Hierarchical Statistical Analysis Research Articles

THE RATIONALE FOR DECISION-MAKING IN TRANSPORT POLICY BASED ON A MULTI-AGENT APPROACH: A CASE STUDY OF THE RUSSIAN TRANSPORT STRATEGY

There are two main methods commonly used for decision-making: multi-criteria analysis (MCA) and cost-benefit analysis (CBA). The significance of this research lies in the fact that currently, the rationale behind the final decision in choosing among multiple options is often based solely on the anticipated financial and economic outcomes of the project. However, the project itself encompasses other strategic implications that are disregarded during the decision-making process. These include, but are not limited to, social, environmental, cultural, and natural consequences. This paper aims to propose a more comprehensive multi-criteria approach, providing a multi-agent solution for selecting from a diverse range of alternatives that align with national interests. The objective of this research is to identify the most promising subproject within the scope of the national transport project, considering not only financial aspects but also other crucial factors such as social, cultural impacts, human capital development, the creation of a new environment, the emergence of fresh opportunities, and the dismantling of institutional obstacles. The paper discusses two main methods used for decision-making in transportation policy: MCA and CBA. A practical experiment was conducted to select and rank promising sub-projects using T. Saaty's hierarchy analysis method, which takes into account the multi-agent approach to the development of transportation systems and their integration with state development in Russia. As part of the study, a practical experiment was conducted to select and rank promising subprojects using the T. Saati method of hierarchical analysis. Criteria for evaluating and prioritizing projects were developed, as well as new tools for future use in public administration of the transport industry. Research methods and methodology included T. Saati's hierarchical analysis method, statistical analysis, specification, mathematical modeling, and statistical tests. The main results of the study were the analysis of four existing promising projects: modernization of railway infrastructure, development of high-speed rail communication, modernization of automotive infrastructure, and development of inland waterway transport. Based on these projects, an applied multi-agent toolkit was proposed for decision-making in public transport administration. The results of the study can be used to inform decision-making processes in transport policy and to evaluate the effectiveness and economic feasibility of projects. The study used methods such as multi-criteria decision analysis (MCDA) and cost-benefit analysis (CBA) to analyze various aspects of transport projects and make informed decisions about their implementation.

Residual Effect of Compost and Biochar Amendment on Soil Chemical, Biological, and Physical Properties and Durum Wheat Response

The residual effect of compost and biochar amendment on soil properties and durum wheat response was evaluated under field conditions in a Mediterranean environment. The treatments compared in a randomized complete block experimental design with three replications were: mineral fertilizer (100 kg N ha−1), compost applied at the rate of 25 Mg ha−1, biochar applied at the rates of 10 and 30 Mg ha−1, unfertilized control. Wheat was the second crop included in a sorghum–wheat cropping system and did not receive fertilizer supply. A hierarchical statistical analysis was carried out to investigate how different treatments could impact the cropping system performance. The findings highlight the significant influence of soil properties, particularly total N, WEOC, and TOC, on wheat and protein yield. One year after the amendment and fertilizer application, compost and biochar significantly increased soil total organic carbon content. The highest soil water extractable organic carbon was found with the compost application (76.9 mg kg−1), whereas the lowest value (50 mg kg−1) was with the highest rate of biochar. Soil respiration rates and hydraulic properties were not affected by the investigated treatments. This behavior is probably related to the short experimental duration and to the silty clayey soil texture. Significant correlations were observed between bulk density and water content at pressure heads in the −20 and −100 cm range; this range accounts for the effect of soil macro and mesopores. Multiple linear regression analysis revealed strong predictive power for grain (R2_adj = 0.78; p < 0.001) and protein yield (R2_adj = 0.77; p < 0.001). The highest grain yield (3.36 Mg ha−1) was observed with compost, and the lowest (2.18 Mg ha−1) with biochar at a rate of 30 Mg ha−1. These findings lay the basis for understanding how different soil amendment management may impact soil quality and wheat performance, even in consideration of climate change.

Chemostratigraphic correlation of Devonian-Carboniferous sedimentary sequences at Roboré SUB-BASIN, Bolivia

A chemostratigraphic analysis was performed on cutting samples from Devonian-Carboniferous intervals belonging to three wells located in the Roboré sub-Basin, east of Chaco Plain, southeast Bolivia.Using multivariate statistical analysis (Factor Analysis), we have established two main geochemical associations serving as control for the chemistry of the analyzed samples: detrital (clay and heavy minerals) and redox-organic matter association.In addition, different geochemical zones (chemozones or chemofacies) were established by the application of a hierarchical statistical analysis (constrained cluster analysis), both for the detrital and redox-organic matter associations. Furthermore, total correspondence of the established chemozones was observed and better definition of the predefined stratigraphic contacts was obtained after a chemostratigraphic correlation scheme was applied. Taking together our chemostratigraphic data, we have identified an interval that represents a possible marker of Lower Carboniferous glacial event in the Roboré sub-Basin. We have evaluated the general characteristics of the sources of sediment provenance along the studied sequences. In conclusion, we proposed a large active continental margin accretionary complex tectonic setting for Los Monos (Late Devonian) and Tupambi (Mississippian) formations in the Roboré sub-Basin (Chaco Plain).

Risk and protective factors for Long COVID in Brazilian adults (CUME Study).

Most people recover from COVID-19, however, between 5 to 20% have experienced new, recurring, or continuous health problems four or more weeks after being infected, a phenomenon called Long COVID, and whose reasons for its manifestation are incipient. Our objective was to analyse the risk and protective factors for Long COVID in Brazilian adults participating in the CUME Study. The CUME Study is a prospective cohort conducted with graduates from federal universities in the State of Minas Gerais, Brazil. In this study, 390 participants who answered the baseline questionnaire in 2016 and the third follow-up questionnaire in 2022 (which contained a block of questions about occurrence of COVID-19 and Long COVID) were included. The diagnosis of Long COVID was based on self-reporting of persistence of signs and symptoms of COVID-19 between 30 days and 6 months after remission of the disease. To estimate the risk and protective factors for Long COVID, a hierarchical multivariate statistical analysis was conducted using the Poisson regression technique. Long COVID was observed in 48.9% of the participants. The following characteristics were identified as risk factors for the outcome: female sex (RR = 1.56; 95% CI = 1.22-1.99); prior diagnosis of hypertension (RR = 1.46; 95% CI = 1.19-1.80); having contracted COVID-19 in the first (RR =1.38; 95% CI = 1.07-1.79) or in the second waves (RR = 1.33; 95% CI = 1.07-1.65) of the pandemic period; and having presented three or more signs and symptoms during the acute phase of COVID-19 (RR = 2.99; 95% CI = 1.08-8.24). On the other hand, having a doctoral/postdoctoral educational level (RR = 0.69; 95% CI = 0.50-0.94) was identified as a protective factor for the outcome. Health system managers and healthcare professionals should be aware of the socioeconomic profile and disease history of patients who have had COVID-19 because women, people with a prior diagnosis of hypertension, and those who manifested multiple signs and symptoms of COVID-19 during the acute phase of the disease were at greater risk of developing Long COVID.

Workforce Diversity, Organisational Culture and Performance of Some Selected Multinational Food and Beverage Companies in Lagos Metropolis

The disruptions in the global economy introduced by covid-19 pandemic have foisted on organizational management the adoption of policies and initiatives of managing their diverse work groups. Therefore, the objective of this study was to investigate the influence of Workforce Diversity Dimensions (WFDDs) of sex, age and educational attainment on organisational performance (OP) and also the mediating effect of organisational cultural values (achievement values, employee involvement and equity) on the relationship between WFDDs and OP. Descriptive survey design was employed and a sample 464 respondents were drawn using Yemane (1967) method from among 3,280 employees of four selected Multi-National Companies (MNC(s)) in the Food and Beverage sub-sector of manufacturing companies operating in Lagos Metropolis. Data collected were analysed using both simple and multiple hierarchical regression statistical analysis. Results obtained of hypothesis One revealed that work force diversity dimensions (WFDDs) insignificantly influenced organizational performance (OP) with coefficient of determination at R2 = 0.0003. When the interaction term organizational cultural values were added to the regression model (MODEL 2), there was a significant increase in organizational performance of 16.3% (Δ R2 =0.163, p = 0.000) because R2 increased from 0.003 to 0.166. This result shows that organizational cultural values have enhancing effect on the relationship between workforce diversity dimensions on organizational performance. The study concluded that there should be a shift from that assumption suggesting direct positive effect of workforce diversity on performance. Rather, the context of the organisation in terms of the cultural values it emplaces will have any of the positive or negative consequences on the organisation performance. It is also suggested that leadership role and organisational business strategies can be investigated for their mediating contribution on the relationship between WFD and OP as further studies.

Bayesian hierarchical modelling of the geospatial distribution of fasciolosis in dairy cattle and the impact on production: Application to the main milk-producing region (Galicia) in Spain

Fasciolosis caused by Fasciola hepatica is a common parasitic infection among cattle in many countries. Although infected adult cows rarely show overt clinical signs, milk production may be impaired. Thus, significant production losses may occur in dairy herds with a high prevalence of fasciolosis. In this study, Bayesian hierarchical modelling was used to estimate the geospatial distribution of dairy cattle fasciolosis and its impact on milk production. The study was conducted in Galicia, the main milk producing region in Spain and a geographically heterogeneous area. The aims were: 1) to model the geospatial distribution of fasciolosis in dairy herds in the study area, 2) to identify clusters of herds with a high prevalence of fasciolosis, and 3) to assess the effect of fasciolosis on milk yield and quality. A large number of dairy cattle farms (n = 4907), of which 1660 provided production records, were surveyed. Fasciola infection status was determined by applying the MM3-SERO ELISA test to bulk tank milk samples. A high probability of infection was predicted in several zones, particularly in the centre, northeast and southeast of Galicia. Conversely, the predicted probability was very low in some parts of the northwest of the region. Infections with high within-herd prevalence (> 25% lactating cows infected) predominated. High within-herd prevalence was associated with loss of milk production (−1.387 kg/cow/ day, on average). No association between Fasciola infection and either milk fat or protein content was observed. This study has generated the first maps of the spatial distribution of the probability of Fasciola infection in dairy cattle herds in Galicia. The maps presented here can be used for reference purposes, enabling the design of better targeted fasciolosis control programmes in the region. Use of Bayesian hierarchical statistical analysis enabled us to ascertain the uncertainty of the predictions and to account for the spatial autocorrelation in the data. It also enabled us to generate maps showing the residual spatial variation in milk production, a topic that may deserve more detailed study.

Spatial Distribution and Factors Influencing the Various Forms of Iron in Alluvial–Lacustrine Clayey Aquitard

The compression release of pore water in clayey aquitards has a significant impact on groundwater quality. Iron is an active variable element that mediates biochemical reactions in groundwater systems, but its transformation mechanisms in clayey aquitards remain unclear. The sediment and pore water samples from the shallow clayey aquitard (thickness = ~20 m) in the Chen Lake area of China were collected in three boreholes. The spatial distribution and influencing factors of Fe occurrence in the aquitard were revealed using hierarchical extraction, statistical analysis, and simulation calculations. The results indicate that the background value of alluvial–lacustrine sediments primarily affects the Fe concentration of clayey sediments. The dissimilatory reduction in free Fe oxide was the main source of Fe ions in pore water, resulting in a major percentage of Fe2+ in the total Fe concentration (0.07−5.91 mg/L). The abundant organic matter in organic-rich clay promoted a dissimilatory reduction in Fe (III) oxides, while the Fe concentrations of sediment and pore water were lower in the sand-rich stratum because of its weak adsorption capacity. The impact of human reclamation activities on the aquitard was mainly concentrated in the shallow layer (>−3 m), resulting in water drainage and O2 and CO2 input, which induced the crystallization of poorly crystalline Fe oxides. The input of reactive organic matter from reclaimed crops promoted the dissimilatory reduction in Fe oxides and the enrichment of Fe in deep pore water. The copious Fe2+ in deep stratum pore water tended to interact with CO32− and S2− to form coprecipitation with Fe (II). The concentrations of As, Cr, Sr, Zn, and Mn in pore water followed a similar variation trend to the Fe ion concentration, and their release could be attributed to the reduction dissolution of sediment Fe (III) oxides.

Origin-Destination Traffic Survey—Case Study: Data Analyse for Bacau Municipality

In order to develop a transport model for the municipality of Bacau, it was necessary to collect data on the current mobility characteristics of people and goods. Traffic data were collected by means of using an origin-destination (O-D) survey. This survey was carried out in the form of a manual traffic census arranged in stations at six points on the entrance sectors of the national roads in the city of Bacau. At the level of the municipality of Bacau, data from a sample of 3040 drivers were used for the origin-destination surveys. The respondents answered 11 questions. The article presents the results obtained from the six control points for seven questions that were considered relevant. The data obtained were initially used to identify, from a percentage and quantitative point of view, the type of traffic specific to the municipality of Bacau. The analysis of the data shows that the majority of vehicles, 78.9%, originate from Bacau County and that 87.2% of those interviewed have Bacau County as their destination. Most vehicles passing through the checkpoints were within the time intervals 7:30–8:30, i.e., 15.55%, and 16:30–17:30, i.e., 16.18%. The highest proportion of registered vehicles were from Romania, 97.99%. Additionally, 40.75% of the respondents were travelling for business purposes, and approximately the same share was found for the number of people in the vehicle; i.e., single occupant vehicles comprised 58.35% of the total vehicles surveyed. Passenger cars accounted for 67.66% of the vehicles. By using the OriginLab software, the aim was to create parallel graphs for each control point in order to identify certain correlations between the data obtained from the questionnaire. At the end of the article, a hierarchical cluster statistical analysis was carried out by using OriginLab, which identified a series of correlations between the analysed parameters.

Comparison of telemonitoring combined with intensive patient support with standard care in patients with chronic cardiovascular disease - a randomized clinical trial

ImportanceHealthcare concepts for chronic diseases based on tele-monitoring have become increasingly important during COVID-19 pandemic.ObjectiveTo study the effectiveness of a novel integrated care concept (NICC) that combines tele-monitoring with the support of a call centre in addition to guideline therapy for patients with atrial fibrillation, heart failure, or treatment-resistant hypertension.DesignA prospective, parallel-group, open-label, randomized, controlled trial.SettingBetween December 2017 and August 2019 at the Rostock University Medical Center (Germany).ParticipantsIncluding 960 patients with either atrial fibrillation, heart failure, or treatment-resistant hypertension.InterventionsPatients were randomized to either NICC (n = 478) or standard-of-care (SoC) (n = 482) in a 1:1 ratio. Patients in the NICC group received a combination of tele-monitoring and intensive follow-up and care through a call centre.Main outcomes and measuresThree primary endpoints were formulated: (1) composite of all-cause mortality, stroke, and myocardial infarction; (2) number of inpatient days; (3) the first plus cardiac decompensation, all measured at 12-months follow-up. Superiority was evaluated using a hierarchical multiple testing strategy for the 3 primary endpoints, where the first step is to test the second primary endpoint (hospitalization) at two-sided 5%-significance level. In case of a non-significant difference between the groups for the rate of hospitalization, the superiority of NICC over SoC is not shown.ResultsThe first primary endpoint occurred in 1.5% of NICC and 5.2% of SoC patients (OR: 3.3 [95%CI 1.4–8.3], p = 0.009). The number of inpatient treatment days did not differ significantly between both groups (p = 0.122). The third primary endpoint occurred in 3.6% of NICC and 8.1% of SoC patients (OR: 2.2 [95%CI 1.2–4.2], p = 0.016). Four patients died of all-cause death in the NICC and 23 in the SoC groups (OR: 4.4 [95%CI 1.6–12.6], p = 0.006). Based on the prespecified hierarchical statistical analysis protocol for multiple testing, the trial did not meet its primary outcome measure.Conclusions and relevanceAmong patients with atrial fibrillation, heart failure, or treatment-resistant hypertension, the NICC approach was not superior over SoC, despite a significant reduction in all-cause mortality, stroke, myocardial infarction and cardiac decompensation.Trial registration ClinicalTrials.gov Identifier: NCT03317951.

ProAKAP4 Concentration Is Related to Sperm Motility and Motile Sperm Subpopulations in Frozen-Thawed Horse Semen.

ProAKAP4 is the precursor of AKAP4 (A-kinase Anchor protein 4), the main structural protein of the fibrous sheath of sperm. The amount of proAKAP4 reflects the ability of spermatozoa to maintain the flagellum activity and functionality up to the site of fertilization and is positively correlated with progressive motility in several mammalian species. The aim of this study was to investigate the relationship between proAKAP4 concentration with horse sperm motility descriptors and spermatic motile subpopulations. For this purpose, a total of 48 ejaculates from 13 different stallions were analyzed. Spermatic motility descriptors were obtained by the CASA system, and four motile subpopulations (SP) with specific motility patterns were statistically identified. ProAKAP4 concentrations were evaluated by ELISA. The relationship between motility descriptors of sperm subpopulations and proAKAP4 concentrations was evaluated. Following a hierarchical cluster statistical analysis, ejaculates were divided into two groups according to their proAKAP4 concentrations, either having low proAKAP4 concentrations (5.06−35.61 ng/10M spz; n = 23) or high (39.92−82.23 ng/10M spz; n = 25) proAKAP4 concentrations (p < 0.001). ProAKAP4 concentrations were positively correlated (p < 0.05) with total and progressive motility, as well as with parameters of velocity. ProAKAP4 amount also showed a negative correlation (p < 0.05) with sperm motile subpopulation number 3, which was the subpopulation with the lowest velocity parameters. In conclusion, proAKAP4 concentration in stallion semen positively reflects sperm progressive motility with the functional velocity kinematic descriptors. Concentrations of proAKAP4 higher than 37.77 ng/10M spz were correlated with a very good quality frozen/thawed stallion semen.

Comparative safety assessment of LNG re-liquefaction systems applied on LNG carriers

ABSTRACT This research was aimed to evaluate the safety of the LNG cargo compressor room against unwanted gas leakage from two different re-liquefaction systems applicable for an LNG carrier: 1) the Partial (Full) Re-liquefaction System (P(F)RS) and 2) the combination of Partial Re-liquefaction System and Mixed Refrigerant Re-liquefaction system (PRS+MRS). To achieve this goal, quantitative risk assessment was carried out with the integration of system hierarchical modelling, statistical analysis, and CFD simulation. The frequency of initial leakages, occurring to each component of the re-liquefaction systems, was analysed, whereas for the consequence analysis, a CFD program of PyroSim was employed to simulate the gas dispersion in the confined room fitted with mechanical ventilation systems. In addition, various ventilation capacities were investigated with changes in their allocations in the room in order to determine these parametric influences on the results. The risk level of re-liquefaction systems was determined in a quantitative way. Research results clearly presented the importance of the proper arrangement of the ventilation systems. The risk levels were estimated at 5.6 E-3/year for P(F)RS whereas about 9.6 E-3/year for the PRS+MRS in consideration of current regulations. However, the increase in the ventilation capacity was found to reduce the risk levels. The research findings are highly believed to offer meaningful guidance into future safety regulatory frameworks.

The Association Between Diabetic Retinopathy and the Prevalence of Age-Related Macular Degeneration-The Kailuan Eye Study.

This study aimed to investigate the prevalence of age-related macular degeneration (AMD) in patients with diabetes mellitus (DM) and diabetic retinopathy (DR) and analyze whether DR is a risk factor for AMD. This population-based epidemiological study included 14,440 people from the Kailuan Eye Study in 2016, of whom 1,618 were patients with type 2 DM aged over 50 years, and 409 had DM with DR. We analyzed whether there were differences in the prevalence of AMD between DM with DR and DM without DR, and conducted a hierarchical statistical analysis according to different stages of DR. Using variable regression analysis, we explored whether DR constituted a risk factor for AMD. In the DM population, the prevalence of wet AMD in patients with DM with and without DR was 0. 3 and 0.2%, respectively, with no significant difference (P = 0.607). Meanwhile, the prevalence of dry AMD in patients with DM with and without DR was 20.8 and 16.0%, respectively, with a significant difference. In the subgroup analysis of dry AMD, the prevalence of early, middle, and late dry AMD in DM with DR was 14.4, 5.9, and 0.5%, respectively. In DM without DR, the prevalence of early, middle, and late dry AMD was 10.5, 4.8, and 0.7%, respectively (P = 0.031). In the subgroup analysis of DR staging, statistical analysis could not be performed because of the limited number of patients with PDR. In the variable regression analysis of risk factors for dry AMD, after adjusting for age, sex, body mass index, hypertension, and dyslipidemia, DR constituted the risk factor for dry AMD. In conclusion, DM did not constitute a risk factor for AMD, and the prevalence of wet AMD and dry AMD in patients with DM and DR was higher than that in patients with DM without DR (among which dry AMD was statistically significant). Multivariate regression analysis confirmed that DR is an independent risk factor for dry AMD. Reasonable control of DM and slowing down the occurrence and development of DR may effectively reduce the prevalence of AMD in patients with DM.

WORKFORCE DIVERSITY, HUMAN RESOURCE MANAGEMENT PRACTICES AND ORGANISATIONAL PERFORMANCE

The inevitability of workforce diversity and the legal requirement of employment opportunities and affirmative action have driven the adoption of diversity policies and initiatives by management of many organisations. The objective of this study is to examine the influence of workforce diversity on organisational performance and the moderating effects of human resource management practices (HRMPs) as moderating factor in the relationship between workforce diversity and organisational performance. Descriptive survey design was employed and a sample of 464 respondents were drawn, using Yemane (1967) method, from among 3,280 total employees of four selected Multinational Companies (MNCs) in the Foods and Beverage sub sector of manufacturing companies operating in Lagos State Nigeria. Data were generated through structured questionnaire schedule from the management, senior, middle and junior staff cadres of the selected MNCs. The data collected were analysed using both simple and multiple hierarchical regression statistical analysis. Result obtained of hypothesis One indicated that workforce diversity dimensions (WFDDs) insignificantly influenced organisational performance (OP) with coefficient of determination at R2 = 0.0003. When the components of HRMPs were added to the regression model, there was a significant increase in OP 19.2% (Δ R2 =0.192, p = 0.000) since R2 increased from 0.003 to 0.195. This result shows that HRMPs have enhancing effect on the relationship between WFDDs and OP. the study concluded that Organisations may not likely reap the benefits of increasing WFDDs except they effectively manage their internal process, specifically their HRMPs. It was therefore recommended among other things that approach to research of WFD should be holistic investigation of the contextual factors of organisation for their climate which could be discriminatory or non-discriminatory and the corresponding OP which could be negative or positive accordingly.

Analysis of fatigue test data of retrieved mooring chain links subject to pitting corrosion

Fatigue is one of the main failure mechanisms of catenary type mooring lines. Fatigue resistance is affected by a large number of factors. In this paper, the effect of pitting corrosion on the fatigue resistance of mooring lines is empirically estimated. Data from fatigue testing of both new and used chain links are considered. The used chain link samples were retrieved from several offshore floating units. A hierarchical statistical analysis is proposed to effectively use the available information. Mean stress effect is taken into account in the analysis of the data. Results show that the effect of pitting corrosion on the structural reliability of mooring lines is significant.

An Analysis of Glucose Effectiveness in Subjects With or Without Type 2 Diabetes via Hierarchical Modeling.

Glucose effectiveness, defined as the ability of glucose itself to increase glucose utilization and inhibit hepatic glucose production, is an important mechanism maintaining normoglycemia. We conducted a minimal modeling analysis of glucose effectiveness at zero insulin (GEZI) using intravenous glucose tolerance test data from subjects with type 2 diabetes (T2D, n=154) and non-diabetic (ND) subjects (n=343). A hierarchical statistical analysis was performed, which provided a formal mechanism for pooling the data from all study subjects, to yield a single composite population model that quantifies the role of subject specific characteristics such as weight, height, age, sex, and glucose tolerance. Based on the resulting composite population model, GEZI was reduced from 0.021 min–1 (standard error – 0.00078 min–1) in the ND population to 0.011 min–1 (standard error – 0.00045 min–1) in T2D. The resulting model was also employed to calculate the proportion of the non–insulin-dependent net glucose uptake in each subject receiving an intravenous glucose load. Based on individual parameter estimates, the fraction of total glucose disposal independent of insulin was 72.8% ± 12.0% in the 238 ND subjects over the course of the experiment, indicating the major contribution to the whole-body glucose clearance under non-diabetic conditions. This fraction was significantly reduced to 48.8% ± 16.9% in the 30 T2D subjects, although still accounting for approximately half of the total in the T2D population based on our modeling analysis. Given the potential application of glucose effectiveness as a predictor of glucose intolerance and as a potential therapeutic target for treating diabetes, more investigations of glucose effectiveness in other disease conditions can be conducted using the hierarchical modeling framework reported herein.

Research on human performance evaluation model based on neural network and data mining algorithm

In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with the adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. A wireless sensor network is a wireless network composed of a large number of stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes, and transmits the information of the perceived objects in the geographical area covered by the network and finally puts these The information is sent to the owner of the network. This algorithm improves the accuracy of personnel performance evaluation, simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers’ performance evaluation, higher efficiency of big data processing, and better integration.

Relationship Between Soil Properties and Banana Productivity in the Two Main Cultivation Areas in Venezuela

To identify the main edaphic variables most correlated to banana productivity in Venezuela and explore the development of an empirical correlation model to predict this productivity based on soil characteristics. Six agricultural fields located in two of the main banana production areas of Venezuela were selected. The experimental sites were in large farms (≥ 50 ha) with four productivity levels in “Gran Nain” bananas, with an area of 4 ha for each of four productive levels: High - High, High - Low, Low - High, and Low - Low. Sixty sampling points were used to characterize the soils under study. Additionally, a Productivity Index (PI) based on three different biometric data on plant productivity was proposed. Through hierarchical statistical analysis, the first 16 soil variables that best explained the PI were selected. Thus, five multiple linear regression models were estimated, using the stepwise regression method. Subsequently, a performance analysis was used to compare the prediction quality range and the error associated with the number of soil variables selected for the proposed models. The selected model included the following soil variables: Mg, penetration resistance, total microbial respiration, bulk density, and omnivorous free-living nematodes. These variables explain the PI with an R2 of 0.55, the mean absolute error (MAE) of 0.8, and the root of the mean squared error (RMSE) of 1.0. The five selected variables are proposed to characterize the soil Productivity Index in banana and could be used in a site-specific soil management program for the banana areas of Venezuela.

Eye tracking in an everyday environment reveals the interpersonal distance that affords infant-parent gaze communication

The unique morphology of human eyes enables gaze communication at various ranges of interpersonal distance. Although gaze communication contributes to infants’ social development, little is known about how infant-parent distance affects infants’ visual experience in daily gaze communication. The present study conducted longitudinal observations of infant-parent face-to-face interactions in the home environment as 5 infants aged from 10 to 15.5 months. Using head-mounted eye trackers worn by parents, we evaluated infants’ daily visual experience of 3138 eye contact scenes recorded from the infants’ second-person perspective. The results of a hierarchical Bayesian statistical analysis suggest that certain levels of interpersonal distance afforded smooth interaction with eye contact. Eye contacts were not likely to be exchanged when the infant and parent were too close or too far apart. The number of continuing eye contacts showed an inverse U-shaped pattern with interpersonal distance, regardless of whether the eye contact was initiated by the infant or the parent. However, the interpersonal distance was larger when the infant initiated the eye contact than when the parent initiated it, suggesting that interpersonal distance affects the infant’s and parent’s social look differently. Overall, the present study indicates that interpersonal distance modulates infant-parent gaze communication.

Using hierarchical statistical analysis and deep neural networks to detect covert timing channels

Covert timing channels provide a mechanism to leak data across different entities. Manipulating the timing between packet arrivals is a well-known example of such approach. The time based property makes the detection of the hidden messages impossible by traditional security protecting mechanisms such as proxies and firewalls. This paper introduces a new generic hierarchical-based model to detect covert timing channels. The detection process consists of the analysis of a set of statistical metrics at consecutive hierarchical levels of the inter-arrival times flows. The statistical metrics considered are: mean, median, standard deviation, entropy, Root of Average Mean Error (RAME). A real statistical metrics timing channel dataset of covert and overt channel instances is created. The generated dataset is set to be either flat where the statistical metrics are calculated on all flows of data or hierarchal (5 levels of hierarchy were considered) where the statistical metrics are computed on sub parts of the flow as well. Following this method, 5 different datasets were generated, and used to train/test a deep neural network based model. Performance results about accuracy and model training time showed that the hierarchical approach outperforms the flat one by 4 to 10 percent (in terms of accuracy) and was able to achieve short model training time (in terms of seconds). When compared to the Support Vector Machine (SVM) classifier, the deep neural network achieved a better accuracy level (about 2.3% to 12% depends on the used kernel) and significantly shorter model training time (few seconds versus few 100’s of seconds). This paper also explores the importance of the used metrics in each level of the detection process.

Holistic approach for quantification and identification of pollutant sources of a river basin by analyzing the open drains using an advanced multivariate clustering.

Global scarcity of freshwater has been gearing towards an unsustainable river basin management and corresponding services to the humans. It needs a holistic approach, which exclusively focuses on effective river water quality monitoring and quantification and identification of pollutant sources, in order to address the issue of sustainability. These days, rivers are heavily contaminated due to the presence of organic and metallic pollutants released from several anthropogenic sources, such as industrial effluents, domestic sewage, and agricultural runoff. It is astonishing to note that even in many developing countries, most of these contaminants are carried through open drains, which enter river premises without proper treatment. Such practice not only devastates riverine ecosystem but also gives rise to deadly diseases, such as minimata and cancer in humans. Considering these issues, the present study develops a novel approach towards simultaneous identification of major sources of pollution in the rivers, along with critical pollutants and locations using an advanced hierarchical cluster and multivariate statistical analysis. A systematic approach has been developed by agglomerating both R-mode and Q-mode analysis, which develops monoplots, two-dimensional biplots, rotated component matrices, and dendrograms (using "SPSS" and "Analyse It" software) to reveal relationships among various quality parameters to identify the pollutant sources along with clustering of critical sampling sites and pollutants. A case study of the Ganges River Basin of India has been considered to demonstrate the efficacy and usefulness of the model by analyzing 85 open drains. Both organic and metallic pollutants are analyzed simultaneously as well as separately to get a holistic understanding of all the relationships and to broaden the perspective of water characterization. Results provide a comprehensive guidance to the policy makers and water managers to optimize corrective efforts, minimize further damage, and improve the water quality condition to ensure sustainable development of the river basin.