Current Block Research Articles

Paper] Memory Bandwidth Constrained Overlapped Block Motion Compensation for Video Coding

Overlapped block motion compensation (OBMC) is an inter prediction tool that improves coding performance by blending reference samples of the current and neighboring block across the block boundaries. For this mechanism, OBMC increases the reference samples fetched from the external memory on hardware decoders, i.e., memory bandwidth. This is a disadvantage when introducing OBMC to video coding standards such as VVC, especially for mobile devices with limited batteries, because the extended memory bandwidth increases decoders' power consumption. In this paper, we propose a memory bandwidth constrained OBMC method with adaptive number of motion vectors and interpolation filter taps of the neighboring blocks depending on the current block sizes. Simulation results show that the proposed method achieves -0.22 % performance improvements over VVC reference software without exceeding the maximum memory bandwidth of VVC, which is comparable to the full performance of OBMC (-0.33 %), requiring 3.8 times its memory bandwidth.

High-Bandwidth, Low-Power CMOS Transistor Based CAB for Field Programmable Analog Array

This article presents an integrated current mode configurable analog block (CAB) system for field-programmable analog array (FPAA). The proposed architecture is based on the complementary metal-oxide semiconductor (CMOS) transistor level design where MOSFET transistors operating in the saturation region are adopted. The proposed CAB architecture is designed to implement six of the widely used current mode operations in analog processing systems: addition, subtraction, integration, multiplication, division, and pass operation. The functionality of the proposed CAB is demonstrated through these six operations, where each operation is chosen based on the user’s selection in the CAB interface system. The architecture of the CAB system proposes an optimized way of designing and integrating only three functional cells with the interface circuitry to achieve the six operations. Furthermore, optimized programming and digital tuning circuitry are implemented in the architecture to control and interface with the functional cells. Moreover, these designed programming and tuning circuitries play an essential role in optimizing the performance of the proposed design. Simulation of the proposed CMOS Transistor Based CAB system is carried out using Tanner EDA Tools in 0.35 μm standard CMOS technology. The design uses a V power supply and results in maximum 3 dB bandwidth of 34.9 MHz and an approximate size of 0.0537 . This demonstrates the advantages of the design over the current state-of-the-art designs presented for comparison in this article. Consequently, the proposed design has a clear aspect of simplicity, low power consumption, and high bandwidth operation, which makes it a suitable candidate for mobile telecommunications applications.

A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing

The video compression sensing method based on multi hypothesis has attracted extensive attention in the research of video codec with limited resources. However, the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task. To resolve this problem, this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimization method. It mainly includes the optimization of prediction blocks (OPBS), the selection of search windows and the use of neighborhood information. Specifically, the OPBS consists of two parts: the selection of blocks and the optimization of prediction blocks. We combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video sequence. In addition, most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on performance. Therefore, Block-level search window (BSW) is constructed to cover the position of the optimal hypothesis block as much as possible. To maximize the availability of reference frames, Nearby reference frame information (NRFI) is designed to reconstruct the current block. The proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction performance. Experimental results show that the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.

A current mode instrumentation amplifier with high common-mode rejection ratio designed using a novel fully differential second-generation current conveyor

This study presents a high common-mode rejection ratio (CMRR), and high power-supply rejection ratio (PSRR) current-mode instrumentation amplifier (CMIA) to overcome the limitations of existing differential voltage second-generation current conveyors (DVCCII)-based CMIAs in achieving high CMRR. The design is based on a fully differential second-generation current conveyor block with a novel circuit design following by a current subtracting stage. The CMIA is designed and laid out in 130 nm CMOS technology operating under ± 1.2 V supply voltage in Cadence software. The post-layout simulation results show that the CMIA achieves low-frequency voltage and current CMRR- BW of 228.8 dB–10 kHz and 246 dB–10.6 kHz, respectively, with PSRR + /PSRR- of 108.2 dB/99.7 dB, power consumption of 507 µW, and a core area of 0.0015 mm2. The unique quality of the circuit is that, it does not need well-matched active blocks, but inherently improves CMRR, bandwidth, and PSRR; hence it gains an excellent choice for integration.

A methodology of coupled modeling of vacuum blocks of industrial installations

The article presents the methodology of coupled modeling of the main blocks of a chemical-technological system operating under vacuum. The system analysis of vacuum blocks is carried out and the basic rules of technological calculation are formed, in which the evacuated technological object and the vacuum overhead system are considered as a single system with inter-dependent elements. The presented methodology was applied when calculating the vacuum block of the primary oil refining process of a mini-refinery working on fuel oil, as a result of which an integrative characteristic of the block was compiled, which takes into account the mutual influence of the vacuum system and the technological object on the residual pressure at the top of the vacuum column. The adequacy of the developed model was ascertained by comparing with industrial research data. In line with the proposed methodology, numerical experiments were carried out accordingly in which the temperature of the service liquid being fed into the pump was changed. The results of the calculations showed that, achieving the given project Pressure under the current block component setup (P= 40 mm Hg) was not possible as a reason of the increased resistance in the shell side of the condenser.

Remote Sensing Image Super-Resolution via Residual-Dense Hybrid Attention Network

Nowadays, remote sensing datasets with long temporal coverage generally have a limited spatial resolution, most of the existing research uses the single image super-resolution (SISR) method to reconstruct high-resolution (HR) images. However, due to the lack of information in low-resolution (LR) images and the ill-posed nature of SISR, it is difficult to reconstruct the fine texture of HR images under large-scale magnification factors (e.g., four times). To address this problem, we propose a new reference-based super-resolution method called a Residual-Dense Hybrid Attention Network (R-DHAN), which uses the rich texture information in the reference image to make up for the deficiency of the original LR image. The proposed SR model employs Super-Resolution by Neural Texture Transfer (SRNTT) as a backbone. Based on this structure, we propose a dense hybrid attention block (DHAB) as a building block of R-DHAN. The DHAB fuses the input and its internal features of current block. While making full use of the feature information, it uses the interdependence between different channels and different spatial dimensions to model and obtains a strong representation ability. In addition, a hybrid channel-spatial attention mechanism is introduced to focus on important and useful regions to better reconstruct the final image. Experiments show that compared with SRNTT and some classical SR techniques, the proposed R-DHAN method performs well in quantitative evaluation and visual quality.

A new continuous hybrid block method with one optimal intrastep point through interpolation and collocation

Implicit block approaches are used by a number of numerical analyzers to model mild, medium, and hard differential systems. Their excellent stability characteristics, self-starting nature, quick convergence, and large decrease in computing cost all contribute to their widespread application. With these numerical benefits in mind, a new one-step implicit block method with three intrastep grid points has been created. The major term of the local truncation error is minimized to determine which of these points is optimal. The reformulation of the suggested technique leads to a significant decrease in computing cost while maintaining the same consistency, zero-stability, mathcal{A}-stability, and convergence. Several sorts of error are calculated, together with CPU time and efficiency plot, to determine which is superior. Differential models from the fields of heat transfer, population dynamics, and chemical engineering show that the suggested method does a better job than some of the current hybrid block and implicit Radau methods with similar properties.

Reverse voltage protection circuits for power MOSFETs in low dropout power applications

This paper proposed three reverse voltage protection circuits for the power MOSFETs in low dropout power applications. Power devices are vulnerable to instantaneous current overshoot when the input voltage is lower than the output voltage. Compared with conventional solutions using diode for reverse current block, the proposed three structures consume fewer voltage drop during normal operation. The first design is suitable for applications with wide output ranges but requires the largest die area. The other two solutions are for applications with low output voltages, and are characterized with effective area arrangement and dead-zone free control, respectively. The proposed three protection structures require 126.2%, 12.25% and 43.05% extra die area of the power devices, respectively.

Recovery of Mixtures of Construction Waste, PET and Sugarcane Bagasse for the Manufacture of Partition Blocks.

The building industry generates millions of tons of construction and demolition waste annually (12 million tons/year are generated in Mexico, of which only 4% is reused or recycled). Concomitantly, the demand for goods and services by the building industry causes significant environmental impacts. On the other hand, plastic waste is also difficult to assimilate into the environment in the short term, and its recovery is of special interest. Therefore, this research focuses on the feasibility of the manufacture of Partition Blocks (essential building element) through the combination of construction and demolition waste (CDW), polyethylene terephthalate (PET) plastic flakes, dust from tire shredding, and residue from the sugar industry (bagasse). The results of this study show that the Partition Blocks made with CDW and PET reach an average compressive strength of 115.003 kgf/cm2 (11.278 MPa) (suitable for structural use according to Mexican regulations); the use of lime enhances the consistency of the mixture of CDW and PET (increases its cohesion and homogeneity); and finally, these Partition Blocks have a cost comparable to the current conventional Partition Blocks made with virgin material, thus, conferring them validity as a feasible recycling option for these residues.

High Gain, Low Noise and Power Transimpedance Amplifier Based on Second Generation Voltage Conveyor in 65 nm CMOS Technology.

A transimpedance amplifier (TIA) based on a voltage conveyor structure designed for high gain, low noise, low distortion, and low power consumption is presented in this work. Following a second-generation voltage conveyor topology, the current and voltage blocks are a regulated cascode amplifier and a down converter buffer, respectively. The proposed voltage buffer is designed for low distortion and low power consumption, whereas the regulated cascode is designed for low noise and high gain. The resulting TIA was fabricated in 65 nm CMOS technology for logic and mixed-mode designs, using low-threshold voltage transistors and a supply voltage of ±1.2 V. It exhibited a 52 dBΩ transimpedance gain and a 1.1 GHz bandwidth, consuming 55.3 mW using a ±1.2 V supply. Our preamplifier stage, based on a regulated cascode, was designed considering detector capacitance, bonding wire, and packaging capacitance. The voltage buffer was designed for low-power consumption and low distortion. The measured input-referred noise of the TIA was 22 pA/√Hz. The obtained total harmonic distortion of the TIA was close to 5%. In addition, the group delay is constant for the considered bandwidth. Comparisons against published results in terms of area (A), power consumption (P), bandwidth (BW), transimpedance gain (G), and noise (N) are were performed. Both figures of merit FoMs—the ratio √ (G × BW) and P × A—and FoM/N values demostrated the advantages of the proposed approach.

HEVC’s intra mode process expedited using Histogram of Oriented Gradients

The brute-force behavior of High Efficiency Video Coding (HEVC) is the biggest hurdle in the communication of multimedia content. Therefore, two novel methods will be presented here to expedite the intra mode decision process of HEVC. In the first algorithm, the feasibility of Histogram of Oriented Gradients (HOG) for early intra mode decision is presented by using statistical evidence. Then, HOG of the current block and 35 intra predictions are obtained. The intra-prediction that gives the least sum of absolute difference (SAD) with the HOG of the current block is selected as the termination point. In the second algorithm, the difference between the Hardmard-cost of intra modes is modeled to achieve fast intra mode decision. The proposed algorithms accelerated the encoding process of the HEVC by 5% and 35.57%, while their Bjontegaard Delta Bit Rate (BD-BR) is 1.09% and 1.61%, respectively.

Effects of waveform shape and electrode material on KiloHertz frequency alternating current block of mammalian peripheral nerve

ObjectivesKiloHertz frequency alternating current waveforms produce conduction block in peripheral nerves. It is not clearly known how the waveform shape affects block outcomes, and if waveform effects are frequency dependent. We determined the effects of waveform shape using two types of electrodes.Materials and methodsAcute in-vivo experiments were performed on 12 rats. Bipolar electrodes were used to electrically block motor nerve impulses in the sciatic nerve, as measured using force output from the gastrocnemius muscle. Three blocking waveforms were delivered (sinusoidal, square and triangular) at 6 frequencies (10–60 kHz). Bare platinum electrodes were compared with carbon black coated electrodes. We determined the minimum amplitude that could completely block motor nerve conduction (block threshold), and measured properties of the onset response, which is a transient period of nerve activation at the start of block. In-vivo results were compared with computational modeling conducted using the NEURON simulation environment using a nerve membrane model modified for stimulation in the kilohertz frequency range.ResultsFor the majority of parameters, in-vivo testing and simulations showed similar results: Block thresholds increased linearly with frequency for all three waveforms. Block thresholds were significantly different between waveforms; lowest for the square waveform and highest for triangular waveform. When converted to charge per cycle, square waveforms required the maximum charge per phase, and triangular waveforms the least. Onset parameters were affected by blocking frequency but not by waveform shape. Electrode comparisons were performed only in-vivo. Electrodes with carbon black coatings gave significantly lower block thresholds and reduced onset responses across all blocking frequencies. For 10 and 20 kHz, carbon black coating significantly reduced the charge required for nerve block.ConclusionsWe conclude that both sinusoidal and square waveforms at frequencies of 20 kHz or higher would be optimal. Future investigation of carbon black or other high charge capacity electrodes may be useful in achieving block with lower BTs and onsets. These findings will be of importance for designing clinical nerve block systems.

An Internet of Things (IoT) Based Block Chain Technology to Enhance the Quality of Supply Chain Management (SCM)

Recent technological developments indicate possible advancements in supply chain management (SCM). These innovations have attracted a lot of interest from industries including logistics, manufacturing, packaging, and transportation. The conventional systems, however, use centralised servers to control all operations, including the exchange of raw materials, making orders, dealing with buyers and sellers, and updating orders. The network’s supply chain may thus be insecure as a result of every activity being routed via centralised servers. The danger is additionally increased by a number of difficulties, including scalability, data integrity, security, and availability. Block chain technology may be used in these circumstances to decentralise transaction processing and eliminate the need for a centralised controller. In this approach, the performance of the resource-constrained supply chain network is improved by the effective use of edge computing and priority data access. The Intelligent K-Means (IKM) clustering algorithm is suggested across the edge nodes in the current research to categorise the priority level of each piece of data. This classifier determines if the edge node has received data that is high priority or low priority. Low priority data is recorded in the log files for future data analysis. Then, to allow safe data flow in the open block chain while excluding outside parties, the High Priority Access based Smart Contract (HPASC) technique is deployed. The whole experiment was conducted in a Python environment, and variables including scalability, reaction time, throughput, and accuracy were studied. Current systems’ constrained block sizes and fork creation lengthen the time transactions must wait before being processed. The suggested methodology is quicker and uses less storage space than current block chain systems. The results show that the suggested approach works better than current blockchain technology to raise the standard of supply chain management.

AN EFFICIENT REVERSIBLE DATA HIDING BASED ON IMPROVED PIXEL VALUE ORDERING METHOD

Pixel value ordering (PVO) has been considered as an effective reversible data hiding method for high embedding capacity and good imperceptibility. In this paper, we propose a novel reversible data hiding based on four sorted pixels. This paper proposes a new reversible hiding scheme based on the arrangement of 4 pixels. Three bits will be embedded into each four pixels sub block without changing the order while the original PVO method only embeds 2 bits. In case the amount of payload is less than the embedding capacity, flatter blocks will be prioritized for embedding to improve image quality. To determine the flat of block, we use 12 neighborhood pixels of current block. Only blocks with satisfactory flatness are used for embedding. The proposed reversible data hiding not only gains high capacity but also gets good imperceptibility. Experimental results also show that the proposed reversible data hiding scheme outperforms several widely schemes using pixel value ordering method in terms of both image quality and embedding capacity.

A 2.45/5.8 GHz high-efficiency dual-band rectifier for low radio frequency input power

This article proposes a concurrent rectifier for radio frequency (RF) energy harvesting from the popular ambient RF sources wireless fidelity (WiFi) 2.45 and 5.8 GHz bands. A voltage doubler-based converter circuit with the Schottky SMS7630 diode is used, this chosen diode has shown good results for low power levels. To ameliorate the resulting circuit, we used an interdigital capacitor (IDC) instead of a lumped component; and then we added a filter to reject the 3rd harmonics of each operating frequency. A dual-band impedance transformer with a direct current (DC) block function is used and optimized at low input power points for more harvested DC power. The final circuit was, therefore, more efficient and more reliable. The maximum conversion efficiencies obtained from the resulting circuit are about 60.321% for 2.45 GHz and 47.175% for 5.8 GHz at 2 dBm of input power. Compared to other previous rectifiers presented in the literature, our proposed circuit presents high efficiencies at low power levels and at these operating frequencies.

Pharmacological characterisation of electrocardiogram J-Tpeak interval in conscious Guinea pigs

Drug-induced human ether-à-go-go-related gene (hERG) channel block and QT interval prolongation increase torsade de pointes (TdP) risk. However, some drugs block hERG channels and prolong QT interval with low TdP risk, likely because they block additional inward currents. We investigated the utility of J-Tpeak interval, a novel biomarker of inward current block and TdP risk, in conscious telemetered guinea pigs. Electrocardiogram parameters were analysed in Hartley guinea pigs orally administered one of eight test compounds (dofetilide, flecainide, nifedipine, quinidine, quinine, ranolazine, sotalol, verapamil) or vehicle alone as controls. Heart rate-corrected QT (QTcX) and J-Tpeak (J-TpeakcX) were calculated to evaluate the relations of QT–RR and J-Tpeak–RR. Dofetilide and sotalol significantly increased ΔQTcX and ΔJ-TpeakcX intervals to similar degrees. Quinidine, quinine and flecainide also increased ΔQTcX and ΔJ-TpeakcX intervals, but the degrees of ΔJ-TpeakcX interval prolongation were shorter than those of ΔQTcX interval prolongation. Ranolazine showed slight increasing trends in ΔQTcX and ΔJ-TpeakcX intervals, but the differences were not significant. Verapamil and nifedipine did not increase the ΔQTcX or ΔJ-TpeakcX intervals. Based on the relations of ΔΔJ-TpeakcX and ΔΔQTcX intervals, dofetilide, sotalol and quinidine were classified as high risk for TdP, quinine, flecainide and ranolazine were classified as intermediate risk and verapamil and nifedipine were classified as low risk. These results supported the usefulness of J-Tpeak interval assessment in conscious guinea pigs for predicting drug-induced balanced block of inward currents and TdP risk in early-stage preclinical studies.

A novel reputation-based consensus framework (RCF) in distributed ledger technology

Distributed ledger technology (DLT) has emerged as a key and effective technology which has caught the attention of variety of disciplines and is capable of changing lots of sciences and related industries. Selecting the transactions of members in DLT-based technologies such as blockchain, especially in finance, is essential and vital. Therefore, in this paper, we present a novel framework for selecting members’ transactions through trust and reputation models called the reputation-based consensus framework (RCF), so that by combining trust and reputation models with blockchain, the target node (or verifier), which has the highest reputation based on its transactions history, is selected to create and publish the current block of blockchain. We have also provided a state machine model to accurately describe the behavior of the RCF. In addition, the RCF algorithms are presented and a prototype is developed based on it. The results of simulation and performance and security analysis proved that RCF leads to fair selection of transactions, improves scalability and throughput, and can resist against attacks such as Sybil and malicious behaviors.

Activity-Based Block Partitioning Decision Method for Versatile Video Coding

Versatile Video Coding (VVC), the latest international video coding standard, has more than twice the compression performance of High-Efficiency Video Coding (HEVC) through adopting various coding techniques. The multi-type tree (MTT) block structure offers more advanced flexible block partitioning by allowing the binary tree (BT) and ternary tree (TT) structures, as well as the quadtree (QT) structure. Because VVC selects the optimal block partition by performing encoding on all possible CU partitions, the encoding complexity increases enormously. In this paper, we observe the relationship between block partitions and activity that indicates block texture complexity. Based on experimental observations, we propose an activity-based fast block partitioning decision method to reduce the encoding complexity. The proposed method uses only information of the current block without using the information of neighboring or upper blocks, and also minimizes the dependency on QP. For these reasons, the proposed algorithm is simple and parallelizable. In addition, by utilizing the gradient calculation used in VVC’s ALF, a VVC-friendly fast algorithm was designed. The proposed method consists of two-step decision-making processes. The first step terminates the block partitioning early based on observed posterior probability through the relationship between the block size and activity per sample. Next, the sub-activities of the current block are used to determine the type and direction of partitioning. The experimental results show that in the all-intra configuration, the proposed method can reduce the encoding time of the VVC test model (VTM) by up to 45.15% with 2.80% BD-rate loss.

The Challenges of Predicting Drug-Induced QTc Prolongation in Humans.

The content of this article derives from a Health and Environmental Sciences Institute (HESI) consortium with a focus to improve cardiac safety during drug development. A detailed literature review was conducted to evaluate the concordance between nonclinical repolarization assays and the clinical thorough QT (TQT) study. Food and Drug Administration and HESI developed a joint database of nonclinical and clinical data, and a retrospective analysis of 150 anonymized drug candidates was reviewed to compare the performance of 3 standard nonclinical assays with clinical TQT study findings as well as investigate mechanism(s) potentially responsible for apparent discrepancies identified. The nonclinical assays were functional (IKr) current block (Human ether-a-go-go related gene), action potential duration, and corrected QT interval in animals (in vivo corrected QT). Although these nonclinical assays demonstrated good specificity for predicting negative clinical QT prolongation, they had relatively poor sensitivity for predicting positive clinical QT prolongation. After review, 28 discordant TQT-positive drugs were identified. This article provides an overview of direct and indirect mechanisms responsible for QT prolongation and theoretical reasons for lack of concordance between clinical TQT studies and nonclinical assays. We examine 6 specific and discordant TQT-positive drugs as case examples. These were derived from the unique HESI/Food and Drug Administration database. We would like to emphasize some reasons for discordant data including, insufficient or inadequate nonclinical data, effects of the drug on other cardiac ion channels, and indirect and/or nonelectrophysiological effects of drugs, including altered heart rate. We also outline best practices that were developed based upon our evaluation.

Diversifying preclinical research tools: expanding patient-derived models to address cancer health disparities

Cancer health disparities define a critical healthcare issue for racial/ethnic minorities in the USA. Key findings have led to cancer treatment improvements tailored to minority patients, but such successes have been rare. Here, we highlight how the use of patient-derived xenograft (PDX) and organoid models could resolve current blocks toward precision cancer health equity.