Out Of Control Research Articles

EV BMS With Temperature and Fire Protection

The rising reception of electric vehicles (EVs) has featured the significance of creating progressed battery the board frameworks (BMS) that focus on security and effectiveness. This theoretical presents an outline of the most recent headways in EV BMS innovation, explicitly zeroing in on temperature and fire security highlights. Temperature the executives assumes a basic part in guaranteeing the ideal presentation and life span of battery frameworks. EV BMS with cutting edge temperature checking and control abilities are intended to moderate the gamble of overheating and warm out of control. These frameworks integrate complex sensors and calculations to constantly screen the battery’s temperature and manage it inside safe cutoff points. Fire assurance is one more significant part of EV BMS plan. Lithium-particle batteries, generally utilized in EVs, are vulnerable to warm out of control occasions that can prompt flames or blasts.

Profile monitoring of residuals control charts under gamma regression model

The statistical control chart is considered one of the superlative tools in quality control. Currently, control charts are being widely used in various areas, one of them being manufacturing processes. They are essential instruments that can impart crucial insights to quality controllers for maintaining productivity. The quality of a product or process can be characterized by a relationship between two or more variables, which is typically referred to as a profile. Also, public health surveillance is considered another important area that widely used control charts. In this regard, they are very useful and reliable tools for detecting outbreaks of infectious diseases. On the other hand, the gamma regression model (GRM) is a popular model considered in medical and other fields. It is applied when the response variable is continuous and positively skewed and well fitted to the gamma distribution. This paper presents a scheme for monitoring the profile. Based upon the generalized linear model (GLM) in the case of two link functions: identity and log link function. Exponentially weighted moving average control charts (EWMA) are proposed using deviance residuals and Pearson residuals for detecting any disturbance in the control variable of the gamma regression model. A detailed simulation study is designed to scrutinize and evaluate the performance of the control charts in phase I analysis and in phase II under parametric maximum likelihood estimation (MLE) using the average run length (ARL) measure. It turns out that using deviance residuals under the identity link function seems more suitable than Pearson residuals. Also, with increasing the sample size, the percentages of out-of-control (OC) samples increased which is theoretically acceptable

A designed antimicrobial peptide with potential ability against methicillin resistant Staphylococcus aureus.

Staphylococcus aureus (S. aureus) is a Gram-positive pathogenic bacterium, which persistently colonizes the anterior nares of approximately 20–30% of the healthy adult population, and up to 60% is intermittently colonized. With the misuse and overuse of antibiotics, large-scale drug-resistant bacteria, including methicillin-resistant S. aureus (MRSA), have been appeared. MRSA is among the most prevalent pathogens causing community-associated infections. Once out of control, the number of deaths caused by antimicrobial resistance may exceed 10 million annually by 2050. Antimicrobial peptides (AMPs) are regarded as the best solution, for they are not easy to develop drug resistance. Based on our previous research, here we designed a new antimicrobial peptide named GW18, which showed excellent antimicrobial activity against S. aureus, even MRSA, with the hemolysis less than 5%, no cytotoxicity, and no acute toxicity. Notably, administration of GW18 significantly decreased S. aureus infection in mouse model. These findings identify GW18 as the ideal candidate against S. aureus infection.

Role of Derivatives Ciprofloxacin on Chronic Myeloid Leukemia: In Silico Approach

Introduction: chronic myeloid leukemia is one of the major diseases, which cause death worldwide. Tyrosine kinase is responsible for uncontrolled cell growth and block its function. Its inhibition is a promising route to control the out of control grow of cells. The purpose of our study involves docking of human Abl kinase with seven ciprofloxacin derivatives and the comparison of results free energy binding with positive control (Imatinib).Methods: the present study aims to examine the interactions between human Abl kinase(2HYY) domain retrieved from protein data bank and seven ciprofloxacin derivatives in comparison with imatinib as a reference. The analysis was performed using Autodock vina Implicated in the PyRx 0.8 tool.Results: docking revealed that, according to their free binding energy imatinib still have the lowest binding energy followed by CHOCP and MPCP. In silico ADMET predictions revealed that except DMOCP all other compounds had toxic effects.Conclusion: these compounds may not serve as a potential inhibitor due to their high free energy binding and their toxicity in comparison with imatinib.

Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach.

As the availability of COVID-19 vaccines, it is badly needed to develop vaccination guidelines to prioritize the vaccination delivery in order to effectively stop COVID-19 epidemic and minimize the loss. We evaluated the effect of age-specific vaccination strategies on the number of infections and deaths using an SEIR model, considering the age structure and social contact patterns for different age groups for each of different countries. In general, the vaccination priority should be given to those younger people who are active in social contacts to minimize the number of infections, while the vaccination priority should be given to the elderly to minimize the number of deaths. But this principle may not always apply when the interaction of age structure and age-specific social contact patterns is complicated. Partially reopening schools, workplaces or households, the vaccination priority may need to be adjusted accordingly. Prematurely reopening social contacts could initiate a new outbreak or even a new pandemic out of control if the vaccination rate and the detection rate are not high enough. Our result suggests that it requires at least nine months of vaccination (with a high vaccination rate > 0.1%) for Italy and India before fully reopening social contacts in order to avoid a new pandemic.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11538-022-01064-w.

Monitoring non-parametric profiles using adaptive EWMA control chart

To monitor the quality of a process in statistical process control (SPC), considering a functional relationship between a dependent variable and one or more independent variables (which is denoted as profile monitoring) is becoming an increasingly common approach. Most of the studies in the SPC literature considered parametric approaches in which the functional relationship has the same form in the in-control (IC) and out-of-control (OC) situations. Non-parametric profiles, which have a different functional relationship in the OC conditions are very common. This paper designs a novel control chart to monitor not only the regression parameters but also the variation of the profiles in Phase II applications using an adaptive approach. Adaptive control charts adjust the final statistic with regard to information of the previous samples. The proposed method considers the relative distance of the chart statistic to the control limits as a tendency index and provides some outcomes about the process condition. The results of Monte Carlo simulations show the superiority of the proposed monitoring scheme in comparison with the common non-parametric control charts.

Analysis on Risk Management of Software Outsourcing Project

Nowadays many companies outsource the whole or part of software projects to other companies to reduce the cost of software projects and focus on the development of core competitive businesses. Due to the rapid update and iteration speed of information technology, the complexity of software projects is also increasing, and the risk factors in software outsourcing projects are also increasing. The existence of these risks can prolong the project cycle, or directly lead to project failure. At present, many software outsourcing companies do not pay much attention to project risk management, and cannot effectively identify, supervise and deal with risks, resulting in out of control or even failure of software outsourcing projects. This paper will summarize the list of risk factors by studying the characteristics and status quo of today's outsourcing projects, and analyzing the possible analysis of each stage of software outsourcing projects. Use brainstorming, expert assessment, and qualitative analysis to evaluate and identify risk factors. Finally, from a practical point of view, this paper will put forward some suggestions for the future software outsourcing project risk management. I hope to achieve two purposes through the research of this paper. One is to contribute some research experience to the risk management of software outsourcing projects and guide the actual work of enterprises. Second, we should advocate innovative thinking and encourage more and better ideas to emerge.

BUILT ENVIRONMENT ROLE IN CHANGING MOTHERS PERCEPTION ON CHILDREN’S WALKING INDEPENDENTLY TO SCHOOL

Women have a great significance in their children's lives from the moment they are born. The choice that mothers make regarding their children's mode of travelling to school will have a significant impact on how those children will think about walking and cycling in the future. The purpose of this study is to identify the perspectives of mothers towards allowing their children to school by walking in an area that is deemed suitable for such trip in our discussion on the nation’s future generation towards walking and not depending on private vehicles as the main mode of travelling. A focus group discussion, also known as FGD, took place in Taman Ilmu, which is in Nibong Tebal, Pulau Pinang. As a result of this study, using thematic analysis to analyse the results of conversation during the FGD session and collective mapping, we discovered four (4) themes of mother’s perspectives towards their children walking to school, which are as follows: (1) confidence and trust; (2) safety; (3) age and gender; and (4) weather. In summary, the built environment can be described as a solution to the 'out of control' scenario in which government and parental roles are effective in resolving the issue of children walking independently to school.

Gloomy and out of control? Consequences of the COVID-19 pandemic on momentary optimism in daily lives of adolescents

In the global COVID-19 pandemic, adolescents are regarded as especially burdened due to school closures and leisure activities being banned, often reducing peer contacts to zero. Experiencing restrictions while being uninvolved in decision-making processes left them with little control over their daily lives. Meanwhile, research highlights that optimism can act as a buffer against the impact of daily hassles and is considered an important resource for mental health. To understand the implications of the COVID-19 pandemic for adolescents' lives, this study examined how momentary perceived control and perceived personal and societal consequences of the COVID-19 pandemic relate to momentary optimism. Using experience-sampling data from N = 242 (Mage = 15.89; 86% female) adolescents assessed during the second pandemic wave in Germany, multilevel modeling revealed positive associations between adolescents’ momentary perceived control and their momentary optimism at both the within- and between-person level. Additionally, perceived consequences of the COVID-19 pandemic showed specific associations with momentary optimism: Whereas perceived societal consequences were directly related to lower momentary optimism, perceived personal consequences strengthened the relationship between momentary perceived control and optimism. These findings highlight the role of perceived control as an important resource for optimism both as a general tendency and within specific situations in daily life. This way, our results may shed light on how to support adolescent optimism during states of emergency, such as a worldwide pandemic.

Analysis of SS Tempe production quality control with the six sigma method at Sirajussa’adah Islamic Boarding School Limo Depok

Quality is a factor to increase the competitiveness of a product. By increasing quality, the production costs will be reduced, thus it will eventually reduce waste. The failure of a product can be caused by the availability of raw materials, machines, equipment, human resources, and environmental factors during the production process. Quality control is a method used to keep the product needed by the market to be within controlled limits. This study aims to determine the quality of Tempe SS products at the Sirajussa’adah Islamic Boarding School in Limo Depok. It is carried out to see whether the quality is still within control limits or not by using the Six Sigma method with several stages of DMAIC (Define, Measure, Analyze, Improve and Control) implementation. In this research, calculations are carried out using the checksheet, flow chart, histogram, Pareto Hart, control, scatter diagram and fishbone diagram methods of production. Based on the results, it can be concluded that for 25 times the study, it is obtained the value of the center line (CL) of 0.0036, the value of the upper control limit (UCL) of 0.0050, and the value of the lower control limit (LCL) of 0. It is also found that there are a number of variations in the process that are outside the control limit (out of control) and within the control limit (in control) in the production process of Tempe SS at the Sirajussa Islamic Boarding School in Limo Depok. However, this is still inadequate for the fermentation process infrastructure, equipment for packaging is still manual and environmental factors determine the cause of the number of defective products.

California in Flames: A Literature Review on the Causes and Effects of Wildfires

Throughout the hot and arid months, (May - September) anthropogenic impacts are causing wildfires to spread immensely in California and are inflicting devastating damage on the surrounding environment. Normally, naturally occurring fires are one of the best things that could help stabilize forest ecosystems. However, human impacts on the environment, ranging from increased fossil fuel consumption to growing logging industries have caused wildfires to spiral out of control. When the natural biosphere gets thrown out of balance, mass death and loss of biodiversity follows. This decrease in biodiversity could cascade into the extinctions of thousands of flora and fauna species across the West Coast. With the world's population increasing and more stress being put on natural resources, there is a growing fear that humans will eventually destroy the ancient forest biomes if no steps are taken to end the plague of wildfires. Currently, the techniques used to help control wildfires are not enough to stop them from causing massive damage to California’s biosphere. Messy cleanups after logging operations and other careless human behavior are still the biggest reasons behind preventable wildfires. If the climate crisis and other human activities are not addressed immediately, the state could lose its most species-rich areas forever.

The Poetics of Transformation: Ovid’s Metamorphoses as Thematic Inspiration, Model of Mythologization and Poetic Model in the Poetry of Sándor Weöres

The Metamorphoses is one of the most productive and complex intertext in the poetry of Hungarian poet Sándor Weöres. This paper addresses some models of complex rewriting of the Ovidian text in the 1950s, analysing the radical poetic rewriting of the Ovidian metaphors, mythical prosopopeias and the poetic figures of metamorphosis in Weöres’ poetry. The epic mythological poems of that decade (Medeia, Minotauros, Orpheus) connect and contrast fragments of the disparate mythic narratives of the characters. The textual and narrative discontinuity and the mixture of epic, lyric and dramatic discourses allow to read these poems as a simultaneous experiment with transformation and interchange of the dramatic functions of the characters, dissolving and establishing the borders of their identity, testing the capacity of the co-reading of contrasting and distant mythologems. Ovid’s characteristically ironic move from admiring the beauty to a distinctly rapacious love of having, the reciprocity of the distant characters’ narratives and the poetical utilization of the sonority (the metaphorisation of the sound, and the out of control of the own speaking, invoking the voice at the moment it is lost) are very fruitful for the Echo (1954).

An ensemble neural network framework for improving the detection ability of a base control chart in non-parametric profile monitoring

Profile monitoring is a challenging issue in statistical process control (SPC). It aims to use a functional relationship between a response variable and one or more explanatory variable(s) to summarize the quality of a process/product. Most of the existing studies consider the same form of a functional relationship for both in-control (IC) and out-of-control (OC) situations or parametric approaches. However, non-parametric profiles with different relationships in OC conditions are very common. In this paper, we propose a novel ensemble framework to monitor changes in both regression relationship and variation of the profile for Phase II applications. This approach employs a pool of artificial neural networks (ANNs) as learners to enhance the efficiency of a base control chart, which is a non-parametric exponentially weighted moving average (NEWMA) in this study. Then, a further ANN is used as a reasoning scheme (incorporator) to perform prediction by combining the outcomes of the learners. Experimental results demonstrate the effectiveness of the proposed framework, denoted by EANNN, in comparison with the base control chart, i.e., NEWMA, and other non-parametric methods. In addition, a practical example regarding a deep reactive ion-etching process from semiconductor device fabrication is provided to show the implementation of the proposed method.

Adaptive CUSUM chart with cautious parameter learning

AbstractThe classic CUSUM chart assumes that the in‐control (IC) mean and variance are known. In practice, these parameters are usually estimated from an IC Phase I sample. Recently, Capizzi and Masarotto proposed a cautious parameter learning scheme to incorporate Phase II IC observations in the estimation of the IC mean and variance to reduce the variation of conditional average run lengths (ARLs). In this paper, we develop a new cautious parameter learning scheme that can distinguish IC observations from out‐of‐control (OC) observations in the Phase II sample more effectively than Capizzi and Masarotto's scheme. As a result, our cautious parameter learning scheme can provide better estimation of the IC mean and variance. Combining the new cautious parameter learning scheme with an adaptive CUSUM chart, our proposed monitoring procedure is easy to implement, and is shown to have less variability in conditional ARLs and better overall performance for detecting different mean shifts than existing methods.

The impact of digital screen use on myopia progression in COVID-19 pandemic: A systematic review

The new coronavirus disease of 2019 (COVID-19) had a worldwide impact, this disease was affecting almost everyone's lives. It has caused many health issues to spiral out of control, one of them is myopia. Evidence suggests that myopia is impacted by environmental and lifestyle factors, with the importance of continuous usage of nearby digital screens being highlighted. The systematic review aims to analyze all the available information about the impact of digital screen use on myopia progression in a COVID-19 pandemic. The literature was searched from e-database PubMed and ScienceDirect. Quality assessment was done using the LEGEND (Let Evidence Guide Every New Decision) Evidence Evaluation Tools & Resources. A total of 10 papers were assessed qualitatively. The prevalence or incidence of myopia was reported in all ten studies. All of the studies discussed in this review suggest a relationship or impact between digital screen use and myopia progression. Four (40%) of the ten studies were cross-sectional, while the other six (60%) were cohort studies. The sample size ranged from 115 to 123535 participants. The majority of the participants in the studies were school-age children (primary and secondary school), but one study included university students. There were three studies involving subjects with myopia at baseline, one study involving subjects without myopia at baseline, and six studies involving subjects with myopia and without myopia. This systematic review shows that there is a significant progression of myopia as an impact of digital screen use during the COVID-19 pandemic.

Control Chart and Its Applicationin Modelling Body Mass Index (BMI) of Students in Delta State Polytechnic, Oghara

This study aimed to examine the health status of students as a function of the body mass index (BMI) using control chart. The utility of body mass index has proven very useful in helping managers to estimate the weight normality of individuals as a measure of healthy living among them. This study evaluated the reported BMI of students and problems associated with abnormal BMI among students. Stratified sampling was adopted since there are three faculties or schools in the polytechnic with each school having several departments, therefore, A simple random sample of 150 students was selected from the three schools of study in the Delta State Polytechnic, Otefe-Oghara and their BMI were examined through data on weight and height. The result of the study revealed that the students BMI are statistically in control for X-chat and out of control for MR-chat in engineering, both X-chart and MR-chart are out of control for Applied sciences but for school of business, both chats are in statistical control. The fact that the test for randomness proved to be false; it implies that the sample result is evident enough to infer on the general population that their current measures of body mass index are not random. Consequent to the study findings, it was concluded that quality control tools: (control chart for individual unit) is a veritable too for student BMI diagnostics. The study also concludes that most students’ BMI was classified according to the World Health Organization (WHO) standard to be obese, which indicates a huge health risk of various obese-related diseases like diabetes, cardiac issues and even stroke especially for school of engineering and applied sciences.

Evaluation of Intervention Policies for the COVID-19 Epidemic in the Seoul/Gyeonggi Region through a Model Simulation.

PurposeTo evaluate the efficacy of intervention policies on coronavirus disease-19 (COVID-19) dissemination.Materials and MethodsAn age-structured compartmental model for the COVID-19 outbreak was proposed to predict the impact of control measures in the Seoul/Gyeonggi region. The model was calibrated based on actual data and realistic situations, including daily vaccine doses, proportion of delta variant cases, and confirmed cases by age. We simulated different scenarios for non-pharmaceutical interventions by varying social distancing and school attendance strategies.ResultsTwo-step mitigation of social distancing without in-person classes would result in a rapid increase in confirmed cases up to 10000 but would keep severe cases within the manageable range of the health care system. The overall impact of taking down the distancing level by one step with twice the increase in contacts at school was comparable to the above scenario. Implementation of two-step mitigation of social distancing along with a two-fold increase in contacts among the school-age group would dramatically increase confirmed and severe cases by over 80000 and 100, respectively, as early as the beginning of December. This policy would cause the situation to spiral out of control, considering the scale of the response and time to prepare. On the other hand, the burden on the current healthcare system caused by two-step mitigation of social distancing and 40% increased contacts in the school-age group was manageable if prepared.ConclusionA compromise between social distancing and school attendance policy and timely preparations for the spread of COVID-19 are required.

EDR을 활용한 자동차 보험사기 의심 사례 분석

According to the recent press release from the Financial Supervisory Service, automobile insurance fraud is increasing every year. The government tried to respond to insurance fraud by enforcing the Special Act on Prevention of Insurance Fraud. However, the size of insurance fraud is increasing due to intelligent and organized insurance scammers. In order to respond to insurance fraud, the vehicle driving information prior to a collision must be objectively verified by the vehicle accident analyst. EDR is one of the functions of ACU to record the event data when crash occurred. EDR data should be verified whether the data is recorded from the specified situation by using PDOF result, airbag deployment status and ignition cycle. In this study, one of the vehicle insurance fraud case was covered. In that accident case, the driver claimed that the vehicle could not be operated due to out of control. In the EDR data, the driver did not manipulate the vehicle event data though it was in a dangerous situation. So, when the EDR data was recorded and could be download from a damaged vehicle, the driver's operation information can be verified.

Self-starting process monitoring based on transfer learning

Conventional self-starting control schemes can perform poorly when monitoring processes with early shifts, being limited by the number of historical observations sampled. In real applications, pre-observed data sets from other production lines are always available, prompting us to propose a scheme that monitors the target process using historical data obtained from other sources. The methodology of self-taught clustering from unsupervised transfer learning is revised to transfer knowledge from previous observations and improve out-of-control (OC) performance, especially for processes with early shifts. However, if the difference in distribution between the target process and the pre-observed data set is large, our scheme may not be the best. Simulation results and two illustrative examples demonstrate the superiority of the proposed scheme.

Reliable Post-Signal Fault Diagnosis for Correlated High-Dimensional Data Streams

Rapid advance of sensor technology is facilitating the collection of high-dimensional data streams (HDS). Apart from real-time detection of potential out-of-control (OC) patterns, post-signal fault diagnosis of HDS is becoming increasingly important in the filed of statistical process control to isolate abnormal data streams. The major limitations of the existing methods on that topic include (i) they cannot achieve reliable diagnostic results in the sense that their performance is highly variable, and (ii) the informative correlation among different streams is often neglected by them. This article elaborates the problem of reliable fault diagnosis for monitoring correlated HDS using the large-scale multiple testing. Under the framework of hidden Markov model dependence, new diagnostic procedures are proposed, which can control the missed discovery exceedance (MDX) at a desired level. Extensive numerical studies along with some theoretical results show that the proposed procedures can control MDX properly, leading to diagnostics with high reliability and efficiency. Also, their diagnostic performance can be improved significantly by exploiting the dependence among different data streams, which is especially appealing in practice for identifying clustered OC streams.