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.

From Rejection to Embracement:The Catholic Perception of Spiritism in Brazil

The history of the relationship between Spiritism and Catholicism in Brazil can be traced through pivotal moments in the trajectory of the First Republic and the religious field since the 19th century,reflecting Brazil’s evolution into a modern,urban,and industrial society.Introduced to Brazil in the 1880s,Spiritism initially faced severe opposition from the Catholic Church,being dismissed as superstition and demon worship due to its engagement with death and spirits.Unlike Christianity,Spiritism denies the divinity of Jesus,the resurrection,and the sanctity of Church sacraments,viewing demons and angels merely as disembodied souls at different spiritual stages.Early perceptions were further complicated by the mixing of Spiritism with African and indigenous rites,which led critics to associate it with madness and mental health threats.However,the relationship between Catholicism and Spiritism in Brazil has evolved positively,particularly following the popularization of Spiritism by figures like Chico Xavier.Modern Brazilian society,characterized by increased education and religious syncretism,has grown more tolerant of diverse practices and beliefs,diminishing historical prejudices against Spiritists.This qualitative study,drawing on scholarly research and first-hand interviews,reveals that Spiritism's acceptance among Brazilian Catholics is due to its convergence with contemporary social values and the evolving profile of the average Catholic.Despite possessing a religion-like character,Spiritism is seen less as a distinct religion and more as a complementary set of practices and beliefs that enhance Catholic faith.This phenomenon mirrors the integration of Agama Hindu practices,reinforcing rather than undermining traditional religious identities.

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.

Analysis of the Spirit of Struggle in the New Era Based on General Secretary Xi Jinping’s New Year’s Greetings in the Past Decade

In order to realize the national rejuvenation,General Secretary Xi Jinping attaches great importance to the spiritual strength of struggle,and has repeatedly advocated that all people should exalt the spirit of strive on different occasions.According to his New Year’s greetings since 2014,Xi Jinping has illustrated the connotation of the spirit of enterprising,the necessity of carrying forward and the requirements for practicing the spirit of struggle from different perspectives,pointing out that all Chinese must keep in mind both domestic and international situations,strive in unity,work creative and industrious with the enthusiasm of seizing every minute,catch the opportunity and solve the problem,make substantial progress on the new journey to construct China into a great modern socialist country in all respects.

Detecting and Adjusting Temporal Inhomogeneity in Chinese Mean Surface Air Temperature Data

Adopting the Easterling-Peterson (EP) techniques and considering the reality of Chinese meteorological observations, this paper designed several tests and tested for inhomogeneities in all Chinese historical surface air temperature series from 1951 to 2001. The result shows that the time series have been widely impacted by inhomogeneities resulting from the relocation of stations and changes in local environment such as urbanization or some other factors. Among these factors, station relocations caused the largest magnitude of abrupt changes in the time series, and other factors also resulted in inhomogeneities to some extent. According to the amplitude of change of the difference series and the monthly distribution features of surface air temperatures, discontinuities identified by applying both the E-P technique and supported by China's station history records, or by comparison with other approaches, have been adjusted. Based on the above processing, the most significant temporal inhomogeneities were eliminated, and China's most homogeneous surface air temperature series has thus been created. Results show that the inhomogeneity testing captured well the most important change of the stations, and the adjusted dataset is more reliable than ever. This suggests that the adjusted temperature dataset has great value of decreasing the uncertaities in the study of observed climate change in China.

Simulating,adjusting and testing regional sustainable development──a case study of Jiangxi Province

Based on impact of human activities on regional information system, this paper focuses on sedating, adjusting and testing methodology adopted for the regional sustainable development. The case study of Jiangxi Province aims to show how to simulate, adjust and test regional sustainable development in all provinces.

Time-adjusting Acupuncture to Treat Neurosism

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Switching mechanism and optimisation research on a pressure-attitude adaptive adjusting coal seam water jet slotter

To investigate the attitude-switching mechanisms of existing jet slotters,which integrate drilling,punching and slotting operations,and to improve its fracture ability,we used the power bond diagram theory to analyse the dynamic flow pressure,and force of slotters.A mathematical model was developed for the dynamic characteristics of slotter systems.Furthermore,to study the effect of the main characteristic parameters on the ability of the nozzle to erode sandstone,multi-orthogonal experiments were carried out.And the optimised slots were applied in later practical operations.The research results show that the inlet fluid passed through the time-varying orifice to generate pressure differential thrust,which overcame the spring force,pushed the valve core to open the side nozzle,and closed the rear cavity channel thereby realising the switch of the slotter attitude.An optimal plan was established to balance the diameter,depth,and volume of punching,and a rock-breaking plan was developed for the slotter.Subsequently,the optimised water jet slotter was practically used in coal seam gas drainage.Compared with conventional dense drilling,water jet slotting technology significantly improves the ability,efficiency,and effect of increasing the permeability of the coal seam.

Selective Area Growth and Characterization of GaN Nanorods Fabricated by Adjusting the Hydrogen Flow Rate and Growth Temperature with Metal Organic Chemical Vapor Deposition

CaN nanorods are successfully fabricated by adjusting the flow rate ratio of hydrogen （H2）/nitrogen （N2） and growth temperature of the selective area growth （SAG） method with metal organic chemical vapor deposition （MOCVD）. The SAG template is obtained by nanospherical-lens photolithography. It is found that increasing the flow rate of 1-12 will change the CaN crystal shape from pyramid to vertical rod, while increasing the growth temperature will reduce the diameters of GaN rods to nanometer scale. Finally the CaN nanorods with smooth lateral surface and relatively good quality are obtained under the condition that the H2：N2 ratio is 1：1 and the growth temperature is 1030℃. The good crystal quality and orientation of GaN nanorods are confirmed by high resolution transmission electron microscopy. The cathodoluminescence spectrum suggests that the crystal and optical quality is also improved with increasing the temperature.

Benign Adjusting Effects of Long Tunnel on Environment and Slope Hazards:taking Erlang Mountain Tunnel as an example

The 21st century shall be a century of accelerated development of tunnel construction in China. But until now, what have been frequently stated in reports about influence of tunnels on environment are basically negative. In fact, this is not true. Tunnels, especially those extend across sensitive areas do exert some positive functions on improving environment and preventing local slope hazards. These positive effects, being new phenomena, are found and put forward by the authors after a series of careful observations have been carried out and in-depth analysis performed the first time. Meanwhile, it is a positive evaluation that the authors made upon tunnels. Many important phenomena and data are cited as evidence and their causative factors are analyzed in this paper as well.

CONTROLLING HYPERCHAOS IN PLANAR SYSTEMS BY ADJUSTING PARAMETERS

For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration of the map. The explicit expressions for the parameter adjustments are derived, and strict proof of convergence for method is given.

Incremental Training for SVM-Based Classification with Keyword Adjusting

This paper analyzed the theory of incremental learning of SVM (support vector machine) and pointed out it is a shortage that the support vector optimization is only considered in present research of SVM incremental learning. According to the significance of keyword in training, a new incremental training method considering keyword adjusting was proposed, which eliminates the difference between incremental learning and batch learning through the keyword adjusting. The experimental results show that the improved method outperforms the method without the keyword adjusting and achieve the same precision as the batch method. Key words SVM (support vector machine) - incremental training - classification - keyword adjusting CLC number TP 18 Foundation item: Supported by the National Information Industry Development Foundation of ChinaBiography: SUN Jin-wen (1972-), male, Post-Doctoral, research direction: artificial intelligence, data mining and system integration.

Control strategy for an intelligent shearer height adjusting system

An intelligent shearer height adjusting system is a key technology for mining at a man-less working face. A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting mechanism is proposed. It considers the non-linearity and time variations in the control process and uses Dynamic Fuzzy Neural Networks (D-FNN). The inverse characteristics of the system are studied. An adaptive on-line learning and error compensation mechanism guarantees sys-tem real-time performance and reliability. Parameters from a German Eickhoff SL500 shearer were used with Matlab/Simulink to simulate a height adjusting control system. Simulation shows that the trace error of a D-FNN controller is smaller than that of a PID controller. Also, the D-FNN control scheme has good generalization and tracking performance, which allow it to satisfy the needs of a shearer height adjusting system.

A METHOD OF ADJUSTING BAR-LENGTH OF STATICALLY INDETERMINATE TRUSS FOR INCREASING ITS LOAD CAPACITY

Based on the character of the internal force distribution of the statically indeterminate truss, the elements stresses were changed by adjusting the length of bars to increase load capacity of structure. The efficiency of the method is illustrated by several examples.

Simulation and Optimization of Amplitude-adjusting Performance of Crane with Virtual Prototyping Technology

In the design of crane,designers often have to study the trajectory of amplitude-adjusting of crane.The tradition- al methods,illustration and analytics both show their limits.In this paper,the simulation of process of amplitude-adjusting is presented and the optimization is also performed with virtual prototyping technology.From the comparison of original solution and optimal solution,the effectiveness of this technique is testified.On the platform ADAMS/View,the interactive optimization can be performed in a visual,intuitive and credible way,which deserves to be introduced to the design of crane.