2D and 3D image localization,compression and reconstruction using new hybrid moments

In this article, we will present a new set of hybrid polynomials and their corresponding moments, with a view to using them for the localization, compression and reconstruction of 2D and 3D images. These polynomials are formed from the Hahn and Krawtchouk polynomials. The process of calculating these is successfully stabilized using the modified recurrence relations with respect to the n order, the variable x and the symmetry property. The hybrid polynomial generation process is carried out in two forms: the first form contains the separable discrete orthogonal polynomials of Krawtchouk–Hahn (DKHP) and Hahn–Krawtchouk (DHKP). The latter are generated as the product of the discrete orthogonal Hahn and Krawtchouk polynomials, while the second form is the square equivalent of the first form, it consists of discrete squared Krawtchouk–Hahn polynomials (SKHP) and discrete polynomials of Hahn–Krawtchouk squared (SHKP). The experimental results clearly show the efficiency of hybrid moments based on hybrid polynomials in terms of localization property and computation time of 2D and 3D images compared to other types of moments; on the other hand, encouraging results have also been shown in terms of reconstruction quality and compression despite the superiority of classical polynomials.

     

Architectural Design,Improvement, and Challenges of Distributed Software-Defined Wireless Sensor Networks

Wireless Personal Communications - Software-defined networking (SDN) is widely perceived to simplify network management and monitoring. The introduction of the SDN model into wireless sensor...     

A hybrid multiagent routing approach for wireless ad hoc networks

Wireless ad-hoc networks are infrastructureless networks that comprise wireless mobile nodes able to communicate each other outside wireless transmission range. Due to frequent network topology changes in one hand and the limited underlying bandwidth in the other hand, routing becomes a challenging task. In this paper we present a novel routing algorithm devoted for mobile ad hoc networks. It entails both reactive and proactive components. More precisely, the algorithm is based on ant general behavior, but differs from the classic ant methods inspired from Ant-Colony-Optimization algorithm [1]. We do not use, during the reactive phase, a broadcasting technique that exponentially increases the routing overhead, but we introduce a new reactive route discovery technique that considerably reduces the communication overhead. In the simulation results, we show that our protocol can outperform both Ad hoc On-demand Distance Vector (AODV) protocol [2], one of the most important current state-of-the-art algorithms, and AntHocNet protocol [5], one of the most important ant-based routing algorithms, in terms of end-to-end delay, packet delivery ratio and the communication overhead.     

On the design of highly linear CMOS digitally programmable operational transconductance amplifiers for low and high-frequency applications

This paper proposes a novel highly linear digitally programmable fully differential operational transconductance amplifier (DPOTA) circuit. Two versions of the proposed DPOTA structure are designed. The first version is optimized for high-frequency operation with current division networks designated to 3-bit control code words. On the other hand, the second version is optimized for low-frequency operation with 4-bit control code words. The third-order harmonic distortion (HD3) of the first DPOTA version remains below ? 66 dB up to 0.4 V differential input voltage at 10 MHz frequency. The second DPOTA version achieved HD3 of ? 70 dB with an amplitude of 20 mV_p–p and at 100 Hz frequency. The proposed circuits are designed and simulated in 90 nm CMOS model, BSIM4 (level 54) under a balanced 1.2 V supply voltage.     

New CMOS Fully‐Differential Transconductor and Application to a Fully‐Differential Gm‐C Filter

A new CMOS voltage‐controlled fully‐differential transconductor is presented. The basic structure of the proposed transconductor is based on a four‐MOS transistor cell operating in the triode or saturation region. It achieves a high linearity range of ± 1 V at a 1.5 V supply voltage. The proposed transconductor is used to realize a new fully‐differential Gm‐C low‐pass filter with a minimum number of transconductors and grounded capacitors. PSpice simulation results for the transconductor circuit and its filter application indicating the linearity range and verifying the analytical results using 0.35 μm technology are also given.     

Harvesting Lost Photons: Plasmon and Upconversion Enhanced Broadband Photocatalytic Activity in Core@Shell Microspheres Based on Lanthanide‐Doped NaYF4, TiO2, and Au

Efficiently harvesting solar energy for photocatalysis remains very challenging. Rational design of architectures by combining nanocomponents of radically different properties, for example, plasmonic, upconversion, and photocatalytic properties, offers a promising route to improve solar energy utilization. Herein, the synthesis of novel, plasmonic Au nanoparticle decorated NaYF₄:Yb³⁺, Er³⁺, Tm³⁺‐core@porous‐TiO₂‐shell microspheres is reported. They exhibit high surface area, good stability, broadband absorption from ultraviolet to near infrared, and excellent photocatalytic activity, significantly better than the benchmark P25 TiO₂. The enhanced activity is attributed to synergistic effects from nanocomponents arranged into the nanostructured architecture in such a way that favors the efficient charge/energy transfer among nanocomponents and largely reduced charge recombination. Optical and energy‐transfer properties are modeled theoretically to support our interpretations of catalytic mechanisms. In addition to yielding novel materials and interesting properties, the current work provides physical insights that can contribute to the future development of plasmon‐enhanced broadband catalysts.     

LAS Detector with Soft-Output MMSE Initialization Under Imperfect Channel Estimation and Channel Correlation

Wireless Personal Communications - This paper proposes a modified likelihood ascent search (LAS) algorithm for multiple-input multiple-output (MIMO) systems under correlated channel and imperfect...     

Best Minimum Summation Scheduler for Long Term Evolution

Resource scheduling in Long Term Evolution (LTE) is an open and rising issue. It has an enormous impact on the entire system performance. Due to the nature of LTE system, the scheduler has to be designed carefully. It has to overcome many challenges such as limited processing time and the high dynamic behavior. This paper proposes a novel scheduling policy for the MAC layer in LTE called the Best Minimum Summation (BMS). The main aim of this scheduling policy is to achieve high performance with low complexity. Three sub-schedulers have been developed. Each one of these schedulers deals with scheduling table in different dimension. The first one operates on the scheduling table through the user dimension (BMS.UE); while the second one operates on the scheduling table through the resource block dimension (BMS.RB). The third scheduler operates on the scheduling table correlating both of these dimensions (BMS.2D). All of the proposed solutions were intensively evaluated in a system level simulator. Three performance metrics were used which are throughput, error rate and fairness. The results have shown that the ability of the BMS.UE scheduler to outperform other existing schedulers of LTE.     

Catalyst Design by NH4OH Treatment of USY Zeolite

Hierarchical zeolites are a class of superior catalysts which couples the intrinsic zeolitic properties to enhanced accessibility and intracrystalline mass transport to and from the active sites. The design of hierarchical USY (Ultra‐Stable Y) catalysts is achieved using a sustainable postsynthetic room temperature treatment with mildly alkaline NH₄OH (0.02 m ) solutions. Starting from a commercial dealuminated USY zeolite (Si/Al = 47), a hierarchical material is obtained by selective and tuneable creation of interconnected and accessible small mesopores (2–6 nm). In addition, the treatment immediately yields the NH₄⁺ form without the need for additional ion exchange. After NH₄OH modification, the crystal morphology is retained, whereas the microporosity and relative crystallinity are decreased. The gradual formation of dense amorphous phases throughout the crystal without significant framework atom leaching rationalizes the very high material yields (>90%). The superior catalytic performance of the developed hierarchical zeolites is demonstrated in the acid‐catalyzed isomerization of α‐pinene and the metal‐catalyzed conjugation of safflower oil. Significant improvements in activity and selectivity are attained, as well as a lowered susceptibility to deactivation. The catalytic performance is intimately related to the introduced mesopores, hence enhanced mass transport capacity, and the retained intrinsic zeolitic properties.     

A hybrid classifier fusion approach for motor unit potential classification during EMG signal decomposition

In this paper, we propose a hybrid classifier fusion scheme for motor unit potential classification during electromyographic (EMG) signal decomposition. The scheme uses an aggregator module consisting of two stages of classifier fusion: the first at the abstract level using class labels and the second at the measurement level using confidence values. Performance of the developed system was evaluated using one set of real signals and two sets of simulated signals and was compared with the performance of the constituent base classifiers and the performance of a one-stage classifier fusion approach. Across the EMG signal data sets used and relative to the performance of base classifiers, the hybrid approach had better average classification performance overall. For the set of simulated signals of varying intensity, the hybrid classifier fusion system had on average an improved correct classification rate (CCr) (6.1%) and reduced error rate (Er) (0.4%). For the set of simulated signals of varying amounts of shape and/or firing pattern variability, the hybrid classifier fusion system had on average an improved CCr (6.2%) and reduced Er (0.9%). For real signals, the hybrid classifier fusion system had on average an improved CCr (7.5%) and reduced Er (1.7%).