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AR Based App for Tourist Attraction in ESKI CARSI (Safranbolu)
(Copernicus Gesellschaft Mbh, 2016) Polat, Merve; Karas, Ismail Rakip; Kahraman, Idris; Alizadehashrafi, Behnam
This research is dealing with 3D modeling of historical and heritage landmarks of Safranbolu that are registered by UNESCO. This is an Augmented Reality (AR) based project in order to trigger virtual three-dimensional (3D) models, cultural music, historical photos, artistic features and animated text information. The aim is to propose a GIS-based approach with these features and add to the system as attribute data in a relational database. The database will be available in an AR-based application to provide information for the tourists.
A Deep Learning Approach for Classification of Dentinal Tubule Occlusions
(Taylor & Francis Inc, 2022) Duru, Anday; Karas, Ismail Rakip; Karayurek, Fatih; Gulses, Aydin
This study aimed to develop a novel deep learning model for reliable quantification of dentinal tubule occlusions instead of manual assessment techniques, and the performance of the model was compared to other methods in the literature. Ninety-six dentin samples were cut and prepared with desensitizing agents to occlude dentinal tubules on different levels. After obtaining images via scanning electron microscope (SEM), 2793 single dentinal tubule images with 48 x 48 resolution were segmented and labeled. Data augmentation techniques were applied for improvement in the learning rate. The augmented data having a total of 10700 images belonging to five classes were used as the network training dataset. The proposed convolutional neural network (CNN) is a class of deep learning model and was able to classify the degree of dentinal tubule occlusions into five classes with an overall accuracy rate of 90.24%. This paper primarily focuses on developing a CNN architecture for detecting the level of dentin tubule occlusions imaged by SEM. The results showed that the proposed CNN architecture is an immensely successful alternative and allowed for objective and automatic classification of segmented dentinal tubule images.
Dijkstra algorithm interactive training software development for network analysis applications in GIS
(Sila Science, 2011) Karas, Ismail Rakip; Demir, Sait
Process of route optimization is one of the basic applications of Network Analyses in Geographic Information Systems. In mathematical background of network analysis applications are graph theory and graph algorithms. Primary graph algorithm employed in process of route optimization is Dijkstra's Algorithm. Dijkstra's Algorithm is placed on the top of linear methods which yield exact solutions. Geographic Information Systems analyses such as the shortest route, the shortest duration and route with the least traffic are solved through Dijkstra's Algorithm. In this study, an interactive training software program, developed for educational use in Geographic Information Systems and Graph Theory classes at postgraduate degree, is introduced. This software provides students with the opportunity to use Dijkstra's Algorithm on graphs which they have designed by themselves and teaches details of algorithm, its working principles and structure of data to them, step by step, through interactive messages and graphics.
Dual-Determination of Modulation Types and Signal-to-Noise Ratios Using 2D-ASIQH Features for Next Generation of Wireless Communication Systems
(Ieee-Inst Electrical Electronics Engineers Inc, 2021) Almohamad, Tarik Adnan; Salleh, Mohd Fadzli Mohd; Mahmud, Mohd Nazri; Karas, Ismail Rakip; Shah, Nor Shahida Mohd; Al-Gailani, Samir Ahmed
In order to pursue rapid development of the new generation of wireless communication systems and elevate their security and efficiency, this paper proposes a novel scheme for automatic dual determination of modulation types and signal to noise ratios (SNR) for next generations of wireless communication systems, fifth-generation (5G) and beyond. The proposed scheme adopts unique signatures depicted in two-dimensional asynchronously sampled in-phase-quadrature amplitudes' histograms (2D-ASIQHs)-based images and applies the support vector machines (SVMs) tool. Along with the estimation of the instantaneous SNR values over 0-35 dB range, the determination of nine modulation types that belong to different modulation categories i.e., phase-shift keying (Binary-PSK, Quadrature-PSK, and 8-PSK), amplitude-shift keying (2-ASK and 4-ASK) and quadrature-amplitude modulation (4-QAM, 16-QAM, 32-QAM, and 64-QAM) could be achieved by this scheme. The application of this scheme has been simulated using a channel model that is impaired by additive white Gaussian noise (AWGN) and Rayleigh fading, covering a broad range of SNRs of 0-35 dB. The performance of this dual-determination scheme shows high modulation recognition accuracy and low mean SNR estimation error. Therefore, it can be a better alternative for designers of next generation wireless communication systems.
Employing Neural Networks Algorithm for LULC Mapping
(Univ Latvia, 2020) Abujayyab, Sohaib K. M.; Karas, Ismail Rakip
Land use/land cover (LULC) maps represent a primary requirement for several geospatial applications around the world such as change detection, time series analysis, environment, and urban researches. Mapping LULC from remotely sensed data based on satellite image classification handle the rapid changes in extensive geographical areas. Several effective and efficient mechanisms suggested for supervised satellite image classification. The neural networks machine learning algorithm became a major method in supervised satellite image classification. The objective of this article is to employ neural networks as a machine learning algorithm for LULC mapping. The study applied in Ankara area, which is the capital city of Turkey. This work utilized a free Landsat 8 satellite image with the Operational Land Imager OLI sensor to implement the analysis. The image was obtained and processed in ArcGIS software. Then, the machine learning data set developed using Python scripting language. Every band out of 8 bands from Landsat 8 image considered as an explanatory variable, while the output variable defined based on visual interpretation. The training dataset built based on the signature file and random sample points. The training dataset divided into three sections, for training, for validation and the last section for testing. The training and testing processes were implemented using Google-Tensor Flow Keres library from Anaconda distribution. Feedforward neural network structure implemented with 500 neurons in the hidden layer. Confusion matrix used as accuracy assessment metrics to measure the performance of the developed model. The overall accuracy of the developed model was 92%. In terms of overall accuracy and robustness, the neural networks algorithm was effectively implemented and the LULC map produces. The model gained high accuracy that it is satisfied with the geospatial accuracy target. The consequence showed the competence of neural networks algorithm to generating LULC maps from Landsat 8 satellite images.
An evacuation system for extraordinary Indoor Air Pollution Disaster Circumstances
(Disaster Advances, 2012) Karas, Ismail Rakip; Batuk, Fatmagul; Abdul-Rahman, Alias
The problem of evacuating the buildings through the shortest path with safety has become more important than ever in a case of indoor air pollution incidents (i.e. fire, gas leak, airlessness, smother) taken place in complex and tall buildings of today's world. In this paper, it is aimed to present a 3D interactive human navigation, and evacuation system which generates an optimum path in 3D modeled buildings and provides 3D visualization and simulation. The system generates and transmits the guiding expression to the mobile devices such as PDA's, laptops etc. via internet. In order to evaluate its performance in a case of extraordinary indoor air pollution circumstance, the system was tested on a complex building model by using GPRS and WIFI internet connections based on the web technologies.
A genetic algorithm approach for finding the shortest driving time on mobile devices
(Academic Journals, 2011) Karas, Ismail Rakip; Atila, Umit
Recently, with the increasing interest in using handheld devices, the application of navigation systems that provide driving information to the drivers has become widespread in daily life. An efficient route guidance system should consider the influential factors of traffic flow such as traffic density and allowable velocity limits of the roads. As the number of influential factors and amount of nodes in road network increase, the computational cost increases. On navigation systems, using handheld devices with limited processing speed and memory capacity, it is not feasible to find the exact optimal solution in real-time for the road networks with excessive number of nodes using deterministic methods such as Dijkstra algorithm. This paper proposes a Genetic Algorithm approach applied to a route guidance system to find the shortest driving time. Constant length chromosomes have been used for encoding the problem. It was found that the mutation operator proposed in this algorithm provided great contribution to achieve optimum solution by maintaining the genetic diversity. The efficiency of the genetic algorithm was tested by applying it on the networks with different sizes.
GIS-Based Terrain Analysis of Balakot Region after Occurred Landslide Disaster in October 2005
(Mehran Univ Engineering & Technology, 2011) Soomro, Abdul Salam; Rajput, Abdul Qadeer Khan; Karas, Ismail Rakip
The landslide susceptibility models require the appropriate and reliable terrain analytical based study of the landslides prone areas using SRTM (Shuttle Radar Topography Mission) data, based on certain GIS (Geographical Information Systems) and remote sensing techniques. This research paper focuses on the analysis of the terrain conditions of Balakot region. The analytical operations have been used in the different phases: (i) Extracting the study area from the large data; (ii) preparing it into grid format; (iii) developing contour lines with certain contour intervals (iv) Reclassification of it into required classes and (v) preparation of digital terrain model with its different required various supplementary models for analyzing the terrain conditions of the study area located in Mansehra district, north part of Pakistan where the great earthquake induced landslide disaster occurred in October 2005. This analytical study has notified the different sensitive issues concerning to the critical slope angles, variation in the elevation and the surface of study area. The various distinctions in the terrain phenomenon validate the occurred and probable landslides because the topography of such study area can predict the various probable landslide hazards, vulnerability and risk threats in the region again. This analytical study can be useful for the decisive authorities by becoming pro-active to rebuild the region to mitigate the expected losses from the natural disaster.
Identification of column edges of DNA fragments by using K-means clustering and mean algorithm on lane histograms of DNA agarose gel electrophoresis images
(Spie-Int Soc Optical Engineering, 2015) Turan, Muhammed Kamil; Sehirli, Eftal; Elen, Abdullah; Karas, Ismail Rakip
Gel electrophoresis (GE) is one of the most used method to separate DNA, RNA, protein molecules according to size, weight and quantity parameters in many areas such as genetics, molecular biology, biochemistry, microbiology. The main way to separate each molecule is to find borders of each molecule fragment. This paper presents a software application that show columns edges of DNA fragments in 3 steps. In the first step the application obtains lane histograms of agarose gel electrophoresis images by doing projection based on x-axis. In the second step, it utilizes k-means clustering algorithm to classify point values of lane histogram such as left side values, right side values and undesired values. In the third step, column edges of DNA fragments is shown by using mean algorithm and mathematical processes to separate DNA fragments from the background in a fully automated way. In addition to this, the application presents locations of DNA fragments and how many DNA fragments exist on images captured by a scientific camera.
Integration of CityGML and Oracle Spatial for implementing 3D network analysis solutions and routing simulation within 3D-GIS environment
(Taylor & Francis Ltd, 2013) Atila, Umit; Karas, Ismail Rakip; Abdul-Rahman, Alias
3D navigation within a 3D-GIS environment is increasingly getting more popular and spreading to various fields. In the last decade, especially after the 9/11 disaster, evacuating the complex and tall buildings of today in case of emergency has been an important research area for scientists. Most of the current navigation systems are still in the 2D environment and that is insufficient to visualize 3D objects and to obtain satisfactory solutions for the 3D environment. Therefore, there is currently still a lack of implementation of 3D network analysis and navigation for indoor spaces in respect to evacuation. The objective of this paper is to investigate and implement 3D visualization and navigation techniques and solutions for indoor spaces within 3D-GIS. For realizing this, we have proposed a GIS implementation that is capable of carrying out 3D visualization of a building model stored in the CityGML format and perform analysis on a network model stored in Oracle Spatial. The proposed GUI also provides routing simulation on the calculated shortest paths with voice commands and visual instructions.
A Knowledge Based Decision Support System: 3D GIS Implementation for Indoor Visualisation and Routing Simulation
(Univ Utari Malaysia-Uum, 2014) Atila, Umit; Karas, Ismail Rakip; Rahman, Alias Abdul
In this study, a knowledge management based Decision Support System has been suggested. By collecting the data of people, event and properties of building, a 3D navigation system has been developed to support building management and users during the extraordinary circumtances. Most of the current navigation systems are still in the 2D environment and that is insufficient to visualize 3D objects and to obtain satisfactory solutions for the 3D environment. Therefore, there is currently still a lack of implementation of 3D network analysis and navigation for indoor spaces in respect to evacuation. 3D navigation within a 3D-GIS environment (Three Dimensional Geographical Information Systems) is increasingly getting more popular and spreading to various fields. In the last decade, especially after the 9/11 disaster; evacuating the complex and tall buildings of today in case of emergency has been an important research area for scientists. The objective of this paper is to implement 3D visualization and navigation techniques and solutions for indoor spaces within 3D-GIS. For realizing this, we have proposed a GIS implementation that is capable of carrying out 3D visualization of a building model stored in the CityGML format and perform analysis on a network model stored in Oracle Spatial. The proposed GUI also provides routing simulation on the calculated shortest paths with voice commands and visual instructions.
Modification of Manual Raindrops Type Observatory Ombrometer with Ultrasonic Sensor HC-SR04
(Science & Information Sai Organization Ltd, 2019) Yudhana, Anton; Rahmayanti, Jessy; Akbar, Son Ali; Mukhopadhyay, Subhas; Karas, Ismail Rakip
Water, in any way it comes, is important for the life of all living things. Indonesia is an area of tropical equatorial with a variation of rain, which is quite high. The regularity of the distribution of rainfall is one of the aspects most important to the activity of the community. As the development of technology, the intensity of rainfall can be measured manually using Ombrometer Observatory tool. The manual tool for measuring the rain precipitation, Ombrometer Observatorium, is used to take data manually. Samples should be taken at 7.00 a.m. everyday using a measuring cup to know the height of the water contained. However, the type is prone to error at the high rainfall intensity, since the drainage of the samples is conducted every 24 hours. Therefore, much water is wasted. To solve the problem, a modification of a rainfall gauge was made, that is Ombrometer Observatory with ultrasonic sensor HC-SR04. The height of the water in the container is sent through a server of which the data is stored in the database every ten minutes to reduce the risk of evaporation. It also minimizes the error in measuring the rainfall intensity. The results have been compared to the ones by BMKG (Meteorology, Climatology, and Geophysics Agency). The correlation value of the measurement ratio reached 0.9739 or 97.39%.
Real-Time Protozoa Detection from Microscopic Imaging Using YOLOv4 Algorithm
(Mdpi, 2024) Kahraman, Idris; Karas, Ismail Rakip; Turan, Muhammed Kamil
Protozoa detection and classification from freshwaters and microscopic imaging are critical components in environmental monitoring, parasitology, science, biological processes, and scientific research. Bacterial and parasitic contamination of water plays an important role in society health. Conventional methods often rely on manual identification, resulting in time-consuming analyses and limited scalability. In this study, we propose a real-time protozoa detection framework using the YOLOv4 algorithm, a state-of-the-art deep learning model known for its exceptional speed and accuracy. Our dataset consists of objects of the protozoa species, such as Bdelloid Rotifera, Stylonychia Pustulata, Paramecium, Hypotrich Ciliate, Colpoda, Lepocinclis Acus, and Clathrulina Elegans, which are in freshwaters and have different shapes, sizes, and movements. One of the major properties of our work is to create a dataset by forming different cultures from various water sources like rainwater and puddles. Our network architecture is carefully tailored to optimize the detection of protozoa, ensuring precise localization and classification of individual organisms. To validate our approach, extensive experiments are conducted using real-world microscopic image datasets. The results demonstrate that the YOLOv4-based model achieves outstanding detection accuracy and significantly outperforms traditional methods in terms of speed and precision. The real-time capabilities of our framework enable rapid analysis of large-scale datasets, making it highly suitable for dynamic environments and time-sensitive applications. Furthermore, we introduce a user-friendly interface that allows researchers and environmental professionals to effortlessly deploy our YOLOv4-based protozoa detection tool. We conducted f1-score 0.95, precision 0.92, sensitivity 0.98, and mAP 0.9752 as evaluating metrics. The proposed model achieved 97% accuracy. After reaching high efficiency, a desktop application was developed to provide testing of the model. The proposed framework's speed and accuracy have significant implications for various fields, ranging from a support tool for paramesiology/parasitology studies to water quality assessments, offering a powerful tool to enhance our understanding and preservation of ecosystems.
Recognizing Human Emotion patterns by applying Fast Fourier Transform based on Brainwave Features
(Ieee, 2019) Yudhana, Anton; Mukhopadhyay, Subhas; Karas, Ismail Rakip; Azhari, Ahmad; Mardhia, Murein Miksa; Akbar, Son Ali; Muslim, Akbar
The natural ability of humans to receive messages from the surrounding environment can be obtained through the senses. The senses will respond to stimuli received in various conditions including emotional conditions. Psychologically, recognizing human emotions directly can be assessed from several criteria, such as facial expressions, sounds, or body movements. This research aims to analyze human emotions from the biomedical side through brainwave signals using EEG sensors. The EEG signal obtained will be extracted using Fast Fourier Transform and first-order statistical features. Monitoring of EEG Signals is obtained by grouping based on four emotional conditions (normal, focus, sadness and shock emotions). The results of this research are expected to help improve users in knowing their mental state accurately. The development of this kind of emotional analysis has the potential to create wide applications in the future environment. Research results have shown and compared frequency stimuli from normal emotions, sadness, focus and shock in a variety of situations.
A review on change detection method and accuracy assessment for land use land cover
(Elsevier, 2021) Chughtai, Ali Hassan; Abbasi, Habibullah; Karas, Ismail Rakip
The assessment of land use land cover change is extremely important for understanding the relationship between humans and nature. The enormous changes at a regional scale and advancements in technology have encouraged researchers to gather more information. The remote sensing technology and GIS tools cooperatively have made it easier to monitor the changes in land use land cover (LULC) from past to present. This technology has unraveled the changes at the regional and global level and has also contributed tremendous benefits to the scientific community. A variety of change detection algorithms have been used in the history of remote sensing to detect changes at earth's surface and newer techniques are still in process. The data from remote sensing satellites are the primary sources that provide an opportunity to acquire information about LULC change in recent decades, which extensively use different algorithms according to the research needs. The selection of appropriate change detection method is highly recommended in every remote sensing project. This review paper begins with the traditional pre and post-classification change detection techniques related to LULC information at the regional level. Therefore, this paper evaluated the mostly used change detection method among all others to find remarkable results. Thus the review concludes the post-classification change detection method using maximum likelihood classifier (MLC) supervised classification is applicable in all cases. The comparative analysis was also performed in a selected region having multiple land features during review in which MLC results best in comparison to others. MLC is the most commonly used technique from the past till present that has achieved high accuracy in all regions comparatively to other techniques.
SmartEscape: A Mobile Smart Individual Fire Evacuation System Based on 3D Spatial Model
(Mdpi, 2018) Atila, Umit; Ortakci, Yasin; Ozacar, Kasim; Demiral, Emrullah; Karas, Ismail Rakip
We propose SmartEscape, a real-time, dynamic, intelligent and user-specific evacuation system with a mobile interface for emergency cases such as fire. Unlike past work, we explore dynamically changing conditions and calculate a personal route for an evacuee by considering his/her individual features. SmartEscape, which is fast, low-cost, low resource-consuming and mobile supported, collects various environmental sensory data and takes evacuees' individual features into account, uses an artificial neural network (ANN) to calculate personal usage risk of each link in the building, eliminates the risky ones, and calculates an optimum escape route under existing circumstances. Then, our system guides the evacuee to the exit through the calculated route with vocal and visual instructions on the smartphone. While the position of the evacuee is detected by RFID (Radio-Frequency Identification) technology, the changing environmental conditions are measured by the various sensors in the building. Our ANN (Artificial Neural Network) predicts dynamically changing risk states of all links according to changing environmental conditions. Results show that SmartEscape, with its 98.1% accuracy for predicting risk levels of links for each individual evacuee in a building, is capable of evacuating a great number of people simultaneously, through the shortest and the safest route.
Study the Effect of Noise on Compressed Images Used in Smart Application Based on JPEG Standard
(Springer International Publishing Ag, 2022) Iman, Elawady; Karas, Ismail Rakip
Recently a lot of smart applications based on using a data set, in the most of the cases, the data set is images, like in smart systems based on detection, recognition and auto decision, also in the systems based on data transmission and smart networks, according to those applications the most critical problem is our ability to save this data from the noise effect, which really could create wrong message or makes our data unclear for proving and analysis, however using data in its original format could take long time, which will consume our storage capacity, the bandwidth usage, processing resources and the energy used for the operation, this will lead us to use a kind of compression that gives us the best solution for all the drawbacks mentioned before. The JPEG compression gets a lot of attention in this term, since its produce a high-compression ratio with reconstructed image close to the original one, due to using DCT transform, which give us a good representation of the image in the frequency domain, however with all this benefits the JPEG standard is so sensitive to the noise effect, since the encoded data related to each other, its look like a related chain, so the smallest perturbation causes a tremendous collapse in terms of decoding (reconstruction of image), in this paper we are going to test and study the data sensitivity to the channel noise based on transmitted using JPEG compression, which allows us to offer efficient techniques in terms of restoration or data correction.
Use of geographic information systems in iron and steel industry
(Sila Science, 2012) Karas, Ismail Rakip; Demir, Sait
Geographic Information Systems are information systems in which spatial data and non-spatial data are managed together. These data related to areas of factoring and production are allowed to be stored, processed, examined and analyzed together with the help of Geographic Information Systems, in contradistinction to other information systems. In our day, the use of Geographic Information Systems is becoming widespread in industrial foundations spread over large areas as a result of the fact that it contains extensive spatial data. Administrations such as inter-facility planning, synchronization of work groups, determining the most suitable areas through the use of environmental and spatial analyses based on location, optimization of production and transportation are some examples of this sort of usage. This paper is going to focus on the usability of Geographic Information Systems in iron-steel industry and bring forward proposals about Geographic Information Systems applications that can be implemented in an iron-steel plant. Advantages that will be gained through the use of Geographic Information Systems, time, cost and performance are going to be examined.
Wireless Communication System For Monitoring Heart Rate In The Detection And Intervention Of Emotional Regulation
(Ieee, 2019) Al Irfan, Syahid; Yudhana, Anton; Mukhopadhyay, Subhas Chandra; Karas, Ismail Rakip; Wati, Dewi Eko; Puspitasari, Intan
Based on data from the Indonesian Child Protection Commission (KPAI) cases of violence against children from 2010 to 2015 continued to increase which from 2010 only 171 cases increased to 2015 as many as 6006 which means that every year cases of violence against children continue to increase at least 1000 cases each year. Changes in heart rate in humans can be known through the flow of blood that flows in blood vessels. When the heart beats, the flow in the blood vessels will move so that's when the heart rate can be measured. In this study, a wireless heart rate condition data collection system will be developed and a heart rate condition sensing device that has the same capabilities as devices used in general medical activities. From the results of testing, the system designed the process of sending data goes well where of the 20 devices that send data all of that can be sent properly with a time interval of 1 second but for the sensor reading process some problem need to be solved such as interruptions in the data collection process when participants doing activities and some constraints on the choice of devices used on the server.

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