IDPF Readium SDK 기반의 전자책 DRM 호환성에 관한 연구

Energy efficiency has become a primary concern in the design of multimedia digital systems, particularly when targeting mobile devices. Approximate computing is a highly promising approach to address this challenge. This paper presents an architectural exploration in a variable block size motion estimation (VBSME) architecture using imprecise Lower-Part-OR Adders (LOA). These adders were applied to Sum of Absolute Differences units (SAD) in order to reduce the energy consumption while introducing a minimum impact on the coding efficiency. Three VBSME architectures with LOA operators were developed by considering different imprecision levels. The conducted evaluations, performed using the High-Efficiency Video Coding standard (HEVC) reference software, showed that this technique introduces a negligible impact on the coding efficiency (between 0.6% and 2.5% increase of the BD-Rate). Nevertheless, when the designed architectures were synthesized for a 45nm standard cells technology, significant power savings were observed (between 7% and 11.5%, depending on the used LOA version), demonstrating the viability and significant gains of the proposed approach.

The rapid advancement of technology has made it imperative for supply chains to adapt to the changing landscape. Blockchain technology holds immense potential to transform supply chain processes, but the challenge lies in identifying the most suitable blockchain characteristics to meet the various performance indicators of a supply chain. To overcome this challenge, this study aims to prioritize the most critical blockchain characteristics in a supply chain. The study adopts a two-stage Quality Function Deployment (QFD) methodology to rank blockchain characteristics based on supply chain and software requirements. The methodology evaluates the supply chain performance indicators using the Supply Chain Operations Reference (SCOR) model and software needs using the International Organization for Standardization (ISO) software quality characteristics. After determining the problematic SCOR and ISO software-related metrics, the study utilizes the QFD Stage 1 to obtain the weights of ISO software characteristics and employs the Fuzzy Cognitive Map (FCM) to determine the most crucial blockchain characteristics for QFD Stage 2. The results of this study show that the top priorities for blockchain characteristics in a supply chain are smart contract functionality, privacy, transaction per second, tokenization, security, permissioned network, scalability, cost, modularity, and licensing, in order of importance.

Missing data are common in clinical trials and could lead to biased estimation of treatment effects. The National Research Council (NRC) report suggests that sensitivity analysis on missing data mechanism should be a mandatory component of the primary reporting of findings from clinical trials, and regulatory agencies are requesting more thorough sensitivity analyses from sponsors. However, recent literature research showed that missing data were almost always inadequately handled. This is partially due to the lack of standard software packages and straightforward implementation platform. With recent availability of flexible Bayesian software packages such as WinBUGS, SAS Proc MCMC, and Stan, it is relatively simple to develop Bayesian methods to address complex missing data problems while incorporating the uncertainty. In this article, we present a case study from the DIA Bayesian Scientific Working Group (BSWG) on Bayesian approaches for missing data analysis. We illustrate how to use Bayesian approaches to fit a few commonly used frequentist missing data models. The properties, advantage, and flexibility of the Bayesian analysis methods will be discussed using a case study based on a schizophrenia clinical trial. Supplementary materials for this article are available online.

Continuous improvement of software development capability is fundamental for organizations to thrive in competitive markets. Nevertheless, software process improvement (SPI) implementation based on software process reference models and standards is a complex and long-term endeavor that requires investment of large sums of money. This paper describes a national program for SPI in Brazilian organizations. The main goal of this initiative is to develop and disseminate a Brazilian software process model (named MPS Model) aiming to establish a feasible pathway for organizations to achieve benefits from implementing SPI at reasonable costs, especially SMEs. This paper presents the main components of MPS Model. The results of MPS Model adoption and dissemination in Brazilian software industry are also presented in this paper. Although the main focus of the MPS Model is on SMEs, the model demonstrated to be adequate to support SPI implementation and assessment in large organizations.

In 1999 was issued commonly by EC, IAEA and OECD the document “A Proposed Standardised List of Items for Costing Purposes in the Decommissioning of Nuclear Installations” (PSL). The main aim of this document was to establish a standard platform for structure of presented decommissioning costs. The decommissioning costs calculated in various projects have in general different structure and for presenting the decommissioning costs in PSL structure, additional recalculation or rearrangement of data are needed. This can increase the uncertainty of data or it is not sure if they really reflect the cost defined in the PSL structure. The paper describes a newly developed cost calculation code, which respect the PSL structure. The calculated costs data are compatible with the standardised structure. The code is intended to use for decommissioning planning of a NPP with a non-standard radiological situation, shutdown after an accident For this purpose the code has an integrated material and radionuclide resolved radioactivity flow control system in calculation process which enables a direct calculation link between the input material and radiological inventory data and the calculated costs and other decommissioning parameters for increasing the accuracy of calculated data. The code has an integrated cost allocating system for generating of user defined working breakdown structure of the decommissioning project with allocated costs calculated in PSL structure. The working breakdown structure can be on-line optimised using the standard Microsoft Office Project Planning tool software.

Predictive fast Motion Estimation (ME) algorithms have been widely used in video CODECs due to their performance efficiency and low computational complexity. In this thesis, a new block-based fast motion estimation technique named Dynamic Predictive Search Algorithm (DPSA) is developed, which can be considered in predictive zonal search category. The proposed approach is based on the observation that temporally and spatially adjacent macro-blocks are not just statically correlated, but also dynamic alterations in their motion content are highly coherent. DPSA introduces a new set of six candidate predicted motion vectors. For early termination criteria, DPSA modifies termination procedure of already existing EPZS algorithm. Performance of this newly proposed algorithm has been compared to four other state-of-the-art algorithms implemented on JVT, H.264 standard software platform. Experimental results have proven that DPSA accomplishes up to 38% compression ratio enhancement achieved by a process with more 14.75% less computational complexity and up to0.47 dB higher PSNR values over the EPZS. It also manages to have up to 13% speed up over EPZS algorithm. Because of its simplicity and low computational complexity DPSA is energy efficient for portable video processing in computation- or power-constrained applications and easy to be implemented on both FPGA- and Microcontroller-based embedded systems. Also, higher compression ratio makes DPSA more compatible with limited capacity storage media, and limited band-width transmission networks.

The Automotive Open System Architecture (AUTOSAR) has recently beenintroduced to most automotive software in Europe with the aim of reducing the development cost. AUTOSAR is a standardized software platform for automotive softwarethat consists of more than 80 modules with a variety of functions. The real-time operating system (OS) is a module in AUTOSAR that plays a critical role in these modules, and it contains a memory protection function for functional safety. Although automotive software including AUTOSAR OS needto be highly dependable, tests involving memory protectionface a number of challenges, such as the high cost of test programs and long execution times.In this paper, we examine and introduce a test program generator that solves these problems, and test its effectiveness. To test our approach, we used a commercial implementation of the AUTOSAR OS. The results showed that our approach can solve the above-mentioned problems andalso be adapted to any implementation compliant with AUTOSAR OS specifications.

The amalgamation of conventional gait analysis devices, such as a force plate, with a machine learning platform facilitates the capability to classify between two disparate software platforms for the same bionic powered prosthesis. The BiOM powered prosthesis is applied with its standard software platform that incorporates a finite state machine control architecture and a biomimetic software platform that uniquely accounts for the muscle modeling history dependence known as the winding filament hypothesis. The feature set is derived from a series of kinetic and temporal parameters derived from the force plate recordings. The multilayer perceptron neural network achieves 91% classification between the software platforms for the BiOM powered prosthesis conventional finite state machine control architecture and biomimetic software platform based on the force plate derived feature set.

Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data

Non-invasive saliva specimens for the diagnosis of COVID-19: caution in mild outpatient cohorts with low prevalence

BackgroundCardiovascular Magnetic Resonance (CMR) myocardial perfusion imaging has the potential to evolve into a method allowing full quantification of myocardial blood flow (MBF) in clinical routine. Multiple quantification pathways have been proposed. However at present it remains unclear which algorithm is the most accurate. An isolated perfused, magnetic resonance (MR) compatible pig heart model allows very accurate titration of MBF and in combination with high-resolution assessment of fluorescently-labeled microspheres represents a near optimal platform for validation. We sought to investigate which algorithm is most suited to quantify myocardial perfusion by CMR at 1.5 and 3 Tesla using state of the art CMR perfusion techniques and quantification algorithms.MethodsFirst-pass perfusion CMR was performed in an MR compatible blood perfused pig heart model. We acquired perfusion images at physiological flow (“rest”), reduced flow (“ischaemia”) and during adenosine-induced hyperaemia (“hyperaemia”) as well as during coronary occlusion. Perfusion CMR was performed at 1.5 Tesla (n = 4 animals) and at 3 Tesla (n = 4 animals). Fluorescently-labeled microspheres and externally controlled coronary blood flow served as reference standards for comparison of different quantification strategies, namely Fermi function deconvolution (Fermi), autoregressive moving average modelling (ARMA), exponential basis deconvolution (Exponential) and B-spline basis deconvolution (B-spline).ResultsAll CMR derived MBF estimates significantly correlated with microsphere results. The best correlation was achieved with Fermi function deconvolution both at 1.5 Tesla (r = 0.93, p < 0.001) and at 3 Tesla (r = 0.9, p < 0.001). Fermi correlated significantly better with the microspheres than all other methods at 3 Tesla (p < 0.002). B-spline performed worse than Fermi and Exponential at 1.5 Tesla and showed the weakest correlation to microspheres (r = 0.74, p < 0.001). All other comparisons were not significant. At 3 Tesla exponential deconvolution performed worst (r = 0.49, p < 0.001).ConclusionsCMR derived quantitative blood flow estimates correlate with true myocardial blood flow in a controlled animal model. Amongst the different techniques, Fermi function deconvolution was the most accurate technique at both field strengths. Perfusion CMR based on Fermi function deconvolution may therefore emerge as a useful clinical tool providing accurate quantitative blood flow assessment.

The analysis of gangliosides is extremely challenging, given their structural complexity, lack of reference standards, databases, and software solutions. Here, we introduce a fast 6 min high field asymmetric ion mobility spectrometry (FAIMS) shotgun lipidomics workflow, along with a dedicated software solution for ganglioside detection. By ramping FAIMS compensation voltages, ideal ranges for different ganglioside classes were obtained. FAIMS revealed both class- and charge-state separation behavior based on the glycan headgroup moiety. The number of sialic acids attached to the glycan moiety correlates positively with their preferred charge states, i.e., trisialylated gangliosides were mainly present as [M - 3H]3- ions, whereas [M - 4H]4- and [M - 5H]5- ions were observed for GQ1 and GP1. For data evaluation, we developed a shotgun/FAIMS extension for the open-source Lipid Data Analyzer (LDA), enabling automated annotation of gangliosides up to the molecular lipid species level. This extension utilized combined orthogonal fragmentation spectra from CID, HCD, and 213 nm UVPD ion activation methods and covers 29 ganglioside classes, including acetylated and fucosylated modifications. With our new workflow and software extension 117 unique gangliosides species were identified in porcine brain extracts. While conventional shotgun lipidomics favored the observation of singly charged ganglioside species, the utilization of FAIMS made multiply charged lipid species accessible, resulting in an increased number of detected species, primarily due to an improved signal-to-noise ratio arising from FAIMS charge state filtering. Therefore, this FAIMS-driven workflow, complemented by new software capabilities, offers a promising strategy for complex ganglioside and glycosphingolipid characterization in shotgun lipidomics.

Adaptive quantization (AQ) proves to be an effective tool to improve coding performance. In this paper, we propose an adaptively spatiotemporal perception aware quantization algorithm to increase subjective coding performance. First, the perceptual complexity models are conducted with spatial and temporal characteristics to measure the spatiotemporally perceptual redundancies, respectively. With the help of the models, the adaptively spatial and temporal quantization parameter (QP) offsets are then calculated for each coding tree unit (CTU), respectively. Finally, the perceptually optimal Lagrange multiplier of each CTU is determined with the spatial-temporal QP offset. Experimental results show that the proposed algorithm reduces 8.6% BD-Rate with SSIM (Structural Similarity Index Metric) in average over the AVS2 (the second generation of Audio Video Coding Standard) reference software RD17.0 in Low-Delay P (LDP) configurations. The subjective assessment proves the proposed algorithm can significantly reduce the bit rates with the same subjective quality.

Aimed at the electromagnetic compatibility problems between same frequency radars on fleet battle ships, the maximum radar range is used to describe the EMC degree between the same frequency or similar frequency radars in radar system. The radar system is divided into Omani-directional antenna and directional antenna radar to analysis and get the two radar electromagnetic compatibility models, then the EMC degree model of entire radar system. Quantitative analysis of the simulation is represented for the relationship between several important parameters and EMC degree. It is an important complement of the radar deployment optimization methods, which provides a digital basis for analyzing the radars maximum benefit when coordinating combat.