Text Augmentation-Based Model for Emotion Recognition Using Transformers

Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally intelligentmachines.Graph-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC tasks.However,their limited ability to collect and acquire contextual information hinders their effectiveness.We propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address this.The proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human emotions.Themodel used text augmentation techniques to producemore training data,improving the proposed model’s accuracy.Transformer encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual information.This integration improves the accuracy and robustness of the proposed model.Furthermore,we present a method for balancing the training dataset by creating enhanced samples from the original dataset.By balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed model.Experimental results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ERC.TA-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based encoding.The balanced dataset and the additional training samples also enhance its resilience.These findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.

Reconfigurable Compact Wideband Circularly Polarised Dielectric Resonator Antenna for Wireless Applications

In this work,a novel compact wideband reconfigurable circularly polarised(CP)dielectric resonator antenna(DRA)is presented.The L-shaped Dielectric resonator antenna is excited by an inverted question mark shaped feed.This arrangement of feed-line helps to generate two orthogonal modes inside the DR,which makes the design circularly polarised.A thin micro-strip line placed on the defected ground plane not only helps to generate a wideband response but also assist in the positioning of the two diode switches.These switches located at the left and right of the micro-strip line helps in performing two switching operations.The novel compact design offers the reconfigurability between 2.9–3.8 GHz which can be used for different important wireless applications.For the switching operation I,the achieved impedance bandwidth is 24%while axial ratio bandwidth(ARBW)is 42%.For this switching state,the design has 100%CP performance.Similarly,the switching operation II achieves 60%impedance bandwidth and 58.88%ARBW with 76.36%CP performance.The proposed design has a maximum measured gain of 3.4 dBi and 93%radiation efficiency.The proposed design is novel in terms of compactness and performance parameters.The prototype is fabricated for the performance analysis which shows that the simulated and measured results are in close agreement.

Cyber Secure Framework for Smart Containers Based on Novel Hybrid DTLS Protocol

The Internet of Things (IoTs) is apace growing, billions of IoT devicesare connected to the Internet which communicate and exchange data among eachother. Applications of IoT can be found in many fields of engineering and sciencessuch as healthcare, traffic, agriculture, oil and gas industries, and logistics. Inlogistics, the products which are to be transported may be sensitive and perishable, and require controlled environment. Most of the commercially availablelogistic containers are not integrated with IoT devices to provide controlled environment parameters inside the container and to transmit data to a remote server.This necessitates the need for designing and fabricating IoT based smart containers. Due to constrained nature of IoT devices, these are prone to different cybersecurity attacks such as Denial of Service (DoS), Man in Middle (MITM) andReplay. Therefore, designing efficient cyber security framework are required forsmart container. The Datagram Transport Layer Security (DTLS) Protocol hasemerged as the de facto standard for securing communication in IoT devices.However, it is unable to minimize cyber security attacks such as Denial of Serviceand Distributed Denial of Service (DDoS) during the handshake process. Themain contribution of this paper is to design a cyber secure framework by implementing novel hybrid DTLS protocol in smart container which can efficientlyminimize the effects of cyber attacks during handshake process. The performanceof our proposed framework is evaluated in terms of energy efficiency, handshaketime, throughput and packet delivery ratio. Moreover, the proposed framework istested in IoT based smart containers. The proposed framework decreases handshake time more than 9% and saves 11% of energy efficiency for transmissionin compare of the standard DTLS, while increases packet delivery ratio andthroughput by 83% and 87% respectively.