MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

The Application Of Renewable Energy For Prefab Houses In Germany

Within the framework of the REBUS project the German building industry has been investigated regarding their energy concepts. The intention was to evaluatethe establishment of renewable energy sources on the German market for new built houses and prefab houses in particular. For this purpose the products of 85manufacturers of prefab houses have been analyzed. Of special interest was the applicationof heating and hot water systems driven by solar energy and biomass. The results show that both techniques are well accepted and established. Almost 90% of themanufacturers offer solar systems on request and almost 70% heating systems based on Pellets. 24% offered solar and 7% as standard options in their range. From theachieved figures the potential of the Swedish market can be worked out. Strategies to introduce renewable energy to a greater extent to Swedish house manufacturers and builders might also be found.

System Integration of PV/T Collectors in Solar Cooling Systems

The demand for cooling and air-conditioning of building is increasingly ever growing. This increase is mostly due to population and economic growth in developing countries, and also desire for a higher quality of thermal comfort. Increase in the use of conventional cooling systems results in larger carbon footprint and more greenhouse gases considering their higher electricity consumption, and it occasionally creates peaks in electricity demand from power supply grid. Solar energy as a renewable energy source is an alternative to drive the cooling machines since the cooling load is generally high when solar radiation is high. This thesis examines the performance of PV/T solar collector manufactured by Solarus company in a solar cooling system for an office building in Dubai, New Delhi, Los Angeles and Cape Town. The study is carried out by analyzing climate data and the requirements for thermal comfort in office buildings. Cooling systems strongly depend on weather conditions and local climate. Cooling load of buildings depend on many parameters such as ambient temperature, indoor comfort temperature, solar gain to the building and internal gains including; number of occupant and electrical devices. The simulations were carried out by selecting a suitable thermally driven chiller and modeling it with PV/T solar collector in Polysun software. Fractional primary energy saving and solar fraction were introduced as key figures of the project to evaluate the performance of cooling system. Several parametric studies and simulations were determined according to PV/T aperture area and hot water storage tank volume. The fractional primary energy saving analysis revealed that thermally driven chillers, particularly adsorption chillers are not suitable to be utilizing in small size of solar cooling systems in hot and tropic climates such as Dubai and New Delhi. Adsorption chillers require more thermal energy to meet the cooling load in hot and dry climates. The adsorption chillers operate in their full capacity and in higher coefficient of performance when they run in a moderate climate since they can properly reject the exhaust heat. The simulation results also indicated that PV/T solar collector have higher efficiency in warmer climates, however it requires a larger size of PV/T collectors to supply the thermally driven chillers for providing cooling in hot climates. Therefore using an electrical chiller as backup gives much better results in terms of primary energy savings, since PV/T electrical production also can be used for backup electrical chiller in a net metering mechanism.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Assessing feasibility and acceptability of study procedures : getting ready for implementation of national stroke guidelines in out-patient health care

BACKGROUND: Even though Swedish national guidelines for stroke care (SNGSC) have been accessible for nearly a decade access to stroke rehabilitation in out-patient health care vary considerably. In order to aid future interventions studies for implementation of SNGSC, this study assessed the feasibility and acceptability of study procedures including analysis of the context in out-patient health care settings. METHODS: The feasibility and acceptability of recruitment, observations and interviews with managers, staff and patients were assessed, as well as the feasibility of surveying health care records. RESULTS: To identify patients from the the hospitals was feasible but not from out-patient care where a need to relieve clinical staff of the recruitment process was identified. Assessing adherence to guidelines and standardized evaluations of patient outcomes through health care records was found to be feasible and suitable assessment tools to evaluate patient outcome were identified. Interviews were found to be a feasible and acceptable tool to survey the context of the health care setting. CONCLUSION: In this feasibility study a variety of qualitative and quantitative data collection procedures and measures were tested. The results indicate what can be used as a set of feasible and acceptable data collection procedures and suitable measures for studying implementation of stroke guidelines in an out-patient health care context.

Methods and background characteristics of the TOHNN study : a population-based study of oral health conditions in northern Norway

OBJECTIVES: The aim of the Tromstannen - Oral Health in Northern Norway (TOHNN) study was to investigate oral health and dental-related diseases in an adult population. This article provides an overview of the background of the study and a description of the sample characteristics and methods employed in data collection. STUDY DESIGN: Cross-sectional population-based study including a questionnaire and clinical dental examination. METHODS: A randomly selected sample of 2,909 individuals (20-79 years old) drawn from the population register was invited to participate in the study. The data were collected between October 2013 and November 2014 in Troms County in northern Norway. The questionnaire focused on oral health-related behaviours and attitudes, oral health-related quality of life, sense of coherence, dental anxiety and symptoms from the temporomandibular joint. The dental examinations, including radiographs, were conducted by 11 dental teams in 5 dental offices. The examination comprised of registration of dental caries, full mouth periodontal status, temporomandibular disorders, mucosal lesions and height and weight. The participants were grouped by age (20-34, 35-49, 50-64 and 65-79) and ethnicity (Norwegian, Sámi, other European and other world). RESULTS: From the original sample of 2,909 individuals, 1,986 (68.3%) people participated, of whom 1,019 (51.3%) were women. The highest attendance rate was among women 20-34 years old (80.3%) and the lowest in the oldest age group of women (55.4%). There was no difference in response rate between rural and urban areas. There was a positive correlation between population size and household gross income (p < 0.001) and education level (p < 0.001). The majority of Sámi resided in smaller municipalities. In larger cities, most participants used private dental health care services, whereas, in rural areas, most participants used the public dental health care service. CONCLUSION: The TOHNN study has the potential to generate new knowledge on a wide range of oral health conditions beneficial to the population in Troms County. Due to the high participation rate, generalization both nationally and to the circumpolar area ought to be possible.