Enhancing performance of Parallel Hybrid Electric Vehicles using Powell's Artificial Bee Colony method.

Hybrid Electric Vehicles (HEVs) demonstrate superior fuel efficiency and reduced emissions in comparison to conventional vehicles. To further enhance the HEV performance, Powell's based Artificial Bee Colony (ABC) heuristic approach is used. Powell's ABC focuses on the improved local search ability and increased speed of convergence.

Retraction Note: Early diagnosis of COVID-19-affected patients based on X-ray and computed tomography images using deep learning algorithm.

[This retracts the article DOI: 10.1007/s00500-020-05275-y.].

Analysis and prediction of land surface temperature with increasing urbanisation using satellite imagery.

The unplanned growth of urbanization in towns and cities has led to variations in Land Surface Temperature (LST) as the green lands are converted into impervious structures without land cover management. In this study, an effort is made to study the transformational change in natural land cover area over the years and its impact on LST in Ernakulum District of Kerala, India. As per the current statistics from one of the reports on "Observed Rainfall Variability and Changes Over Kerala State", by Indian Metrological Department in January 2020 shows that there is a significant decreasing trend in rainy days in many districts of Kerala which has resulted in highest temperature records in recent years.

Hybridization of Deep Learning Pre-Trained Models with Machine Learning Classifiers and Fuzzy Min-Max Neural Network for Cervical Cancer Diagnosis.

Medical image analysis and classification is an important application of computer vision wherein disease prediction based on an input image is provided to assist healthcare professionals. There are many deep learning architectures that accept the different medical image modalities and provide the decisions about the diagnosis of various cancers, including breast cancer, cervical cancer, etc. The Pap-smear test is the commonly used diagnostic procedure for early identification of cervical cancer, but it has a high rate of false-positive results due to human error.

Sign2Pose: A Pose-Based Approach for Gloss Prediction Using a Transformer Model.

Word-level sign language recognition (WSLR) is the backbone for continuous sign language recognition (CSLR) that infers glosses from sign videos. Finding the relevant gloss from the sign sequence and detecting explicit boundaries of the glosses from sign videos is a persistent challenge. In this paper, we propose a systematic approach for gloss prediction in WLSR using the Sign2Pose Gloss prediction transformer model.

Semantic relational machine learning model for sentiment analysis using cascade feature selection and heterogeneous classifier ensemble.

The exponential rise in social media microblogging sites like Twitter has sparked curiosity in sentiment analysis that exploits user feedback towards a targeted product or service. Considering its significance in business intelligence and decision-making, numerous efforts have been made in this area. However, lack of dictionaries, unannotated data, large-scale unstructured data, and low accuracies have plagued these approaches.

Deep learning based detection and analysis of COVID-19 on chest X-ray images.

Covid-19 is a rapidly spreading viral disease that infects not only humans, but animals are also infected because of this disease. The daily life of human beings, their health, and the economy of a country are affected due to this deadly viral disease. Covid-19 is a common spreading disease, and till now, not a single country can prepare a vaccine for COVID-19.

Early diagnosis of COVID-19-affected patients based on X-ray and computed tomography images using deep learning algorithm.

The novel coronavirus infection (COVID-19) that was first identified in China in December 2019 has spread across the globe rapidly infecting over ten million people. The World Health Organization (WHO) declared it as a pandemic on March 11, 2020. What makes it even more critical is the lack of vaccines available to control the disease, although many pharmaceutical companies and research institutions all over the world are working toward developing effective solutions to battle this life-threatening disease.

IoT Based Heart Activity Monitoring Using Inductive Sensors.

This paper presents a system dedicated to monitoring the heart activity parameters using Electrocardiography (ECG) mobile devices and a Wearable Heart Monitoring Inductive Sensor (WHMIS) that represents a new method and device, developed by us as an experimental model, used to assess the mechanical activity of the hearth using inductive sensors that are inserted in the fabric of the clothes. Only one inductive sensor is incorporated in the clothes in front of the apex area and it is able to assess the cardiorespiratory activity while in the prior of the art are presented methods that predict sensors arrays which are distributed in more places of the body. The parameters that are assessed are heart data-rate and respiration.

Diabetic Retinopathy Diagnosis from Retinal Images Using Modified Hopfield Neural Network.

Disease diagnosis from medical images has become increasingly important in medical science. Abnormality identification in retinal images has become a challenging task in medical science. Effective machine learning and soft computing methods should be used to facilitate Diabetic Retinopathy Diagnosis from Retinal Images.

Automatic histologically-closer classification of skin lesions.

According to the American Cancer Society, melanoma is one of the most common types of cancer in the world. In 2017, approximately 87,110 new cases of skin cancer were diagnosed in the United States alone. A dermatoscope is a tool that captures lesion images with high resolution and is one of the main clinical tools to diagnose, evaluate and monitor this disease.

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists.

A case discussion on eczema.

Eczema is a form of dermatitis where inflammation of epidermis occurs. The exact cause of eczema is not known. Although it is activated by the immune system and is related to allergic reactions, it is not the same as other allergic reactions.