keep up with the continuous increases in data rates due to their natural speed limits. We add a multi-byte processing prefilter to the traditional string matcher to detect target patterns on a multiple character basis. The proposed winnowing prefilter significantly reduces the number of identity blocks, thereby reducing the memory requirements.

The overall performance of multi-hop cognitive radio networks (MHCRNs) can be improved significantly by employing the diversity of orthogonal licensed channels in underlay fashion. However, the mutual interference between secondary links and primary links and the congestion due to the contention among traffic flows traversing the shared link become obstacles to this realizing technique. How to control congestion efficiently in coordination with power and spectrum allocation optimally in order to obtain a high end-to-end throughput is motivating cross-layer designs for MHCRNs. In this paper, by taking into account the problem of joint rate adaption, power control, and spectrum allocation (JRPS), we propose a new cross-layer optimization framework for MHCRNs using orthogonal frequency division multiple access (OFDMA). Specifically, the JRPS formulation is shown to be a mix-integer non-linear programming (MINLP) problem, which is NP-Hard in general. To solve the problem, we first develop a partially distributed algorithm, which is shown to converge to the global optimum within a reasonable time interval. We next propose a suboptimal solution which addresses the shortcomings of the first. Using numerical results, we finally demonstrate the efficiency of the proposed algorithms.

In this letter, we analyze the outage performance of cognitive spectrum sharing in two-way relaying systems. We derive expressions of outage probability for the primary and secondary network over independent but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. Monte Carlo simulations are presented to verify the theoretical analyses.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

Self-encoded spread spectrum (SESS) derives its spreading codes from the random information source rather than using traditional pseudo-random codes. It has been shown that the memory in SESS modulated signals not only can deliver a 3 dB gain in additive white Gaussian noise (AWGN) channels, but also can be exploited to achieve time diversity and robust bit-error rate (BER) performance in fading channels. In this paper, we propose an extension to SESS, namely coded-sequence self-encoded spread spectrum (CS-SESS), and show that it can further improve the BER performance. We describe the CS-SESS scheme and present the theoretical analysis and simulation results for AWGN and fading channels. Iterative detector is developed to exploit the inherent temporal diversity of CS-SESS modulation. The simulation results show that it can achieve the expected 4.7 dB gain with a complexity that increases linearly with the spreading sequence length under AWGN. In Rayleigh fading channel, it can effectively mitigate the fading effects by exploiting the overall diversity gain. Chip interleaving is shown to yield a performance improvement of around 4.7 dB when compared to an chip interleaved direct sequence spread spectrum (DSSS) system.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

This paper is concerned with coding theorems in the optimistic sense for separate coding of two correlated general sources X1 and X2. We investigate the achievable rate region Ropt (X1,X2) such that the decoding error probability caused by two encoders and one decoder can be arbitrarily small infinitely often under a certain rate constraint. We give an inner and an outer bounds of Ropt (X1,X2), where the outer bound is described by using new information-theoretic quantities. We also give two simple sufficient conditions under which the inner bound coincides with the outer bound.

We propose optical path routing and frequency slot assignment algorithms that can make the best use of elastic optical paths and the capabilities of distance adaptive modulation. Due to the computational difficulty of the assignment problem, we develop algorithms for 1+1 dedicated/1:1 shared protected ring networks and unprotected mesh networks to that fully utilize the characteristics of the topologies. Numerical experiments elucidate that the introduction of path elasticity and distance adaptive modulation significantly reduce the occupied bandwidth.

Based on a proposed frame structure with an unequal sensing slot duration for each channel, and two sensing scenarios (with or without cooperation), a joint channel and sensing time assignment is suggested to maximize the uplink throughput of the centralized multi-band cognitive radio network with the consideration of the mutual interference among the secondary users (SUs). Firstly, the channel assignment is performed by using the proposed Delta Non-square Hungarian (DNH), which is a modified iterative Hungarian algorithm distinguished by throughput increment maximization and non-square weight matrix. Simulation results illustrate that DNH has significant advantages in enhancing the throughput and reducing the computational complexity. Moreover, a hybrid channel assignment, also performed by DNH, is improved based on the two sensing scenarios to maximize the throughput while efficiently limiting the interference power to primary users. Secondly, the convexity of the throughput functions within the range of sensing time is proved under the proposed frame structure, and then the maximum throughput is achieved through the steepest descent method-based sensing time assignment. Both of these results are corroborated by simulations.

Recently, cooperative spectrum sensing is being studied to greatly improve the sensing performance of cognitive radio networks. To develop an adaptable cooperative sensing algorithm, an important issue is how to properly induce selfish users to participate in spectrum sensing work. In this paper, a new cognitive radio spectrum sharing scheme is developed by employing the trust-based bargaining model. The proposed scheme dynamically adjusts bargaining powers and adaptively shares the available spectrum in real-time online manner. Under widely different and diversified network situations, this approach is so dynamic and flexible that it can adaptively respond to current network conditions. Simulation results demonstrate that the proposed scheme can obtain better network performance and bandwidth efficiency than existing schemes.