Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

Comparative Study of Forecasting Schemes for IoT Device Traffic in Machine-to-Machine Communication

Abstract: We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem of forecasting the traffic generation patterns of individual Internet of Things (IoT) devices in Machine-to-Machine (M2M) communication. We classify IoT traffic into four classes: Fixed-Bit Periodic (FBP), Variable-Bit Periodic (VBP), Fixed-Bit Aperiodic (FBA), and Variable-Bit Aperiodic (VBA). We show that LSTM outperforms all of the other models significantly in the symmetric Mean Absolute Percentage Error (sMAPE) measure for devices in the VBP class in our simulations. Furthermore, we show that LSTM has almost the same performance in this metric for the FBA class as MLP and 1-D CNN. While the training time per IoT device is the highest for LSTM, all of the forecasting models have reasonable training times for practical implementation. Our results suggest an architecture in which an IoT Gateway predicts the future traffic of IoT devices in the FBP, VBP and FBA classes and pre-allocates the uplink wireless channel for these classes in advance in order to alleviate the Massive Access Problem of M2M communication.

Jacobian Coordinates on Genus 2 Curves

Abstract: This paper presents a new projective coordinate system and new explicit algorithms which together boost the speed of arithmetic in the divisor class group of genus 2 curves. The proposed formulas generalize the use of Jacobian coordinates on elliptic curves, and their application improves the speed of performing cryptographic scalar multiplications in Jacobians of genus 2 curves over prime fields by an approximate factor of 1.25x. For example, on a single core of an Intel Core i7-3770 (Ivy Bridge), we show that replacing the previous best formulas with our new set improves the cost of generic scalar multiplications from 239,000 to 192,000 cycles and drops the cost of specialized GLV-style scalar multiplications from 155,000 to 123,000 cycles.

ECG Arrhythmia Classification By Using Convolutional Neural Network And Spectrogram

Abstract: In this study, the electrocardiography (ECG) arrhythmias have been classified by the proposed framework depend on deep neural networks in order to features information. The proposed approaches operates with a large volume of raw ECG time-series data and ECG signal spectrograms as inputs to a deep convolutional neural networks (CNN). Heartbeats are classified as normal (N), premature ventricular contractions (PVC), right bundle branch block (RBBB) rhythm by using ECG signals obtained from MIT-BIH arrhythmia database. The first approach is to directly use ECG time-series signals as input to CNN, and in the second approach ECG signals are converted into time-frequency domain matrices and sent to CNN. The most appropriate parameters such as number of the layers, size and number of the filters are optimized heuristically for fast and efficient operation of the CNN algorithm. The proposed system demonstrated high classification rate for the time-series data and spectrograms by using deep learning algorithms without standard feature extraction methods. Performance evaluation is based on the average sensitivity, specificity and accuracy values. It is also worth to note that spectrogram increases the performance of classification since it extracts the useful time-frequency information of the signal.

Ministers’ statements: a policy implementation instrument for sustainable tourism?

Abstract: Consistent communication of tourism policies by tourism ministers might raise public and industry awareness and promote support for sustainable tourism. The statements made by ministers contain messages that can inform the public and industry stakeholders, and potentially, these statements can draw attention to sensitive issues and bring about changes in practices that encourage sustainability in the tourism industry. Analyzing the statements of the five most recent tourism ministers in Turkey, delivered between 2001 and 2009, this study identifies the ministers’ priorities for tourism and compares them with the tourism policy objectives set out in Turkey's Tourism Strategic Action Plan. Further comparison is undertaken to see whether priorities changed within and between governments. The results of the content analysis indicate that the statements of the Turkish tourism ministers were economically driven and growth-oriented, and that there were inconsistencies between the ministers’ priorities and the co...