Stable Scheduling Policies for Maximizing Throughput in Generalized Constrained Queueing Systems

We consider a class of queueing networks referred to as "generalized constrained queueing networks" which form the basis of several different communication networks and information systems. These networks consist of a collection of queues such that only certain sets of queues can be concurrently served. Whenever a queue is served, the system receives a certain reward. Different rewards are obtained for serving different queues, and furthermore, the reward obtained for serving a queue depends on the set of concurrently served queues. We demonstrate that the dependence of the rewards on the schedules alter fundamental relations between performance metrics like throughput and stability. Specifically, maximizing the throughput is no longer equivalent to maximizing the stability region; we therefore need to maximize one subject to certain constraints on the other. Since stability is critical for bounding packet delays and buffer overflow, we focus on maximizing the throughput subject to stabilizing the system. We design provably optimal scheduling strategies that attain this goal by scheduling the queues for service based on the queue lengths and the rewards provided by different selections. The proposed scheduling strategies are however computationally complex. We subsequently develop techniques to reduce the complexity and yet attain the same throughput and stability region. We demonstrate that our framework is general enough to accommodate random rewards and random scheduling constraints.     

Intergranular structure in dental amalgams

The existence of an intergranular precipitate that provides a structural basis of creep, intergranular corrosion and thermal instability in dental amalgams has been in dispute. Also in dispute is a related matter concerning the solid solubility of Sn in ₁. Both these aspects have been examined in this differential scanning calorimetry (DSC) study using the following materials: (a) a conventional ₂–containing amalgam, (b) six ₂–free amalgams, and (c) a series of ₁ specimens with up to 4 wt% Sn. It has been observed that the solid solubility of Sn in ₁ is about 1.0 wt%. Above this Sn concentration, an intergranular precipitate, identified as the ₂ phase of the SnHg system, appears in ₁. This phase is characterized by a low melting temperature (90°C). The existence of this phase in the conventional dental amalgam has been confirmed. It has been observed further that the ₂–free dental amalgams, depending on their nature and Hg contents, may contain ₂ either as a transient or a permanent phase.     

Secrecy Trade-off at the Physical Layer over Mixed Fading Multicast Channels Employing Antenna Diversity

This paper deals with the secrecy performance analysis of a multicast network over mixed fading scenarios in which a cluster of passive eavesdroppers is trying to overhear the secret transmission. Our key contribution is to prevent this malicious attack of the illegitimate receivers. Rayleigh/ Rician mixed fading channels are considered to model alternately the multicast/ eavesdropper and eavesdropper/ multicast channels as such mixed fading scenarios are often encountered in cellular communication where only one link (either multicast or eavesdropper) undergo a line-of-sight propagation path. At first, we derive the probability density functions for the single-input-multiple-output multicast scenarios and then the secrecy analysis is carried out by obtaining closed-form expressions for the performance matrices such as the probability of non-zero secrecy multicast capacity, ergodic secrecy multicast capacity, and secure outage probability for multicasting. The derived expressions are beneficial to investigate how the antenna diversity can combat the detrimental impact of fading as well as the number of multicast users and eavesdroppers, and improve the secrecy level to the acceptable limit. Moreover, the best secure scenario in terms of the secrecy parameters is obtained when the multicast channels undergo Rician fading whereas the eavesdropper channels experience Rayleigh fading. Finally, the analytical expressions are justified via the Monte-Carlo simulations.

     

High Figure of Merit (FOM) of Bragg Modes in Au‐Coated Nanodisk Arrays for Plasmonic Sensing

Gold‐coated nanodisk arrays of nearly micron periodicity are reported that have high figure of merit (FOM) and sensitivity necessary for plasmonic refractometric sensing, with the added benefit of suitability for surface‐enhanced Raman scattering (SERS), large‐scale microfabrication using standard photolithographic techniques and a simple instrumental setup. Gold nanodisk arrays are covered with a gold layer to excite the Bragg modes (BM), which are the propagative surface plasmons localized by the diffraction from the disk array. This generates surface‐guided modes, localized as standing waves, leading to highly confined fields confirmed by a mapping of the SERS intensity and numerical simulations with 3D finite element method. The optimal gold‐coated nanodisk arrays are applied for refractometric sensing in transmission spectroscopy with better performance than nanohole arrays and they are integrated to a 96‐well plate reader for detection of IgY proteins in the nanometer range in PBS. The potential for sensing in biofluids is assessed with IgG detection in 1:1 diluted urine. The structure exhibits a high FOM of up to 46, exceeding the FOM of structures supporting surface plasmon polaritons and comparable to more complex nanostructures, demonstrating that subwavelength features are not necessary for high‐performance plasmonic sensing.     

Cryptanalysis of RSA with two decryption exponents

In this paper, we consider RSA with N=pq, where p,q are of same bit size, i.e., q<p<2q. We study the weaknesses of RSA when multiple encryption and decryption exponents are considered with same RSA modulus N. A decade back, Howgrave-Graham and Seifert (CQRE 1999) studied this problem in detail and presented the bounds on the decryption exponents for which RSA is weak. For the case of two decryption exponents, the bound was N^0.357. We have exploited a different lattice based technique to show that RSA is weak beyond this bound. Our analysis provides improved results and it shows that for two exponents, RSA is weak when the RSA decryption exponents are less than N^0.416. Moreover, we get further improvement in the bound when some of the most significant bits (MSBs) of the decryption exponents are same (but unknown).     

Handling Movement Epenthesis and Hand Segmentation Ambiguities in Continuous Sign Language Recognition Using Nested Dynamic Programming

We consider two crucial problems in continuous sign language recognition from unaided video sequences. At the sentence level, we consider the movement epenthesis (me) problem and at the feature level, we consider the problem of hand segmentation and grouping. We construct a framework that can handle both of these problems based on an enhanced, nested version of the dynamic programming approach. To address movement epenthesis, a dynamic programming (DP) process employs a virtual me option that does not need explicit models. We call this the enhanced level building (eLB) algorithm. This formulation also allows the incorporation of grammar models. Nested within this eLB is another DP that handles the problem of selecting among multiple hand candidates. We demonstrate our ideas on four American Sign Language data sets with simple background, with the signer wearing short sleeves, with complex background, and across signers. We compared the performance with Conditional Random Fields (CRF) and Latent Dynamic-CRF-based approaches. The experiments show more than 40 percent improvement over CRF or LDCRF approaches in terms of the frame labeling rate. We show the flexibility of our approach when handling a changing context. We also find a 70 percent improvement in sign recognition rate over the unenhanced DP matching algorithm that does not accommodate the me effect.     

Fairness of Transitions in Diagnosability of Discrete Event Systems

Failure diagnosability has been widely studied for discrete event system (DES) models because of modeling simplicity and computational efficiency due to abstraction. In the literature it is often held that for diagnosability, such models can be used not only for systems that fall naturally in the class of DES but also for the ones traditionally treated as continuous variable dynamic systems. A class of algorithms for failure diagnosability of DES models has been successfully developed for systems where fairness is not a part of the model. These algorithms are based on detecting cycles in the normal and the failure model that look identical. However, there exist systems with all transitions fair where the diagnosability condition that hinges upon this feature renders many failures non-diagnosable although they may actually be diagnosable by transitions out of a cycle. Hence, the diagnosability conditions based on cycle detection need to be modified to hold for many real-world systems where all transitions are fair. In this work, however, it is shown by means of an example that a system may have some transitions fair and some unfair. A new failure diagnosability mechanism is proposed for DES models with both fair and unfair transitions. Time complexity for deciding diagnosability of DES models with fair and unfair transitions is analyzed and compared with the time complexities of other DES diagnosability analysis methods reported in the literature.     

Spectral entropy and spectral shape based pre-quantization for real time speaker identification system

Pre-processing is one of the vital steps for developing robust and efficient recognition system. Better pre-processing not only aid in better data selection but also in significant reduction of computational complexity. Further an efficient frame selection technique can improve the overall performance of the system. Pre-quantization (PQ) is the technique of selecting less number of frames in the pre-processing stage to reduce the computational burden in the post processing stages of speaker identification (SI). In this paper, we develop PQ techniques based on spectral entropy and spectral shape to pick suitable frames containing speaker specific information that varies from frame to frame depending on spoken text and environmental conditions. The attempt is to exploit the statistical properties of distributions of speech frames at the pre-processing stage of speaker recognition. Our aim is not only to reduce the frame rate but also to maintain identification accuracy reasonably high. Further we have also analyzed the robustness of our proposed techniques on noisy utterances. To establish the efficacy of our proposed methods, we used two different databases, POLYCOST (telephone speech) and YOHO (microphone speech).     

An imperfect production process for time varying demand with inflation and time value of money – An EMQ model

The paper deals with an economic manufacturing quantity (EMQ) model for time-dependent (quadratic) demand pattern. Every manufacturing sector wants to produce perfect quality items. But in long run process, there may arise different types of difficulties like labor problem, machinery capabilities problems, etc., due to that the machinery systems shift from in-control state to out-of-control state as a result the manufacturing systems produce imperfect quality items. The imperfect items are reworked at a cost to become the perfect one. The rework cost may be reduced by improvements in product reliability i.e., the production process depend on time and also the reliability parameter. We want to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process using Euler–Lagrange theory to build up the necessary and sufficient conditions for optimality of the dynamic variables. Finally, a numerical example is discussed to test the model which is illustrated graphically also.