Original Scheme Research Articles

An efficient HLL-based scheme for capturing contact-discontinuity in scalar transport by shallow water flow

An efficient numerical scheme is developed for coupled hydrodynamic and scalar transport systems to guarantee the conservation and the positivity-preserving properties for water depth and scalar concentration. A second-order well-balanced positivity-preserving central-upwind scheme based on the finite volume method is adopted to discretize both the Saint-Venant system and the advective fluxes in the scalar transport system. In particular, an anti-diffusion modification is augmented in an ad hoc manner to the Harten–Lax–van Leer approximate Riemann solver for the scalar transport system, with the aim of significantly reducing the numerical diffusion near contact discontinuities. The proposed scheme is validated through seven numerical experiments, wherein the advection and diffusion processes of scalar transport are considered either separately or in combination. Accuracy is measured based on the difference between the numerical results and analytical solutions, and the performance of the proposed scheme is assessed by comparing it with that of the existing scheme. Convergence analysis confirms that the proposed scheme is accurate to the second order. The stationary steady state with wet-dry fronts is simulated, which verifies that the proposed scheme can preserve the exact C-property. The results for the pure diffusion case reveal that the original scheme has limitations in precisely predicting scalar diffusion when the diffusion coefficient is small. By contrast, the proposed scheme accurately approximates scalar diffusion, even at low diffusivity. The results under flow conditions with various Froude and Péclet numbers confirm that the proposed scheme is more accurate than the existing scheme in solving scalar transport problems over a wide range of shallow water flows.

A Large Time Step Wave-Adding Simple Scheme for Unsteady Compressible Flows

In this paper, we construct a large time step wave-adding scheme (LTS-WA) for unsteady Euler equations in compressible flows with a much simpler strategy in the wave-adding procedure, named LTS-WAS. The new method does not need to calculate coefficients of contribution and also add the waves according to their types and families, which makes the scheme easy for coding and optimisation. The new scheme has a high speedup ratio, and its formulation is the same in scalar and system cases. The scheme is extended to 3D compressible flows using the dimension split method. Numerical experiments show that the new scheme maintains the advantages of the original LTS-WA scheme at large CFL numbers, and has a higher efficiency.

Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample

BackgroundIn 2014, the National Institute of Health Pain Consortium’s research task force (RTF) on research standards for chronic low back pain (CLBP) proposed the Impact Stratification Score (ISS) as a patient-reported outcome measure that could stratify patients by the impact CLBP has on their lives. This work compares three newly developed ISS-based classifications to the RTF’s original to provide an optimal recommendation.MethodsThe online sample included 1226 individuals from Amazon’s Mechanical Turk who indicated having non-specific CLBP, average age of 40, 49% female, and 67% White. Participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items as well the Roland-Morris Disability Questionnaire (RMDQ) and Graded Chronic Pain Scale (GCPS). Other items included high-impact chronic pain; not working due to health problems; overall health; and number of healthcare visits for back pain in the past 6 months. Three new classifications were created using quartiles (Classification 2), latent profile analysis (Classification 3), and one modeled after the GCPS (Classification 4). Classifications were subsequently compared to the RTF-proposed classification (Classification 1) on several concurrent and prognostic criteria.ResultsClassification 1 had three CLBP severity groups, four in Classification 2, three in Classification 3, and four in Classification 4. All novel classifications improved upon the original. Classification 2 performed best at minimizing the classification of those with negative outcomes into the lowest severity groups at baseline (e.g., 11% with RMDQ ≥ 7) and 6 months (e.g., 8.2% had fair/poor health). Classification 4 performed best at maximizing classification of those with negative outcomes into the most severe group concurrently (e.g., 100% had GCPS grade ≥ 2) and at 6 months (e.g., 100% with RMDQ ≥ 7).ConclusionsWe developed three ISS-based classification schemes and tested them against several outcomes. All three improved upon the original scheme. While appearing more optimal than other classifications in the lowest severity groups, Classification 2 presents some considerations and limitations. Given that Classification 4 was an improvement at the lowest end of severity and was the best at the highest end, it is our tentative recommendation that this approach be adopted to classify individuals with non-specific CLBP.

Syuzevskoye diamond placer: A new stage in studying the diamond potential of Western Urals

Research subject. Geological features of the structure and composition of the Syuzevskoye diamond placer in the Aleksandrovsky region of the Perm Krai. The placer was found in the border zone of two regional tectonic structures of the Urals: the Western Ural outer folding zone and the Central Ural uplift. This placer was developed within the erosion-karst (?), erosion-structural or tectonically determined Chikman-Nyarskaya depression. Materials and methods. The placer was identified in the period from 2017 to 2022 during a geological study of the subsoil area “Glubokiy” (License PEM 02687 KP LLC “Almining”). Mining and enrichment works were carried out according to the original enrichment scheme using the clamshell sampling method, heavy media and electromagnetic separation. The morphometric characteristics of several hundred diamonds were identified and described; reports were prepared; and reserves were assessed. Results. In the section of the Syuzevskoye placer, two diamond-bearing strata are clearly distinguished, separated by poor- and non-diamond-bearing deposits; anomalously high seam thickness for the Ural placers (up to 14-16 m) was established; high areal productivity of the placer (up to 0.7-1.2 ct/m2) and high diamond content (up to 0.5 ct/m3 per sample and an average of 0.09 ct/m3 for the placer). The placer is attributed to the type of placers of tectonic scarp zones. Reserves of alluvial diamonds weighing 430.5 thousand ct of the Syuzevskoye deposit are estimated at C1 + C2 categories in the area limited by the area between exploration lines 107-116 (size 1000 x 750 m); approved by the Minutes of the GKZ Rosnedra No. 7139 dated November 18, 2022 and will be increased. Certificate No. PEM 23 DRK 10147 confirming the discovery of a mineral deposit, issued by the Federal Agency for Subsoil Use of the Russian Federation to LLC Almining on March 29, 2023. Over 90% of diamonds are of gem quality. The average mass of crystals in the reserve calculation loop is 87 mg, and behind the loops is 29 mg. The leading size classes by mass -8 + 4 and -4 + 2 mm are 93.9% and 72.3% in quantity with an average mass of a diamond crystal of 99.9 mg. The shape is dominated by dodecahedroids (66.9%), less fragments of crystals with an unpreserved shape (14.9%) and fragments of crystals (13.1%); octahedrons (2.4%) and tetrahedroids (2.2%) are rare, rhombic dodecahedroids (0.4%) are rare. The preservation of crystals is good: full crystals make up 63.7%, fragments of crystals - 16.3%, fragments - 12.9%. Most of the crystals do not have wear (42.4%), or have weak wear of the tops and ribs (43.0%), medium and strong wear was noted only in 13.7% of the crystals. The average cost of diamonds is estimated at 361.59 USD per 1 ct. Conclusions. A unique deep-seated diamond deposit has been discovered, which is considered as a new type of deep-seated diamond-bearing placers in tectonic ledge zones. The geological criteria for identifying such diamond deposits in the Urals were determined. A new technological scheme for prospecting and exploration of deep-seated diamond placers within erosion-karst and tectonically determined depressions was developed, which is applicable for prospecting for precious metal placers.

Sliding-mode observer-based fault diagnosis and fault-tolerant control of the main drive system of rolling mill

In order to address the problem that the main drive system of rolling mill is easily affected by the impact of biting steel, and considering the nonlinear friction damping and the external perturbations of the main drive system of rolling mill during the rolling process, a fault model of the main drive system of rolling mill is established, and a fault diagnosis and fault tolerance control method of the main drive system of rolling mill based on the nonlinear sliding-mode observer is proposed. In order to suppress the influence of external perturbations on fault diagnosis, a nonlinear sliding-mode observer is constructed for fault diagnosis and fault reconfiguration of the system, and the robustness of the observer to fault reconfiguration is improved by using the sliding-mode control rate [Formula: see text], and the stability of the designed nonlinear sliding-mode observer is proved using Lyapunov’s stability theorem. In order to ensure that the system can operate normally even after a fault occurs, a reference model is designed, and a new controller is redesigned for fault-tolerant control of the system by adding a fault compensation term to the original control scheme using fault estimation information. Through the simulation study of the main drive system of stand F4 of 2030 mm cold rolling mill, it is verified that the observer can accurately track the system state with an angular velocity error of 2.45% and detect and estimate the main drive system failure of rolling mill with an estimation error of no more than 0.04% after a fault occurs; the fault-tolerant control of the main drive system of rolling mill is carried out by using the fault information to restore the system to its normal state, and the angular velocity error is 1.89%.

A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference

Rescheduling is the guarantee to maintain the reliable operation of production system process. In production system, the original scheduling scheme cannot be carried out when machine breaks down. It is necessary to transfer the production tasks in the failure cycle and replan the production path to ensure that the production tasks are completed on time and maintain the stability of production system. To address this issue, in this paper, we studied the event-driven rescheduling policy in dynamic environment, and established the usage rules of right-shift rescheduling and complete rescheduling based on the type of interference events. And then, we proposed the rescheduling decision method based on genetic algorithm for solving flexible job shop scheduling problem with machine fault inter-ference. In addition, we extended the "mk" series of instances by introducing the machine fault interference information. The solution data show that the complete rescheduling method can respond effectively to the rescheduling of flexible job shop scheduling problem with machine failure interference.

Field Extended Birefringent Static Doppler Wind Imaging Interferometer

According to the requirements for wide field of view and high resolution in wind imaging detection, the principle of a novel field extended birefringent wind imaging interferometer is proposed. Based on the principle of birefringent polarization wind imaging interferometer, the new optical system scheme of the field extended birefringent static Doppler wind imaging interferometer is designed, which overcomes the limitation of the field of view in the original birefringent polarization wind imaging interferometer. Compared with the original scheme, the new scheme eliminates the cross-field phase change between the top and bottom fields, and the available field of view of the instrument is no longer limited. The Jones matrix model are used to simulate to prove the correctness of the principal scheme of the field extended birefringent wind imaging interferometer.

2DH modelling and mapping of surfbeat-driven flooding in the shadow of a jettied tidal inlet

Near estuaries and harbours, submerged shoals and defence structures impact the exposure to overtopping. These features may be accounted for in two-dimensional horizontal (2DH) numerical models, either based on phase-resolving or phase-average solvers for wave propagation. In between, surfbeat solvers, such as in XBeach, combine an affordable computational cost with the ability to generate and propagate the longer infragravity (IG). However, surfzone wave characteristics and the overtopping exposure modelled with XBeach are sensitive to settings such as the shape of the forcing wave spectra and the numerical scheme for wave propagation. The present paper explores this sensitivity and assesses the performance of different inundation models built with the 2DH surfbeat solver of XBeach. These models were forced with downscaled water levels and directional wave spectra and the results fuelled a discussion bounded by data collected downdrift of the entrance to the harbour of Figueira da Foz (Portugal). The original second-order upwind scheme, which propagates short-waves with a lower numerical diffusion improved the model performance in terms of long-wave height, and an unconventional breaking criterion better represented the cross-shore distribution of short-wave height near the shore. A calibrated model was validated through the hindcast of an overtopping event observed under moderate swell forcing, and was used to map the overtopping exposure during a hypothetical combination of an energetic swell with a water level having a return period of ∼70 years. Compared to the default wave spectra shape and model settings, using an appropriate representation of the short-wave directional spectrum at the open boundary was necessary to reproduce the observed overtopping extent. Refining the cross-shore resolution of the model helped to better represent the observed inundation extents, as also did the reduction of the friction coefficient. Additional phase-resolving simulations in 1DH overestimated IG wave energy and produced higher and more frequent overtopping discharges. However, differences with the calibrated 2DH surfbeat model increased with the proximity of the inlet and with short-wave height and angle of incidence. Overall, required calibration steps were provided. They aim at making 2DH XBeach surfbeat a credible tool for 1) predicting short and IG wave characteristics until the shoreline, as well as for 2) providing first estimates of exposure to overtopping in areas with shallow and alongshore-irregular morphologies.

Optimization of Daily Trading Strategy

This study proposes a novel method that integrates variational pattern decomposition (VMD), long short-term memory (LSTM) models, and particle swarm optimization (PSO) to optimize daily trading strategies for a portfolio. By analyzing historical price data for gold and bitcoin, we have successfully identified the optimal investment actions (buy, hold, or sell) for a portfolio comprising different assets. The VMD-LSTM model proposed by us mitigates the long-term dependence problem of machine learning algorithm RNN in financial time series prediction through batch normalization optimization, and realizes the accurate prediction of the future price of gold and bitcoin, whose R-squared values reach 0.99 and 0.98 respectively. We also applied the particle swarm optimization algorithm to a sequence of trading decisions generated by predicting prices, ultimately obtaining a maximum portfolio value of $20,560,265.5, which is more than 14.2 times the 10-year growth of Bitcoin and 12,310.5 times the 10-year growth of gold. By verifying the universality and local optimal properties of our model, we use the Sharpe ratio as an objective function to evaluate the effect of the portfolio. After several perturbation tests, the results show that the original scheme is superior to other perturbation schemes considering the Sharpe ratio and the final return, which verifies the validity of the investment scheme selected by us as the local optimal value. These findings make our research more coherent and provide investors with a reliable basis for making decisions to achieve long-term capital appreciation and risk control.

METHODOLOGICAL ASPECTS OF INTERSPECIES EXTRAPOLATION OF EXPERIMENTAL DATA UNDER PULSED ACOUSTIC INFLUENCE ON BIOOBJECTS (REVIEW)

Background. Despite a significant number of theoretical and experimental studies, the issue of determining the threshold levels of pulsed acoustic exposure, when exceeded, their negative effect on the morphofunctional state of a biological object begins to appear. Traditionally, in laboratory conditions, such estimates are obtained in experiments on animals, varying the parameters of exposure, followed by extrapolation of the results obtained to humans. However, the pathophysiological mechanisms of disturbances that develop in experimental animals as a result of impulse acoustic impacts have not been sufficiently studied in this context, and indicators of the state of the physiological systems of a biological object that are sensitive to acoustic impulses are not currently taken into account when determining their safe levels.
 Purpose. The purpose of the work was to analyze the pathophysiological mechanisms of the development of biological effects of pulsed low-intensity acoustic exposure at different levels of the organization of a living system and to develop a methodological approach to obtaining a quantitative assessment and extrapolation of data on such exposure from animals to humans, taking into account the physical parameters of the acoustic factor and characteristics of the state of the experimental biological object.
 Materials and methods. The selection and systematic review of the scientific literature on the topic of research by keywords in specialized bibliographic databases was carried out.
 Results. The analysis and generalization of the existing theories about the pathophysiological mechanisms of the biological action of acoustic impulses at different levels of the organization of a living system have been carried out. An original hypothetical scheme for interpreting the effects of acoustic exposure in animals is proposed, which is suitable for obtaining threshold estimates of the levels of the adverse effect of the factor on clinical parameters in experimental animals, and vulnerable critical links in the regulation of external respiration in mammals that cause the damaging effect of acoustic vibrations are identified. A scientific and methodological approach to interspecies extrapolation of medical and biological effects of exposure to low-amplitude air pressure waves from animals to humans has been developed, taking into account the anatomical and physiological parameters of the respiratory system of experimental animals, as well as the informative characteristics of the acoustic pulse. An empirical model is proposed that makes it possible to predict the threshold levels of the conditional power of adverse acoustic effects in humans using data on the development of lung damage in experimental animals of various biological species, and the features of setting up such a model are formulated.
 Conclusion. It has been substantiated that it is relevant to refine the proposed empirical model and develop a theoretical model for extrapolation of the initial experimental data on the threshold of safe acoustic exposure from animals to humans, taking into account the interspecific patterns of functioning of physiological systems of the body that are critical to the impact.

Multi-objective solution and decision-making framework for coordinating the short-term hydropeaking-navigation-production conflict of cascade hydropower reservoirs

The transformation of energy structure motivates hydropower to participate in peak shaving operations for grid stability, which conflicts with the multiple uses of cascade hydropower reservoirs. To coordinate the principal contradictory tasks of peak shaving, ship navigation, and power generation in day-ahead scheduling, a mixed integer linear programming model for the short-term multi-objective optimal scheduling is constructed. Specifically, a novel power release-based indicator is adopted to describe the navigation objective, while the minimization of the peak-valley difference of the residual load and the total water released are taken as the other two objective functions. Constraint aggregation and rectangular meshing methods are employed to handle the challenging nonlinear and nonconvex constraints. Subsequently, the Normalized Normal Constraint method, integrated with the mathematical optimization solver Gurobi, generates a set of well-distributed Pareto solutions, each representing a scheduling scheme. Finally, the Combined Weighting - Technique for Order Preference by Similarity to Ideal Solution is utilized as a decision-maker to trade off and determine a compromise solution for final implementation. Case studies on the cascade hydropower reservoirs of the Wujiang River in China demonstrate that the proposed model can adequately characterize the demands of various stakeholders, and the suggested framework can obtain an even and extensive Pareto front, mediate conflicts, and make reasonable decisions. Compared to the original peak-shaving scheme, the finalized compromise scheme reduces the peak-shaving effect by just 27.82% but offers simultaneous boosts of 96.54% in navigation benefits and 10.88% in power generation benefits. Consequently, the presented framework can be a promising alternative for conflict resolution of cascade hydropower reservoirs.

One-dimensional ice shelf hardness inversion: Clustering behavior and collocation resampling in physics-informed neural networks

We investigate the use of Physics-Informed Neural Networks (PINNs) for ice shelf hardness inversion. PINNs were trained to invert for ice shelf hardness (B) profiles using synthetic datasets of one-dimensional (1D) ice shelf velocity (u) and thickness (h) contaminated by noise, with no training data provided for B. A hyperparameter γ is introduced in the objective function to adjust the relative weight of the neural network fit to training data and its fit to known physical laws. When the data is contaminated by noise, the equation loss should be weighted more heavily than the data loss to de-noise the predictions. However, we observe that PINN predictive performance is highly unreliable when γ is large. The prediction errors are distributed bimodally, with one cluster corresponding to accurate, “low-error” solutions, and the other consisting of “high-error” solutions that fit poorly to the ground truth datasets. The high-error PINN solutions are associated with the failure of the PINN to correctly learn the velocity spatial gradients that appear in the governing equations. We employ an alternative algorithm to improve the PINN inversion accuracy, which we call collocation resampling: the PINN is initially trained for a small number of iterations for which the collocation points for evaluating the equation loss are randomly resampled after each iteration; then, a fixed set of collocation points are used. This approach achieves predictive accuracies comparable to those attained by low-error solutions for the original training scheme with γ1−γ≫1, but with no clustering and minimal computational cost.

S-BDS: An Effective Blockchain-based Data Storage Scheme in Zero-Trust IoT

With the development of the Internet of Things (IoT) , a large-scale, heterogeneous, and dynamic distributed network has been formed among IoT devices. There is an extreme need to establish a trust mechanism between devices, and blockchain can provide a zero-trust security framework for IoT. However, the efficiency of the blockchain is far from meeting the application requirements of the IoT, which has become the biggest resistance to the application of the blockchain in the IoT. Therefore, this paper combines sharding to build an effective Blockchain-based IoT data storage scheme (S-BDS) . Sharding can solve the problem of blockchain capacity and scalability. While the blockchain provides data immutability and traceability for the IoT, it also brings huge demands for data credibility verification. The communication delay in the IoT system seriously affects the security of the system, while the Merkle proof of traditional blockchain occupies a lot of communication resources. This paper constructs Insertable Vector Commitment (IVC) in the bilinear group and replaces the Merkle tree with IVC to store IoT data in the blockchain. The construct has small-sized proof. It also has the ability to record the number of updates, which can prevent replay-attacks. Experiments show that each block processes 1,000 transactions, the proof size of a single data piece is 30% of the original scheme, and proofs from different shards can be aggregated. IVC can effectively reduce communication congestion and improve the stability and security of the IoT system.

An effective reformative memetic algorithm for distributed flexible job-shop scheduling problem with order cancellation

Order cancellation, due to such as customer plan adjustments or market changes, usually occurs in the real production environment of distributed flexible job shop scheduling problem (DFJSP). However, thus far, all exiting researches about DFJSP have not consider order cancellation, which normally leads to resource waste and makes the original scheme infeasible. Hence, in this work, we propose a DFJSP considering order cancellation (DFJSPC) for the first time; and design a reformative memetic algorithm (RMA) to solve the DFJSPC aiming at optimizing the makespan and total energy consumption. In the RMA, a five-layer encoding operator and a new load balancing initialization method are designed to improve the quality of the initial population. Some effective crossover, mutation and local search operators are designed, which can fully expand the solution space of the algorithm and improve its convergence speed. A total of 60 DFJSPC benchmark instances are constructed, and some comparative experiments are carried out among the proposed RMA and three well-known algorithms, namely NNIA, NSGA-II and NSGA-III. The final experimental results verified the outstanding performance of the RMA. This research will provide a theoretical basis for the order cancellation problem in distributed production settings, and help manufacturers to properly handle canceled orders to reduce resource waste and reschedule the infeasible schemes causing from order cancellation.

Improved Genetic Algorithm for Solving Green Path Models of Concrete Trucks

In this paper, for the problem of high total fuel consumption of distribution trucks when multiple concrete-mixing plants distribute concrete together, we established a green fuel consumption model for distribution trucks and solved the model with an improved genetic algorithm to obtain a green distribution scheme for trucks. Firstly, the fuel consumption model is established for the characteristics of commercial concrete tankers; secondly, the adaptive elite retention strategy, adaptive crossover, mutation operator, and immune operation are added to the genetic algorithm to improve it; and finally, the model is solved to obtain the green distribution scheme. The total fuel consumption in this experiment was 189.6 L when the green distribution scheme was used; compared to the total fuel consumption under the original scheme (240 L), the total fuel consumption was reduced by 21.25%. The experimental results show that the total fuel consumption of delivery trucks can be significantly reduced based on the established green fuel consumption model, and the improved genetic algorithm can effectively solve the model.

Optical Time-Mapped Spectrograms (II): Fractional Talbot Designs

Real-time implementations of joint time-frequency analysis over instantaneous bandwidths above the GHz range remain challenging. In a companion paper, we have proposed an analog photonic processing scheme that enables computing a short-time Fourier transform (STFT), or spectrogram (SP), of an incoming arbitrary broadband signal, over tens-of-GHz analysis bandwidths, in a continuous, gapless and real-time manner. The proposed method involves a temporal sampling of the signal under test (SUT) with a periodic train of interfering, linearly chirped optical pulses followed by group-velocity dispersion to map the spectra of consecutive and overlapping truncated sections of the SUT along the time domain. This scheme offers a notable design versatility to customize the performance specifications of the computed SP, but it generally involves a sub-optimal non-uniform sampling of the SUT and it requires the use of a bulky and expensive pulsed optical source. In this communication, we show that this previous general scheme can be easily configured to ensure an optimal, uniform sampling of the SUT by simply setting the involved dispersive lines to satisfy a fractional self-imaging condition, while keeping all the advantages (e.g., design versatility) of the original scheme. Moreover, the resulting design is further adapted to entirely avoid the need for a pulsed source, using instead a more efficient and simpler phase-only temporal sampling of the SUT, e.g., implemented through electro-optic phase modulation. We derive the design conditions and performance trade-offs of the proposed time-mapped STFT schemes based on dispersion-induced fractional Talbot self-imaging. Through numerical simulations and experimental demonstration, we confirm the potential of this simple and efficient approach for real-time SP analysis of arbitrary signals over instantaneous bandwidths above a few tens of GHz, with MHz frequency resolutions and ultrahigh processing speeds, approaching billions of FTs per second.

The Deformation, Failure Mechanisms, and Stability Control of the Surrounding Rock of Deep Cross-Measure Roadway: A Case Study

In view of the difficulty in controlling the surrounding rock stability of deep cross-measure roadways, a deep cross-measure roadway of the Wanfu coal mine, a typical high-stress mine, was monitored on site and analyzed under the original support scheme. The findings show that the degrees of deformation and failure of the cross-measure roadway varied under different working conditions and that the roadway deformation and failure were mainly characterized by a high fragmentation degree and a large failure range of the surrounding rock and the frequent failure of support components. Considering that the different parts of the cross-measure roadway are located in different lithostratigraphic units, establishing a numerical model of the cross-measure roadway under different working conditions; analyzing the deformation pattern of the surrounding rock of the roadway, the plastic range, and the morphological change pattern; and clarifying the deformation and failure mechanisms of the cross-measure roadway based on field monitoring results. On this basis, two types of evaluation indicators, that is, the deformations of the surrounding rock and the plastic ranges in the four typical parts (roof, shoulder, floor, and sidewalls) of the roadway, were selected to rate the stability of the roadway under different working conditions. Grouting reinforcement-based targeted control countermeasures are proposed to improve the surrounding rock stability. Subsequently, numerical analysis and field application of these control countermeasures were carried out to solve the problem of controlling the surrounding rock stability of deep cross-measure roadways.

Digital Archiving of the Spatial Experience of Cultural Heritage Sites with Ancient Lighting

Although adaptive reuse has made the preservation, restoration, and maintenance of architectural heritage sites possible due to the revenue generated by the new program, it has unfortunately induced unavoidable renovations that have altered the original design. Consequently, while the physical configuration of an architectural scene of a heritage site can be preserved and restored to mimic how it looked in the past, how to experience it as rendered with the original lighting design that might no longer be available. With the advancement of technologies related to High Dynamic Range Imaging, light models of various ancient illumination can be reconstructed and used as lighting sources for the virtual environment. Although ancient light sources can now be preserved in this digital form, this technique falls short of preserving the real visual perception of the significant canonical scene of cultural heritage with the originally intended lighting. This study proposes a conceptual framework for the digital archiving of the perceptual realism of the original lighting scheme of an architectural heritage site. The Taiwanese folk religion temples were included in a case study to demonstrate the framework; the study investigated how to identify the discrepancy between the scene-based lighting from the past and that of the current period due to adaptive reuse; further, this study determined the systematic method to select the canonical view that can best invoke the memorial spatial experience of the historical space; additionally, this study provides a case report of the restoration of past lighting with candles made with ancient recipes that were recovered from the field study, and the computational process of documenting scene-based lighting with related technologies using high dynamic range imaging. Finally, the researcher of this study conducted two perceptual experiments. The results of the first experiment demonstrated that the pattern of light and dark induced by the daylight falling into the courtyard plays a significant role regarding the viewers’ preference of the canonical scene of the traditional temple. The second experiment further demonstrated canonical views of three temples illuminated with artificial light, modern candlelight, and ancient candlelight, with ancient lighting being the preferred option of viewers.

Integrating alternating direction method of multipliers and bush for solving the traffic assignment problem

This paper introduces two novel parallel algorithmic frameworks to address the user equilibrium traffic assignment problem (UE-TAP). Most of the existing solution algorithms for the UE-TAP are executed in a sequential manner. This study endeavors to explore parallel computing methods based on model decomposition. Considering that the TAPs can be decomposed based on their origins, thus, following the spirit of the alternating direction method of multipliers (ADMM), a new parallel algorithm B-ADMM is proposed, which integrates the concept of the bush. Subsequently, the convergence of the proposed algorithm is rigorously proven. To enhance the algorithmic parallelism while maintaining the convergence efficiency of the B-ADMM algorithm, this paper further employs the parallel block coordinate descent (PBCD) method to improve the B-ADMM algorithm. We develop a bi-level parallel algorithm PBCD-ADMM, in which the independent origins/bushes are separated into several blocks, and the origin/bush-based restricted subproblems in each block can be solved in parallel. Furthermore, for the given bush belonging to a block, the bush links can also be grouped into several sub-blocks based on the original link-blocking scheme. Thus, these link-based subproblems in each sub-block can also be solved in parallel. A numerical experiment is conducted to validate the proposed algorithms, which indicates that the two new parallel algorithms perform better in terms of convergence speed compared with the original ADMM algorithm.

An Energy Efficient On-Off Keying Transmitted Reference Pulse Cluster System for UWB Communications

In order to overcome the long wideband delay line issue of conventional transmitted reference (TR) ultra-wideband (UWB) systems, a transmitted reference pulse cluster (TRPC) structure was proposed and many related studies have been done. This paper presents a new on-off keying TRPC (OOK-TRPC) structure which can save half of the transmitting energy of the original TRPC scheme. Based on this new structure, an energy detector (ED) is applied and estimating methods for its symbol decision threshold are designed under different signal-to-noise ratio conditions. Analytical and simulation results show the energy efficiency of the proposed OOK-TRPC ED scheme. Therefore, from a practical point of view, the designed OOK-TRPC ED, which also can be applied to some previous TRPC related studies, is considered as a highly recommended practice, particularly in wireless sensor networks, internet of things, and wireless body area networks etc, where energy-saving has been becoming increasingly crucial.