Important Measure Research Articles

A software trustworthiness evaluation methodology for cloud services with picture fuzzy information

VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is one of the most commonly used decision-making technique. This work provides a software trustworthiness evaluation method based on VIKOR technique in a group decision-making (GDM) environment. Entropy is an important measure that refers to the amount of disorder in a decision support system. To quantify the decision quality of decision maker (DM), a new method for determining DM weights is proposed according to the entropy value of decision matrix, which is provided by that DM. A new normalization-projection measure is developed in order to test the closeness between two evaluation matrices in software trustworthiness evaluation process. The group regret measure in VIKOR-based GDM method is based on two negative reference matrices in this model. A new ranking method with classification is also developed in this work. Aiming at the complex and changeable environment, these new measures and methods are expected to enrich VIKOR techniques and to play a constructive role in group decision support systems. The feasibility and practicability of developed method are verified by some experiments. This study finds that the different methods (models) may have different results in situations where the same decision data are provided by DMs; and this study also finds that the different parameters may have different results in situation where the decision model is same. The practical implications of developed GDM method can apply not only to software trustworthiness evaluation, but also to many other product quality evaluations.

Knowledge, Attitude, and Practice of Contraception Methods among Nursing and Paramedical Staff of Tertiary Care Hospital of Sabarkantha District, Gujarat

Background: Population control contribute towards social and economic growth to the country. Contraceptionis regarded as an important measure to improve maternal and child health. Hospital staff is major contributortowards proving correct information related to contraceptive use among community. This study aimed to assessthe knowledge, attitude, and practice of contraception among nursing and paramedical staff of our hospital.Material and Methods: In this cross-sectional study, 350 nursing and para medical staff were interviewed relatedto their knowledge, attitude and practices pertaining to family planning. A written pre-designed, structuredquestionnaire was used for data collection which included questions on socio-demographic details and Study toolcontained three sections comprising of a total of 20 Questions (Knowledge: 8, Attitude: 7, Practice: 5). MicrosoftExcell was used for data entry and analysis.Results: Most of the participants (96.29%) were having the knowledge related to contraceptive methods. 78% ofparticipants had favourable attitude towards contraception and 74.29% participants were using any method ofcontraception for family planning. Common methods of contraception were condoms and OC pills.Conclusion: Knowledge regarding family planning is universal among hospital staff but still there is gap infavourable attitude and contraceptive use.

Process-based evaluation of carbon emissions from the on-site construction of prefabricated steel structures: A case study of a multistory data center in China

Prefabricated steel structures are being promoted in China as an important measure to reduce building carbon emissions (CEs). Currently, high-quality carbon emission factors and calculation methods that identify the sources of CEs from construction process are lacking. This study proposed a process-based method for calculating on-site construction CEs and empirically demonstrated its feasibility using a case of a multistory steel structure with typical column-beam systems. Six construction processes comprising 38 subprocesses were first categorized, then the energy and materials consumed for each subprocess were determined to obtain the first-hand CE parameters. The CEs from hoisting the first- and second-section columns were 10.52 kgCO2/column and 14.41 kgCO2/column, respectively, and the CEs from their installation were in the range 38.16–69.18 kgCO2/column. The CEs from hoisting the primary and secondary beams using a car crane were 7.73 kgCO2/beam and 4.52 kgCO2/beam, respectively, with lower CEs of 2.40 kgCO2/beam and 2.22 kgCO2/beam, respectively when a tower crane was used for hoisting. The 14 connection types used to install the primary beams and the 11 connection types used to install the secondary beams had CEs of 13.84–125.96 kgCO2/beam and 10.39–43.49 kgCO2/beam, respectively. The total on-site construction CE was subsequently calculated by summing the CEs from each process. This method was able to track the CE sources for each construction process and their contributions to identify those with high CE intensities. In addition, the case study was evaluated to provide specific feedback on the current national standard for calculating CEs from building construction.

Inference of differential gene regulatory networks using boosted differential trees.

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in four different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19, Crohn's disease, breast cancer, prostate adenocarcinoma, and stress response in Bacillus subtilis. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses. BoostDiff is available at https://github.com/scibiome/boostdiff_inference.

Theft and Vandalism Control Measures on Construction Sites

Purpose: The goal of this study is to determine and improve the best security practices within Ghanaian construction sites to control theft and vandalism incidents.
 Design/Methodology/Approach: A purposive sampling technique was adopted for the population which were indigenous small and medium-sized construction firms of D1KI and D2K2 categories to complete the semi-structured questionnaire. Out of the total of 80 questionnaires distributed, only 65 responses were retrieved for analysis. Descriptive statistics comprising, frequencies and mean scores were used. 
 Findings: The findings showed that the most effective and often utilized security measure on construction sites is the hiring of watchmen, with security cameras, alarm systems, and warning signs being the least frequently employed. Sites would most likely be protected from theft by effective implementation of the most important security measures while also guaranteeing that the value for money invested in site security is also realized.
 Research Limitation/Implications: The effectiveness of theft and vandalism control measures may vary based on specific site characteristics, such as location, size, and type of construction. Generalising findings from one site to all construction contexts may not be applicable.
 Social Implication: Incidents of theft and vandalism can lead to social tensions within the community, especially if residents perceive construction activities as a source of risk. Effective control measures mitigate these tensions, fostering a more harmonious relationship between construction companies and the local population.
 Practical Implication: Minimizing the impact of theft and vandalism contributes to the timely completion of construction projects. Unanticipated delays due to security incidents can be avoided, ensuring that projects adhere to planned schedules and deadlines.
 Originality/ Value: The originality of this paper lies in its targeted investigation into theft and vandalism control measures on small and medium-sized construction sites, offering innovative and contextually relevant solutions that address the unique challenges faced by SMEs in the construction industry.

Bayesian analysis of Markov modulated queues with abandonment

AbstractWe consider a Markovian queueing model with abandonment where customer arrival, service and abandonment processes are all modulated by an external environmental process. The environmental process depicts all factors that affect the exponential arrival, service, and abandonment rates. Moreover, the environmental process is a hidden Markov process whose true state is not observable. Instead, our observations consist only of customer arrival, service, and departure times during some period of time. The main objective is to conduct Bayesian analysis in order to infer the parameters of the stochastic system, as well as some important queueing performance measures. This also includes the unknown dimension of the environmental process. We illustrate the implementation of our model and the Bayesian approach by using simulated and actual data on call centers.

The impact of study type and sleep measurement on oxygen desaturation index calculation.

The oxygen desaturation index (ODI) is an important measure of sleep-disordered breathing during polysomnography (PSG); however, the AASM Manual (V3) does not specify whether to include oxygen desaturations occurring during wake epochs. Additionally, an ODI obtained from PSG can differ from an ODI using home sleep apnea tests (HSATs) that do not measure sleep, hampering diagnostic and treatment decision reliability. This study aimed to (1) compare an ODI that included all desaturations with an ODI that excluded desaturations occurring during wake epochs in PSG and (2) compare ODIs obtained from PSG with HSAT. 100 consecutive PSGs for investigation of obstructive sleep apnea were compared. ODIs were calculated including all desaturations (ODIall) and by excluding desaturations entirely during wake epochs (ODIsleep). Additionally, we compared ODIall with an ODI calculated using monitoring time as the denominator (ODIHSAT). The median (interquartile range) 3% ODI for ODIall was 22.8 (13.1, 44.1) events/h and ODIsleep was 17.6 (11.5, 35.2) events/h (median difference: -3.9 events/h [-8.2, -0.9]; 21.0% [8.7%, 33.2%]). This discrepancy was larger with increasing ODI and decreasing sleep efficiency. The ODIHSAT was 17.4 (11.3, 35.2) events/h and the median reduction in ODIHSAT vs ODIall was -4.5 (-10.9, -2.0) events/h (21.6%; 11.1%, 33.8). ODI was significantly reduced when desaturations in wake epochs were excluded, and when ODI was based on monitoring time rather than sleep time, with the potential for underestimation of disease severity. Results suggest that ODI can differ substantially depending on the calculation and study type used, and that there is a need for standardization to ensure consistent diagnosis and treatment outcomes. Whenn CB, Wilson DL, Ruehland WR, Churchward TJ, Worsnop C, Tolson J. The impact of study type and sleep measurement on oxygen desaturation index calculation. J Clin Sleep Med. 2024;20(5):709-717.

Time series importance measure-based reliability optimization for cellular manufacturing systems

Cellular manufacturing systems (CMSs) can improve the quality and efficiency of the manufacturing process by multiple processing cells with different functions and group technology. CMSs require high reliability to complete processing missions successively, so reliability optimization is an important part to guarantee system performance. This paper proposes a binary decision diagram-based three-step evaluation method to analyze CMS reliability. A reliability optimization model of CMS is constructed by considering the limited cost to determine the optimal combination of machine degradation parameters. Considering the advantages of ant colony optimization (ACO) and time series importance measure (TIM), a TIM-based ant colony optimization (TIACO) is developed to solve the optimization model. To verify the performance of TIACO, system reliability and running time are introduced to compare with genetic algorithm (GA), ACO, and time series importance measure-based genetic algorithm (TIGA). (1) System reliability obtained by TIACO is always the best. (2) Running time of TIACO is smaller. A case study of an unmanned aerial vehicle manufacturing company verifies the effectiveness of TIACO, and machines with higher TIMs should be given priority to improving their degradation parameters, which provides a new idea for reliability evaluation and optimization of CMSs.

Estimating relative importance of criteria by post-processing dominance-based rough set approach’s outputs

The dominance-based rough set approach (DRSA) is one of the rare multicriteria sorting methods that does not require a priori values for the relative importance of criteria. This method therefore is cognitively less demanding. However, the decision-maker may lack some valuable information that is needed to explain and justify final decisions to stakeholders. The relative importance of criteria can instead be estimated based on the characteristics of the outputs of the DRSA, which are mainly decision rules and attribute reducts. The estimated values can then be used to understand the role played by each criterion and justify the final decisions to stakeholders. This paper first reviews and improves the decision rule attractiveness measure and the relative importance measures that are based on decision rules and attribute reducts, which were all proposed in the authors’ previous work. It also introduces new measures that rely on the marginal contributions and entropy of the criteria. This paper also extends these measures to estimate the relative importance of criteria with respect to specific unions of classes. The proposed measures have been applied to Brexit referendum and bankruptcy risk assessment datasets. Both applications showed that the proposed measures generally lead to different results. This can be explained by the diversity of the knowledge on which these measures rely and also by the multiplicity of the analytical perspectives associated with them. The results also showed that the marginal contribution-based measure is a good estimator of both Shapley and Banzhaf values.

Candida auris: Emerging fungal pathogen in the US.

Candida auris (C. auris) is a human pathogen that can colonize the skin and various body sites without signs or symptoms or cause serious invasive infections with high mortality. The number of cases involving drug-resistant C. auris infections have increased in the US in recent years. This article provides an overview of C. auris and important infection prevention and control measures.

Alpha heating and avalanche effect simulations for low density proton-boron fusion plasma

The initial interest in p-11B fusion, which produces three (3) alpha particles with total energy of 8.7 MeV, was regained the last few years, due to the important experimental measurements on alpha particle production and theoretical and numerical investigations. The re-evaluation of proton-boron fusion, as an important vector for “aneutronic” energy production, is based on the consideration of the “chain reactions alpha heating effect and the related avalanche effect”, as the important process, for the increase of the fusion species (p, 11B) temperatures, to temperatures corresponding to the optimump-11B fusion cross sections. Investigation of ignition and self-sustained conditions for low density (∼ 1020 m-3) proton-boron fusion plasmas is an interesting study topic for application in magnetic confinement. We use a multi-fluid, global particle and energy balance code, describing the temporal evolution of the physical parameters of the fusion medium, as a function of the initial conditions of density and temperature of the fusion species (p, 11B). For the establishment of the distinct contribution role of the avalanche effect in proton-boron fusion, we explore cases of low (<100 keV) and high (>100 keV) initial p-11B medium temperatures. For these temperature cases, density ratios np /nB > 1between the fusion species (p, 11B) are considered, for the optimization of Bremsstrahlung radiation losses. Simulations using the multi-fluid code in a low density p-11B medium with np /nB > 1, enable the evaluation of the initial temperatures range, which is necessary for the temporal increase of the alpha density, the rapid improvement in the p-11B fusion reaction rate (RR), the temperature rise of the fusion species (p, 11B) and the achievement of higher than 1 Q (Pf /P Brems) values, due to the manifestation of the avalanche effect.In the case of high initial fusion medium temperatures in the range: 150 keV ≤ T in ≤ 350 keV, the chain reactions alpha heating effect and the related avalanche effect contribute to the maintenance and the rise of the fusion species (p, 11B) temperature to high values, for ignition and self-sustained fusion (Q > 1).

دراسة سوسيولوجية لتأثير الهشاشة البيئية على الوضعية الاجتماعية للأفراد: ساكنة جماعة تغدوين الحوز(مراكش) نموذجًا

Climate and environmental changes pose a clear threat to human security worldwide, and Morocco, along with other affected countries, bears a significant portion of this climate burden. The aim of this study is to shed light on the impact of environmental vulnerability on the social situation of families in the "Tirghedouine El haouz Marrakech" community. The study focuses on key theoretical approaches that interpret concepts such as environment, fragility, poverty, and emphasizes the importance of the environmental dimension in sociological studies. In the applied aspect of the study, the main environmental threats faced by families were identified, along with an examination of all the negative repercussions of these threats on various sectors of human security and societal stability. This includes economic decline and reduced income due to the deterioration of the agricultural and tourism sectors, which are essential for the livelihoods of the population, leading to an exacerbation of instability in the region. The study also attempted to identify the most important solutions and measures taken by the population to face floods, which are characterized by their simplicity as they are individual, self-patched solutions that are insufficient to avert danger. Additionally, the study monitored the main strategies and measures adopted by local authorities to address floods, which are characterized by weakness and procrastination. In conclusion, the research results confirm that environmental threats, particularly floods, have disrupted the security and stability of the region, resulting in negative socio-economic repercussions that have affected the livelihoods and environmental, social, and economic security of the population.

Psychosocial Well-being among Diabetic Individuals

Background: Quality of life (QoL) assessment is considered an important outcome measure in chronic disease management. With an increase in the prevalence of diabetes in India, it becomes imperative to assess QoL in diabetic patients for their better care and control. The present study aimed to assess the QoL among diabetic patients attending the diabetic outpatient clinic and probe its association with glycemic status and management. Methodology: A cross-sectional study was conducted for 4 months among 185 type 2 diabetes mellitus (T2DM) patients. Information on sociodemographic profile, diabetic history, and current medications was obtained. QoL was assessed using the General Health Questionnaire-28 (GHQ-28). The results were statistically analyzed. Results: Using GHQ-28, the psychosocial components of the patients in the fields related to somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression were assessed. Significantly higher GHQ scores (P &lt; 0.05) were noted in T2DM patients with higher glycated hemoglobin and increased plasma glucose levels, suggesting stronger associations of poorer QoL with compromised glycemic status. Insulin users exhibited higher GHQ scores (higher scores for depression subdomains) compared to noninsulin users. QoL was also found significantly dependent on the duration of diabetes and other comorbidities. Conclusion: The psychosocial well-being of the patients is significantly impacted in cases of chronic ailments like diabetes which adds to the total disease burden eventually. The present study warrants periodic assessment of QoL in diabetic individuals as a part of routine care along with advise of psychiatric counseling for those in need.

Examining age, period and cohort effects in attitude change to childhood vaccinations in a representative New Zealand survey: a multiyear cohort-sequential growth modelling study

ObjectivesVaccinations are an important preventative measure in reducing the spread of infectious diseases worldwide. However, concerns of undervaccination during childhood have become increasingly common. The current study aims to investigate...

Rabies vaccination adherence and associated factors among rabies-exposed patients in Shenzhen, China: a hospital-based cross-sectional study.

Adherence to post-exposure prophylaxis and post-exposure vaccination (PEV) is an important measure to prevent rabies. The purpose of this study was to explore the adherence to the vaccination protocol and its influencing factors among rabies-exposed patients in Shenzhen, China. A cross-sectional survey was conducted in a tertiary hospital in Shenzhen, China, to obtain epidemiological characteristics of patients; knowledge, attitude, and practice scores of rabies prevention; and medical records. A total of 326 patients requiring full rabies PEV were included in this study, and only 62% (202) completed the full course of vaccination according to the norms of the vaccination guidelines. After multifactor logistic regression, the factors influencing adherence to vaccination were as follows: age 31 to 40 years, time spent to reach the nearest rabies prevention clinic was >60 min, the time of injury was at night to early morning, the place of injury was a school/laboratory, the animal causing injury was a cat, the health status of the animal causing injury could not be determined, and patients with higher practice scores (all p<0.05). Understanding the factors influencing rabies vaccination adherence among rabies-exposed patients in urban areas of China and promote changes in patients' practice toward rabies prevention is essential for rabies elimination by 2030.

Research on countermeasures of China’s Marine culture dissemination under the background of maritime power--Take Zhoushan City of Zhejiang Province as an example

The development of Marine cultural tourism is an important measure to promote the development of Marine economy under the background of maritime power. The report on the work of the 20th National Congress of the CPC emphasized speeding up the construction of a maritime power and promoting the dissemination and development of Marine culture. China's Marine culture is rich and diverse, but the coastal cities are faced with many problems in the actual dissemination process, such as the characteristics of Marine culture are not prominent, homogenization is serious, and integration construction is not formed. This paper starts with the current situation of Marine culture communication, analyses the existing practical experience and existing problems of Marine culture communication, and takes Zhoushan City, a famous coastal city in Zhejiang Province, as an example to discuss the countermeasures for the construction of China's Marine culture communication system under the background of maritime power, so as to promote the new development of Marine culture communication.

Information Security Maturity Model for Healthcare Organizations in the United States

This article provides a maturity model for information security for healthcare organizations in the United States. Healthcare organizations are faced with increasing threats to the security of their information systems. The maturity model identifies specific performance metrics, with relative importance measures, that can be used to enhance information security at healthcare organizations allowing them to focus scarce resources on mitigating the most important information security threat vectors. This generalizable, hierarchical decision model uses both qualitative and quantitative metrics based on objective goals. This model may be used as a baseline by which to measure individual organizational performance, to measure performance against other organizations, or to monitor changes in the information security environment over time.

SEDMA: Self-Distillation with Model Aggregation for Membership Privacy

Membership inference attacks (MIAs) are important measures to evaluate potential risks of privacy leakage from machine learning (ML) models. State-of-the-art MIA defenses have achieved favorable privacy-utility trade-offs using knowledge distillation on split training datasets. However, such defenses increase computational costs as a large number of the ML models must be trained on the split datasets. In this study, we proposed a new MIA defense, called SEDMA, based on self-distillation using model aggregation to mitigate the MIAs, inspired by the model parameter averaging as used in federated learning. The key idea of SEDMA is to split the training dataset into several parts and aggregate multiple ML models trained on each split for self-distillation. The intuitive explanation of SEDMA is that model aggregation prevents model over-fitting by smoothing information related to the training data among the multiple ML models and preserving the model utility, such as in federated learning. Through our experiments on major benchmark datasets (Purchase100, Texas100, and CIFAR100), we show that SEDMA outperforms state-of-the-art MIA defenses in terms of membership privacy (MIA accuracy), model accuracy, and computational costs. Specifically, SEDMA incurs at most approximately 3 - 5% model accuracy drop, while achieving the lowest MIA accuracy in state-of-the-art empirical MIA defenses. For computational costs, SEDMA takes significantly less processing time than a defense with the state-of-the-art privacy-utility trade-offs in previous defenses. SEDMA achieves both favorable privacy-utility trade-offs and low computational costs.

Age at arrival and integration outcomes of refugee youth and emerging adults: a longitudinal study.

Age at arrival is one factor that could influence the integration of humanitarian migrants, especially for children and teenagers. Previous research has focused on the influence of the age at arrival on education, employment, social and language learning outcomes, but there is limited research, especially for longitudinal study, on other important measures of integration. Moreover, young adult and adolescent refugees, and the relationship between age and integration outcomes are under-studied. To address these gaps, this study examined the relationships between age at arrival and different dimensions of integration of young refugees in Australia, using five years' panel data from the Building a New Life in Australia (BNLA) longitudinal study from 2013 to 2018 (282 individuals). Our findings indicate that age at arrival is significantly correlated with multiple integration outcomes. Old entrants tend to have a higher probability of having a paid job but have poorer mental health and English proficiency. On the other hand, older entrants were more likely to know their rights well compared to younger entrants at arrival. However, younger entrants' knowledge of their rights overtook older entrants four to five years after their arrival. These findings suggest that a shorter assessment process and enabling earlier entry especially among refugee youth and young adults could effectively improve their future settlement outcomes under the current humanitarian policies and system.

Reduction of soil methane emissions from croplands with 20–40 years of cultivation mediated by methane-metabolizing microorganisms

Reducing carbon emissions from cropland ecosystems is an important measure to achieve early carbon neutrality. However, how methane-metabolizing microorganisms affect methane emissions from cropland soils of different planting years is not known. In this study, we determined methane emissions from cropland soils of different tobacco-rice rotation years after rice harvesting. By mean of functional gene sequencing, we analyzed the relationship between methane-metabolizing microorganisms and methane emissions, and revealed the microbial mechanism of action for methane emissions from cropland soils. The results showed that the soil organic carbon content was higher (P < 0.05) and methane emissions were lower (P < 0.05) in cropland cultivated for 20–40 years (PY20). Soil methane emissions from PY20 cropland were reduced by 30.11% and 14.58% (P < 0.05) compared to cropland planted for 10–20 years and more than 40 years. The alpha diversity of methanogens communities was significantly lower in PY20 cropland soils, whereas the methanotrophs communities alpha diversity did not differ significantly between planting years. The methanogenic genus Methanocorpusculum was significantly and positively correlated with methane emissions. The relative abundance of Methanocorpusculum in PY20 cropland soil was lower (P < 0.05), and the relative abundance of Methylocystis, a type II methanotrophs with greater oxidizing capacity for methane, was higher (P < 0.05). Reducing PY20 cropland soil methane emissions by reducing methane production and enhancing methane oxidation. At the same time, more methanotrophs in PY20 cropland soil formed a molecular interactions network with methanogens. Planting years altered the diversity and composition of methane-metabolizing microbial communities and the interactions of different taxa, which in turn affected methane emissions. Cropland soils that have been cultivated for 20–40 years have lower methane production capacity and higher methane oxidation capacity, resulting in lower methane emissions. This study provides a scientific reference for the microbial action mechanism of soil methane emission from cropland under different planting years, with a view to contributing to carbon neutralization in cropland ecosystems.