The concept of multidimensional modeling has proven extremely successful in the area of Online Analytical Processing (OLAP) as one of many applications running on top of a data warehouse installation. Although many different modeling techniques expressed in extended multidimensional data models were proposed in the recent past, we feel that many hot issues are not properly reflected. In this paper we address ten common problems reaching from defects within dimensional structures over multidimensional structures to new analytical requirements and more.

Sensor data sets are usually collected in a centralized sensor database system or replicated cached in a distributed system to speed up query evaluation. However, a high data refresh rate disallows the usage of traditional replicated approaches with its strong consistency property. Instead we propose a combination of grid computing technology with sensor database systems. Each node holds cached data of other grid members. Since cached information may become stale fast, the access to outdated data may sometimes be acceptable if the user has knowledge about the degree of inconsistency if unsynchronized data are combined. The contribution of this paper is the presentation and discussion of a model for describing inconsistencies in grid organized sensor database systems.

Global energy constraints and economic conditions have placed large energy consumers under pressure to conserve resources. Several governments have acknowledged this and have employed policies to address energy shortages. In South Africa, the lacking electrical infrastructure caused severe electricity supply shortages during recent years. To alleviate the shortage, the government has revised numerous energy policies. Consumers stand to gain nancially if they embrace the opportunities o ered by the revised policies. Energy management systems provide a framework that ensures alignment with speci cations of the respective programs. Such a system requires a data consolidation platform to import and manage relevant data. A stored combination of consumption data, production data and nancial data can be used to extract information for numerous reporting applications. This study discusses the development of a data consolidation platform. The platform is used to collect and maintain energy related data. The platform is capable of consolidating a wide range of energy and production data into a single data set. The generic platform architecture o ers users the ability to manage a wide range of data from several sources. In order to generate reports, the platform was integrated with an existing software based energy management system. The integrated system provides a web-based interface that allows the generation and distribution of various reports. To do this the system accesses the consolidated data set. The developed energy information tool is used by an ESCo to gather and consolidate data from multiple client systems into a single repository. Speci c reports are generated by the integrated system and can be targeted at both consumers and governing bodies. The system complies with draft legislative guidelines and has been successfully implemented as a energy information tool in practice. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Global energy constraints and economic conditions have placed large energy consumers under pressure to conserve resources. Several governments have acknowledged this and have employed policies to address energy shortages. In South Africa, the lacking electrical infrastructure caused severe electricity supply shortages during recent years. To alleviate the shortage, the government has revised numerous energy policies. Consumers stand to gain nancially if they embrace the opportunities o ered by the revised policies. Energy management systems provide a framework that ensures alignment with speci cations of the respective programs. Such a system requires a data consolidation platform to import and manage relevant data. A stored combination of consumption data, production data and nancial data can be used to extract information for numerous reporting applications. This study discusses the development of a data consolidation platform. The platform is used to collect and maintain energy related data. The platform is capable of consolidating a wide range of energy and production data into a single data set. The generic platform architecture o ers users the ability to manage a wide range of data from several sources. In order to generate reports, the platform was integrated with an existing software based energy management system. The integrated system provides a web-based interface that allows the generation and distribution of various reports. To do this the system accesses the consolidated data set. The developed energy information tool is used by an ESCo to gather and consolidate data from multiple client systems into a single repository. Speci c reports are generated by the integrated system and can be targeted at both consumers and governing bodies. The system complies with draft legislative guidelines and has been successfully implemented as a energy information tool in practice. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Published Article / In response to the Human Immunodeficiency Virus (HIV) epidemic in the country, the South African Government started with the provisioning of Antiretroviral Therapy (ART) in the public health sector. Monitoring and evaluating the effectiveness of the ART programme is of the utmost importance. The current patient information system could not supply the required information to manage the rollout of the ART programme. A data warehouse, consisting of several data marts, was developed that integrated several disparate systems related to HIV/AIDS/ART into one system. It was, however, not possible to trace a patient across all the data marts in the data warehouse. No unique identifiers existed for the patient records in the different data marts and they also had different structures. Record linkage in conjunction with a mapping process was used to link all the data marts and in so doing identify the same patient in all the data marts. This resulted in a longitudinal patient record of an ART patient that displayed all the treatments received by the patient in all public health care facilities in the province.

Many high-volume warehouses for small parts such as pharmaceuticals, cosmetics and office supplies seek to improve efficiency by creating forward pick areas in which many popular products are stored in a small area that is replenished from reserve storage. This thesis addresses the question of how to stock forward pick areas to maximum benefit by answering two key, inter-related decisions that have been called Assignment-Allocation. The assignment question asks which SKUs should be stored in the forward pick area? And the allocation question asks how much space should be allocated to each SKU? We show fast, simple, near-optimal algorithms to answer these questions in a variety of circumstances. To allocate space to SKUS, we introduce a Powers of Two allocation scheme designed to simplify shelf management. In addition, we present a ranking-based algorithm to assign SKUs and allocate space among multiple forward pick areas. We show that a similar algorithm that accounts for constraints on congestion and workload within the forward pick area. We also show how to determine the optimal assignment for warehouses with one or more forward pick areas that allocate space in ways that are common in practice. Warehouses frequently use the 80-20 rule to manage SKUs based on their popularity. We examine empirical data from thirty warehouses and analyze whether the power law distribution is a suitable fit. We test the hypothesis that the power law fits of warehouses in similar industries are themselves similar. We review explanations for why power laws arise in other settings and identify those that are plausible in the warehouse setting.

Wireless technologies and networks are a part of our daily lives and we are surrounded by a constant stream of wireless signals. Unfortunately, there are a lot of limitations. At Toyota Material Handling Europe, future demands and expectations are raising but the technologies available today are not adapting fast enough. Indoor factory environments, moving network nodes and rapidly changing topologies are demanding situations. In this new Internet of Things day and age, transferring information in these challenging environments, the standard master and slave configuration is not enough. This report looks at the specific challenges establishing a wireless communication link between trucks in an indoor factory and warehouse environment. There are many factors to consider. Antennas, noise, frequency bands, different network technologies, propagation and path loss modeling to mention a few. Antennas and on-the-truck antenna positioning require design choices to be made. If we want to benefit from using high gain antennas, positioning is an important factor. Noise, in the highly congested 2.4 GHz band is a problem, especially considering safety critical applications. The license free ISM frequency bands have all different advantages in range, available communication protocols and amount of other technologies sharing the spectrum. The Wi-Fi, Bluetooth, ZigBee and V2X technologies looked at, tailored to the particular case of a warehouse environment like the Toyota factory, and the final selection relates to potential use case scenarios. Prioritizing, scalability, ad hoc network topologies, low latencies and short connection times together with long range, the new V2X technology building upon the IEEE 802.11p standard stands out. This report evaluates the IEEE 802.11p wireless standard running the ETSI ITS G5 V2X protocol in an indoor factory and warehouse environment. Thanks to Kapsch and their EVK-3300 V2X Evaluation Kit it was possible to evaluate transferring information between nodes, the PSR, and looking at how useful different path loss models are for estimating relative distances between trucks.

This licentiate thesis presents the use of participatory approach to developing a data warehouse for data mining in health care. Uganda is one of the countries that faced the largest brunt of the HIV/AIDS epidemic at its inception in the early 1980s with reports of close to a million deaths. Government and nongovernmental interventions over the years saw massive reductions in HIV prevalence rates over the years. This reduction in HIV prevalence rates led to great praises by the international community and a call for other countries to model Uganda’s approach to battling the epidemic. In the last decade the reduction in HIV prevalence rates have stagnated and in some cases increased. This has lead to a call for reexamination of the HIV/AIDS fight with an emphasis on collective efforts of all approaches. One of these collective efforts is the introduction of antiretroviral therapy (ART) for those already infected with the virus. Antiretroviral therapy has numerous challenges in Uganda not least of which is the cost of the therapy especially on a developing country with limited resources. It is estimated that of the close to 1 million infected in Uganda only 300,000 are on antiretroviral therapy (UNAIDS, 2009). Additional challenges of the therapy includes following through a treatment regimen that is prescribed. Given the costs of the therapy and the limited number of people able to access the therapy it is imperative that this effort be as effective as possible. This research hinges on using data mining techniques with monitoring HIV patient’s therapy, most specifically their adherence to ART medication. This is crucial given that failure to adhere to therapy means treatment failure, virus mutation and huge losses in terms of costs incurred in administering the therapy to the patients. A system was developed to monitor patient adherence to therapy, by using a participatory approach of gathering system specification and testing to ensure acceptance of the system by the stakeholders. Due to the cost implications of over the shelf software the development of the system was implemented using open source software with limited license costs. These can be implemented in resource constrained settings in Uganda and elsewhere to assist in monitoring patients in HIV therapy. A algorithm that is used to analyze the patient data warehouses for information on and quickly assists therapists in identifying potential risks such as non-adherence and treatment failure. Open source dimensional modeling tools power architect and DB designer were used to model the data warehouse using open source MYSQL database. The thesis is organized in three parts with the first part presenting the background information, the problem, justification, objectives of the research and a justification for the use of participatory methodology. The second part presents the papers, on which this research is based and the final part contains the summary discussions, conclusions and areas for future research. The research is sponsored by SIDA under the collaboration between Makerere University and Blekinge Institute of Technology (BTH) in Sweden.

Roof venting is often utilised in large warehouses to remove smoke in order to reduce damage to a building and its contents, and to maintain access for fire-fighters. In New Zealand, the Compliance Document for the New Zealand Building Code C clauses recommends 15 % opening area for unsprinklered single floor buildings. This opening area is required to be designed for effective fire venting. There is no justification for why 15 % is required, and no definition of how fire venting qualifies as being effective. Fire Dynamics Simulator (FDS) was used to simulate the performance of various roof venting strategies in two different-sized industrial warehouses (both larger than 1,500 m²) with a 50 MW fire with both a rapid and an extreme t³ growth rate. In particular, roof venting areas of 15 %, 10 %, and 5 % of the floor area were tested with each of the following inlet areas for make-up air: 100 %, 50 %, and 0 % of roof venting area. In each of these cases, the vents were treated as permanently-open holes in the roof. It was shown that roof venting with 15 % geometric area is ample to provide and maintain tenability for fire-fighters. With sufficient inlet area for make-up air, smaller venting areas could also be employed. Further simulations were run to test the effect of square-shaped vents that opened simultaneously at 100°C compared with square-shaped vents that opened sequentially at 100°C, 200°C, and 300°C, and strip-shaped vents that opened progressively as each portion of a vent reached activation temperatures of 200°C and 300°C. Vents that opened at 100°C were intended to represent mechanical vents, while vents opening at higher temperatures were intended to represent plastic sky-light or drop-out type vents. The activation temperature proved to be more influential than the opening sequence or shape: there was a significant advantage to be gained by having vents that activated at 100°C as opposed to 200°C or 300°C. The role of downstands in aiding the effectiveness of roof venting was also investigated, with downstand depths of 10 %, 20 %, and 30 % of the ceiling height being simulated. Downstands were shown to be incredibly useful for exhausting smoke and hot gases, provided their installation was appropriately coordinated with placement of roof venting. It is concluded that a clear definition of effective fire venting must not only include the area of roof venting, but equally important is the definition of required inlet area for make-up air, as it plays a crucial role in the effectiveness of the specified roof venting area. In addition, the clear aerodynamic area should be specified. This could be achieved by use of a discharge coefficient that describes the proportion of the roof venting area that is clear aerodynamic area for a particular material, vent, and geometric area. Development of a clear definition of effective fire venting will help to determine how an economic fire protection system can be continued to be used, while going a long way to ensuring predictable and tenable conditions for fire-fighters in New Zealand.

This thesis and appended papers present the process of tacking the problem of environment modeling for autonomous agent. More specifically, the focus of the work has been semantic mapping of warehouses. A semantic map for such purpose is expected to be layout-like and support semantics of both open spaces and infrastructure of the environment. The representation of the semantic map is required to be understandable by all involved agents (humans, AGVs and WMS.) And the process of semantic mapping is desired to lean toward full-autonomy, with minimum input requirement from human user. To that end, we studied the problem of semantic annotation over two kinds of spatial map from different modalities. We identified properties, structure, and challenges of the problem. And we have developed representations and accompanied methods, while meeting the set criteria. The overall objective of the work is “to develop and construct a layer of abstraction (models and/or decomposition) for structuring and facilitate access to salient information in the sensory data. This layer of abstraction connects high level concepts to low-level sensory pattern.” Relying on modeling and decomposition of sensory data, we present our work on abstract representation for two modalities (laser scanner and camera) in three appended papers. Feasibility and the performance of the proposed methods are evaluated over data from real warehouse. The thesis conclude with summarizing the presented technical details, and drawing the outline for future work. / Automatic Inventory and Mapping of Stock (AIMS)