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- research-articleOctober 2024
What Makes Programmers Laugh? Exploring the Submissions of the Subreddit r/ProgrammerHumor.
ESEM '24: Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and MeasurementPages 371–381https://doi.org/10.1145/3674805.3686696Background: Humor is a fundamental part of human communication, with prior work linking positive humor in the workplace to positive outcomes, such as improved performance and job satisfaction. Aims: This study aims to investigate programming-related ...
- research-articleOctober 2024
MTSCI: A Conditional Diffusion Model for Multivariate Time Series Consistent Imputation
CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge ManagementPages 3474–3483https://doi.org/10.1145/3627673.3679532Missing values are prevalent in multivariate time series, compromising the integrity of analyses and degrading the performance of downstream tasks. Consequently, research has focused on multivariate time series imputation, aiming to accurately impute the ...
- research-articleSeptember 2024
Multi-source transfer learning via optimal transport feature ranking for EEG classification
AbstractMotor imagery (MI) brain-computer interface (BCI) paradigms have been extensively used in neurological rehabilitation. However, due to the required long calibration time and non-stationary nature of electroencephalogram (EEG) signals, it is ...
- research-articleJuly 2024
QBDD: Quantum-resistant blockchain-assisted deep data deduplication protocol for vehicular crowdsensing system
Computer Networks: The International Journal of Computer and Telecommunications Networking (CNTW), Volume 245, Issue Chttps://doi.org/10.1016/j.comnet.2024.110393AbstractVehicular Crowdsensing System (VCS) has emerged as a promising paradigm for alleviating traffic congestion and improving driving safety due to its convenient collection and aggregation of various driving and traffic-related reports. However, the ...
- research-articleApril 2024
SynDroid: An adaptive enhanced Android malware classification method based on CTGAN-SVM
AbstractAndroid mobile phones have the highest market share nowadays, bringing a boom of Android application programming as well as malicious software (malware) issues. Traditional machine learning and deep learning methods are widely used in Android ...
- research-articleMarch 2024
Revealing complexities when adult readers engage in the credibility evaluation of social media posts
- Miikka Kuutila,
- Carita Kiili,
- Reijo Kupiainen,
- Eetu Huusko,
- Junhao Li,
- Simo Hosio,
- Mika Mäntylä,
- Julie Coiro,
- Kristian Kiili
AbstractThe internet, including social networking sites, has become a major source of health information for laypersons. Yet, the internet has also become a platform for spreading misinformation that challenges adults’ ability to critically evaluate the ...
Highlights- We explored how adults evaluated the credibility of health-related social media posts.
- Posts varied in terms of claim accuracy, evidence type, and source characteristics.
- Source expertise and prior belief consistency affected ...
- research-articleMay 2024
Robust Detection for Adversarial Attacks - Based on a Graph Neural Network for Web Application Security Protection System
ICAICE '23: Proceedings of the 4th International Conference on Artificial Intelligence and Computer EngineeringPages 927–932https://doi.org/10.1145/3652628.3652782This paper focuses on constructing a graph neural network deep learning model to analyse malicious Web requests and make timely warnings, in addition to generating adversarial samples for graph data structures through PGD topology attacks, conducting ...
- research-articleSeptember 2023
Assessing Credibility Factors of Short-Form Social Media Posts: A Crowdsourced Online Experiment
- Junhao Li,
- Miikka Kuutila,
- Eetu Huusko,
- Nimantha Kariyakarawana,
- Marko Savic,
- Nazanin Nakhaie Ahooie,
- Simo Hosio,
- Mika Mäntylä
CHItaly '23: Proceedings of the 15th Biannual Conference of the Italian SIGCHI ChapterArticle No.: 9, Pages 1–14https://doi.org/10.1145/3605390.3605406People commonly turn to the Internet and social media for their information needs. Most popular social media platforms focus on short-form content that can be consumed rapidly. Given how fast such content spreads online, its trustworthiness and ...
- ArticleJuly 2023
Dynamic Resampling Based Boosting Random Forest for Network Anomaly Traffic Detection
Advances and Trends in Artificial Intelligence. Theory and ApplicationsPages 333–344https://doi.org/10.1007/978-3-031-36822-6_29AbstractNetwork anomaly traffic detection is an important technique for detecting intrusion activities and maintaining cyberspace security. Random forest is widely used in network anomalous traffic detection due to its good detection performance. However, ...
- research-articleMarch 2023
It is an online platform and not the real world, I don’t care much: Investigating Twitter Profile Credibility With an Online Machine Learning-Based Tool
- Junhao Li,
- Ville Paananen,
- Sharadhi Alape Suryanarayana,
- Eetu Huusko,
- Miikka Kuutila,
- Mika Mäntylä,
- Simo Hosio
CHIIR '23: Proceedings of the 2023 Conference on Human Information Interaction and RetrievalPages 117–127https://doi.org/10.1145/3576840.3578308Social media is now an important source of everyday information. Given the plethora of scandals concerning the rapid spread of misinformation and disinformation on social media, the credibility of the content on these platforms is now a pivotal research ...
- ArticleJanuary 2023
TGPFM: An Optimized Framework for Ordering and Transporting Raw Materials for Production
AbstractDeveloping efficient raw material ordering and transshipment strategies for companies with uncertain supply has attracted extensive interests from both academic and industrial researchers. Some methods have been proposed, such as obtaining a ...
- ArticleJanuary 2023
Data Reconstruction from Gradient Updates in Federated Learning
AbstractFederated learning has become an emerging technology to protect data privacy in the distributed learning area, by keeping each client user’s data locally. However, recent work shows that client users’ data might still be stolen (or reconstructed) ...
- research-articleOctober 2022
Numerical simulation and experimental analysis on the deformation and residual stress in trailing ultrasonic vibration assisted laser welding
Advances in Engineering Software (ADES), Volume 172, Issue Chttps://doi.org/10.1016/j.advengsoft.2022.103200Highlights- A new welding technology is proposed, which introduces the trailing ultrasonic vibration into the conventional laser welding process.
A trailing ultrasonic-assisted laser welding (T-ULW) technology is first proposed to weld SUS301 stainless steel sheet with a thickness of 0.6 mm. Secondly, welding experiments with conventional laser welding and ultrasonic-assisted ...
- research-articleJanuary 2022
Identification of Gene Regulatory Networks Using Variational Bayesian Inference in the Presence of Missing Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 20, Issue 1Pages 399–409https://doi.org/10.1109/TCBB.2022.3144418The identification of gene regulatory networks (GRN) from gene expression time series data is a challenge and open problem in system biology. This paper considers the structure inference of GRN from the incomplete and noisy gene expression data, which is ...
- ArticleJuly 2021
A Dynamic Processing Algorithm for Variable Data in Intranet Security Monitoring
AbstractNowadays corporate Intranet Security Monitoring generally relies on SIEM products or SOC platforms. The data comes from a large number of system logs, application running logs and business data, which are generated by network device, security ...
- research-articleDecember 2019
Vision-Based Kinematic Configuration Recognition for Re-configurable Modular Robots
2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)Pages 2783–2788https://doi.org/10.1109/ROBIO49542.2019.8961524Re-configurable modular robot systems are advantageous for their scalability and versatility. However, creating kinematic models for every new assembly is a time-consuming and error-prone task. In this paper, a vision-based kinematic configuration ...
- ArticleAugust 2019
Two-Encoder Pointer-Generator Network for Summarizing Segments of Long Articles
AbstractUsually long documents contain many sections and segments. In Wikipedia, one article can usually be divided into sections and one section can be divided into segments. But although one article is already divided into smaller segments, one segment ...
- research-articleDecember 2017
Saliency Detection for Unconstrained Videos Using Superpixel-Level Graph and Spatiotemporal Propagation
IEEE Transactions on Circuits and Systems for Video Technology (IEEETCSVT), Volume 27, Issue 12Pages 2527–2542https://doi.org/10.1109/TCSVT.2016.2595324This paper proposes an effective spatiotemporal saliency model for unconstrained videos with complicated motion and complex scenes. First, superpixel-level motion and color histograms as well as global motion histogram are extracted as the features for ...
- research-articleJune 2017
Partitioning dynamic graph asynchronously with distributed FENNEL
Future Generation Computer Systems (FGCS), Volume 71, Issue CPages 32–42https://doi.org/10.1016/j.future.2017.01.014Graph partitioning is important in distributed graph processing. Classical method such as METIS works well on relatively small graphs, but hard to scale for huge, dynamic graphs. Streaming graph partitioning algorithms overcome this issue by processing ...