WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Microstrip Stub Filter Design with Enhanced Performance Inspired by SIW Structures Operating at 1.93 GHz GSMBand(Gazi Univ, 2026-03-29) Tosun, Huseyin; Yentur, Abdulkadir; Kilic, Veli TayfunThis paper reports a microstrip stub filter design operating at 1.93 GHz GSM band with enhanced performance inspired by SIW structures. In the designed filter additional vias are placed around the microstrip lines to enhance the encasing of the electromagnetic fields while propagating through the filter to develop the filter performance. The filter was examined with electromagnetic simulations for various numbers of vias and different via to microstrip line distances. Results show that the maximum transmission coefficient (S21 parameter) magnitude value reached in the pass band of the filter increases with the number of the vias and as the vias get closer to the lines. On the other hand, when the via number increases and the space between them and the lines narrows, the frequency at which the maximum S21 value is attained shifts to lower frequencies. The designed filters were manufactured, too. Results obtained in the measurements agree well with the simulation results. Additionally, a receiver system operating at 1.93 GHz band was constructed. System experiments were carried out with the constructed prototype for the manufactured filters. Results show that a greater signal level in the filter pass band is achieved and unwanted signals outside the filter pass band are suppressed more in the system where the filter with vias is used instead of the filter without any additional via. The findings indicate that the designed filters inspired by SIW structures are promising for applications requiring high signal quality.Article Fluctuations in the European Housing Market: Forecasting the House Price Index Change with Time-Series Models(Gazi Univ, 2026-03-15) Soylemez, Ismet; Nalici, Mehmet Eren; Unlu, RamazanThis study presents a comparative analysis of a time series models for forecasting changes in the Housing Price Index (HPI) in 27 European countries. Accurate HPI forecasting is essential for the development of effective policies and investment strategies. The study uses quarterly data from Q4 2013 to Q3 2024. Methodologically, the stationarity of the data is tested using the Dickey-Fuller test and differencing is applied to non-stationary series. The ARIMA, Holt Linear Trend, Additive Damped Trend and Exponential Smoothing models are evaluated based on the lowest mean squared error (MSE) value for each country. The findings confirmed the heterogeneous structure of the European housing market, showing that no single model is suitable for all countries. The ARIMA model provided the most accurate results for nine countries, while the Holt Linear Trend and Additive Damped Trend models performed best in seven countries each. Forecasts for the period 2025-2026 are generated based on these results. This study highlights the importance of adopting country-specific and adaptable forecasting approaches to accommodate the varying dynamics of European housing markets.Article Citation - WoS: 2Machine Learning Based Network Intrusion Detection With Hybrid Frequent Item Set Mining(Gazi Univ, 2024-10-02) Firat, Murat; Bakal, Gokhan; Akbas, Ayhan; Bakal, MehmetWith the development and expansion of computer networks day by day and the diversity of software developed, the damage that possible attacks can cause is increasing beyond the predictions. Intrusion Detection Systems (STS/IDS) are one of the practical defense tools against these potential attacks that are constantly growing and diversifying. Thus, one of the emerging methods among researchers is to train these systems with various artificial intelligence methods to detect subsequent attacks in real time and take the necessary precautions. However, the ultimate goal is to propose a hybrid feature selection approach to improve the classification performance. The raw dataset originally enclosed 85 descriptor features (attributes) for classification. These attributes are extracted using CICFlowMeter from a PCAP file where network traffic is recorded for data curation. In this study, classical feature selection methods and frequent item set mining approaches were employed in feature selection for constructing a hybrid model. We aimed to examine the effect of the proposed hybrid feature selection approach on the classification task for the network traffic data containing ordinary and attack records. The outcomes demonstrate that the proposed method gained nearly 3% improvement when applied with the Logistic Regression algorithm on classifying more than 225,000 records.Article Loss Calculation Technique With Randomize Load Curves(Gazi Univ, 2017) Onen, AhmetCalculating feeder losses accurately is an important part of evaluating designs for electric power distribution systems. Historically, these losses have been calculated one of three ways: (1) using a peak load calculation and the load factor method, (2) using customer class statistics normalized for a month, season, or year, or (3) using customer class statistics together with feeder measurements to reflect the variation in load every hour of the year. The first two methods require far less data but provide far less accuracy than the third method. In this paper, the authors present a method of calculating losses that achieves better accuracy than the first two methods without the large data requirements of the third method.Article Citation - WoS: 10Self-Healing Performance of Biogranule Containing Microbial Self-Healing Concrete Under Intermittent Wet/Dry Cycles(Gazi Univ, 2021) Ersan, Yusuf CagatayDevelopment of self-sensing and self-healing concrete is essential to minimize the labour-intensive monitoring and repair activities conducted for the maintenance of concrete structures. A type of self-healing concrete can be achieved by using microbial agents that induce calcium carbonate precipitation inside a concrete crack. Recently, biogranules consist of nitrate reducing microorganisms were presented as a new generation microbial healing agent and biogranule containing specimens revealed decent healing performance under completely submerged conditions. However, their performance under intermittent wetting conditions, a common case for various concrete structures, remains unknown. This study presents the self-healing performance of biogranule containing biomortar specimens under intermittent wet/dry conditions. In-house produced biogranules were incorporated into mortar specimens at a dose of 1.45% w/w cement (1.00% of bacteria w/w cement) and self-healing performance of cracked specimens were investigated under alternating wet/dry conditions for a crack width range of 50 to 600 um. Upon alternating wet/dry treatment for 4 weeks, cracks up to a 400 um crack width were effectively healed in biomortar specimens. Their water tightness regain was 44% better than control specimens due to their enhanced healing performance. Overall, non-axenic biogranules appear to be useful in development of self-healing bioconcrete for applications under spraying or intermittent wetting conditions.Article Ball Lens Based Mobile Microscope(Gazi Univ, 2016) Icoz, KutayIn this paper we report a low cost, simple and mobile microscope based on attachment of a ball lens to a cell phone. The system's noise and parameters affecting the image quality is investigated. The ball lens provides approximately 100X magnification and together with the cell phone's integrated lens and image sensor, 3,4-micron resolution is reached. The field-of-view of the system is 1500x1500 mu m where the price of the ball lens and the holder is less than 10 cents. By using this system as an optical light microscope, we are able to acquire images of micro particles and micro sensors. When combined with image processing methods, this optical system is capable of doing complex analysis as an alternative to commercial optical light microscopes.