Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Conference Object Detection of Urban Change Using Remote Sensing and Gis: Izmir Case(Taylor and Francis Ltd., 2008) Tarhan, Çiğdem; Arkon, Cemal; Çelik, M.; Gümüştekin, Şevket; Tecim, V.This study is an example of how land use changes could be detected via high resolution remotely sensed data. In order to perform "change detection" IKONOS satellite images, belonging to 2001 and 2004, have been used. An automated Graphical User Interface (GUI) has been created for detection of environment. Different image enhancement techniques and a fuzzy inference system have been combined in the GUI. The detection results are classified according to some basic levels such as 20-50% and 70%. Additionally, four different change detection algorithms have been applied which are pixel-based, object based, feature based. These algorithms have been examined according to change detection levels with different image enhancement techniques. At the end of the study, the results have been compared.Article Citation - WoS: 62Citation - Scopus: 70Railway Monitoring System Using Optical Fiber Grating Accelerometers(IOP Publishing Ltd., 2018) Yüksel, Kıvılcım; Kinet, Damien; Moeyaert, Veronique; Kouroussis, Georges; Caucheteur, ChristopheOptimal operation, reduced energy consumption, longer service availability, and high safety level are the major concerns in today's railway transport systems. Smart monitoring systems should address these issues without interrupting railway operability. Many successful works have been carried out to provide railway monitoring functions using fiber Bragg grating (FBG) sensors on rail. Most of them are based on strain measurement due to the train passage. This paper presents a highly sensitive means for railway monitoring based on vibration measurement. FBG accelerometers placed on sleeper have been employed as sensor heads, which significantly facilitated the field sensor installation work compared to the positioning on the foot of the rail. An optimized signal demodulation algorithm has been effectively used to extract from the accelerometer traces both the axle number and the average speed information. Excellent capability of the developed system to obtain both parameters has been demonstrated by the way of field trials carried out on a Belgian railway line, during its normal operation. Easy installation, multi-function diagnosis, good data integrity, and compatibility with fiber optic sensors make the proposed sensor a good candidate for railway monitoring applications.