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.

Detection of Hidden Hostile/Terrorist Groups in Harsh Territories by Using Animals as Mobile Biological Sensors

Abstract: Terrorism is the greatest threat to national security and cannot be defeated by conventional military force alone. In critical areas such as Iraq, Afghanistan and Turkey, regular forces cannot reach these hostile/terrorist groups, the instigators of terrorism. These groups have a clear understanding of the relative ineffectiveness of counter-guerrilla operations and rely on guerrilla warfare to avoid major combat as their primary means of continuing the conflict with the governmental structures. In Internal Security Operations, detection of terrorist and hostile groups in their hiding places such as caves, lairs, etc. can only be achieved by professionally trained people such as Special Forces or intelligence units with the necessary experience and tools suitable for collecting accurate information in these often harsh, rugged and mountainous countries. To assist these forces, commercial micro-sensors with wireless interfaces could be utilized to study and monitor a variety of phenomena and environments from a certain distance for military purposes. In order to locate hidden terrorist groups and enable more effective use of conventional military resources, this paper proposes an active remote sensing model implanted into animals capable of living in these environments. By using these mobile sensor devices, improving communications for data transfer from the source, and developing better ways to monitor and detect threats, terrorist ability to carry out attacks can be severely disrupted.

Revealing determinants of two-phase dynamics of P53 network under gamma irradiation based on a reduced 2D relaxation oscillator model.

Abstract: This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two-phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53-regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations' effects using the phase space approach.

Turkish Efforts in Peacekeeping and the Introduction of the TUBAKOV Dataset: An Exploratory Analysis

Abstract: This study introduces the TUBAKOV dataset, which offers extensive data on 57 peacekeeping operations (PKOs) that Turkey has contributed to between the years 1988–2015. TUBAKOV improves existing data in several ways. First, it draws data from governmental resources that have not been previously used. Second, Turkey's contributions for each PKO are presented both at the levels of PKO and PKO-contribution year format. The website of the dataset also allows access to qualitative data such as primary text sources, hence facilitating qualitative and multi-method research on peacekeeping. Preliminary analyses indicate that the frequency, nature and the geographic focus of Turkey's contributions to peacekeeping operations demonstrate a significant shift with the new millennium. Preliminary findings offer interesting insights to the changing characteristics of Turkey's PKO involvements relating to the content, geography and timing of these contributions over the time period covered by this dataset.

Anomaly Detection in Wireless Sensor Networks Data by Using Histogram Based Outlier Score Method

Abstract: Data anomaly detection in wireless sensor networks, which is one of the important technologies and study areas, is a method that enhances data quality and data reliability. Besides data enhancing methods such as estimating missing data, deduplication, noise removal; anomaly detection is important in terms of finding data patterns which are out of normal data. This stage influences next analysis and decision processes and plays an important role in determining events, faults or unexcepted but meaningful patterns. This study proposes the Histogram Based Outlier Score (HBOS) method to detect anomalies in data acquired by wireless sensor networks. In respect to anomaly detection methods used in this area, such as data classification, data clustering, statistical, distance based and support vector machines based approaches, histogram based algorithms are unsupervised and provide fast solutions.