The present study investigated identification, access and usage of periodicals in university libraries in Kenya, with a view of recommending a tool for assisting users to identify information. Using questionnaires completed by 316 university library users and 27 librarians, backed with participant observations, document analysis as well as interviews, it was found that usage of periodicals was low as most users browse through periodicals to identify information, a method that is not effective. In-house indexing was investigated and found to be an effective tool in facilitating access to relevant information. The study recommends establishment of in-house indexing programs and databases in university libraries; formulation of consistent indexing policies to achieve quality indexing; and that indexing should be focused on both content and user requirements by specifying points- of- view, and study methodologies to enhance retrieval of relevant information. / Information Science / M. A. (Information Science)

Continues field monitoring and searching sensor data remains an imminent element emphasizes the influence of the Internet of Things (IoT). Most of the existing systems are concede spatial coordinates or semantic keywords to retrieve the entail data, which are not comprehensive constraints because of sensor cohesion, unique localization haphazardness. To address this issue, we propose deep learning inspired sensor-rank consolidation (DLi-SRC) system that enables 3-set of algorithms. First, sensor cohesion algorithm based on Lyapunov approach to accelerate sensor stability. Second, sensor unique localization algorithm based on rank-inferior measurement index to avoid redundancy data and data loss. Third, a heuristic directive algorithm to improve entail data search efficiency, which returns appropriate ranked sensor results as per searching specifications. We examined thorough simulations to describe the DLi-SRC effectiveness. The outcomes reveal that our approach has significant performance gain, such as search efficiency, service quality, sensor existence rate enhancement by 91%, and sensor energy gain by 49% than benchmark standard approaches.

Main goal of this thesis is to theoretically describe and analyze evaluation of economic efficiency of business plan. Business plan is reconstruction old farm building to 5 apartments. In variant of using govermant plan for supporting social house building. And compare efficiency while using datas from pre-investment phase and datas after realization.

Spreadsheets are very successful content generation tools, used in almost every enterprise to create a wealth of information. However, this information is often intermingled with various formatting, layout, and textual metadata, making it hard to identify and interpret the tabular payload. Previous works proposed to solve this problem by mainly using heuristics. Although fast to implement, these approaches fail to capture the high variability of user-generated spreadsheet tables. Therefore, in this paper, we propose a supervised approach that is able to adapt to arbitrary spreadsheet datasets. We use a graph model to represent the contents of a sheet, which carries layout and spatial features. Subsequently, we apply genetic-based approaches for graph partitioning, to recognize the parts of the graph corresponding to tables in the sheet. The search for tables is guided by an objective function, which is tuned to match the specific characteristics of a given dataset. We present the feasibility of this approach with an experimental evaluation, on a large, real-world spreadsheet corpus.

Thesis (M.Sc. (Agricultural Economics)) -- University of Limpopo, 2022 / Agricultural production measures the performance and efficiency of a country’s agricultural sector. The state of agricultural production can be assessed through the value of agricultural production, which is a product of agricultural gross production and output prices in monetary terms. The study examines the relationship between the value of agricultural production, government spending on agriculture, and other selected variables. Annual data for the value of agricultural production, government expenditure in agriculture, consumer price index, average annual rainfall, food import value, and population from 1983 to 2019 were collected from different sources and were used in the analysis for this study. The Johansen cointegration test was used to determine the existence of a long-run relationship between the value of agricultural production and selected variables by using both the trace and eigenvalue tests. The results indicated that there is a long run relationship among the variables. The study further used the Granger causality test to check the causality between the value of agricultural production and government expenditure in agriculture. The results show that there is no causal effect between the two variables. Lastly, the study used a Vector autoregressive (VAR) model to determine the relationship between the value of agricultural production and selected variables. The results of the VAR model indicated that government expenditure on agriculture, average annual rainfall, food import value, and population positively affect the value of agricultural production. The study also found that the consumer price index negatively affects the value of agricultural production. The study recommends that the government increase its spending on the agricultural sector, which could be in the form of research investment in technologies such as climate-smart agricultural technologies. Additionally, the study recommends that policymakers should review the monetary policy of South Africa to ensure price stability and prevent inflation. Lastly, the study recommends that the South African government should discourage imports and encourage South African agricultural producers to produce more major imported food products.

Physical design has always been an important part of database administration. Today's commercial database management systems offer physical design tools, which recommend a physical design for a given workload. However, these tools work only with static workloads and ignore the fact that workloads, and physical designs, may change over time. Research has now begun to focus on dynamic physical design, which can account for time-varying workloads. In this paper, we consider a dynamic but constrained approach to physical design. The goal is to recommend dynamic physical designs that reflect major workload trends but that are not tailored too closely to the details of the input workloads. To achieve this, we constrain the number of changes that are permitted in the recommended design. In this paper we present our definition of the constrained dynamic physical design problem and discuss several techniques for solving it.

Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2022 / Using the ARFIMA (autoregressive and fractionally integrated moving aver age) model extended with sGARCH (standard generalised autoregressive con ditional heteroscedasticity) and ’gjrGARCH (Glosten-Jagannathan-Runkle gen eralised autoregressive conditional heteroscedascity) innovations, fractional in tegration approach and state space model, this study has empirically examined persistency of inflation dynamics of Ghana and South Africa, the only two coun tries in Sub-Saharan Africa with Inflation Targeting (IT) monetary policy. The first part of the analysis employed monthly CPI (Consumer Price Index) in flation series for the period January 1971 to October 2014 obtained from the Bank of Ghana (BoG), and for the period January 1995 to December 2014 ob tained from Statistics South Africa. The second part involves the estimation of threshold effect of inflation on economic growth using annual data obtained from the IMF (International Monetary Fund) database for the period 1981 to 2014, for both countries. Results from the study showed that structural breaks, long memory and non linearities (or regime shifts) are largely responsible for inflation persistence, hence the ever-changing nature of inflation rates of Ghana and South Africa. ARFIMA(3,0.35,1)-‘gjrGARCH(1,1) under Generalised Error Distribution (GED) and ARFIMA(3,0.50,1)-‘gjrGARCH(1,1) under Student-t Distribution (STD) mod els provided the best fit for persistence in the conditional mean (or level) of CPI for Ghana and South Africa, respectively. The results from these models pro vided evidence of time-varying conditional mean and volatility in CPI inflation rates of both countries. The two models also revealed an asymmetric effect of inflationary shocks, where negative shocks appear to have greater impact than positive shocks, in terms of persistence on the conditional mean with time varying volatility. This thesis proposes a model that combines fractional integration with non linear deterministic terms based on the Chebyshev polynomials in time for the analysis of CPI inflation rates of Ghana and South Africa. We tested for non-linear deterministic terms in the context of fractional integration and esti mated the fractional differencing parameters, d to be 1.11 and 1.32 respectively, for the Ghanaian and the South African inflation rates, but the non-linear trends were found to be statistically insignificant in the two series. New ev idence from this thesis depicts that inflation rate of Ghana is highly persistent and non-mean reverting, with an estimated fractional differencing parameter, d > 1.0, and will therefore require some policy action to steer inflation back to stability. However, the South African inflation series was found to be a cyclical process with an order of integration estimated to be d = 0.7, depicting mean reversion, with the length of the cycles approximated to last for 80 months. Finally, the thesis incorporated structural breaks, long memory, non-linearity, and some explanatory variables into a state space model and estimated the threshold effect of inflation on economic growth. The empirical results suggest that inflation below the estimated levels of 9% and 6% for Ghana and South Africa respectively, will be conducive for economic growth. The policy implications of these results for both countries are as follows. First, both series had similar properties responsible for inducing inflation persistence such as structural breaks, non-linearities, long memory and asymmetric re sponse to negatives shocks - but with varied degrees of magnitude. For both countries, the conditional mean and unobserved components such as volatility for both countries were found to be time-varying. This thesis, therefore, recom mends to the BoG and the South African Reserve Bank (SARB) - responsible for monetary policies, and the Finance Ministers of both governments - respon sible for fiscal policies, to take the above-mentioned properties into account in the formulation of their monetary policies. Second, the thesis recommends that the BoG and the SARB consolidate the IT policy, since keeping inflation below the targets set of 9% and 6%, respectively for Ghana and South Africa, will boost economic growth. Third, policymakers could also design measures (monetary and fiscal policies) such as increase in interest rates, credit control, and reduction of unnecessary expenditure, among others, to control inflation due to its adverse effects on market volatility. Even though an increase in interest rates could assist in curtailing the recent and anticipated increase in inflation rates in both countries, where targets have been missed by Ghana and South Africa, it will also be prudent to legislate monetary policies around demand-supply side since the problem of both coun tries appears to be more of a structuralist than a monetarist. It is, therefore, recommended that both countries tighten the IT monetary policy in order to re duce inflation persistence. This will eventually impact on poverty and income distribution with ramifications for economic growth and/or development. The fourth implication of these results is that governments and central banks should be mindful of the actions and decisions they take, in the sense that unguarded decisions and unnecessary alarms could raise uncertainties in the economy, which could, in turn, affect the future trajectory of inflation. Finally, the thesis recommends that governments of both countries strengthen the pri vate sector, which is the engine of growth. For small and open economies such as Ghana and South Africa, this will grow the economy through job creation and restore investor confidence. / National Research Foundation (NRF), Department of Science and Technology (DST), Telkom’s Tertiary Education Support Programme (TESP) and the NRF-DST Centre of Excellence for Mathematical and Statistical Sciences (CoE-MaSS)

Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Beef and chicken meat play a very crucial role in providing food to South African consumers. However, the rise of food prices in South Africa is viewed to curtail progress and drives consumers into debt and forgone opportunity to access food. Hence, it is of importance to understand the consumer price index (CPI) of meat and the disaggregate components of beef and chicken meat producer price indexes (PPI) as they give a clear insight into how individual commodities contribute to the general and food price inflation. The study aimed to comparatively analyse the relationship between PPI beef and CPI meat as well as PPI chicken meat and CPI meat in South Africa from 1991 to 2018. The objectives of the study were to compare the indexes’ variability, correlation, and causality between the different PPI and CPI components. The objectives were analysed using the Coefficient of variation (CV), the Pearson coefficient correlation, the Granger causality test, and the Vector Error Correction model. The CV findings highlight that PPI beef had high variability (65%) compared to CPI meat (56.7%), whereas PPI chicken meat had low variability (49.2%) compared to CPI meat(56.7%). There was evidence of a positive correlation (0.99) between PPI beef and CPI meat as well as PPI chicken meat and CPI meat using Pearson coefficient correlation. In addition, a long-run relationship was found between PPI beef and CPI meat as well as between PPI chicken meat and CPI meat by using the VEC model. Granger causality results indicated that there was a unidirectional relationship from PPI chicken meat to CPI meat, and independent relationships were found from PPI beef to CPI meat, CPI meat to PPI beef as well as CPI meat to PPI chicken meat. Based on the findings, the study recommends that policymakers, through evaluation of monetary policies, should continue maintaining a specific inflation target range as that will assist in stabilising meat prices in the economy. At the same time, protect meat producers against input price inflation using instruments such as input subsidies, grants, and the provision of modern technologies. / National Research Foundation (NRF)

The increasing number of cores every generation poses challenges for high-performance in-memory database systems. While these systems use sophisticated high-level algorithms to partition a query or run multiple queries in parallel, they also utilize low-level synchronization mechanisms to synchronize access to internal database data structures. Developers often spend significant development and verification effort to improve concurrency in the presence of such synchronization. The Intel ® Transactional Synchronization Extensions (Intel ® TSX) in the 4th Generation Core™ Processors enable hardware to dynamically determine whether threads actually need to synchronize even in the presence of conservatively used synchronization. This paper evaluates the effectiveness of such hardware support in a commercial database. We focus on two index implementations: a B+Tree Index and the Delta Storage Index used in the SAP HANA ® database system. We demonstrate that such support can improve performance of database data structures such as index trees and presents a compelling opportunity for the development of simpler, scalable, and easy-to-verify algorithms.

[pt] Enquanto muitos trabalhos de pesquisa propõem uma forma de listar um conjunto de opções de sintonia fina para uma determinada carga de trabalho, poucos oferecem uma maneira de ajudar o DBA a tomar melhores decisões ao encontrar um conjunto de ações disponíveis. TuningChef é o resultado do desenvolvimento de uma proposta do passo a passo desse processo de decisão. Dado um conjunto de opções de sintonia fina, recomendamos um subconjunto com boa proporção de custo-benefício, com contexto suficiente para que o DBA entenda a motivação por trás de cada decisão, incluindo a possibilidade de deixar o usuário construir seu próprio subconjunto e verificar o impacto esperado. Também são apresentados resultados experimentais que demonstram a importância do processo de decisão, onde dentro de um subconjunto de 50+ ações de sintonia fina sugeridas por uma ferramenta externa, apenas 8 mostram-se como benéficas para a carga de trabalho utilizada. / [en] While many research works propose a way to list a set of fine-tuning options for a given workload, only a few offer a way to help the DBA make better decisions when encountering a set of available options, especially when taking his possibilities into consideration. We propose and develop a step-by-step decision process. Given a set of fine-tuning options, we recommend a subset with good cost-benefit proportion. Enough context for the DBA accompanies the recommendation to understand its reasoning, with the possibility of letting the user build his own subset and check the expected impact. Some experimental results are also described, showing the importance of the decision step when fine tuning a database, where in a set on 50+ fine tuning actions suggested by an external tool, only 8 are considered beneficial for the a specific workload.