Patients with breast cancer are prone to serious health-related complications higher mortality. The primary reason might be a misinterpretation of radiologists in recognizing suspicious lesions due technical issues imaging qualities and heterogeneous densities which increases the false-(positive negative) ratio. Early intervention is significant establishing an up-to-date prognosis process can successfully mitigate disease recovery. manual screening abnormalities through traditional machine...

Dynamic web applications play a vital role in providing resources manipulation and interaction between clients servers. The features presently supported by browsers have raised business opportunities, supplying high interactivity web-based services, like banking, e-commerce, social networking, forums, at the same time, these brought serious risks increased vulnerabilities that enable cyber-attacks to be executed. One of common high-risk cyber-attack application is cross-site scripting (XSS)....

Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally. detection needs accurate mammography interpretation and analysis, which challenging for radiologists owing to intricate anatomy breast low image quality. Advances in deep learning-based models have significantly improved lesions' detection, localization, risk assessment, categorization. This study proposes novel convolutional neural network (ConvNet) that reduces human error diagnosing malignancy...

Diagnosing breast cancer masses and calcification clusters have paramount significance in mammography, which aids mitigating the disease's complexities curing it at early stages. However, a wrong mammogram interpretation may lead to an unnecessary biopsy of false-positive findings, reduces patient's survival chances. Consequently, approaches that learn discern can reduce number misconceptions incorrect diagnoses. Conventionally used classification models focus on feature extraction...

Microcalcifications in breast tissue can be an early sign of cancer, and play a crucial role cancer screening. This study proposes radiomics approach based on advanced machine learning algorithms for diagnosing pathological microcalcifications mammogram images provides radiologists with valuable decision support system (in regard to patients). An adaptive enhancement method the contourlet transform is proposed enhance effectively suppress background noise. Textural statistical features are...

Artificial Intelligence (AI) has emerged as a transformative force in various sectors, and libraries are no exception. The integration of AI revolutionized how information is stored, retrieved, delivered, enhancing operational efficiency improving user experience. Libraries, traditionally dependent on manual labor physical resources, now utilizing technologies such machine learning, natural language processing, automation to streamline processes. This paper explores the role libraries,...

A cataract is the prevailing cause of visual impairment in modern world. The detection at early stages can lessen risk blindness. This study presents an automated system for and grading based on retinal images. comprised image acquisition, preprocessing, feature extraction, classifier building, grading. preprocessing steps such as green channel histogram equalization, top-bottom hat transformation are used to improve quality wavelet texture features extracted from fundus building a...

This study discusses how to increase power quality by integrating a unified conditioner (UPQC) with grid-connected microgrid for clean and efficient generation. An Artificial Neural Network (ANN) controller voltage source converter-based UPQC is proposed minimize the system’s cost complexity eliminating mathematical operations such as a-b-c d-q-0 translation need costly controllers DSPs FPGAs. In this study, nonlinear unbalanced loads harmonic supply are used assess performance of...

Purpose The implementation of green collaboration has evolved from the interfirm level to supply chain level, which requires more participation in information and manufacturing technologies. Despite many efforts (GSCC), research on how enhance it a technological perspective remains unclear. Thus, this study aims address gap by exploring supplier, internal customer through using technology (IT) advanced (AMT), further accelerates environmental economic performance. Design/methodology/approach...

Cataract is the most prevalent cause of blindness worldwide, which accounts for more than 51% overall blindness. The early detection cataract can salvage impaired vision leading to Most existing classification systems are based on traditional machine learning methods with hand-engineered features. manual extraction retinal features generally a time-taking process and requires professional ophthalmologists. Convolutional neural network (CNN) widely accepted model automatic feature extraction,...

Multipath (MP) and/or Non Line-Of-Sight (NLOS) reception remains a potential vulnerability to satellite-based positioning and navigation systems in high multipath environments, such as an urban canyon. In environment, satellite signals are reflected, scattered or faded, sometimes completely blocked by roofs walls of high-rise buildings, fly-over bridges, complex road structures, etc. making information inaccurate, unreliable, largely unavailable. The magnitude the error depends on...

Several developments in computational image processing methods assist the radiologist detecting abnormal breast tissue recent years. Consequently, deep learning-based models have become crucial for early screening and interpretation of mammographic images masses diagnosis, helping successful treatment. Breast calcification is an essential parameter prognosis cancer. However, image's mass detection needs a deeper investigation due to masses' heterogeneity anomalies' characteristics that are...

An accurate and efficient Large-for-Gestational-Age (LGA) classification system is developed to classify a fetus as LGA or non-LGA, which has the potential assist paediatricians experts in establishing state-of-the-art prognosis process. The performance of proposed scheme validated by using dataset collected from National Pre-Pregnancy Examination Program China (2010–2013). A master feature vector created establish primarily data pre-processing, includes features’ discretization process...

In recent times social media has become the most important part of everyone to connect with global world share information. Generally, Social is used for multi-purposes such as reading newspaper, magazines and books. The actual involvement, i.e. likes post providing specific interests community. information which we extract from networking websites requires criteria better understanding essential factors their importance. main focus this research on visualization network an involvement All...

The astonishing growth of sophisticated ever-evolving cyber threats and attacks throws the entire Internet-of-Things (IoT) infrastructure into chaos. As IoT belongs to interconnected devices, it brings along significant security challenges. Cyber threat analysis is an augmentation a network that primarily emphasizes on detection prevention network-based attacks. Moreover, requires by investigation classification malicious activities. In this study, we propose DL-enabled malware scheme using...