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The variation of ultrasonic parameters is closely linked to the mechanical properties and damage evolution of rock and soil mass. In this paper, uniaxial compression tests and real-time ultrasonic monitoring technology were used to explore the strength, deformation and damage characteristics of frozen soil-rock mixture (FSRM) with different block sizes and gradations, as well as the law of ultrasonic wave propagation. The results indicate that: (1) A wider gradation of rock blocks corresponds to a higher specimen strength and a lower breakage degree of rock blocks. Within the same gradation, specimens with smaller block sizes have higher strength. Wider gradation and smaller particle size of rock blocks exerts a delayed effect on damage and failure of FSRM. (2) The particle size of rock blocks plays a key role in the variation of ultrasonic parameters. Within the same gradation, the specimens with larger block sizes possess higher wave velocity and lower first wave amplitude. The effect of gradation on ultrasonic parameters is attributed to the variation of block size. (3) With the first wave amplitude as damage state variable, a damage prediction model based on the improved Duncan–Chang model is established, demonstrating superior prediction potential on the stress–strain curves of FSRM. The research confirms and promotes the quantitative correlation between ultrasonic parameters and mechanical properties of geotechnical materials, which may provide theoretical support for testing and evaluating the mechanical properties of roadbed filling in cold mountainous areas. [ABSTRACT FROM AUTHOR]

Slope leveling is essential for the successful implementation of ground-mounted centralized photovoltaic (PV) plants, but currently, there is a lack of optimization methods available. To address this issue, a linear programming approach has been proposed to optimize PV slope leveling. This method involves dividing the field into blocks and grids and using hyperbolic paraboloids to simulate the design surface. By programming in MATLAB, the globally optimal solution for PV slope leveling can be calculated. Engineering case studies have demonstrated that this optimization method can achieve significant cut-and-fill volume savings ranging from 58% to 78%, when compared to the traditional segmented plane method. Additionally, the effectiveness of the optimization method improves with larger site areas and more complex terrains. A parameter analysis considering slope ratio, grid size, and block size reveals that grid size has a minimal impact on cut-and-fill volume, while slope ratio and block size have a significant influence. For typical PV projects, the recommended ranges of slope ratio, grid size, and block size are 3–7%, 5–20 m, and 30–50 m, respectively, for slope leveling design. In summary, the proposed linear optimization method provides an optimal slope leveling scheme for ground-mounted centralized PV plants, with convenient operation and fast computation. [ABSTRACT FROM AUTHOR]

For the safe transmission of loads to concrete supports, such as column-foundations, corbels, bridge pedestals, post-tension members, support anchorages, and other forms of superstructure supports, the concrete bearing strength is considered an essential design parameter. The usage of recycled aggregate within concrete is considered environmentally friendly since it diverts rubbish from bulldozing and preserves natural resources. End-hooked steel fibre is an almost substantial enhancer for recycled aggregate concrete characteristics. Never before has the bearing behavior of recycled aggregate concrete been evaluated. Thus, this study provides an experimental evaluation of the bearing strength of steel fiber-reinforced recycled aggregate concrete at different replacement levels (0, 10, 20, 30, 50, and 100%) of recycled concrete aggregate (RCA). The used fraction quantities of steel fiber were 0.5%, 1.5%, and 2%. Three sizes of blocks were manufactured (100 × 100 × 100 mm, 150 × 150 × 150 mm, and 250 × 250 × 250 mm). The ratio of concrete block area to bearing area (A2/A1) was kept constant at 2.5 for all three block sizes. The primary purpose of this research was to examine the impact of block size on bearing stiffness, ultimate slip, and ultimate bearing strength. The findings demonstrated that the bearing stiffness and bearing strength reduced as the block size increased. To assess the ultimate bearing stiffness/strength and normalised ultimate bearing slip, analytical models were employed to develop new proposed equations that unaccounted for the impact of compressive strength, RCA, reinforcing index of steel fibre, and block size. In addition, this research led to the creation of a modified ACI 318 formula that accurately forecasts the bearing strength of concrete depending on block size. [ABSTRACT FROM AUTHOR]

Field leveling is crucial for efficiency and performance optimization of concentrated photovoltaic (PV) plants due to their large areas and uneven terrain. Manual adjustment combined with the block plane method is conventionally used for PV field leveling design, which is time-consuming and laborious with non-optimized results. There’s a lack of optimization method for large-scale PV field leveling. This paper introduces a quadratic programming-based optimization approach, dividing the leveling plane into grids and utilizing a hyperbolic paraboloid to model the surface. Constraints are imposed based on earthwork balance and slope ratio, with the objective function being the minimization of total cut-and-fill volume. The globally optimal solution for large-scale PV field leveling is through MATLAB R2022a programming. Case studies demonstrate that the quadratic optimization method, compared to the traditional block plane method, can yield savings of 55 % to 78 % in cut-and-fill volumes, with faster computation and more practical outputs. Moreover, the method proves to be more effective as site area and topography complexity increase. Parametric analyses obtain a critical slope ratio of 2 %, below which the cut-and-fill volumes are significantly impacted by the slope ratio, while above which, the influence diminishes. Meanwhile, the cut-and-fill volumes are found to increase continuously as the block size increases, while remaining mostly constant when the grid size changes within a range of 5–30 m. These findings highlight the significant influence of design slope ratio and block size on the cut-and-fill volume, while the grid size has a minor impact. Recommended parameters for PV field leveling design include a design slope ratio of 3 % to 7 %, a grid size of 5 to 20 m, and a block size of 30 to 50 m. This proposed method provides an optimization method for field leveling design of large-scale PV plants. It achieves the least engineering quantity, substantially improves design efficiencies, and provides more applicable outputs.

Blockchain technology has become a popular platform for conducting secure and decentralised transactions. Performance analysis of Ethereum smart contracts is critical to understanding their limitations and potential for various applications. This study aimed to evaluate the gas cost of different search algorithms and the impact of block size on the throughput of the Ethereum network. Additionally, Bitcoin, Litecoin, and Dogecoin simulations were conducted to analyse the impact of various configurations in the block interval and block propagation on the number of transaction outputs. The results showed that the gas cost of search algorithms varied significantly, with the quick search having a lower cost. Furthermore, increasing the block size had a positive impact on the throughput of the Ethereum network, allowing more transactions to be processed per second. The simulation results revealed that the block interval and block propagation significantly affected the number of transaction outputs, highlighting the importance of optimising these configurations for blockchain-based systems. [ABSTRACT FROM AUTHOR]

Block size in a permissioned blockchain system plays a huge role in scalability and performance of system. A large number of blocks are continuously disseminated into the network and hence it becomes important to study the effect of block size in a decentralized peer-to-peer network. The scalability of the system is the biggest concern. Scalability is a metric that refers to the ability of the system to increase or balance its performance depending upon the load and the processing demands on the system. The success of any blockchain-based application is dependent on the size of block used. Block size governs the time required to transmit a block (block transmission time) and the rate at which the unconfirmed transactions are verified (transaction pool clearance time). Block size also acts as a factor in ordering the blocks in the chain and dictates the performance and security of the system. This paper presents simulation analysis of the influence of block size on blockchain and the role of network bandwidth-aware optimal block size on the performance of the blockchain system. Nature-inspired algorithms have been used to determine the link between block size and scalability and are used for finding the optimal block size for a Blockchain-based application. [ABSTRACT FROM AUTHOR]

The field of information security has many uses in the modern day and beyond. Encryption is a method used to secure information from unauthorized access. Since symmetric key algorithms can decrypt data much more quickly than asymmetric key algorithms, the former are more popular. Blowfish is an unpatented, freely useable, compact, quick, and efficient symmetric key encryption technique. Additionally, this method has a high level of security. The size of its blocks (64 bits) is limiting its use, though. The paper aims to propose a modified version of the Blowfish algorithm that performs high‐speed encryption with high throughput and supports 128‐bit block size, enhancing its applicability in various areas. The algorithm can be an alternative to the AES algorithm with limited power consumption. The proposed algorithm is compared with the original Blowfish algorithm based on execution speed, throughput, and the avalanche effect. The algorithm's performance is also evaluated on images based on diffusion properties, image histogram, entropy, and correlation coefficient. [ABSTRACT FROM AUTHOR]

Information security is a domain having extensive applications in the twenty-first century and beyond. Encryption is a technique used to prevent data from being accessed without authorization. Symmetric key encryption algorithms are extremely fast compared to asymmetric key algorithms and hence, are used widely. Blowfish is a symmetric key encryption algorithm that is unpatented, free-to-use, fast, compact, and efficient. It is also a very secure algorithm. But, its 64-bit block size prevents it from being widespread. The paper aims to propose a modified version of the Blowfish algorithm that performs high-speed encryption with high throughput and supports 128-bit block size, enhancing its applicability in various areas. The algorithm can be an alternative to the AES algorithm with limited power consumption. The proposed algorithm is compared with the original Blowfish algorithm based on execution speed, throughput, and the avalanche effect. The algorithm's performance is also evaluated on images based on diffusion properties, image histogram, entropy, and correlation coefficient. [ABSTRACT FROM AUTHOR]

Dimension-stone quarrying optimization is significantly important to increase the recovery ratio of dimension stone and to reduce the cutting cost. Due to fracture-existed rock mass, in the mining operation block size and mining direction influences to the recovery ratio and the cutting cost. Therefore, the paper suggests the quarrying optimization for dimension stone to obtain the highest recovery ratio and the lowest cutting cost, based on optimizing block size and mining direction to get a cutting grid of dimension stone. Through developing an integrated modelling between joint set modelling and cutting grid modelling, intact blocks and fractured blocks were generated. From this, block statistics were conducted to get the maximum recovery ratio of dimension stone and the minimum cutting rate between the cutting area and the recovered block volume, which helps to choose an optimizing block size and mining direction. The research was carried out at Tan Long dimension stone quarry where a block size (0.9m x 0.6m x 1.35m) and a mining direction paralleling to joint set 1 will ensure the highest recovery ratio of 13.87% and the lowest cutting rate of 25 m²/m³. [ABSTRACT FROM AUTHOR]

The microstructure and mechanical properties of 20MnCr5 low alloy steel fabricated using Laser-based powder bed fusion (PBF-LB) have been investigated. 20MnCr5 steel, which has been traditionally fabricated through forging followed by heat treatment has been successfully produced using PBF-LB by optimizing process parameters in the present study. The microstructure consisted of full martensite, exhibiting alternating tempered and non-tempered regions. The effect of laser power on the microstructure and mechanical properties was analyzed. The results showed that the 20MnCr5 steel's microstructure, namely its pore distribution, melt pool size, martensite block, and lath sizes, and the volume of the tempered region varied by laser power. Each of these characteristics was positively correlated with laser power. This result was due to the difference in cooling rate according to laser power. These microstructural characteristics affected the steel's mechanical properties. The yield strength (σ-y) of 1,054–1,096 MPa, ultimate tensile strength (UTS) of 1,126–1,208 MPa and fracture elongation (ε-f) of 10.7%–17.4%. Laser power was positively correlated with both yield strength and ultimate tensile strength, and negatively correlated with fracture elongation. This study showed that 20MnCr5 low alloy steel's mechanical properties can be effectively controlled when producing it using PBF-LB and the optimal process parameters. [ABSTRACT FROM AUTHOR]

Coin selection method refers to the process undergone when selecting a set of unspent transaction outputs (UTXOs) from a cryptocurrency wallet or account to use as inputs in each transaction. The most applied coin selection method that UTXO-based cryptocurrencies currently employ is an algorithm that decides on a certain set of UTXOs that matches the target amount and limits the transaction fee. However this approach trades off favourable maintenance overhead of the entire network for low transaction fees, as many low-value UTXOs known as "dust" is produced. Over time, this will impact the scalability and management of the cryptocurrency network as the global set of UTXOs become larger. Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs. [ABSTRACT FROM AUTHOR]

Abstract Coin selection method refers to the process undergone when selecting a set of unspent transaction outputs (UTXOs) from a cryptocurrency wallet or account to use as inputs in each transaction. The most applied coin selection method that UTXO-based cryptocurrencies currently employ is an algorithm that decides on a certain set of UTXOs that matches the target amount and limits the transaction fee. However this approach trades off favourable maintenance overhead of the entire network for low transaction fees, as many low-value UTXOs known as “dust” is produced. Over time, this will impact the scalability and management of the cryptocurrency network as the global set of UTXOs become larger. Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs.

By using the PoW protocol, mining pools compete to successfully mine blocks to pursue rewards. Generally, the reward from a mined block includes the fixed block subsidies and the time-varying transaction fees. The latter are offered by the senders whose transactions are packaged into blocks and are increasing with the block size being larger. However, the larger block size brings the longer latency, resulting in a smaller probability of successfully mining. Therefore, decision on the optimal block size of a block to trade off two factors above mentioned is a complex and crucial problem for the mining pools. In this paper, we model the repeated mining competition dynamics among mining pools as an evolutionary game, in which each mining pool has two strategies: following the upper bound of block size B ¯ , or selecting a block size smaller than B ¯. Because of the bounded rationality, each mining pool pursues its evolutionary stable strategy (ESS) on block size by continuous learning and adjustments during the whole mining process. A framework is built for the general evolutionary game, based on which we then explore the existence and stability of the ESSs for a case of two mining pools. Numerical experiments using the real Bitcoin data are conducted to demonstrate the theoretical results in this paper. • A framework is built for the general evolutionary game. • Based on the analysis framework, we then explore the existence and stability of the ESSs for a case of two mining pools. • Numerical experiments using the real-world Bitcoin data are conducted to demonstrate the theoretical results in this paper. [ABSTRACT FROM AUTHOR]

Once deployed, a decentralized blockchain system ensures that it will operate faithfully so that no one can interfere with or manipulate its predefined regulations, such as block size and block creation interval investigated in this paper. However, fixed regulations prevent that system from adapting to the change of the environment, such as increasing the underlying network capacity, and result in sub-optimal performance. For example, Bitcoin remains at 7 TPS (transactions per second), even operating over the current Internet. In this paper, we propose a new paradigm for defining the behavior of a consensus system, named as Meta-Regulation, which allows autonomous evolution of the system behavior. A meta-regulation adjusts the actual behavior of a consensus system in response to the changing capacity of the underlying infrastructure and the community of participants. We demonstrate the effectiveness of the proposed meta-regulation by achieving significantly improved throughput and latency for Bitcoin, adapted to the current capacity of the Internet. Our experimental results show that Meta-Regulation can achieve at least $7\times $ performance improvement over Bitcoin network deployed in 2009, resulting in 49.7 TPS or 68% reduction confirmation latency by fully utilizing the bandwidth and the computing power of average network nodes. [ABSTRACT FROM AUTHOR]

Miners in a blockchain system are typically rewarded in two ways - through a fixed block reward, and by the transaction fees that are voluntarily offered by its users. As the available space inside a block is limited, users must compete against each other by submitting higher fees to obtain this limited resource. In this paper, we model blockchain transaction inclusion as a time-sensitive dynamic game, where users base their fees depending on both what their competitors in the network are offering, and by their own urgency of having their transactions approved. We then investigate the effect that mempool congestion (the aggregate size of transactions waiting to be confirmed) and different block sizes have on the fees users would be willing to pay. Our analysis concludes that miners have no rational reason to artificially limit the block size, which is in direct contrast with previous research findings. Instead, we find that increasing the block size in relation to a growing mempool both lowers the individual fees that users have to pay, and increases the total in fees collected, which raises not only the utility of the miners, but also of the regular users of the blockchain system.

In order to study the influence of foundation pit construction on the deformation of underlying tunnel structure, MIDAS is used to calculate the deformation of tunnel structure under different excavation size and excavation sequence, and the tunnel structure is monitored in real time. The results show that when the upper part of the foundation pit is constructed with different block sizes, the vertical deformation of the tunnel structure increases with the increase of the block size of the foundation pit, and the horizontal deformation of the tunnel structure first decreases and then increases with the increase of the block size of the foundation pit; In the process of foundation pit construction, the foundation pits on both sides of the tunnel are constructed at the same time, which has the most advantage to control the tunnel structure deformation; because the tunnel structure is obliquely intersected with the excavation foundation pit in the longitudinal direction, the horizontal deformation of the cross section of the tunnel structure close to the foundation pit sideline is larger. The numerical simulation better reflects the actual deformation trend of the tunnel structure. Affected by the selection of construction parameters, the measured deformation data of the tunnel structure is significantly smaller than that of the numerical simulation value. [ABSTRACT FROM AUTHOR]

Power consumption is likely to remain a significant concern for exascale performance in the foreseeable future. In addition, graphics processing units (GPUs) have become an accepted architectural feature for exascale computing due to their scalable performance and power efficiency. In a recent study, we found that we can achieve a reasonable amount of power and energy savings based on the selection of algorithms. In this research, we suggest that we can save more power and energy by varying the block size in the kernel configuration. We show that we may attain more savings by selecting the optimum block size while executing the workload. We investigated two kernels on NVIDIA Tesla K40 GPU, a Bitonic Mergesort and Vector Addition kernels, to study the effect of varying block sizes on GPU power and energy consumption. The study should offer insights for upcoming exascale systems in terms of power and energy efficiency. [ABSTRACT FROM AUTHOR]

Debris flows (DFs) are dangerous events that can cause the complete destruction of buildings and infrastructure, such as bridges; DFs therefore represent a high risk to public safety in exposed areas. The impact pressures due to these flows are essentially determined by the flow height, velocity and density, but other parameters that are less often considered are also involved. We developed a numerical model to evaluate the impact pressure of mass flows, focusing on a better description of the influence of the blocks transported in these flows: the block size strongly influences the impact pressure, which has a strong effect on structural damage. The numerical model proposed considers a staggered, loosely one-way granular–fluid coupling based on a distinct-element-method code, using the separate simulation results of a computing fluid dynamics code used to model the fluid phase. This model estimates the impact pressure distribution due to blocks at the local scale of the obstacle; the pressure due to the fluid phase can be added afterwards. The pressure applied by the DF increased with the maximum block size for a given set of DF characteristics: velocity, height and apparent density. The vulnerability of a given structure depends on the intensity of DFs: the pressure applied on the structure is one of considerable intensity. The existing vulnerability functions are interpreted in the light of the results obtained with the numerical model. This interpretation highlights the need to integrate new parameters in the intensity to better evaluate structures' vulnerability to debris flows. [ABSTRACT FROM AUTHOR]

Phyllite bimrocks are widely distributed in the eastern margin of the Tibetan Plateau, and it is the main geomaterial for landslides, slopes, dam basement and subgrades in this area. However, the flow behavior of phyllite bimrocks is unknown, especially the flow behavior of phyllite bimrocks with the orientation of blocks. This paper reports the coupling characteristics of flow and orientation of blocks in phyllite bimrocks. The flow behavior of phyllite bimrocks with different block percentages and block sizes was studied by a series of permeability experiments. A large-scale permeability apparatus was designed, and specimens with varying percentages of block and block sizes were produced by the same dip angle of blocks and compaction degree. Based on the Reynolds number analysis, it was found that the flow in phyllite bimrocks becomes laminar to turbulent under lower hydraulic gradient, and the flow behavior of phyllite bimrocks does not obey Darcy’s law. Furthermore, the Forchheimer equation is better at analyzing the flow behavior of phyllite bimrocks compared with Izbash equation. In addition, based on the coefficients a in the Forchheimer equation, the hydraulic conductivity of phyllite bimrocks can be calculated. The calculation result shows that when the percentage of blocks is 25%, the hydraulic conductivity reaches the minimum. Besides, the hydraulic conductivity increases approximately linear with the block size increase. On the basis of previous studies, coefficients A and B of the Forchheimer equation are detected by the normalized objective function analysis. The results would provide a valuable reference for risk assessment and prevention of phyllite bimrock slope.

• A quadratic optimization method was proposed for large-scale PV field leveling. • The quadratic optimization method provides optimal field leveling scheme with the least engineering quantity for PV plants. • The quadratic optimization method substantially improves design efficiencies, and provides more applicable outputs. • Slope ratio and block size significantly influence the cut-and-fill volume. Field leveling is crucial for efficiency and performance optimization of concentrated photovoltaic (PV) plants due to their large areas and uneven terrain. Manual adjustment combined with the block plane method is conventionally used for PV field leveling design, which is time-consuming and laborious with non-optimized results. There's a lack of optimization method for large-scale PV field leveling. This paper introduces a quadratic programming-based optimization approach, dividing the leveling plane into grids and utilizing a hyperbolic paraboloid to model the surface. Constraints are imposed based on earthwork balance and slope ratio, with the objective function being the minimization of total cut-and-fill volume. The globally optimal solution for large-scale PV field leveling is through MATLAB R2022a programming. Case studies demonstrate that the quadratic optimization method, compared to the traditional block plane method, can yield savings of 55 % to 78 % in cut-and-fill volumes, with faster computation and more practical outputs. Moreover, the method proves to be more effective as site area and topography complexity increase. Parametric analyses obtain a critical slope ratio of 2 %, below which the cut-and-fill volumes are significantly impacted by the slope ratio, while above which, the influence diminishes. Meanwhile, the cut-and-fill volumes are found to increase continuously as the block size increases, while remaining mostly constant when the grid size changes within a range of 5–30 m. These findings highlight the significant influence of design slope ratio and block size on the cut-and-fill volume, while the grid size has a minor impact. Recommended parameters for PV field leveling design include a design slope ratio of 3 % to 7 %, a grid size of 5 to 20 m, and a block size of 30 to 50 m. This proposed method provides an optimization method for field leveling design of large-scale PV plants. It achieves the least engineering quantity, substantially improves design efficiencies, and provides more applicable outputs. [ABSTRACT FROM AUTHOR]

Most mining activities depend on the grade and tonnage of ore reserves; therefore, it is significant to know the validity of estimating the grade and reserve of ore deposits. A key parameter in determining the quality of grade estimates in modeling the reserves is the block size. The main purpose of this research is to estimate the grade of exploratory blocks based on the subsurface data using geostatistical methods in the C-North iron ore reserve, northeast Iran. The grade block model was created using variograms via the kriging estimator (ordinary kriging). In order to model the ore reserve in three dimensions, the ideal block size was obtained using Vlse Kriterijumsk Optimizacija Kompromisno Resenje method. While conducting OK estimation, cross-validation was used for variogram generation that resulted in more accurate estimates for the ore reserve when compared to the local model. OK model results estimated 82 million tons of reserve with an average grade of 41.9 percent iron. The C-North ore reserve has been categorized based on the relative estimation error variance and the Australasian Code for Reporting of Mineral Resources and Ore Reserves. [ABSTRACT FROM AUTHOR]

Blockchain-based applications come up with cryptocurrencies, especially Bitcoin, introducing a distributed ledger technologies for peer-to-peer networks and essentially records the transactions in blocks containing hash value of the previous blocks. Block generation constitutes the basis of this technology, and the optimization of such systems is among the most crucial concerns. Determining either the block size or the number of transactions in the block brings out a remarkable problem that has been solved by the miners in recent years. First, higher block size results in higher transaction time, on the other hand, smaller block size has many disadvantages such as security, lower transaction fees, lower transaction numbers in a given time interval, which makes it unable to compete with other currency systems due to this bulky structure and higher block generation time. In this study, multiobjective optimization problem (OP) is proposed by minimizing block generation and transmission time. This multiobjective OP is transformed into a single OP by applying weighted sum method. To determine the optimal block size, particle swarm optimization (PSO) algorithm and whale optimization evolutionary algorithm (WOA) are employed. Although both algorithms have capability to reach optimum block size and corresponding time, WOA achieves better performance than PSO in terms of the convergence speed and output fluctuation. Moreover, analysis of the prediction of optimum block size is carried out under different weights which creates many optimization functions. Experimental results indicate that if higher weight is assigned to the transmission time, then block size decreases sharply. Furthermore, the experimental results reveal that design of the blockchain network and number of nodes in network profoundly affect the block size selection due to the time constraints. [ABSTRACT FROM AUTHOR]

The process of creating a geological block model as the basis for a further detailed design and planning of mining operations is a very responsible task. Errors made during this initial process are transferred to all other phases of the mining project. Certainly, one of the most important decisions for the modelling process is the choice of the appropriate size of the blocks that form the model itself. The determination of the optimal block size is not a simple process, because it depends on a large number of affecting factors and criteria. This process can be significantly facilitated by the application of multi-criteria analysis methods, which enable establishment of interdependence between the criteria in order to select the optimal solution. This paper presents the possibilities of applying the Analytical Hierarchical Process (AHP) method for selecting the optimal block size for the needs of the coal deposit modelling process and mine planning, as well as the way in which this method can significantly facilitate problem solving, by looking at it from several aspects. The analysis included six criteria and four potential solutions, and the results themselves indicated the advantages and disadvantages of the applied method.

As the basis of stereo observation, epipolar resampling is a critical technology for 3D reconstruction. With the development of the 3D reconstruction using multi-view satellite images, the epipolar resampling of the multi-view satellite images has become a new challenging problem. In this paper, we propose an epipolar resampling method for multi-view high resolution satellite images based on block. Firstly, we establish the relationship between the vertical parallax and image block size for the epipolar resampling based on block. Using this relationship, we can choose the block size to limit the maximum vertical parallax in epipolar resampling. Secondly, we use the rational function model (RFM) to generate virtual corresponding points for fundamental matrix estimation, so image pairs with large stereo angles and poor consistency in multi-view satellite images which are difficult to extract feature matching point can be rectified. Experiments with multi-view satellite images demonstrated the universality and effectiveness of the proposed method. All the image pairs in the multi-view satellite image dataset were rectified successfully. The average epipolar resampling error is only 0.25 pixels when we rectify the multi-view satellite images acquired by WorldView-3 with the block size of 3000*3000 pixels, significantly less than the similar method.

Superblocks are city blocks whose size is significantly larger than average. Despite their widespread use across countries such as China, few studies have investigated how these superblocks affect network traffic performance. This paper aims to narrow that gap in knowledge. To that end, we use a grid network emulating a dense city environment. Then, multiple scenarios corresponding to size, location, shape, and number of superblocks are designed by removing nodes and related links. We evaluate network traffic performance by considering the factors of travel distance, travel time, volume-to-capacity ratios on nodes and links, as well as the level of traffic heterogeneity. The results indicate that superblocks with relatively small size (i.e. less than 1/4 of the network size) do not affect traffic significantly. The importance and connectivity of nodes and links related to superblocks are crucial factors affecting the overall traffic performance. In general, the more central the superblock, the larger its influence on the network traffic, except for extremely large superblocks that can significantly affect traffic when located in the periphery, as they lead to high traffic heterogeneities. Rectangular superblocks are more detrimental than square ones. Furthermore, traffic performance can be significantly improved by dividing the superblock into several relatively smaller blocks. Our results should be of direct interest to city-planning decision-makers in dense urban centers.

The increasing interest in fine-grained blocks requires a deeper understanding of the impact of block size on urban vitality. To date, limited empirical tests of the underlying relationships at the city level have been conducted using the ordinary linear-squares method, assuming a linear relationship. However, urban vitality is a complex system, thus making the use of linear regressions unfeasible because the assumption of homogeneity of variance would be violated. Therefore, the constraint line method was introduced to deepen the understanding of the relationship between block size and urban vitality. This paper employed a kernel density estimation of small catering businesses, point of interest density, social media check-in density, and comment density as proxies of urban vitality. Wuhan is the largest megacity in Central China and has been selected for this case study. When the block size increased to almost 0.08 km2, the maximum kernel density estimation value decreased sharply from above 2.70 to 1.60; when the block size exceeded 0.30 km2, vitality values tended to decrease very slowly. The maximum urban vitality measured by the other three indicators dropped an order of magnitude when the block size increased to 0.06 km2, then gradually slowed down, and tended toward a plateau when the block size increased beyond 0.20. Therefore, the dynamic process can be divided into three phrases with multiple critical thresholds of block size. These are approximately 0.06, 0.08, and 0.20 km2 ranked from the best to worst. The study indicates that block size has a nonlinear and threshold effect on urban vitality by constraining the maximum urban vitality. In general, the positive effect of small block size over urban vitality was confirmed, and additionally, urban planners should propose urban planning schemes with smaller residential blocks below 0.06 km2. [ABSTRACT FROM AUTHOR]

Debris flows (DFs) are dangerous events that can cause the complete destruction of buildings and infrastructure, such as bridges; DFs therefore represent a high risk to public safety in exposed areas. The impact pressures due to these flows are essentially determined by the flow height, velocity and density, but other parameters that are less often considered are also involved. We developed a numerical model to evaluate the impact pressure of mass flows, focusing on a better description of the influence of the blocks transported in these flows: the block size strongly influences the impact pressure, which has a strong effect on structural damage. The numerical model proposed considers a staggered, loosely one-way granular–fluid coupling based on a distinct-element-method code, using the separate simulation results of a computing fluid dynamics code used to model the fluid phase. This model estimates the impact pressure distribution due to blocks at the local scale of the obstacle; the pressure due to the fluid phase can be added afterwards. The pressure applied by the DF increased with the maximum block size for a given set of DF characteristics: velocity, height and apparent density. The vulnerability of a given structure depends on the intensity of DFs: the pressure applied on the structure is one of considerable intensity. The existing vulnerability functions are interpreted in the light of the results obtained with the numerical model. This interpretation highlights the need to integrate new parameters in the intensity to better evaluate structures’ vulnerability to debris flows.

Spatial scale is an eternal topic in landscape pattern related analysis. This paper examined the spatial scale effect of landscape pattern changes and their relationships with urbanization indicators in Qingdao using a series of sampling blocks. The results indicated that, with the increasing block scale, the mean patch density and aggregation within a block decreased, whereas the diversity increased. Furthermore, the expanding scale amplified the mean change ratio of landscape metrics and eliminated local drastic changes and regional variation trends along an urban-to-rural gradient, which would be obvious at a finer block scale. Meanwhile, the adjusted R2 of GWR (Geographically Weighted Regression) models increased with an increasing block size, especially when the block scale changed from 1 km to 5 km. Odd-numbered block scales performed better than even-numbered block scales.

Propagation time on permissionless blockchain plays a significant role in terms of stability and performance in the decentralized systems. A large number of activities are disseminated to the whole nodes in the decentralized peer-to-peer network, thus causing propagation delay. The stability of the system is our concern in the first place. The propagation delay opens up opportunities for attackers to apply their protocol. Either by accelerating or decelerating the propagation time directly without proper calculation, it brings numerous negative impacts to the entire blockchain system. In this paper, we thoroughly review and elaborate on several parameters related to the propagation time in such a system. We describe our findings in terms of data communication, transaction propagation, and the possibility of an interference attack that caused an extra propagation time. Furthermore, we present the influence of block size, consensus, and blockchain scalability, including the relation of parameters. In the last session, we remark several points associated with the propagation time and use cases to avoid dilemmas in the light of the experiments and literary works. [ABSTRACT FROM AUTHOR]

Summary: Graphics Processing Units (GPUs) are used as accelerators for improving performance while executing highly data parallel applications. The GPUs are characterized by a number of Streaming Multiprocessors (SM) and a large number of cores within each SM. In addition to this, a hierarchy of memories with different latencies and sizes is present in the GPUs. The program execution in GPUs is thus dependent on a number of parameter values, both at compile time and runtime. To obtain the optimal performance with these GPU resources, a large parameter space is to be explored, and this leads to a number of unproductive program executions. To alleviate this difficulty, machine learning–based autotuning systems are proposed to predict the right configuration using a limited set of compile‐time parameters. In this paper, we propose a two‐stage machine learning–based autotuning framework using an expanded set of attributes. The important parameters such as block size, occupancy, eligible warps, and execution time are predicted. The mean relative error in prediction of different parameters ranges from of 16% to 6.5%. Dimensionality reduction for the features set reduces the features by up to 50% with further increase in prediction accuracy. [ABSTRACT FROM AUTHOR]

We study the asymptotic behavior of the maximal multiplicity Mn = Mn(σ) of the block sizes in a set partition σ of [n] = {1,2,...,n}, assuming that σ is chosen uniformly at random from the set of all such partitions. It is known that, for large n, the blocks of a random set partition are typically of size W = W(n), with WeW = n. We show that, over subsequences {nk}k ≥ 1 of the sequence of the natural numbers, Mnk, appropriately normalized, converges weakly, as k→∞, to max{Z1,Z2−u}, where Z1 and Z2 are independent copies of a standard normal random variable. The subsequences {nk}k ≥ 1, where the weak convergence is observed, and the quantity u depend on the fractional part fn of the function W(n). In particular, we establish that limk→∞1/(2π)1/4min{fnk,1−fnk}nk/log7/4nk=u∈[0,∞)∪{∞}. The behavior of the largest multiplicity Mn is in a striking contrast to the similar statistic of integer partitions of n. A heuristic explanation of this phenomenon is also given. [ABSTRACT FROM AUTHOR]

Two new encryption algorithms for secure video transmission are proposed in this paper. The two algorithms employ different types of chaotic maps to generate the keystream for encrypting the video frames. Both algorithms involve a substitution step and a permutation step to achieve confusion and diffusion requirements. For efficient transmission, the video file is compressed before being encrypted. In the basic implementation of both algorithms, MPEG‐2 standard is used for compression. However, the algorithms are shown to be compliant with other compression techniques. In the permutation step, the effect of the block size used in the shuffling process is examined. Smaller blocks result in increasing the processing time, while reducing both the correlation between adjacent pixels and the peak‐signal‐to noise ratio of an encrypted frame. The use of a Feistel structure is investigated to enhance security and its negative impact on the encryption time is demonstrated. The experimental results of the two proposed schemes confirm that they represent different tradeoffs between security and computational efficiency. Both schemes are sensitive to slight variations in the encryption key as apparent from the obtained differential measures. The conducted comparative study shows the competitiveness of the proposed schemes to existing schemes in literature. [ABSTRACT FROM AUTHOR]