Separation-of-Duty (SoD) is a fundamental security principle for prevention of fraud and errors in computer security. It has been studied extensively in traditional access control models. However, the research of SoD policy in the recently proposed usage control (UCON) model has not been well studied. This paper formulates and studies the fundamental problem of static enforcement of static SoD (SSoD) policies in the context of UCONA, a sub-model of UCON only considering authorizations. Firstly, we define a set-based specification of SSoD policies, and the safety checking problem for SSoD in UCONA. Secondly, we study the problem of determining whether an SSoD policy is enforceable. Thirdly, we show that it is intractable (coNP-complete) to direct statically enforce SSoD policies in UCONA, while checking whether a UCONA state satisfies a set of static mutually exclusive attribute (SMEA) constraints is efficient, which provides a justification for using SMEA constraints to enforce SSoD policies. Finally, we introduce a indirect static enforcement for SSoD policies in UCONA. We show how to generate the least restrictive SMEA constraints for enforcing SSoD policies in UCONA, by using the attribute-level SSoD requirement as an intermediate step. The results are fundamental to understanding SSoD policies in UCON.

In the current study, stress-induced capacitance determined by direct measurement on MOSFETs was compared with that determined by indirect simulation through the delay of CMOS ring oscillators (ROs) fabricated side by side with MOSFETs. External compressive stresses were applied on <110> silicon-on-insulator (SOI) n-/p-MOSFETs with the ROs in a longitudinal configuration. The measured gate capacitance decreased as the compressive stress on SOI increased, which agrees with the result of the capacitance difference between measured and simulated delay of the ROs. The oscillation frequency shift of the ROs should mainly be attributed to oxide capacitance, aside from the change in mobility of the n-/p-MOSFETs. The result suggests that the stress-induced gate capacitance of partially depleted MOSFETs is an important factor for the capacitance shift in a circuit and that ROs can be used in a vehicle to determine mechanical stress-induced gate capacitance in MOSFETs.

This paper presents analysis and design of a new ultra-low voltage analog front end (AFE) dedicated to strain sensor applications. The AFE, designed in 0.18 µm CMOS process, features a chopper-stabilized instrumentation amplifier (IA), a balanced active MOSFET-C 2nd order low pass filter (LPF), a clock generator and a voltage booster which operate at supply voltage (Vdd) of 0.6 V. The designed IA achieves 30 dB of closed-loop gain, 101 dB of common-mode rejection ratio (CMRR) at 50 Hz, 80 dB of power-supply rejection ratio (PSRR) at 50 Hz, thermal noise floor of 53.4 nV/, current consumption of 14 µA, and noise efficiency factor (NEF) of 9.7. The high CMRR and rail-to-rail output swing capability is attributed to a new low voltage realization of the active-bootstrapped technique using a pseudo-differential gain-boosting operational transconductance amplifier (OTA) and proposed current-driven bulk (CDB) biasing technique. An output capacitor-less low-dropout regulator (LDO), with a new fast start-up LPF technique, is used to regulate this 0.6 V supply from a 0.8–1.0 V energy harvesting power source. It achieves power supply rejection (PSR) of 42 dB at frequency of 1 MHz. A cascode compensated pseudo differential amplifier is used as the filter's building block for low power design. The filter's single-ended-to-balanced converter is implemented using a new low voltage amplifier with two-stage common-mode cancellation. The overall AFE was simulated to have 65.6 dB of signal-to-noise ratio (SNR), total harmonic distortion (THD) of less than 0.9% for a 100 Hz sinusoidal maximum input signal, bandwidth of 2 kHz, and power consumption of 51.2 µW. Spectre RF simulations were performed to validate the design using BSIM3V3 transistor models provided by GLOBALFOUNDRIES 0.18 µm CMOS process.

In this paper, performance analysis of a cognitive radio network is conducted. In the network, there is imperfect sensing and the wireless channel is a Gilbert-Elliott channel. The focus is on the network's capacity in serving traffic with delay constraints. Specifically, the maximum traffic arrival rates of both primary users and secondary users, which the network can support with guaranteed delay bounds, are investigated. The analysis is based on stochastic network calculus. A general relationship between delay bounds, traffic patterns and important characteristics such as spectrum sensing errors and channel fading of the cognitive radio network is derived. This relationship lays a foundation for finding the capacity under different traffic scenarios. Two specific traffic types are exemplified, namely periodic traffic and Poisson traffic. Analytical results are presented in comparison with simulation results. The comparison shows a good match between them, validating the analysis.

The k-edge-connectivity augmentation problem with bipartition constraints (kECABP, for short) is defined by “Given an undirected graph G=(V, E) and a bipartition π = {VB, VW} of V with VB ∩ VW = ∅, find an edge set Ef of minimum cardinality, consisting of edges that connect VB and VW, such that G'=(V, E ∪ Ef) is k-edge-connected.” The problem has applications for security of statistical data stored in a cross tabulated table, and so on. In this paper we propose a fast algorithm for finding an optimal solution to (σ + 1)ECABP in O(|V||E| + |V2|log |V|) time when G is σ-edge-connected (σ > 0), and show that the problem can be solved in linear time if σ ∈ {1, 2}.

We propose a new method, called Subclass-oriented Dimensionality Reduction with Pairwise Constraints (SODRPaC), for dimensionality reduction. In a high dimensional space, it is common that a group of data points with one class may scatter in several different groups. Current linear semi-supervised dimensionality reduction methods would fail to achieve fair performances, as they assume two data points linked by a must-link constraint are close each other, while they are likely to be located in different groups. Inspired by the above observation, we classify the must-link constraint into two categories, which are the inter-subclass must-link constraint and the intra-subclass must-link constraint, respectively. We carefully generate cannot-link constraints by using must-link constraints, and then propose a new discriminant criterion by employing the cannot-link constraints and the compactness of shared nearest neighbors. The manifold regularization is also incorporated in our dimensionality reduction framework. Extensive experiments on both synthetic and practical data sets illustrate the effectiveness of our method.

A method for efficiently representing the state equation in a class of max-plus linear systems is proposed. We introduce a construct referred to as 'cell' in which the list of possible longest paths is stored. By imposing interval constraints on the system parameters, we can reduce the complexity of the state equation. The proposed method would be useful in scheduling applications for systems with adjustable system parameters.

A total-field/scattered-field (TF/SF) boundary for the constrained interpolation profile (CIP) method is proposed for multi-dimensional electromagnetic problems. Incident fields are added to or subtracted from update equations in order to satisfy advection equations into which Maxwell's equations are reduced by means of the directional splitting. Modified incident fields are introduced to take into account electromagnetic fields after advection. The developed TF/SF boundary is examined numerically, and the results show that it operates with good performance. Finally, we apply the proposed TF/SF boundary to a scattering problem, and it can be solved successfully.

The continuous advances in sensing and positioning technologies have resulted in a dramatic increase in popularity of Location-Based Services (LBS). Nevertheless, the LBS can lead to user privacy breach due to sharing location information with potentially malicious services. A high degree of location privacy preservation for LBS is extremely required. In this paper, a clustering K-anonymity scheme for location privacy preservation (namely CK) is proposed. The CK scheme does not rely on a trusted third party to anonymize the location information of users. In CK scheme, the whole area that all the users reside is divided into clusters recursively in order to get cloaked area. The exact location information of the user is replaced by the cloaked spatial temporal boundary (STB) including K users. The user can adjust the resolution of location information with spatial or temporal constraints to meet his personalized privacy requirement. The experimental results show that CK can provide stringent privacy guarantees, strong robustness and high QoS (Quality of Service).

Beamforming with sparse constraint has shown significant performance improvement. In this letter, a least squares constant modulus blind adaptive beamforming with sparse constraint is proposed. Simulation results indicate that the proposed approach exhibits better performance than the well-known least squares constant modulus algorithm (LSCMA).

The doubly constrained robust Capon beamformer (DCRCB), which employs a spherical uncertainty set of the steering vector together with the constant norm constraint, can provide robustness against arbitrary array imperfections. However, its performance can be greatly degraded when the uncertainty bound of the spherical set is not properly selected. In this paper, combining the DCRCB and the weight-vector-norm-constrained beamformer (WVNCB), we suggest a new robust adaptive beamforming method which allows us to overcome the performance degradation due to improper selection of the uncertainty bound. In WVNCB, its weight vector norm is limited not to be larger than a threshold. Both WVNCB and DCRCB belong to a class of diagonal loading methods. The diagonal loading range of WVNCB, which dose not consider negative loading, is extended to match that of DCRCB which can have a negative loading level as well as a positive one. In contrast to the conventional DCRCB with a fixed uncertainty bound, the bound in the proposed method varies such that the weight vector norm constraint is satisfied. Simulation results show that the proposed beamformer outperforms both DCRCB and WVNCB, being far less sensitive to the uncertainty bound than DCRCB.

Networks have gotten bigger recently, and users have a more difficult time finding the information that they want. The use of mobile agents to help users effectively retrieve information has garnered a lot of attention. In this paper, we propose an agent control method for time constrained information retrieval. We pay attention to the highest past score gained by the agents and control the agents with the expectation of achieving better scores. Using computer simulations, we confirmed that our control method gave the best improvement over the whole network while reducing the overall variance. From these results, we can say that our control method improves the quality of information retrieved by the agent.

Identifying the statistical independence of random variables is one of the important tasks in statistical data analysis. In this paper, we propose a novel non-parametric independence test based on a least-squares density ratio estimator. Our method, called least-squares independence test (LSIT), is distribution-free, and thus it is more flexible than parametric approaches. Furthermore, it is equipped with a model selection procedure based on cross-validation. This is a significant advantage over existing non-parametric approaches which often require manual parameter tuning. The usefulness of the proposed method is shown through numerical experiments.

Although a large number of query processing algorithms in spatial network database (SNDB) have been studied, there exists little research on route-based queries. Since moving objects move only in spatial networks, route-based queries, like in-route nearest neighbor (IRNN), are essential for Location-based Service (LBS) and Telematics applications. However, the existing IRNN query processing algorithm has a problem in that it does not consider time and space constraints. Therefore, we, in this paper, propose IRNN query processing algorithms which take both time and space constraints into consideration. Finally, we show the effectiveness of our IRNN query processing algorithms considering time and space constraints by comparing them with the existing IRNN algorithm.

Let T be a tree in which every edge is associated with a real number. The sum of a path in T is the sum of the numbers associated with the edges of the path and its length is the number of the edges in it. For two positive integers L1 ≤ L2 and two real numbers S1 ≤ S2, a path is feasible if its length is between L1 and L2 and its sum is between S1 and S2. We address the problem: Given a tree T, and four numbers, L1, L2, S1 and S2, find the longest feasible path of T. We provide an optimal O(n log n) time algorithm for the problem, where n =|T|.

We propose optimal power allocation schemes for a secondary cognitive user sharing spectrum with a primary user under different interference power constraints in Rayleigh fading channels. Specifically, we consider a practical scenario in which the secondary user has a fixed transmission rate and the instantaneous channel state of the interference channel is not available to the secondary user. Simulation results verify the feasibility of the proposed schemes and evaluate the effective transmission rate loss due to the incomplete channel state information.

This work focuses on a study of strain effects in resistor stress sensors fabricated on (001) silicon and their influences on the determination of piezoresistive (pi) coefficients for the precise measurements of die stresses in electronic packages. We obtained the corrected values of the pi-coefficients by considering the strain effects, without which more than 50% discrepancies may be induced.

We have demonstrated high mobility MOS transistors on high quality epitaxial SiGe films selectively grown on Si (100) substrates. The hole mobility enhancement afforded intrinsically by the SiGe channel (60%) is further increased by an optimized Si cap (40%) process, resulting in a combined ∼100% enhancement over Si channels. Surface orientation, channel direction, and uniaxial strain technologies for SiGe channels CMOS further enhance transistor performances. On a (110) surface, the hole mobility of SiGe pMOS is greater on a (110) surface than on a (100) surface. Both electron and hole mobility on SiGe (110) surfaces are further enhanced in a <110> channel direction with appropriate uniaxial channel strain. We finally address low drive current issue of Ge-based nMOSFET. The poor electron transport property is primarily attributed to the intrinsically low density of state and high conductivity effective masses. Results are supported by interface trap density (Dit) and specific contact resistivity (ρc).

Due to the lack of end-to-end paths between the communication source and destination, the routing of Delay Tolerant Networks (DTN) exploits the store-carry-and-forward mechanism. This mechanism requires nodes with sufficient energy to relay and forward messages in a cooperative and selfless way. However, in the real world, the energy is constrained and most of the nodes exhibit selfish behaviors. In this paper, we investigate the performance of DTN routing schemes considering both the energy constraint and selfish behaviors of nodes. First, we model the two-hop relay and epidemic routing based on a two-dimensional continuous time Markov chain. Then, we obtain the system performance of message delivery delay and delivery cost by explicit expressions. Numerical results show that both the energy constraint and node selfishness reduce the message delivery cost at the expense of increasing the message delivery delay. Furthermore, we demonstrate that the energy constraint plays a more important role in the performance of epidemic routing than that of two-hop relay.

In this paper, we propose a spatially adaptive gradient-projection algorithm for the H.264 video coding standard to remove coding artifacts using local statistics. A hybrid method combining a new weighted constrained least squares (WCLS) approach and the projection onto convex sets (POCS) approach is introduced, where weighting components are determined on the basis of the human visual system (HVS) and projection set is defined by the difference between adjacent pixels and the quantization index (QI). A new visual function is defined to determine the weighting matrices controlling the degree of global smoothness, and a projection set is used to obtain a solution satisfying local smoothing constraints, so that the coding artifacts such as blocking and ringing artifacts can be simultaneously removed. The experimental results show the capability and efficiency of the proposed algorithm.