The term sentiment analysis deals with sentiment classification based on the review made by the user in a social *** sentiment classification accuracy is evaluated using various selection methods,especially those that d...
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The term sentiment analysis deals with sentiment classification based on the review made by the user in a social *** sentiment classification accuracy is evaluated using various selection methods,especially those that deal with algorithm *** this work,every sentiment received through user expressions is ranked in order to categorise sentiments as informative and *** order to do so,the work focus on Query Expansion Ranking(QER)algorithm that takes user text as input and process for sentiment analysis andfinally produces the results as informative or *** challenge is to convert non-informative into informative using the concepts of classifiers like Bayes multinomial,entropy modelling along with the traditional sentimental analysis algorithm like Support Vector Machine(SVM)and decision *** work also addresses simulated annealing along with QER to classify data based on sentiment *** the input volume is very fast,the work also addresses the concept of big data for information retrieval and *** result com-parison shows that the QER algorithm proved to be versatile when compared with the result of *** work uses Twitter user comments for evaluating senti-ment analysis.
This paper proposes a thermal reduction method of DC-link capacitors and SiC MOSFETs in two-level inverters based on discontinuous PWM. The converter reliability has been extensively studied at both the device and the...
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In this work, a method to improve multiple-input-multiple-output (MIMO) antenna system channel capacity based on S-parameter phase difference is proposed. Theoretical derivation and numerical analysis show that the 90...
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This paper presents a methodology for implementing low-power, high-speed artificial neural network based on analog hardware architecture. The key components include current-mode circuits, such as the Gaussian function...
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This paper explores the application of reinforcement learning (RL) to torpedo guidance with a focus on obstacle avoidance and target acquisition in dynamic environments. By employing a dual-actor network approach and ...
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This study investigates the application of Deep Reinforcement Learning (DRL) algorithms, namely Double Deep Q-Network (DDQN) and Deep Deterministic Policy Gradient (DDPG), in the context of path planning within dynami...
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Early fault detection in automotive systems is critical for ensuring user safety and initiating corrective actions. This work proposes an Artificial Intelligence (AI) framework for automotive fault detection. The syst...
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This is because printed circuit boards, also known as PCBs, are essential components of optical sensors and devices, which means that they require an outstanding level of precision and performance. However, deep learn...
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This paper proposes a new score function (SF) of interval-valued intuitionistic fuzzy values (IVIFVs) in order to overcome the shortcomings of the existing SFs of IVIFVs, which are not be able to distinguish the ranki...
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A Power Management Unit aimed for applications requiring low consumption and area efficiency is introduced in this work. Its main goal is to deliver the desired voltage and current outputs to be used from the other ci...
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