Service-based Requirements for Future Mobile Networks

The mobile phone has, as a device, taken the world by storm in the past decade; from only 136 million phones globally in 1996, it is now estimated that by the end of 2008 roughly half of the worlds population will own a mobile phone. Over the years, the capabilities of the phones as well as the networks have increased tremendously, reaching the point where the devices are better called miniature computers rather than simply mobile phones. The mobile industry is currently undertaking several initiatives of developing new generations of mobile network technologies; technologies that to a large extent focus at offering ever-increasing data rates. This thesis seeks to answer the question of whether the future mobile networks in development and the future mobile services are in sync; taking a forward-looking timeframe of five to eight years into the future, will there be services that will need the high-performance new networks being planned? The question is seen to be especially pertinent in light of slower-than-expected takeoff of 3G data services. Current and future mobile services are analyzed from two viewpoints; first, looking at the gradual, evolutionary development of the services and second, through seeking to identify potential revolutionary new mobile services. With information on both current and future mobile networks as well as services, a network capability - service requirements mapping is performed to identify which services will work in which networks. Based on the analysis, it is far from certain whether the new mobile networks, especially those planned for deployment after HSPA, will be needed as soon as they are being currently roadmapped. The true service-based demand for the "beyond HSPA" technologies may be many years into the future - or, indeed, may never materialize thanks to the increasing deployment of local area wireless broadband technologies.

Describing and validating functional requirements as use cases

Requirements engineering is an important phase in software development where customer's needs and expectations are transformed into a software requirements specification. The requirements specification can be considered as an agreement between the customer and the developer where both parties agree on the expected system features and behaviour. However, requirements engineers must deal with a variety of issues that complicate the requirements process. The communication gap between the customer and the developers is among typical reasons for unsatisfactory requirements. In this thesis we study how the use case technique could be used in requirements engineering in bridging the communication gap between the customer and development team. We also discuss how a use case description can be use cases can be used as a basis for acceptance test cases.

Communities of wood-inhabiting fungi : Ecological requirements and responses to forest management and fragmentation

Despite much research on forest biodiversity in Fennoscandia, the exact mechanisms of species declines in dead-wood dependent fungi are still poorly understood. In particular, there is only limited information on why certain fungal species have responded negatively to habitat loss and fragmentation, while others have not. Understanding the mechanisms behind species declines would be essential for the design and development of ecologically effective and scientifically informed conservation measures, and management practices that would promote biodiversity in production forests. In this thesis I study the ecology of polypores and their responses to forest management, with a particular focus on why some species have declined more than others. The data considered in the thesis comprise altogether 98,318 dead-wood objects, with 43,085 observations of 174 fungal species. Out of these, 1,964 observations represent 58 red-listed species. The data were collected from 496 sites, including woodland key habitats, clear-cuts with retention trees, mature managed forests, and natural or natural-like forests in southern Finland and Russian Karelia. I show that the most relevant way of measuring resource availability can differ to a great extent between species seemingly sharing the same resources. It is thus critical to measure the availability of resources in a way that takes into account the ecological requirements of the species. The results show that connectivity at the local, landscape and regional scales is important especially for the highly specialized species, many of which are also red-listed. Habitat loss and fragmentation affect not only species diversity but also the relative abundances of the species and, consequently, species interactions and fungal successional pathways. Changes in species distributions and abundances are likely to affect the food chains in which wood-inhabiting fungi are involved, and thus the functioning of the whole forest ecosystem. The findings of my thesis highlight the importance of protecting well-connected, large and high-quality forest areas to maintain forest biodiversity. Small habitat patches distributed across the landscape are likely to contribute only marginally to protection of red-listed species, especially if habitat quality is not substantially higher than in ordinary managed forest, as is the case with woodland key habitats. Key habitats might supplement the forest protection network if they were delineated larger and if harvesting of individual trees was prohibited in them. Taking the landscape perspective into account in the design and development of conservation measures is critical while striving to halt the decline of forest biodiversity in an ecologically effective manner.

Nitrification (DMPP) and urease (NBPT) inhibitors had no effect on pasture yield, nitrous oxide emissions nor nitrate leaching under irrigation in a hot-dry climate

Modern dairy farming in Australia relies on substantial inputs of fertiliser nitrogen (N) to underpin economic production. However, N lost from dairy systems represents an opportunity cost and can pose a number of environmental risks. Nitrogen cycle inhibitors can be co-applied with N fertilisers to slow the conversion of urea to NH4+ to reduce losses via volatilisation, and slow the conversion of NH4+ to NO3- to minimize leaching of NO3- and gaseous losses via nitrification and denitrification. In a field campaign in a high input ryegrass-kikuyu pasture system we compared the soil N pools, losses and pasture production between a) urea coated with the nitrification inhibitor (3,4-dimethyl pyrazole phosphate - DMPP) b) urea coated with the urease inhibitor (N-(n-butyl) thiophosphoric triamide - NBPT) and c) standard urea. There was no treatment effect (P>0.05) on soil mineral N, pasture yield, N2O flux nor leaching of NO3- cf. standard urea. We hypothesise that at our site, because gaseous losses were highly episodic (rainfall was erratic and displayed no seasonal rainfall nor soil wetting pattern) that there was a lack of coincidence of N application and conditions conducive to gaseous losses, thus the effectiveness of the inhibitor products was minimal and did not result in an increase in pasture yield. There remains a paucity of knowledge on N cycle inhibitors in relation to their effective use in field system to increase N use efficiency. Further research is required to define under what field conditions inhibitor products are effective in order to be able to provide accurate advice to managers of nitrogen in production systems.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

Agricultural expansion and climate change in the Taita Hills, Kenya: an assessment of potential environmental impacts

The indigenous cloud forests in the Taita Hills have suffered substantial degradation for several centuries due to agricultural expansion. Currently, only 1% of the original forested area remains preserved in this region. Furthermore, climate change imposes an imminent threat for local economy and environmental sustainability. In such circumstances, elaborating tools to conciliate socioeconomic growth and natural resources conservation is an enormous challenge. This dissertation tackles essential aspects for understanding the ongoing agricultural activities in the Taita Hills and their potential environmental consequences in the future. Initially, alternative methods were designed to improve our understanding of the ongoing agricultural activities. Namely, methods for agricultural survey planning and to estimate evapotranspiration were evaluated, taking into account a number of limitations regarding data and resources availability. Next, this dissertation evaluates how upcoming agricultural expansion, together with climate change, will affect the natural resources in the Taita Hills up to the year 2030. The driving forces of agricultural expansion in the region were identified as aiming to delineate future landscape scenarios and evaluate potential impacts from the soil and water conservation point of view. In order to investigate these issues and answer the research questions, this dissertation combined state of the art modelling tools with renowned statistical methods. The results indicate that, if current trends persist, agricultural areas will occupy roughly 60% of the study area by 2030. Although the simulated land use changes will certainly increase soil erosion figures, new croplands are likely to come up predominantly in the lowlands, which comprise areas with lower soil erosion potential. By 2030, rainfall erosivity is likely to increase during April and November due to climate change. Finally, this thesis addressed the potential impacts of agricultural expansion and climate changes on Irrigation Water Requirements (IWR), which is considered another major issue in the context of the relations between land use and climate. Although the simulations indicate that climate change will likely increase annual volumes of rainfall during the following decades, IWR will continue to increase due to agricultural expansion. By 2030, new cropland areas may cause an increase of approximately 40% in the annual volume of water necessary for irrigation.

The Impact of New Capital Requirements on the Portfolio Decisions of Finnish Pension Institutions

This paper examines the potential impact of new capital requirements on asset allocations of Finnish pension institutions. We describe the new requirements and consider portfolio construction to minimize regulatory capital, given the investor’s preferred level of expected return. Results identify portfolio transactions that enhance expected return without increasing capital needs. Regulation calls for portfolio diversification and prudence in management, but this paper shows that market participants can exploit inconsistencies in regulation. Possible future consequences include capital outflows from the pension system and an unintended decrease in pre-funding of old-age pensions.

Decision support requirements for intelligent operation of southern grid in India

Control centers (CC) play a very important role in power system operation. An overall view of the system with information about all existing resources and needs is implemented through SCADA (Supervisory control and data acquisition system) and an EMS (energy management system). As advanced technologies have made their way into the utility environment, the operators are flooded with huge amount of data. The last decade has seen extensive applications of AI techniques, knowledge-based systems, Artificial Neural Networks in this area. This paper focuses on the need for development of an intelligent decision support system to assist the operator in making proper decisions. The requirements for realization of such a system are recognized for the effective operation and energy management of the southern grid in India The application of Petri nets leading to decision support system has been illustrated considering 24 bus system that is a part of southern grid.

Systems Analysis of Tank Irrigation: II. Delayed Start and Water Deficit

Tank irrigation systems in the semiarid regions of India are discussed in this paper. To optimize the grain yield of rice, it is essential to start the agricultural operations in the second week of July so that favorable climatic conditions will prevail during flowering and yield formation stages. Because of low inflow during the initial few weeks of the crop season, often farmers are forced to delay planting until sufficient sowing rain and inflow have occurred or to adopt deficit irrigation during this period. The delayed start affects the grain yield, but will lead to an improved irrigation efficiency. A delayed start of agricultural operations with increased irrigation efficiency leads to the energy resources becoming critical during the peak requirement week, particularly those of female labor and animal power. This necessitates augmenting these resources during weeks of their peak use, either by reorganizing the traditional methods of cultivation or by importing from outside the system.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Artificial neural networks and multicriterion analysis for sustainable irrigation planning

The objective of the present paper is to select the best compromise irrigation planning strategy for the case study of Jayakwadi irrigation project, Maharashtra, India. Four-phase methodology is employed. In phase 1, separate linear programming (LP) models are formulated for the three objectives, namely. net economic benefits, agricultural production and labour employment. In phase 2, nondominated (compromise) irrigation planning strategies are generated using the constraint method of multiobjective optimisation. In phase 3, Kohonen neural networks (KNN) based classification algorithm is employed to sort nondominated irrigation planning strategies into smaller groups. In phase 4, multicriterion analysis (MCA) technique, namely, Compromise Programming is applied to rank strategies obtained from phase 3. It is concluded that the above integrated methodology is effective for modeling multiobjective irrigation planning problems and the present approach can be extended to situations where number of irrigation planning strategies are even large in number. (c) 2004 Elsevier Ltd. All rights reserved.

Structural requirements for the induction and inhibition of 2,3-dihydroxybenzoic acid decarboxylase ofAspergillus niger

2,3-Dihydroxybenzoic acid decarboxylase inAspergillus niger was induced by many substrate analogs including salicylate and gentisate. Catechol, which is the product, induced the enzyme tenfold. The purified enzyme was competitively inhibited by manyortho substituted benzoic acids. The Ki values for salicylate,o-fluoro ando-chloro benzoic acids were 0.12 mM, 0.12 mM, and 0.13 mM respectively; these values were lower than the Km value for the substrate. As the size of the group in theortho position increased, as in the case of bromo- and iodo-derivatives, there was an increase in their Ki values. The C-2 hydroxyl group was essential both for the induction and for interaction with the enzyme. The C-3 hydroxyl group was not necessary for induction or inhibition, but it might be essential for the catalysis.