Reducing the Heart Failure Burden in Romania by Predicting Congestive Heart Failure Using Artificial Intelligence: Proof of Concept

Due to population aging, we are currently confronted with an increased number of chronic heart failure patients. The primary purpose of this study was to implement a noncontact system that can predict heart failure exacerbation through vocal analysis. We designed the system to evaluate the voice characteristics of every patient, and we used the identified variations as an input for a machine-learning-based approach. We collected data from a total of 16 patients, 9 men and 7 women, aged 65–91 years old, who agreed to take part in the study, with a detailed signed informed consent. We included hospitalized patients admitted with cardiogenic acute pulmonary edema in the study, regardless of the precipitation cause or other known cardiovascular comorbidities. There were no specific exclusion criteria, except age (which had to be over 18 years old) and patients with speech inabilities. We then recorded each patient’s voice twice a day, using the same smartphone, Lenovo P780, from day one of hospitalization—when their general status was critical—until the day of discharge, when they were clinically stable. We used the New York Heart Association Functional Classification (NYHA) classification system for heart failure to include the patients in stages based on their clinical evolution. Each voice recording has been accordingly equated and subsequently introduced into the machine-learning algorithm. We used multiple machine-learning techniques for classification in order to detect which one turns out to be more appropriate for the given dataset and the one that can be the starting point for future developments. We used algorithms such as Artificial Neural Networks (ANN), Support Vector Machine (SVM) and K-Nearest Neighbors (KNN). After integrating the information from 15 patients, the algorithm correctly classified the 16th patient into the third NYHA stage at hospitalization and second NYHA stage at discharge, based only on his voice recording. The KNN algorithm proved to have the best classification accuracy, with a value of 0.945. Voice is a cheap and easy way to monitor a patient’s health status. The algorithm we have used for analyzing the voice provides highly accurate preliminary results. We aim to obtain larger datasets and compute more complex voice analyzer algorithms to certify the outcomes presented.

Strategy of Muhammadiyah 1 Pandaan Vocational School in Learning Activities in the midst of the Covid-19 Pandemic

This scientific works was created with a purpose, to describe the learning strategis of Vocational High School of Muhammadiyah 1 Pandaan during the Covid pandemic. In this research process to get the data using techniques by interview, observation and also the voice recording when the research process was carried out. Vocational High School of Muhammadiyah 1 Pandaan use daring (online learning) for strategies during pandemic Covid-19, as for several supporting apllications used like Youtube, Zoom Meeting, Google Classroom ,ect. In the implementation of a strategy Vocational High School of Muhammadiyah 1 Pandaan have some obtacles, but even so Vocational High School of Muhammadiyah 1 Pandaan keep to develop the learning strategy, so that online learning goes well.

Monitoring and Feeding System for Pets

Over the years, more and more households are beginning to have pets. So, the most important issue recently was how to raise pets in an easy way. In today’s world, there is a growing focus on the regular interactions between human and physical devices. This paper introduces a smart pet monitoring and feeding system that is working in an environment of Internet of Things (IoT). Pet feeders came into existence as pet owners found it difficult to cater time to feed their pets. This system allows the owner to schedule and manage feeding times, portion sizes, and food supply for pets. They are controllable on smartphones using blynk and computers in order to feed them even when owners are away. The food dispensing mechanism is performed by the servomotor. It allows the user to monitor the pets using IP camera. A voice recording module is interfaced to the Arduino Uno with the owner’s voice recording for calling the pets at the meal time. Automatic water refilling has been designed and implemented along with the food dispenser.It offers new and developed way of feeding pets without the need of human intervention with refill alert and feeding alert. . Using smart pet feeder in houses will assure pet owners and increase comfort and peace of mind. Especially when we are unavailable for them.

THE USING OF WHATSAPP IN TEACHING PRONUNCIATION PRACTICE TO THE THIRD SEMESTER STUDENTS OF TADRIS ENGLISH STUDY PROGRAM IN IAIN PALU

This research focuses on the using of WhatsApp in teaching pronunciation practice to the third semester students of Tadris English Study Program in IAIN Palu. The research question is “How is the using of WhatsApp in teaching Pronunciation Practice to the third semester students of Tadris English Study Program in IAIN Palu?” This is a qualitative research by using two instruments of data collections namely questionnaire and interview. The participants consisted of 19 third semester students of Tadris English Study Program of State Institute for Islamic Studies (IAIN) Palu. The researcher conducted five meetings of Pronunciation Practice class to the participants via WhatsApp before distributing the questionnaire and interview sheet. The questionnaire consisted of five questions by applying Likert Scale, while the interview consisted of ten questions. From the questionnaire and interview, the researcher concludes that the using of WhatsApp in teaching Pronunciation Practice to the third semester students of Tadris English Study Program in IAIN Palu is practical. The students could understand the material shared via WhatsApp in the form of documents shared, videos shared, as well as voice recording shared. They could use the features in WhatsApp well such as sharing documents, voice notes, sharing videos, video call and so on in learning pronunciation practice. The students like Pronunciation Practice Class and enjoy studying it via WhatsApp. Learning Pronunciation Practice via WhatsApp has some advantages such as time flexibility as well as structured and easily accessed materials. However, it also has some limitations such as internet data availability and video call limitation. Besides, the participants faced several obstacles in learning Pronunication Practice via WhatsApp, such as the limitation of smartphone memory to save files, down internet server, and unavailability of internet data. Nevertheless, they could passed those obstacles well by deleting some unused files to give more space to the memory and finding out wifi connection to stay connected to WhatsApp when the server was down or they ran out of internet data. They could understand the teaching of Pronunciation Practice via WhatsApp by downloading and reading the documents shared, the videos shared, and the voice recording shared by the lecturer. When they found a difficulty, they asked their friends or the lecturer via WhatsApp group.