Doppler filtering approach to reduce the effect of in‐band interference in FMCW propagation data

Recommender System (RS) is an information filtering approach that helps the overburdened user with information in his decision making process and suggests items which might be interesting to him. While presenting recommendation to the user, accuracy of the presented list is always a concern for the researchers. However, in recent years, the focus has now shifted to include the unexpectedness and novel items in the list along with accuracy of the recommended items. To increase the user acceptance, it is important to provide potentially interesting items which are not so obvious and different from the items that the end user has rated. In this work, we have proposed a model that generates serendipitous item recommendation and also takes care of accuracy as well as the sparsity issues. Literature suggests that there are various components that help to achieve the objective of serendipitous recommendations. In this paper, fuzzy inference based approach is used for the serendipity computation because the definitions of the components overlap. Moreover, to improve the accuracy and sparsity issues in the recommendation process, cross domain and trust based approaches are incorporated. A prototype of the system is developed for the tourism domain and the performance is measured using mean absolute error (MAE), root mean square error (RMSE), unexpectedness, precision, recall and F-measure.

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Contextualized Filtering for Shared Cyber Threat Information

Sensors ◽

10.3390/s21144890 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4890

Author(s):

Athanasios Dimitriadis ◽

Christos Prassas ◽

Jose Luis Flores ◽

Boonserm Kulvatunyou ◽

Nenad Ivezic ◽

...

Keyword(s):

Information Sharing ◽

Business Processes ◽

State Of The Art ◽

Contextual Information ◽

Coarse Grained ◽

Business Information ◽

Cyber Threat ◽

Domain Expertise ◽

Multi Level ◽

Filtering Approach

Cyber threat information sharing is an imperative process towards achieving collaborative security, but it poses several challenges. One crucial challenge is the plethora of shared threat information. Therefore, there is a need to advance filtering of such information. While the state-of-the-art in filtering relies primarily on keyword- and domain-based searching, these approaches require sizable human involvement and rarely available domain expertise. Recent research revealed the need for harvesting of business information to fill the gap in filtering, albeit it resulted in providing coarse-grained filtering based on the utilization of such information. This paper presents a novel contextualized filtering approach that exploits standardized and multi-level contextual information of business processes. The contextual information describes the conditions under which a given threat information is actionable from an organization perspective. Therefore, it can automate filtering by measuring the equivalence between the context of the shared threat information and the context of the consuming organization. The paper directly contributes to filtering challenge and indirectly to automated customized threat information sharing. Moreover, the paper proposes the architecture of a cyber threat information sharing ecosystem that operates according to the proposed filtering approach and defines the characteristics that are advantageous to filtering approaches. Implementation of the proposed approach can support compliance with the Special Publication 800-150 of the National Institute of Standards and Technology.

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State of Charge Estimation of Lithium-ion Batteries Subject to Random Sensor Data Unavailability: A Recursive Filtering Approach

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2021.3078376 ◽

2021 ◽

pp. 1-1

Author(s):

Hui Chen ◽

Engang Tian ◽

Licheng Wang

Keyword(s):

Lithium Ion Batteries ◽

Lithium Ion ◽

State Of Charge ◽

Sensor Data ◽

Recursive Filtering ◽

State Of Charge Estimation ◽

Filtering Approach

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Dual-finite distributed H∞ filtering in sensor networks

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651821997587 ◽

2021 ◽

pp. 095965182199758

Author(s):

Changshuo Wang ◽

Jiwei Wen ◽

Xiaoli Luan

Keyword(s):

Sensor Networks ◽

Disturbance Attenuation ◽

Time Interval ◽

Frequency Range ◽

Frequency Scale ◽

Attenuation Level ◽

Exogenous Noise ◽

Disturbance Attenuation Level ◽

Reference Input ◽

Filtering Approach

Generally, distributed H∞ filtering approach achieves a certain disturbance attenuation level in the full frequency range. However, the energy of system noise or reference input usually limits in a specified frequency range. To reduce such a design conservatism, this article develops a distributed filtering approach based on dual scale, that is, filtering over a finite-time interval from time scale and also on a specified finite-frequency region from the frequency scale. Our target is to make the filtering error under sensor networks monitoring be relaxed into an ellipsoid bound rather than asymptotically converging to zero for exogenous noise in a specified frequency range. Finally, two illustrative examples demonstrate the strength of the developed filtering approach.

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