How different cultures react and respond given a crisis is predominant in society's norms political will to combat the situation. Often, decisions made are necessitated by events, social pressure, or need of hour, which may not represent nation's will. While some pleased with it, others might show resentment. Coronavirus (COVID-19) brought mix similar emotions from nations towards taken their respective governments. Social media was bombarded posts containing both positive negative...

MOOC represents an ultimate way to deliver educational content in higher education settings by providing high-quality material the students throughout world. Considering differences between traditional learning paradigm and MOOCs, a new research agenda focusing on predicting explaining dropout of low completion rates MOOCs has emerged. However, due different problem specifications evaluation metrics, performing comparative analysis state-of-the-art machine architectures is challenging task....

In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly education domain, where dealing with processing students’ opinions is a complicated task due to nature of language used by students large volume information, application growing yet remains challenging. Several literature reviews reveal state this domain from different perspectives contexts. However, body lacking review that systematically classifies...

Students' feedback is an effective mechanism that provides valuable insights about teaching-learning process. Handling opinions of students expressed in reviews a quite labour-intensive and tedious task as it typically performed manually by the human intervention. While this may be viable for small-scale courses involve just few students' feedback, unpractical large-scale cases applies to online general, MOOCs, particular. Therefore, address issue, we propose paper framework automatically...

Smart home applications are ubiquitous and have gained popularity due to the overwhelming use of Internet Things (IoT)-based technology. The revolution in technologies has made homes more convenient, efficient, even secure. need for advancement smart technology is necessary scarcity intelligent that cater several aspects simultaneously, i.e., automation, security, safety, reducing energy consumption using less bandwidth, computation, cost. Our research work provides a solution these problems...

Due to the rapid development of artificial intelligence technology, industrial sectors are revolutionizing in automation, reliability, and robustness, thereby significantly increasing quality productivity. Most surveillance monitored by visual sensor networks capturing different surrounding environment images. However, during tempestuous weather conditions, images is reduced due contaminated suspended atmospheric particles that affect overall systems. To tackle these challenges, this article...

Supply Chain Management (SCM) consists of handling and optimizing all the facets supply chain process goods services. Modern SCM is reaping benefits from emerging growing Internet Things (IoT) field. IoT technology can automate digitalize processes to get maximum operational efficiencies by reducing operating costs. The mass proliferation devices has revolutionized chains. in track trace shipments using latest real-time monitoring technologies, including GPS. are also used for asset...

With the emerging technologies of augmented reality (AR) and virtual (VR), learning process in today’s classroom is much more effective motivational. Overlaying content into real world makes methods attractive entertaining for students while performing activities. AR techniques make easy, fun as compared to traditional methods. These lack focused interactivity between educational content. To effective, we propose use handheld marker-based technology primary school students. We developed a...

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous risky practice in real life, one of these is road safety training for children. Traditional video- presentation-based average output results it lacks physical the involvement children during training, without any practical testing examination check learned abilities child before their exposure real-world environments. Therefore, this paper, we propose 3D...

Diagnosing and treating abnormalities in the wrist, specifically distal radius, ulna fractures, is a crucial concern among children, adolescents, young adults, with higher incidence rate during puberty. However, scarcity of radiologists lack specialized training medical professionals pose significant risk to patient care. This problem further exacerbated by rising number imaging studies limited access specialist reporting certain regions. highlights need for innovative solutions improve...

Skin cancer is a widespread disease associated with eight diagnostic classes. The diagnosis of multiple types skin challenging task for dermatologists due to the similarity classes in phenotype. average accuracy multiclass 62% 80%. Therefore, classification using machine learning can be beneficial and treatment patients. Several researchers developed models binary class but could not extend research better performance ratios. We have deep learning-based ensemble classification. Experimental...

Data imbalance is a frequently occurring problem in classification tasks where the number of samples one category exceeds amount others. Quite often, minority class data great importance representing concepts interest and often challenging to obtain real-life scenarios applications. Imagine customers’ dataset for bank loans-majority instances belong non-defaulter class, only small customers would be labeled as defaulters, however, performance accuracy more important on defaulters labels than...

Online learning environments (OLE) including management systems (LMS) and massive open online courses (MOOCs) are gaining popularity as the best modern alternate solutions available for education in current era. The luxury to learn irrespective of geographical temporal restrictions makes it an attractive resource. At start 2020, global pandemic enforced social distance practice worldwide, changing work environment dynamics, leaving options like trading, from home, education. gained...

In recent years, significant progress has been made in text generation. The latest generation models are revolutionizing the domain by generating human-like text. It gained wide popularity recently many domains like news, social networks, movie script writing, poetry composition, to name a few. application of various fields resulted lot interest from scientific community this area. To best our knowledge, there is lack extensive review and up-to-date body knowledge deep learning models....

Social media platforms have been widely used as a communication tool where most of the population expresses their feelings and shares life experiences. Along with general information about public, these hold an ample amount content related to depressed users thus can generate sensitive social signals indicating if person is suffering from some serious issues, such self-harm, suicidal thoughts, or intention for unlawful act. Early depression detection using advanced natural language...

Deep neural networks have emerged as a leading approach towards handling many natural language processing (NLP) tasks. initially conquered the problems of computer vision. However, dealing with sequential data such text and sound was nightmare for traditional deep are not reliable in preserving contextual information. This may harm results case image where we do care about sequence, but when consider collected from processing, trigger disastrous results. Moreover, establishing sentence...

Data imbalance in datasets is a common issue where the number of instances one or more categories far exceeds others, so case with educational domain. Collecting feedback on course large scale and lack publicly available this domain limits models' performance, especially for deep neural network based models which are data hungry. A model trained such an imbalanced dataset would naturally favor majority class. However, minority class could be critical decision-making prediction systems,...

The rise in technological advancements and Social Networking Sites (SNS) made people more engaged their virtual lives. Research has revealed that feel comfortable posting feelings, including suicidal thoughts, on SNS than discussing them through face-to-face settings due to the social stigma associated with mental health. This research study aims develop a multi-class machine learning classifier for identifying risk levels media posts. proposed Enhanced Feature Engineering Approach Suicidal...

Abstract Nowadays, various applications across industries, healthcare, and security have begun adopting automatic sentiment analysis emotion detection in short texts, such as posts from social media. Twitter stands out one of the most popular online media platforms due to its easy, unique, advanced accessibility using API. On other hand, supervised learning is widely used paradigm for tasks involving polarity fine-grained informal posts. However, models are data-hungry heavily reliant on...

Bloom's taxonomy is a popular model to classify educational learning objectives into different levels for three domains including cognitive, affective and psycho motor. Each domain further detailed levels. The cognitive includes knowledge, comprehension, application, analysis, synthesis evaluation In institutions, designing course outcomes (CLOs) as per of Bloom mapping assessment items on designed CLOs an important task—every semester, faculty administrators read thousands statements...