Dans un contexte où la consommation de viande bovine est en constante diminution, en partie à cause de sa composition lipidique, il apparaît important pour l'ensemble de la filière de pouvoir communiquer sur l’intérêt nutritionnel de cette viande et plus particulièrement sur sa composition en acides gras (AG). Pour que cette communication soit « efficiente » à tous les niveaux de la filière, il faut disposer de moyens analytiques fiables mais aussi faciles de mise en œuvre et de surcroît peu coûteux. La méthode analytique que nous avons choisi de tester est la spectrométrie proche infrarouge (SPIR) qui présente l’avantage d’être peu coûteuse, peu invasive et qui pourrait ainsi être utilisée à grande échelle et en routine en abattoir. Nous avons montré que la SPIR est performante pour déterminer les teneurs en AG saturés (AGS) et monoinsaturés (AGMI) (R2>0,9). Dans les meilleures conditions pour la prédiction des AGPI (échantillons comportant des teneurs élevées en AGPI et/ou une grande variabilité), les performances de prédiction restent encore insuffisantes (R2 <0,75). Pour pallier cette faiblesse de la SPIR, des équations de prédiction indirectes des AGPI ont été mises en place à partir des teneurs en AGS et AGMI, teneurs correctement déterminées par SPIR, et les informations disponibles en abattoir. Ces équations élaborées par régression linéaire multiple ont permis de prédire correctement les AGPI totaux et les AGPI n-6 (R2 >0,8). Elles restent perfectibles pour la détermination des AGPI n-3 totaux (R2=0,64) mais surtout pour le 18:3 n-3, le 20:5 n-3 et le 22:6 n-3 (R2 <0,55). L’objectif final de ce travail étant d'utiliser les équations en complément des mesures réalisées par SPIR à des fins industrielles afin de déterminer rapidement la composition en AG de la viande bovine, des études complémentaires seront nécessaires pour tester l'ensemble de notre démarche associant SPIR et équations de prédiction. / In a context where the consumption of beef is declining in part because of its lipid composition, an opportunity to revive the beef industry is to communicate with consumers on nutritional quality of beef, especially its fatty acids (FA) composition. To ensure this communication is “efficient” at all levels of the industry, we must have reliable analytical resources but also easy to implement and also inexpensive. The analytical method proposed for determining the beef FA composition is the near-infrared spectroscopy (NIRS) which is inexpensive, minimally invasive and could thus be widely used in routine in slaughterhouse. We showed that NIRS was effective to determine the concentrations of saturated (SFA) and monounsaturated (MUFA) FA (R2> 0.9). Under the best conditions for the prediction of PUFA (samples containing high levels of PUFA and / or with a high variability), PUFA predictions were still not enough (R2 <0.75). So, to overcome this weakness of NIRS, indirect prediction equations of PUFA were performed from the SFA and MUFA contents correctly determined by NIRS and information available in slaughterhouses. These equations, developed by multiple linear regression, were used to correctly predict total and n-6 PUFA (R2> 0.8). These equations are still to be improved for the determination of the total n-3 PUFA (R2 = 0.64) and of the 18:3 n-3, the 20:5 n-3 and the 22:6 n-3 (R2 <0.55). Given that the ultimate aim of this research is to use the equations as a complementary tool in tandem with NIRS measurements to serve industry as a way to rapidly determine the FA content of beef, further studies will be needed to trial and test our novel coupled NIRS–prediction equations approach.

Higher order modes (HOM) are electromagnetic resonant fields. They can be excited by an electron beam entering an accelerating cavity, and constitute a component of the wakefield. This wakefield has the potential to dilute the beam quality and, in the worst case, result in a beam-break-up instability. It is therefore important to ensure that these fields are well suppressed by extracting energy through special couplers. In addition, the effect of the transverse wakefield can be reduced by aligning the beam on the cavity axis. This is due to their strength depending on the transverse offset of the excitation beam. For suitably small offsets the dominant components of the transverse wakefield are dipole modes, with a linear dependence on the transverse offset of the excitation bunch. This fact enables the transverse beam position inside the cavity to be determined by measuring the dipole modes extracted from the couplers, similar to a cavity beam position monitor (BPM), but requires no additional vacuum instrumentation.At the FLASH facility in DESY, 1.3 GHz (known as TESLA) and 3.9 GHz (third harmonic) cavities are installed. Wakefields in 3.9 GHz cavities are significantly larger than in the 1.3 GHz cavities. It is therefore important to mitigate the adverse effects of HOMs to the beam by aligning the beam on the electric axis of the cavities. This alignment requires an accurate beam position diagnostics inside the 3.9 GHz cavities. It is this aspect that is focused on in this thesis. Although the principle of beam diagnostics with HOM has been demonstrated on 1.3 GHz cavities, the realization in 3.9 GHz cavities is considerably more challenging. This is due to the dense HOM spectrum and the relatively strong coupling of most HOMs amongst the four cavities in the third harmonic cryo-module. A comprehensive series of simulations and HOM spectra measurements have been performed in order to study the modal band structure of the 3.9 GHz cavities. The dependencies of various dipole modes on the offset of the excitation beam were subsequently studied using a spectrum analyzer. Various data analysis methods were used: modal identification, direct linear regression, singular value decomposition and k-means clustering. These studies lead to three modal options promising for beam position diagnostics, upon which a set of test electronics has been built. The experiments with these electronics suggest a resolution of 50 micron accuracy in predicting local beam position in the cavity and a global resolution of 20 micron over the complete module. This constitutes the first demonstration of HOM-based beam diagnostics in a third harmonic 3.9 GHz superconducting cavity module. These studies have finalized the design of the online HOM-BPM for 3.9 GHz cavities at FLASH.

The aim of this work was to present the issue of neural network, which is still, despite the fact it exist and has been applied for several years, remains quite unknown for a considerably big part of public and academical environment. The aim of the practical part was to verify via practical application if neural network are truly a better instrument of statistical analysis, than the commonly used ones, especially when the goal is to analyze and describe complex processes and relationships between them. Further aim of the work was to investigate and describe the relationships between the development of trading volumes of Apple shares and the shares of competitive companies regarding the market of smart phones such as Google, HTC, Nokia, Samsung using neural network models. The attainment of these goals was realized through a rather extensive description of neural networks theory as well as the presentation of valuable theoretical tools for avoiding the frequent barriers occurring during the practical implementation. This practical application was realized via software called R, which has widely spread lately due to its availability and a vast range of flexibility, which is provided to users. The value of this work is familiarization and the creation of an integrated knowledge within readers about the issue of neural networks and the deliverance of a proof, that neural networks are indeed a better tool compared to the commonly used ones (ARMA models, linear regression). The author of the work gained a lot of useful knowledge about neural networks, learned how to use them in practice especially in the environment of R software, by which he shifted his proficiency with the current software to a whole new level.

Text in English / Scrum is the most adopted and under-researched Agile methodology. The research conducted on Scrum adoption is mainly qualitative. Therefore, there was a need for a quantitative study to investigate Scrum adoption challenges. The general objective of this study was to investigate the factors that have a significant relationship with Scrum adoption as perceived by Scrum practitioners working within South African organisations. To achieve this objective a narrative review to synthesise the existing challenges was conducted, followed by the use of these challenges in the development of a conceptual framework. After that, a survey questionnaire was used to test and evaluate the developed framework. The research findings indicate that relative advantage, complexity, and sprint management are factors that have a significant linear relationship with Scrum adoption. The findings are generalisable to the population, and the author recommends that organisations review the findings during their adoption phase of Scrum. / Council for Scientific and Industrial Research (CSIR) / University of South Africa (UNISA) / School of Computing / M.Sc. (Computing)

<p>In the field of the construction industry, the research work has been widely focused on identifying key performance indicators and critical success factors without assessing the impact of conflict environment factors. This study focusses on the impact of post-conflict environment factors on local construction organization performance. This research presents a performance prediction model comprising the effect of post-conflict environment factors on construction organization performance. The proposed framework of this study has four stages: identify key performance indicators (KPIs), identify post-conflict environment impacting factors, determine critical success factors (CSFs), and formulate success strategy to improve performance. Analytical hierarchy process (AHP) and multiple linear regression (MLR) techniques are applied to analyze the data.</p> <p>The study finding indicates that there is a significant relationship between the post-conflict condition impacting factors and local construction organization performance, which is insufficiently studied in previous research work. Thus, the developed framework will benefit academic scholars and industry practitioners to analyze and evaluate challenges and opportunities caused by different external environment conditions in the post-conflict construction industry. </p>

Magister Commercii (Industrial Psychology) - MCom(IPS) / The present study investigated the relationship between the Sense Of Coherence and Satisfaction With Life amongst the unemployed. The study attempted to test the following hypotheses. 1. People with a high Sense Of Coherence tend to be satisfied with their lives in general. 2. Demographic variables such as age, gender, race and level of education have an influence on the subjects' scores on the Sense Of Coherence and Satisfaction With Life scales. 3. Length of unemployment has an impact on the subjects' Sense Of Coherence and Satisfaction With Life. In this study, subjects were drawn from the Department of Manpower in the Western Cape region. The data were obtained from a sample of 100 participants. Of this 100, 52 were males. Subjects were asked to complete the Sense Of Coherence and the Satisfaction With Life scales. Statistical procedures that were used are Multiple Linear Regression analysis, Product Moment Correlational Co-efficients, Analysis of Variance test (ANOVA) and the Cronbach Alphas of the various scales. It was found that Sense Of Coherence correlated significantly with Satisfaction With Life, thus supporting the first hypothesis. This led to the conclusion that a person with a strong Sense Of Coherence tends to be more satisfied with his/her life. However, a person with a weaker Sense Of Coherence finds it difficult to make sense out of his/her life. It was also found that most of the demographic variables did not reach any statistical significance. The general trend in this sample was that younger people had higher education and had been unemployed for fewer years. In comparison, older people were found to have less education and had been unemployed for more years. It was concluded that formal and informal education system will be necessary to develop and equip both young and older people with the experience and skills to use at work. This study was concluded by the discussion of the implications of the findings and suggestions for future research.

No description available.

El presente estudio tiene como objetivo identificar la calidad demandada, el precio internacional y el desarrollo agrícola como principales factores que favorecieron el crecimiento de las exportaciones peruanas de cacao tostado al mercado de los Estados Unidos de América en los años 2013 - 2020. Al iniciar la investigación, se presentó la hipótesis general de que la calidad demandada, el precio internacional y el desarrollo agrícola son factores que favorecieron el crecimiento de las exportaciones peruanas de cacao tostado al mercado de los Estados Unidos de América en los años 2013 - 2020.  Para comprobar la hipótesis y objetivos estructurados, se aplicó el modelo de análisis de regresión lineal múltiple, donde se pudo comprobar que la calidad demandada si cumplía con lo planteado. El precio internacional no cumple dado al valor agregado que presenta el cacao peruano, permitiendo vender por encima del precio base. Asimismo, se puede debatir el desarrollo agrícola, dado a que expertos y empresas afirman que la implementación de nuevas tecnologías y técnicas de cultivo permiten mayor producción de cacao; sin embargo, el análisis indica que no cumple con la data histórica analizada.  Finalmente, se puede concluir que el desarrollo agrícola permite un mejor desarrollo para la producción; sin embargo, el cacao presenta distintas versiones de exportación, tales como la manteca, licor, polvo, grano, etc. / The objective of this study is to identify the quality demanded, the international price and agricultural development as the main factors that favored the growth of Peruvian exports of roasted cocoa to the United States of America market in the years 2013-2020. At the beginning of the investigation, the general hypothesis was presented that the quality demanded, the international price and agricultural development are factors that favored the growth of Peruvian exports of roasted cocoa to the market of the United States of America in the years 2013 - 2020. To verify the hypothesis and structured objectives, the multiple regression analysis model was applied, where it was possible to verify that the quality demanded did comply with what was proposed. The international price does not comply given the added value that Peruvian cocoa presents, allowing it to be sold above the base price. Likewise, agricultural development can be debated, given that experts and companies affirm that the implementation of new technologies and cultivation techniques allow greater cocoa production; however, the analysis indicates that it does not comply with the historical data analyzed. Finally, it can be concluded that agricultural development allows better development for production; However, cocoa presents different versions for export, such as butter, liquor, powder, grain, etc. / Tesis

El presente proyecto de investigación es un análisis desde la perspectiva de negocios y estadístico de la empresa Agrokasa. El objetivo principal es encontrar nuevos mercados alternativos en crecimiento que le permitan obtener una mejor rentabilidad por el precio de kilo exportado de palta. Para alcanzar lo mencionado, se llevó a cabo un análisis empresarial que nos permita comprender el contexto y rubro de la empresa. Una vez alcanzado ese objetivo, se aplicó la metodología de la ciencia de datos para encontrar países de destino que son atractivos para Agrokasa. En cuanto al conjunto de datos, se obtuvo de diferentes fuentes públicas y privadas como Veritrade, Trade Map y Adex Data Trade. En consecuencia, se logró identificar 03 mercados alternativos y potenciales, tales como, Rusia, China y Corea Del Sur. En el análisis se utilizaron diferentes herramientas tecnológicas para la compilación, depuración, procesamiento y visualización de los datos, tales como Excel, Power Bi y Python. Con lo cual se demostró la importancia de ver todas las variables en una visualización que nos permite entender el comportamiento de los datos y nos sirve como fundamento para la toma de decisiones. En cuanto a los nuevos mercados, China presento el mayor valor total FOB exportado en el periodo analizado, 2018 -2020. Pese a presentar una tendencia negativa en la Regresión Lineal. Sin embargo, el precio promedio por kilo de palta aun es conveniente. Por otro lado, Rusia fue el mercado con mayores perspectivas de crecimiento y Corea Del Sur con un mejor precio por KG. Finalmente, para todos los mercados se utilizó una técnica de ciencia de datos con aprendizaje supervisado con un enfoque predictivo para pronosticar las importaciones de cada uno de ellos a fin de establecer estrategias comerciales para penetrar en ellos. / This paper is an analysis from a business and statistical perspective of the Agrokasa company in order to find new potential markets that allow it to grow in the volume of its avocado exports and in profitability per Kg exported. To achieve the aforementioned, a previous analysis from a business approach has been used, to understand the context and business area. Once this is understood, the methodology of data science has been applied to find destination countries that are attractive to Agrokasa. The data set was obtained from different public and private sources such as Veritrade and Trademap, with which it was possible to identify 03 potential markets that were China, Russia and South Korea. In the analysis, different technological tools were used to compile, debug, process and visualize the data, such as Excel, Power Bi and Python. With which it was demonstrated the importance of seeing all the variables in a visualization that allows us to understand the behavior of the data and serves as a basis for decision-making. China was the market with the highest total FOB value exported in the analyzed period, which was from 2018 -2020, however, with a negative trend, but with a convenient average price. On the other hand, Russia was the market with the best growth prospects and South Korea with a better price per KG. ​Finally, for all markets, a data science technique with supervised learning with a predictive approach was used to forecast the imports of each of them in order to establish commercial strategies to penetrate them. / Trabajo de investigación

This thesis deals with processing of real data regarding waste collection. It describes select parts of the fields of statistical tests, identification of outliers, correlation analysis and linear regression. This theoretical basis is applied through the programming language Python to process the data into a form suitable for creating linear models. Final models explain between 70 \% and 85 \% variability. Finally, the information obtained through this analysis is used to specify recommendations for the waste management company.