Sentiment analysis (SA) is a technique used in natural language processing (NLP), which determines the sentiment or emotion expressed piece of text. SA frequently implemented on text datasets to assist understanding customer needs, product feedback, and businesses monitoring brands. Accordingly, deep learning (DL) model evolved as promising that has been widely employed attained considerable outcomes. Because DL models automatically extract features from dataset, it can be claimed...

The Translation System (TS) serves as a communication bridge for individuals with disabilities to interact others in society. As computers play vital role our daily lives, advancements human-computer interaction (HCI) have particularly benefited the deaf and mute community. Our proposed system aims develop an intelligent translator that facilitates seamless between speech impairments general population. This seeks establish effective efficient means of those speaking deficiencies regular...

Towards tackling the phenomenon of textual information overload that is exponentially pumping with redundancy over Internet, this paper investigates a solution depending on Automatic Text Summarization (ATS) method. The idea ATS to assist, e.g., online readers, in getting simplified version texts for preserving their time/effort required skim given large body text. However, deemed as one most complex NLP applications, particularly Arabic language has not been intelligently developed like...

The COVID-19 pandemic has been a disastrous event that elevated several psychological issues such as depression given abrupt social changes and lack of employment. At the same time, scientists psychologists have gained significant interest in understanding way people express emotions sentiments at time pandemics. During rise cases with stricter lockdowns, expressed their on media. This offers deep human psychology during catastrophic events. By exploiting user-generated content media...

Artificial Intelligence (AI) is expanding with colossal applications in various sectors. In the healthcare sector, it booming to make life simpler utmost accuracy by predicting, diagnosing and up care help of Machine Learning (ML) Deep (DL) applications. Modern computer algorithms have attained levels comparable those human specialists medical sciences, although computers often do jobs more quickly than people do. It also expected that there will not be a mandate for humans present machines...

<abstract> <p>Cardiovascular disease (CVD) detection using deep learning (DL) includes leveraging advanced neural network (NN) models to analyze medical data, namely imaging, electrocardiograms (ECGs), and patient records. This study introduces a new Nature Inspired Metaheuristic Algorithm with Deep Learning for Healthcare Data Analysis (NIMADL-HDA) technique. The NIMADL-HDA technique examines healthcare data the recognition classification of CVD. In presented technique, Z-score...

In the notion of communication system resource provision specifically, beam-forming is a concept proficient utilization power transmission. Network densification and massive MIMO allows us to control efficiency can be effectively distributed among different users by reducing cost. We presented practical scenario for performance multi-small cell analyze overall system. Our work based on allocation with optimal structural constraints maintain cost effectiveness while considering economic...

With the progression of information technologies, unmanned aerial vehicles (UAV) or drones are more significant in remote monitoring environment. One main application UAV technology relevant to nature is wild animals. Among several natural disasters, Wildfires one deadliest and cause damage millions hectares forest lands resources which threatens lives animals people. Drones present novel features convenience include rapid deployment, adjustable wider viewpoints, less human intervention,...

SARS-CoV-2 is a recently discovered virus that poses an urgent threat to global health. The disease caused by this termed COVID-19. Death tolls in different countries remain rise, leading continuous social distancing and lockdowns. Patients of ages are susceptible severe disease, particular those who have been admitted ICU. Machine learning (ML) predictive models based on medical data patterns emerging topic areas such as the prediction liver diseases. Prediction combine several variables or...

Background:: Segmenting tumors in MRI scans is a difficult and time-consuming task for radiologists. This because come different shapes, sizes, textures, making them hard to identify visually. Objective:: study proposes new method called the enhanced regularized ensemble encoder-decoder network (EREEDN) more accurate brain tumor segmentation. Methods:: The EREEDN model first preprocesses data by normalizing intensity levels. It then uses series of autoencoder networks segment tumor. These...

In outcome-based academic programs, Program Education Objects (PEOs) are the key pillars on which program components built. They articulated linguistically as broad statements of graduates’ professional and career accomplishments within a few years graduation. Moreover, PEOs mapped into set skills attributes known Learning Outcomes (PLOs). It goes without saying that profound understanding is factor in success an program. For this sake, paper proposes data analytics-based approach to examine...

Little attention has been given to the development of lower respiratory tract infections (LRTIs) in patients with pulmonary tuberculosis (PTB) during their anti-tuberculosis (anti-TB) treatment and how that might affect patients' health status. Here, prevalence etiologies other LRTIs a cohort PTB were determined, clinical features outcomes described.Adult between 2015 2020 recruited monitored anti-TB for presence LRTIs. Clinical data retrospectively collected from medical records.Data 76 (57...

With the features provided by wireless mesh networks (WMN) and increasing number of users, Quality Service (QoS) has become essential to support multimedia applications. In addition, employing multichannel approach led improvement network performance. However, selecting a path with maximum available bandwidth transmit data from source destination is critical issue because intraflow interference inter-flow interference. this paper, we propose routing metric Delay Interference Aware Metric...

World Wide Web enables its users to connect among themselves through social networks, forums, review sites, and blogs these interactions produce huge volumes of data in various forms such as emotions, sentiments, views, etc. Sentiment Analysis (SA) is a text organization approach that applied categorize the sentiments under distinct classes positive, negative, neutral. However, challenging perform due inadequate volume labeled domain Natural Language Processing (NLP). Social networks...

Sentiment Analysis (SA) is one of the Machine Learning (ML) techniques that has been investigated by several researchers in recent years, especially due to evolution novel data collection methods focused on social media. In literature, it reported SA created for English language excess any other language. It challenging perform Arabic Twitter owing informal nature and rich morphology An earlier study conducted upon mostly automatic extraction features from text. Neural word embedding...

Wireless Mesh Networks (WMNs) are gaining popularity due to the features provided, especially low cost and self-configuration ability. In WMNs, data traffic is transmitted through intermediate nodes a number of packets dropped during transmission various reasons. One significant reason limitation network resources such as bandwidth buffer size. Because these limitations, becomes congested under high volumes. Therefore, large will be overflow in Interface Queue (IFQ). Hence, controlling...

In recent times, computer vision related face image analysis has gained significant attention in various applications namely biometrics, surveillance, security, data retrieval, informatics, etc. The main objective of the facial is to extract soft biometrics like expression, identity, age, ethnicity, gender, Of these, ethnicity recognition considered a hot search topic, major part community with deep connections many social and ecological concerns. learning machine methods merit for effective...