The transformation from conventional power grid to smart grid has brought interdisciplinary concepts together. The distribution management system is a part of the smart grid and is a complex entity which requires different applications for monitoring, control and manage the distribution network operator (DNO). In this paper the communication framework is proposed for microgrid control center (MGCC) to DMS using long term evolution protocol (LTE). The LTE physical layer is modeled in MATLAB/SIMULINK and the bit error rate (BER) to signal to noise ratio (SNR) curves are plotted.
This Gestures is one of the best ways of communication between dumb and blind people depend on the expression of signs. In this paper we suggest an algorithm to recognizing hand gestures of Arabic letters to communicate between the dumb (through signs) and blind (hear the voice corresponding to sings). The proposed algorithm used the video of gesture from the dumb then convert the video into frames ( images) and calculate the distance to recognition the letters by using k-mean, k- medoid and artificial neural network, calculate the distance by using Euclidean distance and slop. There are sixteen features (8-features from Euclidean distance and 8-features from slop ). The results were (93.3673% For k-mean),(93.1354% for k-medoid ) and(92.9499% for ANN). We create our data base (from 5- videos with 308 frames).
In industrial plants or any critical utility plants, the ultimate goal is to maximize the production quantity and quality but at the same time keeping the production cost as low as possible. To achieve this, it is mandatory to keep plants in fully efficient condition so that the throughput of the system is maximum. In order to keep the system fully efficient it needs to be maintained properly. There are different maintenance strategies being used to maintain the efficiency of the plant. For any specific type of industry, maintenance affects the cost of goods produced. To avoid breakdown, the maintenance strategies should be planned in such a way that the maintenance tasks are executed at right time. Unnecessary maintenance tasks increase the maintenance costs and also the time required to execute them. Through this paper, the prospect of optimizing the plant operation i.e. to reduce the down time of the system using predictive maintenance (PdM) approach which will lead to reduced production cost has been explored.
Wind power is one of the fastest emerging green energy sources all over the worldwide with the lowest cost of electricity production. It is clean and reduces greenhouse gas emissions during operation in a high amount and uses little land for installation of the system. Higher investments have made by many countries to develop wind energy as an substitute to fossil fuels and economical energy source. Wind energy systems are non-linear sources that need precise on-line recognition on the best possible operating point. Planning at optimizing the performance of wind energy harvesting systems to ensure optimal functioning of the unit, new intelligent technique such as the fuzzy logic (FL) have been applied to the dynamic control of wind power system. It effectively controls the pitch angle to adjust the speed of the generator according to the wind speed to produce better power and protect the system from damage.
Indigenous design of a multi-link flexible robotic system and its hardware manifestation is a challenging domain of today's research in robotics. In the present work, a novel test setup has been made for experimenting on a prototype Flexible Robotic System (FRS), focusing mainly in the drive and actuation mechanism. Due to the slenderness and inherent trembling of FRS, selection as well as design of the drive system of the robot is truly competitive. The FRS test-bed is finally intended for developing a full-fledged application-centric robotic system, namely, Patient Assistance Robot (PAR). Various metrics of the real-time operation of the proposed PAR have been attained in this work through the successful commissioning of the test set-up of the FRS.
The subsystem of IoMT (Internet of Military of Things) called IoBT (Internet of Battle of Things) is the major resource of the military where the various stack holders of the battlefield and different categories of equipment are tightly integrated through the internet. The proposed architecture mentioned in this paper will be helpful to design IoBT effectively for warfare using irresistible technologies like information technology, embedded technology, and network technology. The role of Machine intelligence is essential in IoBT to create smart things and provide accurate solutions without human intervention. Non-Destructive Testing (NDT) is used in Industries to examine and analyze the invisible defects of equipment. Generally, the ultrasonic waves are used to examine and analyze the internal defects of materials. Hence the proposed architecture of IoBT is enhanced by ultrasonic based NDT to study the properties of the things of the battlefield without causing any damage.
In present days, data security and citizen privacy are the vulnerable areas globally. Amongst them, healthcare systems are the most targeted ones. In Nepal, among the few ehealth systems available, most are disconnected, fragmented and cyber security aspect is overlooked, creating even more risk. To effectively guide health care systems and make it more citizen-centric, centralized secured online healthcare system is essential. This study proposes a centralized, permissioned Blockchain based secured healthcare system using hyperledger for developing countries. This system follows distributed storage technology to facilitate better availability, redundancy and strong confidentiality using cryptographic encryption. Besides, this technique creates a transparent yet secure and immutable data storage and sharing platform. It optimally and effectively contributes to the transfer of health information that is cost effective. Regarding it, a pilot study was performed taking a tertiary care hospital; Hospital for Children, Eye, ENT and Rehabilitation Services (CHEERS) and its community hospital at Chapagaun. It was validated using the balanced scorecard to confirm its cost-effective performance. Nineteen most essential key progress indicators were chosen for study. From this study, it was deduced that transforming internal business process of a hospital setting by implementing proposed healthcare system results in 75% customer satisfaction as well as 63% financial gain. This approach uplifts the healthcare organizations and their financial status. It, in turn, sets a benchmark for a secured health care system of developing countries as a whole.
These days the safety of an individual is at stake, it may be due to ill health or due to the increasing crimes such as the sexual assaults, molestation, abuse etc. So in order to prevent these to a certain extent, this paper proposes an automated wearable smart device to prevent the above mentioned cause, which has access to internet (IOT). There are few bio sensors to sense the user's bodily changes and alert the required help when any abnormality is found as per the pre program of the device. The GSM and GPS are used to identify the victim's location when in need. The IP address of the Arduino is linked with the web server. The victim location is shared to the near by police station and to the pre registered mobile. While the buzzer alerts the surroundings of the victim.
Marine fishermen need weather updates in realtime. Currently, there is no affordable communication mechanism for them from the sea. OceanNet is a solution developed by our research center to serve this purpose. It is proposed to monitor oceanic microclimate using OceanNet by installing weather stations and sensors on boats and to issue realtime weather alerts to fishermen. A low-cost solar irradiance sensor is one of the sensors to be built in-house to monitor the weather changes. Accurate measurement of solar irradiance will aid research in the area of climate change adaptation. This paper describes the survey of solar irradiance sensors and measurement techniques conducted for this purpose. The review covers three types of commercial instruments and five different research prototypes for solar irradiance measurement. A suitable technique is formulated for our prototype based on this survey.
Angular Velocity(AV) estimation is necessary for controllers used for rotation motion monitoring. The velocity estimated is used for feedback and is very crucial in speed control for a variety of applications such as spacecraft tumbling detection, propeller speed control etc. Linear motion detection and linear velocity estimation has been exploited vastly. But, when it comes to angular velocity estimation of a randomly moving object with varying angular speeds, computation is very complex. Hence, computation of AV by non-contact based methods are in huge demand. The need for detection of the direction and value of rotation of a tumbling spacecraft in the Earth's orbit is a huge necessity. Accurate AV estimation has applications in spacecraft docking in space. In the proposed work we have developed an improved algorithm for real-time estimation of rotation using live video feed. The AV of the object can be measured by the camera feed of the rotating bodies as grabbed by the video camera. Angle is computed on every frame with respect to a reference and monitored for a certain number of frames to give the instantaneous AV. The number of frames processed by the camera is dynamic and is estimated prior to the angle calculation. Comparison of performance of AV estimation by the proposed algorithm with state-of-the-art Lucas Kanade(LK) object tracking method based AV estimation is also reported. The proposed approach shows significant improvement in estimating velocities whose motion is circular in nature. Additionally, this work advocates a novel approach towards an effective real-time angular velocity calculation by thresholding techniques, blob identification, and centroid detection.
At present day, we want everything in one space to save our time and maximize the utility. If we install different applications for different purposes then it will occupy more device memory and reduce device's efficiency. Therefore, we need to develop such kind of application which can be used for many purposes. To fulfill user-need, we have developed Multi-Utility Calculator Application where user will get four kind of functionality in a single App. Our proposed application can be installed in any android device and this is easy to use. This Multi-Utility Calculator App provides Standard Calculator, Scientific Calculator, Unit Converter and Alarm. This Application is efficient and user-friendly. Furthermore, this App is suitable for low memory and less-advanced devices. We have developed simple user interface of this application to reduce power consumption power consumption. Its light dark background saves power.
Migraine is a prolonged neurovascular illness, which causes outbreaks of severe pain and autonomic nervous system disturbance. The clinical analysis of Electroencephalogram signals helps in management and prognosis of migraine disease. Recent advancement in biomedical signal processing field led to generation of various techniques for multi-resolution analysis of Electroencephalogram signals and diagnosis of diseased condition. In present work, a nonlinear parametric approach of Electroencephalogram feature extraction is proposed and analysed for automated diagnosis of migraine disease. The Electroencephalogram database studied in present study was prepared in SMS Hospital, Jaipur, India. The database contains Electroencephalogram activity record of 26 healthy and migraineurs subjects. The Permutation Entropy, Higuchi's Fractal Dimension and Katz Fractal Diemension based features are extracted from processed Electroencephalogram signals. The extracted Electroencephalogram activity is classified using SVM, ANN and RF classifiers. It is illustrated from the classification results that the classification accuracy of 88% is achieved in migraine disease diagnosis task in present work.
Chronic Kidney Disease (CKD) is an increasing failure of kidney function leading to kidney failure over the years. The disease settles down and hence makes its diagnosis difficult. Analyzing CKD stages from standard office visit records can assist in premature recognition of the disease and prompt auspicious mediation. Hereby, we propose a methodology using inspired optimization model and learning procedure to classify CKD. The proposed method selects applicable features of kidney data with the help of Ant Lion Optimization (ALO) technique to choose optimal features for the classification process. After that, we sort the CKD data based on chosen features by utilizing Deep Neural Network (DNN). Performance comparison indicates that our proposed model accomplishes better classification accuracy, precision, F-measure, sensitivity measures when compared with other data mining classifiers.
An individual's proof of identity on the basis of gait has initiated inquisitiveness in the realm of computer vision owing to its extraordinary differentiation proficiency even at a remote distance. Biometric systems are vital as they offer trustworthy and effective ways to verify humans. Human gait or an individual's style of walking is a valuable biometric trait, which has lately invited inordinate consideration in applications like video surveillance. Gait recognition intends to tackle the problem of distantly identifying humans by recognizing them based on the manner they walk. This study aims to propose and develop a system of gait recognition for identifying humans using artificial neural networks (ANNs). In this study, a publicly available CASIA gait database was used, and gait recognition algorithm was applied to identify humans. Classification was done via ANNs. MATLAB was used to implement this research work. It was observed that the developed system was able to appropriately identify humans through gait recognition. When four databases were considered, the recognized ID was from database 2, which means that out of four databases, human gait was correctly recognized in ID 2 with a total time of 28.6713 seconds. The results of this work prove to be quite promising, which implies that if the count of databases is increased, then the developed system is able to correctly extract features and appropriately identify humans within a stipulated time.
Road safety is an important consideration in the transportation system. Many accidents occur due to road safety problems. Road accidents in India are increasing day by day, due to the rapid growth in a number of vehicles. The traffic congestion is growing at a rate of 7 to 10 % per annum while the vehicles are 12% per annum, hence this is one of the primary factors for the road safety problem. Every year nearly 1 million people died and 50 million are injured due to road accidents around the world. Particularly in India, 70,000 people died every year, this problem needs to overcome to save the life of the people. In this paper, a survey is done based on the various road safety problems and the comparison is done to identify the problem which leads to major accidents. Here the idea is proposed based on the statistics of the road safety issues to reduce the number of accidents that occur in a year.
Cloud storage and Social Media Applications can be accessed by using various Web and Portable Browsers. These applications available in Windows 10 Operating System. The cloud storage and social media applications allow its users to share their personal information, ideas, and files through their respective accounts. Because of this, the cloud storage and social media platforms has become a target for criminals to commit different type of cybercrimes. In order to identify the criminal activities, the traces of evidence which are present in user's machine by the use of these applications need to be extracted and analyzed. In this paper, potential locations of evidence in the Windows10 machines related to social media and cloud storage are collected and analyzed to find artifact locations and their details.
Real-time weather alerts will be very helpful to marine fishermen to avert the dangers from storms. Problems happen when the alerts are issued when the fishermen are already in sea. OceanNet, an affordable communication infrastructure for marine fishermen developed by our research center, will be used for this purpose. Weather stations installed on fishing vessels will perform fine-grained monitoring of the sea weather and alert the fishermen in real-time. The weather station will consist of low-cost sensors to monitor temperature, light, salinity, wind, humidity, etc. Towards this, we plan to develop a low-cost sensor for measuring the temperature of sea surface for better understanding of weather changes. Several techniques are existing to measure the sea surface temperature but most of them are expensive with less accuracy. This paper presents a survey of the available techniques and their comparison. A cost-effective technique based on thermopiles is selected for our prototype based on this survey.
In the recent years, natural disasters have become frequent due to many causes such as global warming. Flooding is one of the most common natural disasters. In this work, we introduce a flood monitoring system based on Computer Vision. The system determines the depth of the water from images captured using smartphones. The average human height is used as reference to estimate the water level. The human face is classified based on gender and age group so that the average human height of the corresponding category can be used in estimation of water depth. The data set for the system is preprocessed to mitigate the effect of poor lighting conditions, occlusions and alignment. The ground-truth validation is done using images with known water depth to determine the accuracy of the system developed.
key management is major issue in cryptographic algorithms. Key management includes key generation and sharing of secret key between sender and the receiver. The generated key should be random in nature. The sharing of key through secure channel is also a major research area. In this paper, different key generation methods are considered for a symmetric algorithm. In the first method, lfsr based key is used. In the second method, hash function method is used for key generation. The cryptographic system with above key generation techniques is modelled using hardware description language using VIVADO software
