An EMG study to evaluate Chewing Efficiency and Maximum voluntary clenching (MVC) for different malocclusion groups before and during Orthodontic Treatment

The purpose of this study was to investigate the efficacy of chewing and maximum voluntary clenching (MVC) of patients with different malocclusion types by measuring the EMG activity in the masseter and temporalis muscles before and during orthodontic treatment

ADAPTIVE MULTI-OBJECTIVE OPERATING ROOM PLANNING WITH STOCHASTIC DEMAND AND CASE TIMES

The operating room (OR) is accountable for most hospital admissions and is one of the most cost and work intensive areas in the hospital. From recent trends, we discover an unexpected parallel increase in expenditure and waiting time. Therefore, improving OR planning has become obligatory, particularly regarding utilization, and service level. Significant challenges in OR planning are the high variations in demand, processing times of surgical specialties, the trade-off between the objectives, and control of OR performance in long-term. Our model provides OR configurations at a strategical level of OR planning to minimize the tradeoff between the utilization and service level accounting for variation in both demand and processing times of surgical specialties. An adaptive control scheme is proposed to aid OR managers to maintain the OR performance within the prescribed controllable limits. Our model is validated using a simulation of demand and processing time data of surgical services at University of Kentucky Health Care

Artificial Intelligence Framework for Sugarcane Diseases Classification using Convolutional neural Network

In many regions of the world, plant disorders have long been a threat to crop development and agricultural production, negatively affecting the availability of food for people. The best organised sector of agriculture is sugarcane cultivation. It is the first crop that farmers grow because of the ideal conditions for its development. It is closely related to the sugar sector and has a significant impact on the economy of several countries. Of all the crops grown for commercial purposes, sugarcane has the highest production value. In contrast, a different type of diseases can affect the quality and productivity of the crop. Growers can detect some of them by visual inspection of the leaves. Unfortunately, the majority of infections go undetected, causing farmers to suffer significant losses. To reduce the damage caused by an infestation, it is important to determine the type of infestation. So, we proposed a Deep Learning (DL) model that uses images of diseased leaves to train the model to recognise a specific disease affecting the sugarcane plant. In this work, we have used bacterial blight, red rot, red rust and healthy leaf images. The method used two convolutional neural networks to classify the 851 sugarcane leaf images. As a result, Resnet50 achieved the highest accuracy of and 99.70% for binary classification (normal and abnormal images). The trained model achieved its goal by identifying photos of sugarcane and classifying them into classes of healthy and diseased leaves. As a result, this research provides a proposal for using deep learning algorithms to help farmers detect and categorise sugarcane infections. Finally, we have applied an DL visualization technique such as gradient class activation map, occlusion sensitivity, and local interpretable model-agnostic to differentiate and understanding the classification process by highlighting area that is more used for the classification

Multi-modal Sensor Registration for Vehicle Perception via Deep Neural Networks

The ability to simultaneously leverage multiple modes of sensor information is critical for perception of an automated vehicle's physical surroundings. Spatio-temporal alignment of registration of the incoming information is often a prerequisite to analyzing the fused data. The persistence and reliability of multi-modal registration is therefore the key to the stability of decision support systems ingesting the fused information. LiDAR-video systems like on those many driverless cars are a common example of where keeping the LiDAR and video channels registered to common physical features is important. We develop a deep learning method that takes multiple channels of heterogeneous data, to detect the misalignment of the LiDAR-video inputs. A number of variations were tested on the Ford LiDAR-video driving test data set and will be discussed. To the best of our knowledge the use of multi-modal deep convolutional neural networks for dynamic real-time LiDAR-video registration has not been presented.Comment: 7 pages, double column, IEEE format, accepted at IEEE HPEC 201

GSU Event Portal

GSU Event is an event organizing portal, and it provides the events of all types that are organized by the event organizers and create your own Events of all kinds in any place in the United States and sell out the ticket with certain prices. The event portal is an easy way of searching events happening in all over the major cities across United States. The site provides information regarding the event, where it is happening, when it is happening and what is the entry for the event whether it is free or paid to the event goer. For the event organizer, it’s very easy to reach out to the millions of people around the world, easy, economical and efficient way to market the event, it gives event organizer to inform necessary information while booking to the event, organizer can change the price of entry based on the seating levels or different categories, if it is a free event it helps organizer to check the turn-out ratio and monitor who attended the event vs registered members. Another user of this application is administrator who monitors all the activity from the event organizer and event goer. Administrator has right to resolve issues between the organizer and event goer and policies for the type of events posted on the site. This portal is mobile-friendly, with easy-to-navigate interfaces and workflow to enable organizers to manage events, and help visitors discover events using the search by Either Event name, locations or Both and buy tickets with ease. The Portal responsive front-end Page is created by using HTML5, CSS, Bootstrap, JavaScript\u27s, jQuery and for the Back--End we are using C# Programming and Centralized database

Maximizing Operating Room Performance Using Portfolio Selection

The operating room (OR) is responsible for most hospital admissions and is one of the most cost and work intensive areas in the hospital. From recent trends, we observe an ironic parallel increase among expenditure and waiting time. Therefore, improving OR scheduling has become obligatory, particularly in terms of patient flow and benefit. Most of the hospitals rely on average patient arrivals and processing times in OR planning. But in practice, variations in arrivals and processing times causes high instability in OR performance. Our model of optimization provides OR schedules maximizing patient flow and benefit at a fixed level of risk using portfolio selection. The simulation results show that the performance of the OR has a direct relationship with the risk

Nature Quotes

Recent days an increasing number of mobile applications and its uploading of photos/images shows that normal in every mobile application, so here is the latest idea we come up with an image/photo uploading with some quotation display on top of the image/photo from the selection of predefined feature quote data bank, and also we can add some user defined inspirational quotes to data bank for further usage and this will be like displaying of photos in slide show manner based on user setup. In this paper, we present an automatic approach that first aligns the photos and displays to the user based on random manner and this will also set up the display of quote and background sequentially, randomly, or fixed on certain one they selected. A user interactive application that can process addition or modification to the feature data bank like photos uploading and quotes changing. Also user can set the speed limit to the slide show to display background and its feature quote and this we are developing with both the versions of android and IOS environments