History of cosmic ray research in Finland

The history of cosmic ray research in Finland can be traced back to the end of 1950s, when first ground-based cosmic ray measurements started in Turku. The first cosmic ray station was founded in Oulu in 1964 performing measurements of cosmic rays by a muon telescope, which was later complemented by a neutron monitor. Since the 1990s, several research centers and universities, such as The Finnish Meteorological Institute, Helsinki University of Technology, University of Oulu, University of Turku and University of Helsinki have been involved in space science projects, such as SOHO, AMS, Cluster, Cassini, BepiColombo, etc. At the same time, ground-based cosmic ray measurements have reached a new level, including a fully automatic on-line database in Oulu and a new muon measuring underground site in Pyhäsalmi. Research groups in Helsinki, Oulu and Turku have also extensive experience in theoretical investigations of different aspects of cosmic ray physics. Cosmic ray research has a 50-year long history in Finland, covering a wide range from basic long-running ground-based observations to high-technology space-borne instrumentation and sophisticated theoretical studies. Several generations of researchers have been involved in the study ensuring transfer of experience and building the recognized Finnish research school of cosmic ray studies.     

Power Generation?Some Tasks and Goals

Generating capacity additions planned for the 1970's and beyond include a high percentage of nuclear power plants. The light water reactor is the dominant type of commercial nuclear reactor being installed during the 1970's. Advancement to more efficient designs, such as the high-temperature gas-cooled reactor, is expected around 1980. Prospects for the breeder reactor and fusion energy systems dictate a major research and development effort. Attempts to control effluents from fossil-fired plants have resulted in a sharp increase in the use of low sulfur fuels. Research and development efforts are being intensified in an attempt to obtain a breakthrough in methods of stack emission control.     

A Data Compression Technique for Synthetic Aperture Radar Images

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.     

Variations of the magnetosheath ion flux and geomagnetic activity

The magnetosheath plays a dominant role in the Sun–Earth connection because the magnetosheath field and plasma actually interact with the magnetosphere. The interactions change the magnetospheric magnetic field from its nominal value through a long chain of different processes. The change is usually described by geomagnetic indices and thus it can be expected that these indices would reflect changes in the magnetosheath. The present paper analyzes the relation between geomagnetic activity characterized by changes of the K_p, D_ST and AE indices and ion flux measured in the night-side magnetosheath. The results suggest a weak dependence of the D_ST index on the ion flux in the inner magnetosheath that is connected with a magnetopause displacement. On the other hand, fluctuations of the ion flux in the analyzed frequency range do not correlate with any of the indices.     

Comparative study of productivity of the Rosetta target Comet 67P/Churyumov-Gerasimenko

In an attempt to evaluate correlations between several properties of comets we report the results of a cometary research involving a criterious analysis of gas and dust mass production rates in Comets 67P/Churyumov-Gerasimenko (main target of Rosetta Mission), 1P/Halley, Hyakutake (C/1996 B2), and 46P/Wirtanen and make a comparison between them.     

Adaptive Estimation for a System with Unknown Measu rement Bias

An adaptive state estimator for passive underwater tracking of maneuvering targets is developed. The state estimator is designed specifically for a system containing unknown or randomly switching biased measurements. In modeling the stochastic system, it is assumed that the bias sequence dynamics can be modeled by a semi-Markov process. By incorporating the semi-Markovian concept into a Bayesian estimation technique, an estimator consisting of a bank of parallel, adaptively weighted, Kalman filters has been developed. Despite the large and randomly varying measurement biases, the proposed estimator, provides an accurate estimate of the system states.     

Radar Track Acquisition Range

The track acquisiton range of a track-while-scan radar is defined as the range at which the cumulative probability of M detections in N scans is 90 percent. Track acquisition ranges for 2 out of 3, 2 out of 4, and 3 out of 4 detection criteria are presented for Swerling 0, 1, and 3 target models.     

Explicit solutions for some simple decentralized detection problems

A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems     

Accommodating controller malfunctions through fault tolerant control architecture

In previous work we have proposed a supervised globalized dual heuristic programming (GDHP) controller as a solution to the fault tolerant control (FTC) problem of nonlinear plants subject to abrupt and incipient faults capable of drastically modifying the system dynamics to maintain stability and performance. The neural network (NN) based adaptive critic controller presented the best choice for the flexibility and power necessary to accomplish the task, however no success guarantees can be made for the online training of neural weights for the unrestricted fault recovery problem. Built on the existing framework, we propose a novel supervisory system capable of detecting controller malfunctions before the stability of the plant is compromised. Furthermore, due to its ability to discern between controller malfunctions and faults within the plant, the proposed supervisor acts in a specific fashion in the event of a controller malfunction to provide new avenues with a greater probability of convergence using information from a dynamic model bank. The classification and distinction of controller malfunctions from the faults in the plant itself is achieved through an advanced decision logic based on three independent quality indexes. Proof-of-the-concept simulations over a nonlinear plant demonstrate the validity of the approach.