2024-03-29T14:59:00Z
http://ntmsci.com/CIWSN/ajaxtool/oai
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8541
2019-08-31T21:00:00Z
1
Comparative Analysis of Linear, Non Linear and Ensemble Machine LearningAlgorithms for Credit Worthiness of Consumers
David Oyewola, Emmanuel Dada, Oluwatosin Omotehinwa and Isa Ibrahim
Credit Worthiness, Consumers, Machine Learning, Ensemble Learning, Genetic Algorithms.
We apply machine-learning techniques to construct linear, non-linear and ensemble machine learning algorithms. The linear comprises of logistic regression(LR), linear discriminant analysis(LDA) and least absolute shrinkage and selection operator (LASSO) while non-linear comprises of support vector machine(SVM), neural network(NN) and decision tree while ensemble learning are boosting, bagging and weighted average. We compared linear, non-linear and ensemble learning using the entire feature in consumer credit data sets. In the first experiment, the study revealed that ensemble learning performs significantly well follow by non-linear and linear machine learning. In the second experiment, we use the selected features from genetic algorithms. It was observed that there was a slight improvement in the result obtained from some of the linear and non-linear machine learning but slight decrease in the result obtained from ensemble learning. The grading scale was used on the overall accuracy of area under the curve(AUROC) in which bagging and weighted average score between 90-100 grade and performs excellently well, boosting obtained 80-90 grade, support vector machine obtained 70-80 grade, logistic regression, linear discriminant analysis, neural network and decision tree obtained 60-70 grade and lasso performs worse with 50-60 grade.
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-31T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8541
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8541
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8541
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8542
2019-08-27T21:00:00Z
1
Social Engineering & Awareness of Turkey
Mehmet Barışkan and Muhammed Ali Aydın
Cyber Security, Turkey, Cyber Fraud, Social Engineering.
Rapid changes in technology threaten the reliability of the country's systems while trying to catch the world in terms of technology. With the development of the Internet of Things in recent years, security has become a serious situation. The biggest DDOS work that has been done so far is not with computers, but small smart devices like ipcam, tv, washing machine with internet connection. Information such as the user name and password used in the control of these devices can easily be captured by the methods of collecting information from Social Engineering. Especially when we think that according to wearesocial research 63% of the total population and 80% of 13+ age population of Turkey is a social media user as of the end of 2018 and 29% of the internet users use social media for work so the information that people share can be an appetite for attackers. In this research, we examined the usage habits of the people of Turkey and look at what measures are necessary to protect Turkey.As we take account of this dark results we learned that we must take more measurements to make Turkey safe
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-27T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8542
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8542
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8542
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8543
2019-08-27T21:00:00Z
1
Hive Tracking and Early Warning System By Using Embedded System Technology
Tuğba Saray Çetinkaya, Kadir Cem Tuna and Ali Okatan
Location Tracking in Embedded Systems, GPS and GSM Microcontroller Control, Beekeeping Early Warning System.
In this study, the high costs and theft of bee swashes and hives, natural disasters, based on losses caused by various environmental factors; A system that performs continuous monitoring of hive, monitoring environmental factors with various sensors, warning and position monitoring against theft status has been developed. The latitude and longitude data provided by the GY-NEO6MV2 GPS module, the data obtained from the DHT 11 humidity and temperature sensors, data from the ultrasonic distance sensor are transmitted through the 800L GSM module. Embedded System (ATMEGA2560 microcontroller) is used in the hardware section of this system.
As a result, the data received by the programming of various sensors through this system are designed and sent as SMS to the desired phone number with the help of the GSM module. The software is triggered by the message sent to the SIM card in the system. According to the user's choice of internal temperature and humidity, external temperature and humidity, system location information is taken instantaneously. A separate trigger was created using the distance sensor. With this trigger, notification is automatically sent when motion is detected around the system. In addition to the system, the desired temperature and humidity threshold values have been defined and the other triggering triggered when these threshold values have been established.
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-27T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8543
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8543
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8543
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8544
2019-08-27T21:00:00Z
1
Emergency Autonomous Robot Design with Fuzzy Logic Control Approach
Ali Çetinkaya and Ali Okatan
Fuzzy Controller, Autonomous Fire Extinguisher Robot, Emergency Situation Position Control.
In this study, the application of an autonomous fire extinguishing robot with a fuzzy controller approach was carried out. For this purpose, an autonomous robot which can provide motion is designed and reaching the target and controlling the position were aimed.
The embedded system (Atmega2560) was used on the designed autonomous robot. Flame Sensor, Li-po battery, L298 Motor drive, DC motor, servo motor, digital compass sensor are used on this system. Robot is processing the position and route information through a fuzzy controller. As a result of the data obtained, flames created in the environment are detected by robot through the patrol and then the robot extinguishes the flames with its impeller and continues its patrol.
As a result, the autonomous robot detects the flames considered as target point during the patrol task and the fuzzy controller is used to determine the distance to be taken and the direction with the digital compass.
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-27T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8544
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8544
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8544
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8545
2019-08-27T21:00:00Z
1
Study of the reliability of a composite used in the knee prosthesis
Alimi Latifa, Boulkra Mohamed, Sassane Nacira, Boukhezar Skander, Hassani Mohamed, Bedoud Khouloud and Kamel Bey
Reliability analysis, critical stress intensity factor, crack length, load, reliability index.
In orthopedic surgery, the effectiveness of the implants used, such as hip and knee prostheses, depends mainly on their geometries and the type of loading to which they are subjected. In this work a probabilistic approach is chosen to study the reliability of a composite structure used in the manufacture of knee prostheses. The purpose of integrating reliability concepts is to consider uncertainty in several aspects including loading and material properties. The reliability index ß is an excellent indication of durability and safety for given operating conditions. ß is obtained using failure probability and a mechanical model. The critical stress intensity factor (Kc) is adopted as a criterion to the maximum limit of a numerically calculated KI. The results presented are discussed according to the length of the crack (a), and the limit load used.
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-27T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8545
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8545
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8545
oai:ntmsci.com/CIWSN/ajaxtool/oai:article/8546
2019-08-27T21:00:00Z
1
Optimizing A Route Path for A Mobile Blood Collection System
Erhan Baran
Vehicle Routing Problem, Health-care Logistic, Multi Objective Programming, Mobile Blood Collection.
Today the population of the world is growing rapidly. Human life is under threat. There are many health problems all around the world. The most needed item for the healthcare is blood. Many of people search for suitable blood in case of a health problem. This is really necessary to get the suitable blood in right time. In this study, the optimal route for mobile blood collection system is determined. The blood is collected by the bus. An application is made in Ankara, Turkey. The bus must be placed in critical places in Ankara. Multi-objective programming is used for routing the buses. The objectives are minimizing the total distance and minimizing the fuel consumption. In this study, taking the blood in different parts of Ankara is helped to give the blood in right time to right person.
Computational Intelligence & Wireless Sensor Network
Computational Intelligence & Wireless Sensor Network
2019-08-27T21:00:00Z
Research Article
application/pdf
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8546
ISSN: 2687-3710
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8546
Computational Intelligence & Wireless Sensor Network, Year:2019, Vol:1, Issue:1
http://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8546