MPH / Department of Public Health / Post-apartheid South Africa’s healthcare system improved with many community members being able to easily access basic health care services. However, patient waiting time has remained a critical issue. Patients are well-known for arriving at healthcare facilities very early for the reason of avoiding lengthy queues. This, however, does not solve their problem. The purpose of the study was to explore factors influencing patient waiting time in Nthabiseng clinic in the Capricorn district of the Limpopo Province. The study was conducted at Nthabiseng clinic in the Capricorn District. A qualitative approach was adopted, and a sample was chosen from a targeted population through purposive sampling. Data were collected through a one-to-one semi-structured interview and analysed through the Thematic Data Analysis approach. The study found out that the Department of Health does not have a patient waiting time specific policy or legislative framework and/or a guiding document. It also showed that healthcare professionals define and calculate patient waiting time differently. Moreover, what is an acceptable waiting time to one is an unacceptable waiting time to another. The study recommended that a policy and Standard Operation Procedure be drafted to guide healthcare professionals on how to improve waiting time in their specific facilities.

The main objective of this paper is to utilizing the Shadow Moiré method to study the effect of IR-reflow Condition Variations on the warpage of PBGA Packages. Two combinations of different moisture and temperature status are also chosen for the purpose of the study. The result shows that the first peak temperature is the most effective variable on the warpage of PBGA packages under the IR-reflow process.

Consumers often have to wait during the process of acquiring and consuming many products and services. These waiting experiences are typically negative and have been known to affect customers¡¦ overall satisfaction with the product or service. To better manage these waiting experiences, many firms have instituted a variety of programs to reduce the actual duration of the wait. However, consumers are influenced by their perceptions of the waiting duration, not the actual one. Therefore, understanding how consumers perceive their waiting time is particularly important in the marketing of service. In this paper, I use laboratory experiment method and examine the impact of mood, distance to the goal state, and filled mechanism on consumers¡¦ perceptions of waiting time and their affective responses. A total of 206 students recruited at the university participated in the study. The results demonstrate that people in a positive mood tend to perceive shorter duration of the wait than those in a negative mood. Further, the distance to the goal state, i.e. the stage at which the delay occurs during the service encounter, has the impacts on consumers¡¦ time perception and affective responses. The delay produced longer time estimates and stronger affective responses at further from the goal state than at closer to the goal state. And filling time resulted in shorter time perception and less negative emotions. However, the relevance to the service of filled mechanism will not affect consumers¡¦ time estimates but only consumers¡¦ positive affective responses. The distance to the goal and different kind of filled mechanism have an interactive effect only on the time perceptions. Moreover, consumers¡¦ involvements toward service and time style have moderating effects. The higher the involvement, the longer the time estimates and the more negative responses. Qualitative subjects perceived longer waiting time, and quantitative ones have more positive affective responses.

The aim of this thesis is to first give a brief review of waiting line problems which often is a subject related to queueing theory. Simple counting processes such as the Poisson process and the duration of service time of each customer being exponentially distributed are often taught in a undergraduate or graduate stochastic process course. In this thesis, we will continue discussing such waiting line problems with priority assignment on each customer. This type of queueing processes are called priority queueing models. Patients requiring ER service are triaged and the order of providing service to patients more than often reflects early symptoms and complaints than final diagnoses. Triage systems used in hospitals vary from country to country and region to region. However, the goal of using a triage system is to ensure that the sickest patients are seen first. Such wait line system is much comparable to a priority queueing system in our study. The finite Markov chain imbedding technique is very effective in obtaining the waiting time distribution of runs and patterns. Applying this technique, we are able to obtain the probability distribution of customer wait time of priority queues. The results of this research can be applied directly when studying patient wait time of emergency medical service. Lengthy ER wait time issue often is studied from the view of limited spacing and complications in hospital administration and allocation of resources. In this thesis, we would like to study priority queueing systems by mathematical and probabilistic modeling.

The aim of this thesis is to first give a brief review of waiting line problems which often is a subject related to queueing theory. Simple counting processes such as the Poisson process and the duration of service time of each customer being exponentially distributed are often taught in a undergraduate or graduate stochastic process course. In this thesis, we will continue discussing such waiting line problems with priority assignment on each customer. This type of queueing processes are called priority queueing models. Patients requiring ER service are triaged and the order of providing service to patients more than often reflects early symptoms and complaints than final diagnoses. Triage systems used in hospitals vary from country to country and region to region. However, the goal of using a triage system is to ensure that the sickest patients are seen first. Such wait line system is much comparable to a priority queueing system in our study. The finite Markov chain imbedding technique is very effective in obtaining the waiting time distribution of runs and patterns. Applying this technique, we are able to obtain the probability distribution of customer wait time of priority queues. The results of this research can be applied directly when studying patient wait time of emergency medical service. Lengthy ER wait time issue often is studied from the view of limited spacing and complications in hospital administration and allocation of resources. In this thesis, we would like to study priority queueing systems by mathematical and probabilistic modeling.

Vehicular Ad-Hoc Network (VANET)s are a key element of Intelligent Transport System (ITS)s. One of the challenges in VANETs is dealing with awareness and congestion due to the high amount of messages received from the vehicles in communication range. As VANETs are used in critical applications, congestion on the receiver side caused by the buffering of the packets is a safety hazard. In this thesis, we propose a stream-wise queuing system on the receiver side and show how it improves the timeliness of the messages received and main- tains the awareness of the system in a congestion situation.

Consideremos uma sequência de lançamentos de moedas em que denotamos o resultado de cada lançamento por H, se der cara, ou por T, se der coroa. Formemos uma palavra apenas com H\'s e T\'s, por exemplo, HHHHH ou HTHTH. Quantas vezes arremessaremos uma mesma moeda ate que uma das duas palavras acima ocorrera? Por exemplo, dadas as sequências THTHHHHH e TTHTTHTHTH. O numero de vezes que arremessamos a moeda ate que HHHHH e HTHTH ocorreram pela primeira vez e oito e dez, respectivamente. Podemos generalizar a ideia acima para um numero finito de palavras em um alfabeto finito qualquer. Assim, o nosso principal objetivo dessa dissertação e encontrarmos a distribuição do tempo de espera ate que um membro de uma coleção finita de palavras seja observado em uma sequência de ensaios de Markov de letras de um alfabeto finito. Mais especificamente, as letras de um alfabeto finito são geradas por uma cadeia de Markov ate que uma das palavras de uma coleção finita ocorra. Além disso encontraremos a probabilidade de que determinada palavra ocorra antes das demais palavras pertencentes a um mesmo conjunto finito. Por ultimo encontraremos a função geradora de probabilidade do tempo de espera. / Consider a sequence of independent coin flips where we denote the result of any landing for H, if coming up head, or T, otherwise. Create patterns with H\'s and T\'s, for example, HHHHH or HTHTH. How many times do we have to land the same coin until one such two patterns happens? For example, let the sequences being THTHHHHH and TTHTTHTHTH. The number of times that we landed the coin until HHHHH and HTHTH happens it was eight and ten times respectively. We can generalize this idea for a finite number of patterns in any finite set. Then, the first of all interest of this dissertation is to find the distribution of the waiting time until a member of a finite colection of patterns is observed in a sequence of Markov chains of letters in from finite set. More specically the letters in a finite set are generated by Markov chain until one of the patterns in any finite set happens. Besides that, we will find the probability of a pattern happen before of all patterns in the same finite set. Finally we will find the generator function of probability of waiting time.

Chat rooms are of enormous interest to social network researchers as they are one of the most interactive internet areas. To understand the behaviour of users in a chat room, there have been studies on the analysis of the Response Waiting Time (RWT) based on traditional approaches of aggregating the network contacts. However, real social networks are dynamic and properties such as RWT change over time. Unfortunately, the traditional approach focuses only on static network and neglecting the temporal variation in RWT which may have lead to misrepresentation of the true nature of RWT. In order to determine the true nature of RWT, we analyse and compare the RWT of three online chat room logs (Walford, IRC and T-REX) putting into consideration the dynamic nature of RWT. Our research shows that the distribution of the RWT exhibits multi-scaling behaviour, which signi cantly a ects the current views on the nature of RWT. This is a shift from simple power-law distribution to a more complex pattern. The previous study on users RWT between pairs of people claims that the RWT has a power-law distribution with an exponent of 1. However, our research shows that multi-scaling behaviour and the exponent has a wider range of values which depend on the environment and time of day. The di erent exponents observed on di erent time scales suggest that the time context or environment has a signi cant in uence on users RWT. Furthermore, using the chat characterise, we predicted the factors which could minimize response waiting time and improving the friendship connection during online chat sessions. We apply our ndings to design an algorithm for chat thread detection. Here, we proposed two variations of cluster algorithm. The rst algorithm involves the traditional approach while in the second one, the temporal variations in RWT was taken into consideration to capture the dynamic nature of a text stream. An advantage of our proposed method over the previous models is that previous models have involved highly computationally intensive methods and often lead to deterioration in the accuracy of the result whereas our proposed approach uses a simple and effective sequential thread detection method, which is less computationally intensive.

In a controlled lab experiment, we investigate hypothetical biases in the value of time by comparing stated preference (SP) and revealed preference (RP) values attached to unexpected waiting times. The SP and RP choice sets are identical in terms of design with the only difference being that the RP choices have real consequences in terms of unexpected waiting times and monetary incentives. We find a substantial hypothetical bias with the average SP value of time being only 71% of the corresponding RP value. The bias is mainly driven by participants who have scheduling constraints during the time of the unexpected wait. Scheduling constraints are taken into account to a much lesser extent in the SP setting than in the RP setting, presumably because only in the latter, the consequences of ignoring them are costly. We find evidence that this effect is stronger for persons with relatively low cognitive ability.

<p>The aim of the study was to measure patient waiting and service times, describe the causes of high waiting time as well as to determine staff and patient derived norms on waiting times at the Manzini Regional Hospital HIV Clinic. Literature reviewed show that complaints regarding long waiting time have been effectively dealt with through patient flow analysis studies, which measure patient waiting and service times as well as other characteristics. A descriptive cross sectional quantitative survey methodology was undertaken using a time-delimited sample of all patients attending the HIV clinic over one week and all the staff who were in contact with the patients. Waiting time tracking instruments and short questionnaires were used to collect data from both patients and staff. Data were analysed quantitatively.</p>