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Metrics for evaluating explainable recommender systems
(Springer, 2023)
Recommender systems aim to support their users by reducing information overload so that they can make better decisions. Recommender systems must be transparent, so users can form mental models about the system’s goals, ...
The populist framing of the Russia-Ukraine war by the Hungarian government: convergence or contestation in the EU
(Taylor & Francis, 2023)
This study examines how the Hungarian government frames the Russia-Ukraine War within the context of its relations with the European Union (EU) using discourse historical strand of critical discourse analysis (CDA). This ...
Analysis of communication distance and energy harvesting for vehicular VLC using commercial taillights
(IEEE, 2023)
This paper presents an investigation into the communication range and energy harvesting capabilities of a vehicle-to-vehicle (V2V) visible light communication (VLC) system that utilizes commercial taillights (TLs) as ...
Single photon detection with silicon-based avalanche photodiode
(SPIE, 2023)
Thanks to the significant advances in quantum technologies, the use of single photon detectors (SPDs) is becoming increasingly common. As a result of the excellent photodetection performance of these detectors, they have ...
Capacity planning for forming sustainable and cost-effective nanogrids
(IEEE, 2023)
This paper proposes a new strategy for nanogrid capacity planning as a bilevel programming mathematical model with look-ahead logic. The first program, the Planner, is a linear program that solves for the optimal size of ...
The role of art in the construction of public space: Istanbul biennials from 1987 to 2019
(Springer, 2023)
This study focuses on the interaction of public space and art, and uses the Istanbul Biennale (1987–2019) as an example to explore the role of art in public space. This study firstly examines public space, art in public ...
Bimanual rope manipulation skill synthesis through context dependent correction policy learning from human demonstration
(IEEE, 2023)
Learning from demonstration (LfD) with behavior cloning is attractive for its simplicity; however, compounding errors in long and complex skills can be a hindrance. Considering a target skill as a sequence of motor primitives ...
Optimizing distributed generation sizing and siting using particle swarm optimization: A comparative study
(IEEE, 2023)
In recent years, distributed generation (DG) has become increasingly popular as a means of mitigating the impact of climate change and ensuring a reliable and resilient power supply. To optimize the use of DG, it is essential ...
A comparative study for 6D pose estimation of textureless and symmetric objects used in automotive manufacturing industry
(IEEE, 2023)
6D pose estimation of industrial objects on RGB images has a high potential to accelerate the automation of robotic manipulations in the automotive manufacturing industry. Despite its high potential, this problem has not ...
Using different loss functions with YOLACT++ for real-time instance segmentation
(IEEE, 2023)
In this paper, we study and analyze the performance of various loss functions on a recently proposed real-time instance segmentation algorithm, YOLACT++. In particular, we study the loss functions, including Huber Loss, ...
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