Journal of ISMAC - June 2019
Latest Publications


TOTAL DOCUMENTS

64
(FIVE YEARS 64)

H-INDEX

10
(FIVE YEARS 10)

Published By Inventive Research Organization

2582-1369
Updated Saturday, 26 June 2021

2021 ◽  
Vol 3 (2) ◽  
pp. 163-175
Author(s):  
Bindhu V ◽  
Ranganathan G

With the advent of technology, several domains have b on Internet of Things (IoT). The hyper spectral sensors present in earth observation system sends hyper spectral images (HSIs) to the cloud for further processing. Artificial intelligence (AI) models are used to analyse data in edge servers, resulting in a faster response time and reduced cost. Hyperspectral images and other high-dimensional image data may be analysed by using a core AI model called subspace clustering. The existing subspace clustering algorithms are easily affected by noise since they are constructed based on a single model. The representation coefficient matrix connectivity and sparsity is hardly balanced. In this paper, connectivity and sparsity factors are considered while proposing the subspace clustering algorithm with post-process strategy. A non-dominated sorting algorithm is used for that selection of close neighbours that are defined as neighbours with high coefficient and common neighbours. Further, pruning of useless, incorrect or reserved connections based on the coefficients between the close and sample neighbours are performed. Lastly, inter and intra subspace connections are reserved by the post-process strategy. In the field of IoT and image recognition, the conventional techniques are compared with the proposed post-processing strategies to verify its effectiveness and universality. The clustering accuracy may be improved in the IoT environment while processing the noise data using the proposed strategy as observed in the experimental results.


2021 ◽  
Vol 3 (2) ◽  
pp. 149-162
Author(s):  
Sejal Bagde ◽  
Pratiksha Ambade ◽  
Manasvi Batho ◽  
Piyush Duragkar ◽  
Prathmesh Dahikar ◽  
...  

As the years progress, our world is becoming more technologically advanced, and humanity will soon be technologically focused. Henceforth, some fundamental measures should be made by individuals in order to develop the advanced next generation technologies. In this perspective, the proposed research work has developed an Android application with a unit comprising of ESP8266 Wi-Fi module, relay, logic level converter module, capacitive touch sensor module and also a Wi-Fi technology has been used to control the switches.


2021 ◽  
Vol 2 (2) ◽  
pp. 132-148
Author(s):  
Joy Iong-Zong Chen

COVID-19 appears to be having a devastating influence on world health and well-being. Moreover, the COVID-19 confirmed cases have recently increased to over 10 million worldwide. As the number of verified cases increase, it is more important to monitor and classify healthy and infected people in a timely and accurate manner. Many existing detection methods have failed to detect viral patterns. Henceforth, by using COVID-19 thoracic x-rays and the histogram-oriented gradients (HOG) feature extraction methodology; this research work has created an accurate classification method for performing a reliable detection of COVID-19 viral patterns. Further, the proposed classification model provides good results by leveraging accurate classification of COVID-19 disease based on the medical images. Besides, the performance of our proposed CNN classification method for medical imaging has been assessed based on different edge-based neural networks. Whenever there is an increasing number of a class in the training network, the accuracy of tertiary classification with CNN will be decreasing. Moreover, the analysis of 10 fold cross-validation with confusion metrics can also take place in our research work to detect various diseases caused due to lung infection such as Pneumonia corona virus-positive or negative. The proposed CNN model has been trained and tested with a public X-ray dataset, which is recently published for tertiary and normal classification purposes. For the instance transfer learning, the proposed model has achieved 85% accuracy of tertiary classification that includes normal, COVID-19 positive and Pneumonia. The proposed algorithm obtains good classification accuracy during binary classification procedure integrated with the transfer learning method.


2021 ◽  
Vol 2 (2) ◽  
pp. 121-131
Author(s):  
Jennifer S. Raj

In this research work and unmanned aerial vehicle (UAV) that uses blockchain methodology to collect health data from the users and saves it on a server nearby is introduced. In this paper the UAV communicates with the body sensor hives (BSH) through a low-power secure manner. This process is established using a token with which the UAV establishes relationship with the BSH. The UAV decrypts the retrieved HD with the help of of the shared key, creating a two-phase authentication mechanism. When verified, the HT is transmitted to a server nearby in a safe manner using blockchain. The proposed healthcare methodology is analysed to determine its feasibility. Simulation and implementation is executed and a performance of the work is observed. Analysis indicates that the proposed work provides good assistance in a secure environment.


2021 ◽  
Vol 2 (2) ◽  
pp. 96-110
Author(s):  
Smys S ◽  
Abul Bashar ◽  
Wang Haoxiang

This research article investigates effective energy protocols for wireless sensor networks (WSN). The newly proposed taxonomic classification and comparison provides the following protocol categories: latency and efficient routing based on energy and hop selection in network and its architecture, communication sensor network, networking structure, procedure functioning, sending and receiving round mode, and route setting. This research work has examined each class to discuss and compare the different parameters of its representative routing protocols (mechanisms, advantages, disadvantages) based on the energy efficient rate along with delivery delay and network time. The simulation results on the NS-simulator of various protocols show that, the routing task has to be built upon different intelligent technologies to improve the network life and ensures better sensory area coverage.


2021 ◽  
Vol 2 (2) ◽  
pp. 111-120
Author(s):  
Madhura S ◽  
Deepthi G ◽  
Chinnitaha B ◽  
Disha D

Various physical parameters like humidity, temperature, raindrop, GSM, atmospheric pressure and LDR can be monitored effectively and can be made more interactive with the help of different sensors that are interfaced with microcontrollers like ATmega328P. All the sensors can be connected to this microcontroller ATmega328P as the center preparing unit for the whole framework and plans can be associated with the microcontroller. The real-time monitoring of the various systems becomes possible with this IoT based system. The Paper displays different application based on IoT and proves that the monitoring and control of the system becomes flexible, robust and effective for any real-time implementation .


2021 ◽  
Vol 2 (2) ◽  
pp. 82-95
Author(s):  
Edriss Eisa Babikir Adam ◽  
Sathesh

Recently, the image reconstruction study on EIT plays a vital role in the medical application field for validation and calibration purpose. This research article analyzes the different types of reconstruction algorithms of EIT in medical imaging applications. Besides, it reviews many methods involved in constructing the electrical impedance tomography. The spatial distribution and resolution with different sensitivity has been discussed here. The electrode arrangement of various methods involved in the EIT system is discussed here. This research article comprises of adjacent drive method, cross method, and alternative opposite current direction method based on the voltage driven pattern. The assessment process of biomedical EIT has been discussed and investigated through the impedance imaging of the existent substances. The locality of the electrodes can be calculated and fixed for appropriate methods. More specifically, this research article discusses about the EIT image reconstruction methods and the significance of the alternative opposite current direction approach in the biomedical system. The change in conductivity test is further investigated based on the injection of current flow in the system. It has been established by the use of Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EDITORS) software, which is open-source software.


2021 ◽  
Vol 2 (2) ◽  
pp. 69-81
Author(s):  
Jayaram Hariharakrishnan ◽  
Bhalaji N

Ubiquitous Networks powered by Wireless Sensor Networks (WSN) is cutting across many technologies assisting day-to-day human activities. This technology confers the ability to sense and surmise the external environmental factors of various ecologies. Interconnection of these sensing devices for Machine to Machine (M2M) communication leads to the origination of Internet-of-Things (IoT). Recent advancements in the technology of Internet-of-Things guides the production of smart objects that can accomplish location, identification, connection and measurement of external factors. This leads to a new type of communication paradigm between objects and humans. One of the important problem due to the population explosion that can be addressed by IoT is the Healthcare of individual human beings. Remote health monitoring is one of the greatest technology exploited in medical professionals to keep a check on the patient’s important health factors periodically. This was done in a smaller geographical area before the era of IoT. As IoT can communicate to other Internet, This remote healthcare monitoring can now be applied over a wider geographical topology. This paper extensively analyses the performance of 6LoWPAN and RPL IoT for healthcare applications. This paper especially focuses on monitoring an athlete's thermoregulation. Also, a new technique to identify and train marathon athletes to the race topography has been proposed. In this technique, each athlete is fitted with wearable sensors in their body in the training session to monitor and analyze the thermoregulation process occurring during training. After a detailed analysis of the athletes’ thermoregulation process, personal training schedules are charted down according to variation in the thermoregulation process in each athlete. This technique helps to monitor each athlete’s progress personally with less number of coaches and medical professionals leading to the prevention of unexpected death of a healthy athlete.


2021 ◽  
Vol 3 (1) ◽  
pp. 60-68
Author(s):  
Sivaganesan D

The users largely contributing towards product adoption or information utilization in social networks are identified by the process of influence maximization. The exponential growth in social networks imposes several challenges in the analyses of these networks. Important has been given to modeling structural properties while the relationship between users and their social behavior has being ignored in the existing literature. With respect to the social behavior, the influence maximization task has been parallelized in this paper. In order to maximize the influence in social networks, an interest based algorithm with parallel social action has been proposed. This is algorithm enables identifying influential users in social network. The interactive behavior of the user is weighted dynamically as social actions along with the interests of the users. These two semantic metrics are used in the proposed algorithm. An optimal influential nodes set is computed by implementing the machines with CPU architecture with perfect parallelism through community structure. This helps in reducing the execution time and overcoming the real-word social network size challenges. When compared to the existing schemes, the proposed algorithm offers improved efficiency in the calculation speed on real world networks.


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