Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Rigidloop Adjustable可调袢钢板治疗踝关节骨折并下胫腓联合损伤

目的比较Rigidloop Adjustable(RLA)可调袢钢板与螺钉治疗踝关节骨折合并下胫腓联合损伤的临床效果。方法回顾性分析2019年9月至2022年5月武汉市第三医院收治的44例踝关节骨折合并下胫腓联合损伤的患者。踝关节骨折行切开复位内固定后,下胫腓联合采用RLA可调袢钢板固定22例,2枚皮质骨螺钉三皮质骨固定22例。应用AOFAS踝与后足功能评分、术侧与健侧踝关节活动度平均差值及术前、术后随访时正位X线片下胫腓间隙(tibiofibular bottom clear space,TBCS)、下胫腓重叠距离(tibiofibular bottom overlap,TBOL)比较两组临床效果。结果患者均获得随访,随访时间12~18个月,平均(16.41±1.66)个月。患者踝关节功能满意,无伤口感染、皮肤激惹等并发症。术后3、6、12个月时,RLA可调袢钢板组双侧踝关节活动度差值均显著小于螺钉组,差异有统计学意义(P<0.05);术后3、6、12个月时,两组的AOFAS评分比较,差异无统计学意义(P>0.05);TBCS、TBOL术前、术后即刻、术后3个月及末次随访时,差异无统计学意义(P>0.05)。结论RLA可调袢钢板和螺钉均可有效固定下胫腓联合,与螺钉固定相比,RLA可调袢钢板组可早期功能锻炼,获得更好的踝关节活动度。

Cross-Cultural Adjustment and Coping:U.S.Students in Taiwan Residents Higher Education

The aim of this study was to investigate the adjustment problems of students from the United States enrolled in universities in the East,specifically in Taiwan,their problems related to cultural adaptation,and the process of adjustment to student life in Taiwan.Under investigation were cultural adjustment and coping skills as these students transitioned from West to East.Qualitative data were collected from interviews with participants and faculty members as well as participant observations.Results indicated that U.S.students found their own ways to acclimate to their new academic setting as well as to social relations,cross-cultural issues,and the linguistic environment in Taiwan to achieve effective adaptation.They made changes in themselves to cope with all situations they encountered.This study provides suggestions for international students abroad in Taiwan,for the Taiwan Residents government,and for universities or colleges in terms of what they should offer to current and future international students.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

An adjusted energy-saving quantity calculation method for building energy-efficient retrofit

Aiming at a comprehensive assessment of energy-saving retrofitting effect on existing buildings,a calculation method is developed to adjust energy-saving quantity in standard condition for comparison under the same conditions. A mathematical model,method theory and calculation steps are given. Error analysis results show that this method can be applied accurately to practical engineering projects. In a case study of energy-saving quantity assessment before and after retrofitting on a certain hospital in Shanghai,with energy simulation software TRNSYS,detailed application of this method is introduced and analyzed. The method is applied to the case of energy-saving quantity assessment to a hospital in Shanghai before and after retrofitting with the energy simulation software TRNSYS.

Hydraulic impactor with impact energy and frequency adjusted independently and steplessly

Based on analysis of the present hydraulic impactor, a new hydraulic impactor with pressure feedback control was developed, whose structure and operation principle were introduced. The results show that the pressure of the impact system can be adjusted steplessly to change the impact energy of the impactor steplessly. By adjusting the oil flow of supply pump steplessly, the impact frequency will also be changed steplessly. So the impact energy and frequency of the new impactor can be adjusted independently and steplessly. In order to decrease the energy loss, a new kind of sleeve valve has been designed, which has features of little leakage, little pressure loss and low energy cost. The new type hydraulic impactor can be operated under various conditions with decreased energy consumption and improved operation efficiency.

Photoluminescence in fluorescent 4H-SiC single crystal adjusted by B,Al,and N ternary dopants

This paper reports the sensitive effect of photoluminescence peak intensity and transmittance affected by B, Al, and N dopants in fluorescent 4H-SiC single crystals. The crystalline type, doping concentration, photoluminescence spectra,and transmission spectra were characterized at room temperature. It is found that the doped 4H-SiC single crystal emits a warm white light covering a wide range from 460 nm to 720 nm, and the transmittance increases from ~10% to ~60%with the fluctuation of B, Al, and N ternary dopants. With a parameter of C_(D-A), defined by B, Al, and N concentration, the photoluminescence and transmittance properties can be adjusted by optimal doping regulation.

DFIG Voltage Control Based on Dynamically Adjusted Control Gains

The increasing penetration of wind power presents many technical challenges to power system operations. An important challenge is the need of voltage control to maintain the terminal voltage of a wind plant to make it a PV bus like conventional generators with excitation control. In the previous work for controlling wind plant, especially the Doubly Fed Induction Generator (DFIG) system, the proportional-integral (PI) controllers are popularly applied. These approaches usually need to tune the PI controllers to obtain control gains as a tradeoff or compromise among various operating conditions. In this paper, a new voltage control approach based on a different philosophy is presented. In the proposed approach, the PI control gains for the DFIG system are dynamically adjusted based on the dynamic, continuous sensitivity which essentially indicates the dynamic relationship between the change of control gains and the desired output voltage. Hence, this control approach does not require any good estimation of fixed control gains because it has the self-learning mechanism via the dynamic sensitivity. This also gives the plug-and-play feature of DFIG controllers to make it promising in utility practices. Simulation results verify that the proposed approach performs as expected under various operating conditions.

IN 1997 SOME IMPORT AND EXPORT TARIFF RATES ADJUSTED

The General Customs Administration issued a circular statingthat,based upon a decision of the State Council,in 1997 someimport and export tariff rates would be adjusted.The major con-tents of the circular are the adjustment of the import tariff rates of 4tariff lines of commodities and items under 124 tariff lines;theelimination of the export tariffs for 14 tariff lines of commodities,addition of export tariff rates for 2 kinds of precious metals andimposition of provisional export tariff rates for 4 kinds of corn-

A Self-calibration Bundle Adjustment Algorithm Based on Block Matrix Cholesky Decomposition Technology

In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.

A Modified Transformed Soil Adjusted Vegetation Index for Cropland in Jilin Province,China

1 Introduction Vegetation indices(VIs)derived from satellite observations are an essential source of information for operational monitoring of the Earth’s vegetation(Qu et al.,2018;Yan et al.,2008).However,soil background dramatically affects the performances ofⅥs(Baret and Guyot,1991;Gilabert et al.,2002;Huete,1988;Qi et al,1994).

Traffic prediction using a self-adjusted evolutionary neural network

Short-term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems.The aim of this paper is to provide a model based on neural networks(NNs)for multi-step-ahead traffic prediction.NNs'dependency on parameter setting is the major challenge in using them as a predictor.Given the fact that the best combination of NN parameters results in the minimum error of predicted output,the main problem is NN optimization.So,it is viable to set the best combination of the parameters according to a specific traffic behavior.On the other hand,an automatic method—which is applicable in general cases—is strongly desired to set appropriate parameters for neural networks.This paper defines a self-adjusted NN using the non-dominated sorting genetic algorithm II(NSGA-II)as a multi-objective optimizer for short-term prediction.NSGA-II is used to optimize the number of neurons in the first and second layers of the NN,learning ratio and slope of the activation function.This model addresses the challenge of optimizing a multi-output NN in a self-adjusted way.Performance of the developed network is evaluated by application to both univariate and multivariate traffic flow data from an urban highway.Results are analyzed based on the performance measures,showing that the genetic algorithm tunes the NN as well without any manually pre-adjustment.The achieved prediction accuracy is calculated with multiple measures such as the root mean square error(RMSE),and the RMSE value is 10 and 12 in the best configuration of the proposed model for single and multi-step-ahead traffic flow prediction,respectively.

致癌物评估实验中的Time-adjusted趋势检验

在致癌物评估实验中 ,随药物剂量的增加 ,动物死亡率变化呈现某种趋势 .本文给出分组评估实验中的 time-adjusted趋势检验和相关参数的极大似然估计 。

Improvement of the Algorithm for Computing Adjusted Structure Number for Determination of Backlog Maintenance

The pavement strength is very important for the evaluation of backlog maintenance. The current trend in many developing countries used pavement conditions index-PCI in estimating maintenance costs. The PCI can only justify periodic and routine recurrent maintenance. The condition strength is rarely determined in a flexible pavement creating an opportunity for back long maintenance. This paper reports the study conducted to develop and improve the algorithm for estimating the adjusted structure number to estimate the remaining thickness of the flexible pavement. The analysis of eight ways of computing structure numbers from FWD data ware analyzed and found that the improvement of the HDM 3 - 4 models can influence the usefulness of data collected from road asset management in Tanzania. The algorithm for estimating structural numbers from CBR was improved to compute adjusted structural numbers finally used to estimate the remaining life of the flexible pavement. The analysis of the network of about 6900 km including ST and AM was found that 64.72% were very good, 12% were Good, 10% were fair and 7.84% were poor and 5.4% were very poor.

Determination of correlation of Adjusted Blood Requirement Index with outcome in patients presenting with acute variceal bleeding

AIM:To determine the correlation of Adjusted Blood Requirement Index(ABRI) with the 7th day outcome in patients presenting with acute variceal bleeding.METHODS:All patients presenting with acute variceal hemorrhage(AVH) were included.Patients with previous band ligation,sclerotherapy,gastrointestinal or hepatic malignancies were excluded.Patients were managed as per standard protocol for AVH with terlipressin and band ligation.ABRI scores were calculated using the formula outcome of alive or expired up to the 7th day after treatment.The correlation between ABRI and mortality was estimated and a receiver operative characteristic(ROC) curve was plotted.RESULTS:A total of 113 patients(76 male;37 female) were included.On assessment,18 were in Child's Pugh Class A,82 in Class B and 13 were in Class C.The median number of blood units transfused ± inter-quartile range was 3.0 ± 2.0.The median ± inter-quartile range for ABRI was 1.3 ± 1.1.The ROC curve of ABRI for expiry showed a signifi cantly large area of 0.848(P < 0.0001;95% CI:0.75-0.95) .A significant correlation of log transformation of ABRI with an outcome of mortality was present(P < 0.0001) .CONCLUSION:ABRI correlates strongly with mortality.

Vertical deformation analysis based on combined adjustment for GNSS and leveling data

A method is proposed to fuse the velocity data of the global navigation satellite system(GNSS) and leveling height via combined adjustment with constraints. First, stable GNSS-leveling points are uniformly selected, and the constraints of the geodetic height change velocity and normal height change velocity are given. Then, the GNSS vertical velocities and leveling height difference are used as observations of combined adjustment, and robust least-squares estimation are used to estimate the velocities of the unknown points. Finally, a vertical movement model is established with the GNSS vertical velocities and leveling vertical velocities obtained via combined adjustment. Data from the second-order leveling network and GNSS control points in Shandong Province are taken as test data, and eight calculation schemes are used for discussion. One of the schemes, the bifactor robust combined adjustment method based on variance component estimation with two kinds of vertical velocity constraints achieves the optimal results. The method applied in the scheme can be recommended for data fusion of GNSS and leveling, further improving the reliability of vertical crustal movement in Shandong Province.