A decision aid model for the selection of appropriate payment and pricing systems for construction projects

Abstract unavailable please refer to PD

Modelling the Inhomogeneities of the extragalactic background light

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science. August 2015.This work investigates the impact of the extragalactic background light fluctuations on very high energy !-ray spectra from distant blazars. We calculate the extragalactic background light spectral energy distribution using a model that extends those proposed by Razzaque et al. (2009ApJ.697.483R) and Finke et al. (2010ApJ.712.238F). We introduce a model for fluctuations in the extragalactic background light based on fluctuations in the star formation rate density, since these two fluctuations can reasonably be expected to be correlated. Fluctuations in the star formation rate are estimated from the semi-analytical galaxy catalogue of Guo et al. (2013MNRAS.428.1351G), we use his model to derive the resulting opacities for !-rays from distant sources. We determine the mean, lower and upper limits for the scatter of the star formation rate density, which then allow us to compute corresponding limits on the extragalactic background light spectrum. We then calculate the impact of these fluctuations limits on the !-ray optical depth. This appears to be the first detailed analytical model that aims to account for the impact of extragalactic background light fluctuations on the !-ray opacity. The model predicts relatively high variations ( 15%) on the opacity in the energy range less than 100 GeV for nearby sources. The impact is found to be smaller (⇠ 5%) for very high energy !-rays from distant sources

Prevalence of Pathogenic Vibrio SPP and Molecular Characterisation of Selected Vibrio Cholerae Serovars Isolated from Seafood in Malaysia

The global resurgence of cholera is an important public health challenge as the number of countries affected by this infection continues to increase. Cholera continues to be a major health challenge in Malaysia. To adequately control the infection requires a thorough understanding of its modes of transmission and implementing a comprehensive programme which takes into account not only the health aspect but also social, economic, behavioral and political dimension as well. The food-borne cholera and other pathogenic vibrios have not been thoroughly investigated in food in Malaysia. This study demonstrated the presence of toxigenic and non-toxigenic Vibrio cholerae 01, Vibrio cholerae 0139, Vibrio cholerae non-0l/0139 and other vibrios pathogenic to mankind, which were isolated from seafood marketed from wet-markets and supermarkets from different locations in Malaysia from July 1998 to June 1999. In this prevalence study, a total of 768 seafood samples were examined for the presence of pathogenic Vibrio species. A total of 431 of 768 (56.1%) seafood samples were contaminated with Vibrios. The frequencies of Vibrio contamination in seafood were: shrimp (Panaeus indicus) 58.6%, squids (Logio sp.) 44%, squids (Sepia sp. ) 60%, cockles (Anadara granosa) 82%, blue crabs (Callinectes sapiduy) 62%, Shellfish (Lithophaga ma/accana) 48% and peel mussels (Perna viridis) 24%. V. damsela and V. alginolyticus was the most frequently isolated species, followed by V. meschnikovii, V. jluvalis, V. parahaemolyticus, V. vulnijicus, V. cholerae and V. mimicus. Of the 433 shrimp samples examined, 35.5% (254/433) were found to be positive for Vibrio, which yielded 791 isolates of Vibrios. Thus, 68.2 (58/85), 62.2 (28/45), 88 (22/25), 96 (24/25), 25 (5/20) and 100% (48/48) of the samples obtained from Selayang, Kajang, Bangi in Selangor; Seremban in Negri Sembi Ian; Penang (North Peninsula Malaysia); and Kuching in Sarawak (on Borneo island) yielded 158, 74, 62, 68, 14, and 231 isolates of Vibrios, respectively. Examination of 185 shrimp samples from Serdang wet market in Selangor over a nine-month period gave a contamination rate of 37.2% with incidence for the months ranged from 15 to 40%

Learning Readiness Assessment Framework In Promoting E-Health Engagement Among Libyan Nurses

The use of e-health services by the Libyan government has become of high concern recently. This study focused on how the main factors or elements of working capacity in terms of structural environment, technological availability, and other competence-related issues may influence nurses’ engagement in e-health. Therefore, this research was established to build a learning readiness assessment framework (LRAF) for Libyan regional hospitals based on the adaptation of e-health services in nursing education. Penggunaan perkhidmatan e-Kesihatan oleh kerajaan Libya telah menerima perhatian yang tinggi kebelakangan ini. Kajian ini memfokuskan kepada cara faktorfaktor utama atau unsur-unsur keupayaan bekerja dari segi persekitaran struktural, ketersediaan teknologi, dan isu-isu lain yang berkaitan dengan kecekapan mempengaruhi penglibatan jururawat dalam penggunaan e-Kesihatan

Educational Department Web Site for Libya Embassy, Malaysia

The educational department of the Libyan embassy in Malaysia website playing major rule in different fields that explore and become important economic,commerce, military, health, education, diplomatic Etc.On the other hand many embassies in several countries facing difficulties in accessing organizing and collecting the data related to students specifically the register student in education department of the Libyan embassy in Malaysia, So I studied design website the educational department Libyan embassy in Malaysia,and is interested in opening a file for the student follow-up to the most important news of the educational department, to insert some data, File Number, Student Name, Libyan Address, Phone Number, Support Direction, Current Institution,Scientific Grade, Major, Start Study, End Study, Malaysian Address and Mail's Student,, also if there is any problem in the area of study a student can send a message to the educational department website or the consulted educational department e-mail for the consideration and resolution as soon as possible

Partial Open Source HVDC Control

High voltage direct current (HVDC) transmission, with the help of cutting-edge power electronic technological advancements, is envisioned to be the leading mode of transmission of electric power, superseding the traditional alternating current (AC) transmission. HVDC transmission allows for the transmission of large amounts of power over much longer distances in a more efficient and environmentally friendly way than AC transmission. Moreover, HVDC technology paves the way for the integration of renewable energy sources (RES) into the electric power grid. The main attractive feature possessed by HVDC systems that allows for the integration of RESs into the electric power grid is the ability to connect two unsynchronized AC networks. This allows for a seamless transition to renewable energy power generation as opposed to traditional generation methods. HVDC systems will inevitably be responsible for the expansion of power systems in a more controlled and stable way. When it comes to the design and implementation of HVDC systems, several factors must be taken into account; namely, the architecture of the HVDC system (point-to-point or multi-terminal networks), the converter technology (voltage source converter, line commutated converter, hybrid VSC-LCC, etc.), and the VSC converter topology (2-level, 3-level, or multi-level converter topology). The main focus of this thesis revolves around the converter controls. It has been seen in several commissioned HVDC projects that interoperability plays a massive role in the successful operation of multivendor HVDC systems. Moreover, in multivendor HVDC systems, the converter control software pertaining to each vendor is kept closed. This inaccessibility of vendor-specific converter information leads to inefficient methods of handling interoperability issues. This thesis aims to propose a partially open converter control software that is hypothesized to ease investigations into converter control interactions, interoperability, and system stability issues. Functional models of the control systems are designed with the help of the software Modelio using the systems engineering language known as SysML in order to provide a higher-level perspective of the system, aiding in the understanding and proper navigation of complex HVDC converter control elementsObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.b - Per a 2030, ampliar la infraestructura i millorar la tecnologia per tal d’oferir serveis d’energia moderns i sos­tenibles per a tots els països en desenvolupament, en particular els països menys avançats, els petits estats insulars en desenvolupament i els països en desenvolupament sense litoral, d’acord amb els programes de suport respectiu

Biological control of three grain storage pests: maize weevil, Sitophilus zeamais (Motschulsky), almond moth, Ephestia cautella (Walker) and cigarette beetle, Lasioderma serricorne (Fabricius), using novel strains of Beauveria bassiana (Balsamo) Vuillemin in powder formulation.

Doctor of Philosophy in Plant Pathology. University of KwaZulu-Natal, Pietermaritzburg, 2017.Abstract available in PDF file

Estimation of real traffic radiated emissions from electric vehicles in terms of the driving profile using neural networks

The increment of the use of electric vehicles leads to a worry about measuring its principal source of environmental pollution: electromagnetic emissions. Given the complexity of directly measuring vehicular radiated emissions in real traffic, the main contribution of this PhD thesis is to propose an indirect solution to estimate such type of vehicular emissions. Relating the on-road vehicular radiated emissions with the driving profile is a complicated task. This is because it is not possible to directly measure the vehicular radiated interferences in real traffic due to potential interferences from another electromagnetic wave sources. This thesis presents a microscopic artificial intelligence model based on neural networks to estimate real traffic radiated emissions of electric vehicles in terms of the driving dynamics. Instantaneous values of measured speed and calculated acceleration have been used to characterize the driving profile. Experimental electromagnetic interference tests have been carried out with a Vectrix electric motorcycle as well as Twizy electric cars in semi-anechoic chambers. Both the motorcycle and the car have been subjected to different urban and interurban driving profiles. Time Domain measurement methodology of electromagnetic radiated emissions has been adopted in this work to save the overall measurement time. The relationship between the magnetic radiated emissions of the Twizy and the corresponding speed has been very noticeable. Maximum magnetic field levels have been observed during high speed cruising in extra-urban driving and acceleration in urban environments. A comparative study of the prediction performance between various static and dynamic neural models has been introduced. The Multilayer Perceptron feedforward neural network trained with Extreme Learning Machines has achieved the best estimation results of magnetic radiated disturbances as function of instantaneous speed and acceleration. In this way, on-road magnetic radiated interferences from an electric vehicle equipped with a Global Positioning System can be estimated. This research line will allow quantify the pollutant electromagnetic emissions of electric vehicles and study new policies to preserve the environment

Estimation of real traffic radiated emissions from electric vehicles in terms of the driving profile using neural networks

The increment of the use of electric vehicles leads to a worry about measuring its principal source of environmental pollution: electromagnetic emissions. Given the complexity of directly measuring vehicular radiated emissions in real traffic, the main contribution of this PhD thesis is to propose an indirect solution to estimate such type of vehicular emissions. Relating the on-road vehicular radiated emissions with the driving profile is a complicated task. This is because it is not possible to directly measure the vehicular radiated interferences in real traffic due to potential interferences from another electromagnetic wave sources. This thesis presents a microscopic artificial intelligence model based on neural networks to estimate real traffic radiated emissions of electric vehicles in terms of the driving dynamics. Instantaneous values of measured speed and calculated acceleration have been used to characterize the driving profile. Experimental electromagnetic interference tests have been carried out with a Vectrix electric motorcycle as well as Twizy electric cars in semi-anechoic chambers. Both the motorcycle and the car have been subjected to different urban and interurban driving profiles. Time Domain measurement methodology of electromagnetic radiated emissions has been adopted in this work to save the overall measurement time. The relationship between the magnetic radiated emissions of the Twizy and the corresponding speed has been very noticeable. Maximum magnetic field levels have been observed during high speed cruising in extra-urban driving and acceleration in urban environments. A comparative study of the prediction performance between various static and dynamic neural models has been introduced. The Multilayer Perceptron feedforward neural network trained with Extreme Learning Machines has achieved the best estimation results of magnetic radiated disturbances as function of instantaneous speed and acceleration. In this way, on-road magnetic radiated interferences from an electric vehicle equipped with a Global Positioning System can be estimated. This research line will allow quantify the pollutant electromagnetic emissions of electric vehicles and study new policies to preserve the environment