355 research outputs found
A történeti Magyarország statisztikai adatforrásai
Tanulmányunkban a 19. század vĂ©gi, 20. század eleji magyar törtĂ©nelem tanulmányozásának nĂ©gy kiemelt forráscsoportjával kĂvánunk foglalkozni. A földadĂł kataszter anyagai, a felekezeti Ă©s polgári anyakönyvek, a nĂ©pszámlálási adatok, valamint az Ăşn. "gazdacĂmtárak" elhasználhatĂłságát fogjuk vizsgálni. A forráscsoportok általános jellemzĂ©sĂ©n tĂşl kitĂ©rĂĽnk az egyes forrásokban rejlĹ‘ kutatási lehetĹ‘sĂ©gekre, s bemutatjuk elhasználhatĂłságuk korlátait is. Az elemzĂ©s során elsĹ‘sorban saját kutatási eredmĂ©nyeinkre támaszkodunk. A fentieken tĂşl jelen Ărás cĂ©lja annak megvilágĂtása, hogy a források minĂ©l nagyobb körĂ©t bevonĂł, komplexitásra törekvĹ‘ kutatás segĂtsĂ©gĂ©vel kikĂĽszöbölhetĹ‘k az egyes forráscsoportok hiányosságai, s Ăgy egy teljesebb kĂ©pet alkothatunk a vizsgált korszakrĂłl. A kijelölt nĂ©gy forrástĂpus közĂĽl kiemelt szerepet szánunk a kataszteri anyagok Ă©s a földtulajdoni Ă©s gazdasági cĂmtárak bemutatásának
Challenges and Possibilities of Overtaking Strategies for Autonomous Vehicles
This paper present three distinct probability-based methods for decision making and trajectory planning layers of overtaking maneuvering functionality for autonomous vehicles. The computation time of the proposed decision-making algorithms may be high, because the number of describing parameters of the traffic situations may vary in a high range. The presented clustering-based, graph-based and dynamic-based methods differ in the complexity of their computation algorithms. Since the decision-making process may require considerable online computation effort, a neural-network-based approach is presented for implementation purposes
Runtime exception detection in Java programs using symbolic execution
Most of the runtime failures of a software system can be revealed during test execution only, which has a very high cost. In Java programs, runtime failures are manifested as unhandled runtime exceptions. In this paper we present an approach and tool for detecting runtime exceptions in Java programs without having to execute tests on the software. We use the symbolic execution technique to implement the approach. By executing the methods of the program symbolically we can determine those execution branches that throw exceptions. Our algorithm is able to generate concrete test inputs also that cause the program to fail in runtime. We used the Symbolic PathFinder extension of the Java PathFinder as the symbolic execution engine. Besides small example codes we evaluated our algorithm on three open source systems: jEdit, ArgoUML, and log4j. We found multiple errors in the log4j system that were also reported as real bugs in its bug tracking system
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