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48 results on '"Boujnah, Noureddine"'

1. Synthetic Time Series for Anomaly Detection in Cloud Microservices

Author

Allam, Mohamed, Boujnah, Noureddine, O'Connor, Noel E., and Liu, Mingming

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

This paper proposes a framework for time series generation built to investigate anomaly detection in cloud microservices. In the field of cloud computing, ensuring the reliability of microservices is of paramount concern and yet a remarkably challenging task. Despite the large amount of research in this area, validation of anomaly detection algorithms in realistic environments is difficult to achieve. To address this challenge, we propose a framework to mimic the complex time series patterns representative of both normal and anomalous cloud microservices behaviors. We detail the pipeline implementation that allows deployment and management of microservices as well as the theoretical approach required to generate anomalies. Two datasets generated using the proposed framework have been made publicly available through GitHub., Comment: The paper has been accepted by the 10th International Conference on Machine Learning, Optimization and Data Science

Published
2024

3. MAC Protocols for Terahertz Communication: A Comprehensive Survey

Author

Ghafoor, Saim, Boujnah, Noureddine, Rehmani, Mubashir Husain, and Davy, Alan

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Terahertz communication is emerging as a future technology to support Terabits per second link with highlighting features as high throughput and negligible latency. However, the unique features of the Terahertz band such as high path loss, scattering and reflection pose new challenges and results in short communication distance. The antenna directionality, in turn, is required to enhance the communication distance and to overcome the high path loss. However, these features in combine negate the use of traditional Medium access protocols. Therefore novel MAC protocol designs are required to fully exploit their potential benefits including efficient channel access, control message exchange, link establishment, mobility management, and line-of-sight blockage mitigation. An in-depth survey of Terahertz MAC protocols is presented in this paper. The paper highlights the key features of the Terahertz band which should be considered while designing an efficient Terahertz MAC protocol, and the decisions which if taken at Terahertz MAC layer can enhance the network performance. Different Terahertz applications at macro and nano scales are highlighted with design requirements for their MAC protocols. The MAC protocol design issues and considerations are highlighted. Further, the existing MAC protocols are also classified based on network topology, channel access mechanisms, and link establishment strategies as Transmitter and Receiver initiated communication. The open challenges and future research directions on Terahertz MAC protocols are also highlighted., Comment: Submitted to IEEE Communication Surveys and Tutorials Journal

Published
2019

5. Link Level Capacity Analysis of Precoded FBMC/OQAM Systems

Author

Ghodhbane, Jihed, Boujnah, Noureddine, Bouallegue, Ridha, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2020
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6. Energy Saving in HetNet Network Using eNB Parameters Tuning

Author

Lassoued, Narjes, Boujnah, Noureddine, Bouallegue, Ridha, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2019
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9. NIVA Geotagged Photos AI Platform and Irish Challenge (privacy and pasture identification)

Author

Hearne, Dave and Boujnah, Noureddine Dr

Subjects
Geotagged photos, NIVA4CAP, AI, pasture detection, face detection, image classification
Abstract

As part of the NIVA project, a platform for AI powered auto review and pre-validation of geo-tagged agriculture images for IACS (Integrated Administration and Control System) will be developed. This platform, described in this presentation,is developed by TheWalton Institute/ South East Technological University,on behalf of NIVA. The platform is split into two main aspects, a general facility for image uploading and tagging, and a facility for reviewing by a human or auto-reviewing by an AI model. For the targeted initial three auto-review (AI) tasks, suitable auto-review challenges have been proposed by Paying Agencies. Including the Irish challenge (pasture identification)for which the model training and validation is described in this document. In Ireland it is already possible for farmers to use images from a geo-tagged app to prove presence of pasture. However, this is resulting in many images being sent in and needing manual inspection for approval. A possible pre-selection by an AI model is helpful. This document summarises AI work on pasture identification and soil quality. Additionally models trained to detect and obscure faces (privacy preservation) are described. All source code is available in NIVA gitlab -–https://gitlab.com/niva-ai-platform. A full wiki is also available -–https://gitlab.com/niva-ai-platform/infrastructure/-/wikis/Architecture.

Published
2022
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25. A new hybrid deep learning model for human action recognition.

Author

Jaouedi, Neziha, Boujnah, Noureddine, and Bouhlel, Med Salim

Subjects
HUMAN activity recognition, HUMAN behavior, BLENDED learning, DEEP learning, RECURRENT neural networks
Abstract

Human behavior has been always an important factor in social communication. The human activity and action recognition are all clues that facilitate the analysis of human behavior. Human action recognition is an important challenge in a variety of application including human-computer interaction and intelligent video surveillance to enhance security in different domains. The evaluation algorithm relies on the proper extraction and the learning data. The success of the deep learning led to many imposing results in several contexts that include neural network. Here the emergence of Gated Recurrent Neural Networks with increased computation powers is being adopted for sequential data and video classification. However, to have an efficient classifier for assigning the class label, it is very necessary to have a strong features vector. Features are the most important information in each data. Indeed, features extraction can influence on the performance of the algorithm and the computation complexity. This paper proposes a novel approach for human action recognition based on hybrid deep learning model. The proposed approach is evaluated on the challenging UCF Sports, UCF101 and KTH datasets. An average of 96.3% is obtained when we have tested on KTH dataset. [ABSTRACT FROM AUTHOR]

Published
2020
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39. Design of MIMO Satellite System: Inter-antenna Spacing Determination and Possible Enhancement of Capacity

Author

Boujnah Noureddine and Issaoui Leyla

Subjects
Computer science, business.industry, Covariance matrix, MIMO, Throughput, Satellite system, Data_CODINGANDINFORMATIONTHEORY, Antenna diversity, Precoding, Hardware_GENERAL, Communications satellite, Electronic engineering, Telecommunications, business, Computer Science::Information Theory, Communication channel
Abstract

MIMO(Multiple Input Multiple Output) technology was found to exploit the channel richness and spatial diversity, its possible to increase data throughput and reduce the error probability [1]. MIMO channel capacity was derived by Teletar in [2], MIMO find its application in many technology such as HSPA and WLAN. Recent research were devoted to applicability of MIMO to satellite communication and for high altitude platforms (HAPs) [3]. Previous works were concentrated on describing the MIMO model [4] by mean of ray tracing. This paper is organized as follow: first, we investigate MIMO-SAT model for clear sky case and presents new method of computation of the covariance matrix in order to determine the inter-antenna spacing for the MIMO-SAT system at ground and in the satellite side by mean of capacity maximization. The second part will be devoted to MIMO-SAT model with atmospheric effect and impairment mitigation using precoding and dual polarization scheme.

Published
2011

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