Planck Quantised General Relativity Theory Written on Different Forms

This paper is a brief review of our work on the Planck quantized version of general relativity theory. It demonstrates several straightforward methods to rewrite the same equations that we have already presented in other papers. We also explore a relatively new general relativity-inspired field equation based on the original Newtonian mass, which is very different from today’s kilogram mass. Additionally, we examine two other field equations based on collision space-time, where both energy and matter can be described simply as space and time. We are thereby fulfilling Einstein’s dream of a theory where energy and mass are not needed, or are just aspects of space and time. If this is extended beyond the 4-dimensional space-time formalism of general relativity theory to a 6-dimensional framework with 3 space dimensions and 3 time dimensions, this ultimately reveals that they are two sides of the same coin. In reality, it is a three-dimensional space-time theory, where space and time are just two sides of the same coin.

Improving Channel Estimation in a NOMA Modulation Environment Based on Ensemble Learning

This study presents a layered generalization ensemble model for next generation radio mobiles,focusing on supervised channel estimation approaches.Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout.The model,called Stacked Generalization for Channel Estimation(SGCE),aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput.The SGCE model incorporates six machine learning methods:random forest(RF),gradient boosting machine(GB),light gradient boosting machine(LGBM),support vector regression(SVR),extremely randomized tree(ERT),and extreme gradient boosting(XGB).By generating meta-data from five models(RF,GB,LGBM,SVR,and ERT),we ensure accurate channel coefficient predictions using the XGB model.To validate themodeling performance,we employ the leave-one-out cross-validation(LOOCV)approach,where each observation serves as the validation set while the remaining observations act as the training set.SGCE performances’results demonstrate higher mean andmedian accuracy compared to the separatedmodel.SGCE achieves an average accuracy of 98.4%,precision of 98.1%,and the highest F1-score of 98.5%,accurately predicting channel coefficients.Furthermore,our proposedmethod outperforms prior traditional and intelligent techniques in terms of throughput and bit error rate.SGCE’s superior performance highlights its efficacy in optimizing channel estimation.It can effectively predict channel coefficients and contribute to enhancing the overall efficiency of radio mobile systems.Through extensive experimentation and evaluation,we demonstrate that SGCE improved performance in channel estimation,surpassing previous techniques.Accordingly,SGCE’s capabilities have significant implications for optimizing channel estimation in modern communication systems.

特色鲜明General Mobile新机一览

General Mobile在CeBIT 2008前夕推出了两款手机产品,其型号分别为G777和DST11,并在展会期间再次亮相了两款新品。基本上每款产品都有自己特色。

GPP Based Open Cellular Network Towards 5G

Due to 5G's stringent and uncertainty traffic requirements,open ecosystem would be one inevitable way to develop 5G.On the other hand,GPP based mobile communication becomes appealing recently attributed to its striking advantage in flexibility and re-configurability.In this paper,both the advantages and challenges of GPP platform are detailed analyzed.Furthermore,both GPP based software and hardware architectures for open 5G are presented and the performances of real-time signal processing and power consumption are also evaluated.The evaluation results indicate that turbo and power consumption may be another challengeable problem should be further solved to meet the requirements of realistic deployments.

Toward a Common Ground for Gravity and Optics

A long enough period of observation of the Sun’s gravitational dragging effects by using a modified Cavendish’s balance output of experimental evidence shows new patterns. Those patterns can be explained assuming that the Sun has a torus with rotation, precession, and nutation. This purpose of this paper is to introduce the frequencies of all those movements. The torus’s rotational period can be used to explain the Sun’s magnetic pole reversal. Utilizing a modified Cavendish’s balance showed an output of dragging forces stronger than the attraction between the gravitational masses. This tool afforded this research a new experimental possibility to a more precise determination of the Universal Gravitational Constant Big G. Moreover, the dragging forces directly affect any volume of mass, which includes the atmosphere. This paper shows a correlation between the Sun’s dragging peaks and density of the air squared. The aforementioned correlation and the inverse cubic relation with the distance to the Sun are common for the dragging and tide forces providing the possibility that tidal forces are also a gravitational dragging consequence. The last 2017 total Solar eclipse created a new temporal reaction on the modified Cavendish’s balance. That temporal pattern looks as the spatial pattern created by an opaque disk. This similarity allows the researcher to calculate that the dragging forces are transmitted by photons with spatial periodicity of value λ = 6.1 km.

The Implications of the Sun’s Dragging Effect on Gravitational Experiments

Experimental determinations of Newton’s gravitational constant, Big G, have increased, in number and precision, during the last 30 years. There is, however, a persistent discrepancy between various authors. After examining some literature proposing that the differences in Big G might be a function of the length of the day along the years, this paper proposes an alternative hypothesis in which the periodicity of said variation is a function of the relative periodicity of the Sun-Earth distance. The hypothesis introduced here becomes a direct application of the Kerr Metric that describes a massive rotating star. The Kerr solution for the equations of the General Theory of Relativity of Albert Einstein fits well with this relative periodicity and adequately predicts the arrangement of the ex-perimental G values reported by sixteen different laboratories. Also, the author explains how the Sun disturbs gravity on the surface of the Earth.

1980—2020年安徽省土地利用时空演化特征

为分析安徽省土地利用时空演化特征,以1980年、1995年、2000年、2005年、2010年、2015年、2020年土地利用现状图为基础,利用Sankey图、土地利用动态度等方法分析了安徽省近40年土地利用演变特征;结合Getis-Ord General G聚类方法和多距离空间聚类(Ripleys K函数)方法对安徽省土地利用变化累积量进行了时空模式分析;并基于地理探测器模型分析了多种驱动因子对土地利用变化的单一与交互解释程度。结果表明:①1980—2020年安徽省建设用地、草地、水域面积分别增加35.04%、2.44%和0.75%,耕地、林地分别减少4.63%和0.98%;安徽省综合土地利用动态度逐渐增加,建设用地和耕地变化较快,单一动态度最高分别达到3.15%和-0.39%;林地、草地、水域变化较为稳定。②1980—2020年安徽省土地利用的剧烈变化具有显著的聚集性,通过K-means聚类可将不同程度的变化较好地分类;土地利用剧烈变化区域聚集特征受观测尺度变化的影响小于平缓变化区域。③地理探测结果表明:与人类活动强度密切联系的社会因子(夜间灯光数据、GDP、人口、到城市和主要道路距离等)和地形因子(高程、坡度)以及各因子间交互作用是土地利用变化的重要推动力。

Spatiotemporal Property Analysis of Birth Defects in Wuxi,China

Objective To describe the temporal trends and spatial patterns of birth defects occurring in Wuxi, a developed region of China. Methods Wavelet analysis was used to decompose the temporal trends of birth defect prevalence based on the birth defect rates over the past 16 years. Birth defect cases with detailed personal and family information were geo-coded and the relative risk in each village was calculated. General G statistic was used to test the spatial property with different scales. Results Wavelet analysis showed an increasing temporal trend of birth defects in this region. Clustering analysis revealed that changes continued in the spatial patterns with different scales. Conclusion Wuxi is confronted with severe challenges to reduce birth defect prevalence. The risk factors are stable and show no change with spatial scale but an increasing temporal trend. Interventions should be focused on villages with a higher prevalence of birth defects.

Next Decade of Telecommunications Artificial Intelligence

It has been an exciting journey since the mobile communications and artificial intelligence(AI)were conceived in 1983 and 1956.While both fields evolved independently and profoundly changed communications and computing industries,the rapid convergence of 5th generation mobile communication technology(5G)and AI is beginning to significantly transform the core communication infrastructure,network management,and vertical applications.The paper first outlined the individual roadmaps of mobile communications and AI in the early stage,with a concentration to review the era from 3rd generation mobile communication technology(3G)to 5G when AI and mobile communications started to converge.With regard to telecommunications AI,the progress of AI in the ecosystem of mobile communications was further introduced in detail,including network infrastructure,network operation and management,business operation and management,intelligent applications towards business supporting system(BSS)&operation supporting system(OSS)convergence,verticals and private networks,etc.Then the classifications of AI in telecommunication ecosystems were summarized along with its evolution paths specified by various international telecommunications standardization organizations.Towards the next decade,the prospective roadmap of telecommunications AI was forecasted.In line with 3rd generation partnership project(3GPP)and International Telecommunication Union Radiocommunication Sector(ITU-R)timeline of 5G&6th generation mobile communication technology(6G),the network intelligence following 3GPP and open radio access network(O-RAN)routes,experience and intent-based network management and operation,network AI signaling system,intelligent middle-office based BSS,intelligent customer experience management and policy control driven by BSS&OSS convergence,evolution from service level agreement(SLA)to experience level agreement(ELA),and intelligent private network for verticals were further explored.The paper is concluded with the vision that AI will reshape the future beyond 5G(B5G)/6G landscape,and we need pivot our research and development(R&D),standardizations,and ecosystem to fully take the unprecedented opportunities.

2000~2020年中国典型经济区PM_(2.5)时空变化及其与植被景观格局的关系

探究典型经济区PM_(2.5)时空变化特征及其与植被景观格局的关系,对区域PM_(2.5)污染治理和大气环境保护具有重要意义.基于PM_(2.5)数据和MODIS NDVI数据集,采用像元二分模型、 Getis-Ord G*i分析、 Theil-Sen Median趋势分析、 Mann-Kendall检验、皮尔逊相关分析和复相关分析等方法,探究中国三大经济区PM_(2.5)空间聚集性、时空变化特征及其与植被景观格局指数的相关性.结果表明,2000~2020年环渤海地区PM_(2.5)主要表现为热点区扩张,冷点区缩减;长江三角洲地区冷点区和热点区面积占比无显著变化;珠江三角洲地区冷点区和热点区均发生扩张.2000~2020年三大经济区PM_(2.5)整体表现为下降趋势,改善程度由高到低依次是:珠江三角洲地区、长江三角洲地区和环渤海地区.2000~2020年三大经济区不同植被覆盖度等级下PM_(2.5)均表现为下降趋势,三大经济区PM_(2.5)均在极低植被覆盖度区域改善最为显著.在景观尺度下,与环渤海地区、长江三角洲地区和珠江三角洲地区PM_(2.5)相关性最强的植被景观格局指数分别是聚集度指数(AI)、最大斑块指数(LPI)和香农多样性指数(SHDI).在类型尺度下,与环渤海地区、长江三角洲地区和珠江三角洲地区PM_(2.5)相关性最强的景观格局指数分别是聚集度指数(AI)、斑块形状指数(LSI)和类型斑块面积比(PLAND).植被景观格局指数对PM_(2.5)的综合影响强于单个植被景观格局指数的影响.综上所述,2000~2020年三大经济区PM_(2.5)空间聚集性均发生了改变.在研究时段内,三大经济区PM_(2.5)整体表现为下降趋势.在景观尺度和类型尺度下,三大经济区PM_(2.5)与植被景观格局指数的关系均表现出明显差异.

基于乡镇尺度的黄土高原干旱脆弱性时空演变分析——以榆中县为例

干旱脆弱性评价是干旱半干旱地区人地关系研究的重要内容,对减缓和应对干旱具有重要作用,乡镇尺度的干旱脆弱性评价为西北乡村人地系统可持续性研究提供新的视角。本文引用干旱脆弱性分析框架,从暴露度、敏感性和适应能力三个维度构建指标体系,选择甘肃榆中县作为黄土高原典型研究区域,采用2002—2015年统计数据、气象数据和遥感数据,运用熵值法、综合指数法和局部空间自相关指数法等分析方法分别对指标权重、干旱脆弱性指数与类型及其空间集聚性进行分析。研究结果表明:(1)榆中县干旱脆弱性指数呈波动式变化趋势,阶段性升降明显;(2)不同脆弱类型的乡镇数量由高到低分别为中脆弱>高脆弱>低脆弱,且高脆弱的乡镇数量增加趋势明显;(3)干旱脆弱性影响因素由高到低分别为年降水量、坡度、年平均气温、干旱影响面积、农民纯收入、人口密度和农业人口比例,年降水量为干旱脆弱性的首要决定因素;(4)干旱脆弱性热点区域总体格局呈现"南-北热中部冷"的空间格局,具有明显的地理集聚特征,且局部乡镇热点区域趋于稳定。