In Wideband DS-CDMA system, increasing the utilization of Orthogonal Variable Spreading Factor (OVSF) code tree can serve more users. As Dynamic Code Assignment (DCA) does, the allocated codes will be reassigned when a new call can¡¦t be served even if the capacity is enough. However, reassigning occupied codes is expensive. In this thesis, we have proposed a state classification code assignment principle and a proportional reservation policy. In the proposed algorithm, the OVSF code tree is classified into four states. Then, the system will decide whether to reassign codes or not by checking the current state of the tree. In other words, the occupied codes will be reallocated in an appropriate occasion. Besides, we reserve vacant and available codes corresponding to the probability of requests for each supported rate when reassignment occurs. Therefore, the reassignment is reduced. It is also proved on the basis of the property of Markov Chain. Taking advantage of the proposed states classification code assignment and the policy of proportional code reservation, the call blocking rate and the number of reassignment can be reduced.

In this dissertation, we present mathematical analyses for a cellular CDMA communication system by investigating two important performance factors, the spreading code reservation periods and the cell coverage in soft handoff. First, an innovative code assignment scheme is presented by fully utilizing the characteristics of voice and data traffic. In other words, a voice terminal has higher priority to reserve a spreading code to transmit packets in multiple talk spurts, while a data terminal can only transmit packets by either employing the unassigned codes or borrowing the codes from the voice terminals during their silent periods. The code assignment scheme is then extended to analyze a priority-based CDMA system where the code reservation periods can be varied. Two performance measures, the average dropping probability for delay-sensitive traffic and the average packet delay for delay-insensitive traffic, are derived from the analytic models based on the equilibrium point analysis (EPA). Finally, for the cellular CDMA system, we study the influences of enlarging or shrinking the soft handoff coverage on the new-call blocking and the handoff-call dropping probabilities. From the mathematical analyses, we reveal that enlarging the outer cell while fixing the inner cell may significantly increase both blocking and dropping probabilities. On the other hand, if we enlarge the inner cell and fix the outer cell, the two probabilities can be reduced slightly. The impact of activating a call admission control on the proposed cellular CDMA system is also discussed.

This research investigated the efficient utilization of wireless bandwidth in Code Division Multiple Access (CDMA)systems that support multiple data rates with Orthogonal Variable Spreading Factor (OVSF)codes. The specific problem being addressed was that currently proposed public-domain algorithms for assigning OVSF codes make inefficient use of wireless bandwidth for bursty data traffic sources with different Quality of Service (QoS) requirements. The purpose of this research was to develop an algorithm for the assignment of OVSF spreading codes in a Third-Generation (3G)Wideband CDMA (WCDMA)system. The goal of this algorithm was to efficiently utilize limited, wireless resources for bursty data traffic sources with different QoS requirements. The key contribution of this research was the implementation and testing of two code sharing techniques which are not implemented in existing OVSF code assignment algorithms. These techniques were termed statistical multiplexing and dynamic code sharing. The statistical multiplexing technique used a shared channel to support multiple bursty traffic sources. The dynamic code sharing technique supported multiple data users by temporarily granting access to dedicated channels. These techniques differed in terms of both complexity and performance guarantees. / Ph. D.

Examiners of programming assignments in higher education and people in the software industry both need to test and review code. However, the assessing techniques used are often quite different. The IT industry often uses agile work methods like continuous integration and automated tests, while examiners either do manual assessments or rely on code grading tools. The students will most likely become developers and work using agile processes. Therefore, there are possible benefits of universities trying to imitate the work processes of the software industry. The purpose of this study was to develop a workflow for programming assignments inspired by continuous integration, Scrum, and GitLab flow. The workflow was developed based on the requirements of Linnaeus University and tested on one of their programming assignments. It showed that a simplified agile work process is suitable for programming assignments since the demonstration fulfilled all of the predefined requirements. However, examiners might miss some of the workflow’s benefits if the programming assignment can not be tested automatically since it will require more manual work while grading.

WCDMA是一個寬頻直接序列分碼多工存取(DS-CDMA)系統，使用正交可變展頻係數(Orthogonal Variable Spreading Factor，OVSF)碼以支援多樣化的資料傳輸速率，提供可變動位元速率和服務品質(Quality of Service，QoS)保障，以滿足使用者對多媒體應用服務的需求。在本研究中我們將訊務分群並配置符合的正交變數展頻係數碼的方式，來處理資源分配的問題，期讓每位使用者都能有滿意的服務品質。在論文中，為提供不同等級的差別服務以兼顧QoS和避免頻寬浪費，我們提出以動態群組配置的方式，從所有提出服務要求的訊務中，依其服務優先等級順序，挑選適合的訊務，將其放置於同一群組。系統會配置一OVSF碼給此群組，透過分時共用來進行資料傳輸，使其能提供多樣化的資料傳輸速率，減少碼阻斷，提高系統頻寬的使用率，並滿足使用者對服務品質的需求。實驗模擬顯示，本研究所提出的方法能提供多樣化的資料傳輸速率，並能有效減少碼阻斷，提高頻寬及系統使用率，並達到QoS的要求。 / WCDMA is a wideband Direct-Sequence Code Division Multiple Access (DS-CDMA) system, it uses Orthogonal Variable Spreading Factor (OVSF) codes to support diverse data transmission rates. Orthogonal variable spreading factor codes have the ability to provide variable bit rates and QoS to meet different multimedia application requirements. In this research, we group the traffic and use Orthogonal Variable Spreading Factor (OVSF) technique to deal with resource allocation problem in order to offer satisfactory quality of service to the users. We propose dynamic group allocation method to provide differentiated services in order to meet the QoS requirement and avoid bandwidth wasting. From all those requested services, we move all those services of the same service priority to the same group. The system will subsequently assign OVSF code to each group. Data transmission of each group is based on time-sharing mechanism. Simulations show that the proposed method can provide diverse data transmission rates, and is able to reduce code blocking rate, increase bandwidth and system utilization, and meet the QoS requirement.

Diagnosis code assignment is a field that looks at automatically assigning diagnosis codes to free-text clinical notes. Assigning a diagnosis code to clinical notes manually needs expertise and time. Being able to do this automatically makes getting structured data from free-text clinical notes in Electronic Health Records easier. Furthermore, it can also be used as decision support for clinicians where they can input their notes and get back diagnosis codes as a second opinion. This project investigates the effects of using the hierarchies the diagnosis codes are structured in when training the diagnosis code assignment models compared to models trained with a standard loss function, binary cross-entropy. This has been done by using the hierarchy of two systems of diagnosis codes, ICD-9 and SNOMED CT, where one hierarchy is more detailed than the other. The results showed that hierarchical training increased the recall of the models regardless of what hierarchy was used. The more detailed hierarchy, SNOMED CT, increased the recall more than what the use of the less detailed ICD-9 hierarchy did. However, when using the more detailed SNOMED CT hierarchy the precision of the models decreased while the differences in precision when using the ICD-9 hierarchy was not statistically significant. The increase in recall did not make up for the decrease in precision when training with the SNOMED CT hierarchy when looking at the F1-score that is the harmonic mean of the two metrics. The conclusions from these results are that using a more detailed hierarchy increased the recall of the model more than when using a less detailed hierarchy. However, the overall performance measured in F1-score decreased when using a more detailed hierarchy since the other metric, precision, decreased by more than what recall increased. The use of a less detailed hierarchy maintained its precision giving an increase in overall performance. / Diagnoskodstilldeling är ett fält som undersöker hur man automatiskt kan tilldela diagnoskoder till fri-text läkaranteckningar. En manuell tildeling kräver expertis och mycket tid. Förmågan att göra detta automatiskt förenklar utvinning av strukturerad data från fri-text läkaranteckningar i elektroniska patientjournaler. Det kan även användas som ett hjälpverktyg för läkare där de kan skriva in sina läkaranteckningar och få tillbaka diagnoskoder som en andra åsikt. Detta arbete undersöker effekterna av att ta användning av hierarkierna diagnoskoderna är strukturerade i när man tränar modeller för diagnoskodstilldelning jämfört med att träna modellerna med en vanlig loss-funktion. Det här kommer att göras genom att använda hierarkierna av två diagnoskod-system, SNOMED CT och ICD-9, där en av hierarkierna är mer detaljerad. Resultaten visade att hierarkisk träning ökade recall för modellerna med båda hierarkierna. Den mer detaljerade hierarkien, SNOMED CT, gav en högre ökning än vad träningen med ICD-9 gjorde. Trots detta minskade precision av modellen när man den tränades med SNOMED CT hierarkin medan skillnaderna i precision när man tränade hierarkiskt med ICD-9 jämfört med vanligt inte var statistiskt signifikanta. Ökningen i recall kompenserade inte för minskningen i precision när modellen tränades med SNOMED CT hierarkien som man kan see på F1-score vilket är det harmoniska medelvärdet av de recall och precision. Slutsatserna man kan dra från de här resultaten är att en mer detaljerad hierarki kommer att öka recall mer än en mindre detaljerad hierarki ökar recall. Trots detta kommer den totala prestandan, som mäts av F1-score, försämras med en mer detaljerad hierarki eftersom att recall minskar mer än vad precision ökar. En mindre detaljerad hierarki i träning kommer bibehålla precision så att dens totala prestandan förbättras.