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Fine Tuning an AraT5 Transformer for Arabic Abstractive Summarization

Fine Tuning an AraT5 Transformer for Arabic Abstractive Summ...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Yasmin Einieh Amal Almansour Amani Jamal Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9781665487726

Creating an abstractive summary of a document by rephrasing its most crucial sentences is a challenging but crucial task in natural language processing. the field witnessed a remarkable development with deep learning techniques, especially with the emergence of pre-trained models that achieved the best results by training them on very large data and trained later on specific tasks. In this paper, we used the T5 model, which achieved results that are considered the best in different tasks of natural language processing. AraT5 is the newly launched Arabic language version, as we have worked on fine-tuning it on a dataset of 267,000 Arabic articles. the model was evaluated through ROUGE-1, ROUGE-2, ROUGE-L, and BLEU and the results were 0.494 0.339 0.469 0.4224, respectively. In addition, the AraT5 model is superior to other state-of-the-art research studies using the sequence-to-sequence model.

关键词： Training Deep learning Computational modeling Transformers Natural language processing Data models communication networks

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WSN Routing Protocols: Anonymity Prospective Analysis

WSN Routing Protocols: Anonymity Prospective Analysis

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international conference on Computational Intelligence and communication networks (CICN)

作者： Abdulrahman Abu Elkhail Uthman Baroudi Mohammed Younis Department of Computer Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

ISBN: (纸本)9781665487726

A Wireless Sensor Network (WSN) is composed of a number of sensor nodes and a single Base-Station (BS), distributed randomly in an area of interest. WSNs have proven very beneficial in various applications in unattended setup in many domains such as scientific, civil, and military. In these applications, sensors send their measurements to the Base Station over multi-hop wireless routes where the Base Station is responsible for collecting and processing the sensed data. Given the importance of the BS, a potential attacker would look to locate the base station by examining network traffic patterns in order to launch specific attacks intended to interfere with network functionality. In this paper, we analyze traffic analysis attack models from the viewpoint of an adversary. Additionally, we examine the benefits and drawbacks of various routing protocols in terms of exposing the network to traffic analysis attacks. Our evaluation is supported by simulation results.

关键词： Wireless communication Measurement Wireless sensor networks Base stations Analytical models Simulation Telecommunication traffic

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Accuracy Prediction on Detection of Breast Cancer Using Machine Learning Classifiers

Accuracy Prediction on Detection of Breast Cancer Using Mach...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Aditya Pratap Singh Shobit Agrawal Computer Engineering and Application GLA University Mathura INDIA

ISBN: (纸本)9781665487726

Breast Cancer becomes a curse to women, and it increases day by day. So, there is a need for a more reliable and precise method for its detection. In this technical era, the medical field has become more advanced with its integration with computer technology. Its detection accuracy is proven more than humans. As it detects the feature that may remain unnoticed by humans. So, in this proposed work it is studied to detect the type of cancers how it can be detected using machine learning algorithm which algorithm is best for detection of these type of dataset i.e. (malignant and benign) these are further introduced in this work. the used dataset has 569 instances with 30 attributes. therefore, several machine learning techniques i.e., naïve Bayes, logistics Regression, decision tree, k nearest neighbor (KNN), adaptive boosting (Adaboost) are used to make a comparative analysis of these algorithms on basis of their accuracy. Logistic regression outperforms the other classifiers in terms of confusion matrix parameter.

关键词： Machine learning algorithms Prediction algorithms Feature extraction Breast cancer Classification algorithms Reliability communication networks

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An Empirical Study on Fake News Prediction with Machine Learning Methods

An Empirical Study on Fake News Prediction with Machine Lear...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Manisha Aluri Divya Panchumarthi Bhargav Boddupalli Murali Krishna Enduri Sumana G Sree Satish Anamalamudi Department of CSE SRM University AP India

ISBN: (纸本)9781665487726

Due to advancement in technology and distributed networking, there is huge information available on the internet. Due to this, it is possible that some users may try to post fake news through some platforms to get the financial credibility. A common user finds it difficult to differentiate the fake news in comparison with the authentic news. Due to this, a fake news can be main agenda against a particular individual, society, organization or even related to political party. To date, lot of research has been done to detect the fake news on the internet. But, most of the solutions are proposed by comparing with very few performance metrics along with limited data sets. In this work, we propose to use Decision tree, SVM, LSTM, Naive Bayes techniques to analyse and observe the behavior on different datasets. Furthermore, we compare and demonstrate the best approach through experimental analysis.

关键词： Support vector machines Measurement Organizations Machine learning Behavioral sciences Decision trees communication networks

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Development of Proximity-Coupled-Fed S-Band Array Antenna for Microwave Imaging

Development of Proximity-Coupled-Fed S-Band Array Antenna fo...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Sri Muliyani Fauzia Anis Sekar Ningrum Edwar Achmad Munir Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Satellite Communication and Radar Laboratory School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9781665487726

this paper deals with the development of a proximity-coupled-fed S-band array antenna intended for microwave imaging application. the array antenna which is designed to work at the center frequency of 3 GHz is employed as a sensing device to transmit and receive emitted electromagnetic waves. the proposed array antenna is deployed on two layers of FR4 epoxy dielectric substrate and composed of four square patches arranging in a 2 × 2 configuration. After hardware realization, the fabricated array antenna is experimentally characterized and measured in an anechoic chamber. the characterization result demonstrate that the fabricated array antenna has the reflection coefficient of −17.29 dB at its center frequency, with the fractional bandwidth of 9.3% in the frequency range from 2.92 GHz to 3.2 GHz. these results are comparable to the simulated ones and adequate for the desired application.

关键词： Antenna measurements Microwave measurement Dielectric substrates Transmitting antennas Bandwidth Microwave communication Dielectric measurement

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Session-based News Recommendation from Temporal User Commenting Dynamics 14

Session-based News Recommendation from Temporal User Comment...

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14th IEEE/ACM international conference on Advances in Social networks Analysis and Mining, ASONAM 2022

作者： Shen, Chen Han, Chao He, Lihong Mukherjee, Arjun Obradovic, Zoran Dragut, Eduard Megagon Labs United States Temple University Computer and Information Sciences United States Almaden Lab Ibm Research United States University of Houston Computer Science Department United States

ISBN: (纸本)9781665456616

With the increase in volume of daily online news items, it is more and more difficult for readers to identify news articles relevant to their interests. thus, effective recommendation systems are critical for an effective user news consumption experience. Existing news recommendation methods usually rely on the news click history to model user interest. However, there are other signals about user behaviors, such as user commenting activity, which have not been used before. We propose a recommendation algorithm that predicts articles a user may be interested in, given her historical sequential commenting behavior on news articles. We show that following this sequential user behavior the news recommendation problem falls into in the class of session-based recommendation. the techniques in this class seek to model users' sequential and temporal behaviors. While we seek to follow the general directions in this space, we face unique challenges specific to news in modeling temporal dynamics, e.g., users' interests shift over time, users comment irregularly on articles, and articles are perishable items with limited lifespans. We propose a recency-regularized neural attentive framework for session-based news recommendation. the proposed method is able to capture the temporal dynamics of both users and news articles, while maintaining interpretability. We design a lag-aware attention and a recency regularization to model the time effect of news articles and comments. We conduct extensive empirical studies on 3 real-world news datasets to demonstrate the effectiveness of our method. © 2022 IEEE.

关键词： Recommender systems

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Testing and Exploiting Tools to Improve OWASP Top Ten Security Vulnerabilities Detection

Testing and Exploiting Tools to Improve OWASP Top Ten Securi...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Malak Aljabri Maryam Aldossary Noor Al-Homeed Bushra Alhetelah Malek Althubiany Ohoud Alotaibi Sara Alsaqer Networks and Communications Department SAUDI ARAMCO Cybersecurity Chair College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Networks and Communications Department College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

ISBN: (纸本)9781665487726

In many different sorts of businesses, including public and private, government, critical infrastructures, etc., web apps have grown recently. therefore, securing web applications is a major concern to protect businesses from loss and unauthorized access to sensitive information. Developers use vulnerable thirdparty modules or components or create programming security flaws themselves and occasionally work with tight budgets. these situations frequently cause people to overlook a crucial aspect of development life cycle security. this paper studies and tests the currently available web security and exploitation tools of OWASP's top ten security vulnerabilities. the main aim of this paper is to improve the detection of OWASP's top ten security vulnerabilities by proposing an exploitation and detection tool that combined features of the tools that has been tested in the paper.

关键词： Government Programming Feature extraction Critical infrastructure Security communication networks Computational intelligence

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Whispering at the shot noise limit: communication using single photons through photon-starved channels 14

Whispering at the shot noise limit: communication using sing...

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14th conference on Next Generation Optical communication - Components Sub systems and systems

作者： Dacha, Sai Kanth Essiambre, Rene-Jean Ashikhmin, Alexei Blanco-Redondo, Andrea Kschischang, Frank R. Banaszek, Konrad Zhang, Yuanhang Nokia Bell Labs 600 Mt Ave New Providence NJ 07974 USA Columbia Univ Dept Appl Phys & Appl Math 500 West 120th St New York NY 10027 USA Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Univ Warsaw Ctr Quantum Opt Technol PL-02097 Warsaw Poland

ISBN: (纸本)9781510684966;9781510684973

the ability to transmit information from one point to another using as low received power as possible has a fundamental impact in many contexts, including covert communication, energy-efficient networks, and communication over channels with extreme loss. An immediate application is deep-space exploration, in which there has been significant interest in moving from microwaves to optical signals due to considerably lower diffraction loss and larger bandwidth. At a given data rate and transmit power, systems with the highest photon information efficiency (PIE), defined as the number of information bits extracted per received photon, can bridge the largest loss. We report here an experimental demonstration, using large-order pulse-position modulation and superconducting single-photon detectors, of a record PIE of 14.5 (17.8) bits per incident (detected) photon after 87.5 dB of channel loss. this corresponds to 8.84 zeptojoules, or 0.069 photons, per bit at 1550 nm. the record result was achieved using a new low-complexity transmitter design that produces short optical pulses on-demand with an average extinction ratio exceeding 90 dB per time slot. To our knowledge, this is the most sensitive optical detection system ever demonstrated for high-path-loss optical communication.

关键词： deep-space communication photon information efficiency record sensitivity optical communication pulse-position modulation free-space

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OVERCOMING CHALLENGES FOR QUANTITATIVE RISK MODELING USING MACHINE LEARNED DATA CORRELATIONS AND PREDICTIVE MODELING 14

OVERCOMING CHALLENGES FOR QUANTITATIVE RISK MODELING USING M...

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2022 14th international Pipeline conference, IPC 2022

作者： Biagiotti, Stephen F. Williams, Dan Kondratyuk, Sergiy Johnson, Brett Dynamic Risk Assessment Systems DenverCO United States Dynamic Risk Assessment Systems CalgaryAB Canada Dynamic Risk Assessment Systems TorontoON Canada Pembina Pipeline Corporation CalgaryAB Canada

ISBN: (纸本)9780791886571

After 20 years of learnings and successful risk reduction, the pipeline industry is striving to achieve the next step change in risk performance by migrating from relative index-based risk models toward probabilistic approaches across all threats and all pipeline segments for system-wide risk assessment. While the quantification of pipeline risk can be readily supported by in-line inspection (ILI) results coupled with probabilistic limit state modeling for certain threats and pipeline segments where this information is available, where such data is lacking for other pipeline segments or threats, it is necessary to apply a meaningful methodology to establish the probability of failure for all dynamic segments used to quantify risk. the process for establishing probability-based threat assessments for these other segments involves several stages: (1) identify correlations based on ILI historical results (i.e., create the "training" dataset);(2) leverage classification trees to identify statistically relevant data observations of key variables;(3) apply machine learning techniques to develop probabilistic and/or causal models that predict target outcomes from the combinations of key variables;and, (4) apply the relationships established in stages 1, 2 and 3 to all assets lacking ILI results. Although seemingly straightforward, several challenges exist for achieving seamless implementation. this paper will review each process step and provide guidance on preparing and tackling common data intelligence challenges. the paper will also propose strategies for classifying assets, other than indexing, for application in those situations where machine learning does not indicate statistically significant variable correlations or yield strong predictions of target outcomes. Although still early in the understanding of migrating from relative index-based to probabilistic risk algorithms, the value provided in this paper is the sharing of lessons learned regarding "how" to gather

关键词： Bayesian networks

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Scada Web-Based Instrumentation and Control Laboratory with Real-Time Remote Monitoring and Control System for Columban College

Scada Web-Based Instrumentation and Control Laboratory with ...

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international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment and Management (HNICEM)

作者： Deiescart D’Mitrio C. Maceda Glenn V. Magwili College of Engineering Columban College Inc City of Olongapo Zambales Philippines School of Graduate Studies Mapua University City of Olongapo Zambales Philippines College of Engineering Pamantasan ng Lungsod ng Maynila City of Olongapo Zambales Philippines School of Electrical Electronics and Computer Engineering Mapua University City of Olongapo Zambales Philippines

this paper provides a remote access control experiment for students who can't go to the campus because of the COVID-19 pandemic. this paper utilizes the SCADA (supervisory control and data acquisition) using LabView with the Internet of things technology to control the laboratory remotely in real-time. Remote access experiments of a Linear actuator, PID algorithm, Dynamics and Control of Second-order system response, and survey questionnaires were applied and used as an example to show how effective the research study is. the safety of the SCADA system was also considered by using the Virtual Private Network as the primary connection between the student and the server. the remote access laboratory will give a solution to the current problem of the academe for not providing a real-time laboratory equipment experiment.

关键词： Pandemics Instruments Heuristic algorithms SCADA systems Real-time systems Virtual private networks Safety

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