Breast cancer is one of the most common cancer types especially met in women. The number of breast cancer patients increases every year. Thus, to detect breast cancer at its early stages gains importance. Breast region detection is the pioneering step of breast cancer diagnosis researches performed via image processing techniques. The performance of computer-aided breast cancer diagnosis systems can be improved by exactly determining the breast region of interest. In this study, the goal is to determine a region of interest for breast MR images, in which one or more lesion can appear. The achieved region includes two breasts and lymph nodes. The proposed region of interest detection system is fully automatic and it utilizes several image processing techniques. At first, the local adaptive thresholding technique is applied to the noise-filtered grey level breast magnetic resonance images taken with ethical permissions from Sakarya Education and Research Hospital. After adaptive thresholding, connected component analysis is performed to exclude extra structures around the breast region as thorax area. This analysis selects the largest area in the binary image which corresponds to a gyrate region including breast area and lymph nodes over the backbone. Then, the integral of horizontal projection is calculated to determine an optimum horizontal line that allows setting the region of interest apart. In the following step, sternum midpoint is detected to separate the right breast from the left one. Finally, a masking operation is applied to get corresponding right and left breast regions in the original MR image. To evaluate the performance of the proposed study, the results of automatic region of interest detection system are compared with the manual region of interest selection performed by an expert radiologist. Dice similarity coefficient and Jaccard coefficient are used as performance criteria. According to the results, the proposed system can detect region of interest for computer-aided breast cancer diagnosis researches, exactly.
{"title":"Detection of Breast Region of Interest via Breast MR Scan on an Axial Slice","authors":"G. Çetinel, F. Mutlu, Sevda Gül","doi":"10.18100/ijamec.679142","DOIUrl":"https://doi.org/10.18100/ijamec.679142","url":null,"abstract":"Breast cancer is one of the most common cancer types especially met in women. The number of breast cancer patients increases every year. Thus, to detect breast cancer at its early stages gains importance. Breast region detection is the pioneering step of breast cancer diagnosis researches performed via image processing techniques. The performance of computer-aided breast cancer diagnosis systems can be improved by exactly determining the breast region of interest. In this study, the goal is to determine a region of interest for breast MR images, in which one or more lesion can appear. The achieved region includes two breasts and lymph nodes. The proposed region of interest detection system is fully automatic and it utilizes several image processing techniques. At first, the local adaptive thresholding technique is applied to the noise-filtered grey level breast magnetic resonance images taken with ethical permissions from Sakarya Education and Research Hospital. After adaptive thresholding, connected component analysis is performed to exclude extra structures around the breast region as thorax area. This analysis selects the largest area in the binary image which corresponds to a gyrate region including breast area and lymph nodes over the backbone. Then, the integral of horizontal projection is calculated to determine an optimum horizontal line that allows setting the region of interest apart. In the following step, sternum midpoint is detected to separate the right breast from the left one. Finally, a masking operation is applied to get corresponding right and left breast regions in the original MR image. To evaluate the performance of the proposed study, the results of automatic region of interest detection system are compared with the manual region of interest selection performed by an expert radiologist. Dice similarity coefficient and Jaccard coefficient are used as performance criteria. According to the results, the proposed system can detect region of interest for computer-aided breast cancer diagnosis researches, exactly.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129429719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, the use of multi-propellers has been increased, because of some basic advantages such as vertical take-off and landing, simple mechanical structure. In addition, different usage fields such as carrying an object and making video records over the cities. This paper exposes design and control of two different multi propeller systems and both systems have 12 rotors to carry more load. In first, all motors are arranged at identical angles in the same plane. In the other, the motors are mounted in two groups, eight and four in two different planes, the lower and upper. Flight performances of these two different UAVs were compared under disturbing effect. It was observed that the flight performances were close in the simulation study. Although the average and maximum of the position errors for three axes in the first model was less than the other, for the same propeller dimensions, the first model must have larger dimensions than the other in the context of the smallest vehicle dimensions.
{"title":"Modelling and Control of Proposed Two Dodecacopter Systems","authors":"Ş. Yıldırım, Nihat Çabuk, Veli Bakırcıoğlu","doi":"10.18100/ijamec.698462","DOIUrl":"https://doi.org/10.18100/ijamec.698462","url":null,"abstract":"Nowadays, the use of multi-propellers has been increased, because of some basic advantages such as vertical take-off and landing, simple mechanical structure. In addition, different usage fields such as carrying an object and making video records over the cities. This paper exposes design and control of two different multi propeller systems and both systems have 12 rotors to carry more load. In first, all motors are arranged at identical angles in the same plane. In the other, the motors are mounted in two groups, eight and four in two different planes, the lower and upper. Flight performances of these two different UAVs were compared under disturbing effect. It was observed that the flight performances were close in the simulation study. Although the average and maximum of the position errors for three axes in the first model was less than the other, for the same propeller dimensions, the first model must have larger dimensions than the other in the context of the smallest vehicle dimensions.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134344303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Parkinsonism is a syndrome that occurs as a combination of six cardinal signs; resting tremor, rigidity, bradykinesia, loss of postural reflex, flexion posture and freezing (motor block). Parkinson disease occurs with the loss of brain cells which are generating dopamine. The most important primary motor symptoms of Parkinson’s disease are shaking of hands, slowness of movement, and speech changes. Sound changes are not recognized at the early stages of the disease while it becomes evident at the progressive stages. However, speech changes can be detected with some acoustic parameters. This study aims to detect Parkinson’s disease by using voice recordings. In this study, 342 voice recordings that belong to 174 healthy subjects and 168 Parkinson’s disease patients are used. 21 features are extracted from each voice record. The classification of subjects as healthy or with Parkinson disease is achieved by using logistic regression, k-nearest neighboring and ensemble gentle boost techniques. Furthermore, ten-fold and leave-one-out cross validation techniques are applied to improve the performance and reliability of the classifier. Sensitivity, specificity, maximum and average accuracy values are calculated to evaluate the success of the system. The obtained results show that the proposed system can be utilized by the neurologists to diagnose Parkinson’s disease at its early stages.
{"title":"The Role of Dysphonia and Voice Recordings in Diagnosis of Parkinson’s Disease","authors":"G. Çetinel, Elif Sarica, Alhasan Alkhatib","doi":"10.18100/ijamec.679038","DOIUrl":"https://doi.org/10.18100/ijamec.679038","url":null,"abstract":"Parkinsonism is a syndrome that occurs as a combination of six cardinal signs; resting tremor, rigidity, bradykinesia, loss of postural reflex, flexion posture and freezing (motor block). Parkinson disease occurs with the loss of brain cells which are generating dopamine. The most important primary motor symptoms of Parkinson’s disease are shaking of hands, slowness of movement, and speech changes. Sound changes are not recognized at the early stages of the disease while it becomes evident at the progressive stages. However, speech changes can be detected with some acoustic parameters. This study aims to detect Parkinson’s disease by using voice recordings. In this study, 342 voice recordings that belong to 174 healthy subjects and 168 Parkinson’s disease patients are used. 21 features are extracted from each voice record. The classification of subjects as healthy or with Parkinson disease is achieved by using logistic regression, k-nearest neighboring and ensemble gentle boost techniques. Furthermore, ten-fold and leave-one-out cross validation techniques are applied to improve the performance and reliability of the classifier. Sensitivity, specificity, maximum and average accuracy values are calculated to evaluate the success of the system. The obtained results show that the proposed system can be utilized by the neurologists to diagnose Parkinson’s disease at its early stages.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134262295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Malware basically means malicious software that can be an intrusive program code or anything that is designed to perform malicious operations on system and executes malicious actions such as clandestine, listening, monitoring, saving, and deleting without the user's knowledge and consent. Malware review and analysis requires an advanced level of programming knowledge, in-depth file systems knowledge, deep code inspection, and reverse engineering capability. New techniques are needed to reduce indirect costs of malware analysis. This paper aims to provide insights into the malware visualization techniques and its applications, most common malware types and the extracted features that used to identify the malware are demonstrated in this study. In this work, Systematic Literature Review (SLR) conducted to investigate the current state of knowledge about Malware detection techniques, data visualization and malware features. An advanced research has been carried out in most relevant digital libraries for potential published articles. 90 preliminary studies (PS) were determined on the basis of inclusion and exclusion criteria. The analytical study is based mainly on the PSs to achieve the goals. The results clarify the importance of visualization techniques and which are the most common malware as well as the most useful features. Several ways to visualize malware to help malware analysts have been suggested.
{"title":"Malware Visualization Techniques","authors":"Ahmet Efe, S. Hussin","doi":"10.18100/ijamec.526813","DOIUrl":"https://doi.org/10.18100/ijamec.526813","url":null,"abstract":"Malware basically means malicious software that can be an intrusive program code or anything that is designed to perform malicious operations on system and executes malicious actions such as clandestine, listening, monitoring, saving, and deleting without the user's knowledge and consent. Malware review and analysis requires an advanced level of programming knowledge, in-depth file systems knowledge, deep code inspection, and reverse engineering capability. New techniques are needed to reduce indirect costs of malware analysis. This paper aims to provide insights into the malware visualization techniques and its applications, most common malware types and the extracted features that used to identify the malware are demonstrated in this study. In this work, Systematic Literature Review (SLR) conducted to investigate the current state of knowledge about Malware detection techniques, data visualization and malware features. An advanced research has been carried out in most relevant digital libraries for potential published articles. 90 preliminary studies (PS) were determined on the basis of inclusion and exclusion criteria. The analytical study is based mainly on the PSs to achieve the goals. The results clarify the importance of visualization techniques and which are the most common malware as well as the most useful features. Several ways to visualize malware to help malware analysts have been suggested.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127371644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image processing applications usually requires nonlinear methods due to the nonlinear characteristics of images. Quadratic image filter which is a class of nonlinear image filters are widely used in practice such as noise elimination edge detection and image enhancement. On the other hand, second order products of the pixels make quadratic image filters computationally expensive to implement when compared to linear convolution. In the last decade, CUDA accelerated computing has been widely used in image processing applications to reduce computation times. In this study, an efficient method for the CUDA acceleration of the quadratic image filter has been implemented. For this purpose, alternative algorithms were examined comparatively since the performance of the GPU is sensitive to memory utilization. Because quadratic filter has a large number of coefficients and quadratic terms, the algorithm which utilizes the shared memory for storing image blocks provided the best throughput among the examined methods. Comparative results that were obtained using various images in different sizes show significant accelerations over sequential implementation.
{"title":"CUDA Based Computation of Quadratic Image Filters","authors":"D. Akgün, Süleyman Uzun","doi":"10.18100/ijamec.652564","DOIUrl":"https://doi.org/10.18100/ijamec.652564","url":null,"abstract":"Image processing applications usually requires nonlinear methods due to the nonlinear characteristics of images. Quadratic image filter which is a class of nonlinear image filters are widely used in practice such as noise elimination edge detection and image enhancement. On the other hand, second order products of the pixels make quadratic image filters computationally expensive to implement when compared to linear convolution. In the last decade, CUDA accelerated computing has been widely used in image processing applications to reduce computation times. In this study, an efficient method for the CUDA acceleration of the quadratic image filter has been implemented. For this purpose, alternative algorithms were examined comparatively since the performance of the GPU is sensitive to memory utilization. Because quadratic filter has a large number of coefficients and quadratic terms, the algorithm which utilizes the shared memory for storing image blocks provided the best throughput among the examined methods. Comparative results that were obtained using various images in different sizes show significant accelerations over sequential implementation.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116687519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emine Rumeysa Kocaer, H. Koruca, Samia Chehbi-Gamoura
It is important for both the bus owner and the passengers to determine the bus and minibus routes that are frequently used in urban passenger transport. Because the distance between the stops, the streets where the vehicle passes, the distance to reach the bus stop of passengers, how many minutes the bus will move, the waiting and transport time effects. Bus routes surround the entire residential area of the city as a network in various ways. The use of buses as a means of public transportation is preferred because it requires fewer infrastructure investments. The distance between stops, the population of settlements, the size/capacity of the bus and how many minutes the bus will move, determines the waiting time of passengers at the stop and duration of the tour. In this study, it is aimed to reduce bus operating costs and waiting times of passengers. Bus stops between Isparta center and Suleyman Demirel University West Campus, number and density of passengers, bus departure times and bus capacities were analyzed and modeled in the simulation software. As an alternative improvement scenario, buses with little and very passenger capacity were used and departure times were arranged. The effect of alternative scenarios on operating costs and waiting time was evaluated with the results obtained from simulation software.
{"title":"Evaluation of Waiting Time and Transport Costs with Simulation in Urban Bus Transport","authors":"Emine Rumeysa Kocaer, H. Koruca, Samia Chehbi-Gamoura","doi":"10.18100/IJAMEC.621174","DOIUrl":"https://doi.org/10.18100/IJAMEC.621174","url":null,"abstract":"It is important for both the bus owner and the passengers to determine the bus and minibus routes that are frequently used in urban passenger transport. Because the distance between the stops, the streets where the vehicle passes, the distance to reach the bus stop of passengers, how many minutes the bus will move, the waiting and transport time effects. Bus routes surround the entire residential area of the city as a network in various ways. The use of buses as a means of public transportation is preferred because it requires fewer infrastructure investments. The distance between stops, the population of settlements, the size/capacity of the bus and how many minutes the bus will move, determines the waiting time of passengers at the stop and duration of the tour. In this study, it is aimed to reduce bus operating costs and waiting times of passengers. Bus stops between Isparta center and Suleyman Demirel University West Campus, number and density of passengers, bus departure times and bus capacities were analyzed and modeled in the simulation software. As an alternative improvement scenario, buses with little and very passenger capacity were used and departure times were arranged. The effect of alternative scenarios on operating costs and waiting time was evaluated with the results obtained from simulation software.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122754352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The need for energy is increasing by the day. Renewable energy sources already have a significant place in electricity production both around the world and also in Turkey and the share of solar energy going higher within the renewable energy sources. Solar energy is extremely easy to use, it is preferable too because it is environmentally friendly-clean energy. Solar energy plant is the energy source of the future, because the production costs of solar plants are lower than other energy sources and the economic difficulties are overcome. To get optimal production, the solar energy plant must make maximum use of the sun. In the designed system, solar panels are provided with both fixed and seasonal variations. The first variations of solar panel systems is are placed at constant 25° angle and the position angle of second variation is shifted from 10° to 30°in summer and winter accordingly. In this study, the performance of 1148 kWp PV plants which is established in Altinekin district of Konya and planned to be connected to the grid was evaluated by PVSYST analysis program. Power generation of the two different systems, specific data and performance value are calculated. Result of the study shows that the seasonal system produced 32.2 MWh more per year than the fixed system. Global irradiation in the seasonal system is 26.4 kWh/m², and the specific yield is concluded to be more than 28 kWh / kWc / year.
{"title":"The Importance of Fixed and Variable Angle in Solar Power Plants Analysis","authors":"O. Kilci, M. Koklu","doi":"10.18100/ijamec.653371","DOIUrl":"https://doi.org/10.18100/ijamec.653371","url":null,"abstract":"The need for energy is increasing by the day. Renewable energy sources already have a significant place in electricity production both around the world and also in Turkey and the share of solar energy going higher within the renewable energy sources. Solar energy is extremely easy to use, it is preferable too because it is environmentally friendly-clean energy. Solar energy plant is the energy source of the future, because the production costs of solar plants are lower than other energy sources and the economic difficulties are overcome. To get optimal production, the solar energy plant must make maximum use of the sun. In the designed system, solar panels are provided with both fixed and seasonal variations. The first variations of solar panel systems is are placed at constant 25° angle and the position angle of second variation is shifted from 10° to 30°in summer and winter accordingly. In this study, the performance of 1148 kWp PV plants which is established in Altinekin district of Konya and planned to be connected to the grid was evaluated by PVSYST analysis program. Power generation of the two different systems, specific data and performance value are calculated. Result of the study shows that the seasonal system produced 32.2 MWh more per year than the fixed system. Global irradiation in the seasonal system is 26.4 kWh/m², and the specific yield is concluded to be more than 28 kWh / kWc / year.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115741756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electromyography (EMG) signals that obtained by electrodes connected to the forearm are the monitoring of the muscles by the electrical method. These signals are quite useful during the use of prosthesis as a source signal to the moving prosthesis. Therefore, it is essential that classifying the EMG signals with high accuracy by analyzing. This study aims that classifying the individual and combined finger movements using surface EMG signals taken from the surface of the human forearm. EMG signals that belong to 10 different finger movements obtained from eight subjects were used. Firstly, EMG signals have been split into segments by the windowing process, and temporal feature vectors are formed by applying various feature extraction methods to these segments. Feature vectors have been classified with the ensemble bagged tree algorithm, which is a combination of classifiers, to obtain the correct classification decision. As a result of 10-fold cross-validation, with the proposed method, 96.6% overall classification accuracy was achieved. The results obtained show that the ensemble classifier can be used successfully in determining finger movements when compared with similar studies.
{"title":"An Ensemble Classifier for Finger Movement Recognition using EMG Signals","authors":"I. Ozkan","doi":"10.18100/IJAMEC.659781","DOIUrl":"https://doi.org/10.18100/IJAMEC.659781","url":null,"abstract":"Electromyography (EMG) signals that obtained by electrodes connected to the forearm are the monitoring of the muscles by the electrical method. These signals are quite useful during the use of prosthesis as a source signal to the moving prosthesis. Therefore, it is essential that classifying the EMG signals with high accuracy by analyzing. This study aims that classifying the individual and combined finger movements using surface EMG signals taken from the surface of the human forearm. EMG signals that belong to 10 different finger movements obtained from eight subjects were used. Firstly, EMG signals have been split into segments by the windowing process, and temporal feature vectors are formed by applying various feature extraction methods to these segments. Feature vectors have been classified with the ensemble bagged tree algorithm, which is a combination of classifiers, to obtain the correct classification decision. As a result of 10-fold cross-validation, with the proposed method, 96.6% overall classification accuracy was achieved. The results obtained show that the ensemble classifier can be used successfully in determining finger movements when compared with similar studies.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116656346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today, information technologies are used in almost every stage of life. It seeks to find solutions too many issues and problems. Image processing applications have been widely used in many areas in recent years and are trying to solve problems. Many applications which perform tasks such as classification, counting, measurement, target tracking have been developed. The aim of this study is to provide a solution for different applications using an effective and cost-effective method to detect the brand and model of vehicles. A classification method is implemented using deep neural network in the determination of the vehicle brand. The proposed solution is tested on various images taken from different angles and obtained from different sources. Faster-RCNN method which is one of deep neural networks is used to brand detection of vehicles in this study. It is observed that Faster-RCNN method performs 67.66% classification accuracy.
{"title":"Vehicle Brand Detection Using Deep Learning Algorithms","authors":"Mehmet Furkan Kunduraci, Humar Kahramanlı Örnek","doi":"10.18100/IJAMEC.578497","DOIUrl":"https://doi.org/10.18100/IJAMEC.578497","url":null,"abstract":"Today, information technologies are used in almost every stage of life. It seeks to find solutions too many issues and problems. Image processing applications have been widely used in many areas in recent years and are trying to solve problems. Many applications which perform tasks such as classification, counting, measurement, target tracking have been developed. The aim of this study is to provide a solution for different applications using an effective and cost-effective method to detect the brand and model of vehicles. A classification method is implemented using deep neural network in the determination of the vehicle brand. The proposed solution is tested on various images taken from different angles and obtained from different sources. Faster-RCNN method which is one of deep neural networks is used to brand detection of vehicles in this study. It is observed that Faster-RCNN method performs 67.66% classification accuracy.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117074780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today, it is one of the most invested areas of organizations to ensure the interoperability of existing corporate applications and newly developed or purchased applications. Developed systems are designed to be shaped according to the needs of the businesses that use it. Classical systems are automation systems that operate from point to point and from other platforms in the enterprise without interaction. Unlike these, the service-oriented architecture (SOA) contains a structure that is ready to interact. In this study, a system has been designed in order to reduce the integration costs between the applications in the long term by using SOA approach, to shorten the business processes in the institution and to reduce the economic costs. In the project, work pieces were published as a method of service over the service layer. Thus, the platform independent main application is accessible to each work piece. At the same time, these work pieces can come together and be reconfigured according to the request of the enterprise. Some of the advantages achieved by using SOA are: Providing improved work processes for services and actors, ensuring collaboration, utilizing from existing and reuse with savings, providing business flexibility by responding to changing business needs.
{"title":"Application Development wtih Service Oriented Architecture","authors":"Ridvan Saraçoglu, Emine Doğaç","doi":"10.18100/ijamec.588865","DOIUrl":"https://doi.org/10.18100/ijamec.588865","url":null,"abstract":"Today, it is one of the most invested areas of organizations to ensure the interoperability of existing corporate applications and newly developed or purchased applications. Developed systems are designed to be shaped according to the needs of the businesses that use it. Classical systems are automation systems that operate from point to point and from other platforms in the enterprise without interaction. Unlike these, the service-oriented architecture (SOA) contains a structure that is ready to interact. In this study, a system has been designed in order to reduce the integration costs between the applications in the long term by using SOA approach, to shorten the business processes in the institution and to reduce the economic costs. In the project, work pieces were published as a method of service over the service layer. Thus, the platform independent main application is accessible to each work piece. At the same time, these work pieces can come together and be reconfigured according to the request of the enterprise. Some of the advantages achieved by using SOA are: Providing improved work processes for services and actors, ensuring collaboration, utilizing from existing and reuse with savings, providing business flexibility by responding to changing business needs.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128461010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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