A figurative language expression known as sarcasm implies the complete contrast of what is being stated with meant, latter usually rather or extremely offensive, meant to offend humiliate someone. In routine conversations on social media websites, frequently utilized. Sentiment analysis procedures are prone errors because can change a statement’s meaning. Analytic accuracy apprehension has increased automatic networking tools have grown. According preliminary studies, computerized sentiment...

This study proposes an advanced method for plant disease detection utilizing a modified depthwise convolutional neural network (CNN) integrated with squeeze-and-excitation (SE) blocks and improved residual skip connections. In light of increasing global challenges related to food security sustainable agriculture, this research focuses on developing highly efficient accurate automated system identifying diseases, thereby contributing enhanced crop protection yield optimization. The proposed...

This paper introduces the design and exploration of a compact, high-performance multiple-input multiple-output (MIMO) antenna for 6G applications operating in terahertz (THz) frequency range. Leveraging meta learner-based stacked generalization ensemble strategy, this study integrates classical machine learning techniques with an optimized multi-feature to predict properties greater accuracy. Specifically, neural network is applied as base learner predicting parameters, resulting increased...

Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the world. Every year, thousands die brain tumors. Brain-related diagnoses require caution, and even smallest error in diagnosis have negative repercussions. Medical errors tumor common frequently result higher patient mortality rates. Magnetic resonance imaging (MRI) is widely used for evaluation detection. However, MRI generates large amounts data, making manual segmentation difficult laborious work,...

Background: Examining chest radiograph images (CXR) is an intricate and time-consuming process, sometimes requiring the identification of many anomalies at same time. Lung segmentation key to overcoming this challenge through different deep learning (DL) techniques. Many researchers are working improve performance efficiency lung models. This article presents a DL-based approach accurately identify mask region in CXR assist radiologists recognizing early signs high-risk diseases. Methods:...

As IoT devices proliferate in critical areas like healthcare or nuclear safety, it necessitates the provision of cryptographic solutions with security and computational efficiency. Very well-established encryption mechanisms such as AES, RC4, XOR cannot strike a balance between speed, energy consumption, robustness. Moreover, most DNA-based are not cognizant hardware limitations platforms Arduino R3. This paper proposes an improved technique incorporating stochastic DNA-inspired processing...

In this paper, multilayer cryptosystems for encrypting audio communications are proposed. These combine signals with other active concealing signals, such as speech by continuously fusing the signal a without silent periods. The goal of these is to prevent unauthorized parties from listening encrypted communications. Preprocessing performed on both and before they combined, necessary get ready fusion. Instead encoding decoding methods, rely values samples, which allows saving time while...

Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development computer-aided diagnosis (CAD) systems for classifying brain in magnetic resonance imaging (MRI) has been subject many research papers so far. However, this sector is still its early stage. The ultimate goal to develop a lightweight effective implementation U-Net deep network use performing exact real-time segmentation. Moreover, simplified convolutional neural (DCNN) architecture BT classification...

Time series forecasting across different domains has received massive attention as it eases intelligent decision-making activities. Recurrent neural networks and various deep learning algorithms have been applied to modeling multivariate time data. Due intricate non-linear patterns significant variations in the randomness of characteristics categories real-world data, achieving effectiveness robustness simultaneously poses a considerable challenge for specific deep-learning models. We...

Plant diseases annually cause damage and loss of much the crop, if not its complete destruction, this constitutes a significant challenge for farm owners, governments, consumers alike. Therefore, identifying classifying at an early stage is very important in order to sustain local global food security. In research, we designed new method identify plant by combining transfer learning Gravitational Search Algorithm (GSA). Two state-of-the-art pretrained models have been adopted extracting...

Chemotherapy is a widely used cancer treatment method globally. However, cells can develop resistance towards single-drug-based chemotherapy if it infused for extended periods, resulting in failure many cases. To address this issue, oncologists have progressed using multi-drug (MDC). This considers different drug concentrations treatment, but choosing incorrect adversely affect the patient’s body. Therefore, crucial to recognize trade-off between and their adverse effects. closed-loop...

Securing medical data while transmission on the network is required because it sensitive and life-dependent data. Many methods are used for protection, such as Steganography, Digital Signature, Cryptography, Watermarking. This paper introduces a novel robust algorithm that combines discrete wavelet transform (DWT), cosine (DCT), singular value decomposition (SVD) digital image-watermarking algorithms. The host image decomposed using two-dimensional DWT (2D-DWT) to approximate low-frequency...

Anxiety is a common mental health issue that affects significant portion of the global population and can lead to severe physical psychological consequences. The proposed system aims provide an objective reliable method for early detection anxiety levels by using patients' symptoms as input variables. This paper introduces expert utilizing fuzzy inference (FIS) predict levels. designed address anxiety's complex uncertain nature comprehensive set variables logic techniques. It based on rules...

In this paper, we propose an SVD-based watermarking scheme in complex wavelet domain for color video. Video is well known as the process of embedding copyright information video bit streams. It has been proposed recent years to solve problem illegal manipulation and distribution digital study, effective, robust imperceptible algorithm proposed. This was based on a cascade two powerful mathematical transforms; 2-level dual tree transform (DT-CWT) singular value decomposition (SVD). hybrid...

This paper presents an efficient SVD based image Steganography approach. approach aims at increasing the fidelity of images after data embedding. Rather than embedding in singular values images, Left vectors are used for this purpose. The objective is to reduce errors as well maintain fidelity. Several solutions problem presented paper. Experimental results show superiority proposed existing approaches.

The software industry plays a vital role in driving technological advancements. Software projects are complex and consist of many components, so change is unavoidable these projects. requirements must be predicted early to preserve resources, since it can lead project failures. This work focuses on small-scale systems which changed gradually. provides probabilistic prediction model, predicts the probability changes requirement specifications. first part considers analyzing due certain...

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds achieve ultra-high reliability, availability, ultra-low latency. The requirements of such the main challenges that can be handled using a range recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), software-defined networking. Many aspects design associated MEC-based 5G/6G should solved...

In this paper, A quantization based method for digital image watermarking is presented here. This on inserting a watermark bit into the coarsest scale wavelet coefficients. three level decomposition used in paper. technique blind requiring neither original nor any side information recovery process. It computationally efficient. Experimental results show superiority of proposed techniques to traditional techniques.

Efficient monitoring and achievement of the Sustainable Development Goals (SDGs) has increased need for a variety data statistics. The massive increase in gathering through social networks, traditional business systems, Internet Things (IoT)-based sensor devices raises real questions regarding capacity national statistical systems (NSS) utilizing big sources. Further, this current era, is captured sensor-based public sector organizations. To gauge institutions regard, work provides an...

Digital Signature using Self-Image signing is introduced in this paper. This technique used to verify the integrity and originality of images transmitted over insecure channels. In order protect user's medical from changing or modifying, must be signed. The proposed approach uses Discrete Wavelet Transform subdivide a picture into four bands Cosine DCT embed mark each sub-band another DWT according determined algorithm. To increase security, marked image then encrypted Double Random Phase...