Current Block Research Articles

Cross-Component Prediction Boosted With Local and Non-Local Information in Video Coding.

In the versatile video coding (VVC) standard, cross-component prediction (CCP) is introduced to utilize the correlation between luma and chroma components. To further exploit the cross-component redundancy, a bundle of novel CCP methods with more sophisticated models are studied in enhanced compression model (ECM), which is a platform targeting at the next generation video coding standard, developed by JVET. This paper presents two methods, known as local-boosting CCP (LB-CCP) and non-local CCP (NL-CCP) to improve CCP with local and non-local information. With LB-CCP, prediction samples of CCP can be filtered with neighbouring samples. Besides, neighbouring template costs are calculated to determine the range of training samples, as well as the cross-component prediction method used in the chroma fusion mode. With NL-CCP, a CCP model can be derived with samples non-adjacent to the current block. As an equivalent but simpler implementation, the CCP model can be inherited from a CCP-coded neighbouring block as a spatial CCP candidate. Moreover, the CCP model of a previous CCP-coded block can be stored in a history-based table, which can be fetched and used by the current block as a history-based CCP candidate. A NL-CCP candidate list is built with the two kinds of candidates. The encoder can select the optimal candidate and send an index to the decoder. Experimental results show that LB-CCP together with NL-CCP can provide an average Bjontegaard delta rate (BD-rate) reduction of 0.27%, 2.31%, 2.44% on Y, Cb, Cr components, respectively, with a negligible change in the running time, compared with ECM-8.0 in all intra configurations. Both LB-CCP and NL-CCP have been adopted into ECM.

An efficient hardware architecture of integer motion estimation based on early termination and data reuse for Versatile video coding

The integer motion estimation (IME) involves high computational complexity and large amount of computation data due to the variable block sizes, and it is one of the most critical bottlenecks in video coding. The traditional algorithm for integer motion estimation loses search accuracy when simplifying the motion search process, or it becomes complex to pursue search accuracy, which is not conducive to video encoding and transmission. This paper presents a data reuse algorithm based on search window division, block splitting, the arrangement of search points in the Test Zone (TZ) search algorithm and block division. which divides pixel blocks of different sizes into several 8x8 pixel blocks and then reuses the overlapping 8x8 pixel blocks between adjacent search points of the Test Zone (TZ) search algorithm to reduce hardware resource consumption. By comparing the Sum of Absolute Differences (SAD) values of left and top pixel blocks with current pixel block, the integer motion estimation (IME) can be terminated in advance, reducing the computation complexity of integer motion estimation by over 70 %. Furthermore, the paper also presents a hardware architecture based on the data reuse algorithm, which can process 7680 × 4320@60fps videos at an operating clock frequency of 182.99 MHz, with lower resource consumption compared to similar hardware designs.

Efficient and precise docking trajectory optimization for the ship block assembly

The assembly of the ship block is an extremely important stage of the shipbuilding process. Nevertheless, currently, the manual assembly efficiency is low, the accuracy is poor, and collision is very easy to occur. Therefore, there is an urgent need to conduct technical research on the automatic docking of ship blocks. The core of the automated docking technology is the attitude estimation and the trajectory planning of the posturing equipment. However, current data measurement and point set matching methods lead to large attitude-estimation errors, and it is difficult to meet the accuracy requirements of the assembly. Moreover, the current ship block trajectory planning methods pay more attention to single metrics, for example, time or energy consumption, while omitting the shock degree. In response to the above, this study first proposes a high-precision matching method for measuring point sets, in order to estimate the exact attitude of the ship block. Subsequently, trajectory translation for the block is performed using the seventh-degree polynomial. On this basis, a nonlinear weighted improved particle swarm optimization (IPSO) method is proposed to optimize the time, energy consumption and shock degree in the ship block trajectory planning process. Finally, the accuracy of the matching optimization is validated by simulation analysis and it is concluded that the seventh-degree polynomial leads to less shock than other polynomials. Furthermore, the shock force does not change abruptly even when the ship block is poised in steps. Through IPSO, the energy consumption and shock degree performance indices are optimized by 37.07% and 50.06%, respectively, in the ship block translation process.

Comparison of diagnostic accuracy of current left bundle branch block and ventricular pacing ECG criteria for detection of occlusion myocardial infarction

BackgroundElectrocardiographic detection of patients with occlusion myocardial infarction (OMI) can be difficult in patients with left bundle branch block (LBBB) or ventricular paced rhythm (VPR) and several ECG criteria for the detection of OMI in LBBB/VPR exist. Most recently, the Barcelona criteria, which includes concordant ST deviation and discordant ST deviation in leads with low R/S amplitudes, showed superior diagnostic accuracy but has not been validated externally. We aimed to describe the diagnostic accuracy of four available ECG criteria for OMI detection in patients with LBBB/VPR at the emergency department. MethodsThe unweighted Sgarbossa criteria, the modified Sgarbossa criteria (MSC), the Barcelona criteria and the Selvester criteria were applied to chest pain patients with LBBB or VPR in a prospectively acquired database from five emergency departments. ResultsIn total, 623 patients were included, among which 441 (71%) had LBBB and 182 (29%) had VPR. Among these, 82 (13%) patients were diagnosed with AMI, and an OMI was identified in 15 (2.4%) cases. Sensitivity/specificity of the original unweighted Sgarbossa criteria were 26.7/86.2%, for MSC 60.0/86.0%, for Barcelona criteria 53.3/82.2%, and for Selvester criteria 46.7/88.3%. In this setting with low prevalence of OMI, positive predictive values were low (Sgarbossa: 4.6%; MSC: 9.4%; Barcelona criteria: 6.9%; Selvester criteria: 9.0%) and negative predictive values were high (all >98.0%). ConclusionsOur results suggests that ECG criteria alone are insufficient in predicting presence of OMI in an ED setting with low prevalence of OMI, and the search for better rapid diagnostic instruments in this setting should continue.

State Priorities and Needs: The Role of Block Grants.

Block grant funding provides federal financial support to states, with increased flexibility as to how those funds can be allocated at the community level. At the state level, block grant amounts and distributions are often based on outdated formulas that consider population measures and funding environments at the time of their creation. We describe variation in state-level funding allocations for 5 federal block grant programs and the extent to which funding aligns with the current needs of state populations. We conducted an analysis in 2022 of state block grant allocations as a function of state-level characteristics for 2015-2019 for all 50 states. We provide descriptive statistics of state block grant allocations and multivariate regression models for each program. Models include base characteristics relevant across programs plus supplemental characteristics based on program-specific goals and state population needs. Mean state block grant allocations per 1000 population by program ranged from $618 to $21 528 during 2015-2019. Characteristics associated with state allocations varied across block grants. For example, for every 1-percentage-point increase in the percentage of the population living in nonmetropolitan areas, Preventive Health and Health Services Block Grant funding was approximately $7 per 1000 population higher and Community Services Block Grant funding was approximately $40 per 1000 population higher. Few supplemental characteristics were associated with allocations. Current block grant funding does not align with state characteristics and needs. Future research should consider how funds are used at the state level or allocated to local agencies or organizations and compare state block grant allocations with other types of funding mechanisms, such as categorical funding.

Fast Probing Amyloid Polymorphism via Nanopore Translocation.

Neurodegenerative diseases are characterized by the presence of cross-β-sheet amyloid fibrils and a rich mesoscopic polymorphism, requiring noninvasive detection with high fidelity. Here, we introduce a methodology that can probe via a sensitive synthetic nanopore the complex polymorphism of amyloid fibrils by an automated and fast screening protocol. Statistically analyzing the translocation events on two model amyloid systems derived from β-lactoglobulin and lysozyme allows extracting the cross-sectional configuration of hydrated amyloid fibrils from current block amplitude and correlating dwell time with fibril length. These findings are consistent with the amyloid polymorphs observed in solution by atomic force microscopy. Furthermore, the ionic current signal of a single translocation event can reveal abnormally aggregated conformations of amyloid fibrils without potential artifacts associated with microscopy methods. This study introduces an effective approach to physically discriminating and separating amyloid and may serve in the rapid diagnosis of early aggregating pathological amyloidosis.

M-current modulation of cortical slow oscillations: Network dynamics and computational modeling.

The slow oscillation is a synchronized network activity expressed by the cortical network in slow wave sleep and under anesthesia. Waking up requires a transition from this synchronized brain state to a desynchronized one. Cholinergic innervation is critical for the transition from slow-wave-sleep to wakefulness, and muscarinic action is largely exerted through the muscarinic-sensitive potassium current (M-current) block. We investigated the dynamical impact of blocking the M-current on slow oscillations, both in cortical slices and in a cortical network computational model. Blocking M-current resulted in an elongation of Up states (by four times) and in a significant firing rate increase, reflecting an increased network excitability, albeit no epileptiform discharges occurred. These effects were replicated in a biophysical cortical model, where a parametric reduction of the M-current resulted in a progressive elongation of Up states and firing rate. All neurons, and not only those modeled with M-current, increased their firing rates due to network recurrency. Further increases in excitability induced even longer Up states, approaching the microarousals described in the transition towards wakefulness. Our results bridge an ionic current with network modulation, providing a mechanistic insight into network dynamics of awakening.

Ionic current changes underlying action potential repolarization responses to physiological pacing and adrenergic stimulation in adult rat ventricular myocytes.

This study aimed to simulate ventricular responses to elevations in myocyte pacing and adrenergic stimulation using a novel electrophysiological rat model and investigate ion channel responses underlying action potential (AP) modulations. Peak ion currents and AP repolarization to 50% and 90% of full repolarization (APD50-90 ) were recorded during simulations at 1-10 Hz pacing under control and adrenergic stimulation conditions. Further simulations were performed with incremental ion current block (L-type calcium current, ICa ; transient outward current, Ito ; slow delayed rectifier potassium current, IKs ; rapid delayed rectifier potassium current, IKr ; inward rectifier potassium current, IK1 ) to identify current influence on AP response to exercise. Simulated APD50-90 closely resembled experimental findings. Rate-dependent increases in IKs (6%-101%), IKr (141%-1339%), and ICa (0%-15%) and reductions in Ito (11%-57%) and IK1 (1%-9%) were observed. Meanwhile, adrenergic stimulation triggered moderate increases in all currents (23%-67%) except IK1 . Further analyses suggest AP plateau is most sensitive to modulations in Ito and ICa while late repolarization is most sensitive to IK1 , ICa , and IKs , with alterations in IKs predominantly stimulating the greatest magnitude of influence on late repolarization (35%-846% APD90 prolongation). The modified Leeds rat model (mLR) is capable of accurately modeling APs during physiological stress. This study highlights the importance of ICa , Ito , IK1, and IKs in controlling electrophysiological responses to exercise. This work will benefit the study of cardiac dysfunction, arrythmia, and disease, though future physiologically relevant experimental studies and model development are required.

Overmodulation Harmonic Modeling and Suppression for Induction Motor Field-Weakening Control With Extended Voltage Tracking Method

The overmodulation strategy can improve the maximum output torque capability of induction motor field-weakening control. However, the harmonic voltages accompanied with the extended voltage would cause the harmonics of current and torque, deteriorating system performance. To reveal the generation mechanism of harmonics, an overmodulation harmonic modeling is proposed based on vector analysis. It is quantitatively proved that the constant extended voltage should be reduced as much as possible to suppress the harmonic when providing the expected torque. On this basis, an extended voltage tracking method is proposed to suppress the harmonic and achieve the high output torque capability according to different operation requirements. The flux current preselection block is designed to preset the steady-state operation point. The expected extended voltage tracking block is designed to set appropriate voltage constraint, thereby redistributing the stator current properly. Finally, the experimental results confirm that the investigated method can improve the steady-state performance with harmonic suppression, and achieve the maximum output torque during the dynamic process and the high-load driving process.

Investigating the Flexural Behavior of a Two-Span High-Performance Concrete Beam Using Experimentally Derived Stress Block Parameters.

High-performance concrete (HPC) is increasingly used in construction due to its superior strength and durability. However, current stress block parameters used for designing normal-strength concrete cannot be safely applied to HPC. To address this issue, new stress block parameters have been proposed through experimental works, which are used for designing HPC members. In this study, the behavior of HPC was investigated using these stress block parameters. Two-span beams made of HPC were tested under five-point bending, and an idealized stress block curve was derived from the experimental stress-strain curve for grades 60, 80, and 100 MPa. Based on the stress block curve, equations for the ultimate moment of resistance, depth of the neutral axis, limiting moment of resistance, and maximum depth of the neutral axis were proposed. An idealized load-deformation curve was also developed, which identified four significant events: first cracking, yielding of reinforced steel, crushing of concrete with spalling of cover, and ultimate failure. The predicted values were found to be in good agreement with the experimental values, and the average location of the first crack was identified to be 0.270 L, measured from the central support on either side of the span. These findings provide important insights for the design of HPC structures, contributing to the development of more resilient and durable infrastructure.

Mild elevation of extracellular potassium greatly potentiates the effect of sodium channel block to cardiovert atrial fibrillation: The Lankenau approach

Cardioversion of atrial fibrillation (AF) is a common clinical necessity and there is a need for more effective and safe options for acute cardioversion of AF. To test the hypothesis that the efficacy and time course of AF cardioversion by sodium channel current (INa) block can be improved by mild elevation of extracellular potassium ([K+]0). Using a canine acetylcholine (ACh)-mediated AF model (isolated coronary-perfused right atrial preparations with a rim of right ventricle), we evaluated the ability of flecainide to suppress AF in the presence of [K+]0 ranging from 3 to 8 mM. At [K+]0 of 4 mM (baseline), persistent AF (>1 hour) was induced in 5/5 atria in the presence of 0.5 μM ACh. Flecainide alone (1.5 μM) cardioverted 3/6 atria at 4 mM [K+]0, 1/6 atria at 3 mM [K+]0, 5/5 atria at 5 mM and 6 mM [K+]0, and 4/4 atria at 8 mM [K+]0. In the absence of flecainide, an increase in [K+]0 from 4 to 5, 6 and 8 mM terminated AF in 0/5, 2/6, and 4/4 atria. The time to conversion was also abbreviated by elevation of [K+]0. Following AF termination with flecainide plus elevated [K+]0, AF was either not inducible or brief (< 100 sec). Combined flecainide and elevated [K+]0 (6 mM) caused an atrial preferential depression of excitability. Our findings suggest that a combination of INa block accompanied by mild elevation of serum potassium may be a novel approach to more effectively, rapidly, and safely cardiovert AF and prevent its recurrence in the short term.

A Countermeasure for Double Spending Attacks on Blockchain Technology in Smart Grid

As a distributed technology, blockchain has been applied in many fields. Much research has been done on its inherent security issues. Among these security issues, double spending is one of the most pernicious. Current countermeasures are not systematic, they either focus on monitoring or detection with no effective strategy to prevent future double spending. These countermeasures also have serious drawbacks, such as high network traffic, high CPU utilization, and heavy management overhead. In this paper, we present a systematic approach to address double spending attack on smart grid. A reputable node is selected, which constantly compares all transactions in current time window with previously validated block and current block. Upon discovering conflicting transactions, a warning message with the conflicting transaction and two penalty transactions are broadcasted to the network to stop the current attack and to prevent future attacks. Our experiment has demonstrated our design is highly effective to detect double spending, with short detection time and low CPU utilizations.

Cholinergic depolarization recruits a persistent Ca2+ current in Aplysia bag cell neurons.

Many behaviors and types of information storage are mediated by lengthy changes in neuronal activity. In bag cell neurons of the hermaphroditic sea snail Aplysia californica, a transient cholinergic synaptic input triggers an ∼30-min afterdischarge. This causes these neuroendocrine cells to release egg laying hormone and elicit reproductive behavior. When acetylcholine is pressure-ejected onto a current-clamped bag cell neuron, the evoked depolarization is far longer than the current evoked by acetylcholine under voltage clamp, suggesting recruitment of another conductance. Our earlier studies found bag cell neurons to display a voltage-dependent persistent Ca2+ current. Hence, we hypothesized that this current is activated by the acetylcholine-induced depolarization and sought a selective Ca2+ current blocker. Rapid Ca2+ current evoked by 200-ms depolarizing steps in voltage-clamped cultured bag cell neurons demonstrated a concentration-dependent sensitivity to Ni2+, Co2+, Zn2+, and verapamil but not Cd2+ or ω-conotoxin GIVa. Leak subtraction of Ca2+ current evoked by 10-s depolarizing steps using the IC100 (concentration required to eliminate maximal current) of Ni2+, Co2+, Zn2+, or verapamil revealed persistent Ca2+ current, demonstrating persistent current block. Only Co2+ and Zn2+ did not suppress the acetylcholine-induced current, although Zn2+ appeared to impact additional channels. When Co2+ was applied during an acetylcholine-induced depolarization, the amplitude was reduced; furthermore, protein kinase C activation, previously established to enhance the persistent Ca2+ current, extended the depolarization. Therefore, the persistent Ca2+ current sustains the acetylcholine-induced depolarization and may translate brief cholinergic input into afterdischarge initiation. This could be a general mechanism of triggering long-term change in activity with a short-lived input.NEW & NOTEWORTHY Ionotropic acetylcholine receptors mediate brief synaptic communication, including in bag cell neurons of the sea snail Aplysia. However, this study demonstrates that cholinergic depolarization can open a voltage-gated persistent Ca2+ current, which extends the bag cell neuron response to acetylcholine. Bursting in these neuroendocrine cells results in hormone release and egg laying. Thus, this emphasizes the role of ionotropic signaling in reaching a depolarized level to engage Ca2+ influx and perpetuating the activity necessary for behavior.

Estimation for the number of MDS Matrices, Recursive MDS Matrices and Symmetric Recursive MDS Matrices from the Reed-Solomon Codes

The diffusion layer of the SPN block ciphers is usually built on the basis of the MDS (Maximum Distance Separable) matrices which is the matrix of the maximum distance separable code (MDS code). MDS codes have long been studied in error correcting code theory and have applications not only in coding theory but also in the design of block ciphers and hash functions. Thanks to that important role, there have been many studies on methods of building MDS matrices. In particular, the recursive MDS matrices and the symmetric recursive MDS matrices have particularly important applications because they are very efficient for execution. In this paper, we will give an estimate of the number of MDS matrices, recursive MDS matrices and symmetric recursive MDS matrices built from Reed-Solomon codes. This result is meaningful in determining the efficiency from this method of building matrices based on the Reed-Solomon codes. From there, this method can be applied to find out many MDS matrices, secure and efficient symmetric recursive MDS matrices for execution to apply in current block ciphers. Furthermore, recursive MDS matrices can be efficiently implemented using Linear Feedback Shift Registers (LFSR), making them well suited for lightweight cryptographic algorithms, so suitable for limited resources application.

Neural Network-Based Reference Block Quality Enhancement for Motion Compensation Prediction

Inter prediction is a crucial part of hybrid video coding frameworks, and it is used to eliminate redundancy in adjacent frames and improve coding performance. During inter prediction, motion estimation is used to find the reference block that is most similar to the current block, and the following motion compensation is used to shift the reference block fractionally to obtain the prediction block. The closer the reference block is to the original block, the higher the coding efficiency is. To improve the quality of reference blocks, a quality enhancement network (RBENN) that is dedicated to reference blocks is proposed. The main body of the network consists of 10 residual modules, with two convolution layers for preprocessing and feature extraction. Each residual module consists of two convolutional layers, one ReLU activation, and a shortcut. The network uses the luma reference block as input before motion compensation, and the enhanced reference block is then filtered by the default fractional interpolation. Moreover, the proposed method can be used for both conventional motion compensation and affine motion compensation. Experimental results showed that RBENN could achieve a −1.35% BD rate on average under the low-delay P (LDP) configuration compared with the latest H.266/VVC.

Exploiting Temporal Side Information in Massive IoT Connectivity

This paper considers the joint device activity detection and channel estimation problem in a massive Internet of Things (IoT) connectivity system, where a large number of IoT devices exist but merely a random subset of them become active for short-packet transmission in each coherence block. In particular, we propose to leverage the temporal correlation in device activity, e.g., a device active in the previous coherence block is more likely to be still active in the current coherence block, to improve the detection and estimation performance. However, it is challenging to utilize this temporal correlation as side information (SI), which relies on the knowledge about the exact statistical relation between the estimated activity pattern for the previous coherence block (which may be imperfect with unknown error) and the true activity pattern in the current coherence block. To tackle this challenge, we establish a novel SI-aided multiple measurement vector approximate message passing (MMV-AMP) framework. Specifically, thanks to the state evolution of the MMV-AMP algorithm, the correlation between the activity pattern estimated by the MMV-AMP algorithm in the previous coherence block and the real activity pattern in the current coherence block is quantified explicitly. Based on the well-defined temporal correlation, we further manage to embed this useful SI into the denoiser design under the MMV-AMP framework. Specifically, the SI-based soft-thresholding denoiser with binary thresholds and the SI-based minimum mean-squared error (MMSE) denoiser are characterized for the cases without and with the knowledge of the channel distribution, respectively. Numerical results are given to show the significant gain in device activity detection and channel estimation performance brought by our proposed SI-aided MMV-AMP framework.

Unpicking DNA translocation in nanopores with simultaneous single-molecule fluorescence and optical single channel recording.

Nanopore-based DNA sequencing offers high throughput and long reads by measuring blockades in current as a strand is translocated through the pore, providing a single-molecule readout with high time resolution. However, electrical measurements alone offer only information regarding the current block itself; to improve nanopore sensing, a molecular picture of the steps of analyte binding, capture and translocation is required. Optical single channel recording of calcium flux through the nanopore enables parallel single-molecule capture events to be distinguished. We combine optical single channel recording with a single molecule fluorescence readout of DNA unzipping to correlate the steps of individual translocations and image the location of the system components. By annealing short oligomers bearing fluorophore-quencher pairs to the translocating DNA strand, we map the process of nanopore capture, threading and unzipping.

Effects on heart rate from direct current block of the stimulated rat vagus nerve

Objective. Although electrical vagus nerve stimulation has been shown to augment parasympathetic control of the heart, the effects of electrical conduction block have been less rigorously characterized. Previous experiments have demonstrated that direct current (DC) nerve block can be applied safely and effectively in the autonomic system, but additional information about the system dynamics need to be characterized to successfully deploy DC nerve block to clinical practice. Approach. The dynamics of the heart rate (HR) from DC nerve block of the vagus nerve were measured by stimulating the vagus nerve to lower the HR, and then applying DC block to restore normal rate. DC block achieved rapid, complete block, as well as partial block at lower amplitudes. Main Results. Complete block was also achieved using lower amplitudes, but with a slower induction time. The time for DC to induce complete block was significantly predicted by the amplitude; specifically, the amplitude expressed as a percentage of the current required for a rapid, 60 s induction time. Recovery times after the cessation of DC block could occur both instantly, and after a significant delay. Both blocking duration and injected charge were significant in predicting the delay in recovery to normal conduction. Significance. While these data show that broad features such as induction and recovery can be described well by the DC parameters, more precise features of the HR, such as the exact path of the induction and recoveries, are still undefined. These findings show promise for control of the cardiac autonomic nervous system, with potential to expand to the sympathetic inputs as well.

GNSS-Free End-of-Row Detection and Headland Maneuvering for Orchard Navigation Using a Depth Camera

GPS-based navigation in orchards can be unstable because trees may block the GPS signal or introduce multipath errors. Most research on robot navigation without GPS has focused on guidance inside orchard rows; end-of-row detection has not received enough attention. Additionally, navigation between rows relies on reference maps or artificial landmarks. In this work, a novel row-end detection method is presented, which detects drastic changes in the statistical distribution of the sensed point cloud as the robot gets closer to the row’s end. A row-entry method was also implemented that builds a local map that is used by a reactive path tracker. The system was evaluated in a 24-row block in a vineyard. Once the robot was closer than 7 m from the end of a row, the algorithm detected it with a 100% success rate and calculated the distance from it with a mean error of 0.54 m. The system was also evaluated in vineyard configurations with parallel and slanted vine rows in consecutive blocks. The system worked well in all configurations, except where the next block had rows aligned to the rows of the current block and the headland width was closer than 5 m.

Region-based Template Matching Prediction for Intra Coding.

Copy prediction is a renowned category of prediction techniques in video coding where the current block is predicted by copying the samples from a similar block that is present somewhere in the already decoded stream of samples. Motion-compensated prediction, intra block copy, template matching prediction etc. are examples. While the displacement information of the similar block is transmitted to the decoder in the bit-stream in the first two approaches, it is derived at the decoder in the last one by repeating the same search algorithm which was carried out at the encoder. Region-based template matching is a recently developed prediction algorithm that is an advanced form of standard template matching. In this method, the reference area is partitioned into multiple regions and the region to be searched for the similar block(s) is conveyed to the decoder in the bit-stream. Further, its final prediction signal is a linear combination of already decoded similar blocks from the given region. It was demonstrated in previous publications that region-based template matching is capable of achieving coding efficiency improvements for intra as well as inter-picture coding with considerably less decoder complexity than conventional template matching. In this paper, a theoretical justification for region-based template matching prediction subject to experimental data is presented. Additionally, the test results of the aforementioned method on the latest H.266/Versatile Video Coding (VVC) test model (version VTM-14.0) yield an average Bjøntegaard-Delta (BD) bit-rate savings of -0.75% using all intra (AI) configuration with 130% encoder run-time and 104% decoder run-time for a particular parameter selection.