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Does safety make a difference? The impact of safety observations on injury likelihoods
Get PDFAccording to Liberty Mutual’s 2021 Workplace Safety Index, it was estimated that employers paid more than $1 billion per week in direct workers’ compensation costs for disabling, non-fatal workplace injuries in 2018 (2021 workplace, 2021). Accordingly, organizations frequently engage in safety practices in the hopes of reducing these financial and human costs. The aim of this study was to examine whether performing safety observations reduced the likelihood of adverse outcomes. A safety observation refers to a checklist of behaviors deemed “safe” that should be conducted to help decrease or completely eliminate a safety incident. A safety incident is an event that causes an injury to an employee. We obtained three years of safety data, which included the observation counts and incident counts, from a large chemical manufacturing company in the United States. Safety observations were normalized by work hours to ultimately reflect the total number of observations per an 8-hour shift. Safety incidents were dichotomized to indicate: did an incident occur (1) or an incident did not occur (0). A rolling sum time-series logistic regression analysis was performed to analyze whether observations over the previous seven days decreased the odds of an incident occurring over the next seven days. The logistic regression analyses were performed within two different work units: Division 1 (chemical manufacturer) and Division 2 (maintenance). These divisions engage in disparate yet similarly risky types of work, allowing us to examine the generalizability of results across multiple work units. Our results indicated that observations reported today (day 0) reduce the probability of an incident occurring over the next three days across Division 1 and Division 2. Specifically, the odds of an incident occurring over the next three days was reduced by 0.23 (odds ratio) and 0.14 respectively, per each additional observation performed. This could prevent three incidents for Division 1 and could result in 16 fewer incidents for Division 2 over a year. These results suggest that using safety observations to mitigate incident risk is possible and highly advantageous. Performing safety observations while engaging in dangerous work can reduce injuries in the workplace, saving not only lives, but also time, energy, effort, and money. However, to make this a consistent practice requires a very proactive safety culture, accurate and consistent safety reporting, and support from upper management
Corrosion assessment of biodegradable metal implants for orthopedic applications
Get PDFMagnesium alloys are the most promising materials to be used as biodegradable implants mainly due to their superior biocompatibility and lower specific density compared to other biodegradable metals (i.e., zinc and iron-based alloys). This study is investigating the effect of two different manufacturing methods and purity levels on the corrosion rates of a novel Mg-Zn-Ca-Mn-based alloy. Experimental in vitro corrosion tests were conducted on the biocompatible Mg-Zn-Ca-Mn-based alloy fabricated using conventional casting and hot rolling with low and high purity levels. The experimental research conducted, assessed the corrosion rates of the following Mg-1.2Zn-0.5Ca-0.5Mn-based alloys: Hot Rolled High Purity, As-Cast High Purity, As-Cast Low Purity, and Commercial Pure Magnesium. This was done using two testing methods, in vitro corrosion immersion testing and in vitro electrochemical testing. By doing so, the experiments aid in assessing how different purity levels or different manufacturing methods affect corrosion behavior. It was hypothesized that when comparing two magnesium-based alloys fabricated using different levels of purity, the high purity alloy would demonstrate a slower corrosion rate. Based on electrochemical testing and immersion testing, the hypothesis was proven to be true. It was also hypothesized that an alloy fabricated with a thermomechanical process would show slower corrosion rates than the as-cast ones. Based on electrochemical testing, this was proven to be false. Based on immersion testing, this was proven to be true, which provides more reliable data for corrosion rates. Data gathered aided in assessing corrosion rates of differently fabricated magnesium-based alloys. Further experiments should be conducted to determine the most desirable magnesium-based alloy fabrication
Beheaded: an alternate look into the life of England\u27s most notorious queen
Get PDFBeheaded: an alternate look into the life of England\u27s most notorious queen is a craft paper and accompanying novel chapters. The craft paper focuses on dialogue and its use in historical fiction to build both character and setting. The novel Beheaded is a historical fiction that focuses on Anne Boleyn, queen of England and second wife of Henry VIII. Anne served as queen from 1533 until her execution on May 19, 1536. She is one of the most notorious royal women in history, and she was never formally charged, witchcraft is one of the many claims laid against her during her trial. She was ultimately beheaded after she was found guilty of conspiracy against the king, however, rumors about her supernatural gifts lingered even after her death. This story reimagines Anne’s life as if she were a witch, while also showcasing her political successes and failures, emotional hardships, and her intense relationship with Henry
Battle of the Sexes: Similarities and Differences in Lay People’s Perceptions about Male and Female Sex Offenders
Get PDFThe aim of this research was to examine public perceptions about male and female sex offenders to help address gender disparities that exist in the justice system and society. Participants (N = 226) completed the revised Community Attitudes Towards Sex Offenders Scale (ATS; Harper & Hogue, 2015) and a questionnaire concerning opinions about female sex offenders. While there were no observed differences in perceptions between gender overall, differences emerged when examining only parents. Parents perceived male sex offenders worse than female sex offenders. This study also brings awareness to gender bias regarding male and female sex offenders. The implication of this study is that it helps inform the justice system perceptions of sex offenders which could bias potential jurors
The adaptation and innovation model of organizational resilience
Get PDFThe present study was designed to broaden the way researchers and practitioners of the organizational sciences conceptualize, measure, and ultimately work to improve the adaptability, innovativeness, and resilience of organizations. This involved identifying how to measure and delineate the relationships between the interlinked multilevel psychosocial constructs of organizational adaptability, innovativeness, and resilience and the individual and organizational level resources of personal resources, human capital, social capital, and job-related resources as components to a conceptual model of organizational effectiveness coined The Adaptation and Innovation Model of Organizational Resilience, or AIR model. A survey was developed and administered to operationalize worker perceptions of the presence of each of these constructs within their organization of work. The data generally supported the relatedness of the AIR model’s components and pointed towards the possibility of an indirect pathway between worker perceptions of their organization’s adaptability and their perceptions of its resilience
Documenting Religion in Chattanooga in 360-Degrees
No full textThis poster presentation consists of student-created 360-degree videos and audio interviews of Chattanooga-area religious communities, along with accompanying websites. The videos were recorded and edited by students over the Spring 2022 Honors College course “Religions Embodied and Virtual” during visits to local religious sites in Chattanooga. The project not only documented the area’s rich religious diversity but explored how communities have coped with the challenges brought by COVID-19
Application of Machine Learning and Deep Learning Approaches for Traffic Operation and Safety Assessment at Signalized Intersections
Get PDFThe exponential traffic growth hasn\u27t been well-handled by traditional control systems. Adaptive controls are necessary at signalized intersections since they foresee traffic demand based on AI approaches and make decisions ahead of time. These approaches also boost traffic safety by predicting near-crash events leveraging cutting-edge datasets like LiDAR. This thesis addresses such applications of machine learning and deep learning approaches using emerging traffic datasets. A novel deep learning model, MGCNN is suggested for short-term turning volume prediction using GRIDSMART data from the MLK corridor in Chattanooga, Tennessee. During assessments for 1-to-5-minute future prediction, MGCNN surpasses contemporary models with 0.9 MSE. Traditional machine learning models are applied efficiently for forecasting speed and arrival at green with 0.04 and 0.05 MSE. Convolutional Gated Recurrent Neural Network model is proposed for near-crashes prediction that shows 100% recall, precision, and F1-score: accurately predicting all near-crashes based on LiDAR data from Georgia intersection, MLK
Knowledge-based artificial neural network modeling assessment: integrating heterogeneous genomics data to uncover lifespan regulation
Get PDFBiological analytics and more advanced data analysis techniques have made remarkable advancements as the area of machine learning continues to grow. More specifically, genetic modeling and neural network building are gaining interest as it becomes a fundamental piece of most model building we see today. We propose a Knowledge-Based Artificial Neural Network (KBANN) to predict phenotype while providing insight to effected subsystems. Within KBANN, the input layers are a single or group of Gene Ontology (GO) terms while each layer’s input is a single number between 0 and 1, explaining how expressed the given term is. The expression number provides an average of the number of copies that a gene is producing at its current age compared to that over the average of its entire lifespan. Preliminary results show that KBANN model can potentially be used to predict lifespan phenotype using the Genotype-Tissue Expression data
Male rape myth - The role of gender role conformity in men\u27s perceptions of male rape
Get PDFPrior studies have examined connections between homophobia and rape myth acceptance. While homophobia has not been found to be a significant mediator, conformity to rigid male gender roles is theorized to correlate with rape myth acceptance, or victim blaming. The current study surveyed 60 men regarding rape myth acceptance and adherence to traditional male gender roles. Participants were also presented a scenario of man-on-man sexual assault. Data was analyzed to determine relationships between gender role conformity, victim/perpetrator sexual orientation, and victim blaming. Three hypotheses regarding association between rates of gender role conformity, the sexual orientations of perpetrator/victim and levels of victim blame are examined. Analysis revealed partial support and demonstrated a novel effect of perpetrator orientation on victim blaming
Novel parallel computing decoupling methods for power system distribution networks
Get PDFThis work presents and describes three strategies for decoupling distribution power networks among parallel processing cores in a real-time (RT) multi-core environment. The proposed techniques help remove computational limitations and speedup real-time simulation of networks. Prior to this work, the solutions employed include approaches such as decoupling with Stublines or delay-free State Space Nodal (SSN) solvers. Further, these approaches are limited to high-end proprietary hardware and software. The main issues addressed in this work are reducing computational complexity, storage complexity, and employing general-purpose computers to allow simulation of large power networks using RT-systems. The Compensated Distributed Line Decoupling (CDLD) method enhances the existing Stubline decoupling by improving its accuracy and transient response. In addition, CDLD combined with an SSN solver improves computational performance and removes bottleneck issues. The CDLD method was tested on three IEEE benchmark systems and resulted in significant improvement in the network response and computational performance compared to the Stubline method. When compared to SSN, mean computation time improved and overrun issues are removed. The combined SSN-CDLD method proved the most promising approach for network decoupling using dedicated high-end RT hardware and software. The second part of this work involved decoupling the power network into arbitrarily sized clusters, where each cluster was discretized using state-space equations. For each time-step, an approach following the published SSN method combined the individual clusters into a single nodal admittance matrix to resolve interfacing voltages at the nodes and use them for updating the clusters state-space equations. This method was programed and implemented on real-time general-purpose computers. The method was tested on two IEEE benchmark systems. The objective of this effort was to develop the SSN methodology for further investigations and make the capability available on none-dedicated hardware and software. Finally, a novel technique for decoupling the SSN nodal matrices that requires an approximation approach to resolve the complexity of the nodal admittance was developed. This technique allows distribution of computation effort to multiple cores and isolates the communications to interfaced cores only. The method was tested on an IEEE benchmark system and found to improve computational runtime complexity with acceptable accuracy