The challenges that military families face due to deployments can become very stressful. These changes directly impact at-home partners and children, changing the dynamic and routines of the entire family. The new roles and routines established can be conflicting for both partners, resulting in marital conflict and lower levels of satisfaction. In general, it has been found that the quality and frequency of communication are related to the quality of relationships. However, for deployed military families, engaging in frequent and good communication between couples can be challenging. This study will examine if quality and quantity of communication are related to the level of satisfaction in deployed military couples. Also, what method of communication is more likely to related to satisfaction will be explored.

Potreba dodania hodnoty uživatelom každodočne rastie na kompetitívnom trhu IT. Agilita a DevOps sa stávajú kritickými aspektami pre vývoj software, vyhľadávajúci nástroje ktoré podporujú agilnú kultúru. Softwarové projekty v agilnej kultúre majú častú tendenciu zaoberať sa stratégiami nasadenia ktoré redukujú risk nasadenia nových zmien do existujúceho systému. A však, prostredia určené pre vývoj a testovanie sa takmer vždy odlišujú od produkčných. Využitie primeranej stratégie nasadenie ako canary zlepšuje celkovú stabilitu systému testovaním nových zmien na malej vzorke produkčnej prevádzky. Bolo vykonaných niekoľko experimentov pre dôkaz, že stratégia canary môže pozitívne ovplyvniť stabilitu nasadení a redukovať risk ktorý prinášajú nové zmeny.

While it is commonly known that combat-related posttraumatic stress disorder (PTSD) has profound, long-term effects on soldiers, its effects on spouses of affected soldiers are less understood. Some spouses who provide care for soldiers with PTSD develop symptoms that are similar in nature. These symptoms include but are not limited to depression, anxiety, isolation, hypervigilance, and a strong startle effect. This study explored the lived experiences of 8 spouses of Army Reservists who returned from deployment in either Iraq or Afghanistan with combat-related PTSD. This study used the couple adaptation to traumatic stress model to explore the couple's response to traumatic stress. The study also includes a discussion of the history of PTSD, including changes in criteria with the revisions of the Diagnostic and Statistical Manual of Mental Disorders (DSM), including the most recent change in the latest version (DSM 5). Although secondary traumatic stress is not recognized in the DSM 5, an increase in awareness may result in a better understanding of mental health needs within the military culture. The study consisted of 8 semi-structured interviews among 8 female spouses of Army Reserve soldiers, using Colaizzi's method of data analysis. The results of this study identified psychological distress in all participants in connection with relationship changes, psychological distress, and lack of available mental health services. The results of this study may assist mental health professionals understand that the mental health needs of spouses of Reservists often differ from those of active duty spouses. This study may support social change by promoting the need for additional training for counselors who work with this population.

Over 1.5 million U.S. soldiers have deployed oversees since the beginning of the War on Terror in 2001; consequently, spouses are faced with new physical, emotional, and psychological challenges. Many researchers have documented the effects of deployment on marriages and families. However, few researchers have explored the correlates of trust, marital commitment, and marital satisfaction for wives during deployment. This quantitative study, grounded in risk and resilience theory and interdependence theory, used a web-based survey to investigate the relationship between perceived likelihood of spousal infidelity, trust, marital commitment, and marital satisfaction in a sample of 127 military wives whose husbands were deployed oversees. The 'Events with Others' questionnaire, Dyadic Trust Scale, Commitment Inventory Revised, Kansas Marital Satisfaction Scale, and Revised Dyadic Adjustment Scale were used. Results indicated that length of deployment did not have a statistically significant impact on marital satisfaction. Bivariate correlation analysis indicated statistically significant relationships among wives' perceived likelihood of spousal infidelity, trust, marital commitment, and marital satisfaction. After controlling for wives' attachment style, marital commitment and trust were significant explanatory variables of marital satisfaction. The findings from this study can inform establishing effective programs to support military marriages during deployment. Such programs will promote social change by improving satisfaction, decreasing relationship conflicts, and reducing the rate of divorce. The Armed Forces may benefit from the results of this study by addressing marital commitment and trust issues prior to deployment, thereby supporting wives, husbands, and children during deployment.

Context: With the advent of Machine Learning (ML) and especially Deep Learning (DL) technology, companies are increasingly using Artificial Intelligence (AI) in systems, along with electronics and software. Nevertheless, the end-to-end process of developing, deploying and evolving ML and DL models in companies brings some challenges related to the design and scaling of these models. For example, access to and availability of data is often challenging, and activities such as collecting, cleaning, preprocessing, and storing data, as well as training, deploying and monitoring the model(s) are complex. Regardless of the level of expertise and/or access to data scientists, companies in all embedded systems domain struggle to build high-performing models due to a lack of established and systematic design methods and processes. Objective: The overall objective is to establish systematic and structured design methods and processes for the end-to-end process of developing, deploying and successfully evolving ML/DL models. Method: To achieve the objective, we conducted our research in close collaboration with companies in the embedded systems domain using different empirical research methods such as case study, action research and literature review. Results and Conclusions: This research provides six main results: First, it identifies the activities that companies undertake in parallel to develop, deploy and evolve ML/DL models, and the challenges associated with them. Second, it presents a conceptual framework for the continuous delivery of ML/DL models to accelerate AI-driven business in companies. Third, it presents a framework based on current literature to accelerate the end-to-end deployment process and advance knowledge on how to integrate, deploy and operationalize ML/DL models. Fourth, it develops a generic framework with five architectural alternatives for deploying ML/DL models at the edge. These architectural alternatives range from a centralized architecture that prioritizes (re)training in the cloud to a decentralized architecture that prioritizes (re)training at the edge. Fifth, it identifies key factors to help companies decide which architecture to choose for deploying ML/DL models. Finally, it explores how MLOps, as a practice that brings together data scientist teams and operations, ensures the continuous delivery and evolution of models. / <p>Due to copyright reasons, the articles are not included in the fulltext online</p>

Research suggests that using data driven solutions in policing strategies improves the quality of service provided by the police department. Unfortunately, many police departments, including the Denton Police Department, do not use their spatial data to inform beat zone placement. Analysis of the current beat zone configuration found that there are disparities in the workload, as measured by number of calls for service, between beat zones. Further, there was also a statistically significant difference between the median response times across all the five beat zones in Denton. This means that the median response time varies depending on where the call for service originates. Using readily available data, these police departments can apply methods such as UPAS to improve the quality of service provided by the department. UPAS is a deterministic algorithm that produces a given number of contiguous spatial partitions of approximately equal population size; in this case, calls for service are substituted for population. Although this algorithm was originally developed to create solutions for bio-terrorism response planning, it has been applied to the problem of creating beat zones of roughly equal workload in this research. I have shown that this algorithm results in a beat zone configuration that significantly reduces the difference in workload between the busiest and least busy beat zone (~94% reduction). Assuming an equal distribution of resources across beat zones, having approximately similar workloads should lead to fewer disparities in quality of service.

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A structured and disciplined Systems Engineering process is essential for the effective and efficient design and development of products and systems which are both responsive to customer needs and competitive in the global economy. The emphasis of this research is on the conceptual design phase of the Systems Engineering process. Conceptual system design is characterized by imprecision and vagueness. Designers make significant commitments to system-level design requirements and the system design concept in the face of this vagueness. Accordingly, the primary goal of this research is to develop an aid to facilitate the definition of system-level design requirements. During conceptual design, needs analysis and requirements definition is facilitated by the Quality Function Deployment (QFD) method. Quality Function Deployment is a design methodology chosen as the central focus of this research effort. Consistency within the QFD procedure must be maintained in order to accurately translate customer specified requirements into design requirements. This research, leading to the development of an expert system based advisor for system designers, is unique. A rule-based expert system was implemented to parse a completed QFD matrix and to identify occurrences of inconsistencies and strategic opportunities. / Master of Science