| 1. |
|
|
| 2. |
- Ahmad, Iftikhar, et al.
(författare)
-
Fake News Detection Using Machine Learning Ensemble Methods
- 2020
-
Ingår i: Complexity. - : WILEY-HINDAWI. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- The advent of the World Wide Web and the rapid adoption of social media platforms (such as Facebook and Twitter) paved the way for information dissemination that has never been witnessed in the human history before. With the current usage of social media platforms, consumers are creating and sharing more information than ever before, some of which are misleading with no relevance to reality. Automated classification of a text article as misinformation or disinformation is a challenging task. Even an expert in a particular domain has to explore multiple aspects before giving a verdict on the truthfulness of an article. In this work, we propose to use machine learning ensemble approach for automated classification of news articles. Our study explores different textual properties that can be used to distinguish fake contents from real. By using those properties, we train a combination of different machine learning algorithms using various ensemble methods and evaluate their performance on 4 real world datasets. Experimental evaluation confirms the superior performance of our proposed ensemble learner approach in comparison to individual learners.
|
|
| 3. |
- Ahmad, Iftikhar, et al.
(författare)
-
Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection
- 2020
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- Vegetable and fruit plants facilitate around 7.5 billion people around the globe, playing a crucial role in sustaining life on the planet. The rapid increase in the use of chemicals such as fungicides and bactericides to curtail plant diseases is causing negative effects on the agro-ecosystem. The high scale prevalence of diseases in crops affects the production quantity and quality. Solving the problem of early identification/diagnosis of diseases by exploiting a quick and consistent reliable method will benefit the farmers. In this context, our research work focuses on classification and identification of tomato leaf diseases using convolutional neural network (CNN) techniques. We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. We test the underlying models on two datasets, a laboratory-based dataset and self-collected data from the field. We observe that all architectures perform better on the laboratory-based dataset than on field-based data, with performance on various metrics showing variance in the range 10%–15%. Inception V3 is identified as the best performing algorithm on both datasets.
|
|
| 4. |
- Alghamdi, Azza, et al.
(författare)
-
Attractors of compactly generated semigroups of regular polynomial mappings.
- 2018
-
Ingår i: Complexity. - : Hindawi Limited. - 1076-2787 .- 1099-0526.
-
Tidskriftsartikel (refereegranskat)abstract
- We investigate the metric space of pluriregular sets as well as the contractions on that space induced by infinite compact families of proper polynomial mappings of several complex variables. The topological semigroups generated by such families, with composition as the semigroup operation, lead to the constructions of a variety of Julia-type pluriregular sets. The generating families can also be viewed as infinite iterated function systems with compact attractors. We show that such attractors can be approximated both deterministically and probabilistically in a manner of the classic chaos game.
|
|
| 5. |
- Baroumand, Salman, et al.
(författare)
-
A Covariance Feedback Approach to Covariance Control of Nonlinear Stochastic Systems
- 2020
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, the covariance control algorithm for nonlinear stochastic systems using covariance feedback is studied. Covariance control of nonlinear systems scenario involves the theory of covariance control based on the idea of the covariance feedback. Therefore, the proposed covariance control algorithm is derived for our case, firstly by applying the covariance control method and linear approximation of nonlinear systems, and then it is achieved by adopting this method for a class of nonlinear stochastic systems by using feedback linearization idea and a covariance feedback controller. The effectiveness of the proposed covariance feedback algorithm is studied using numerous simulations concerning different nonlinear case studies.
|
|
| 6. |
|
|
| 7. |
- Gil, David, et al.
(författare)
-
Review of the Complexity of Managing Big Data of the Internet of Things
- 2019
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2019
-
Forskningsöversikt (refereegranskat)abstract
- There is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing field of the Internet of Things (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description Framework (RDF), and the application of machine learning methods to carry out classifications, predictions, and visualizations. In this review, the state of the art of all the aforementioned aspects of Big Data in the context of the Internet of Things is exposed. The most novel technologies in machine learning, deep learning, and data mining on Big Data are discussed as well. Finally, we also point the reader to the state-of-the-art literature for further in-depth studies, and we present the major trends for the future.
|
|
| 8. |
- Lamb, Maurice, et al.
(författare)
-
A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions
- 2019
-
Ingår i: Complexity. - : John Wiley & Sons. - 1076-2787 .- 1099-0526.
-
Tidskriftsartikel (refereegranskat)abstract
- Interactive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation in these collaborative pick-and-place tasks could also include robotic assistants. However, for human-machine and human-robot interactions, interactive pick-and-place tasks present a unique set of challenges. A key challenge is that high-level task-representational algorithms and preplanned action or motor programs quickly become intractable, even for simple interaction scenarios. Here we address this challenge by introducing a bioinspired behavioral dynamic model of free-flowing cooperative pick-and-place behaviors based on low-dimensional dynamical movement primitives and nonlinear action selection functions. Further, we demonstrate that this model can be successfully implemented as an artificial agent control architecture to produce effective and robust human-like behavior during human-agent interactions. Participants were unable to explicitly detect whether they were working with an artificial (model controlled) agent or another human-coactor, further illustrating the potential effectiveness of the proposed modeling approach for developing systems of robust real/embodied human-robot interaction more generally.
|
|
| 9. |
- Liu, Biyu, et al.
(författare)
-
Optimal Operational Decision Making of Manufacturers and Authorized Remanufacturers with Patent Licensing under Carbon Cap-and-Trade Regulations
- 2020
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- Constrained by production capacity and the pressure to reduce emissions, many original equipment manufacturers (OEMs) authorize third-party remanufacturers (TPRs) to remanufacture patented products. We investigate the operational decisions of OEMs and authorized TPRs under carbon cap-and-trade regulations in a two-echelon supply chain. We first formulate an operational decision model for OEMs before a TPR enters. Then, for the cases of centralized and decentralized decision making, we formulate an operational decision-making model for the TPR and, subsequently, establish one for the OEM after the TPR enters. We further analyze the effects of carbon emissions cap, trading price of carbon permits, yield rate, and consumer willingness to pay (WTP) on optimal decisions. Our results indicate: whether TPRs accept authorization remanufacturing depending on the ratio of carbon emissions cap to carbon emissions for producing per remanufactured product; royalty rate is negatively affected by trading price of carbon permits and per remanufactured product’ carbon emissions other than that for per new product, and can offset the threat caused by TPRs; the implementation of carbon cap-and-trade regulations causes OEMs to charge TPRs lower royalty rate; centralized decision making increases the total profit of the supply chain and delivers superior environmental benefits. As yield rate and WTP increase, the total profit increases, increasingly sensitive to WTP.
|
|
| 10. |
- Lizier, Joseph T., et al.
(författare)
-
An Interview-Based Study of Pioneering Experiences in Teaching and Learning Complex Systems in Higher Education
- 2018
-
Ingår i: Complexity. - : Hindawi Limited. - 1076-2787 .- 1099-0526. ; 2018
-
Tidskriftsartikel (refereegranskat)abstract
- Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at university level have diverse disciplinary backgrounds. This brings challenges (e.g., wide range of computer programming skills) but also opportunities (e.g., facilitating interdisciplinary interactions and projects) for the classroom. However, little has been published regarding how these challenges and opportunities are handled in teaching and learning complex systems as an explicit subject in higher education and how this differs in comparison to other subject areas. We seek to explore these particular challenges and opportunities via an interview-based study of pioneering teachers and learners (conducted amongst the authors) regarding their experiences. We compare and contrast those experiences and analyze them with respect to the educational literature. Our discussions explored approaches to curriculum design, how theories/models/frameworks of teaching and learning informed decisions and experience, how diversity in student backgrounds was addressed, and assessment task design. We found a striking level of commonality in the issues expressed as well as the strategies handling them, for example, a significant focus on problem-based learning and the use of major student-led creative projects for both achieving and assessing learning outcomes.
|
|
