An Adaptive Policy Management Approach to BGP Convergence

The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently adopt a set of local policies that specify which routes it accepts and advertises from/to other networks, as well as which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme (APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially-conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts (policy conflict-avoidance vs. -control mode), each AS dynamically adjusts its own path preferences—increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the substability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, routing load, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.National Science Foundation (ANI-0095988, EIA-0202067, ITR ANI-0205294

A randomized solution to BGP divergence

The Border Gateway Protocol (BGP) is an interdomain routing protocol that allows each Autonomous System (AS) to define its own routing policies independently and use them to select the best routes. By means of policies, ASes are able to prevent some traffic from accessing their resources, or direct their traffic to a preferred route. However, this flexibility comes at the expense of a possibility of divergence behavior because of mutually conflicting policies. Since BGP is not guaranteed to converge even in the absence of network topology changes, it is not safe. In this paper, we propose a randomized approach to providing safety in BGP. The proposed algorithm dynamically detects policy conflicts, and tries to eliminate the conflict by changing the local preference of the paths involved. Both the detection and elimination of policy conflicts are performed locally, i.e. by using only local information. Randomization is introduced to prevent synchronous updates of the local preferences of the paths involved in the same conflict.National Science Foundation (ANI-0095988, EIA-0202067, ITR ANI-0205294); Sprint Labs; Motorola Lab

FIGO: Enhanced Fingerprint Identification Approach Using GAN and One Shot Learning Techniques

Fingerprint evidence plays an important role in a criminal investigation for the identification of individuals. Although various techniques have been proposed for fingerprint classification and feature extraction, automated fingerprint identification of fingerprints is still in its earliest stage. The performance of traditional \textit{Automatic Fingerprint Identification System} (AFIS) depends on the presence of valid minutiae points and still requires human expert assistance in feature extraction and identification stages. Based on this motivation, we propose a Fingerprint Identification approach based on Generative adversarial network and One-shot learning techniques (FIGO). Our solution contains two components: fingerprint enhancement tier and fingerprint identification tier. First, we propose a Pix2Pix model to transform low-quality fingerprint images to a higher level of fingerprint images pixel by pixel directly in the fingerprint enhancement tier. With the proposed enhancement algorithm, the fingerprint identification model's performance is significantly improved. Furthermore, we develop another existing solution based on Gabor filters as a benchmark to compare with the proposed model by observing the fingerprint device's recognition accuracy. Experimental results show that our proposed Pix2pix model has better support than the baseline approach for fingerprint identification. Second, we construct a fully automated fingerprint feature extraction model using a one-shot learning approach to differentiate each fingerprint from the others in the fingerprint identification process. Two twin convolutional neural networks (CNNs) with shared weights and parameters are used to obtain the feature vectors in this process. Using the proposed method, we demonstrate that it is possible to learn necessary information from only one training sample with high accuracy

Performance of using Mel-Frequency Cepstrum Based Features in Nonlinear Classifiers for Phonocardiography Recordings

Cardiovascular system diseases can be identified by using a specialized diagnostic process utilizing a digital stethoscope. Digital stethoscopes provide phonocardiography (PCG) recordings for further inspection, besides filtering and amplification of heart sounds. In this paper, a framework that is useful to develop feature extraction and classification of PCG recordings is presented. This framework is built upon a previously proposed segmentation algorithm that processes a feature vector produced by the agglutinate application of Mel-frequency cepstrum and discrete wavelet transform (DWT). The performance of the segmentation algorithm is also tested on a new data set and compared to the previously reported results. After identifying the fundamental heart sounds and segmenting the PCG recordings, five principal features are extracted from the time domain signal and Mel-Frequency cepstral coefficients (MFCC) of each cardiac cycle. Classification outcomes are reported for three nonlinear models: k nearest neighbor (k-NN), support vector machine (SVM), and multilayer perceptrons (MLP) classifiers in comparison with a linear approach, namely Mahalanobis distance linear classifier. The results underline that although neural networks and linear classifier show compatible performance in basic classification problems, with the increase in the nonlinearity of the classification problem their performance significantly vary.Comment: in 2023 31st European Signal Processing Conference (EUSIPCO

Erzincan Yöresinde Organik Kuru Fasulye (Phaseolus Vulgaris L.) Üretiminin Araştırılması

Proje 2005–2007 yılları arasında Erzincan Bahçe Kültürleri Araştırma Enstitüsü arazisinde tarla sistemi şeklinde kurulup yürütülmüştür. Bu araştırmada; Erzincan koşullarında kuru fasulyenin organik olarak yetiştiriciliğinin araştırılması amaçlanmıştır. Yetiştirme sezonu boyunca kültürel bakım işlemleri yapılmıştır. Hastalık ve zararlılar takip edilmiş ve ekonomik zarar eşiğini geçmediği için mücadele yapılmamıştır. Bitkilerde fenolojik ve morfolojik gözlemler alınmıştır. Çalışmada organik uygulama da ortalama 201,31 kg/da, geleneksel uygulama da ise ortalama 208,01 kg/da verim alınmıştır. Baklada tane sayısı ve tane verimi bakımından farklılık çıkmış incelenen diğer özellikler bakımından farklılıkların oluşmadığı görülmüştür. Araştırma da ele alınan farklı iki yetiştiriciliğin uygulanabilirlik durumları incelenmiş ve organik yetiştiriciliğin Erzincan bölgesinde yapılabilir olduğu tespit edilmiştir

Self-Congruence and Tourist Happiness: The Mediating Role of Positive Emotions and Meaning

Although a considerable number of earlier studies have empirically investigated the effects of self-congruity on various constructs such as motivation, revisit intention, word-of-mouth, and evaluation of a destination (e.g. Usakli and Baloglu, 2011; Tassiello and Tillotson, 2020; Šegota, Chen and Golja, 2021), the direct and indirect relationship between self-congruity and tourist happiness remain under-investigated in tourism and hospitality settings (Sirgy, 2019). Therefore, to fill this gap in the literature, drawing on marketing, psychology, and tourism literature, the present study aims to investigate the relationship between self-congruity and tourist happiness via the influence of positive emotions (hedonia) and meaning (eudaimonia). The integrative model was tested using data generated from a convenient sample of 460 tourists from USA. Using Structural Equation Modelling (SEM), a powerful multivariate statistical analysis technique, the results statistically confirm that actual and ideal self-congruity influence tourist happiness and the conditions necessary for mediation are supported

Do repeated surgical interventions in patients with lumbar paraspinal Ewing's sarcoma increase survival by supporting pharmacological treatment? A comprehensive systematic review

Aim: To present the medical and surgical treatment of a patient who was diagnosed with Ewing's sarcoma (EWS) in the paraspinal region and was operated on, in line with a comprehensive systematic literature review. Method: A comprehensive and systematic literature search of electronic databases was performed. Keywords used were “EWS” and “EWS treatment”. Randomized, controlled clinical trials were included in the study. Letters to the editor, bibliographies, reviews, and meta-analyses were excluded. In addition, our EWS case was presented in full detail. Results As a results of a comprehensive and systematic literature search of electronic databases, the full texts of the appropriate 323 studies conducted between the years 1786 to 2021 were retrieved and evaluated. In the case we present here, the expandable mass was largely excised together with the invasive skin tissue. Immunohistochemical examination of the excised tumor tissue using vimentin antibody revealed that the mass was compatible with EWS, a mesenchymal malignant tumor. Conclusion: Many different pharmacological agents can be administered in different posologies and different combinations before and after paraspinal/paravertebral lumbar surgery of EWS.  Further studies containing more cases from different races, gender must be performed to comprehensively evaluate the effects of repeated surgical interventions of patients with EWS  due to recurrence and/or residue, which may positively contribute to patient's survival and prognosis by giving more time to standard chemotherapy