Browsing Computer Science by Title
Now showing items 168-187 of 549
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Evaluating the effectiveness of multi-level greedy modularity clustering for software architecture recovery
(Springer Nature, 2019)Software architecture recovery approaches mainly analyze various types of dependencies among software modules to group them and reason about the high-level structural decomposition of a system. These approaches employ a ... -
Evaluating the English-Turkish parallel treebank for machine translation
(TÜBİTAK, 2022)This study extends our initial efforts in building an English-Turkish parallel treebank corpus for statistical machine translation tasks. We manually generated parallel trees for about 17K sentences selected from the Penn ... -
Evaluating the performance of apple’s low-latency HLS
(IEEE, 2020-09-21)In its annual developers conference in June 2019, Apple has announced a backwards-compatible extension to its popular HTTP Live Streaming (HLS) protocol to enable low-latency live streaming. This extension offers new ... -
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ... -
Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech
(Springer Science+Business Media, 2015-12)Automatic diagnosis and monitoring of Alzheimer’s disease can have a significant impact on society as well as the well-being of patients. The part of the brain cortex that processes language abilities is one of the earliest ... -
Evidential deep learning to quantify classification uncertainty
(Neural Information Processing Systems Foundation, 2018)Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant ... -
EXPECTATION: Personalized explainable artificial intelligence for decentralized agents with heterogeneous knowledge
(Springer, 2021)Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current ... -
Experimental studies on chemical concentration map building by a multi-robot system using bio-inspired algorithms
(Springer Science+Business Media, 2014-01)In this article we describe implementations of various bio-inspired algorithms for obtaining the chemical gas concentration map of an environment filled with a contaminant. The experiments are performed using Khepera III ... -
Explain to me: Towards understanding privacy decisions
(International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2023)Privacy assistants help users manage their privacy online. Their tasks could vary from detecting privacy violations to recommending sharing actions for content that the user intends to share. Recent work on these tasks are ... -
Explanation-based negotiation protocol for nutrition virtual coaching
(ACM, 2023)People’s awareness about the importance of healthy lifestyles is rising. This opens new possibilities for personalized intelligent health and coaching applications. In particular, there is a need for more than simple ... -
Exploration with intrinsic motivation using object–action–outcome latent space
(IEEE, 2023-06)One effective approach for equipping artificial agents with sensorimotor skills is to use self-exploration. To do this efficiently is critical, as time and data collection are costly. In this study, we propose an exploration ... -
Exploring scaling efficiency of intel loihi neuromorphic processor
(IEEE, 2023)In this paper, we focus on examining how scaling efficiency evolves in winner-take-all (WTA) network models on Intel Loihi neuromorphic processor, as network-related features such as network size, neuron type, and connectivity ... -
Extending static code analysis with application-specific rules by analyzing runtime execution traces
(Springer International Publishing, 2016)Static analysis tools cannot detect violations of application-specific rules. They can be extended with specialized checkers that implement the verification of these rules. However, such rules are usually not documented ... -
Extraction of novel features based on histograms of MFCCs used in emotion classification from generated original speech dataset
This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from ... -
Extraction of novel features based on histograms of mfccs used in emotion classification from generated original speech dataset
(Kauno Technologijos Universitetas, 2020-02-17)This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from ... -
FAS: introducing a service for avoiding faults in composite services
(Springer Science+Business Media, 2012)In service-oriented architectures, composite services depend on a set of partner services to perform the required tasks. These partner services may become unavailable due to system and/or network faults, leading to an ... -
Fashion image retrieval with capsule networks
(IEEE, 2019)In this study, we investigate in-shop clothing retrieval performance of densely-connected Capsule Networks with dynamic routing. To achieve this, we propose Triplet-based design of Capsule Network architecture with two ... -
Fast and efficient implementation of lightweight crypto algorithm PRESENT on FPGA through processor instruction set extension
(IEEE, 2019)As Internet of Things (IoT) technology becomes widespread, the importance of information security increases. PRESENT algorithm is a major lightweight symmetric-key encryption algorithm for IoT devices. Compared to the ... -
Fast and efficient terrain-aware motion planning for exploration rovers
(IEEE, 2021)This paper presents a fast, energy-efficient, and low computational cost traversal solution on sloped terrain. The use of grid-based search algorithms requires high computational power and takes a long time because almost ... -
A fast circuit topology for finding the maximum of n k-bit numbers
(IEEE, 2013)Finding the value and/or address (position) of the maximum element of a set of binary numbers is a fundamental arithmetic operation. Numerous systems, which are used in different application areas, require fast (low-latency) ...
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