Page 40 - Vm Java Mission News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Stay updated with breaking news from Vm java mission. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

Top News In Vm Java Mission Today - Breaking & Trending Today

UVM to build $100M undergraduate housing complex

Catamount Woods will house approximately 540 undergraduates near the southern edge of Centennial Woods, in what is currently a Hilton Doubletree parking lot. ....

United States , Board Of Trustees , University Of Vermont , Catamount Woods , Centennial Woods , Hilton Doubletree , Catamount Woods , Centennial Woods , Hilton Doubletree , Student Housing ,

"A Machine Learning Approach to Classify Biomedical Acoustic Features f" by Gaurav Aggarwal, Kavita Jhajharia et al.

Communication is imperative for living beings for exchanging information. But for newborns, the only way of communicating with the world is through crying, and it is the only medium through which caregivers can know about the needs of their children. Timely addressing baby cries is very important so that the child is relieved at the earliest. It has been a challenge, especially for new parents. The literature says newborn babies use The Dustan Baby Language to communicate. According to this language, there are five words to understand a baby's needs, which are “Neh” (hungry), “Eh” (burp is needed), “Owh/Oah” (fatigue), “Eair/Eargghh” (cramps), “Heh” (feel hot or wet, physical discomfort). This research aims to develop a model for recognizing baby cries and distinguishing between different kinds of baby cries. Here we more broadly focus on whether the infant is in pain due to hunger or discomfort. The study proposes a comparative approach using four classificati ....

Eair Eargghh , Dustan Baby Language , Acoustic Features , Pectral Features ,

"Hate Speech Detection: Performance Based upon a Novel Feature Detectio" by Saugata Bose

Hate speech is abusive or stereotyping speech against a group of people, based on characteristics such as race, religion, sexual orientation, and gender. Internet and social media have made it possible to spread hatred easily, fast, and anonymously. The large scale of data produced through social media platforms requires the development of effective automatic methods to detect such content. Hate speech detection in short text on social media has become an active research topic in recent years, as it differs from the traditional information retrieval for documents. My research is to develop a method to effectively detect hate speech based on deep learning techniques. I have proposed a novel feature based on the lexicon of short text. Experiments have shown that proposed deep-neural-network-based models improve the performance when a novel feature combines with CNN and SVM. ....

Eature Detection , Hate Speech ,