Advanced mobile network monitoring and automated optimization methods

The operation of mobile networks is a complex task with the networks serving a large amount of subscribers with both voice and data services, containing extensive sets of elements, generating extensive amounts of measurement data and being controlled by a large amount of parameters. The objective of this thesis was to ease the operation of mobile networks by introducing advanced monitoring and automated optimization methods. In the monitoring domain the thesis introduced visualization and anomaly detection methods that were applied to detect intrusions, mal-functioning network elements and cluster network elements to do parameter optimization on network-element-cluster level. A key component in the monitoring methods was the Self-Organizing Map. In the automated optimization domain several rule-based Wideband CDMA radio access parameter optimization methods were introduced. The methods tackled automated optimization in areas such as admission control, handover control and mobile base station cell size setting. The results from test usage of the monitoring methods indicated good performance and simulations indicated that the automated optimization methods enable significant improvements in mobile network performance. The presented methods constitute promising feature candidates for the mobile network management system.reviewe

Semantic Support for Log Analysis of Safety-Critical Embedded Systems

Testing is a relevant activity for the development life-cycle of Safety Critical Embedded systems. In particular, much effort is spent for analysis and classification of test logs from SCADA subsystems, especially when failures occur. The human expertise is needful to understand the reasons of failures, for tracing back the errors, as well as to understand which requirements are affected by errors and which ones will be affected by eventual changes in the system design. Semantic techniques and full text search are used to support human experts for the analysis and classification of test logs, in order to speedup and improve the diagnosis phase. Moreover, retrieval of tests and requirements, which can be related to the current failure, is supported in order to allow the discovery of available alternatives and solutions for a better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic discovery, ontology, big dat

Data analysis methods for cellular network performance optimization

Modern cellular networks including GSM/GPRS and UMTS networks offer faster and more versatile communication services for the network subscribers. As a result, it becomes more and more challenging for the cellular network operators to enhance the usage of available radio resources in order to meet the expectations of the customers. Cellular networks collect vast amounts of measurement information that can be used to monitor and analyze the network performance as well as the quality of service. In this thesis, the application of various data-analysis methods for the processing of the available measurement information is studied in order to provide more efficient methods for performance optimization. In this thesis, expert-based methods have been presented for the monitoring and analysis of multivariate cellular network performance data. These methods allow the analysis of performance bottlenecks having an effect in multiple performance indicators. In addition, methods for more advanced failure diagnosis have been presented aiming in identification of the causes of the performance bottlenecks. This is important in the analysis of failures having effect on multiple performance indicators in several network elements. Finally, the use of measurement information in selection of most useful optimization action have been studied. In order to obtain good network performance efficiently, the expected performance of the alternative optimization actions must be possible to evaluate. In this thesis, methods to combine measurement information and application domain models are presented in order to build predictive regression models that can be used to select the optimization actions providing the best network performance

SMS Text-Messaging and the Nigerian Christian Context: Constructing Values and Sentiments

The Global System of Mobile Communications (GSM) in Nigeria brought with it a variety of English that is situationally distinct and context sensitive. Thus SMS text-messages are viewed as discourses that presuppose speech events among interlocutors that share a common social behaviour and cultural values. This study shows the extent to which test-messaging constructs Christian values, belief systems and sentiments in Nigeria. Fifty-three (53) text samples collected in Lagos and Ota areas of Southwest Nigeria between 2005 and 2007 are analysed within the framework of computer-mediated discourse analysis (Herring 2001). Result shows that with its peculiar orthographic convention and style, text-messaging has become popular among Christian adherents not just because it is short, cheap and fast but that it is individualistic and fits well into a context where respect for individuals is emphasized. Analysis also shows that SMS text-messaging is used to disseminate messages associated with faith-based pronouncements, prayer and well-wishing, admonition and assurance, appreciation and praise, seasons greetings and general information/announcements. These functions tend to promote love and cooperation among church members. Key words: SMS-text messages, Christian, Discourse Introduction Th

Assessing the Nigerianness of SMS Text-Messages in English

In the history of the English language certain developments have left significant linguistic marks on the language. As new developments and cultural forms occur, new words and styles of expression evolve with them and spread. This is true of the new linguistic style that is associated with the Global System for Mobile Communications (GSM) revolution in Nigeria since 2001. GSM has brought with it a variety of English that is situationally distinctive and context sensitive (Awonusi, 2004:45)

Unsupervised Methods for Anomalies Detection through Intelligent Monitoring Systems

The success of intelligent diagnosis systems normally depends on the knowledge about the failures present on monitored systems. This knowledge can be modelled in several ways, such as by means of rules or probabilistic models. These models are validated by checking the system output fit to the input in a supervised way. However, when there is no such knowledge or when it is hard to obtain a model of it, it is alternatively possible to use an unsupervised method to detect anomalies and failures. Different unsupervised methods (HCL, K-Means, SOM) have been used in present work to identify abnormal behaviours on the system being monitored. This approach has been tested into a real-world monitored system related to the railway domain, and the results show how it is possible to successfully identify new abnormal system behaviours beyond those previously modelled well-known problems

Knowledge discovery from trajectories

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAs a newly proliferating study area, knowledge discovery from trajectories has attracted more and more researchers from different background. However, there is, until now, no theoretical framework for researchers gaining a systematic view of the researches going on. The complexity of spatial and temporal information along with their combination is producing numerous spatio-temporal patterns. In addition, it is very probable that a pattern may have different definition and mining methodology for researchers from different background, such as Geographic Information Science, Data Mining, Database, and Computational Geometry. How to systematically define these patterns, so that the whole community can make better use of previous research? This paper is trying to tackle with this challenge by three steps. First, the input trajectory data is classified; second, taxonomy of spatio-temporal patterns is developed from data mining point of view; lastly, the spatio-temporal patterns appeared on the previous publications are discussed and put into the theoretical framework. In this way, researchers can easily find needed methodology to mining specific pattern in this framework; also the algorithms needing to be developed can be identified for further research. Under the guidance of this framework, an application to a real data set from Starkey Project is performed. Two questions are answers by applying data mining algorithms. First is where the elks would like to stay in the whole range, and the second is whether there are corridors among these regions of interest

Radio network planning and optimisation for WCDMA

The present thesis introduces the radio network planning process and optimisation for WCDMA (FDD mode), as defined by 3GPP. This thesis consists of three parts: modelling and tools for radio network planning, process for pre-operational network control and optimisation for the operational network. General challenges to face in 3G network control are based on the fact that many issues are interconnected and should be simultaneously considered, such as Planning means not only to meet current status and demands, but the solution should also comply with the future requirements by providing an acceptable development path. Traffic modelling is not only the question about the total amount of traffic growth, but also the question about the future service distribution and performance demands. All CDMA systems have a relation between capacity and coverage. Consequently, the network planning itself is not only based on propagation estimation but also on the interference situation in the network. Ideally, site selection consideration will be done based on the network analysis with planned load and traffic/service portfolio, taking possible co-siting constraints into account. Provision of multiple services and seamless management of at least two multiple access systems require rapid evolution of the management tools and processes. The network performance in terms of capacity, quality, and implementation and operational costs forms a multidimensional space. Operators' task will be to convert the business strategy to an operating point in the performance space in a cost efficient manner. The contribution of this thesis in terms of modelling and tools is as follows: Improvement of the accuracy of radio link budget by introducing power control headroom (also called fast fading margin). Improvement of loading equation by introducing a transmit power increase term. Development of theory and modelling for a planning tool capable of multi-service and multi-carrier interference, capacity and coverage analysis. Development and implementation an interface taking into account the true traffic distribution (not uniform) and terminal speed. In the area of pre-operational planning process the contribution of this thesis is as follows: Development of dimensioning methodology for multi-service network site density estimation, utilising the modelling of power control headroom, transmit power increase, soft handover and Eb/N0. Development of radio network planning process for multi-service environment including capacity and coverage evaluation for a given traffic mixture, quality and area requirements. Analysis of means to improve radio network performance with Mast Head Amplifier (MHA), diversity reception, sectorisation and proper antenna selection. In the area of optimisation of the operational network the contribution of this thesis is as follows: Definition for optimisation target in the case of 3G. The optimisation will be capacity-quality trade-off management instead of plain quality improvement process. Introduction of Self Organizing Map (SOM) in the analysis of cellular networks. Analysis of the applicability of SOM in WCDMA cellular network optimisation. Introduction of SOM based applications to support network capacity-quality trade-off management. It is worth noting that process and methods described in this work are not limited to 3G systems with WCDMA radio access technology, but they are applicable to other CDMA standards as well.reviewe

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most