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In order to enhance the robustness of image compression sensing system and reduce the mutual coherence between measurement matrix and sparse basis, this paper proposes an image measurement matrix optimization algorithm based on posterior information. Based on the traditional measurement matrix optimization model, the proposed algorithm considers the image reconstruction error from the OMP algorithm and uses it as a regular term. Matrix F-norm expansion and singular value decomposition are used to reduce the computational complexity and ensure the convergence of algorithm. Besides, the gradient matrix method is used to iteratively solve the measurement matrix. The proposed measurement matrix optimization model makes full use of the reconstruction error information of the image itself, not only improves the robustness of image compression sensing system, but also reduces the mutual coherence between the measurement matrix and the sparse basis. Experiments results show that compared with the state-of-the-art measurement matrix optimization algorithms, the proposed algorithm can reduce the average correlation coefficient more effectively, and the peak signal-to-noise ratio of the image can be increased by up to 1.2 dB.

International audience; In dataflow representations for signal processing systems, applications are represented as directed graphs in which vertices represent computations and edges correspond to buffers that store data as it passes among computations. The edges in the dataflow graph are single-input, single-output components that manage data transmission in a first-in, first-out (FIFO) fashion. In this paper, we formulate the vertices and edges into concepts called "active blocks" and "passive blocks", respectively in the graph representation. Computation in the dataflow graph is represented as "active blocks", while the concept of dataflow buffers is represented as "passive blocks". Like dataflow edges, passive blocks are used to store data during the intervals between its production and consumption by actors. However, passive blocks can have multiple inputs and multiple outputs, and can incorporate operations on and rearrangements of the stored data subject to certain constraints. We define a form of flowgraph representation that is based on replacing dataflow edges with the proposed concept of passive blocks. We present a structured design methodology for utilizing this new form of signal processing flowgraph, and demonstrate its application to improving memory management efficiency, and execution time performance.

Herein we present an investigation into the scope and mechanism for the synthesis of cyclopentyl and heterocyclic fused pyridones from the corresponding enyne amides. In the presence of a secondary amine, cyclization proceeds smoothly to form 5,6-bicyclic pyridones in 12-90% yield. The cyclization fails with enyne amides of six-membered and larger ring systems. The ring closure reaction is catalytic in nature with respect to the secondary amine and proceeds via sequential 1,6-addition of the amine, 6-exo-trig ring closure of the iminium intermediate, and subsequent elimination of the secondary amine. Computations show reduced conjugation between the enyne and amide for six-membered and larger systems, thereby providing an explanation for the inability of such enyne amides to form fused pyridones.

Driven by recent advances in video capture technology, multispectral video analytics is gaining increased interest due to its potential to exploit increased spectral resolution and diversity across sets of multispectral bands. In this chapter, methods are developed for integrated band subset selection and video processing parameter optimization in multispectral video processing. The methods are designed to systematically trade off processing requirements and accuracy, as well as to maximize accuracy for a given set of processed bands. Using the proposed methods together with the Dynamic Data Driven Applications Systems (DDDAS) paradigm, dynamic constraints and measurements can be incorporated into embedded software adaptation in real-time, bandwidth-constrained applications. While the methods developed in the chapter are demonstrated concretely in the context of background subtraction, the underlying approach is more general and can be adapted to other video analysis solutions.

This paper presents novel models and design optimization methods for gapless deep waveform applications, where continuous streams of data must be processed reliably without dropping any samples. The approaches developed in this paper involve unified dataflow-based modeling of the interfaces and signal processing functionality of gapless deep waveform analysis. Bottleneck actors (computational modules) in the resulting dataflow model are then identified and tackled with approximate computing techniques. These techniques are developed and configured carefully so that large performance gains are achieved while keeping reductions in signal processing accuracy to a manageable level. Efficient actor- and graph-level code optimization techniques are also applied to further improve real-time performance. In addition to providing accurate, real-time processing on the experimental platform used in our experiments, the algorithm- and model-based formulation of the contributions in this part promotes their general utility in deep waveform analysis and their retargetability to other platforms. publishedVersion

Nucleophilic addition of Grignard reagents to tetrahydro-β-carboline (THC) N-sulfonyl N,S-acetal generates exclusively cis-1,3-disubstituted THCs with a unique 1,3-diaxial conformation. The stereochemical relationship of the 1,3-substituents was confirmed by 2-dimensional NMR spectroscopy and X-ray crystallography. The mechanism of the reaction is proposed based on crystal structures and molecular orbital calculations.

The dataflow-model of computation is widely used in design and implementation of signal processing systems. In dataflow-based design processes, scheduling—the assignment and coordination of computational modules across processing resources—is a critical task that affects practical measures of performance, including latency, throughput, energy consumption, and memory requirements. Dataflow schedule graphs (DSGs) provide a formal abstraction for representing schedules in dataflow-based design processes. The DSG abstraction allows designers to model a schedule as a separate dataflow graph, thereby providing a formal, abstract (platform- and language-independent) representation for the schedule. In this paper, we introduce a design methodology that is based on explicit specifications of application graphs and schedules as cooperating dataflow models. We also develop new techniques and tools for automatically synthesizing efficient implementations on multicore platforms from these coupled application and schedule models. We demonstrate the proposed methodology and synthesis techniques through a case study involving real-time detection of people and vehicles using acoustic and seismic sensors.

In this work, a facile synthesis strategy was used to fabricate the carbon-coated new spinel Fe1.5V1.5O4 nanorods. The initial obtained precursor was prepared by a facile solvothermal process. After it was treated by different methods, hierarchical Fe1.5V1.5O4@C nanorods consisted of Fe1.5V1.5O4 primary nanoparticles with different particle sizes could be obtained. As anode materials for lithium ion batteries, the hierarchical Fe1.5V1.5O4@C nanorods composed of smaller primary particles show higher reversible capacity, better cycling performance and rate capability. Its reversible capacity can retain at 753 mAh g−1 and 709 mAh g−1 even cycled at 0.5 A g−1 and 2 A g−1 after 100 cycles and 1000 cycles, respectively. The excellent lithium storage performance of carbon-coated Fe1.5V1.5O4 nanorods is dependent on the spinel crystal structure, unique hierarchical structure, and synergistic effect of active materials and carbon layer in the composites. The results of CV curves imply that the overall capacity upon cycling is determined by both of the surface-controlled capacitive contribution and diffusion-controlled Li+ intercalation process.

The composites of N-doped carbon-coated Fe3O4 nanoclusters (Fe3O4@NC) were prepared by a facile preparation process. The microwave-assisted solvothermal method was first employed to obtain Fe3O4 nanoclusters, and then using dopamine as carbon sources, the N-doped carbon-coated Fe3O4 nanoclusters were obtained by calcining in vacuum. By changing the amount of dopamine and calcination temperature, a series of products with different carbon-coating thickness and crystallinity were obtained. The composite synthesized by adding 0.08 g dopamine hydrochloride and calcining at 500 °C exhibits ultra-long cycle life and good rate capability, its reversible capacity can retain at 445 mAh g−1 after 2000 cycles even at a current density of 2 A g−1. The results indicate that the hierarchical Fe3O4@NC composites are promising high-performance anode materials for lithium ion batteries.

We proposed a new approach to determination of Judd-Ofelt intensity parameters of Er 3+ doped phosphors via their absorption spectra. To validate this approach, JO parameters of Er 3+ doped BaGd 2 ZnO 5 /PMMA and NaYF 4 /PMMA composites were calculated and in a good agreement with the other glass and crystal. The spontaneous radiative transition probability, branching ratio, and radiative lifetime of the optical transitions were calculated by using the Judd-Ofelt theory. Intense near-infrared emission at 1553 nm was observed under 980 nm laser diode excitation at room temperature. The samples possessing high full-width at half-maximum reach 85 nm have potential application in broadband optical amplifier.

Video analytics plays an important role in a wide variety of defense-, monitoring- and surveillance-related systems for air and ground environments. In this context, multispectral video processing is attracting increased interest in recent years, due in part to technological advances in video capture. Compared with monochromatic video, multispectral video offers better spectral resolution, and different bands of multispectral video streams can enhance video analytics capabilities in different ways. For example, the infrared bands can provide better separation of shadows from objects, and improved spatial resolution in scenes that are impaired by fog or haze [16].

Er3+/Yb3+ co-doped BaGd2CuO5 upconversion luminescent materials are obtained by solid phase method. Rietveld refinement on X-ray diffraction data indicates that Er3+/Yb3+ ions are inclined to occupy the Gd(1) site in the structure of BaGd2CuO5 (green phase). Two green emission peaks located at 523 nm and 547 nm have been produced by the excitation of 971 nm LD. The fluorescence intensity ratio (FIR) of the two green emission peaks have been investigated in the temperature range of 290 K–594 K. The maximum sensitivity derived from the FIR technique of the green upconversion emission is approximately 0.0038 K−1, and it has a high transmission power at low excitation density. This result implies that the Er3+/Yb3+ co-doped BaGd2CuO5 phosphors can play an important role in temperature measurements with a better sensitivity.

La2W2O9:2%Eu3+ phosphors were synthesized by a typical hydrothermal procedure. The samples were characterized by X-ray diffraction and scanning electron microscope (SEM). X-ray diffraction analysis showed that a stock solution pH value equal to 9 is the ideal value, while the crystallization of the hydroxyl sodium yttrium tungstate crystal is improved by increasing the PH values of stock solution within limits. Meanwhile, SEMs of different pH values were recorded. Additionally, photoluminescence excitation (PLE) and emission (PL) spectra were measured. It was found that this phosphor can be effectively excited by C–T band (266 nm) and ultraviolet light 342 nm. The wavelengths at 342 nm fit in nicely with the whole visible region, thus the La2W2O9:2%Eu3+ phosphors emit white light. Furthermore, the annealing temperature’s impact on PLE and PL spectra was also studied. The Eu3+-doped La2W2O9 phosphor may be a better candidate than current method for solid-state lighting applications.

International audience; Current trends in high performance and embedded computing include design of increasingly complex hardware architectures with high parallelism, heterogeneous processing elements and non-uniform communication resources. In order to take hardware and software design decisions, early evaluations of the system non-functional properties are needed. These evaluations of system efficiency require Electronic System-Level (ESL) information on both the algorithms and the architecture. Contrary to algorithm models for which a major body of work has been conducted on defining formal Models of Computation (MoCs), architecture models from the literature are mostly empirical models from which reproducible experimentation requires the accompanying software. In this paper, a precise definition of a Model of Architecture (MoA) is proposed that focuses on reproducibility and abstraction and removes the overlap previously existing between the notions of MoA and MoC. A first MoA, called the Linear System-Level Architecture Model (LSLA), is presented. To demonstrate the generic nature of the proposed new architecture modeling concepts, we show that the LSLA Model can be integrated flexibly with different MoCs. LSLA is then used to model the energy consumption of a State-of-the-Art Multiprocessor System-on-Chip (MPSoC) when running an application described using the Synchronous Dataflow (SDF) MoC. A method to automatically learn LSLA model parameters from platform measurements is introduced. Despite the high complexity of the underlying hardware and software, a simple LSLA model is demonstrated to estimate the energy consumption of the MPSoC with a fidelity of 86%.

In dataflow representations for signal processing systems, applications are represented as directed graphs in which vertices represent computations and edges correspond to buffers that store data as it passes between computations. The buffers are single-input, single-output components that manage data in a first-in, first-out (FIFO) fashion. In this paper, we generalize the concept of dataflow buffers with a concept called "passive blocks". Like dataflow buffers, passive blocks are used to store data during the intervals between its generation by producing actors, and its use by consuming actors. However, passive blocks can have multiple inputs and multiple outputs, and can incorporate operations on and rearrangements of the stored data subject to certain constraints. We define a form of flowgraph representation that is based on replacing dataflow edges with the proposed concept of passive blocks. We present a structured design methodology for utilizing this new form of signal processing flowgraph, and demonstrate its utility in improving memory management efficiency, and execution time performance., This is a pre-publication version of a paper that has been accepted for publication in the 2018 IEEE International Workshop on Signal Processing Systems

Ho3+ ions doped tellurite-borate glass samples with varying compositions were prepared. The compositional dependence on phenomenological Judd-Ofelt parameters was compared in different kinds of rare earth ions doped tellurite-borate glasses. Two methods were used to obtain radiative transition probability of 5I7 level with the aim of assuring the fitting quality. The integral absorption cross-sections and line shapes corresponding to 5I8→5G6 and 5I8→5I7 transition of Ho3+ ions were investigated in tellurite-borate glasses. The obtained data indicated that the integral absorption cross-sections corresponding to 5I8→5G6 transition of Ho3+ ions mainly depended on phenomenological Judd-Ofelt parameter, Ω2, because 5I8→5G6 transition belonged to hypersensitive transitions, which led to a larger Ω2 value. The change of line shapes of absorption spectra corresponding to 5I8→5G6 and 5I8→5I7 transitions of Ho3+ ions came from the lower energy regions, which could be attributed to the changed distribution of Stark levels and thermal population.

Yb3+ doped BaGd2ZnO5 phosphor was synthesized via sol–gel method. X-ray diffraction, scanning electron microscopy and photoluminescence spectra were employed to characterize the as-obtained products. Upon 274 nm excitation, a single strong narrow-band emission from 2F5/2 → 2F7/2 of Yb3+ ion around 977 nm was obtained in Yb3+ doped BaGd2ZnO5 phosphor, which was well suited to efficient absorption in a silicon solar cell. After adding Ce3+ into Yb3+-doped BaGd2ZnO5, the excitation spectra of samples monitored at 977 nm indicated that the excitation peaks were in the broad range from 230 nm to 400 nm, which covered ultraviolet and blue light with poor solar cell spectral response. Furthermore, Er3+ was introduced into Yb3+-doped BaGd2ZnO5 phosphor to prove the high energy transfer efficiency from Gd3+ ion to Yb3+ ion by comparing it with that of Er3+ ion to Yb3+ ion. With access to broad-band absorption, narrow-band emission as well as high energy transfer efficiency, Ce3+, Yb3+-codoped BaGd2ZnO5 may have potential applications in modifying the solar spectrum to enhance the efficiency of silicon solar cells.

Heavily Eu3+-doped BaCa2In6O12 phosphors were prepared by conventional solid-state reaction, and its structural properties were investigated by means of Rietveld refinement method using an X-ray source. XRD patterns confirm the hexagonal phase of BaCa2In6O12: Eu3+ phosphors. The obtained spectrum data indicate that the emission spectra of Ba1−xEuxCa2In6O12 samples excited at 393 nm exhibit a series of shaped peaks assigned to the 5D0,1,2,3 →7FJ (J = 0,1,2,3,4) transitions. Luminescence from the higher excited states, such as 5D1, 5D2, and 5D3, were also observed even though the Eu3+ concentration was up to x = 0.4. More importantly, the Ba1−xEuxCa2In6O12 phosphor still emits white luminescence, when the Eu3+ ion concentration is up to x = 0.07 before concentration quenching is observed, which shows that the phosphor is a promising single-phase phosphor for near ultraviolet (NUV) light-emitting diodes (LED). Furthermore, the temperature's impact on white luminescent properties was studied. Finally, a white-light-emitting diodes (W-LEDs) fabricated with the Ba0.95Eu0.05Ca2In6O12 phosphor incorporated with an encapsulant in ultraviolet LEDs (λmax = 395 nm) is discussed.

A series of BaIn6Y2O13:Yb(3+), Er(3+), Tm(3+) phosphors with different dopant concentrations have been successfully synthesized by a sol-gel method. In order to obtain efficient white light emitting samples, tri-doped and biphasic samples were prepared. Afterwards, we carried out a systematic study on the up-conversion luminescence (UCL) properties of the samples as functions of doping concentrations and excitation densities. The up-conversion (UC) white light emission powers and efficiencies of samples with different dopant concentrations at different excitation power densities were obtained. The highest white UCL efficiency of up to 0.38% was achieved at excitation densities down to 17.5 W cm(-2) in the biphasic samples. More importantly, we demonstrated that the UC materials with higher efficiency do not necessarily have stronger emission power, and the emission power is the most important parameter. A maximum emission power of up to 1.23 mW was obtained. Furthermore, the impact of temperature on the white UCL was studied, and transparent polymer composites that can emit white light were synthesized by doping BaIn6Y2O13 samples into polymethylmethacrylate (PMMA).

Neural decoding focuses on predicting behavior variables based on neural activities. Linear discriminant analysis (LDA) has been successfully used in pattern recognition and machine learning to find the set of discriminant vectors to characterize two or more classes of objects. However, LDA cannot be directly used for real-time neural decoding problems. In this paper, we propose an incremental LDA with online learning method to overcome this limitation. The dataflow techniques are implemented in the LIDE (LIghtweight Dataflow Environment), which provides capabilities to systematically optimize and integrate embedded software components for signal and information processing. Using these techniques along with online learning, an efficient real-time neural decoding system can be attained.

In this paper, we propose a novel framework, called Hierarchical MDP framework for Compact System-level Modeling (HMCSM), for design and implementation of adaptive embedded signal processing systems. The HMCSM framework applies Markov decision processes (MDPs) to enable autonomous adaptation of embedded signal processing under multidimensional constraints and optimization objectives. The framework integrates automated, MDP-based generation of optimal reconfiguration policies, dataflow-based application modeling, and implementation of embedded control software that carries out the generated reconfiguration policies. HMCSM systematically decomposes a complex, monolithic MDP into a set of separate MDPs that are connected hierarchically, and that operate more efficiently through such a modularized structure. We demonstrate the effectiveness of our new MDP-based system design framework through experiments with an adaptive wireless communications receiver.

The fluorescence intensity ratio (FIR) of the two green emission bands centered at 524 and 547 nm in Yb3+/Er3+ co-doped La2O2S phosphor was studied as a function of temperature in the range 300–573 K for optical temperature measurement. Upconversion phosphor La2O2S: Yb3+, Er3+ show intense double-band green emission at low pump power, and the maximum sensor sensitivity derived from the FIR of the upconversion green emissions was approximately 0.008 K−1. This indicates that the phosphor has potential application in optical temperature sensors. Based on the Judd–Ofelt theory, an interpretation on how the factors influence the sensitivity of temperature sensing was proposed for the first time.

Yb3+/Er3+ codoped La2S3 upconversion (UC) phosphors have been synthesized using high-temperature solid-state method. Under 971-nm excitation, the maximum luminescence power can reach 0.64 mW at the excitation power density of 16 W/cm2 and an absolute power yield of 0.36% was determined by an absolute method at the excitation power density of 3 W/cm2, and the quantum yield of La2S3:Yb3+, Er3+ (green ~0.18%, red ~0.03%, integration ~0.21) was comparable to that of NaYF4:Yb3+, Er3+ nanocrystals (integration ~0.005–0.30). Frequency upconverted emissions from two thermally coupled excited states of Er3+ were recorded in the temperature range 100–900 K. The maximum sensitivity of temperature sensing is 0.0075 K−1. As the excitation power density increases, the temperature of host materials rapidly rises and the top temperature can reach to 600 K. Given the intense UC emission, high sensitivity, as well as good photothermal stability, La2S3:Yb3+/Er3+ phosphor can become a promising composite material for photothermal ablation of cancer cells possessing the functions of temperature sensing and in vivo imaging.

We observed unexpected thiazole 1B formation when 2,6-dichlorobenzothioamide 1 and ethyl bromopyruvate were reacted under basic conditions at elevated temperatures in ethanol. Thiazole 1B, regio-isomeric to that expected under conventional Hantzsch conditions, was extensively characterized and later confirmed by single crystal X-ray structure. We carried out this transformation with several substituted benzothioamides and found that the formation of the unexpected thiazole regio-isomer was highly dependent on the steric as well as the electronic characteristics of the ortho-substituents on the phenyl ring. A mechanism to account for this novel transformation was proposed.

Herein we report our lead optimization effort to identify potent, selective, and orally bioavailable TYK2 inhibitors, starting with lead molecule 3. We used structure-based design to discover 2,6-dichloro-4-cyanophenyl and (1R,2R)-2-fluorocyclopropylamide modifications, each of which exhibited improved TYK2 potency and JAK1 and JAK2 selectivity relative to 3. Further optimization eventually led to compound 37 that showed good TYK2 enzyme and interleukin-12 (IL-12) cell potency, as well as acceptable cellular JAK1 and JAK2 selectivity and excellent oral exposure in mice. When tested in a mouse IL-12 PK/PD model, compound 37 showed statistically significant knockdown of cytokine interferon-γ (IFNγ), suggesting that selective inhibition of TYK2 kinase activity might be sufficient to block the IL-12 pathway in vivo.

The current trend in high performance and embedded signal processing consists of designing increasingly complex heterogeneous hardware architectures with non-uniform communication resources. In order to take hardware and software design decisions, early evaluations of the system non-functional properties are needed. These evaluations of system efficiency require high-level information on both the algorithms and the architecture. In this paper, we define the notion of Model of Architecture (MoA) and study the combination of a Model of Computation (MoC) and an MoA to provide a design space exploration environment for the study of the algorithmic and architectural choices. A cost is computed from the mapping of an application, represented by a model conforming a MoC onto an architecture represented by a model conforming an MoA. The cost is composed of a processing-related part and a communication-related part. It is an abstract scalar value to be minimized and can represent any non-functional requirement of a system such as memory, energy, throughput or latency.