Gruvrätten vid Stora Kopparberget 1641-1682 : en undersökning över rannsakade brott och utdömda straff

The purpose of this essay is to examine and explain how the Swedish mining court of Stora Kopparberget (the Great Copper Mountain) implemented its judicial legislation between 1641-1682. Questions are asked about which counts of indictments the court tried, which sentences they handed out, in what quantities and how these results looks in comparison with other contemporary courts. The index cards of the court judicial protocols are the primary source of information. The methods are those of quantity- and comparative analysis.The results show that theft of copper ore was the most common crime ransacked by the court. Other common crimes were (in order): sin of omission, transgression of work directions, fights, slander and disdain, trade of stolen ore, failing appearance in court etc.Fines were by far the most common sentence followed by shorter imprisonments, gauntlets, loss of right to mine possession, twig beating, loss of work, penal servitude, banishment, “wooden horse riding” and finally military transcription. Even though previous re-search, in the field of Swedish specialized courts, is almost non existent evidence confirms great similarities between the Stora Kopparberget mining court and Sala mining court. This essay will, hopefully, enrich our knowledge of specialized courts, of 17th century mining industry and society and let us reach a broader understanding of the working conditions of the mountain.

En sociologisk förståelse av förlåtelse och försoning

Forgiveness and reconciliation in a sociological context Are forgiveness and reconciliation left to the theologians to define or can these concepts also be genuine concepts in sociology? In spite of the fact that sociology and social psychology have a lot of research about relationship, interaction and groups, there is not much research about forgiveness and reconciliation. This article presents the understanding of how relations can be revived, if once broken, if using these conceptions. The discussion also includes the concepts of shame and guilt and even confidence, particularly in relations where you find victim and perpetrator. The discussion is developed in a perspective of symbolic interactionism with examples from sociological research about men´s violence against women and adults, especially fathers, abuse to their daughters. In this article the perpetrator feels guilt and the victim shame and the feeling of guilt makes the perpetrator to ask for forgiveness. When hate and hard feelings have come to an end, the reconciliation can occur as a consequence of the forgiveness.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.