ISO25000-Related Metrics for Evaluating the Quality of Complex Information Systems

Evaluating complex information systems necessitates deep contextual knowledge of technology, user needs, and quality. The quality evaluation challenges increase with the system’s complexity, especially when multiple services supported by varied technological modules, are offered. Existing standards for software quality, such as the ISO25000 series, provide a broad framework for evaluation. Broadness offers initial implementation ease albeit, it often lacks specificity to cater to individual system modules. This paper maps 48 data metrics and 175 software metrics on specific system modules while aligning them with ISO standard quality traits. Using the ISO25000 series as a foundation, especially ISO25010 and 25012, this research seeks to augment the applicability of these standards to multi-faceted systems, exemplified by five distinct software modules prevalent in modern information ecosystems.

EKELAND’S VARIATIONAL PRINCIPLE AND CARISTI’S COINCIDENCE THEOREM FOR SET-VALUED MAPPINGS IN PROBABILISTIC METRIC SPACES

By using the partial ordering method,a more general type,of Ekeland’s ariational principle and a set-valued Caristi’s coincidence theorem in probabilistic metric spaces are obtained.In addition,a direct simple proof of the equivalence between these two theorems in probabilistic metric spaces is given.

A Variational Principle in Probabilistic Metric Spaces(Ⅱ)~* 概率度量空间中的变分原理

本文研究概率度量空间中的变分原理.我们证明了概率分析中的一个序原理,应用这个序原理并引入分布值映射的下半连续性概念,把Ekeland变分原理和Caristi不动点定理推广到概率度量空间中.

Some Approximation in Cone Metric Space and Variational Iterative Method

In this paper, we give some new results of common fixed point theorems and coincidence point case for some iterative method. By using of variation iteration method and an effective modification of He’s variation iteration method discusses some integral and differential equations, we give out some new conclusion and more new examples.

基于SVMD-Informer-XGBoost的风电功率区间预测

为了提高风电功率区间预测的精度,文章提出逐次变分模态分解(SVMD)、Informer和XGBoost算法模型的结合,实现风电功率区间预测。首先,SVMD算法自适应地分解出风电功率数据的各模态分量(IMF)和残差分量。其次,通过网格搜索算法(CV)对Informer和XGBoost模型算法进行优化,并通过网格搜索算法确定Informer-XGBoost输出预测值的最优权重,构建基于SVMD-Informer-XGBoost的预测模型。最后,通过分位数回归法(Quantile regression)输出预测值和真实值的误差,得到风电功率的区间预测。实验结果表明,所提出的方法相较于传统单一模型,在区间预测的准确度和稳定性上有了显著提升。在95%置信度水平下,区间预测指标区间覆盖率(PICP)和区间平均宽度(PINAW)分别可达94.96%和0.0362。

基于STAGCN-Informer时空组合模型的风电功率预测方法

针对风电功率预测中,空间信息受时空波动性和随机性影响无法有效提取,导致预测精度不足的问题,提出一种基于变分模态分解(Variational Mode Decomposition,VMD)、融合时空注意力图卷积网络(Spatiotemporal Attention Graph Convolutional Network,STAGCN)和改进Informer的组合模型(STAGCN-Informer-DCP)。首先运用VMD对原始特征进行模态分解,提取出不同时间尺度上的特征信息。同时利用北方苍鹰算法(Northern Goshawk Optimization,NGO)优化VMD的核心参数(惩罚因子和K值)选择。其次,利用融合时空注意力的STAGCN模块动态捕捉目标风机与近邻相似风机的时空特征,并将其与原始的信号分量融合获得携带空间尺度信息的特征向量。最后使用改进的Informer模型提取时序上下文的长期依赖关系,并实现多步输出预测。实验结果表明,该组合模型能较好地捕捉动态时空依赖,并有效提高了中长期风电预测的准确度。

Algorithms of common solutions to quasi variational inclusion and fixed point problems

The purpose of this paper is to present an iterative scheme for finding a common element of the set of solutions to the variational inclusion problem with multivalued maximal monotone mapping and inverse-strongly monotone mappings and the set of fixed points of nonexpansive mappings in Hilbert space.Under suitable conditions, some strong convergence theorems for approximating this common elements are proved. The results presented in the paper not only improve and extend the main results in Korpelevich（Ekonomika i Matematicheskie Metody,1976,12（4）：747-756）,but also extend and replenish the corresponding results obtained by Iiduka and Takahashi（Nonlinear Anal TMA,2005,61（3）：341-350）,Takahashi and Toyoda（J Optim Theory Appl,2003, 118（2）：417-428）,Nadezhkina and Takahashi（J Optim Theory Appl,2006,128（1）：191- 201）,and Zeng and Yao（Taiwan Residents Journal of Mathematics,2006,10（5）：1293-1303）.

An analysis on spatial variation of urban human thermal comfort in Hangzhou, China

Urban human thermal comfort(UHTC) is affected for interacting of weather condition and underlying surface framework of urban area. Urban underlying surface temperature value and Normalized Difference Vegetation Index(NDVI) were calculated using image interpreting and supervised classification technique by ERDAS IMAGE software using 1991 and 1999 Landsat TM images data. Reference to the relational standard of assessing human thermal comfort and other meteorology data of Hangzhou City in summer, air temperature and relative humidity variation of different land types of underlying surface were inversed. By choosing discomfort index as an indictor, the spatial distribution characteristic and the spatial variation degree of UHTC were estimated and mapped on a middle scale, that is, in six districts of Hangzhou. The main characteristics of UHTC spatial variation from 1991 to 1999 were revealed using a GIS-based calculation model. The variation mechanism were analyzed and discussed from the viewpoint of city planning, construction and environmental protection.

基于VMD-Informer-BiLSTM模型的超短期光伏功率预测

由于光伏出力的波动性和随机性给电网的规划和运行带来了挑战,因此提高光伏功率预测的精度对提升新能源系统的稳定性具有重要意义。为此提出了一种结合模态分解、多维特征建模、Informer、双向长短期神经网络(bidirectional long short-term memory network,BiLSTM)的超短期光伏组合预测模型。首先通过变分模态分解将光伏功率序列分解成不同频率的本征模态函数(intrinsic mode function,IMF),降低光伏功率信号的非平稳性与复杂度;随后使用离散小波变换提取天气因素中的细节分量,实现不同分解算法的优势互补,并用随机森林算法为每个IMF筛选冗余特征,然后将特征矩阵送入Informer进行建模,提取不同时间步中关键时刻的信息,提高对长时间序列的预测效率;最后为进一步提高模型预测精度,分析误差序列特性,利用BiLSTM进行误差校正。采用实际光伏数据进行算例分析,结果表明所提方法提高了超短期光伏功率预测精度。

Spatial and Temporal Variation of Urban Air Quality: A GIS Approach

This study investigated the seasonal variation of ambient air quality status of Burdwan town using GIS approach. Concentration of SOR2R (sulphur dioxide), NOR2R (nitrogen dioxide) and RSPM (respiratory suspended particulate matter) were measured once a week for 24 hour in both premonsoon and postmonsoon season. The seasonal average concentration of the RSPM, SOR2R and NOR2R in premonsoon season was observed to be 188.56 ± 88.63, 5.12 ± 6.27 and 92.51 ± 64.78 mg/mP3P respectively whereas in postmonsoon it was 53.03 ± 38.27, 8.51 ± 7.11 and 162.85 ± 184.80 mg/mP3P respectively. Statistical analysis showed the significant monsoonal effect on mean difference of RSPM, SOR2R and NOR2R concentration. Postmonsoon concentration of ambient SOR2R and NOR2R were observed to be higher than premonsoon, suggesting longer residence times of these pollutants in the atmosphere due to stagnant conditions and low mixing height. Spatial distribution of pollutants throughout the town in both the season was represented by digital elevation model (DEM). On the basis of Air Quality Index (AQI) a GIS based air pollution surface models were generated in both the seasons by means of Inverse Distance Interpolation (IDINT) technique. From the output surface model it was found that in comparison to premonsoon there was a significant increase of clean and fairly clean area and decrease of moderately polluted area of the town during postmonsoon.

Online RGB-D person re-identification based on metric model update

Person re-identification （re-id） on robot platform is an important application for human-robot- interaction （HRI）, which aims at making the robot recognize the around persons in varying scenes. Although many effective methods have been proposed for surveillance re-id in recent years, re-id on robot platform is still a novel unsolved problem. Most existing methods adapt the supervised metric learning offline to improve the accuracy. However, these methods can not adapt to unknown scenes. To solve this problem, an online re-id framework is proposed. Considering that robotics can afford to use high-resolution RGB-D sensors and clear human face may be captured, face information is used to update the metric model. Firstly, the metric model is pre-trained offline using labeled data. Then during the online stage, we use face information to mine incorrect body matching pairs which are collected to update the metric model online. In addition, to make full use of both appearance and skeleton information provided by RGB-D sensors, a novel feature funnel model （FFM） is proposed. Comparison studies show our approach is more effective and adaptable to varying environments.

Metric of States

Metric of quantum states plays an important role in quantum information theory. In this letter, we find the deep connection between quantum logic theory and quantum information theory. Using the method of quantum logic, we can get a famous inequality in quantum information theory, and we answer a question raised by S. Gudder.

On Generalized Multivalued Random Variational-Like Inclusions

In this paper, we posed a random iterative algorithm for generalized multivalued random variational like inclusions. We define the random relaxed Lipschitz and relaxed monotone mappings and prove the existence and convergence of solutions of the random iterative sequences generated by a random iterative algorithm.

Single Nucleotide Polymorphisms: A Window into the Informatics of the Living Genome

Nested in the environment of the nucleus of the cell, the 23 sets of chromosomes that comprise the human genome function as one integrated whole system, orchestrating the expression of thousands of genes underlying the biological characteristics of the cell, individual and the species. The extraction of meaningful information from this complex data set depends crucially upon the lens through which the data are examined. We present a biophysical perspective on genomic information encoded in single nucleotide polymorphisms (SNPs), and introduce metrics for modeling information encoded in the genome. Information, like energy, is considered to be a conserved physical property of the universe. The information structured in SNPs describes the adaptation of a human population to a given environment. The maintained order measured by the information content is associated with entropies, energies, and other state variables for a dynamic system in homeostasis. “Genodynamics” characterizes the state variables for genomic populations that are stable under stochastic environmental stresses. The determination of allelic energies allows the parameterization of specific environmental influences upon individual alleles across populations. The environment drives population-based genome variation. From this vantage point, the genome is modeled as a complex, dynamic information system defined by patterns of SNP alleles and SNP haplotypes.

Genetic Variation of Inbred Lines of Maize Detected by SSR Markers

Simple sequence repeats (SSRs) were used to detect genetic variation among 21 maize(Zea mays L. ) inbred lines. Forty-three SSR primers selected from 69 primers gave stable amplification profiles, which could be clearly resolved on 3% Metaphor agarose gel, and produced 127 polymorphic amplified fragments.The average number of alleles per SSR locus was 2.95 with a range from 2 to 7. The polymorphism information content (PIC) for the SSR loci varied from 0.172 to 0.753 with an average of 0.511. Genetic similarities among the 21 lines ranged from 0.480 between the combination of Zhongzi451 vs. K12 up to 0.768 between CA156 vs. Ye478. The cluster analysis showed that 21 inbred lines could be classified into two distinct clusters with several subclusters, which corresponded to the heterotic groups determined by their pedigree information.Eight SSR primers, which had high level of polymorphism, could allow a rapid and efficient identification of 21 inbreds. Consequently, SSR markers could be used for measuring genetic variation of maize inbred lines and assigning them to heterotic groups.

A Modified Newton Method Based on the Metric Projector for Solving SOCCVI Problem

In this paper, based on the second-order sufficient condition, the Clarke's generalized Jacobian of the Karush-Kuhn-Tucker system of the second-order cone constrained variational inequality (SOCCVI) problem that is nonsingular is proved by us. A modified Newton method with Armijo line search is presented. Three illustrative examples are given to show how the modified Newton method works.

Remote Sensing and Landscape Metrics-Based Forest Physical Degradation: Two-Decades Assessment in Gishwati-Mukura Biological Corridor in Rwanda, East-Central Africa

The management of forest corridors and related ecology is one of the effective strategies to minimize the adverse effects of forest degradation. It controls the connectivity of inhabitant species and the connection of the isolated patches. This study analyzed spatial and temporal forest physical degradation based on forest cover change and forest fragmentation in the Gishwati-Mukura biological corridor from 1990-2019. Remotely sensed datasets, Geographical Information System (GIS) and FRAGSTATS software were used to analyze the spatial and temporal physical degradation and changes in forest cover. The results indicated that the Gishwati-Mukura corridor experienced massive deforestation where approximately 7617.1 ha (64.22%) of forest cover was completely cleared out, which implies an annual forest loss of 262.6 ha·year-1 (2.21%) during 1990-2019. The forest cover transitions patterns and geostatistical analysis indicated that extensive deforestation was associated with intensive agriculture. The results demonstrated that agriculture has dramatically increased from 29.46% in 1990 to 57.22% in 2019, with an annual increase of 1.97%. Since Gishwati-Mukura has changed to National Park (NP), it lacks diversified scientific studies addressing the analysis of the remote and spatial patterns to investigate its physical degradation and landscape dynamics. This research study will serve as remote forest analysis gap-filling and as the cornerstone of numerous other research that will contribute to the improvement of the connectivity assessments along the Gishwati-Mukura corridor and other related ecosystems.

EXISTENCE AND ITERATIVE ALGORITHMS OF SOLUTIONS FOR GENERALIZED MIXED QUASI_VARIATIONAL INEQUALITIES

In this paper, by using the auxiliary technique of variational inequalities, the existence and iterative algorithm; of solutions for a class of generalized mixed quasi-variational inequalities are studied. Our results answer the open problems mentioned by Noor, improve and generalize some recent known results.

特征与度量联合优化信息几何检测器

目前,信息几何检测器主要采用协方差矩阵特征模型,在矩阵流形上度量待检测单元数据与杂波数据间的差异,以区分目标与杂波,从而实现雷达目标检测.然而,在复杂杂波背景下,雷达回波信号信杂比低,杂波在其中占据主导地位.因此,含有目标回波的雷达回波信号与纯杂波具有统计相似性,该相似性使得二者在矩阵流形上较难区分,从而限制了信息几何检测器的性能优势.为突破特征表示所造成的性能增益限制,本文提出了基于特征与度量联合优化的信息几何检测器.首先设计了特征与度量可调的信息几何检测器灵活框架,并在此基础上基于纽曼-皮尔逊准则建立了特征与度量的联合优化模型,而后利用局部平坦假设与多层感知器,将联合优化模型中的决策变量参数化,并提出了双阶段优化求解方法.基于仿真数据与实测海杂波数据的实验结果表明,该方法检测性能优于现有信息几何检测器等典型目标检测方法,且在目标多普勒接近杂波谱峰时具有较大优势.