Two-stage Implementation Research Articles

МЕТОД ДВОКАСКАДНОЇ ІМПЛАНТАЦІЇ ПРИХОВАНОЇ ІНФОРМАЦІЇ НА ОСНОВІ СТЕГАНОКОМПРЕСІЙНИХ ПЕРЕТВОРЕНЬ

In the article, the need for further development of the state is directly related to: solving issues of increasing defense capability and information security; development of information and intelligent systems. The necessity of ensuring the required level of completeness of information, compliance with the requirements of its relevance, achievement and maintenance of the appropriate level of integrity, accessibility and confidentiality is substantiated. The article emphasizes that for this purpose, complex systems of coding and information protection are being built. It is shown that recently, in order to further increase the level of security of information resources, methods of hidden embedding of information have been used. In this field of scientific and applied research, the direction of timely delivery of integral video information in a secure mode is outlined. For protection, the following can be used: meta-messages, which are formed on the basis of intelligent analysis of video frames; separate video segments of aerial photographs containing the most important information for decision-making. This article examines a class of methods of steganographic transformations, which are associated with embedding messages in digital containers, which are formed by a stream of video segments (VS). However, existing steganographic systems are based mainly on the use of the amount of psychovisual (PSV) redundancy available for reduction. Therefore, an increase in steganographic capacity leads to a loss of integrity and efficiency of delivery of video-container information. Steganocompression coding in the stegano-polyadic basis was created on the basis of taking into account the amount of redundancy permissible for reduction. In this case, in the process of compression of the components of the VS, the direct embedding of hidden information is organized. Concealment of information is carried out by technological stages, depending on the compression transformation of the transitional syntax of the quilted sequence. The key stage is the technology of two-stage implementation of the elements of the concealed message added to the stegano sequences to the syntax of the steganocompression representation of the BC components.

Multi-network approach for image segmentation in non-contrast enhanced cardiac 3D MRI of arrhythmic patients

Left atrial appendage (LAA) is the source of thrombi formation in more than 90% of strokes in patients with nonvalvular atrial fibrillation. Catheter-based LAA occlusion is being increasingly applied as a treatment strategy to prevent stroke. Anatomical complexity of LAA makes percutaneous occlusion commonly performed under transesophageal echocardiography (TEE) and X-ray (XR) guidance especially challenging. Image fusion techniques integrating 3D anatomical models derived from pre-procedural imaging into the live XR fluoroscopy can be applied to guide each step of the LAA closure. Cardiac magnetic resonance (CMR) imaging gains in importance for radiation-free evaluation of cardiac morphology as alternative to gold-standard TEE or computed tomography angiography (CTA). Manual delineation of cardiac structures from non-contrast enhanced CMR is, however, labor-intensive, tedious, and challenging due to the rather low contrast. Additionally, arrhythmia often impairs the image quality in ECG synchronized acquisitions causing blurring and motion artifacts. Thus, for cardiac segmentation in arrhythmic patients, there is a strong need for an automated image segmentation method. Deep learning-based methods have shown great promise in medical image analysis achieving superior performance in various imaging modalities and different clinical applications. Fully-convolutional neural networks (CNNs), especially U-Net, have become the method of choice for cardiac segmentation. In this paper, we propose an approach for automatic segmentation of cardiac structures from non-contrast enhanced CMR images of arrhythmic patients based on CNNs implemented in a multi-stage pipeline. Two-stage implementation allows subdividing the task into localization of the relevant cardiac structures and segmentation of these structures from the cropped sub-regions obtained from previous step leading to efficient and effective way of automated cardiac segmentation.

Optimum Arrangement of TADAS Dampers for Seismic Drift Control of Buildings Using Accelerated Iterative Methods

Triangular added-damping-and-stiffness (TADAS) dampers are reliable passive control devices for earthquake-excited buildings. The arrangement of TADAS dampers in buildings is essentially the allocation of triangular energy dissipation plates (TEDPs) among different stories, which directly influence the passive control effect and the construction cost. This paper proposes four iterated methods to achieve the optimum arrangement of TADAS dampers for seismic drift control of buildings, including the regular iterative method (RIM), the accelerated iterative method (AIM), and two modified accelerated iterative methods (MAIM-I and MAIM-II). Typical high-rise and low-rise buildings are used as application examples to evaluate their performance. Results of the study indicate that the two modified accelerated iterative methods are the most cost-efficient methods for achieving the optimum arrangement of TADAS dampers. This may be attributed to their two-stage implementation mechanism, which combines the set-by-set strategy and the one-by-one strategy in a reasonable way. Additionally, the modified accelerated iterative methods can be especially advantageous for high-rise buildings.

DEVELOPMENT OF A VIRTUAL DEVICE FOR CONTROLLING THE CONDITION OF INDUSTRIAL UNITS NODES USING LABVIEW TOOLS

This article is devoted to the research, construction, configuration and implementation of a virtual device for monitoring the condition of nodes ofcomplex industrial units. Modern units used in heavy engineering require no less modern means of management, control and diagnostics of damage tosuch units and their components. The development of the structure of control tools is based on multi-level or multi-stage procedures of transformationsof incoming measuring signals from aggregates. As the structure of the control device, a structure with a two-stage implementation of the spectraltransformation of measurement signals – with a primary static transformation and a secondary static transformation – was chosen. The basis of theprimary static transformation is the spectral transformation procedure based on the wavelet transformation. The basis of the secondary statictransformation is the procedure of linear discrimination with the indication of the decisive rule. The article demonstrates and implements approaches tobuilding a virtual device in terms of creating a block diagram, developing software, organizing the front panel of the device, setting up and carryingout simulation modeling for blocks of primary and secondary static transformations. The research uses the LabView platform. To prepare incomingmeasurement signals from nodes of industrial units, in the first block, the procedures of graduation, calibration and normalization of the target functionare carried out. To receive input measuring signals from units of industrial nodes, the COM port of the computer is used which, according to thedeveloped program, polls the COM port and inputs measuring signals to the primary static transformation procedure. The article describes a completevirtual control device that is formed and tested, which structurally contains all the blocks for achieving the control result and indicating the controlresult on the graphic interpretation of the computer.

The impact of an accelerated depreciation tax policy on employment: Evidence from China

We examine the impact of an accelerated depreciation tax policy (ADP) on employment. As a tax incentive policy, we expect an ADP to impact firm behavior significantly, but its effect on employment remains uninvestigated. Leveraging the two-stage implementation of an ADP in selected industries in China in 2014 and 2015 and using a difference-in-differences research design, we find that: 1) the ADP significantly increases employment, which is consistent with the output effect hypothesis; and 2) the ADP increases firms’ labor demand, mainly by stimulating investment in fixed assets and easing their financial constraints. Additional analysis suggests that the impact of ADP on employment is more salient for small firms, non-state-owned firms, and high growth firms, and skilled labor employment, indicating that the ADP is more effective for firms with high financial constraints and hiring skilled labor to accompany the increase in capital investment.

Conceptual bases for forming a hybrid drive of a high traffic vehicle

The hybrid drive is growing in popularity and is already present in almost the majority of classes of the new model generation of military vehicles (MV) of the NATO countries, the Russian Federation, and the People's Republic of China. The main advantage of the hybrid MV drive is, first of all, a significant reduction in the ability to locate the movement in the sound and infrared frequency spectra when driving on electric traction with the internal combustion engine turned off, as well as an increase in the power reserve due to a decrease in the linear consumption of motor fuel. The purpose of the study is to form a general structure - a scheme of a hybrid drive of a high-possibility car for off-road and to evaluate the basic necessary parameters of power drive units, taking into account the characteristics of off-road driving. Based on the analysis of trends in the development of military buggies and areas of use in modern conditions of war and the urgent need for machines of this class at the front, the feasibility of actually two-stage implementation of modifications with a hybrid drive for the Armed Forces of Ukraine of the ultralight domestic buggy TUR KV 02 “Mamai” was determined, which meets the regulatory requirements of the NATO base countries regarding of wheeled equipment of the front edge, and provides appropriate mobility for off-road traffic.
 In contrast to serial passenger cars and crossovers, the hybrid drive of MV is based on a series scheme with the possibility of external plug-in charging, as well as the use of the hybrid drive as an autonomous power source for other consumers in the field. At the 2nd stage of the development of the hybrid drive of the TUR KV02 “Mamay” buggy, a unified layout of the drive units is provided with the possibility of short-term simultaneous connection of the drive wheels of both the traction electric motor and the internal combustion engine with the synchronization of their speed modes for driving on difficult off-road or increasing acceleration dynamics. The capacity of the batteries is formed by the necessary reserve of autonomous driving on electric traction in typical off-road areas in the area of combat use. The unit of traction batteries is easily replaceable in the conditions of places of permanent deployment and has increased protection against water ingress during short-term forcing of minor water obstacles and provides for the option of Level 1 STANAG 4589 ballistic protection.

Fast Sidelobe Suppression Based on Two-Dimensional Joint Iterative Adaptive Filtering

In multitarget scenarios, the masking of small targets by large targets nearby may severely deteriorate radar detectability due to the range and Doppler sidelobes. In this article, a 2-D joint iterative adaptive filtering (2-D JIAF) method is proposed, by adopting the reiterative minimum mean square error (RMMSE) criterion to the outputs of a 2-D matched filter. The main advantages of the proposed method over the state-of-the-art (SOTA) methods, including modified adaptive multipulse compression and iterative adaptive approach, are twofold: 1) it is able to suppress the sidelobes in both range and Doppler dimensions and thus obtain an improved range-Doppler image; 2) the computational complexity is significantly reduced by adopting a small processing window in both range and Doppler dimensions. The derivation of 2-D JIAF is detailed and an efficient two-stage implementation is outlined. The performance of 2-D JIAF is validated with simulation results over a wide range of scenarios and compared with two SOTA approaches. The impacts of different parameters, including the number of iterations and the choice of the size of the processing window, are also extensively studied with Monte Carlo trials.

Compact and robust supercontinuum generation and post-compression using multiple thin plates

Abstract We report on compact and robust supercontinuum generation and post-compression using transmission of light through multiple thin solid plates at the SwissFEL X-ray free-electron laser facility. A single stage consisting of three thin plates followed by a chirped mirror compressor achieves compression of initially 30-fs pulses with 800-nm center wavelength to sub-10-fs duration. We also demonstrate a two-stage implementation to compress the pulses further to sub-5-fs duration. With the two-stage setup, the generated supercontinuum includes wavelengths ranging from 500 to 1100 nm. The multi-plate setup is compact, robust, and stable, which makes it ideal for applications at free-electron laser facilities such as pump-probe experiments and laser-arrival timing tools.

КАК ОБУЧАТЬ ИНОСТРАННОМУ ЯЗЫКУ СТУДЕНТОВ ПЕДАГОГИЧЕСКОГО ВУЗА: АКТУАЛЬНЫЕ ПРОБЛЕМЫ И ВОЗМОЖНЫЕ РЕШЕНИЯ

The article discusses a new strategy of professionally-directed (didactic-oriented) foreign language teaching to students of a language pedagogical university (future teachers of a foreign language). The study analyses the components of the teacher’s methodological (linguodidactic) competence, revealing a number of problems concerning their formation in a pedagogical university, as well as showing the dependence of their development on the intensity of their actualisation in the Foreign Language Practice discipline. The article identifies several factors hindering the formation of the linguodidactic competence within foreign language classes. In order to overcome these negative factors, the article offers a new model of teaching foreign languages, described in the formula “from the acquisition of didactic experience to one’s own educative decisions”. The methodology of this model is based on two interrelated methods: contextual teaching and vocation-focused foreign languages teaching, as well as related methods for organizing productive teaching of a foreign language. The model mentioned above assumes a two-stage implementation. At the first stage, analytical work of students is organized. Its aim is to understand and analyse the teaching practice. An important condition is the modelling of basic structural elements and some procedural features of a school lesson while organising university foreign language classes. Particular attention is paid to the implementation of individualised goal-setting, planning and self-assessment (reflection), demonstration of lexis, grammar and phonetics mastering, of active forms and techniques for organising communicative activities, methodological reflection. At the first stage, university students are also offered some methodological tools (for example, goalsetting maps and maps for academic work planning, etc.), which can be used in teaching foreign languages at school. When organising the educational process, much attention is paid to the awareness of methodological facts, phenomena, patterns. Therefore, a new type of exercises (educational-methodological) has been proposed. In addition to an educational task, these exercises contain a methodological task in form of a short comment, an additional question, etc. At the second stage, there is a transition to the organising of a productive methodologically oriented foreign language activity. Three main methods of methodologically oriented teaching are distinguished: modification of authentic (university) materials for different age groups of schoolchildren, conventional “professional test”, and project educational-methodological activity. In conclusion, the main results of the study are summarised.

Low-complexity GLRT for FDA radar without training data

Conventionally adaptive detection for frequency diverse array (FDA) radar requires extra training data to estimate the range-dependent interference covariance matrix (ICM). In this paper, we propose an adaptive moving target detection approach for FDA radar without training data, where the ICM is directly estimated by applying a structured generalized likelihood ratio test (SGLRT) to the target-present samples. In order to reduce the three-dimensional (3D) search complexity of the SGLRT, we then propose an efficient unstructured GLRT (UGLRT) approach, which transforms the 3D search into a 1D Doppler-only search and a joint range-angle search. Moreover, we design a low-complexity two-stage implementation of the UGLRT for practical application. The first stage is to test multiple discrete frequency bins for target detection, while the second stage is to precisely estimate the frequency through locally optimizing the estimator function around the coarse estimate provided by the first-stage detection. As the UGLRT approach avoids the 3D search, it significantly reduces the computational complexity, compared to the SGLRT counterpart. Numerical results show that the UGLRT approach achieves almost the same detection and estimation performance as the SGLRT one.

The Implementation of the Soviet Healthcare Model in ‘People’s Democracy’ Countries—the Case of Post-war Poland (1944–1953)

Abstract This article aims at presenting a Soviet model of public health service, the so-called Siemaszko model, and its implementation in the People’s Republic of Poland (1944/45–1953). Based on the Marx’s and Lenin’s interpretations, the Soviet model assumed a universal nature of health service, financing healthcare from the public purse, full state (party) control over public health, full access to medical services for all, entire staff put on the public payroll and state education for medical personnel. After the Second World War a modified version of that model was implemented in the so-called people’s democracies (i.e. communist countries). In the post-war years, a two-stage implementation of this socialist model was rolled out in the People’s Republic of Poland. The first stage, in 1944–48, was based on the so-called multisector approach. The second began in 1948 and assumed a full and planned unification and nationalisation of the healthcare system.

Power-mode-aware Memory Subsystem Optimization for Low-power System-on-Chip Design

The memory subsystem is increasingly subject to an intensive energy minimization effort in embedded and System-on-Chip development. While the main focus is typically put on energy consumption reduction, there are other optimization aspects that become more and more relevant as well, e.g., peak power constraints or time budgets. In this regard, the present article makes the following contributions. Taking industrial-grade information into account, different Static Random-Access Memory (SRAM) power modes and their characteristics are presented at first. Using this information, a comprehensive optimization model with the main intention of energy minimization is defined. It is based on memory access statistics that represent the embedded software of interest, which allows for application-tailored improvements. Further, it considers different power states of the memory subsystem and enables the definition of peak power and time corridor constraints. The presented two-stage implementation of this optimization model allows the handling of large design spaces. Clearly defined interfaces facilitate the exchange of individual workflow parts in a plug-and-play fashion and further enable a neat integration of our optimization method with existing hardware/software (HW/SW) codesign synthesis flows. A general evaluation for different technology nodes yields that the optimization potential of memory low-power modes increases with advancing miniaturization but also depends on the data footprint of the embedded software. Experimental results for a set of benchmark applications confirm these findings and provide energy savings of up to 90% and over 60% on average compared to a monolithic memory layout without low-power modes.

A Single-Stage Dual-Output Tri-Mode AC-DC Regulator for Inductively Powered Application

This paper presents a one-stage AC-DC voltage regulator with dual-output for inductively powered applications. In order to maximize the circuit performances, more than one independent regulated output voltage is often required to cater for different sub-modules in a system. The typical two-stage implementation which consists of a rectifier and a multiple-output DC-DC converter limits the overall power conversion efficiency of the receiver. A new architecture which is able to rectify and regulate two or more output voltages simultaneously in a single-stage is proposed and thereby improving the overall power conversion efficiency substantially. In addition, an energy-efficient control scheme is adopted to control the multiple switches in the architecture. Since no inductor is required in the proposed one-stage conversion structure, the cross-regulation problem that used to exist in a multiple-output switching converter has been eliminated. Apart from this, it is easier to be integrated with a system-on-chip (SoC) due to its minimized footprint. The tri-mode dual-output design was fabricated in standard $0.18~\mu \text{m}$ CMOS process. It delivers a maximum output power of 114mW. The measured peak power conversion efficiency is 91.7% at dual regulated output voltages of 1.8V and 2V.

Low-complexity carrier phase recovery based on principal component analysis for square-QAM modulation formats.

We propose, numerically analyze and experimentally demonstrate a low-complexity, modulation-order independent, non-data-aided (NDA), feed-forward carrier phase recovery (CPR) algorithm. The proposed algorithm enables synchronous decoding of arbitrary square-quadrature amplitude modulation (QAM) constellations and it is suitable for a realistic hardware implementation based on block-wise parallel processing. The proposed method is based on principal component analysis (PCA) and it outperforms the well-known and widely used blind phase search (BPS) algorithm at low signal-to-noise ratio (SNR) values, showing much lower cycle slip rate (CSR) both numerically and experimentally. For operation at higher SNR values, a hybrid two-stage implementation combining the proposed method and BPS is also proposed and their performance are investigated benchmarking them against the two-stage BPS (2S-BPS). The complexity of the proposed simple and hybrid methods are evaluated against 2S-BPS and computational complexity savings of 92% and 40% are expected for the simple and hybrid methods, respectively.

A Wide-Input-Range High-Efficiency Step-Down Power Factor Correction Converter Using a Variable Frequency Multiplier Technique

This paper demonstrates a two-stage implementation of a step-down power factor preregulator design that achieves a high efficiency across the entire universal input voltage range ( $\text{85}\text{--}\text{265}\,\textrm {V}_{\textrm {rms}}$ ) for an offline power supply application. In this implementation, a resonant LLC converter supplies power to a boost converter operating in a continuous conduction mode. A variable frequency multiplier technique is used in a resonant LLC converter stage to provide different dc gains and compress the effective input voltage range. The efficiency performance achieved is flatter and higher than other conventional offline power converter design consisting of a boost power factor correction circuit followed by a resonant LLC converter, whose efficiency tends to drop significantly at low-line input voltages. The proposed circuit allows MOSFETs with lower voltage ratings and better conduction/switching characteristics to be used in both converter stages. Both of the LLC stage and boost circuit can be better optimized due to the compressed operation range and better semiconductor switches. A scaling law of power losses versus breakdown voltage requirement for boost circuit under the condition of the same output power is presented. Experimental results demonstrated a flatter high efficiency performance across a wide input range.

Pan-sharpening via compressed superresolution reconstruction and multidictionary learning

In recent compressed sensing (CS)-based pan-sharpening algorithms, pan-sharpening performance is affected by two key problems. One is that there are always errors between the high-resolution panchromatic (HRP) image and the linear weighted high-resolution multispectral (HRM) image, resulting in spatial and spectral information lost. The other is that the dictionary construction process depends on the nontruth training samples. These problems have limited applications to CS-based pan-sharpening algorithm. To solve these two problems, we propose a pan-sharpening algorithm via compressed superresolution reconstruction and multidictionary learning. Through a two-stage implementation, compressed superresolution reconstruction model reduces the error effectively between the HRP and the linear weighted HRM images. Meanwhile, the multidictionary with ridgelet and curvelet is learned for both the two stages in the superresolution reconstruction process. Since ridgelet and curvelet can better capture the structure and directional characteristics, a better reconstruction result can be obtained. Experiments are done on the QuickBird and IKONOS satellites images. The results indicate that the proposed algorithm is competitive compared with the recent CS-based pan-sharpening methods and other well-known methods.

Estimation of the Magnetotelluric Response Function: The Path from Robust Estimation to a Stable Maximum Likelihood Estimator

The robust statistical model of a Gaussian core contaminated by outlying data in use since the 1980s, and which underlies modern estimation of the magnetotelluric (MT) response function, is re-examined from first principles. The residuals from robust estimators applied to MT data are shown to be systematically long-tailed compared to a distribution based on the Gaussian and hence inconsistent with the robust model. Instead, MT data are pervasively described by the stable distribution family for which the Gaussian is an end member, but whose remaining distributions have algebraic rather than exponential tails. The validity of the stable model is rigorously demonstrated using a permutation test. A maximum likelihood estimator (MLE), including the use of a remote reference, that exploits the stable nature of MT data is formulated, and its two-stage implementation, in which stable parameters are first fit to the residuals, and then the MT responses are solved for, with iteration between them, is described. The MLE is inherently robust, but differs from a conventional robust estimator because it is based on a statistical model derived from the data rather than being ad hoc. Finally, the covariance matrices obtained from MT data are pervasively improper as a result of weak non-stationarity, and the Cramer–Rao lower bound for the improper covariance matrix is derived, resulting in reliable second-order statistics for MT responses. The stable MLE was applied to an exemplar broadband data set from northwest Namibia. The stable MLE is shown to be consistent with the statistical model underlying linear regression and hence is unconditionally unbiased, in contrast to the robust model. The MLE is compared to conventional robust remote reference and two-stage estimators, establishing that the standard errors of the former are systematically smaller than for either of the latter, and that the standardized differences between them exhibit excursions that are both too frequent and too large to be described by Gaussian statistics. These excursions are more prevalent when the tail thickness parameter of the stable distribution is small, and are attributed to rising bias in the robust estimator that is also consistent with the Berry–Esseen theorem that defines the rate of convergence to the central limit theorem value. An explanation for weak non-stationarity of MT data is proposed, and several extensions to the present work are described.

Modeling nutrient removal using watershed-scale implementation of the two-stage ditch

Western Lake Erie Basin (WLEB) is the most intensively farmed region of the Great Lakes. Because of the flat topography and poorly-drained soils many farmers rely on drainage management practices (e.g., subsurface tile drainage, ditch channelization) to maintain productive agriculture. However, these practices also facilitate the delivery of excess nutrients and sediments to Lake Erie, which have been linked to recurring harmful algal blooms (HABs) and associated environmental degradation. Implementation of inset floodplains in formerly channelized waterways via the two-stage ditch can improve water quality but the efficacy has been tested using only implementation in short reaches. Watershed models are critical tools for assessing watershed-scale implementation and as such can guide effective management. We evaluated the effectiveness of the two-stage ditch in improving water quality in the River Raisin Watershed (RRW), a major subbasin in the WLEB, combining empirical measurements for nutrient reductions from two-stage ditches across the Midwest with output from a Soil Water Assessment Tool (SWAT) model. We modeled two-stage implementation in 25, 50, and 100% of headwater reaches in the RRW, and found that the practice could reduce total annual NO3−-N export by 2, 5 and 10%, respectively. The two-stage was even more effective at reducing total phosphorus (TP) export, which was reduced by 12, 20 and 31%, respectively. Compared to other conservation practices, nutrient reduction efficiency for the two-stage ditch was good, both in terms of percent load reduction and cost, but watershed-scale adoption will be required in order to achieve significant nutrient reductions as called for by policymakers.

Social worker accreditation plans spark two-tier workforce concerns

Consultation on social worker accreditation system outlines plans for a two-stage implementation, with 31 areas volunteering in the first phase. But sector leaders are concerned this will create a two-tier workforce

MR-CLOPE: A MapReduce based transactional clustering algorithm for DNS query log analysis

DNS (domain name system) query log analysis has been a popular research topic in recent years. CLOPE, the represented transactional clustering algorithm, could be readily used for DNS query log mining. However, the algorithm is inefficient when processing large scale data. The MR-CLOPE algorithm is proposed, which is an extension and improvement on CLOPE based on MapReduce. Different from the previous parallel clustering method, a two-stage MapReduce implementation framework is proposed. Each of the stage is implemented by one kind MapReduce task. In the first stage, the DNS query logs are divided into multiple splits and the CLOPE algorithm is executed on each split. The second stage usually tends to iterate many times to merge the small clusters into bigger satisfactory ones. In these two stages, a novel partition process is designed to randomly spread out original sub clusters, which will be moved and merged in the map phrase of the second phase according to the defined merge criteria. In such way, the advantage of the original CLOPE algorithm is kept and its disadvantages are dealt with in the proposed framework to achieve more excellent clustering performance. The experiment results show that MR-CLOPE is not only faster but also has better clustering quality on DNS query logs compared with CLOPE.