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Yayın On the sensitivity of desirability functions for multiresponse optimization(American Institute of Mathematical Sciences, 2008-11) Aksezer, Sezgin ÇağlarDesirability functions have been one of the most important multiresponse optimization technique since the early eighties. Main reasons for this popularity might be counted as the convenience of the implementation of the method and it's availability in many experimental design software packages. Technique itself involves somehow subjective parameters such as the importance coefficients between response characteristics that are used to calculate overall desirability, weights used in determining the shape of each individual response and the size of the specification band of the response. However, the impact of these sensitive parameters on the solution set is mostly uninvestigated. This paper proposes a procedure to analyze the sensitivity of the important characteristic parameters of desirability functions and their impact on pareto-optimal solution set. The proposed procedure uses the experimental design tools on the solution space and estimates a prediction equation on the overall desirability to identify the sensitive parameters. For illustration, a classical desirability example is selected from the literature and results are given along with the discussion.Yayın Sınıflandırma için diferansiyel mahremiyete dayalı öznitelik seçimi(Gazi Univ, Fac Engineering Architecture, 2018) Var, Esra; İnan, AliVeri madenciliği ve makine öğrenmesi çözümlerinin en önemli ön aşamalarından biri yapılacak analizde kullanılacak verinin özniteliklerinin uygun bir alt kümesini belirlemektir. Sınıflandırma yöntemleri için bu işlem, bir özniteliğin sınıf niteliği ile ne oranda ilişkili olduğuna bakılarak yapılır. Kişisel gizliliği koruyan pek çok sınıflandırma çözümü bulunmaktadır. Ancak bu yöntemler için öznitelik seçimi yapan çözümler geliştirilmemiştir. Bu çalışmada, istatistiksel veritabanı güvenliğinde bilinen en kapsamlı ve güvenli çözüm olan diferansiyel mahremiyete dayalı özgün öznitelik seçimi yöntemleri sunulmaktadır. Önerilen bu yöntemler, yaygın olarak kullanılan bir veri madenciliği kütüphanesi olan WEKA ile entegre edilmiş ve deney sonuçları ile önerilen çözümlerin sınıflandırma başarımına olumlu etkileri gösterilmiştir.Yayın Asymptotic solutions of love wave propagation in a covered half-space with inhomogeneous initial stresses G(3)(1)(Işık University Press, 2015) Hasanoğlu, Elman; Negin, MasoudThe dispersive behavior of Love waves in an elastic half-space substrate covered by an elastic layer under the effect of inhomogeneous initial stresses has been investigated. Classical linearized theory of elastic waves in initially stressed bodies for small deformations is used and the well-known WKB high-frequency asymptotic technique is applied for the theoretical derivations. Numerical results on the action of the influence of the initial stresses on the wave propagation velocity for a geophysical example are presented and discussed.Yayın A survey of algorithms and architectures for H.264 sub-pixel motion estimation(World Scientific, 2012-05) Fatemi, Mohammad Reza Hosseiny; Ateş, Hasan Fehmi; Salleh, Rosli BinThis paper reviews recent state-of-the-art H. 264 sub-pixel motion estimation (SME) algorithms and architectures. First, H.264 SME is analyzed and the impact of its functionalities on coding performance is investigated. Then, design space of SME algorithms is explored representing design problems, approaches, and recent advanced algorithms. Besides, design challenges and strategies of SME hardware architectures are discussed and promising architectures are surveyed. Further perspectives and future prospects are also presented to highlight emerging trends and outlook of SME designs.Yayın Design of a global extremum seeking algorithm for an omni-directional robot model(Romanian Soc Control Tech Informatics, 2017-06) Dinçmen, ErkinA global extremum seeking algorithm is developed for a mobile robot model where the aim is to find the location of the most powerful signal source among the others. In other words, the control problem is to seek the global extremum point of a performance function when there are local extremas. The locations of the signal sources and signal distribution characteristics are unknown, i.e. the gradient of the performance function is unknown. The control algorithm also doesn't use any position measurement of the mobile robot itself. Henceforth, the controller is suitable for the missions where the robot moves in an unknown terrain with no GPS signal and no inertial measurements. Only the signal magnitude should be measured via a sensor mounted on the robot during the motion. A gradient estimator is designed to determine the motion direction towards the extremum point. When a local extremum is found, the robot will continue its search for another extremum points. Once each extremums have been visited, the robot will compare the signal levels on each source and identify the global extremum i.e. the most powerful signal source. In the absence of any position measurements, the robot can move towards the global extremum by repeating its motion history backwards. In the literature, this is the first global extremum seeking algorithm that has been developed for an omni-directional mobile robot model. Via the simulation studies it has been shown that the control algorithm can seek and find both stationary and non stationary signal sources and it can find the global extremum point when there are local extremas.Yayın A new late holocene eolianite record from Altinkum Beach, North Cyprus(Scientific technical research council Turkey-Tubitak, 2012-06) Erginal, Ahmet Evren; Güneç Kıyak, Nafiye; Ertek, Topçu AhmetIn this study, we investigated the main depositional characteristics and obtained Optically Stimulated Luminescence (OSL) ages of coastal eolianite on the north coast of Cyprus, where this occurrence had not previously been recorded. Based on EDX/SEM and XRD data and field observations, the studied eolianite that crops out between elevations of 1 m and 14 m a.s.l. is made up predominantly of quartz grains, most of which consist of medium- to fine-grained sand. The rock comprises aragonite, calcite and quartz with lesser amounts of bornite and hematite as accessory minerals. OSL ages indicated that the initial deposition of eolianite sands took place at 1.51 +/- 0.21 ka years ago.Yayın Neuropsychiatric outcomes and caregiver distress in primary progressive aphasia(Wiley, 2023-01) Seçkin, Mustafa; Yıldırım, Elif; Demir, İlayda; Orhun, Ömer; Bülbül, Ezgi; Velioğlu, H. Aziz; Öget, Öktem; Yeşilot, Nilüfer; Çoban, Oğuzhan; Gürvit, HakanBackground: In this study, we aimed to outline the neuropsychiatric consequences of primary progressive aphasia (PPA) and to understand how neuropsychiatric symptomatology affects distress in caregivers. Methods: The Neuropsychiatric Inventory (NPI) including the distress index (NPI-Distress) was used. Additional information about the caregiver burden was obtained using Zarit Burden Interview (ZBI). NPI, NPI-Distress, and ZBI data from 17 patients with a clinical diagnosis of PPA were compared with 10 stroke aphasia patients. Neuropsychiatric symptomatology was investigated based on three clusters; Mood, Frontal/Comportmental, and Psychotic/Disruptive. Additionally, the Activities of Daily Living Questionnaire (ADLQ) was used to outline the functional impairment. Twelve healthy controls were included to compare the neurocognitive test scores with PPA and stroke aphasia groups. Results: A greater number of neuropsychiatric symptoms were observed in the PPA group compared to the stroke aphasia group. The number of symptoms in Mood, and Frontal/Comportmental clusters were greater than the number of symptoms in Psychotic/Disruptive clusters in the PPA group, whereas no significant relationship between the number of symptoms and symptom clusters was found in the stroke aphasia group. In the PPA group, a strong correlation was found between the NPI-Frequency × Severity scores and the NPI-Distress scores. Moreover, the NPI-Distress scores in the PPA group strongly correlated with the ZBI scores. Scores for anxiety, irritability/lability, and apathy had a stronger correlation with the NPI-Distress scores compared to the other NPI symptoms. The Communication subscale was the most impaired domain in the PPA group. Travel, and Employment and Recreation subscales showed greater functional impairment in the stroke aphasia group compared to the PPA group. Conclusions: Neuropsychiatric symptoms in PPA in our study were more frequent than previously reported. Furthermore, the distress index of the NPI was not only correlated with the severity of the neuropsychiatric symptoms but also reflected the overall burden on the caregivers in the PPA group.Yayın The dynamic relationship between technological change and employment: a comparison of youth and total employment using panel VAR approach and causality analysis(Sosyoekonomi Derneği, 2022-10) Görkey, SeldaThis study empirically examines the relationship and causality between technological change and employment by comparing youth and total employment. It covers data from 16 OECD economies from 1985 to 2018 and uses multifactor productivity (MFP) as a proxy for technological change. The findings from the general method of moments panel vector autoregression (GMM Panel-VAR) approach indicate significant and positive effects of MFP on youth and total employment, and a significant yet negative impact of youth employment on MFP. According to Panel-VAR-Granger- Causality analysis results, there is a two-way causality between MFP and youth employment and a one-way causality from MFP to total employment. Thus, this study empirically confirms the jobcreation effect of technology and finds out that the technological change and employment nexus differs for youth employment compared to that for total employment.Yayın Driver recognition using gaussian mixture models and decision fusion techniques(Springer-Verlag Berlin, 2008) Benli, Kristin Surpuhi; Düzağaç, Remzi; Eskil, Mustafa TanerIn this paper we present our research in driver recognition. The goal of this study is to investigate the performance of different classifier fusion techniques in a driver recognition scenario. We are using solely driving behavior signals such as break and accelerator pedal pressure, engine RPM, vehicle speed; steering wheel angle for identifying the driver identities. We modeled each driver using Gaussian Mixture Models, obtained posterior probabilities of identities and combined these scores using different fixed mid trainable (adaptive) fusion methods. We observed error rates is low as 0.35% in recognition of 100 drivers using trainable combiners. We conclude that the fusion of multi-modal classifier results is very successful in biometric recognition of a person in a car setting.Yayın Mobile applications discovery: a subscriber-centric approach(Wiley Periodicals, 2011-03) Erman, Bilgehan; İnan, Ali; Nagarajan, Ramesh; Uzunalioğlu, HüseyinRapid adoption of smartphones and the business success of the Apple App Store have resulted in the rampant growth of mobile applications. Seeking new revenue opportunities from application development has created a gold rush. However, free or very cheap applications constitute a great bulk of the application downloads putting great pricing pressure on the developers. Furthermore, usage statistics suggest that most of the applications have been either one-trick applications or are downright useless, meriting no attention from the user beyond the first day. This is not surprising since cheap prices will dissuade developers from investing large sums of money to continue to develop more sophisticated, high quality applications. Developers have been complaining about the lack of visibility of their applications in stores that are beginning to resemble a high volume warehouse. It is clear that enhancing application discovery and building better marketing tools will be essential for the continued success of the mobile application marketplace and application stores. This paper proposes and investigates techniques for effective discovery of applications by matching user interests with application characteristics, with a special focus on adapting classical data mining techniques to user ratings of the applications. The user ratings are leveraged to make recommendations on potential applications of interest.
