Person: YAYLA, AYŞE
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
YAYLA
First Name
AYŞE
Name
5 results
Search Results
Now showing 1 - 5 of 5
Publication Metadata only Poster: A Mobile Application for Voice and Remote Control of Programmable Instruments(SPRINGER INTERNATIONAL PUBLISHING AG, 2019) YAYLA, AYŞE; Ece, Burak; Yayla, Ayse; Korkmaz, Hayriye; Auer, ME; Langmann, RThe purpose of this work is to add a new feature to bench-type conventional instruments used in Electrical and Electronics Engineering Laboratory which do not have any voice recognition and wireless communication technology. By this way, the user can control these instruments/devices remotely with voice commands and also monitor the results/values in graphical or numerical/text format as well over a mobile device screen. The only limitation is that such instruments should have a driver supported by any software such as NI LabVIEW and a PC connectivity interface such as USB, GPIB or LXI (LAN extensions for Instrumentation). Controlling the instruments (such as oscilloscope or signal generators which are frequently used for training purposes and whose functions are manually set) over a mobile device with voice commands will make life easier for disabled students who especially have difficulties in using their hands.Publication Metadata only Fiber optic training program with intensive experiments using both real laboratory and simulation environments(WILEY, 2019) SARIKAŞ, ALİ; Aydin, Serkan; Sarikas, Ali; Ak, Ayca; Yayla, Ayse; Kesen, Ugur; Oral, BekirThis paper highlights a fiber optic training program developed according to the occupational competencies using real and simulation platforms to train young people aged between 15 and 24. The most important objective is to overcome the shortages of fiber optic employees by providing training qualifications accredited by the Fiber Optic Association. This training program was designed on three levels, and participants were tested at the end of each level. Successful participants continued with a higher level of training. Theoretical knowledge was given to the participants at the first two levels and extensive practical applications were done. At the third level, computer networks trainings were provided to identify the much more fiber optic network modules by using simulation software tool. The training program includes installation of DVB-X (Digital Video Broadcast - satellite, cable) and the FFT-X (fiber-to-the - home, building, curb) devices that have a fiber optic cable infrastructure, and point-to-point line measurements. This training program differs from similar programs due to the inclusion of effective real laboratory, simulation platform, and field practices. It is significantly found that this training program supported by more extensive real experiments and simulations besides of theoretical education increases the technical qualifications and satisfaction ratio of the participants.Publication Metadata only Development of a remote laboratory for an electronic circuit design and analysis course with increased accessibility by using speech recognition technology(WILEY, 2021) SARIKAŞ, ALİ; Yayla, Ayse; Korkmaz, Hayriye; Buldu, Ali; Sarikas, AliWhen the curricula of engineering undergraduate programs are examined, it can be seen that experimentation plays a very important role and the learning outcomes of the courses are mostly dependent on practical abilities. However, there may be a few who cannot use their hands permanently or temporarily among the students who are attending these courses. Therefore, the participation of disabled students in this part of the course has always been a problem. In this paper, a remote laboratory application that aims to increase the accessibility of electronic circuit design and analysis courses by using speech recognition technology is introduced. This laboratory is designed for hands-free operation and enables students to analyze the electronic circuits by speaking. Google Web Speech API was used for speech recognition and the user interface was designed using Adobe Flash Professional. The parameters are sent to the ASP.NET page by using ActionScript 2.0 programming language. The application developed by using C# programming language enables programming the experimental hardware that includes a signal generator, a Raspberry Pi 2 with a camera, an oscilloscope, and a new test card. In the Raspberry Pi 2, Python programming language was used to select the desired experiment from those present on the board and to control digitally programmable circuit components such as digital potentiometers or parameters such as the DC reference voltage level. When the student successfully completes the predefined experimental procedures, an automatically generated e-mail is sent to the instructor including the student's username, log-in time, the oscilloscope screenshots, and ideal experimental results.Publication Metadata only Ön Lisans Öğrencilerinin Girişimcilik Eğilimlerinin Bazı Değişkenlere Göre Araştırılması(2017-10-12) CEVİZ, NURAY; POLAT, ZÜHAL; YAYLA, AYŞE; SARIKAŞ, ALİ; TEKTAŞ N., TEKTAŞ M., CEVİZ N., POLAT Z., YAYLA A., SARIKAŞ A.Publication Metadata only Using an rtificial neural network approach for supplier evaluation process and a sectoral application(2011-01-01) YAYLA, AYŞE; HARTOMACIOĞLU, SELİM; YAYLA A., HARTOMACIOĞLU S.In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN) model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network\"s independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network\"s input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network\"s inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network\"s outputs. The data set of the network\"s are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.