Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training

Receive antenna selection (AS) reduces the hardware complexity of multi-antenna receivers by dynamically connecting an instantaneously best antenna element to the available radio frequency (RF) chain. Due to the hardware constraints, the channels at various antenna elements have to be sounded sequentially to obtain estimates that are required for selecting the ``best'' antenna and for coherently demodulating data. Consequently, the channel state information at different antennas is outdated by different amounts. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, the channel estimates of different antennas should be weighted differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then derive an explicit formula for the optimal selection weights that minimize the SEP. We find that when selection weights are not used, the SEP need not improve as the number of antenna elements increases, which is in contrast to the ideal channel estimation case. However, the optimal selection weights remedy this situation and significantly improve performance.

Optimal management of conflicting species: Grey seal (Halichoerus grypus) and Atlantic salmon (Salmo salar) in the Baltic Sea

The objective of this thesis is to examine the economic effects in the conflict between grey seal population and the salmon fishery in the Baltic Sea. We will formulate a bioeconomic model which provides new insights on the optimal management of Atlantic salmon with respect to the effects brought about by the grey seal population. As the catch losses caused by seals have an effect on salmon fishery in Baltic, we will study how seal population affects the present value of the salmon fishery. The study considers the Finnish coastal trap net fishery. The bioeconomic model considers a scenario of sole salmon fishery and a scenario of salmon fishery affected by the grey seal population. On the basis of these scenarios, a seal compensation scheme is introduced. We can observe a significant economic seal-induced effect on the salmon fishery. The results suggest that the present seal compensation scheme emploid by the Finnish government is suboptimal. This thesis is part of the TARMO –project, in which the conflict between grey seal population and salmon fishery is studied using the methods of environmental economics.

Air Fleet and Facility Planning via Optimal Control Models

A study is presented which is aimed at developing techniques suitable for effective planning and efficient operation of fleets of aircraft typical of the air force of a developing country. An important aspect of fleet management, the problem of resource allocation for achieving prescribed operational effectiveness of the fleet, is considered. For analysis purposes, it is assumed that the planes operate in a single flying-base repair-depot environment. The perennial problem of resource allocation for fleet and facility buildup that faces planners is modeled and solved as an optimal control problem. These models contain two "policy" variables representing investments in aircraft and repair facilities. The feasibility of decentralized control is explored by assuming the two policy variables are under the control of two independent decisionmakers guided by different and not often well coordinated objectives.

Air Fleet and Facility Planning via Optimal Control Models

A study is presented which is aimed at developing techniques suitable for effective planning and efficient operation of fleets of aircraft typical of the air force of a developing country. An important aspect of fleet management, the problem of resource allocation for achieving prescribed operational effectiveness of the fleet, is considered. For analysis purposes, it is assumed that the planes operate in a single flying-base repair-depot environment. The perennial problem of resource allocation for fleet and facility buildup that faces planners is modeled and solved as an optimal control problem. These models contain two "policy" variables representing investments in aircraft and repair facilities. The feasibility of decentralized control is explored by assuming the two policy variables are under the control of two independent decisionmakers guided by different and not often well coordinated objectives.

Towards Optimal Testing of Auditory Memory : Methodological development of recording of the mismatch negativity (MMN) of the auditory event-related potential (ERP)

The overlapping sound pressure waves that enter our brain via the ears and auditory nerves must be organized into a coherent percept. Modelling the regularities of the auditory environment and detecting unexpected changes in these regularities, even in the absence of attention, is a necessary prerequisite for orientating towards significant information as well as speech perception and communication, for instance. The processing of auditory information, in particular the detection of changes in the regularities of the auditory input, gives rise to neural activity in the brain that is seen as a mismatch negativity (MMN) response of the event-related potential (ERP) recorded by electroencephalography (EEG). --- As the recording of MMN requires neither a subject s behavioural response nor attention towards the sounds, it can be done even with subjects with problems in communicating or difficulties in performing a discrimination task, for example, from aphasic and comatose patients, newborns, and even fetuses. Thus with MMN one can follow the evolution of central auditory processing from the very early, often critical stages of development, and also in subjects who cannot be examined with the more traditional behavioural measures of auditory discrimination. Indeed, recent studies show that central auditory processing, as indicated by MMN, is affected in different clinical populations, such as schizophrenics, as well as during normal aging and abnormal childhood development. Moreover, the processing of auditory information can be selectively impaired for certain auditory attributes (e.g., sound duration, frequency) and can also depend on the context of the sound changes (e.g., speech or non-speech). Although its advantages over behavioral measures are undeniable, a major obstacle to the larger-scale routine use of the MMN method, especially in clinical settings, is the relatively long duration of its measurement. Typically, approximately 15 minutes of recording time is needed for measuring the MMN for a single auditory attribute. Recording a complete central auditory processing profile consisting of several auditory attributes would thus require from one hour to several hours. In this research, I have contributed to the development of new fast multi-attribute MMN recording paradigms in which several types and magnitudes of sound changes are presented in both speech and non-speech contexts in order to obtain a comprehensive profile of auditory sensory memory and discrimination accuracy in a short measurement time (altogether approximately 15 min for 5 auditory attributes). The speed of the paradigms makes them highly attractive for clinical research, their reliability brings fidelity to longitudinal studies, and the language context is especially suitable for studies on language impairments such as dyslexia and aphasia. In addition I have presented an even more ecological paradigm, and more importantly, an interesting result in view of the theory of MMN where the MMN responses are recorded entirely without a repetitive standard tone. All in all, these paradigms contribute to the development of the theory of auditory perception, and increase the feasibility of MMN recordings in both basic and clinical research. Moreover, they have already proven useful in studying for instance dyslexia, Asperger syndrome and schizophrenia.

Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: stability and moving-horizon approximations

Stability results are given for a class of feedback systems arising from the regulation of time-varying discrete-time systems using optimal infinite-horizon and moving-horizon feedback laws. The class is characterized by joint constraints on the state and the control, a general nonlinear cost function and nonlinear equations of motion possessing two special properties. It is shown that weak conditions on the cost function and the constraints are sufficient to guarantee uniform asymptotic stability of both the optimal infinite-horizon and movinghorizon feedback systems. The infinite-horizon cost associated with the moving-horizon feedback law approaches the optimal infinite-horizon cost as the moving horizon is extended.

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.

Optimal Receive Antenna Selection in Time-Varying Fading Channels with Practical Training Constraints

Hardware constraints, which motivate receive antenna selection, also require that various antenna elements at the receiver be sounded sequentially to obtain estimates required for selecting the `best' antenna and for coherently demodulating data thereafter. Consequently, the channel state information at different antennas is outdated by different amounts and corrupted by noise. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, a preferable strategy is to linearly weight the channel estimates of different antennas differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then characterize explicitly the optimal selection weights that minimize the SEP. We also consider packet reception, in which multiple symbols of a packet are received by the same antenna. New suboptimal, but computationally efficient weighted selection schemes are proposed for reducing the packet error rate. The benefits of weighted selection are also demonstrated using a practical channel code used in third generation cellular systems. Our results show that optimal weighted selection yields a significant performance gain over conventional unweighted selection.

A modell of socially optimal hydro reservoir usage - yelding socially optimal outcomes in nordic electricity markets

An extensive electricity transmission network facilitates electricity trading between Finland, Sweden, Norway and Denmark. Currently most of the area's power generation is traded at NordPool, where the trading volumes have steadily increased since the early 1990's, when the exchange was founded. The Nordic electricity is expected to follow the current trend and further integrate with the other European electricity markets. Hydro power is the source for roughly a half of the supply in the Nordic electricity market and most of the hydro is generated in Norway. The dominating role of hydro power distinguishes the Nordic electricity market from most of the other market places. Production of hydro power varies mainly due to hydro reservoirs and demand for electricity. Hydro reservoirs are affected by water inflows that differ each year. The hydro reservoirs explain remarkably the behaviour of the Nordic electricity markets. Therefore among others, Kauppi and Liski (2008) have developed a model that analyzes the behaviour of the markets using hydro reservoirs as explanatory factors. Their model includes, for example, welfare loss due to socially suboptimal hydro reservoir usage, socially optimal electricity price, hydro reservoir storage and thermal reservoir storage; that are referred as outcomes. However, the model does not explain the real market condition but rather an ideal situation. In the model the market is controlled by one agent, i.e. one agent controls all the power generation reserves; it is referred to as a socially optimal strategy. Article by Kauppi and Liski (2008) includes an assumption where an individual agent has a certain fraction of market power, e.g. 20 % or 30 %. In order to maintain the focus of this thesis, this part of their paper is omitted. The goal of this thesis is two-fold. Firstly we expand the results from the socially optimal strategy for years 2006-08, as the earlier study finishes in 2005. The second objective is to improve on the methods from the previous study. This thesis results several outcomes (SPOT-price and welfare loss, etc.) due to socially optimal actions. Welfare loss is interesting as it describes the inefficiency of the market. SPOT-price is an important output for the market participants as it often has an effect on end users' electricity bills. Another function is to modify and try to improve the model by means of using more accurate input data, e.g. by considering pollution trade rights effect on input data. After modifications to the model, new welfare losses are calculated and compared with the same results before the modifications. The hydro reservoir has the higher explanatory significance in the model followed by thermal power. In Nordic markets, thermal power reserves are mostly nuclear power and other thermal sources (coal, natural gas, oil, peat). It can be argued that hydro and thermal reservoirs determine electricity supply. Roughly speaking, the model takes into account electricity demand and supply, and several parameters related to them (water inflow, oil price, etc.), yielding finally the socially optimal outcomes. The author of this thesis is not aware of any similar model being tested before. There have been some other studies that are close to the Kauppi and Liski (2008) model, but those have a somewhat different focus. For example, a specific feature in the model is the focus on long-run capacity usage that differs from the previous studies on short-run market power. The closest study to the model is from California's wholesale electricity markets that, however, uses different methodology. Work is constructed as follows.

Synthesis of Cost-Optimal Shell-and-Tube Heat Exchangers

Synthesis of cost-optimal shell-and-tube heat exchangers is a difficult task since it involves a large number of parameters. An attempt is made in this article to simplify the process of choosing the parameter values that will minimize the cost of any heat exchanger satisfying a given heat duty and a particular set of constraints. The simplification is based on decoupling of the geometric and the thermal aspects of the problem. The concept of curves for cost-optimal design is introduced and is shown to simplify the synthesis process for shell-and-tube heat exchangers.

An optimal local approximation algorithm for max-min linear programs

In a max-min LP, the objective is to maximise ω subject to Ax ≤ 1, Cx ≥ ω1, and x ≥ 0 for nonnegative matrices A and C. We present a local algorithm (constant-time distributed algorithm) for approximating max-min LPs. The approximation ratio of our algorithm is the best possible for any local algorithm; there is a matching unconditional lower bound.

Optimal Use of Treatment Modalities and Treatment Results of Osteosarcoma and Soft Tissue Sarcomas

Soft tissue sarcomas are malignant tumours of mesenchymal origin. Because of infiltrative growth pattern, simple enucleation of the tumour causes a high rate of local recurrence. Instead, these tumours should be resected with a rim of normal tissue around the tumour. Data on the adequate margin width are scarce. At Helsinki University Central Hospital (HUCH) a multidisciplinary treatment group started in 1987. Surgical resection with a wide margin (2.5 cm) is the primary aim. In case of narrower margin radiation therapy is necessary. The role of adjuvant chemotherapy remains unclear. Our aims were to study local control by the surgical margin and to develop a new prognostic tool to aid decision-making on which patients should receive adjuvant chemotherapy. Patients with soft tissue sarcoma of the extremity or the trunk wall referred to HUCH during 1987-2002 form material in Studies I and II. External validation material comes from the Lund university sarcoma registry. The smallest surgical margin of at least 2.5 centimetres yielded local control of 89 per cent at five years. Amputation rate was 9 per cent. The proposed prognostic model with necrosis, vascular invasion, size on a continuous scale, depth, location and grade worked well both in Helsinki material and in the validation material, and it also showed good calibration. Based on the present study, we recommend the smallest surgical margin of 2-3 centimetres in soft tissue sarcoma irrespective of grade. Improvement in local control was present but modest in margins wider than 1 centimetre. In cases where gaining a wider margin would lead to a considerable loss of function, smaller margin is to be considered combined to radiation therapy. Patients treated with inadequate margins should be offered radiation therapy irrespective of tumour grade. Our new prognostic model to estimate 10-year survival probability in patients with soft tissue sarcoma of the extremities or trunk wall showed good dicscrimination and calibration. For time being the prognostic model is available for scientific use and further validations. In the future, the model may aid in clinical decision-making. For operable osteosarcoma, neoadjuvant multidrug chemotherapy followed by delayed surgery and multidrug adjuvant chemotherapy is the treatment of choice. Overall survival rates at five years are approximately 75 per cent in modern trials with classical osteosarcoma. All patients diagnosed and reported to the Finnish Cancer Registry with osteosarcoma in Finland during 1971-2005 form the material in Studies III and IV. Limb-salvage rate increased from 23 per cent to 78 per cent during 1971-2005. The 10-year sarcoma-specific survival for the whole study population improved from 32 per cent to 62 per cent. It was 75 per cent for patients with a local high-grade osteosarcoma of the extremity diagnosed during 1991-2005. This study outlines the improved prognosis of osteosarcoma patients in Finland with modern chemotherapy. The 10-year survival rates are good also in an international scale. Nonetheless, their limb-salvage rate remains inferior to those seen for highly selected patient series. Overall, the centralisation of osteosarcoma treatment would most likely improve both survival and limb-salvage rates even further.