Sibghat Ullah Bazai

Balochistan University of Information Technology, Engineering and Management Sciences | BAUITEMS · Computer Engineering

Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals’ lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artifici...

In recent years, the Internet of Things (IoT) has emerged rapidly in the field of smart home automation. However, the short battery life, low processing power, and limited memory of IoT technology result in limited fault lines. According to the Open Web Application Security Project (OWASP) report, approximately 70% of IoT devices are vulnerable. Ho...

Due to recent development in different sectors such as industrialization, transportation, and the global economy, air pollution is one of the major issues in the twenty-first century. In this work, we aimed to predict ambient PM2.5 concentration using the prophet forecasting model (PFM) in Anhui Province, China. The data were collected from 68 air...

Blind and visually impaired people find difficulty in detecting obstacles and recognizing people in their way, which makes it dangerous for them to walk, to work, or to go in a crowded area/place. They have to be cautious all the time to move, while avoiding any solid obstacles in their way. Typically, they use different aid devices to reach their...

The aim of this review is to examine the integration of artificial intelligence (AI) in cyber-physical systems (CPS) and create a conceptual framework for enhancing the resilience of AI through automation on both technological and human levels. To do this, a literature review and taxonomy analysis of the interconnected CPS that make up the Internet...

With the continuous development of information technology and medical data information, more and more clinicians recognize artificial intelligence or will completely change medical practice by using advanced machine learning methods. The potential of using machine learning and predictive analysis to customize specific treatments for individuals is...

Internet of Things (IoT) has revolutionized the world in the last decade. Today millions of devices are connected to each other utilizing IoT technology in one way or the other. With the significant growth in IoT devices, the provision of IoT security is imperative. Routing protocol for low power and lossy networks (RPL) is a network layer protocol...

Smart grids are frequently targeted by false data injection, also known as FDI. Foreign direct interference (FDI) cannot be detected using data detection methods that are insufficient today. FDI attacks can be detected using a variety of methods, including machine learning. The purpose of this study is to look at six different supervised learning (...

In recent years, cellular technology has grown in popularity, increasing the importance of 5G networks. Security standards are losing trust as large attacks and concerns about privacy increase. A number of fundamental security issues are addressed in this paper. Major telecommunications firms and academic studies provide this information. Many intr...

China’s economy has made significant strides in the past three decades. As a direct result of China’s “one belt, one road” (OBOR) initiative, the country’s rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely dependent on the enormous amounts of energy currently being consumed an...

Emotions play a vital role in education. Technological advancement in computer vision using deep learning models has improved automatic emotion recognition. In this study, a real-time automatic emotion recognition system is developed incorporating novel salient facial features for classroom assessment using a deep learning model. The proposed novel...

During the epidemic period, primary emissions across the world were significantly reduced, while the response to secondary pollution such as ozone differed from region to region. To study the impact of the strict control measures of the new COVID-19 epidemic on the air quality of Anhui in early 2020, the air quality monitoring data of Anhui, from 2...

Due to recent developments in the global economy, transportation, and industrialization, air pollution is one of main environmental issues in the 21st century. The current study aimed to predict both short-term and long-term air pollution in Jiangsu Province, China, based on the Prophet forecasting model (PFM). We collected data from 72 air quality...

Quantifying atmospheric aerosols and their linkages to climatic repercussions is necessary to understand the dynamics of climate forcing and enhance our knowledge of climate change. Because of this reactivity to precipitation, temperature, topography, and human activity, the atmospheric boundary layer (ABL) is one of the most dynamic atmospheric re...

An important measurable indicator of urbanization and its environmental implications has been identified as the urban impervious surface. It presents a strategy based on three-dimensional convolutional neural networks (3D CNNs) for extracting urbanization from the LiDAR datasets using deep learning technology. Various 3D CNN parameters are tested t...

An important measurable indicator of urbanization and its environmental implications has been identified as the urban impervious surface. It presents a strategy based on three-dimensional convolutional neural networks (3D CNNs) for extracting urbanization from the LiDAR datasets using deep learning technology. Various 3D CNN parameters are tested t...

Multi-dimensional data anonymization approaches (e.g., Mondrian) ensure more fine-grained data privacy by providing a different anonymization strategy applied for each attribute. Many variations of multi-dimensional anonymization have been implemented on different distributed processing platforms (e.g., MapReduce, Spark) to take advantage of their...

Introduction: The primary aim was to develop convolutional neural network (CNN)-based artificial intelligence (AI) models for pneumothorax classification and segmentation for automated chest X-ray (CXR) triaging. A secondary aim was to perform interpretability analysis on the best-performing candidate model to determine whether the model's predict...

Mitigation measures and control strategies relating to the novel coronavirus disease 2019 (COVID-19) have been widely applied in many countries to reduce the transmission of this pandemic disease. China was the first country to implement a strong lockdown policy to control COVID-19 when countries worldwide were struggling to manage COVID-19 cases....

Studying the progress and trend of the novel coronavirus pneumonia (COVID-19) transmission mode will help effectively curb its spread. Some commonly used infectious disease prediction models are introduced. The hybrid model is proposed, which overcomes the disadvantages of the logistic model’s inability to predict the number of confirmed diagnoses...

Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates...

Education is the cultivation of people to promote and guarantee the development of society. Education reforms can play a vital role in the development of a country. However, it is crucial to continually monitor the educational model's performance by forecasting the outcome's progress. Machine learning-based models are currently a hot topic in impro...

Sustainable development goals (SDG) involve not only environmental issues but also economic, social, and cultural concerns. Higher education plays a key role in promoting sustainable development initiatives and in empowering people to change their thinking and to strive for a sustainable future. However, the main issue that needs to be presently re...

Data anonymization strategies such as subtree generalization have been hailed as techniques that provide a more efficient generalization strategy compared to full-tree generalization counterparts. Many subtree-based generalizations strategies (e.g., top-down, bottom-up, and hybrid) have been implemented on the MapReduce platform to take advantage o...

Recent studies in data anonymization techniques have primarily focused on MapReduce. However, these existing MapReduce based approaches often suffer from many performance overheads due to their inappropriate use of data allocation, expensive disk I/O access and network transfer, and no support for iterative tasks. We propose “SparkDA” which is a ne...

Recent proposals in data anonymization have mostly been focused around MapReduce, though the advantages of Spark have been well documented. To address this concern, we propose a new novel data anonymization technique for Apache Spark. SparkDA, our proposal, takes the full advantages of innovative Spark features, such as better partition control, in...

Data analytics scenario such as a classification algorithm plays an important role in data mining to identify a category of a new observation and is often used to drive new knowledge. However, classification algorithm on a big data analytics platform such as MapReduce and Spark, often runs on plain text without an appropriate privacy protection mec...

Big data applications typically require a large number of clusters, running in parallel, to process data fast and more efficiently. This is typically controlled and managed by MapReduce. In MapReduce operations, Mappers transform input original key/value pairs to a set of intermediate key/value pairs while Reducers aggregate a set of intermediate v...