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"A cost-sensitive deep learning based approach for network traffic clas" by Akbar Telikani, Amir H. Gandomi et al.

Network traffic classification (NTC) plays an important role in cyber security and network performance, for example in intrusion detection and facilitating a higher quality of service. However, due to the unbalanced nature of traffic datasets, NTC can be extremely challenging and poor management can degrade classification performance. While existing NTC methods seek to re-balance data distribution through resampling strategies, such approaches are known to suffer from information loss, overfitting, and increased model complexity. To address these challenges, we propose a new cost-sensitive deep learning approach to increase the robustness of deep learning classifiers against the imbalanced class problem in NTC. First, the dataset is divided into different partitions, and a cost matrix is created for each partition by considering the data distribution. Then, the costs are applied to the cost function layer to penalize classification errors. In our approach, costs are diverse in each typ ....

Class Imbalance , Convolutional Neural Networks , Cost Sensitive Learning , Deep Learning , Ncrypted Traffic Classification , Generative Adversarial Networks , Intrusion Detection , Task Analysis ,

Martin Robert, PhD. Joins Pleio, Inc. to Energize Innovation in Patient Engagement

/PRNewswire/ Pleio, Inc announced today that Martin Robert will head up their new Product innovation lab. "We re pretty excited to have Martin join our. ....

United States , Doctorate In Sciences , Technologies Education Cognitive Sciences Task Analysis , Laval Marketing Market Research , Pleio Inc , Communication Studies , Market Research , Educational Technologies , Instructional Design , Artificial Intelligence , Technologies Education , Cognitive Sciences , Task Analysis ,

Elecard Company

Elecard Company
club.cnews.ru - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from club.cnews.ru Daily Mail and Mail on Sunday newspapers.

Default Service , Task Organization , Region Research , More Info , Features Protocol , They Are , Decision Selected , For Example , Decision Server , Task Analysis , Decision Installation , Task Estimated , Bit Rate , Low East , Task Search , Bit Rate Structure , High Quality , Task Headache Station ,

FOXNEWS Americas Newsroom With Bill Hemmer Dana Perino September 29, 2021 14:21:00

To 650. it was a task analysis with the task being to go to zero but you also have to defend the embassy. i m thinking about the chain of command. somebody is making decisions about troop levels. my understanding it was not the d.o.d. but the state department or the white house. i want to know who said we ll go from 2500 to 650 and just protect kabul and the state department. it was a military analysis 600 to 700 could adequately defend the embassy until the contractors came up and approved through the chain and approved at the highest levels. who made the decision? i would say that the decision was made in a national security consul tateive process in the highest levels of our government. general mckenzie, did you receive advice from general ....

Chain Of Command , Troop Levels , Task Analysis , State Department , White House , Department Of Defense , Biden Decision , Consul Tateive Process , Secretary Of Defense Miller , The Cent Com Commander General Mckenzie ,

"Sarcasm Detection using Deep Learning with Contextual Features" by Md Saifullah Razali, Alfian Abdul Halin et al.

Abstract
Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is extracted from a Convolutional Neural Network (CNN) architecture before it is combined with carefully handcrafted feature sets. These handcrafted feature sets are created based on their respective contextual explanations. Each feature sets are specifically designed for the sole task of sarcasm detection. The objective is to find the most optimal features. Some sets are good to go even when it is used in independence. Other sets are not really significant without any combination. The results of the experiments are positive in terms of Accuracy, Precision, Recall and F1-measure. The combination of features are classified using a few machine learning techniques for comparison purposes. Logistic Regression is found to be the best classification algorithm for this task. Furthermore, result comparison to recent works and the ....

Convolutional Neural Network , Deep Learning , Deep Learning , Feature Extraction , Natural Language Processing , Sarcasm Detection , Ocial Networking Online , Task Analysis , ஆழமான கற்றல் , கேளுங்கள் பகுப்பாய்வு ,