R. Sujatha, K. Nimala^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1669-1686, 2024, DOI:10.32604/cmc.2023.046963

Abstract Sentence classification is the process of categorizing a sentence based on the context of the sentence. Sentence categorization requires more semantic highlights than other tasks, such as dependence parsing, which requires more syntactic elements. Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence, recognizing the progress and comparing impacts. An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus. The conversational sentences are classified into four categories: information, question, directive, and commission. These classification label sequences are for analyzing the conversation progress and… More >

Lanyao Zhang¹, Shichao Kan², Yigang Cen³, Xiaoling Chen¹, Linna Zhang^1,*, Yansen Huang^4,5

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1631-1648, 2024, DOI:10.32604/cmc.2024.046924

Abstract Unsupervised methods based on density representation have shown their abilities in anomaly detection, but detection performance still needs to be improved. Specifically, approaches using normalizing flows can accurately evaluate sample distributions, mapping normal features to the normal distribution and anomalous features outside it. Consequently, this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network (NF-BMR). It utilizes pre-trained Convolutional Neural Networks (CNN) and normalizing flows to construct discriminative source and target domain feature spaces. Additionally, to better learn feature information in both domain spaces, we propose the Bidirectional Mapping Residual Network (BMR), which maps sample features to these two spaces… More > Graphic Abstract

Sherly Alphonse^*, Harshit Verma

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2067-2086, 2024, DOI:10.32604/cmc.2024.046070

Abstract Although lots of research has been done in recognizing facial expressions, there is still a need to increase the accuracy of facial expression recognition, particularly under uncontrolled situations. The use of Local Directional Patterns (LDP), which has good characteristics for emotion detection has yielded encouraging results. An innovative end-to-end learnable High Response-based Local Directional Pattern (HR-LDP) network for facial emotion recognition is implemented by employing fixed convolutional filters in the proposed work. By combining learnable convolutional layers with fixed-parameter HR-LDP layers made up of eight Kirsch filters and derivable simulated gate functions, this network considerably minimizes the number of network… More >

Amal Hkiri^1,*, Mouna Karmani¹, Omar Ben Bahri², Ahmed Mohammed Murayr², Fawaz Hassan Alasmari², Mohsen Machhout¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 227-247, 2024, DOI:10.32604/cmc.2023.047087

Abstract The RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) protocol is essential for efficient communication within the Internet of Things (IoT) ecosystem. Despite its significance, RPL’s susceptibility to attacks remains a concern. This paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the decreased rank attack in both static and mobile network environments. We employ the Random Direction Mobility Model (RDM) for mobile scenarios within the Cooja simulator. Our systematic evaluation focuses on critical performance metrics, including Packet Delivery Ratio (PDR), Average End to End Delay (AE2ED), throughput, Expected Transmission Count (ETX), and Average Power Consumption… More >

Zhenxiang He^*, Xunxi Wang, Chunwei Li

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 845-871, 2024, DOI:10.32604/cmc.2023.046607

Abstract In the fast-evolving landscape of digital networks, the incidence of network intrusions has escalated alarmingly. Simultaneously, the crucial role of time series data in intrusion detection remains largely underappreciated, with most systems failing to capture the time-bound nuances of network traffic. This leads to compromised detection accuracy and overlooked temporal patterns. Addressing this gap, we introduce a novel SSAE-TCN-BiLSTM (STL) model that integrates time series analysis, significantly enhancing detection capabilities. Our approach reduces feature dimensionality with a Stacked Sparse Autoencoder (SSAE) and extracts temporally relevant features through a Temporal Convolutional Network (TCN) and Bidirectional Long Short-term Memory Network (Bi-LSTM). By… More >

Zhiwei Lin¹, Hui Wang^1,*, Tianding Chen¹, Yingtao Jiang², Jianmei Jiang³, Yingpin Chen¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1357-1379, 2024, DOI:10.32604/cmes.2023.045990

Abstract In the domain of autonomous industrial manipulators, precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance, such as handling, heat sealing, and stacking. While Multi-Degree-of-Freedom (MDOF) manipulators offer kinematic redundancy, aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites, their path planning entails intricate multi-objective optimization, encompassing path, posture, and joint motion optimization. Achieving satisfactory results in practical scenarios remains challenging. In response, this study introduces a novel Reverse Path Planning (RPP) methodology tailored for industrial manipulators. The approach commences by conceptualizing the manipulator’s end-effector as an… More > Graphic Abstract

Wei Zhong¹, Zhenfang Xin², Lihua Wang^1,*, Haiping Liu²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1427-1453, 2024, DOI:10.32604/cmes.2023.031271

Abstract Flash boiling atomization (FBA) is a promising approach for enhancing spray atomization, which can generate a fine and more evenly distributed spray by increasing the fuel injection temperature or reducing the ambient pressure. However, when the outlet speed of the nozzle exceeds 400 m/s, investigating high-speed flash boiling atomization (HFBA) becomes quite challenging. This difficulty arises from the involvement of many complex physical processes and the requirement for a very fine mesh in numerical simulations. In this study, an HFBA model for gasoline direct injection (GDI) is established. This model incorporates primary and secondary atomization, as well as vaporization and… More >

Manimaran Renganathan, Thundil Karuppa Raj Rajagopal^*

Frontiers in Heat and Mass Transfer, Vol.4, No.1, pp. 1-11, 2013, DOI:10.5098/hmt.v4.1.3008

Abstract In this work, fuel spray parameters are studied by varying the fuel temperature. To overcome the tedious experimental task, a 3-D Computational Fluid Dynamics methodology is adopted by injecting fuel at specified temperatures of 313 K, 353 K and 393 K. The validation is accomplished after the optimal spatial and temporal steps of discretization are found out. At a fuel temperature of 313 K, advancing the injection timing from 6 deg bTDC to 20 deg bTDC increases cylinder peak pressure from 79.8 bar to 90.9 bar. Relation between the emission characteristics and spray SMD and temperature is studied. More >

Tapas Ray Mahapatra^a, Sumanta Sidui^b, Samir Kumar Nandy^c,*

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-15, 2014, DOI:10.5098/hmt.5.15

Abstract The effect of variable transverse magnetic field on steady two-dimensional indirect natural convection flow of an incompressible viscous fluid over a horizontal hot flat plate is theoretically studied. The governing partial differential equations are transformed into ordinary ones by similarity transformation and solved numerically using fourth order Runge-Kutta method with shooting technique. The results are obtained for the skin friction coefficient and the local Nusselt number as well as the dimensionless velocities, temperature for some values of the magnetic parameter (M) subject to either prescribed (constant or variable) surface temperature or prescribed (variable) heat flux. It is seen that the… More >

Biswajit De^*, Rajsekhar Panua

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-6, 2014, DOI:10.5098/hmt.5.7

Abstract This paper presents a pre-mixed combustion model for diesel and Jatropha oil blends combustion studies. Jatropha oil blends are considered as a mixture of diesel and Jatropha oil. CFD package, FLUENT 6.3 is used for modeling the complex combustion phenomenon in compression ignition engine. The experiments are carried out on a single cylinder, four strokes, water cooled direct injection compression ignition engine at compression ratio of 17.5 at full load condition at constant speed of 1500 rpm fuelled with diesel and jatropha oil blends with diesel. The numerical model is solved by considering pressure based, implicit and unsteady solver and… More >