No abstract

Humanoid robots may be utilized in daily life and are more efficient at performing tasks that humans would find unpleasant. Robots are getting more proficient and are capable of performing many tasks that humans can. In a world designed for people, creating robots that behave like humans is a significant problem for robotics. In this study, we introduce a Voice Controlled Humanoid Robot, a mobile robot that can be moved by the operator by issuing precise voice instructions. The Google Voice API is used to handle the voice command when it is picked up by an Android phone's microphone. The vocal signals are then translated into text by the app, which creates a variable against the text and sends it to the Arduino Node MCU in the form of a command. The Arduino Node MCU then examines the instruction and performs the necessary operations. The VCHR app and VCHR system are linked together using the Bluetooth module. The android app also has a camera for live video streaming, and the robot can utilize its SONAR sensors to identify any obstacles in its path and sound an alert as a result. VCHR can carry out around 20 distinct tasks in total. When given voice input through the supplied external mic, the VCHR system is also capable of speech-emotion recognition in addition to these characteristics. The IoT cloud service provider ThingSpeak receives the temperature sensor data from the VCHR system in order to analyze and interpret the sensor data at various time intervals. The performance obtained for movement, speech emotion recognition, and sensor data processing is demonstrated by experimental findings.

The area of Computer Vision has gone through exponential growth and advancement over the past decade. It is mainly due to the introduction of effective deep-learning methodologies and the availability of massive data. This has resulted in the incorporation of intelligent computer vision schemes to automate the different number of tasks. In this paper, we have worked on similar lines. We have proposed an integrated system for the development of robotic arms, considering the current situation in fruit identification, classification, counting, and generating their masks through semantic segmentation. The current method of manually doing these processes is time-consuming and is not feasible for large fields. Due to this, multiple works have been proposed to automate harvesting tasks to minimize the overall overhead. However, there is a lack of an integrated system that can automate all these processes together. As a result, we are proposing one such approach based on different machine learning techniques. For each process, we propose to use the most effective learning technique with computer vision capability. Thus, proposing an integrated intelligent end-to-end computer vision-based system to detect, classify, count, and identify the apples. In this system, we modified the YOLOv3 algorithm to detect and count the apples effectively. The proposed scheme works even under variable lighting conditions. The system was trained and tested using a standard benchmark i.e., MinneApple. Experimental results show an average accuracy of 91%.

Objective: The aim of this study is to analyze significant findings of upper gastrointestinal endoscopy in patients having alarming features of dyspepsia. Study Design: Retrospective study Methodology: This retrospective study was conducted in the Gastroenterology Department at RIHS Islamabad from March 2021 to March 2022 and included adult patients presenting with alarm features and were referred for gastroscopy for dyspepsia. Those ageing below 18 years were excluded. The information including demographic data, referral for the procedure, endoscopic findings and present alarm features and dyspeptic symptoms was recorded. The diagnosis was made on the basis of visual examination. Results: A total of 140 patients who underwent gastroscopic procedures were included in the study. Most of the subjects (74.1%) reported epigastric burning, 10.8% complained of heartburn, 10.8% of regurgitation and 8% reported globus. Few of the participants reported symptoms such as bloating (5.3%), burping (5.3%), abdominal fullness (3.8%), chest pain (3.8%) and early satiety (0.8%). No significant relation was observed between warning signs and findings from the endoscopy. Conclusion: Dyspeptic patients showing alarming signs such as vomiting, dysphagia and upper gastrointestinal bleeding must be prescribed immediate endoscopy. Keywords: Dyspepsia, gastroenterology, endoscopic findings, epigastric burning

Objective: To determine the association between endoscopic findings vs. serology findings of patients with suspected celiac disease Methods: All the suspected cases (based on their clinical manifestations) of celiac disease were initially recruited having age >14 years and <40 years of both gender. Patients who did not willing to participate, patients already taking gluten diet for more than 3 months, patients with other causes of chronic diarrhea and alternate diagnosis like thyrotoxicosis, whipple’s disease, giardiasis, patients with drug induced diarrhea, patients in whom we cannot perform endoscopy, pregnant women, and patients already diagnosed cases of celiac disease were excluded from this study. Celiac disease was confirmed based on positive anti-tTG antibodies. Endoscopic evaluation of duodenum was performed in all positive cases. Results: A total of 50 patients were recruited for final analysis. Diagnostic accuracy of endoscopy was 34.6%. Young population (31.14±6.07 years) with females predominance (72%, n=36) were more common than males. The most common symptoms were presence of chronic diarrhea (74%, n=37) followed by abdominal pain (52%, n=26), nausea & vomiting (34%, n=17), and least common was presence of constipation (2%, n=1). On endoscopic evaluation, out of 50 positive anti-tTG antibodies cases, 24 had normal mucosa while partial villous atrophy observed in 15 (30%) cases and total villous atrophy observed in 11 cases (22%). Conclusions: Celiac disease was more prevalent in young females and patients usually presents with history of chronic diarrhea. Anti-tTG antibodies have more diagnostic value than duodenal endoscopy. Villous atrophy was found in more than 50% of the patients who were diagnosed with celiac disease.