Asghar ali shah - Academia.edu (original) (raw)
Papers by Asghar ali shah
Scientific Reports
In recent times, deep learning has emerged as a great resource to help research in medical scienc... more In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep Learning algorithm Convolutional Neural Network (CNN) to detect a Lung Nodule, which can be cancerous, from different CT Scan images given to the model. For this work, an Ensemble approach has been developed to address the issue of Lung Nodule Detection. Instead of using only one Deep Learning model, we combined the performance of two or more CNNs so they could perform and predict the outcome with more accuracy. The LUNA 16 Grand challenge dataset has been utilized, which is available online on their website. The dataset consists of a CT scan with annotations that better understand the data and information about each CT scan. Deep Learning works the same way our brain neurons work; therefore, deep learning is based on Artificial Neural Ne...
IEEE Access
Order management system is one of supply chain management system which has an important part rela... more Order management system is one of supply chain management system which has an important part related to the customer satisfaction and profit of the company. Order Management process is a software which is supportive for the businesses work hardware goods, where storeowner saves the records of sales and purchase. Mishandled record means disappointed clients, too much money tied up in storerooms, and slower sales. In the current scenario, people place the orders customers must visit hotels or cafeterias to know about foods and then delivered order and pay. In this process time and manual work is required. Due to the enhancement in technology, it is very easy for us to buy all the things of daily use by ordering online on E-Commerce sites. But in this advanced era of technology, we did not have any application or site for buying ingredients of the recipe that we want to make. In this paper, we are saving money, time, and Quantity of ingredients from wastage. In which we are providing Recipes and the Quantitative ingredients for that recipe within 1 to 2 hours. This system will provide quick service of order delivering to our consumer. INDEX TERMS Inventory management system, just in time, GPS tracking system, home of distributive ingredients (HODI).
DIGITAL HEALTH
The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is ... more The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is sarcoma, mostly found in human bones and soft tissue cells. It commonly occurs in children. According to a survey of the United States of America, there are more than 17,000 sarcoma patients registered each year which is 15% of all cancer cases. Recognition of cancer at its early stage saves many lives. The proposed study developed a framework for the early detection of human sarcoma cancer using deep learning Recurrent Neural Network (RNN) algorithms. The DNA of a human cell is made up of 25,000 to 30,000 genes. Each gene is represented by sequences of nucleotides. The nucleotides in a sequence of a driver gene can change which is termed as mutations. Some mutations can cause cancer. There are seven types of a gene whose mutation causes sarcoma cancer. The study uses the dataset which has been taken from more than 134 samples and includes 141 mutations in 8 driver genes. On these gene s...
International Journal of Molecular Sciences
Genes are composed of DNA and each gene has a specific sequence. Recombination or replication wit... more Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocarcinoma starts in secretary cells. Breast adenocarcinoma is the most common of all cancers that occur in women. According to a survey within the United States of America, there are more than 282,000 breast adenocarcinoma patients registered each 12 months, and most of them are women. Recognition of cancer in its early stages saves many lives. A proposed framework is developed for the early detection of breast adenocarcinoma using an ensemble learning technique with multiple deep learning algorithms, specifically: Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Bi-directional LSTM. There are 99 types of driver genes involved in breast adenocarcinoma. This study uses a dataset of 4127 samples including men and women taken fr...
Scientific Reports
Breast adenocarcinoma is the most common of all cancers that occur in women. According to the Uni... more Breast adenocarcinoma is the most common of all cancers that occur in women. According to the United States of America survey, more than 282,000 breast cancer patients are registered each year; most of them are women. Detection of cancer at its early stage saves many lives. Each cell contains the genetic code in the form of gene sequences. Changes in the gene sequences may lead to cancer. Replication and/or recombination in the gene base sometimes lead to a permanent change in the nucleotide sequence of the genome, called a mutation. Cancer driver mutations can lead to cancer. The proposed study develops a framework for the early detection of breast adenocarcinoma using machine learning techniques. Every gene has a specific sequence of nucleotides. A total of 99 genes are identified in various studies whose mutations can lead to breast adenocarcinoma. This study uses the dataset taken from 4127 human samples, including men and women from more than 12 cohorts. A total of 6170 mutatio...
2021 International Conference on Innovative Computing (ICIC), 2021
Cancer has been identified as a serious genetic disorder which cause numerous deaths every year. ... more Cancer has been identified as a serious genetic disorder which cause numerous deaths every year. Late diagnosis of cancer is one of the major cause of deaths. Mutation is the disturbance in gene sequence and mutated genes are crucial for cancer growth. This study develops a machine learning model for the solution of mutation detection problem in genes sequence which may help in diagnosing the cancer at early stages. The aim of this system is to detect the mutation in gene sequences whether it is mutated or not. To detect mutation in gene sequences, several techniques and models of machine learning has been considered such as SVM, Logistic Regression and Linear Discriminant Analysis to achieve better accuracy.
2021 International Conference on Innovative Computing (ICIC), 2021
Epidemiogical evidence has shown that tumor suppressor genes early detection can play an importan... more Epidemiogical evidence has shown that tumor suppressor genes early detection can play an important part in the management of cancer. The statistics at a glance for all over the world about the burden of cancer have proved that cancer is another principal reason of death across the globe and it is also responsible for the about 9.6 million deaths in a single year. It is perceived that about 1 out of 6 deaths across the globe is due to cancer and about 70% of the deaths are more likely to occur in low and middle income or developing countries because tumor suppressor genes are not detected on early stages. In this regard, a systematic meta-analysis is conducted for the observation of role imparted. In this regard, 50 research articles have been used for the observation of role of tumor suppressor genes and one of the really exciting things about the tumor suppressor genes which is excluded from the research involves the fact that through genes transplant, cancer can be cured if the abnormal functionality is detected in early stages of cancer.
2019 International Conference on Innovative Computing (ICIC), 2019
In the current era of Science and Technology, every kind of field enables human life to use the i... more In the current era of Science and Technology, every kind of field enables human life to use the internet in excess amount for connecting with the world. Depending completely on services of the internet creates vulnerability for their private data, which allows attackers to strike for various limits. Well-ordered net applies assembled as diverge from past web time. There are attacks on the internet of Things (IOTs) as well, which causes big security challenges. A question arises here; what methodology to use for the appropriate working of network incoming and outgoing traffic data. For this, the Intrusion Detection System (IDS) is the item pack application used to provide security. IDS is used for screen and explore the principal reason for the framework in a couple of systems. In literature, researchers use the feeble date to play out the strike against association affiliation. It provides the substance care, complete guide and concentrates concerning IDS. The fundamental goal of concerning IDS is to watch out evil traps, goods work out, threats and so on. There exist several algorithms which are used for the classification of Intrusion Detection Attacks. In this study, the classification model Logistic Regression is applied on the dataset containing attacks. The performance of the Logistic Regression algorithm is evaluated by two means and compared. Classification of attacks is made using the Logistic Regression algorithm. For evaluation, the corresponding Specificity, Accuracy, Sensitivity and MCC are calculated to evaluate the prediction framework to attain the respective True Positive, false-positive rate for both of the aforementioned algorithms. By following scheme of 10-fold and Jack-Knife, it was discovered that the Sensitivity for classifiers was 99%, Specificity 96%, Accuracy 99% and MCC 98%. IDS is each consolidated with one another to make the Brought Together Danger, the board mix presence of mind into the fundamental unit.
Alexandria Engineering Journal, 2021
Background: Cardiac tumors are an exceedingly rare phenomena. Papillary fibroelastomas are the se... more Background: Cardiac tumors are an exceedingly rare phenomena. Papillary fibroelastomas are the second most common benign cardiac tumors. Despite their propensity to cause embolic strokes and acute coronary syndrome, a major consideration is also that of symptomatic peripheral artery disease as a presentation. Case: A 77 year-old female with history of a prior transient ischemic attack and hypertension presented to the hospital with severe pain within her right great toe after undergoing partial amputation a couple of weeks prior. On physical exam, she was found to have absent pulses within the popliteal and right femoral arteries. In anticipation for further surgical intervention, pre-operative cardiac evaluation was performed with a transthoracic echocardiogram that showed an ejection fraction of 75%, no regional wall motion abnormalities, and a well defined, mobile mass within the left ventricle measuring 18x14mm. Decision-Making: Further cardiovascular evaluation was obtained, with transesophageal echocardiogram confirming the finding of a 18x12mm pedunculated mass attached to the septal wall of the left ventricle. Right lower extremity angiography revealed total occlusion of the proximal segments of the right anterior tibial and peroneal arteries, as well as a total occlusion within the distal segment of the posterior tibial artery. Due to the finding of a cardiac mass causing peripheral embolization, the decision for surgical resection was reached. Pathological examination confirmed the diagnosis of papillary fibroelastoma of the left ventricle. The patient tolerated the procedure well and made a successful recovery. Conclusions: This case highlights the importance of a complete cardiac evaluation for patients presenting with peripheral vascular disease without known risk factors. Furthermore, it reinforces the importance of the echocardiogram to identify or exclude cardiac tumors as a potential cause of peripheral embolic phenomena
Energies, 2021
Internet of Things (IoT) performs a vital role in providing connectivity between computing device... more Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and tr...
IT Professional, 2021
Machine learning techniques are proven valuable for the Internet of things (IoT) due to intellige... more Machine learning techniques are proven valuable for the Internet of things (IoT) due to intelligent and cost-effective computing processes. In recent decades, wireless sensor network (WSN) and machine learning are integrated to give significant improvements for energy-based systems. However, resourceful routes analytic with nominal energy consumption are some demanding challenges. Moreover, WSN operates in an unpredictable space and a lot of network threats can be harmful to smart and secure data gathering. Consequently, security against such threats is another major concern for low-power sensors. Therefore, we aim to present a machine learning-based approach for autonomous IoT Security to achieve optimal energy efficiency and reliable transmissions. First, the proposed protocol optimizes network performance using a model-free Q-learning algorithm and achieves fault-tolerant data transmission. Second, it accomplishes data confidentiality against adversaries using a cryptography-based deterministic algorithm. The proposed protocol demonstrates better conclusions than other existing solutions.
SMART MOVES JOURNAL IJOSCIENCE, 2019
The purpose of image enhancement and image restoration techniques is to perk up a quality and fea... more The purpose of image enhancement and image restoration techniques is to perk up a quality and feature of an image that result in improved image than the original one. Unlike the image restoration, image enhancement is the modification of an image to alter impact on the viewer. Generally enhancement distorts the original digital values; therefore enhancement is not done until the restoration processes are completed. In image enhancement the image features are extracted instead of restoration of degraded image. Image enhancement is the process in which the degraded image is handled and the appearance of the image by visual is improved. It is a subjective process and increases contrast of image but image restoration is a more objective process than image enhancement. Many research work have been done for image enhancement. In this paper, different techniques and algorithms are discussed for contrast enhancement.
International Journal of Computer Applications, 2015
Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) ... more Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
IEEE Access
Machine learning and deep learning algorithms are widely used in computer science domains. These ... more Machine learning and deep learning algorithms are widely used in computer science domains. These algorithms are mostly used for classification and regression problems in almost every field of life. Semantic segmentation is an instantly growing research topic in the last few decades that refers to the association of each pixel in the image to the class it belongs. This paper illustrates the systematic survey of advanced research in the field of semantic segmentation till date. This study provides the brief knowledge about the latest proposed methods in the domain of semantic segmentation. The proposed study comprehends the concepts, techniques, tool, and results of different research frameworks proposed in the context of semantic segmentation. This study discusses the latest research papers in which machine learning and deep learning techniques are exploited for semantic segmentation and published between 2016 and 2021. The systematic literature review collected from seven different article libraries including ACM digital Library, Google Scholar, IEEE Xplore, Science Direct, Google Books, Refseek and Worldwide Science. For assuring the quality of the paper those papers are selected which have several citations on standardized platforms. Most of the studies used COCO, PASCAL, Cityscapes and CamVid dataset for training and validation of the machine learning and deep learning models. The results of the selected research articles are collected in the form of accuracy, mIoU value, F1 score, precision, and recall. In this study, we also conclude that most of the semantic segmentation studies use ResNet as the backbone of the architecture and none of the researchers used ensemble learning methods for semantic segmentation that is the loophole of the selected studies.
VAWKUM Transactions on Computer Sciences, 2018
TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) are the most important proto... more TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) are the most important protocols in complete protocol architecture. There are many types of attacks that can block the communication or reduce the performance of a protocol. This study provides a detail analysis of TCP and UDP attacks and their application layer protocols. The authors will also suggest that where the security administrator should focus for providing best security. The old datasets such as KDD99 and NSLKDD has many limitations. This study uses UNSW-NB15 dataset which has recently been generated.
Scientific Reports, 2020
Glutamic acid is an alpha-amino acid used by all living beings in protein biosynthesis. One of th... more Glutamic acid is an alpha-amino acid used by all living beings in protein biosynthesis. One of the important glutamic acid modifications is post-translationally modified 4-carboxyglutamate. It has a significant role in blood coagulation. 4-carboxyglumates are required for the binding of calcium ions. On the contrary, this modification can also cause different diseases such as bone resorption, osteoporosis, papilloma, and plaque atherosclerosis. Considering its importance, it is necessary to predict the occurrence of glutamic acid carboxylation in amino acid stretches. As there is no computational based prediction model available to identify 4-carboxyglutamate modification, this study is, therefore, designed to predict 4-carboxyglutamate sites with a less computational cost. A machine learning model is devised with a Multilayered Perceptron (MLP) classifier using Chou’s 5-step rule. It may help in learning statistical moments and based on this learning, the prediction is to be made a...
Lahore Garrison University Research Journal of Computer Science and Information Technology
Information and Communication Technology (ICT) has revolutionized the lives of the people. The te... more Information and Communication Technology (ICT) has revolutionized the lives of the people. The technology is embedded in daily life of literate or semiliterate/illiterate users. However, the user interface (UI) requirements for semiliterate/illiterate users are different from that of an educated person. The researchers of Human Computer Interaction for Development (HCI4D) face challenges to improve the usability of a UI for the semiliterate users. Therefore, a Systematic Literature Review (SLR) is conducted to provide a set of design factors and guidelines for UI development of semiliterate users. The study is based on extensive research gathered from literature to understand the user-centered design (UCD) approach, enhancing user experience (UX) for semiliterate users. This study analyses fifty two research articles that are published during 2010-2020. The findings shed light on the systematization of UI design guidelines for semiliterate/illiterate users. These guidelines can help...
Journal of Healthcare Engineering, 2022
Facial expression is one of the most significant elements which can tell us about the mental stat... more Facial expression is one of the most significant elements which can tell us about the mental state of any person. A human can convey approximately 55% of information nonverbally and the remaining almost 45% through verbal communication. Automatic facial expression recognition is presently one of the most difficult tasks in the computer science field. Applications of facial expression recognition (FER) are not just limited to understanding human behavior and monitoring person’s mood and the mental state of humans. It is also penetrating into other fields such as criminology, holographic, smart healthcare systems, security systems, education, robotics, entertainment, and stress detection. Currently, facial expressions are playing an important role in medical sciences, particularly helping the patients with bipolar disease, whose mood changes very frequently. In this study, an algorithm, automated framework for facial detection using a convolutional neural network (FD-CNN) is proposed ...
VAWKUM Transactions on Computer Sciences
CCTV cameras are commonly used for security issues. Pan-tilt-zoom (PTZ) cameras are mostly used f... more CCTV cameras are commonly used for security issues. Pan-tilt-zoom (PTZ) cameras are mostly used for this purpose. To stitch two or more video streams from different cameras is much cheaper than PTZ solution. There are three stages of video stitching. Feature identification is the first stage of video stitching. To scale the invariant features like rotation, scaling and noise etc. Direct and feature base identification has basically two types of feature identification. Shifting and warping the images purpose to identify how these features are agreeing with each other is the main concern for direct base identification. While feature identification rely on extracting the features and then perform matching among them on the base of features. Calibration is the second stage of the video stitching. The images are stitch in panoramic way in calibration depending upon alignment among them. Blending is the last stage of video stitching where numerous videos are display in single panoramic way. Any blending algorithm is used to blend the pixels together and for final view.
VAWKUM Transactions on Computer Sciences
As the research increased in computer science highlight the scientists mind for the growing resea... more As the research increased in computer science highlight the scientists mind for the growing research world towards security. Researchers have done a lot of research work in network Security. Cybersecurity has progressively become a zone of alarm for officials, Government agencies and industries, including big commercialized infrastructure, are under attack daily. First signature-based intrusion detection systems were developed, and it detects only novel attacks. To detect strange attacks statistical IDS came into being recognized as anomaly-based IDS. It is not as much efficient as it detects all. In this, study the author focus on the efficiency of IDS using NSL-KDD99 dataset and support vector machine (SVM) technique to identify attacks. NSL-KDD dataset is used for the evaluation of these type of systems.
Scientific Reports
In recent times, deep learning has emerged as a great resource to help research in medical scienc... more In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep Learning algorithm Convolutional Neural Network (CNN) to detect a Lung Nodule, which can be cancerous, from different CT Scan images given to the model. For this work, an Ensemble approach has been developed to address the issue of Lung Nodule Detection. Instead of using only one Deep Learning model, we combined the performance of two or more CNNs so they could perform and predict the outcome with more accuracy. The LUNA 16 Grand challenge dataset has been utilized, which is available online on their website. The dataset consists of a CT scan with annotations that better understand the data and information about each CT scan. Deep Learning works the same way our brain neurons work; therefore, deep learning is based on Artificial Neural Ne...
IEEE Access
Order management system is one of supply chain management system which has an important part rela... more Order management system is one of supply chain management system which has an important part related to the customer satisfaction and profit of the company. Order Management process is a software which is supportive for the businesses work hardware goods, where storeowner saves the records of sales and purchase. Mishandled record means disappointed clients, too much money tied up in storerooms, and slower sales. In the current scenario, people place the orders customers must visit hotels or cafeterias to know about foods and then delivered order and pay. In this process time and manual work is required. Due to the enhancement in technology, it is very easy for us to buy all the things of daily use by ordering online on E-Commerce sites. But in this advanced era of technology, we did not have any application or site for buying ingredients of the recipe that we want to make. In this paper, we are saving money, time, and Quantity of ingredients from wastage. In which we are providing Recipes and the Quantitative ingredients for that recipe within 1 to 2 hours. This system will provide quick service of order delivering to our consumer. INDEX TERMS Inventory management system, just in time, GPS tracking system, home of distributive ingredients (HODI).
DIGITAL HEALTH
The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is ... more The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is sarcoma, mostly found in human bones and soft tissue cells. It commonly occurs in children. According to a survey of the United States of America, there are more than 17,000 sarcoma patients registered each year which is 15% of all cancer cases. Recognition of cancer at its early stage saves many lives. The proposed study developed a framework for the early detection of human sarcoma cancer using deep learning Recurrent Neural Network (RNN) algorithms. The DNA of a human cell is made up of 25,000 to 30,000 genes. Each gene is represented by sequences of nucleotides. The nucleotides in a sequence of a driver gene can change which is termed as mutations. Some mutations can cause cancer. There are seven types of a gene whose mutation causes sarcoma cancer. The study uses the dataset which has been taken from more than 134 samples and includes 141 mutations in 8 driver genes. On these gene s...
International Journal of Molecular Sciences
Genes are composed of DNA and each gene has a specific sequence. Recombination or replication wit... more Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocarcinoma starts in secretary cells. Breast adenocarcinoma is the most common of all cancers that occur in women. According to a survey within the United States of America, there are more than 282,000 breast adenocarcinoma patients registered each 12 months, and most of them are women. Recognition of cancer in its early stages saves many lives. A proposed framework is developed for the early detection of breast adenocarcinoma using an ensemble learning technique with multiple deep learning algorithms, specifically: Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Bi-directional LSTM. There are 99 types of driver genes involved in breast adenocarcinoma. This study uses a dataset of 4127 samples including men and women taken fr...
Scientific Reports
Breast adenocarcinoma is the most common of all cancers that occur in women. According to the Uni... more Breast adenocarcinoma is the most common of all cancers that occur in women. According to the United States of America survey, more than 282,000 breast cancer patients are registered each year; most of them are women. Detection of cancer at its early stage saves many lives. Each cell contains the genetic code in the form of gene sequences. Changes in the gene sequences may lead to cancer. Replication and/or recombination in the gene base sometimes lead to a permanent change in the nucleotide sequence of the genome, called a mutation. Cancer driver mutations can lead to cancer. The proposed study develops a framework for the early detection of breast adenocarcinoma using machine learning techniques. Every gene has a specific sequence of nucleotides. A total of 99 genes are identified in various studies whose mutations can lead to breast adenocarcinoma. This study uses the dataset taken from 4127 human samples, including men and women from more than 12 cohorts. A total of 6170 mutatio...
2021 International Conference on Innovative Computing (ICIC), 2021
Cancer has been identified as a serious genetic disorder which cause numerous deaths every year. ... more Cancer has been identified as a serious genetic disorder which cause numerous deaths every year. Late diagnosis of cancer is one of the major cause of deaths. Mutation is the disturbance in gene sequence and mutated genes are crucial for cancer growth. This study develops a machine learning model for the solution of mutation detection problem in genes sequence which may help in diagnosing the cancer at early stages. The aim of this system is to detect the mutation in gene sequences whether it is mutated or not. To detect mutation in gene sequences, several techniques and models of machine learning has been considered such as SVM, Logistic Regression and Linear Discriminant Analysis to achieve better accuracy.
2021 International Conference on Innovative Computing (ICIC), 2021
Epidemiogical evidence has shown that tumor suppressor genes early detection can play an importan... more Epidemiogical evidence has shown that tumor suppressor genes early detection can play an important part in the management of cancer. The statistics at a glance for all over the world about the burden of cancer have proved that cancer is another principal reason of death across the globe and it is also responsible for the about 9.6 million deaths in a single year. It is perceived that about 1 out of 6 deaths across the globe is due to cancer and about 70% of the deaths are more likely to occur in low and middle income or developing countries because tumor suppressor genes are not detected on early stages. In this regard, a systematic meta-analysis is conducted for the observation of role imparted. In this regard, 50 research articles have been used for the observation of role of tumor suppressor genes and one of the really exciting things about the tumor suppressor genes which is excluded from the research involves the fact that through genes transplant, cancer can be cured if the abnormal functionality is detected in early stages of cancer.
2019 International Conference on Innovative Computing (ICIC), 2019
In the current era of Science and Technology, every kind of field enables human life to use the i... more In the current era of Science and Technology, every kind of field enables human life to use the internet in excess amount for connecting with the world. Depending completely on services of the internet creates vulnerability for their private data, which allows attackers to strike for various limits. Well-ordered net applies assembled as diverge from past web time. There are attacks on the internet of Things (IOTs) as well, which causes big security challenges. A question arises here; what methodology to use for the appropriate working of network incoming and outgoing traffic data. For this, the Intrusion Detection System (IDS) is the item pack application used to provide security. IDS is used for screen and explore the principal reason for the framework in a couple of systems. In literature, researchers use the feeble date to play out the strike against association affiliation. It provides the substance care, complete guide and concentrates concerning IDS. The fundamental goal of concerning IDS is to watch out evil traps, goods work out, threats and so on. There exist several algorithms which are used for the classification of Intrusion Detection Attacks. In this study, the classification model Logistic Regression is applied on the dataset containing attacks. The performance of the Logistic Regression algorithm is evaluated by two means and compared. Classification of attacks is made using the Logistic Regression algorithm. For evaluation, the corresponding Specificity, Accuracy, Sensitivity and MCC are calculated to evaluate the prediction framework to attain the respective True Positive, false-positive rate for both of the aforementioned algorithms. By following scheme of 10-fold and Jack-Knife, it was discovered that the Sensitivity for classifiers was 99%, Specificity 96%, Accuracy 99% and MCC 98%. IDS is each consolidated with one another to make the Brought Together Danger, the board mix presence of mind into the fundamental unit.
Alexandria Engineering Journal, 2021
Background: Cardiac tumors are an exceedingly rare phenomena. Papillary fibroelastomas are the se... more Background: Cardiac tumors are an exceedingly rare phenomena. Papillary fibroelastomas are the second most common benign cardiac tumors. Despite their propensity to cause embolic strokes and acute coronary syndrome, a major consideration is also that of symptomatic peripheral artery disease as a presentation. Case: A 77 year-old female with history of a prior transient ischemic attack and hypertension presented to the hospital with severe pain within her right great toe after undergoing partial amputation a couple of weeks prior. On physical exam, she was found to have absent pulses within the popliteal and right femoral arteries. In anticipation for further surgical intervention, pre-operative cardiac evaluation was performed with a transthoracic echocardiogram that showed an ejection fraction of 75%, no regional wall motion abnormalities, and a well defined, mobile mass within the left ventricle measuring 18x14mm. Decision-Making: Further cardiovascular evaluation was obtained, with transesophageal echocardiogram confirming the finding of a 18x12mm pedunculated mass attached to the septal wall of the left ventricle. Right lower extremity angiography revealed total occlusion of the proximal segments of the right anterior tibial and peroneal arteries, as well as a total occlusion within the distal segment of the posterior tibial artery. Due to the finding of a cardiac mass causing peripheral embolization, the decision for surgical resection was reached. Pathological examination confirmed the diagnosis of papillary fibroelastoma of the left ventricle. The patient tolerated the procedure well and made a successful recovery. Conclusions: This case highlights the importance of a complete cardiac evaluation for patients presenting with peripheral vascular disease without known risk factors. Furthermore, it reinforces the importance of the echocardiogram to identify or exclude cardiac tumors as a potential cause of peripheral embolic phenomena
Energies, 2021
Internet of Things (IoT) performs a vital role in providing connectivity between computing device... more Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and tr...
IT Professional, 2021
Machine learning techniques are proven valuable for the Internet of things (IoT) due to intellige... more Machine learning techniques are proven valuable for the Internet of things (IoT) due to intelligent and cost-effective computing processes. In recent decades, wireless sensor network (WSN) and machine learning are integrated to give significant improvements for energy-based systems. However, resourceful routes analytic with nominal energy consumption are some demanding challenges. Moreover, WSN operates in an unpredictable space and a lot of network threats can be harmful to smart and secure data gathering. Consequently, security against such threats is another major concern for low-power sensors. Therefore, we aim to present a machine learning-based approach for autonomous IoT Security to achieve optimal energy efficiency and reliable transmissions. First, the proposed protocol optimizes network performance using a model-free Q-learning algorithm and achieves fault-tolerant data transmission. Second, it accomplishes data confidentiality against adversaries using a cryptography-based deterministic algorithm. The proposed protocol demonstrates better conclusions than other existing solutions.
SMART MOVES JOURNAL IJOSCIENCE, 2019
The purpose of image enhancement and image restoration techniques is to perk up a quality and fea... more The purpose of image enhancement and image restoration techniques is to perk up a quality and feature of an image that result in improved image than the original one. Unlike the image restoration, image enhancement is the modification of an image to alter impact on the viewer. Generally enhancement distorts the original digital values; therefore enhancement is not done until the restoration processes are completed. In image enhancement the image features are extracted instead of restoration of degraded image. Image enhancement is the process in which the degraded image is handled and the appearance of the image by visual is improved. It is a subjective process and increases contrast of image but image restoration is a more objective process than image enhancement. Many research work have been done for image enhancement. In this paper, different techniques and algorithms are discussed for contrast enhancement.
International Journal of Computer Applications, 2015
Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) ... more Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
IEEE Access
Machine learning and deep learning algorithms are widely used in computer science domains. These ... more Machine learning and deep learning algorithms are widely used in computer science domains. These algorithms are mostly used for classification and regression problems in almost every field of life. Semantic segmentation is an instantly growing research topic in the last few decades that refers to the association of each pixel in the image to the class it belongs. This paper illustrates the systematic survey of advanced research in the field of semantic segmentation till date. This study provides the brief knowledge about the latest proposed methods in the domain of semantic segmentation. The proposed study comprehends the concepts, techniques, tool, and results of different research frameworks proposed in the context of semantic segmentation. This study discusses the latest research papers in which machine learning and deep learning techniques are exploited for semantic segmentation and published between 2016 and 2021. The systematic literature review collected from seven different article libraries including ACM digital Library, Google Scholar, IEEE Xplore, Science Direct, Google Books, Refseek and Worldwide Science. For assuring the quality of the paper those papers are selected which have several citations on standardized platforms. Most of the studies used COCO, PASCAL, Cityscapes and CamVid dataset for training and validation of the machine learning and deep learning models. The results of the selected research articles are collected in the form of accuracy, mIoU value, F1 score, precision, and recall. In this study, we also conclude that most of the semantic segmentation studies use ResNet as the backbone of the architecture and none of the researchers used ensemble learning methods for semantic segmentation that is the loophole of the selected studies.
VAWKUM Transactions on Computer Sciences, 2018
TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) are the most important proto... more TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) are the most important protocols in complete protocol architecture. There are many types of attacks that can block the communication or reduce the performance of a protocol. This study provides a detail analysis of TCP and UDP attacks and their application layer protocols. The authors will also suggest that where the security administrator should focus for providing best security. The old datasets such as KDD99 and NSLKDD has many limitations. This study uses UNSW-NB15 dataset which has recently been generated.
Scientific Reports, 2020
Glutamic acid is an alpha-amino acid used by all living beings in protein biosynthesis. One of th... more Glutamic acid is an alpha-amino acid used by all living beings in protein biosynthesis. One of the important glutamic acid modifications is post-translationally modified 4-carboxyglutamate. It has a significant role in blood coagulation. 4-carboxyglumates are required for the binding of calcium ions. On the contrary, this modification can also cause different diseases such as bone resorption, osteoporosis, papilloma, and plaque atherosclerosis. Considering its importance, it is necessary to predict the occurrence of glutamic acid carboxylation in amino acid stretches. As there is no computational based prediction model available to identify 4-carboxyglutamate modification, this study is, therefore, designed to predict 4-carboxyglutamate sites with a less computational cost. A machine learning model is devised with a Multilayered Perceptron (MLP) classifier using Chou’s 5-step rule. It may help in learning statistical moments and based on this learning, the prediction is to be made a...
Lahore Garrison University Research Journal of Computer Science and Information Technology
Information and Communication Technology (ICT) has revolutionized the lives of the people. The te... more Information and Communication Technology (ICT) has revolutionized the lives of the people. The technology is embedded in daily life of literate or semiliterate/illiterate users. However, the user interface (UI) requirements for semiliterate/illiterate users are different from that of an educated person. The researchers of Human Computer Interaction for Development (HCI4D) face challenges to improve the usability of a UI for the semiliterate users. Therefore, a Systematic Literature Review (SLR) is conducted to provide a set of design factors and guidelines for UI development of semiliterate users. The study is based on extensive research gathered from literature to understand the user-centered design (UCD) approach, enhancing user experience (UX) for semiliterate users. This study analyses fifty two research articles that are published during 2010-2020. The findings shed light on the systematization of UI design guidelines for semiliterate/illiterate users. These guidelines can help...
Journal of Healthcare Engineering, 2022
Facial expression is one of the most significant elements which can tell us about the mental stat... more Facial expression is one of the most significant elements which can tell us about the mental state of any person. A human can convey approximately 55% of information nonverbally and the remaining almost 45% through verbal communication. Automatic facial expression recognition is presently one of the most difficult tasks in the computer science field. Applications of facial expression recognition (FER) are not just limited to understanding human behavior and monitoring person’s mood and the mental state of humans. It is also penetrating into other fields such as criminology, holographic, smart healthcare systems, security systems, education, robotics, entertainment, and stress detection. Currently, facial expressions are playing an important role in medical sciences, particularly helping the patients with bipolar disease, whose mood changes very frequently. In this study, an algorithm, automated framework for facial detection using a convolutional neural network (FD-CNN) is proposed ...
VAWKUM Transactions on Computer Sciences
CCTV cameras are commonly used for security issues. Pan-tilt-zoom (PTZ) cameras are mostly used f... more CCTV cameras are commonly used for security issues. Pan-tilt-zoom (PTZ) cameras are mostly used for this purpose. To stitch two or more video streams from different cameras is much cheaper than PTZ solution. There are three stages of video stitching. Feature identification is the first stage of video stitching. To scale the invariant features like rotation, scaling and noise etc. Direct and feature base identification has basically two types of feature identification. Shifting and warping the images purpose to identify how these features are agreeing with each other is the main concern for direct base identification. While feature identification rely on extracting the features and then perform matching among them on the base of features. Calibration is the second stage of the video stitching. The images are stitch in panoramic way in calibration depending upon alignment among them. Blending is the last stage of video stitching where numerous videos are display in single panoramic way. Any blending algorithm is used to blend the pixels together and for final view.
VAWKUM Transactions on Computer Sciences
As the research increased in computer science highlight the scientists mind for the growing resea... more As the research increased in computer science highlight the scientists mind for the growing research world towards security. Researchers have done a lot of research work in network Security. Cybersecurity has progressively become a zone of alarm for officials, Government agencies and industries, including big commercialized infrastructure, are under attack daily. First signature-based intrusion detection systems were developed, and it detects only novel attacks. To detect strange attacks statistical IDS came into being recognized as anomaly-based IDS. It is not as much efficient as it detects all. In this, study the author focus on the efficiency of IDS using NSL-KDD99 dataset and support vector machine (SVM) technique to identify attacks. NSL-KDD dataset is used for the evaluation of these type of systems.