Design rework includes unnecessary repetition in design tasks to correct design problems. Resolving design matters in advance, through in-depth understanding of the design planning and rework issues and development of effective predictive tools could contribute to higher business profit margins and a faster product time-to-market. This research aims to develop three novel and structured methods to predict the design rework occurrence and effort at the very early design stage, which may otherwise remain undiscovered until the testing and refinement phase. The major contribution obtained from the Design Rework Probability of Occurrence Estimation method, DRePOE, is the development of design rework drivers. The developed drivers have been synthesised with data from interview results, direct observations, and archival records obtained from eleven world-class aerospace and automotive components manufacturers. To predict the probability of occurrence, the individual score of each driver was compared against historical records utilising the analogy-based method. The Design Rework Effort Estimation method, DREE, was developed to interconnect functional structures and identify failure relationships among components. A significant contribution of The DREE method is its capability to assess the design rework effort at the component level under the worst-case scenario. Next a Prioritisation Design by Design Rework Effort Based method, PriDDREB, was developed to provide a tool to forecast the maximum design rework given the constraint. This method provides a tool to determine and prioritise the components that may require a significant design rework effort. The three methods developed were validated with an automotive water pump, a turbocharger, and a McPherson strut suspension system in accordance with the validation square method. It is demonstrated that DRePOE, DREE, PriDDREB methods can offer the product design team a means to predict the probability of design rework occurrence and assess the required effort during the testing and refinement phase at the very early design phase.

People and animals use various kinds of motion in a multitude of ways to communicate their ideas and affective states, such as their moods or emotions. Further, people attribute affect and personalities to movements of even abstract entities based solely on the style of their motions, e.g., movement of a geometric shape (how it moves about) can be interpreted as being shy, aggressive, etc. In this thesis, we investigated how flying robots can leverage this locomotion-style communication channel for communicating their states to people. One problem in leveraging this style of communication in robot design is that there are no guidelines, or tools that Human-Robot Interaction (HRI) designers can leverage to author affect communicating locomotion paths for flying robots. Therefore, we propose to adapt the Laban Effort System (LES), a standard method for interpreting human motion commonly used in the performing arts, to develop a set of guidelines that can be leveraged by HRI designers to author affective locomotion paths for flying robots. We further validate our proposed approach by conducting a small design workshop with a group of interaction designers, where they were asked to design robotic behaviors using our design method. We conclude this thesis with an original adaption of LES to the locomotion path of a flying robot, and a set of design guidelines that can be leveraged by interaction designers for building affective locomotion path for a flying robot.

Följande studie avser att undersöka relationen mellan engagemang, belöning och välbefinnande på arbetsplatsen. Siegrist (1996) förklarar sambandet genom Effort-Reward Imbalance model (ERI), något som denna studie kombinerar med Dieners (1986) teori om subjektivt välbefinnande. 156 personer deltog i enkätstudien, där 97 var kvinnor. Enkäterna var utformade med påståenden där deltagarna fick skatta sina svar. Datan analyserades genom en multipel regressionsanalys, korrelationer och t-test. I den multipla regressionen framkom det att hög insats/ låg belöning och överengagemang inte var signifikanta prediktorer utav variansen i subjektivt välbefinnande. Genom korrelationer kunde man utläsa att tre hypoteser visade signifikanta resultat, medan en hypotes inte visade något signifikant resultat genom stora t-test i avseende på huruvida kvinnor skattar högre nivå av överengagemang än män. Studien bidrog till en ökad förståelse för obalansen mellan hög insats/ låg belöning och överengagemang och dess betydelse för individens subjektiva välbefinnande.

People and animals use various kinds of motion in a multitude of ways to communicate their ideas and affective states, such as their moods or emotions. Further, people attribute affect and personalities to movements of even abstract entities based solely on the style of their motions, e.g., movement of a geometric shape (how it moves about) can be interpreted as being shy, aggressive, etc. In this thesis, we investigated how flying robots can leverage this locomotion-style communication channel for communicating their states to people. One problem in leveraging this style of communication in robot design is that there are no guidelines, or tools that Human-Robot Interaction (HRI) designers can leverage to author affect communicating locomotion paths for flying robots. Therefore, we propose to adapt the Laban Effort System (LES), a standard method for interpreting human motion commonly used in the performing arts, to develop a set of guidelines that can be leveraged by HRI designers to author affective locomotion paths for flying robots. We further validate our proposed approach by conducting a small design workshop with a group of interaction designers, where they were asked to design robotic behaviors using our design method. We conclude this thesis with an original adaption of LES to the locomotion path of a flying robot, and a set of design guidelines that can be leveraged by interaction designers for building affective locomotion path for a flying robot.

The motivation for this study is to understand the factors affecting police officers’ willingness to exert extra effort for providing better service through knowledge sharing in different working environments such as riots. Since managers’ leadership styles may be important factors affecting subordinates’ willingness to exert extra effort, this study investigates which of the leadership styles -- transformational, transactional or laissezfaire leadership -- will have a positive effect on officers’ willingness to exert extra effort. In addition, the current study also examines the effect of the mentioned leadership styles on knowledge sharing, which, in turn, affects the officers’ willingness to exert extra effort in the riot unit of the Turkish National Police (TNP) in Ankara, Turkey. The sworn line police officers working in the riot unit in Ankara, Turkey, were the participants in this study. Three questionnaires --a Multifactor Leadership (MLQ), knowledge sharing, and demographic questionnaire -- were arranged as a booklet to be distributed to the respondents. The results of the study indicate that police supervisors' perceived transformational leadership behavior has a positive effect on officers' willingness to exert extra effort. In addition, the findings also reveal that although both officers' years of service in TNP and police supervisors' perceived transactional leadership behavior has no direct effect on officers' willingness to exert extra effort, they have an indirect positive effect through officers' knowledge sharing. On the other hand, police supervisors' perceive that laissez-fair leadership behavior has no effect on riot officers' willingness to exert extra effort. The findings also indicate that officers’ knowledge sharing is positively related to both their supervisors’ perceived transformational and transactional leadership behaviors. However, police supervisors’ perceived laissez-fair leadership behavior has no effect on officers’ knowledge sharing activities. This research study will provide police administrations with the data necessary to adopt the most appropriate leadership styles for increasing police officers' knowledge sharing and extra effort. The findings will also serve as guidance for police managers commanding line police officers working in different environments, such as social movements, demonstrations, and riots. In that they will be aware of how important it is to create a knowledge sharing environment in riot units to provide better security in all legal and illegal demonstrations and riots. Finally, the findings will be a valuable resource not only for Turkish National Police, but also for future research studies and various police organizations in other countries.

The purpose of the study was to determine whether or not a variance in the quality of the public high school facilities existed among the Commonwealth of Virginia school divisions, since the 1982 Peccia study, An Analysis Of The Financing Of Public High School Capital Facilities In Virginia. Reasons for the variance in the quality of the public high school facilities, if any, were determined from an examination of a capital facilities survey instrument and various economic and financial characteristics. Methods and procedures used in the study included the capital facilities survey instrument, Crossman CAFIS. The Crossman CAFIS accurately reflected not just the number of facilities that existed in the school divisions but the quality of each facility. The researcher sent an electronic survey instrument to each high school principal within the sampled school divisions to rate their facilities using 75 indicators. The researcher visited all the high schools within the study in order to ensure the variance in how one perceives the differences in facilities would be limited. Any variance in the quality of the public high school facilities among the sampled school divisions were examined for economic factors that include; local composite index, fiscal effort and fiscal capacity. A significant finding of the study was that a large variance existed between the quality of high school facilities within the sampled school divisions, as measured by Crossman CAFIS. Reasons for that variance can be partially attributed to the fiscal effort of the sampled school divisions. School divisions that made a large fiscal effort and had a large fiscal capacity scored high on the Crossman CAFIS. School divisions that made a low fiscal effort and had low fiscal capacity, also scored low on the Crossman CAFIS. The lowest quality of high school facilities were found to be in the Western region of Virginia, despite isolated instances of high fiscal effort by some school divisions. Implications and recommendations were made in accordance with the findings of the study. A large variance existed in the Virginia school divisions between the quality of high school facilities as measured by CAFIS. The reason for the variance in high school facilities were due in part to the level of fiscal effort exerted by the school divisions. / EDD

Agtarap, Wright, Mlynski, Hammad, and Blackledge took an initial step in providing support for the predictive validity of a new conceptual analysis concerned with behavioral restraint - defined as active resistance against a behavioral impulse or urge. The current study was designed to partially replicate and extend findings from their study, employing a common film clip protocol and a procedure for inducing low- and high levels of fatigue. Analyses indicated that key cardiovascular (CV) responses rose with the evocativeness of the film clip among low fatigue participants but fell with the evocativeness of the film clip among high fatigue participants. This is consistent with the prediction that high fatigue participants would put forth more restrain intensity than low fatigue participants when confronted with the less evocative clip, but less restraint intensity than low fatigue participants when confronted with the more evocative clip. Behavioral restraint performance - quantified as duration of facial non-neutrality - was also consistent with predictions, being impaired by fatigue under high- but not low evocativeness conditions. Findings support the broad theoretical suggestion that fatigue influence on behavioral restraint is multifaceted, dependent on the perceived magnitude of the impulse or urge experienced and the importance of resisting it.

Thesis (Ed.D.)--Boston University / Discretionary effort (DE) is energy over which an individual has control, beyond that which is minimally required by the organization, expended pro-organizationally (to benefit the organization), consistent with organizational goals and requiring both a behavioral as well as a cognitive expenditure by the individual. The major question motivating this study was, "what relationships exist between DE and the previously established measures of organizational commitment (OC), psychological attachment (PA) and organizational citizenship behavior (OCB)?" A Discretionary Effort Scale (DES) was developed and integrated into a larger, 64-item Workplace Questionnaire (consisting of items from established measurement tools for OC, PA and OCB) and administered to 212 members of three business organizations (using both paper-and-pencil and electronic versions of the Questionnaire). Using principal components analyses, the original 15-item DES was reduced to a 10-item scale loading on two, key factors: In Role DE (IRDE) and Extra Role DE (ERDE). Analysis of results generally supported positive correlations between DE and OC, DE and PA, and DE and OCB. Analyses of relationships between IRDE (and ERDE) and specific components of the other dimensions (OC, PA, OCB) yielded pattems and results consistent with the nature of the constructs. The ve:ry early, rudimentary findings (1983) regarding levels of DE exhibited by workplace members were replicated in this study. The construct of DE does appear to merit further attention as one that may offer researchers and organizational managers opportunity for a better understanding of the relationship between organizational members and their organizations.

Background: Software Development Effort Estimation is a process that focuses on estimating the required effort to develop a software project with a minimal budget. Estimating effort includes interpretation of required manpower, resources, time and schedule. Project managers are responsible for estimating the required effort. A model that can predict software development effort efficiently comes in hand and acts as a decision support system for the project managers to enhance the precision in estimating effort. Therefore, the context of this study is to increase the efficiency in estimating software development effort. Objective: The main objective of this thesis is to identify an effective ensemble method to build and implement it, in estimating software development effort. Apart from this, parameter tuning is also implemented to improve the performance of the model. Finally, we compare the results of the developed model with the existing models. Method: In this thesis, we have adopted two research methods. Initially, a Literature Review was conducted to gain knowledge on the existing studies, machine learning techniques, datasets, ensemble methods that were previously used in estimating Software Development Effort. Then a controlled Experiment was conducted in order to build an ensemble model and to evaluate the performance of the ensemble model for determining if the developed model has a better performance when compared to the existing models.   Results: After conducting literature review and collecting evidence, we have decided to build and implement stacked generalization ensemble method in this thesis, with the help of individual machine learning techniques like Support vector regressor (SVR), K-Nearest Neighbors regressor (KNN), Decision Tree Regressor (DTR), Linear Regressor (LR), Multi-Layer Perceptron Regressor (MLP) Random Forest Regressor (RFR), Gradient Boosting Regressor (GBR), AdaBoost Regressor (ABR), XGBoost Regressor (XGB). Likewise, we have decided to implement Randomized Parameter Optimization and SelectKbest function to implement feature section. Datasets like COCOMO81, MAXWELL, ALBERCHT, DESHARNAIS were used. Results of the experiment show that the developed ensemble model performs at its best, for three out of four datasets. Conclusion: After evaluating and analyzing the results obtained, we can conclude that the developed model works well with the datasets that have continuous, numeric type of values. We can also conclude that the developed ensemble model outperforms other existing models when implemented with COCOMO81, MAXWELL, ALBERCHT datasets.

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