Browsing Computer Science by Title
Now showing items 367-386 of 549
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On spectral analysis of the Internet delay space and detecting anomalous routing paths
(TÜBİTAK, 2019)Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ... -
On the co-absence of input terms in higher order neuron representation of boolean functions
(Springer International Publishin, 2017)Boolean functions (BFs) can be represented by using polynomial functions when −1 and +1 are used represent True and False respectively. The coefficients of the representing polynomial can be obtained by exact interpolation ... -
On the use of evolutionary coupling for software architecture recovery
(IEEE, 2021)Software architecture documentation can be partially obtained automatically by means of software architecture recovery tools. These tools mainly cluster software modules to provide a high level structural organization of ... -
On the use of machine learning for predicting defect fix time violations
(Science and Technology Publications, 2022)Accurate prediction of defect fix time is important for estimating and coordinating software maintenance efforts. Likewise, it is useful to predict whether or not the initially estimated defect fix time will be exceeded ... -
Online association rule mining over fast data
(IEEE, 2013)To extract useful and actionable information in real-time, the information technology (IT) world is coping with big data problems today. In this paper, we present implementation details and performance results of ReCEPtor, ... -
Optimal negotiation decision functions in time-sensitive domains
(IEEE, 2015)The last two decades have seen a growing interest in automated agents that are able to negotiate on behalf of human negotiators in a wide variety of negotiation domains. One key aspect of a successful negotiating agent is ... -
Optimization by runtime specialization for sparse matrix-vector multiplication
(ACM, 2014)Runtime specialization optimizes programs based on partial information available only at run time. It is applicable when some input data is used repeatedly while other input data varies. This technique has the potential ... -
Optimizing complex sequence pattern extraction using caching
(IEEE, 2011)Complex Event Processing (CEP) has become increasingly important for tracking and monitoring complex event anomalies and trends in event streams emitted from business processes such as supply chain management to online ... -
Optimizing decomposition of software architecture for local recovery
(Springer Science+Business Media, 2013-06)The increasing size and complexity of software systems has led to an amplified number of potential failures and as such makes it harder to ensure software reliability. Since it is usually hard to prevent all the failures, ... -
Optimum encoding approaches on video resolution changes: a comparative study
(IEEE, 2018)Video resolution changes in an HTTP adaptive streaming session may negatively affect the viewer's quality of experience. Our goal is, through encoding, to make such resolution changes less noticeable for the viewers. This ... -
ORTPiece: An ORT-based Turkish image captioning network based on transformers and WordPiece
(IEEE, 2023)Recent transformers-based systems are advancing image captioning applications. However, those works have been mainly applied to English-based image captioning problems. In this paper, we introduce a transformers-based ... -
OzU-NLP at TREC NEWS 2019: Entity ranking
(National Institute of Standards and Technology (NIST), 2019)This paper presents our work and submission for TREC 2019 News Track: Entity Ranking Task. Our approach utilizes Doc2Vec's ability to represent documents as fixed sized numerical vectors. Applied on news articles and ... -
Öbekleme eniyilemesi ve sağlamlığı için yinelemeli bir yaklaşım
(IEEE, 2012)Clustering is a common technique, in all areas where information is obtained from the collected data. In this work, three well-known clustering algorithms namely, K-means, Spectral and DBSCAN are investigated in terms of ... -
ÖZÜ konuşmacı doğrulama sisteminin çok sınıflı senaryoda NIST 2010 veritabanı ile başarımı
(IEEE, 2011)Performance of the speaker verification systems is typically measured based on their binary decision accuracy. However, in speaker verification applications where close to %100 accuracy is required, such as the systems ... -
Parental scaffolding as a bootstrapping mechanism for learning grasp affordances and imitation skills
(Cambridge University Press, 2015-06)Parental scaffolding is an important mechanism that speeds up infant sensorimotor development. Infants pay stronger attention to the features of the objects highlighted by parents, and their manipulation skills develop ... -
Partial observable update for subjective logic and its application for trust estimation
(Elsevier, 2015)Subjective Logic (SL) is a type of probabilistic logic, which is suitable for reasoning about situations with uncertainty and incomplete knowledge. In recent years, SL has drawn a significant amount of attention from the ... -
Patch-wise contrastive style learning for instagram filter removal
(IEEE, 2022)Image-level corruptions and perturbations degrade the performance of CNNs on different downstream vision tasks. Social media filters are one of the most common resources of various corruptions and perturbations for real-world ... -
Pedestrian tracking in outdoor spaces of a suburban university campus for the investigation of occupancy patterns
(Elsevier, 2019-02)The design of a livable and comfortable environment has been one of the main aims of sustainable university campus design. The creation of outdoor spaces for accommodating amenities has a positive effect on users with ... -
Performance analysis of ACTE: A bandwidth prediction method for low-latency chunked streaming
(Association for Computing Machinery, Inc, 2020-07)HTTP adaptive streaming with chunked transfer encoding can offer low-latency streaming without sacrificing the coding efficiency. This allows media segments to be delivered while still being packaged. However, conventional ... -
Performance analysis of meta-learning based bayesian deep kernel transfer methods for regression tasks
(IEEE, 2023)Meta-learning aims to apply existing models on new tasks where the goal is 'learning to learn' so that learning from a limited amount of labeled data or learning in a short amount of time is possible. Deep Kernel Transfer ...
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