Browsing Computer Science by Title
Now showing items 303-322 of 549
-
Let’s negotiate with jennifer! towards a speech-based human-robot negotiation
(Springer, 2021)Social robots are becoming prevalent in our society, and most of the time, they need to interact with humans in order to accomplish their tasks. Negotiation is one of the inevitable processes they need to be involved to ... -
LIG at MediaEval 2015 multimodal person discovery in broadcast TV task
(CEUR-WS, 2015)In this working notes paper the contribution of the LIG team (partnership between Univ. Grenoble Alpes and Ozyegin University) to the Multimodal Person Discovery in Broadcast TV task in MediaEval 2015 is presented. The ... -
The likeability-success tradeoff: results of the 2nd annual human-agent automated negotiating agents competition
(IEEE, 2019)We present the results of the 2nd Annual Human-Agent League of the Automated Negotiating Agent Competition. Building on the success of the previous year's results, a new challenge was issued that focused exploring the ... -
Load and stress testing for SDN’s northbound API
(Springer Nature, 2020-01)In this work, we apply load and stress testing for well-known Software defined networking (SDN) controllers from an SDN application perspective. More precisely, we focus on the communication between the controller and SDN ... -
Location attestation and access control for mobile devices using GeoXACML
(Elsevier, 2017-02)Access control has been applied in various scenarios in the past for negotiating the best policy. Solutions with XACML for access control has been very well explored by research and have resulted in significant contributions ... -
A longitudinal case study on Nexus transformation: Impact on productivity, quality, and motivation
(Wiley, 2023-09)There have been success stories reported regarding the adoption of agile software development methods in the industry. There also exist observations on their limitations. One of these limitations is scalability since agile ... -
A machine learning approach for mechanism selection in complex negotiations
(Springer Nature, 2018-04)Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A ... -
Machine learning based activity learning for behavioral contexts in Internet of things (IoT)
(Springer Nature, 2020-12)Ontology based activity learning models play a vital role in diverse fields of Internet of Things (IoT) such as smart homes, smart hospitals or smart communities etc. The prevalent challenges with ontological models are ... -
Machine learning to predict junction temperature based on optical characteristics in solid-state lighting devices: A test on WLEDs
(MDPI, 2022-08)While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based ... -
MaLeFICE: Machine learning support for continuous performance improvement in computational engineering
(Wiley, 2022-04-25)Computer aided engineering (CAE) practices improved drastically within the last decade due to ease of access to computing resources and open-source software. However, increasing complexity of hardware and software settings ... -
Manus manum lavat: media clients and servers cooperating with common media client/server data
(ACM, 2021-07-24)The newly rectified CTA standard - Common Media Client Data (CMCD) - allows content providers to get insights into the performance of their large-scale streaming operations. Its sister standard - Common Media Server Data ... -
Marrying WebRTC and DASH for Interactive Streaming
(ACM, 2022-03-17)WebRTC is a set of W3C and IETF standards that allows the delivery of real-time content to users, with an end-to-end latency of under half a second. Support for WebRTC is built into all modern browsers across desktop and ... -
Maximum likelihood estimate of parameters of Nakagami-m distribution
(IEEE, 2012)Nakagami-m distribution is well known for its ability to model a number of probability density functions, be it symmetric or asymmetric. Many Maximum Likelihood parameter estimation techniques for this distribution have ... -
Media over QUIC: Initial testing, findings and results
(ACM, 2023-06-08)With its advantages over TCP, QUIC created a new field for developing media-Aware low-latency delivery solutions. The problem space is being examined by the new Media over QUIC (moq) working group in the IETF. In this ... -
Medical podcasting in Iran; pilot, implementation and attitude evaluation
(Tehran University of Medical Sciences, 2013)Podcasting has become a popular means of transferring knowledge in higher education through making lecture contents available to students at their convenience. Accessing courses on media players provides students with ... -
MedSpecSearch: Medical specialty search
(Springer Nature, 2019)MedSpecSearch (www.medspecsearch.com) is a search engine for helping users to find the relevant medical specialty for a doctor visit based on users’ description of symptoms. This system is useful for users who are not sure ... -
Meta reinforcement learning for rate adaptation
(IEEE, 2023)Adaptive bitrate (ABR) schemes enable streaming clients to adapt to time-varying network/device conditions to achieve a stall-free viewing experience. Most ABR schemes use manually tuned heuristics or learning-based methods. ... -
Metadata-based user interface design for enhanced content access and viewing
(The ACM Digital Library, 2020-05)The nature of viewing is changing due to the huge volumes of content being produced including user content generated by amateurs and the proliferation of personalized services. The type of content being produced is not ... -
Metric labeling and semimetric embedding for protein annotation prediction
(Mary Ann Liebert, Inc., 2021-05-01)Computational techniques have been successful at predicting protein function from relational data (functional or physical interactions). These techniques have been used to generate hypotheses and to direct experimental ... -
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, ...
Share this page
