Measure Of Distribution Research Articles

Policy Framework and Financial Corporate Compliance in Public Universities in Kenya

One of the important components of corporate governance that improves accountability and transparency in an institution's financial management is financial corporate compliance. The emergence of alarming cases of financial impropriety in Kenya's public universities has intensified the demand for financial accountability in the public sector and exposed the boards and management to increasing scrutiny. Public organizations have reported cases of inadequate or absence of financial compliance, and public universities have also cited comparable circumstances in audit reports. It is unclear, however, what the causes of this compliance are or what function corporate governance plays in it. The purpose of this study was to explore the effect of policy framework on financial corporate compliance at Kenya's public universities. The study adopted a descriptive survey research design. The study's target population was 40 accredited public universities in Kenya. The data were gathered through the use of extensive, quasi-structured questionnaires. The study used descriptive statistics such as frequency distribution tables, percentages, and measures of central tendency such as the mean. Chi-square and correlation analysis were used to establish the relationship between the study variables. The study reached a finding that policy framework has a positive impact on prudential corporate compliance during the period of study. The study found that most universities have adopted ethics and a code of conduct that the universities operate under a specific code of conduct and ethics which enables the university to actualize financial corporate compliance. The study recommends all public universities to be keeping track of all activities required to be adhered to by the public institution finance department more regularly to ensure the smooth running of the institutions. It is also recommended the university management facilitate regular training for the officers in the finance department to equip them with the relevant information of the newly amended policies by the government to govern the finances used to run public universities.

Regulatory Framework and Financial Corporate Compliance in Public Universities in Kenya

One of the important components of corporate governance that improves accountability and transparency in an institution's financial management is financial corporate compliance. The emergence of alarming cases of financial impropriety in Kenya's public universities has intensified the demand for financial accountability in the public sector and exposed the boards and management to increasing scrutiny. Public organizations have reported cases of inadequate or absence of financial compliance, and public universities have also cited comparable circumstances in audit reports. It is unclear, however, what the causes of this compliance are or what function corporate governance plays in it. The purpose of this study was to determine the effect of regulatory framework on financial corporate compliance at Kenya's public universities. The study adopted a descriptive survey research design. The study's target population was 40 accredited public universities in Kenya. The data were gathered through the use of extensive, quasi-structured questionnaires. The study used descriptive statistics such as frequency distribution tables, percentages, and measures of central tendency such as the mean. Chi-square and correlation analysis were used to establish the relationship between the study variables. The study findings indicated that regulatory framework affects positively financial corporate compliance during the period of study and its effects are significant. The study also found that the universities are regulated by accredited regulatory bodies as stipulated by the constitution. This study recommends that the government should employ thorough accountability measures and policies that will make every officer in public universities be held responsible for every activity he/she has undertaken on behalf of the university that may lead the university to incur some expenditures.

Institutional Framework and Financial Corporate Compliance in Public Universities in Kenya

One of the important components of corporate governance that improves accountability and transparency in an institution's financial management is financial corporate compliance. The emergence of alarming cases of financial impropriety in Kenya's public universities has intensified the demand for financial accountability in the public sector and exposed the boards and management to increasing scrutiny. Public organizations have reported cases of inadequate or absence of financial compliance, and public universities have also cited comparable circumstances in audit reports. It is unclear, however, what the causes of this compliance are or what function corporate governance plays in it. The purpose of this study was to determine the effect of the institutional framework on financial corporate compliance at Kenya's public universities. The study adopted a descriptive survey research design. The study's target population was 40 accredited public universities in Kenya. The data were gathered through the use of extensive, quasi-structured questionnaires. The study used descriptive statistics such as frequency distribution tables, percentages, and measures of central tendency such as the mean. Chi-square and correlation analysis were used to establish the relationship between the study variables. The results of the study showed that institutional framework has a positive impact on financial corporation compliance. This illustrated that institutional framework had a compelling impact on financial corporate compliance. This study recommends that the government should employ thorough accountability measures and policies that will make every officer in public universities be held responsible for every activity he/she has undertaken on behalf of the university that may lead the university to incur some expenditures.

Legal Framework and Financial Corporate Compliance in Public Universities in Kenya

One of the important components of corporate governance that improves accountability and transparency in an institution's financial management is financial corporate compliance. The emergence of alarming cases of financial impropriety in Kenya's public universities has intensified the demand for financial accountability in the public sector and exposed the boards and management to increasing scrutiny. Public organizations have reported cases of inadequate or absent financial compliance, and public universities have also cited comparable circumstances in audit reports. It is unclear, however, what the causes of this compliance are or what function corporate governance plays in it. The purpose of this study was to investigate the effect of the legal framework on financial corporate compliance at Kenya's public universities. The study adopted a descriptive survey research design. The study's target population was 40 accredited public universities in Kenya. The data were gathered through the use of extensive, quasi-structured questionnaires. The study used descriptive statistics such as frequency distribution tables, percentages, and measures of central tendency such as the mean. Chi-square and correlation analysis were used to establish the relationship between the study variables. The study discovered that the legal framework had a considerable impact on financial corporation compliance during the study period and had a favorable impact on it. These results show that Kenya's public universities are accredited by the commission on higher education and operate by its rules, which increases financial corporate compliance. The study recommends all public universities to be keeping track of all activities required to be adhered to by the public institution finance department more regularly to ensure the smooth running of the institutions. It is also recommended the university management facilitate regular training for the officers in the finance department to equip them with the relevant information of the newly amended policies by the government to govern the finances used to run public universities.

Social perceptions of the value of green spaces: A view from the South

Despite the expanding scientific understanding that green spaces are substantially beneficial to urban communities and their host cities, along with the evidence that some global cities are making progress to include nature as part of mainstream planning, this article argues that social perceptions also play a critical part in the successful planning and realization of urban green space provision in practice, especially in the Global South. This research thus reflected on the pedagogical effect on the social perception of the presence of green spaces in an urban area. To understand the impact of social perceptions on the valuation of green spaces, this article investigated the views of a convenience sample of professionals working in the Built Environment in South Africa and employed frequency distribution, two-way frequencies, and statistical measures to draw conclusions pertaining to the perception of green space value. The research illustrated that social perceptions inform how urban risks are perceived and that these perceptions of green space are often limited due to a lack of knowledge and awareness. The research exemplified that the actual community benefit provided by green spaces should be better articulated to gain traction in practice and that the appreciation and use of these urban green spaces should also be understood from a context-based and personal valuation perspective, to position these spaces as the critical resource and public good. This research concluded that social perceptions should be comprehensively understood, especially in the quest of realizing green(er) spaces and cities in the Global South.

Using dynamic data reconciliation to improve the performance of PID feedback control systems with Gaussian/non-Gaussian distributed disturbance and measurement noise

For a stochastic PID feedback control system, the uncertainty of the working environment often leads to the unsatisfied performance of the system, which does not meet the profit requirements. The working environment generally includes external disturbance and measurement noise, etc. Gaussian distributed measurement noise and disturbances are widely considered while non-Gaussian distributed measurement noise and disturbances are rarely considered. In this paper, the performance degradation of Gaussian/non-Gaussian disturbances and measurement noise on a stochastic PID feedback system is considered and analyzed. An efficient method, dynamic data reconciliation (DDR) is developed to filter measurement noise and disturbances and improve the performance of the stochastic PID feedback control system. By utilizing model-based and measured information, DDR avoids time delays in output estimation. With the detailed theoretical analysis and simulation verification, the effectiveness of the proposed DDR technology on the stochastic PID feedback control system is verified. Compared with conventional exponential filters, DDR can achieve better control performance. The proposed DDR is also used for the control system of the DC–AC​ converter. The improved effect of DDR on the output quality is demonstrated by the results.

High-speed high-resolution optical correlation-domain reflectometry without using electrical spectrum analyzer

We propose a newly configured optical correlation-domain reflectometry (OCDR) without the use of an electrical spectrum analyzer (ESA) for high-speed distributed reflectivity measurement with an enhanced spatial resolution. First, the operation of ESA-free OCDR is analyzed by numerical simulation, the results of which show the potential of the configuration to perform distributed reflectivity measurement with an improved spatial resolution. Subsequently, the simulation results are verified by comparison experiments, where distributed reflectivity measurements along a 32-m-long single-mode fiber joint with multiple connectors are performed using both conventional (with averaging) and ESA-free OCDR configurations (without averaging) at a repetition rate of 100 Hz. The widths of the reflectivity peaks experimentally obtained by the conventional and ESA-free OCDR configurations are 22.9 cm and 7.0 cm, respectively. Finally, we experimentally evaluated the performance of the ESA-free OCDR at higher repetition rates, achieving 6.3-cm spatial resolution at a repetition rate of 1 kHz. This result indicates that the ESA-free OCDR can perform a distributed reflectivity measurement with an improved spatial resolution at a higher operation speed than ever.

Impact of Digital Platform Organization on Reducing Green Production Risk to Tackle COVID-19: Evidence from Farmers in Jiangsu China

The agricultural organization based on digital platforms in C2F (Company–Platform–Farmers) may be an effective way to reduce the increased risk of green production caused by the COVID-19 pandemic, but the specific mechanism and impact involved are unclear. Applying risk cognition and decision theory, we built the theoretical framework on platform organization, pandemic risk, perception value, and green production continuity, and ascertained the impact effects and path using the PLS-SEM method. We found that the risk of COVID-19 overflow had a significant impact on farmers’ green production continuity by mediating perception value, especially regarding reduced green technology adoption intention and increased cost of living. Utilizing perfect platform value cognition, participation co-operation, access and benefit distribution, and safeguard and restraint measures of platform organization in C2F, we offered a new approach to reduce the green production risks caused by COVID-19, such as material and labor shortages, financial pressure, sales channel blockages, and price volatility. We explained the behavior-moderating motivation of farmers with different risk preferences and subjective norms in relation to tackling COVID-19. We should aim to perfect the functions of digital platform organizations to optimize the benefit linkages in C2F, accelerate farmers’ digitization ability cultivation to increase the cognitive risk level, and strengthen the policy guidance of COVID-19 prevention to reduce the influence of farmers’ subjective norms.

Some results on multivariate measures of elliptical and skew-elliptical distributions: higher-order moments, skewness and kurtosis

<abstract><p>The kurtosis and skewness of distributions are important measures that can describe the shape of a distribution, and there have been many results for symmetric distributions, but there are still many difficulties and challenges in the characterization of skew distributions. Based on the results of Mardia's and Song's kurtosis measures of elliptical distributions obtained by Zografos <sup>[<xref ref-type="bibr" rid="b1">1</xref>]</sup>, we generalize the results and study some measures for elliptical and skew-elliptical distributions. We also derive the expressions of moments of skew-elliptical distributions in terms of the ones of skew-normals and take skew-$ t $, skew-Pearson type Ⅶ and skew-Pearson type Ⅱ distributions as examples.</p></abstract>

An Ultra-Low Energy Solution for Large-Scale Distributed Audio Monitoring

This paper presents a flexible, low-cost, and ultra-low-energy acoustic sensor network solution. This enables both highly distributed and real-time audio measurements to be employed in a wide variety of scenarios. These types of distributed measurements can be useful in environmental monitoring, healthcare settings, smart cities, and security surveillance systems. However, they are typically inflexible in their applications and require specialized deployment. The proposed solution is nonintrusive and uses long-range radio to enable low-power distributed audio monitoring. The system can recognize and be configured for different types of audio measurement and analysis tasks (such as sound pressure level, annoyance, direction of arrival, and roughness), and is shown to be as accurate r=0.998 as a high-cost measurement system. Remote control, time of day, and grid capture mechanisms can also be realized. The proposed solution provides the ability for an over-the-air configuration, leading to minimal physical access required once deployed. In addition, higher data rates are possible, offering real-time monitoring metrics.

Automated Mapping of Residual Distortion Severity in Diffusion MRI.

Susceptibility-induced distortion is a common artifact in diffusion MRI (dMRI), which deforms the dMRI locally and poses significant challenges in connectivity analysis. While various methods were proposed to correct the distortion, residual distortions often persist at varying degrees across brain regions and subjects. Generating a voxel-level residual distortion severity map can thus be a valuable tool to better inform downstream connectivity analysis. To fill this current gap in dMRI analysis, we propose a supervised deep-learning network to predict a severity map of residual distortion. The training process is supervised using the structural similarity index measure (SSIM) of the fiber orientation distribution (FOD) in two opposite phase encoding (PE) directions. Only b0 images and related outputs from the distortion correction methods are needed as inputs in the testing process. The proposed method is applicable in large-scale datasets such as the UK Biobank, Adolescent Brain Cognitive Development (ABCD), and other emerging studies that only have complete dMRI data in one PE direction but acquires b0 images in both PEs. In our experiments, we trained the proposed model using the Lifespan Human Connectome Project Aging (HCP-Aging) dataset and apply the trained model to data from UK Biobank. Our results show low training, validation, and test errors, and the severity map correlates excellently with an FOD integrity measure in both HCP-Aging and UK Biobank data. The proposed method is also highly efficient and can generate the severity map in around 1 second for each subject.

Characterizing Markov Random Fields and Coefficient of Variations as Measures of Spatial Distributions for Hyperspectral Image Classification

Characterizing Markov Random Fields and Coefficient of Variations as Measures of Spatial Distributions for Hyperspectral Image Classification

On the free Lévy measure of the normal distribution

On the free Lévy measure of the normal distribution

Determinants of Life Expectancy over a Century in a Developing Country: The Case of Chile, 1900–2010

Although life expectancy is a key metric for assessing a population’s health and well-being, there is a lack of both data and studies on this phenomenon over long periods of time in developing countries. Using original datasets for 1900–2010, this paper empirically measures the effect of certain determinants of life expectancy in Chile. The data considered includes sociodemographic information, measures of income distribution, and other indicators related to economic growth and the political system. The results show that, during the twentieth century, aspects related to certain sociodemographic variables, social inequality, and economic growth had a strong impact on the evolution of life expectancy in this country.

Limit spectral measures of the matrix distributions of the metric triples

Определяется понятие предельной спектральной меры метрической тройки, т.е. пространства с мерой и метрикой ($mm$-пространства). Если метрика интегрируема по мере с квадратом, то предельная спектральная мера детерминирована и совпадает с точечным спектром вполне непрерывного интегрального оператора в $L^2(\mu)$, ядро которого есть метрика $\rho$. В работе строится пример тройки, не имеющей детерминированной предельной спектральной меры.

Comparison of Some Entropy Measures for Non-Central Fisher Probability Distribution

In this paper, many entropy measures of noncentral Fisher distribution were driven including Shannon, Renyi, Sharma, Havrda, Arimoto and Tsallis. A comparison between these entropies was made according to distribution’s shift parameter, distribution’s degrees of freedom, shape parameter and truncation parameter. The entropy that had less relative loss was said to be better than the other. There were significant differences according to all studied parameters except the shift parameter and we found that the best entropy of the mentioned entropies for noncentral Fisher distribution was Renyi entropy.

Single-photon detector-based long-distance Brillouin optical time domain reflectometry

We present a long-range Brillouin optical time domain reflectometer (BOTDR) based on photon counting technology. We demonstrate experimentally the ability to perform a distributed temperature measurement, by detecting a hot spot in a thermal bath at 100 km, and the possibility to achieve measurement until 120 km with a spatial resolution of 10 m. We use the slope of a fiber Bragg grating (FBG) as a frequency discriminator, to convert count rate variation into a frequency shift. A performance study of our distributed sensor as a function of spatial resolution is also presented.

Entropy of credibility distribution for intuitionistic fuzzy variable

<abstract> <p>This paper handles the new information entropy measure and divergence measure associated with intuitionistic fuzzy variables (IFVs). Based on credibility distribution and credibility measure of intuitionistic fuzzy variable, the credibility entropy formulas of discrete and continuous IFVs are proposed and some of their properties are investigated. The cross-entropy of intuitionistic fuzzy variable and its relationship with credibility entropy are then discussed. Finally, some numerical examples are given to illustrate the practicability of the presented credibility entropy and cross-entropy of intuitionistic fuzzy variable. Also, we make some comparative analysis on the credibility cross-entropy measure and some existing distance measures of IFVs in the pattern recognition problem.</p> </abstract>

Data-Driven Event-Triggered Bipartite Consensus for Multi-Agent Systems Preventing DoS Attacks

This paper considers event-triggered bipartite consensus issues for discrete-time nonlinear networked multi-agent systems with antagonistic interactions and denial-of-service (DoS) attacks. Firstly, a pseudo partial derivative technology is applied to obtain an equivalent dynamic linearization model of the controlled system. The signed graph theory is employed to analyze the coopetition relationships among agents. Next, a distributed combined measurement error function is formulated to transform the bipartite consensus issue into a consensus issue. Then, an output predictive compensation scheme is proposed to offset the influence of DoS attacks. Furthermore, a dead-zone operator is designed to improve the flexibility of the proposed event-triggered mechanism. Additionally, a data-driven event-triggered resilient bipartite consensus scheme is formulated. Then, the convergence of the proposed method is strictly proved by using the Lyapunov theory and the contraction mapping principle, which indicates that the bipartite consensus error could be cut to a small region around zero. Finally, hardware tasks are conducted to verify the effectiveness of the proposed method.

Embedded Distributed Temperature Sensing Enabled Multistate Joint Observation of Smart Lithium-Ion Battery

Accurate monitoring of the internal statuses is highly valuable for the management of the lithium-ion battery (LIB). This article proposes a thermal-model-based method for multistate joint observation, enabled by a novel smart battery design with an embedded and distributed temperature sensor. In particular, a novel smart battery is designed by implanting the distributed fiber optical sensor internally and externally. This promises a real-time distributed measurement of LIB internal and surface temperature with a high space resolution. Following this endeavor, a low-order joint observer is proposed to coestimate the thermal parameters, heat generation rate, state of charge, and maximum capacity. Experimental results disclose that the smart battery has space-resolved self-monitoring capability with high reproducibility. With the new sensing data, the heat generation rate, state of charge, and maximum capacity of LIB can be observed precisely in real time. The proposed method validates to outperform the commonly-used electrical-model-based method regarding the accuracy and the robustness to battery aging.