The main aim of this research is to develop an on-line tool wear condition monitoring intelligent system for single-point turning operations. This is to provide accurate and reliable information on the different states of tool wear. Calibrated acoustic emission and vibration techniques were implemented to monitor the progress of wear on carbide tool tips. Previous research has shown that acoustic emission (AE) is sensitive to tool wear. However, AE, as a monitoring technique, is still not widely adopted by industry. This is because it is as yet impossible to achieve repeatable measurements of AE. The variability is due to inconsistent coupling of the sensor with structures and the fact that the tool structure may have different geometry and material property. Calibration is therefore required so that the extent of variability becomes quantifiable, and hence accounted for or removed altogether. Proper calibration needs a well-defined and repeatable AE source. In this research, various artificial sources were reviewed in order to assess their suitability as an AE calibration source for the single-point machining process. Two artificial sources were selected for studying in detail. These are an air jet and a pulsed laser; the former produces continuous-type AE and the latter burst type AE. Since the air jet source has a power spectrum resembling closely the AE produced from single-point machining and since it is readily available in a machine shop, not to mention its relative safety compared to laser, an air-jet source is a more appealing choice. The calibration procedure involves setting up an air jet at a fixed stand-off distance from the top rake of the tool tip, applying in sequence a set of increasing pressures and measuring the corresponding AE. It was found that the root-mean-square value of the AE obtained is linearly proportional to the pressure applied. Thus, irrespective of the layout of the sensor and AE source in a tool structure, AE can be expressed in terms of the common currency of 'pressure' using the calibration curve produced for that particular layout. Tool wear stages can then be defined in terms of the 'pressure' levels. In order to improve the robustness of the monitoring system, in addition to AE, vibration information is also used. In this case, the acceleration at the tool tip in the tangential and feed directions is measured. The coherence function between these two signals is then computed. The coherence is a function of the vibration frequency and has a value ranging from 0 to 1, corresponding to no correlation and full correlation respectively between the two acceleration signals. The coherence function method is an attempt to provide a solution, which is relatively insensitive to the dynamics and the process variables except tool wear. Three features were identified to be sensitive to tool wear and they are; AErms, and the coherence function of the acceleration at natural frequency (2.5-5.5 kHz) of the tool holder and at high frequency end (18-25kHz) respectively. A belief network, based on Bayes' rule, was created providing fusion of data from AE and vibration for tool wear classification. The conditional probabilities required for the belief network to operate were established from examples. These examples were presented to the belief network as a file of cases. The file contains the three features mentioned earlier, together with cutting conditions and the tool wear states. Half of the data in this file was used for training while the other half was used for testing the network. The performance of the network gave an overall classification error rate of 1.6 % with the WD acoustic emission sensor and an error rate of 4.9 % with the R30 acoustic emission sensor.

This thesis set out to meet the following aim and objectives: Aim: Examine cognition and personality of people who hold different types of supernatural belief. Objective 1: Create and validate a new scale to measure supernatural belief. Objective 2: Create and test a new model of supernatural belief based on cognition and personality. This would potentially test two hypotheses: the Cognitive Deficits Hypothesis and the Psychodynamics Functions Hypothesis. This was accomplished by conducting four studies. Studies one and two created and validated the new Belief in the Supernatural Scale (BitSS), a 44 item scale with the following five factors: ‘mental and psychic phenomena’, ‘religious belief’, ‘psychokinesis’, ‘supernatural entities’, and ‘common paranormal perceptions’. Cognition and personality would be looked at within the context of four different types of believer: ‘believers’, ‘paranormal believers’, ‘sceptics’ and ‘religious believers’. Study three revealed two profiles relating to cognition: ‘reflective thinkers’ and ‘intuitive believers’. The reflective profile was more likely to contain ‘sceptics’ and ‘believers’, and least likely to contain ‘paranormal believers’. The intuitive group was more likely to contain ‘religious believers’ and ‘believers’. The final study looked at personality alongside cognition and revealed ‘sensitive and abstract thinkers’ and ‘reflective metacognitive dogmatists’ profiles. The ‘sensitive and abstract thinkers’ were least likely to contain ‘sceptics’ and ‘religious believers’ and most likely to contain ‘believers’ and ‘paranormal believers’. The ‘reflective metacognitive dogmatists’ were most likely to contain ‘religious believers’ and ‘believers’ and least likely to contain ‘paranormal believers’. Following this analysis, Structural Equation Modelling was used to test seven different models of personality, cognition and belief. Studies one and two indicated a clear separation of religious and paranormal belief within the new scale, and that spiritual belief overlaps between the two. The scale developed was reliable and valid, and accurately reflected the concept of supernatural belief and enabled the measurement of religious and paranormal belief, where the overlaps were acknowledged whilst still being separate beliefs. Studies three and four found the ‘sceptics’ and ‘religious believers’ have remarkably similar profiles, indicating that the religious beliefs themselves may have been cognitively ring-fenced off in some way. The ‘paranormal believers’ however were not reflective thinkers and were not metacognitively active, indicating that they were not aware that they were not thinking critically or analytically. The Structural Equation Model showed that schizotypy was the main predictor of belief. The relationship between belief and cognition was more complex; it was dependent on what type of belief was active. Paranormal belief required a more intuitive thinking style to be present, whereas religious belief could withstand a reflective mind set. This thesis develops a new scale that measures supernatural belief provides a unique contribution to knowledge by establishing a model of cognition, personality and belief.

In managing organisations for optimal performance, managers are faced with the dilemma of either positioning their employees to compete or collaborate internally within the organisation. Internal competition can motivate individuals and teams to strive to be the best and in so doing result in continuous incremental performance improvements. In contrast, internal collaboration can result in effective problem solving through knowledge sharing and innovation. Management is therefore faced with a challenging dilemma of how best to leverage these seemingly opposing tensions for optimal performance. This study investigated the key factors that drive the adoption of internal competition and internal collaboration in organisations, the consequences of implementing either management approach, how levels of internal competition and internal collaboration vary at different management levels in the organisation and finally whether a viable hybrid combination of both management approaches was possible. To this end a qualitative research study with an explorative design was conducted with twenty senior executives. The insights from these in-depth interviews formed the basis of the data that was analysed to produce the research findings in this study. The research identified drivers and outcomes of the management approaches under review. The Internal Competition and Internal Collaboration Hybrid Model (Figure 14) emerged from these research findings. This model was found to confirm while the management approaches are different there is an optimal way of combining them to allow managers to leverage competitive and collaborative tensions. In this way managers can achieve sustainable high performance within their organisation. / Dissertation (MBA)--University of Pretoria, 2013. / lmgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

Human Immune Virus (HI)V /Acquired Immune Deficiency Syndrome (AIDS) has emerged as the most devastating epidemic that the world has experienced. Voluntary counselling and testing (VCT) has proven to be an effective way of preventing and controlling HIV. South African universities provide free VCT services on their campuses; however, these facilities are underused. The study’s objectives were to use the components of the health belief model (HBM) to explore and describe the factors that influenced the decision made by university students who have gone for VCT. The sample consisted of five male students. Data was collected through one-on-one in depth interviews, which were recorded. Data was analysed using thematic analysis, and the components of the HBM were used as codes for the data. Themes were generated for each component. The results indicated that perceived severity, perceived benefits and cues to action played a role in influencing the participants’ decision to go for VCT. In addition, results show that perceived susceptibility had little influence on their decision to go for VCT. Even though participants acknowledged barriers to VCT, they reported that the perceived benefits for VCT outweighed the barriers, and the decision to go for VCT was made. Participants suggested that to increase uptake of VCT on their campus, the university could improve current VCT campaigns, introduce rewards for VCT and introduce couples VCT.

This dissertation presents results of ethnographic study at a non-religious summer camp called Camp Quest Montana in the summer of 2011 and the numerous insights gained into the lived experiences of non-religious Americans. These particular Americans, because of their non-religion, have experienced unique pressures while navigating through life in a country that is and has been dominated by religious identification and belief. The ethnographic accounts gathered over the course of a week at Camp Quest Montana show how these non-religious people were using a language of belief, informed by a spirituality derived from science, as part of an effort to fit themselves into this wider and religiously steeped American culture. This dissertation argues that the Camp Questers express themselves through a language of “belief” because of the current and historical pressures to be religious, along with Americans’ tendency to distrust non-religious people. Using “belief” language allows them to talk about themselves in a way that makes sense to religious Americans, while also maintaining a non-religious identification. Moreover, this study found differences between how first and second-generation non-religious Americans (the parents and children at Camp Quest Montana) interact with religious Americans. These variations are important because they point to different experiences of the social and cultural landscape of the United States, differences that are reflected in each generation’s non-religious expression. This data also presents a challenge to current arguments regarding the benefits of religion to the socialization and overall well-being of youth.

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

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Indiana University-Purdue University Indianapolis (IUPUI) / This thesis discusses occupancy grid map, collision avoidance system and belief theory, and propose some of the latest and the most effective method such as predictive occupancy grid map, risk evaluation model and OGM role in the belief function theory with the approach of decision uncertainty according to the environment perception with the degree of belief in the driving command acceptability. Finally, how the proposed models mitigate or prevent the occurrence of the collision.

A collection of poems that explores notions of disability, family, and belief, with a preface that meditates on questions related to the ethical ramifications of various approaches to the making of poetry and art that takes up the suffering of others as subject matter.

Elevers inställning och uppfattning angående matematik kan påverka elevers självtilltro och ens matematiska förmåga. Syftet med studien är att beskriva synliggöra hur svenska elevers uppfattningar angående matematik ser ut, inom den svenska skolan.. Studien är inspirerad och bygger på en fenomenografisk ansats och empirin samlades in genom kvalitativa intervjuer med elever i årskurs två. Analysen av empirin utgick från en fenomenografisk analysmetod bestående av flera olika steg. Analysen har noggrant bearbetats för att få fram trovärdiga resultat. Resultatet av analysen visade att det finns flera olika uppfattningar angående matematik. Elever kan uppfatta matematik som räkneinnehåll, som vanligt förekommande fenomen i vardagen, som inre process samt som ett ämne man har känslor kring. Det går däremot inte att säkerhetsställa att alla möjliga uppfattningar av matematik har synliggjorts. Utifrån resultatet kan slutsatsen dras att yngre svenska elever i den svenska  yngre skolanåldern har olika sätt att uppfatta matematik. Det är viktigt att vi som lärare beaktar de yngre elevernas första möten med matematik, då det är avgörande för framtida attityder och uppfattningar.