The purpose of this study is to measure and compare the degree of personal and social adjustment which high school girls exhibited during a "split semester" and a "continuous semester."

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This thesis deals with the design and implementation of a mobile application for BUT employees. The final application is written for Android and iOS in React Native. The goal is to facilitate the daily activities of an employee, which leads to more efficient work and reduced administration. The theoretical part deals with the selection of the most important modules in the information system based on statistical data and questionnaires. The implementation part contains the design of the user interface of selected modules and a description of the application implementation. The final application was tested by a group of employees and received a very good verbal evaluation.

The token economy is a widely used and versatile motivational system within applied behavior analysis. Moreover, token reinforcement procedures have been shown to be highly effective in the treatment of children with autism spectrum disorder (ASD). In the experimental analysis of behavior, token reinforcement contingencies are conceptualized as three interconnected schedule components: (1) the token-production schedule, (2) the exchange-production schedule, and (3) the token-exchange schedule. Basic work with nonhuman subjects has demonstrated that the exchange-production schedule is the primary driver of performance in these arrangements, and that variable-ratio exchange-production results in reduced pre-ratio pausing and greater overall rates of responding relative to fixed-ratio exchange-production schedules. However, little applied research has been conducted to assess the generality of these findings within applied settings. The purpose of this study was to determine if fixed- and variable-ratio token exchange-production schedules would exert differential effects on pre-ratio pausing and overall rates of responding for three children with ASD during a free-operant sorting task. The results showed that pre-ratio pausing and overall rates of responding were not differentially effected by the fixed- and variable-ratio exchange-production schedules. Discrepancies between the experimental work and the current study are discussed along with additional limitations.

Syfte: Det finns idag stor förbättringspotential i arbetet med logistik och tidplanering på byggarbetsplatser. Ökad komplexitet har lett till ökade krav på detta. Dock har det visats i studier att byggbranschen är en av de minst digitaliserade branscherna som finns, trots alla verktyg som finns. Syftet med studien är att undersöka fördelar med att använda sig av BIM i arbetet med logistik- och tidplanering jämfört med de traditionella metoder som finns, och på så sätt se hur detta arbete kan effektiviseras. Metod: De valda undersökningsmetoderna för att besvara våra frågeställningar är fallstudie samt litteraturstudie. Dessa metoder lämpar sig bäst för den typen av studie som ska utföras. Empirin är insamlad via intervjuer med anställda på Gärahovs Bygg AB. Resultat: Studien har visat att respondenterna tror att kommunikationen mellan olika aktörer i projektet, till exempel entreprenörer och underentreprenörer, kan förbättras med hjälp av den BIM-baserade metoden. De tror också att det blir lättare att se att allt tas med i planeringen i projekteringsskedet. Nyttan med att använda BIM: • BIM-metoden kan ge en visuell fördel i kommunikationen mellan entreprenörer och underentreprenörer. • BIM-metoden kan ge en tydligare bild av hur arbetet ska fortskrida genom visuella simuleringar. • BIM-metoden kan göra det lättare att i tidplaneringsskedet se om alla tänkta aktiviteter finns med i planeringen. • BIM-metoden kan göra det lättare att göra avstämningar mot tidplanen under projektets gång. Begränsningar: Begränsningar är att endast göra en tidplan över en typlägenhet i ett projekt, och gör jämförelser endast med denna. Studien har endast gjorts tillsammans med ett företag. För att få högre trovärdighet i resultatet behövs fler företag att jämföra med. En simulering av en större modell hade kunnat ge en ännu klarare bild av vilka fördelar och nackdelar som finns med BIM-metoden. / Purpose: Today there is big room for improvements in the work with logistics and scheduling on construction sites. Increased complexity has led to increased demands on planning. However, studies have shown that construction is one of the least digitalised industries today, in spite of all tools available. The purpose of the study is to study the advantages of using BIM in the work with logistics and scheduling compared to the traditional methods available, and in that way see how this increase efficiency. Method: The research methods that was chosen to answer our issue are case studies and literature studies. Those methods are the best suited for these types of studies that are going to be done. Collection of data has been made through qualitative interviews with employees at Gärahovs Bygg AB. Findings: The study has shown that the interviewees believe that communication between different participants in the project can be improved using the BIM-based method. They also believe that it will be easier to see that everything is included in the planning phase. The benefit of using BIM: • The BIM method can provide a visual advantage in the communication between contractors and subcontractors. • The BIM method can give a clearer picture of how the work will proceed through visual simulations. • The BIM method can make it easier to see if all the planned activities are included in the planning phase. • The BIM method can make it easier to make reconciliations against the schedule during the project. Limitations: The study is limited to only make a production schedule over one typeapartment in a project, and to only make comparisons with this. The study has only been made together with one company. For a more reliable result, more companies would have to be included in the study. A simulation of a larger model could have given an even clearer picture of what advantages and disadvantages that comes with the BIM-based method.

This study investigated the effects of an electronic visual activity schedule (eVAS; i.e., FIRST THEN Visual Schedule application) paired with the system of least prompts on the latency period and level of independence that a fifth-grade student with Intellectual Disability needed to transition throughout the day. Also investigated were the value that the teacher and student placed on the use of an eVAS to teach daily life and school routines instead of typical instruction (e.g., traditional visual schedule) and the student’s ability to generalize the use of the eVAS across instructors and materials (display). An ABAB single case design was used to investigate the effects of the eVAS app. Study research results indicated a functional relation between the use of the eVAS paired with the system of least prompts and the students correct responding and decreased latency. Limitations of the study and the suggestions for future research are discussed.

Improving the predictability of airline schedules in the National Airspace System (NAS) has been a constant endeavor, particularly as system delays grow with ever-increasing demand. Airline schedules need to be resistant to perturbations in the system including Ground Delay Programs (GDPs) and inclement weather. The strategic search heuristic proposed in this dissertation significantly improves airline schedule reliability by assigning airport departure and arrival slots to each flight in the schedule across a network of airports. This is performed using a multi-objective optimization approach that is primarily based on historical flight and taxi times but also includes certain airline, airport, and FAA priorities. The intent of this algorithm is to produce a more reliable, robust schedule that operates in today's environment as well as tomorrow's 4-Dimensional Trajectory Controlled system as described the FAA's Next Generation ATM system (NextGen). This novel airline schedule optimization approach is implemented using a multi-objective evolutionary algorithm which is capable of incorporating limited airport capacities. The core of the fitness function is an extensive database of historic operating times for flight and ground operations collected over a two year period based on ASDI and BTS data. Empirical distributions based on this data reflect the probability that flights encounter various flight and taxi times. The fitness function also adds the ability to define priorities for certain flights based on aircraft size, flight time, and airline usage. The algorithm is applied to airline schedules for two primary US airports: Chicago O'Hare and Atlanta Hartsfield-Jackson. The effects of this multi-objective schedule optimization are evaluated in a variety of scenarios including periods of high, medium, and low demand. The schedules generated by the optimization algorithm were evaluated using a simple queuing simulation model implemented in AnyLogic. The scenarios were simulated in AnyLogic using two basic setups: (1) using modes of flight and taxi times that reflect highly predictable 4-Dimensional Trajectory Control operations and (2) using full distributions of flight and taxi times reflecting current day operations. The simulation analysis showed significant improvements in reliability as measured by the mean square difference (MSD) of filed versus simulated flight arrival and departure times. Arrivals showed the most consistent improvements of up to 80% in on-time performance (OTP). Departures showed reduced overall improvements, particularly when the optimization was performed without the consideration of airport capacity. The 4-Dimensional Trajectory Control environment more than doubled the on-time performance of departures over the current day, more chaotic scenarios. This research shows that airline schedule reliability can be significantly improved over a network of airports using historical flight and taxi time data. It also provides for a mechanism to prioritize flights based on various airline, airport, and ATC goals. The algorithm is shown to work in today's environment as well as tomorrow's NextGen 4-Dimensional Trajectory Control setup.

Smart metering and precise measurement of energy consumption levels have brought more detailed information and interest on the actual load profile of a house which continues to improve consumer-retailer relationships. Participation in demand response (DR) programs is one of these relationships but studies have shown that there are considerable impacts resulting to some level of discomfort on consumers as they aim to follow a suggested load profile. This research therefore investigates the impact on consumers while participating in DR programs by evaluating various perspectives that includes:  Modelling the causes discomfort during participation in DR programs;  Evaluation of user participation capabilities in DR programs;  Identification of schedulable and non-schedulable loads and opportunities;  Application of load scheduling mechanism which caters for specific user concerns.  Investigation towards ensuring a secure and robust system design. The key source of information that enhances this work is obtained from data on historical user behavior which can be stored within a smart controller installed in the home and optimised using genetic algorithm implemented on MATLAB. Results show that user participation in DR programs can be improved and effectively managed if the challenges facing home owners are adequately understood. This is the key contribution of this work whereby load schedules created are specifically tailored to meet the need of the users hence minimizing the impact of discomfort experienced due to participation in DR programs. Finally as part of the test for robustness of the system design in order to prevent or minimize the impact of any event of a successful cyber-attack on the load or price profiles, this work includes means to managing any such attacks thereby mitigating the impact of such attacks on users who participate in demand response programs. Solutions to these attacks are also proffered with the aim of increasing robustness of the grid by being sufficiently proactive.

The systems development life cycle (SDLC) has been the traditional method of decision support systems design. However, in the last decade several methodologies have been introduced to address the limitations arising in the use of the traditional method. These approaches include Courban's iterative design, Keen's adaptive design, prototyping and a number of mixed methodologies incorporating prototyping into the SDLC. Each of the previously established design methodologies has a number of differing characteristics that make each of them a more suitable strategy for certain environments. However, in some environments the current methodologies present certain limitations or unnecessary expenditures. These limitations suggest the need for an alternative methodology. This dissertation develops a new methodology, priority design, to meet this need. To determine what methodology would be most effective in a given situation, an analysis of the operating environment must be performed. Such issues as project complexity, project uncertainty, and limited user involvement must be addressed. This dissertation develops a set of guidelines to assist in this analysis. For clarity, the guidelines are applied to three, well-documented case studies. As an application of the priority design methodology, a decision support system for nurse scheduling is developed. The development of a useful DSS for nurse scheduling requires that projected staff requirements and issues of both coverage and differential assignment of personnel be addressed. / Ph. D.

Power limits on future high-performance computing (HPC) systems will constrain applications. However, HPC applications do not consume constant power over their lifetimes. Thus, applications assigned a fixed power bound may be forced to slow down during high-power computation phases, but may not consume their full power allocation during low-power I/O phases. This paper explores algorithms that leverage application semantics-phase frequency, duration and power needs-to shift unused power from applications in I/O phases to applications in computation phases, thus improving system-wide performance. We design novel techniques that include explicit staggering of applications to improve power shifting. Compared to executing without power shifting, our algorithms can improve average performance by up to 8% or improve performance of a single, high-priority application by up to 32%.