Development and Control of a 3-DoF Exoskeleton Robot for Forearm and Wrist Rehabilitation

The research conducted under this project directly contributes to the development of a forearm and wrist rehabilitation robot (UWM-FWRR). Upper extremity impairment following stroke, trauma, sports injuries, occupational injuries, spinal cord injuries, and orthopaedic injuries results in significant deficits in hand manipulation and the performance of everyday tasks. Strokes affect nearly 800,000 people in the United States each year. Rehabilitation programs are the main method of promoting functional recovery in individuals with finger impairment. The conventional therapeutic approach requiring a long commitment by both the clinician and the patient. Robotic devices (RDs) are novel and rapidly expanding technologies in hand rehabilitation. However, existing RDs have not been able to fully restore hand functionality as they cannot provide the independent joint control and levels of velocity and torque required. Our customer discovery [1] reveals that therapists often prescribe therapeutic devices for passive arm/leg movement assistance but no therapeutic devices exist for combined hand, wrist, and forearm movements that can be used at home/clinic. Regaining hand strength and mobility plays an important role in supporting essential activities of daily living, such as eating, and thus has the potential to improve the physical and mental status of both stroke patients and their family caregivers. Therefore, through this research author has develop UWM-FWRR that can provide rehabilitative exercises for forearm and, wrist movements. In contrast to existing RDs, developed UWM-FWRR is a portable, light weight, low cost, and novel powered rehabilitation device that will be developed to provide therapeutic exercises to a wide group of patients with different degrees of impairments. This innovation provides an opportunity for the patients to perform exercises not only with the guidance of a therapist at clinic but also be used at home as a telerehabilitation device through smartphone application (Future works)

Sentiment Analysis of COVID-19 Vaccination Impact on Twitter Tweets Using NLP Supervised Learning and RNN Classification Comparison

Twitter provides a platform for exchanging information and opinions on global concerns like the COVID-19 epidemic. During the COVID-19 pandemic, we used a collection of around 16,180 tweets to derive inferences regarding public views toward the vaccine impact once immunizations became widely available to the community. We use natural language processing and sentiment analysis techniques to uncover information regarding the public's perception of the COVID-19 vaccine. Our findings demonstrate that people are more pleased about taking COVID-19 shots than they are about some of the vaccines' side effects. We also look at people's reactions to COVID-19 safety measures after they have received the immunizations. In terms of maintaining safety precautions against COVID-19 among the vaccinated population, good attitude outnumbers negative emotion. We also estimate that around 48 percent of individuals have a neutral attitude, 36 percent have a positive opinion, and around 16 percent have a negative opinion towards vaccination. This research will help policymakers better assess public reaction and plan vaccination campaigns, as well as health and safety measures, amid the current global health crisis

Vulnerability to Flooding in Cities at Local Scale: New Methodology with Application to a Local Council in Sydney

Background. Flood studies are conducted mostly at city or catchment scales. While such studies are necessary for developing flood policies, municipalities require, in addition, place-specific data and strategies that can identify population at risk and develop tailored measures to reduce vulnerability and increase resilience. Local authorities commonly conduct their own flood studies, concentrating on the geophysical aspects of floods without considering their differential social impacts. Different communities and individuals may be at risk for different reasons and for effective flood risk management and better adaptation to floods, it is important to know not only how significant the aggregate flooding risk is, but who is at risk and what are the drivers of their vulnerability. Objectives and Methods. The objective of the study is to develop a new methodology for assessing urban flood risk at local scale by constructing a Flood Social Vulnerability (FSV) model and use it assess the extent to which vulnerability to flooding is likely to change under different scenarios of climate change. The model is based on a hybrid approach, combining hydrological and hydraulic flood simulations with social vulnerability and built-environment indicators. The methodology is tested by applying it to the Marrickville Study Region (MSR), which consists of a number of suburbs in Sydney’s Inner-West known to be prone to flooding. The study area is divided into a set of local spatial units, determined by the smallest unit at which aggregated data is available. This is, in the case of MSR, the SA1 scale of the Australian Bureau of Statistics. A set of indicators under each dimension of a flood risk pyramid – hazard, exposure and social vulnerability – are extracted from simulation analyses and socio-economic databases, for each local unit, and combined into a flood social vulnerability index (FSVI). Moreover, this research investigated how vulnerability might change in the future due to the impact of climate change under today’s demographic, socioeconomic and built-environment conditions. To test the suitability of FSVI in informing flood mitigation policy making within a local government, results were discussed with the local government authority (the Inner-West Council) of the MSR. Findings. FSVI developed in this study helped in detecting local flood vulnerability hotspots. There was little overlap between the spatial distribution of the three sets of indicators (hazard, exposure and social vulnerability). Hence, drawing on socio-economic information to assess vulnerability to flooding was found to be useful. Simulation of climate change scenarios show noticeable increases in the duration of floods, but limited changes in flood depths, velocities and extents. Stakeholders at the Inner-West Council stated that the study’s findings could inform the Council’s current flood management planning, especially in relation to emergency services

Impact of Social Media Marketing on development of brand awareness among target customers

Masteroppgave International Business and Marketing - Nord universitet 202

Movie Popularity Classification based on Inherent Movie Attributes using C4.5,PART and Correlation Coefficient

Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we propose classification scheme of pre-release movie popularity based on inherent attributes using C4.5 and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient.Comment: 6 page

Burning of Crop Residue and its Potential for Electricity Generation

This paper identified the factors influencing the rice crop residue burning decision of the farmers and the potential of the burnt residue to generate electricity. For this study, data were collected from 400 farmers in the rice-wheat cropping system. Effects of different variables on the burning decision of rice residue are investigated through logit model. A number of factors had significant effects on the burning decision of crop residue. These included farming experience of the farmer, Rajput caste, farm size, owner operated farm, owner-cum-tenants operated farm, silty loam soil type, livestock strength, total cost associated with the handling of residue and preparation of wheat field after rice, availability of farm machinery for incorporation, use of residue as feed for animals, use of residue as fuel, intention of the respondent to reduce turnaround time between harvesting of rice and sowing of wheat, convenience in use of farm machinery after burning of residue and the geographic location of farm. The overall quantity of rice straw burnt is estimated to be 1704.91 thousand tonnes in the rice-wheat cropping areas with a potential to generate electric power of 162.51 MW. This power generation from crop residues would be a source of income for the farmers along with generation of additional employment opportunities and economic activities on sustainable basis. In order to minimise the cost of haulage of rice straw, installation of decentralised power plants at village level would be a good option. Further, use of rice crop residue as an energy source can help in reducing foreign exchange requirements for import of furnace oil. JEL Classification: O44, Q12, Q16, Q42, Q48 Keywords: Bioenergy, Crop Residue, Electricity, Energy, Growth, Ric