International Journal of Innovations in Science & Technology

Accountable and Trustworthy IoT Networks, Based on Blockchain

2023-02-28T02:42:06-05:00

The term "Internet of Things" (IoT) refers to a situation in which intelligent things are linked to a network or the internet. IoT objects have become more prevalent over the past several years in many industries, and fields, and are now used in all facets of our life. The privacy of data is a crucial problem as the number of devices rises. Researchers in this discipline have employed a variety of strategies to address this issue. Regrettably, there is less accountability, data protection, and traceability with these solutions. In this study, a blockchain-based network architecture for accountability, privacy, and traceability is designed (TDA). Blockchain technologies are referred to as a distributed ledger of transaction records, which time-stamped information about a transaction's lifetime. Persistence, decentralization, and audibility are three of blockchain's key characteristics. The budget is reduced and efficiency is increased thanks to these characteristics. This study also discusses the performance of the suggested architecture in order to strengthen the TDA architecture.

Design of Mega LEO Constellations for Continuous Coverage over Pakistan

2023-01-31T22:51:57-05:00

Satellite communication was effectively done in Geostationary Earth Orbit (GEO) in the past years. Recently the trend has shifted from GEO to Low Earth Orbit (LEO). The objective of our study is to propose a satellite constellation for Pakistan in LEO that will provide continuous coverage over Pakistan. As LEO is much closer to the earth as compared to other orbits such as GEO and High Earth Orbit (HEO) etc. one can achieve benefits like low latency rate, less fuel consumption, and signal transmission loss. In ongoing research, an attempt has been made to design the satellite constellation in LEO using the software, System Tool Kit (STK) which has 2D and 3D environment modeling. In the designed constellation, the satellites pass over Pakistan and access the target area. To get uninterrupted continuous coverage, the number of satellites per plane and the number of orbits is increased. The orbital inclinations were also adjusted to achieve the objective. One of the important tasks for continuous coverage is the concept of satellite handshaking which means that soon a satellite gets away from the line of sight of the ground station antenna; another satellite comes within the line of sight of that antenna. LEO satellites are more favorable for communication purposes as they provide reliable communication as well as higher bandwidth.

Detection And Quantification of Lung Nodules Using 3D CT images

2023-01-06T05:06:49-05:00

In computer vision image detection and quantification play an important role. Image Detection and quantification is the process of identifying nodule position and the amount of covered area. The dataset which we have used for this research contains 3D CT lung images. In our proposed work we have taken 3D images and those are high-resolution images. We have compared the accuracy of the existing mask and our segmented images. The segmentation method that we have applied to these images is Sparse Field Method localized region-based segmentation and for Nodule detection, I have used ray projection. The ray projection method is efficient for making the point more visible by its x, y, and z components. like a parametric equation where the line crossing through a targeted point by that nodule is more dominated. The Frangi filter was to give a geometric shape to the nodule and we got 90% accurate detection. The high mortality rate associated with lung cancer makes it imperative that it be detected at an early stage. The application of computerized image processing methods has the potential to improve both the efficiency and reliability of lung cancer screening. Computerized tomography (CT) pictures are frequently used in medical image processing because of their excellent resolution and low noise. Computer-aided detection systems, including preprocessing and segmentation methods, as well as data analysis approaches, have been investigated in this research for their potential use in the detection and diagnosis of lung cancer. The primary objective was to research cutting-edge methods for creating computational diagnostic tools to aid in the collection, processing, and interpretation of medical imaging data. Nonetheless, there are still areas that need more work, such as improving sensitivity, decreasing false positives, and optimizing the identification of each type of nodule, even those of varying size and form.

Pragmatic Evidence on Android Malware Analysis Techniques: A Systematic Literature Review

2022-11-28T02:01:00-05:00

A large number of studies including research articles and surveys on android malware detection and analysis techniques have been presented during the last one and a half decades. The authors proposed different systems and frameworks to identify malware from software applications. However, there is no recent and comprehensive systematic literature review on the detection and analysis of android malware methods, systems, and frameworks. We present a systematic review of literature on android malware detection and analysis techniques and tools by following standard guidelines for Systematic Literature Review methodology from 2010 to 2021. We selected 75 most relevant studies out of 3343 published studies. We found that the prominent malicious datasets are Genome (39%) and Drebin (36%) used by different researchers for the detection of malware. The static, dynamic, and hybrid source code analysis methods are applied by android malware detection techniques. We also identified the limitations and future research directions of existing techniques as research gaps for the community. Based on the pragmatic evidence of this research, we have proposed a hybrid analysis-based multiple feature analysis framework. This framework will not only address the limitations of static and dynamic-based approaches, but it also analyzes evolving android malware datasets using deep neural network and machine learning techniques and improve the accuracy of evolving malware samples.

Action Recognition of Human Skeletal Data Using CNN and LSTM

2022-12-21T04:27:24-05:00

Human action recognition recognizes an action performed by human beings in order to witness the type of action being performed. A lot of technologies have been developed in order to perform this task like GRN, KNN, SVM, depth maps, and two-stream maps. We have used 3 different methods in our research first method is a 2D CNN model, the second method uses an LSTM model and the third method is a combination of CNN+LSTM. With the help of ReLu as an activation function for hidden and input layers. Softmax is an activation function for output training of a neural network. After performing some epochs the results of the recognition of activity are declared. Our dataset is WISDM which recognizes 6 activities e.g., Running, Walking, Sitting, Standing, Downstairs, and Upstairs. After the model is done training the accuracy and loss of recognition of action are described. We achieved to increase in the accuracy of our LSTM model by tuning the hyperparameter by 1.5%. The accuracy of recognition of action is now 98.5% with a decrease in a loss that is 0.09% on the LSTM model, the accuracy of 0.92% and loss of 0.24% is achieved on our 2D CNN model while the CNN+LSTM model gave us an accuracy of 0.90% with the loss of 0.46% that is a stupendous achievement in the path of recognizing actions of a human. Then we introduced autocorrelation for our models. After that, the features of our models and their correlations with each other are also introduced in our research.

Historical Development of Urban Planning Theory: Review and Comparison of Theories in Urban Planning

2022-12-01T02:11:15-05:00

Discipline of urban planning only developed around a century back with the first academic school at the University of Liverpool in 1909. However, the theory of this discipline is relatively older and might date to varying timelines around various parts of the world. However, modern urban planning discipline has got birth in the US and Western Europe. Early development in the theory of urban planning develops challenges for the cities. In response to such challenges, the planning approaches seem to adapt to the needs of emerging regimes evident from the high-scale urban renovation of Paris by Haussmann. This is called the Progressive Model of Planning wherein planners of the time struggled to deal with the challenges imparted by the Industrial Revolution through scientific and engineering-based knowledge. Early urban planning efforts were mostly anarchist movements that reacted to the social issues of the time and include Garden City, Radiant City, Broadacre, etc. This study sought to present these theoretical considerations with respect to certain development classifications in urban planning. Accordingly, the methodology of the research study comprises the following sections/segments for a better understanding of urban planning at different times:

Pre-History of Urban Planning
Foundational Years
Modernism (Rational Planning)
Post Modernism (Post war suburbia)
Current Era

In short, it is concluded that cities have emerged as a result of conscious decisions. Accordingly, looking into the planning theory requires due consideration of the planning approaches utilized over time. This perceives that planning theory is essentially the study of the decisions made from intuition and that is equally right because planning theory and practice development are in parallel.

Frontal System Track Variation and Its Impact on Water Availability in Northern Pakistan Using Remote Sensing and Ground Data During Monsoon Season- 2019

2022-12-07T02:37:46-05:00

Pakistan, which is positioned in the South Asian sub-continent, occupies a significant climatological location. It is included among the world's few countries which experience a comprehensive transformation from summer all the way to winter season. The variation in precipitation has direct and significant consequences on society. In this ongoing research, the latitudinal variation in the track of the frontal system and trends in Pakistan during the monsoon period have been examined. Meteorological data (monthly rainfall, maximum temperature, satellite images, upstream data for Tarbela, Mangla, Rasool, and Marala) has been taken to conduct the ongoing research. Consequently, the focus of the study is the frontal weather system that moves North of Pakistan and energizes the monsoon rainfall over the Indus Basin which makes it a source of flooding. The rainfall is the cause of flooding downstream of rivers in the plains of Punjab and Sindh. Varying trends in rainfall were observed across the selected stations in Pakistan. The ongoing research is conducted across Pakistan with Gilgit and Skardu being the cities in Northern Pakistan. Among all the water reservoirs, Tarbela exhibited an increased upstream flow due to the snow melt factor over glaciers in Gilgit and Skardu because of an increase in maximum temperature.