International Journal of Electrical and Computer Engineering (IJECE), 2021
House combustion is one of the main concerns for builders, designers, and property residents. Sin... more House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors can not measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the neces...
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to pr...
Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practic... more Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practice. Hence, herbs identification via a vision system is beneficial since the pharmacist and botanic need not to collect them through traditional ways. Thus, this paper proposed an efficient and automatic classification system to recognize Malaysian herbs that would be used in medical or cooking areas. As per the authors' knowledge, there is no evidence for similar studies on medical herbs in Malaysia. In the proposed system, we have investigated different classifiers to build an efficient classifier; then, the classifier was integrated with a mobile app to ease the real-time classification. The proposed system employed two classifiers, namely Support Vector Machine (SVM) and Deep Learning Neural Network (DLNN). The two models have been tested on our own dataset, which contains 1000 leaves. The experimental results showed that SVM achieved 74.63% recognition accuracy, and DLNN achieved 93% recognition accuracy for both the experimental model and the developed mobile app. Furthermore, the processing time was 4 seconds for SVM and 5 seconds for DLNN classifier, while the processing time using the mobile app was 2 seconds only.
The advent of social media, particularly Twitter, raises many issues due to a misunderstanding re... more The advent of social media, particularly Twitter, raises many issues due to a misunderstanding regarding the concept of freedom of speech. One of these issues is cyberbullying, which is a critical global issue that affects both individual victims and societies. Many attempts have been introduced in the literature to intervene in, prevent, or mitigate cyberbullying; however, because these attempts rely on the victims’ interactions, they are not practical. Therefore, detection of cyberbullying without the involvement of the victims is necessary. In this study, we attempted to explore this issue by compiling a global dataset of 37,373 unique tweets from Twitter. Moreover, seven machine learning classifiers were used, namely, Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), Stochastic Gradient Descent (SGD), Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB), and Support Vector Machine (SVM). Each of these algorithms was evaluated using accuracy, precision, recall, an...
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2020
The smart fitness mirror proposed in this researchaims to provide the users with a platform to mo... more The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user's body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user's body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
International Journal of Computing and Digital Systems, 2019
Library management system aims to automate the library processes throughout a collection of actio... more Library management system aims to automate the library processes throughout a collection of actions as book loan, catalogue, indexing, and recording. This paper goes one-step further in the automation of library systems by using the IoT and robot for more precise and reliable automation. In this proposed work, Pick and place robot has been integrated with GSM technology, Radio Frequency Identification (RFID) equipment, and sensory technology to enhance the robot functionality. The augmented robot, in this work, is used to automate the process of picking the library books and sending them to the borrower table. The user can control the robot movement inside library remotely using SMS commands. In this paper, redesigning the library ground was implemented to let the robot moves freely between the shelves. The experimental results showed the ability of robot to collect books with different thickness and weights from different shelf levels at different distances with accuracy up to 97.33%.
Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence... more Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence, the adoption of Blockchain is becoming an increasingly significant topic. The number of publications discussing the potential of Blockchain adoption has been expanding significantly. In addition, not enough attention has been given to Blockchain adoption in the software development industry. As a result, a systematic overview to investigate the research trends in this area is needed. This study uses a Scientometric analysis and critical review to examine the evolution of Blockchain adoption research on the Web of Science Principal Collection. In addition, a systematic literature review (SLR) was conducted to identify gaps in Blockchain adoption research and the top reasons for adopting Blockchain with the intention of proposing a sustainable adoption framework. This study extends the body of knowledge by discussing the most influential countries, authors, organizations, publication the...
Amidation is an important post translational modification where a peptide ends with an amide grou... more Amidation is an important post translational modification where a peptide ends with an amide group (–NH2) rather than carboxyl group (–COOH). These amidated peptides are less sensitive to proteolytic degradation with extended half-life in the bloodstream. Amides are used in different industries like pharmaceuticals, natural products, and biologically active compounds. The in-vivo, ex-vivo, and in-vitro identification of amidation sites is a costly and time-consuming but important task to study the physiochemical properties of amidated peptides. A less costly and efficient alternative is to supplement wet lab experiments with accurate computational models. Hence, an urgent need exists for efficient and accurate computational models to easily identify amidated sites in peptides. In this study, we present a new predictor, based on deep neural networks (DNN) and Pseudo Amino Acid Compositions (PseAAC), to learn efficient, task-specific, and effective representations for valine amidation...
Coma or unconsciousness is a state wherein the patient cannot respond to any internal or external... more Coma or unconsciousness is a state wherein the patient cannot respond to any internal or external stimulus. In this situation, the patient has no physical control over his entire body. Such cases require a serious attention and continuous monitoring to save patient's life. Currently, monitoring coma patients critically is very expensive and needs more manpower. Besides, such continuous intensive care by a paramedical assistant are error-prone, which may lead to further complications. Thus, the need for automated healthcare systems still exist. These automated systems help in continuously monitoring and recording all the vital information of a particular subject by maintaining all the comatose records. In this article, a health monitoring system for the coma patient based on the global system for mobile (GSM) and the Internet of Things (IoT) is proposed. IoT as a new technology which facilitates the process of extracting, analyzing and sending data with high efficiency. In this p...
In biological systems, Nitration is a crucial post-translational modification which occurs on var... more In biological systems, Nitration is a crucial post-translational modification which occurs on various amino acids. Nitration of Tyrosine is regarded as nitorsative stress biomarker resulting in the formation of peroxynitrite and other reactive and harmful nitrogen species. NitroTyrosine is closely related to Carcinogenesis, tumor growth progression and other major pathological conditions including systemic autoimmune diseases, inflammation, neurodegeneration and cardiovascular disorders. Additionally, the alteration in Nitrotyrosine profile occurs well before appearance of any symptoms of aforementioned diseases making nitrotyrosine a biomarker and potential target for early prognosis of aforementioned diseases. The wet lab identification of potential nitrotyrosine sites is laborious, time-taking and costly due to challenges of in vitro, ex vivo and in vivo identification processes. To supplement wet lab identification of nitrotyrosine, we proposed, implemented and evaluated a different approach to develop tyrosine nitration site predictors using pseudo amino acid compositions (PseAAC) and deep neural networks (DNNs). Proposed approach does not require any feature extraction and uses DNNs for learning a feature representation of peptide sequences and classification thereof. Validation of proposed approach is done using well-known model evaluation measures. Among different deep neural networks, convolutional neural network-based predictor achieved best scores on independent dataset with accuracy of 87.2%, matthew's correlation coefficient score of 0.74 and AuC score of 0.91 which outperforms the previous reported scores of Nitrotyrosine predictors.
IAES International Journal of Robotics and Automation (IJRA), 2021
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to provide high-quality painting without any gaps, the current speed was selected as the most suitable, without any harm to the working process.
International Journal of Electrical and Computer Engineering (IJECE), 2021
House combustion is one of the main concerns for builders, designers, and property residents. Sin... more House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors cannot measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the necessary data. Finally, the main feature of the proposed system is to minimize false alarms, which, in turn, makes this system more reliable. The experimental results showed the superiority of our model in terms of affordability, effectiveness, and responsiveness as the system uses the Ubidots platform, which makes the data exchange faster and reliable. Keywords: Fire detection system Flame sensor GSM network Internet of things Smart water system Ubidots platform This is an open access article under the CC BY-SA license.
IAES International Journal of Robotics and Automation (IJRA) , 2021
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to provide high-quality painting without any gaps, the current speed was selected as the most suitable, without any harm to the working process.
International Journal of Computing and Digital Systems, 2019
Library management system aims to automate the library processes throughout a collection of actio... more Library management system aims to automate the library processes throughout a collection of actions as book loan, catalogue, indexing, and recording. This paper goes one-step further in the automation of library systems by using the IoT and robot for more precise and reliable automation. In this proposed work, Pick and place robot has been integrated with GSM technology, Radio Frequency Identification (RFID) equipment, and sensory technology to enhance the robot functionality. The augmented robot, in this work, is used to automate the process of picking the library books and sending them to the borrower table. The user can control the robot movement inside library remotely using SMS commands. In this paper, redesigning the library ground was implemented to let the robot moves freely between the shelves. The experimental results showed the ability of robot to collect books with different thickness and weights from different shelf levels at different distances with accuracy up to 97.33%.
The smart fitness mirror proposed in this researchaims to provide the users with a platform to mo... more The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user's body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user's body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practic... more Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practice. Hence, herbs identification via a vision system is beneficial since the pharmacist and botanic need not to collect them through traditional ways. Thus, this paper proposed an efficient and automatic classification system to recognize Malaysian herbs that would be used in medical or cooking areas. As per the authors' knowledge, there is no evidence for similar studies on medical herbs in Malaysia. In the proposed system, we have investigated different classifiers to build an efficient classifier; then, the classifier was integrated with a mobile app to ease the real-time classification. The proposed system employed two classifiers, namely Support Vector Machine (SVM) and Deep Learning Neural Network (DLNN). The two models have been tested on our own dataset, which contains 1000 leaves. The experimental results showed that SVM achieved 74.63% recognition accuracy, and DLNN achieved 93% recognition accuracy for both the experimental model and the developed mobile app. Furthermore, the processing time was 4 seconds for SVM and 5 seconds for DLNN classifier, while the processing time using the mobile app was 2 seconds only.
The advent of social media, particularly Twitter, raises many issues due to a misunderstanding re... more The advent of social media, particularly Twitter, raises many issues due to a misunderstanding regarding the concept of freedom of speech. One of these issues is cyberbullying, which is a critical global issue that affects both individual victims and societies. Many attempts have been introduced in the literature to intervene in, prevent, or mitigate cyberbullying; however, because these attempts rely on the victims' interactions, they are practical. Therefore, detection of cyberbullying without the involvement of the victims is necessary. In this study, we attempted to explore this issue by compiling a global dataset of 37,373 unique tweets from Twitter. Moreover, seven machine learning classifiers were used, namely, Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), Stochastic Gradient Descent (SGD), Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB), and Support Vector Machine (SVM). Each of these algorithms was evaluated using accuracy, precision, recall, and F1 score as the performance metrics to determine the classifiers' recognition rates applied to the global dataset. The experimental results show the superiority of LR, which achieved a median accuracy of around 90.57%. Among the classifiers, logistic regression achieved the best F1 score (0.928), SGD achieved the best precision (0.968), and SVM achieved the best recall (1.00).
International Journal of Electrical and Computer Engineering (IJECE), 2021
House combustion is one of the main concerns for builders, designers, and property residents. Sin... more House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors can not measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the neces...
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to pr...
Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practic... more Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practice. Hence, herbs identification via a vision system is beneficial since the pharmacist and botanic need not to collect them through traditional ways. Thus, this paper proposed an efficient and automatic classification system to recognize Malaysian herbs that would be used in medical or cooking areas. As per the authors' knowledge, there is no evidence for similar studies on medical herbs in Malaysia. In the proposed system, we have investigated different classifiers to build an efficient classifier; then, the classifier was integrated with a mobile app to ease the real-time classification. The proposed system employed two classifiers, namely Support Vector Machine (SVM) and Deep Learning Neural Network (DLNN). The two models have been tested on our own dataset, which contains 1000 leaves. The experimental results showed that SVM achieved 74.63% recognition accuracy, and DLNN achieved 93% recognition accuracy for both the experimental model and the developed mobile app. Furthermore, the processing time was 4 seconds for SVM and 5 seconds for DLNN classifier, while the processing time using the mobile app was 2 seconds only.
The advent of social media, particularly Twitter, raises many issues due to a misunderstanding re... more The advent of social media, particularly Twitter, raises many issues due to a misunderstanding regarding the concept of freedom of speech. One of these issues is cyberbullying, which is a critical global issue that affects both individual victims and societies. Many attempts have been introduced in the literature to intervene in, prevent, or mitigate cyberbullying; however, because these attempts rely on the victims’ interactions, they are not practical. Therefore, detection of cyberbullying without the involvement of the victims is necessary. In this study, we attempted to explore this issue by compiling a global dataset of 37,373 unique tweets from Twitter. Moreover, seven machine learning classifiers were used, namely, Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), Stochastic Gradient Descent (SGD), Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB), and Support Vector Machine (SVM). Each of these algorithms was evaluated using accuracy, precision, recall, an...
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2020
The smart fitness mirror proposed in this researchaims to provide the users with a platform to mo... more The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user's body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user's body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
International Journal of Computing and Digital Systems, 2019
Library management system aims to automate the library processes throughout a collection of actio... more Library management system aims to automate the library processes throughout a collection of actions as book loan, catalogue, indexing, and recording. This paper goes one-step further in the automation of library systems by using the IoT and robot for more precise and reliable automation. In this proposed work, Pick and place robot has been integrated with GSM technology, Radio Frequency Identification (RFID) equipment, and sensory technology to enhance the robot functionality. The augmented robot, in this work, is used to automate the process of picking the library books and sending them to the borrower table. The user can control the robot movement inside library remotely using SMS commands. In this paper, redesigning the library ground was implemented to let the robot moves freely between the shelves. The experimental results showed the ability of robot to collect books with different thickness and weights from different shelf levels at different distances with accuracy up to 97.33%.
Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence... more Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence, the adoption of Blockchain is becoming an increasingly significant topic. The number of publications discussing the potential of Blockchain adoption has been expanding significantly. In addition, not enough attention has been given to Blockchain adoption in the software development industry. As a result, a systematic overview to investigate the research trends in this area is needed. This study uses a Scientometric analysis and critical review to examine the evolution of Blockchain adoption research on the Web of Science Principal Collection. In addition, a systematic literature review (SLR) was conducted to identify gaps in Blockchain adoption research and the top reasons for adopting Blockchain with the intention of proposing a sustainable adoption framework. This study extends the body of knowledge by discussing the most influential countries, authors, organizations, publication the...
Amidation is an important post translational modification where a peptide ends with an amide grou... more Amidation is an important post translational modification where a peptide ends with an amide group (–NH2) rather than carboxyl group (–COOH). These amidated peptides are less sensitive to proteolytic degradation with extended half-life in the bloodstream. Amides are used in different industries like pharmaceuticals, natural products, and biologically active compounds. The in-vivo, ex-vivo, and in-vitro identification of amidation sites is a costly and time-consuming but important task to study the physiochemical properties of amidated peptides. A less costly and efficient alternative is to supplement wet lab experiments with accurate computational models. Hence, an urgent need exists for efficient and accurate computational models to easily identify amidated sites in peptides. In this study, we present a new predictor, based on deep neural networks (DNN) and Pseudo Amino Acid Compositions (PseAAC), to learn efficient, task-specific, and effective representations for valine amidation...
Coma or unconsciousness is a state wherein the patient cannot respond to any internal or external... more Coma or unconsciousness is a state wherein the patient cannot respond to any internal or external stimulus. In this situation, the patient has no physical control over his entire body. Such cases require a serious attention and continuous monitoring to save patient's life. Currently, monitoring coma patients critically is very expensive and needs more manpower. Besides, such continuous intensive care by a paramedical assistant are error-prone, which may lead to further complications. Thus, the need for automated healthcare systems still exist. These automated systems help in continuously monitoring and recording all the vital information of a particular subject by maintaining all the comatose records. In this article, a health monitoring system for the coma patient based on the global system for mobile (GSM) and the Internet of Things (IoT) is proposed. IoT as a new technology which facilitates the process of extracting, analyzing and sending data with high efficiency. In this p...
In biological systems, Nitration is a crucial post-translational modification which occurs on var... more In biological systems, Nitration is a crucial post-translational modification which occurs on various amino acids. Nitration of Tyrosine is regarded as nitorsative stress biomarker resulting in the formation of peroxynitrite and other reactive and harmful nitrogen species. NitroTyrosine is closely related to Carcinogenesis, tumor growth progression and other major pathological conditions including systemic autoimmune diseases, inflammation, neurodegeneration and cardiovascular disorders. Additionally, the alteration in Nitrotyrosine profile occurs well before appearance of any symptoms of aforementioned diseases making nitrotyrosine a biomarker and potential target for early prognosis of aforementioned diseases. The wet lab identification of potential nitrotyrosine sites is laborious, time-taking and costly due to challenges of in vitro, ex vivo and in vivo identification processes. To supplement wet lab identification of nitrotyrosine, we proposed, implemented and evaluated a different approach to develop tyrosine nitration site predictors using pseudo amino acid compositions (PseAAC) and deep neural networks (DNNs). Proposed approach does not require any feature extraction and uses DNNs for learning a feature representation of peptide sequences and classification thereof. Validation of proposed approach is done using well-known model evaluation measures. Among different deep neural networks, convolutional neural network-based predictor achieved best scores on independent dataset with accuracy of 87.2%, matthew's correlation coefficient score of 0.74 and AuC score of 0.91 which outperforms the previous reported scores of Nitrotyrosine predictors.
IAES International Journal of Robotics and Automation (IJRA), 2021
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to provide high-quality painting without any gaps, the current speed was selected as the most suitable, without any harm to the working process.
International Journal of Electrical and Computer Engineering (IJECE), 2021
House combustion is one of the main concerns for builders, designers, and property residents. Sin... more House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors cannot measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the necessary data. Finally, the main feature of the proposed system is to minimize false alarms, which, in turn, makes this system more reliable. The experimental results showed the superiority of our model in terms of affordability, effectiveness, and responsiveness as the system uses the Ubidots platform, which makes the data exchange faster and reliable. Keywords: Fire detection system Flame sensor GSM network Internet of things Smart water system Ubidots platform This is an open access article under the CC BY-SA license.
IAES International Journal of Robotics and Automation (IJRA) , 2021
Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation... more Wall painting is a repetitive, stressful, and hazardous process that makes it an ideal automation case. In the automotive industry, painting had been automated but not yet for the construction industry. However, there is a strong need for a mobile robot that can move to paint residential interior walls. In this study, we aim to design and implement an automatic painting mobile robot. The conceptual design of the proposed wall painting robot consisting paint mechanism with a spray gun and ultrasonic sensor. The spray gun is attached to a pulley mechanism that has linear motion. The ultrasonic sensor is used to detect the spray gun when it reached a certain limit. The DC motor rotates clockwise and counterclockwise based on the ultrasonic sensor condition made. The experimental results indicate that the robot was able to paint the walls smoothly vertically, and horizontally. The spraying gun structure's speed is at a tolerable speed of 0.07 m/s, which could be increased, but to provide high-quality painting without any gaps, the current speed was selected as the most suitable, without any harm to the working process.
International Journal of Computing and Digital Systems, 2019
Library management system aims to automate the library processes throughout a collection of actio... more Library management system aims to automate the library processes throughout a collection of actions as book loan, catalogue, indexing, and recording. This paper goes one-step further in the automation of library systems by using the IoT and robot for more precise and reliable automation. In this proposed work, Pick and place robot has been integrated with GSM technology, Radio Frequency Identification (RFID) equipment, and sensory technology to enhance the robot functionality. The augmented robot, in this work, is used to automate the process of picking the library books and sending them to the borrower table. The user can control the robot movement inside library remotely using SMS commands. In this paper, redesigning the library ground was implemented to let the robot moves freely between the shelves. The experimental results showed the ability of robot to collect books with different thickness and weights from different shelf levels at different distances with accuracy up to 97.33%.
The smart fitness mirror proposed in this researchaims to provide the users with a platform to mo... more The smart fitness mirror proposed in this researchaims to provide the users with a platform to monitor their health and fitness status on a daily basis. The system employs a number of sensors to monitor the body mass index (BMI) and amount of body fat present in the user's body. A weight scale consisting of four load sensors has been implemented to obtain the weight of the user whereas an ultrasonic sensor has been used to measure the height of the user. In addition, four electrode plates have been implemented on the foot weight scale to infuse a small amount of electric current (1mA) for BIA (bioelectrical impedance analysis) to estimate the amount of body fat percentage, lean body mass and total body water. An IR temperature sensor has been implemented in the research to measure the temperature of the user's body from the forehead. Tests conducted on the system illustrate that it is able to accurately compute the body mass index and perform a bioelectrical impedance analysis on the user. The system is able to achieve a 92.5 % and 93.7 % accuracy in determining the body mass index and body fat percentage respectively. An accuracy of 95.3 % was observed in the determination of the body temperature.
Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practic... more Recognizing the desired herb among thousands of herbs is an exhausting and time-consuming practice. Hence, herbs identification via a vision system is beneficial since the pharmacist and botanic need not to collect them through traditional ways. Thus, this paper proposed an efficient and automatic classification system to recognize Malaysian herbs that would be used in medical or cooking areas. As per the authors' knowledge, there is no evidence for similar studies on medical herbs in Malaysia. In the proposed system, we have investigated different classifiers to build an efficient classifier; then, the classifier was integrated with a mobile app to ease the real-time classification. The proposed system employed two classifiers, namely Support Vector Machine (SVM) and Deep Learning Neural Network (DLNN). The two models have been tested on our own dataset, which contains 1000 leaves. The experimental results showed that SVM achieved 74.63% recognition accuracy, and DLNN achieved 93% recognition accuracy for both the experimental model and the developed mobile app. Furthermore, the processing time was 4 seconds for SVM and 5 seconds for DLNN classifier, while the processing time using the mobile app was 2 seconds only.
The advent of social media, particularly Twitter, raises many issues due to a misunderstanding re... more The advent of social media, particularly Twitter, raises many issues due to a misunderstanding regarding the concept of freedom of speech. One of these issues is cyberbullying, which is a critical global issue that affects both individual victims and societies. Many attempts have been introduced in the literature to intervene in, prevent, or mitigate cyberbullying; however, because these attempts rely on the victims' interactions, they are practical. Therefore, detection of cyberbullying without the involvement of the victims is necessary. In this study, we attempted to explore this issue by compiling a global dataset of 37,373 unique tweets from Twitter. Moreover, seven machine learning classifiers were used, namely, Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), Stochastic Gradient Descent (SGD), Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB), and Support Vector Machine (SVM). Each of these algorithms was evaluated using accuracy, precision, recall, and F1 score as the performance metrics to determine the classifiers' recognition rates applied to the global dataset. The experimental results show the superiority of LR, which achieved a median accuracy of around 90.57%. Among the classifiers, logistic regression achieved the best F1 score (0.928), SGD achieved the best precision (0.968), and SVM achieved the best recall (1.00).
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Papers by Amgad Moneer