Dr. Ali Abd Almisreb received his Bachelor in Computer Engineering from IPU University, Syria, in 2008, and Master in Computer Science from University Teknologi Mara (UiTM), Malaysia, in 2012. Dr. Ali received his PhD in Electrical Engineering from University Teknologi Mara (UiTM), Malaysia, in 2016. He also received the Best Research Student Award (APC). He was working as a Robotics Engineer at Robopreneur Sdn Bhd. His work includes NAO programming and integration of NAO with IBM Bluemix and Watson. His expertizes are robotics programming, image and speech recognition, advanced computing and IoT. Currently, he is working as a researcher at Universiti Tenaga Nasional. work scope includes satellite image processing, deep learning using Matlab and Tensorflow. Phone: +60179915290 Address: UiTM , MALAYSIA
Transfer Learning is an efficient platform to solve problems with little amount of data. In this ... more Transfer Learning is an efficient platform to solve problems with little amount of data. In this paper, the performance of three well-known Convolution Neural Network (CNN)-based learning model that are AlexNet, VGG16 and VGG19 for human identification based on ear images are compared. The respective convolution neural networks (CNNs) are fine-tuned to customize it to the ear images dataset. The last fully connected later is replaced with another fully connected layer to recognize 10 classes instead of 1000 classes. A total of 3,000 ear images are captured and augmented from 10 male subjects aged between 18 to 27 years old. To train the fine-tuned CNN-based networks, 2,500 images are used and the remaining 500 image are allocated for validation. The proposed fine-tuned CNN-based networks performed well in ear recognition as validation accuracy achieved 100% for all 10 male subjects.
2019 IEEE 9th International Conference on System Engineering and Technology (ICSET)
Transfer learning is highly recommended in image recognition studies due to its ability in levera... more Transfer learning is highly recommended in image recognition studies due to its ability in leveraging the finest architecture of pre-trained convolution neural networks (CNNs) for instance AlexNet, GoogLeNet and several others in learning new dataset at a faster learning process with smaller input images and could yield better classification rate as well. Hence, this study discussed deep learning with transfer learning approach in recognizing and classifying normal behavior and anomalous behavior referring to housebreaking crime behavior at the gate of the residential unit. Firstly, the dataset of normal behavior and housebreaking crime behavior are acquired. Next, these images are extracted and classified using remodeled AlexNet and GoogLeNet that have been fine-tuned using transfer learning technique. Results attained showed that the classification accuracy for both AlexNet and GoogLeNet are within 97%.
Coral reefs are organisms that mainly inhabit marine ecosystem. The formation of coral reefs are ... more Coral reefs are organisms that mainly inhabit marine ecosystem. The formation of coral reefs are due to the symbiotic relationship between algae and coral animals and coral reefs have become an important element to the marine community. Coral reefs not only provides a shelter for coastal fishes and crustacean, but also protects and supply food to them. Reefs community are also useful to human that depends on marine products for their daily income. Other than that, coral reefs are one of the major attraction to tourist due to the various species of marine organisms that can be found there. The monitoring of coral reefs types, community size and health are important to ensure the ecosystem are continuous. Several attempts had been conducted to efficiently classify significant characteristics of coral reefs. The techniques used to monitor the coral reefs include on-site and remotely-sensed. All of the techniques developed have their own beneficial values and different methods are suita...
One way for analysis of vowels in any language is an analysis using formant frequency analysis. T... more One way for analysis of vowels in any language is an analysis using formant frequency analysis. The Bosnian language has five vowels and those are a, e, i, o, u. The research was conducted in such a way that words with a minimum of two identical vowels per word were selected for each vowel. Several samples were then collected that recorded each of the words, and then those words were analyzed in PRAAT software. The total number of samples was 1050, twenty-one subjects were included, twelve females and nine males. Each of them recorded ten words for each of five vowels, therefore fifty words by each subject. The outcomes are based on related articles and dissertations, recognition, and analysis of vowels. Recognition was based on the statement, reading the literature, that each person has a narrow band of F4 formant values that should identify the person. And the analysis part was done by comparing formant values. Also, the work was based on gender differences for this analysis, as w...
Periodicals of Engineering and Natural Sciences (PEN), 2021
Examine the reliability and validity of smartwatches measuring heart rate and Blood Pressure. Met... more Examine the reliability and validity of smartwatches measuring heart rate and Blood Pressure. Methods: Eighty-eight healthy participant is recruited to be measured heart rate and Blood Pressure. the reliability and validity were determined by comparing the smart-watches with the home standard Blood Pressure using mean differences, Bland Altman plot, Interclass correlation (ICC) and Cronbach's alpha. Results: the reliability varied with ICC ranging from 0.533 to 0.852. Two smartwatches showed relatively weak ICC and broad limits of agreement of the Bland–Altman plots at both, heart rate and Blood Pressure Measurement. For heart rate measurement, F1 Smartband Bracelet Watch showed slightly better results than Y2 Plus Smart Wrist Band. conversely, Y2 Plus Smart Wrist Band demonstrated the best accuracy at Systolic measurement. And for Diastolic Blood Pressure was relatively the same in the reliability and validity. Conclusion: reliability and validity of smartwatches use, especiall...
The paper reviews the usage, development and keystroke dynamics as a viable authentication system... more The paper reviews the usage, development and keystroke dynamics as a viable authentication system. AI methods are advancing, but we are still lacking biometric authentication systems in modern software which is being used daily. This paper shows the usage of long short term memory layers for solving problems like keystroke dynamics and efficiently shows that with modern hardware, training and maintaining a small model is not taxing on the resources, as it may have been.
In accordance with the advancement in robotics and the scholarly literature, the extents of utili... more In accordance with the advancement in robotics and the scholarly literature, the extents of utilizing robots for autistic children are widened and could be a promising method for individual with Autism Spectrum Disorder (ASD) treatments, where the different form of robot (humanoid, non-humanoid, animal-like, toy, and kits) can be employed effectively as a support tool to augment the learning skills and rehabilitate of the individual with Autism Spectrum Disorder (ASD). Thus, the robots were exploited for ASD children in different aspects namely; modelling, teaching, and skills practicing; testing, highlighting and evaluating; providing feedback or encouragement; join Attention; eliciting social behaviours; emotion recognition and expression; imitation; vocalization; turn-taking; and diagnostic. The related literature published recently in journals and conferences is taken into account. In this paper, we review the use of robots that help in the therapy of individuals with Autism Spe...
2020 14th International Conference on Innovations in Information Technology (IIT), 2020
In this paper, we utilize the concept of transfer learning in fruits and vegetable quality assess... more In this paper, we utilize the concept of transfer learning in fruits and vegetable quality assessment. The transfer learning concept applies the idea of reuse the pre-trained Convolutional Neural Network to solve a new problem without the need for large-scale datasets for training. Eight pre-trained deep learning models namely AlexNet, GoogleNet, ResNet18, ResNet50, ResNet101, Vgg16, Vgg19, and NasNetMobile are fine-tuned accordingly to evaluate the quality of fruits and vegetable. To evaluate the training and validation performance of each fine-tuned model, we collect a dataset consists of images from 12 fruits and vegetable samples. The dataset builds over five weeks. For every week 70 images collected therefore the total number of images over five weeks is 350 and the total number of images in the dataset is (12*350) 4200 images. The overall number of classes in the dataset is (12*5) 60 classes. The evaluation of the models was conducted based on this dataset and also based on an...
Transfer learning is highly recommended in image recognition studies due to its ability in levera... more Transfer learning is highly recommended in image recognition studies due to its ability in leveraging the finest architecture of pre-trained convolution neural networks (CNNs) for instance AlexNet, GoogLeNet and several others in learning new dataset at a faster learning process with smaller input images and could yield better classification rate as well. Hence, this study discussed deep learning with transfer learning approach in recognizing and classifying normal behavior and anomalous behavior referring to housebreaking crime behavior at the gate of the residential unit. Firstly, the dataset of normal behavior and housebreaking crime behavior are acquired. Next, these images are extracted and classified using remodeled AlexNet and GoogLeNet that have been fine-tuned using transfer learning technique. Results attained showed that the classification accuracy for both AlexNet and GoogLeNet are within 97%.
In this paper the utilization of transferred deep learning techniques for transmission tower imag... more In this paper the utilization of transferred deep learning techniques for transmission tower image classification is investigated using Alexnet and Googlenet. The database upon fine tuning of the overall images is acquired from Google Earth and internet totaling to 1300 images specifically 650 are images of transmission tower whilst another 650 images are non-transmission tower. Here, 600 images are chosen at random as the training dataset for fine-tuned deep learning neural networks and the balance namely 50 images are used for validation. The same dataset is used as input to both networks. In addition, both networks own similar training setting too. Results attained showed that Alexnet and Googlenet are capable to perform this classification task with perfect classification by Alexnet specifically 100% while Google obtained 99% accuracy rate. As for computational performance, Googlenet performed faster as compared to Alexnet with 787 minutes by Googlenet versus 853 minutes by Alex...
Nowadays, it is a crucial to develop a monitoring system to detect faulties in machines as it hel... more Nowadays, it is a crucial to develop a monitoring system to detect faulties in machines as it helps to prevent high maintenance costs, prolong the lifetime of the machines as well as prevent production lost. This study has been motivated by the increasing number of machine failure, which has become an oustanding issue in the industries. In this study, infrared thermal camera has been employed as an instrument to identify and analyze thermal anomalies, so that the information of the machine condition can be analyzed effectively. Infrared thermal camera is one of the most efficient testing approaches and it is known as non-destructive technique for fast detection. This paper also discussed a review of the previous work regarding the different thermal imaging approach for induction motor fault detection. In this work, Histogram-based approach was used to classify the healthy and unhealthy bearing variation temperature behavior of a three-phase induction motor. Eventually, the analysis ...
One of the advantages of transfer learning technique is its capability to learn new dataset using... more One of the advantages of transfer learning technique is its capability to learn new dataset using its finest pre-trained architecture. Other advantages of this technique are small dataset requirements along with faster learning process that could yield high accuracy results. Hence in this paper, anomalous gait detection or also known as forensic gait during housebreaking crime at the gate of residential units is discussed with transfer learning technique based on five popular pre-trained convolution neural networks (CNNs) as classifiers. High accuracy and sensitivity are achieved from remodeled of the pre-trained CNNs for the learning process, offline test, and real-time test. The accuracy attained from remodeled of the pre-trained CNNs have pledged high potential towards developing the forensic intelligent surveillance technique.
Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel c... more Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel cause difficulties for the non-native Arabic speakers, particularly the Malay speakers, to pronounce these letters correctly. Hence, in this thesis, noise reduction and consonants recognition are conducted among the Malay speakers. The Malay race has been chosen due to the high usage of the Arabic language for reciting Al-Quran. Generally, the study is divided into two parts, namely, the study of noise reduction and consonant recognition. First, two noise removal methods were developed. The first method is based on combining Negative function with Gamma correction function. The second noise reduction method is addressed by utilising 2D Gabor filter. Furthermore, the consonant study was conducted based on Automatic Speech Recognition (ASR) system concept. The ASR composes of feature extraction stage followed by speech recognition. On the other hand, the feature extraction was implemented b...
A binary grammar is a relational grammar with two nonterminal alphabets, two terminal alphabets, ... more A binary grammar is a relational grammar with two nonterminal alphabets, two terminal alphabets, a set of pairs of productions and the pair of the initial nonterminals that generates the binary relation, i.e., the set of pairs of strings over the terminal alphabets. This paper investigates the binary context-free grammars as mutually controlled grammars: two context-free grammars generate strings imposing restrictions on selecting production rules to be applied in derivations. The paper shows that binary context-free grammars can generate matrix languages whereas binary regular and linear grammars have the same power as Chomskyan regular and linear grammars.
Sustainable Engineering and Innovation, ISSN 2712-0562
The previous existing mobile technologies were only limited to voice and short messages, organize... more The previous existing mobile technologies were only limited to voice and short messages, organized between several network operators and service providers. However, recent advancements in technologies, introduction, and development of the smartphones added many features such: high-speed processors, huge memory, multitasking, screens with large-resolution, utile communication hardware, and so on. Mobile devices were evolving into general-purpose computers, which resulted in the development of various technological platforms, operating systems, and platforms for the development of the applications. All these results in the occurrence of various competitive offers on the market. The above-mentioned features, processing speed and applications available on mobile devices are affected by underlying operating systems. In this paper, there will be discussed the mobile operating systems and application development platforms.
Sustainable Engineering and Innovation, ISSN 2712-0562
Internet of Things (IoT) paradigm became particularly popular in the last couple of years in such... more Internet of Things (IoT) paradigm became particularly popular in the last couple of years in such a way that the devices are present in almost every home across the globe. Using cheap components one can connect any device to the internet and enable information collecting from the environment, making everyday life a lot easier. Even though it does bring multiple advantages to the table, at the same time it brings certain challenges and vulnerabilities that need to be addressed. In this paper we focus on Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks and we provide a review of the current architecture of Internet of Things which is prone to these.
Indonesian Journal of Electrical Engineering and Computer Science
This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with com... more This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with complementary split ring resonator (CSRR) for radio frequency identification (RFID). The total size of the antenna is 208 × 208 × 1.6 mm3. The proposed antenna is designed, fabricated and measured in order to verify the proposed concept. The characterization for radiation parameters, like return loss, radiation pattern and antenna gain have been done experimentally. The proposed antenna is operated at 921 MHz for and achieved a gain of 8.285 dBi. All simulations in this work have been carried out by means of the commercial computer simulation technology (CST) software. In compare to the simulated results, the measured outcomes are promised.
Transfer Learning is an efficient platform to solve problems with little amount of data. In this ... more Transfer Learning is an efficient platform to solve problems with little amount of data. In this paper, the performance of three well-known Convolution Neural Network (CNN)-based learning model that are AlexNet, VGG16 and VGG19 for human identification based on ear images are compared. The respective convolution neural networks (CNNs) are fine-tuned to customize it to the ear images dataset. The last fully connected later is replaced with another fully connected layer to recognize 10 classes instead of 1000 classes. A total of 3,000 ear images are captured and augmented from 10 male subjects aged between 18 to 27 years old. To train the fine-tuned CNN-based networks, 2,500 images are used and the remaining 500 image are allocated for validation. The proposed fine-tuned CNN-based networks performed well in ear recognition as validation accuracy achieved 100% for all 10 male subjects.
2019 IEEE 9th International Conference on System Engineering and Technology (ICSET)
Transfer learning is highly recommended in image recognition studies due to its ability in levera... more Transfer learning is highly recommended in image recognition studies due to its ability in leveraging the finest architecture of pre-trained convolution neural networks (CNNs) for instance AlexNet, GoogLeNet and several others in learning new dataset at a faster learning process with smaller input images and could yield better classification rate as well. Hence, this study discussed deep learning with transfer learning approach in recognizing and classifying normal behavior and anomalous behavior referring to housebreaking crime behavior at the gate of the residential unit. Firstly, the dataset of normal behavior and housebreaking crime behavior are acquired. Next, these images are extracted and classified using remodeled AlexNet and GoogLeNet that have been fine-tuned using transfer learning technique. Results attained showed that the classification accuracy for both AlexNet and GoogLeNet are within 97%.
Coral reefs are organisms that mainly inhabit marine ecosystem. The formation of coral reefs are ... more Coral reefs are organisms that mainly inhabit marine ecosystem. The formation of coral reefs are due to the symbiotic relationship between algae and coral animals and coral reefs have become an important element to the marine community. Coral reefs not only provides a shelter for coastal fishes and crustacean, but also protects and supply food to them. Reefs community are also useful to human that depends on marine products for their daily income. Other than that, coral reefs are one of the major attraction to tourist due to the various species of marine organisms that can be found there. The monitoring of coral reefs types, community size and health are important to ensure the ecosystem are continuous. Several attempts had been conducted to efficiently classify significant characteristics of coral reefs. The techniques used to monitor the coral reefs include on-site and remotely-sensed. All of the techniques developed have their own beneficial values and different methods are suita...
One way for analysis of vowels in any language is an analysis using formant frequency analysis. T... more One way for analysis of vowels in any language is an analysis using formant frequency analysis. The Bosnian language has five vowels and those are a, e, i, o, u. The research was conducted in such a way that words with a minimum of two identical vowels per word were selected for each vowel. Several samples were then collected that recorded each of the words, and then those words were analyzed in PRAAT software. The total number of samples was 1050, twenty-one subjects were included, twelve females and nine males. Each of them recorded ten words for each of five vowels, therefore fifty words by each subject. The outcomes are based on related articles and dissertations, recognition, and analysis of vowels. Recognition was based on the statement, reading the literature, that each person has a narrow band of F4 formant values that should identify the person. And the analysis part was done by comparing formant values. Also, the work was based on gender differences for this analysis, as w...
Periodicals of Engineering and Natural Sciences (PEN), 2021
Examine the reliability and validity of smartwatches measuring heart rate and Blood Pressure. Met... more Examine the reliability and validity of smartwatches measuring heart rate and Blood Pressure. Methods: Eighty-eight healthy participant is recruited to be measured heart rate and Blood Pressure. the reliability and validity were determined by comparing the smart-watches with the home standard Blood Pressure using mean differences, Bland Altman plot, Interclass correlation (ICC) and Cronbach's alpha. Results: the reliability varied with ICC ranging from 0.533 to 0.852. Two smartwatches showed relatively weak ICC and broad limits of agreement of the Bland–Altman plots at both, heart rate and Blood Pressure Measurement. For heart rate measurement, F1 Smartband Bracelet Watch showed slightly better results than Y2 Plus Smart Wrist Band. conversely, Y2 Plus Smart Wrist Band demonstrated the best accuracy at Systolic measurement. And for Diastolic Blood Pressure was relatively the same in the reliability and validity. Conclusion: reliability and validity of smartwatches use, especiall...
The paper reviews the usage, development and keystroke dynamics as a viable authentication system... more The paper reviews the usage, development and keystroke dynamics as a viable authentication system. AI methods are advancing, but we are still lacking biometric authentication systems in modern software which is being used daily. This paper shows the usage of long short term memory layers for solving problems like keystroke dynamics and efficiently shows that with modern hardware, training and maintaining a small model is not taxing on the resources, as it may have been.
In accordance with the advancement in robotics and the scholarly literature, the extents of utili... more In accordance with the advancement in robotics and the scholarly literature, the extents of utilizing robots for autistic children are widened and could be a promising method for individual with Autism Spectrum Disorder (ASD) treatments, where the different form of robot (humanoid, non-humanoid, animal-like, toy, and kits) can be employed effectively as a support tool to augment the learning skills and rehabilitate of the individual with Autism Spectrum Disorder (ASD). Thus, the robots were exploited for ASD children in different aspects namely; modelling, teaching, and skills practicing; testing, highlighting and evaluating; providing feedback or encouragement; join Attention; eliciting social behaviours; emotion recognition and expression; imitation; vocalization; turn-taking; and diagnostic. The related literature published recently in journals and conferences is taken into account. In this paper, we review the use of robots that help in the therapy of individuals with Autism Spe...
2020 14th International Conference on Innovations in Information Technology (IIT), 2020
In this paper, we utilize the concept of transfer learning in fruits and vegetable quality assess... more In this paper, we utilize the concept of transfer learning in fruits and vegetable quality assessment. The transfer learning concept applies the idea of reuse the pre-trained Convolutional Neural Network to solve a new problem without the need for large-scale datasets for training. Eight pre-trained deep learning models namely AlexNet, GoogleNet, ResNet18, ResNet50, ResNet101, Vgg16, Vgg19, and NasNetMobile are fine-tuned accordingly to evaluate the quality of fruits and vegetable. To evaluate the training and validation performance of each fine-tuned model, we collect a dataset consists of images from 12 fruits and vegetable samples. The dataset builds over five weeks. For every week 70 images collected therefore the total number of images over five weeks is 350 and the total number of images in the dataset is (12*350) 4200 images. The overall number of classes in the dataset is (12*5) 60 classes. The evaluation of the models was conducted based on this dataset and also based on an...
Transfer learning is highly recommended in image recognition studies due to its ability in levera... more Transfer learning is highly recommended in image recognition studies due to its ability in leveraging the finest architecture of pre-trained convolution neural networks (CNNs) for instance AlexNet, GoogLeNet and several others in learning new dataset at a faster learning process with smaller input images and could yield better classification rate as well. Hence, this study discussed deep learning with transfer learning approach in recognizing and classifying normal behavior and anomalous behavior referring to housebreaking crime behavior at the gate of the residential unit. Firstly, the dataset of normal behavior and housebreaking crime behavior are acquired. Next, these images are extracted and classified using remodeled AlexNet and GoogLeNet that have been fine-tuned using transfer learning technique. Results attained showed that the classification accuracy for both AlexNet and GoogLeNet are within 97%.
In this paper the utilization of transferred deep learning techniques for transmission tower imag... more In this paper the utilization of transferred deep learning techniques for transmission tower image classification is investigated using Alexnet and Googlenet. The database upon fine tuning of the overall images is acquired from Google Earth and internet totaling to 1300 images specifically 650 are images of transmission tower whilst another 650 images are non-transmission tower. Here, 600 images are chosen at random as the training dataset for fine-tuned deep learning neural networks and the balance namely 50 images are used for validation. The same dataset is used as input to both networks. In addition, both networks own similar training setting too. Results attained showed that Alexnet and Googlenet are capable to perform this classification task with perfect classification by Alexnet specifically 100% while Google obtained 99% accuracy rate. As for computational performance, Googlenet performed faster as compared to Alexnet with 787 minutes by Googlenet versus 853 minutes by Alex...
Nowadays, it is a crucial to develop a monitoring system to detect faulties in machines as it hel... more Nowadays, it is a crucial to develop a monitoring system to detect faulties in machines as it helps to prevent high maintenance costs, prolong the lifetime of the machines as well as prevent production lost. This study has been motivated by the increasing number of machine failure, which has become an oustanding issue in the industries. In this study, infrared thermal camera has been employed as an instrument to identify and analyze thermal anomalies, so that the information of the machine condition can be analyzed effectively. Infrared thermal camera is one of the most efficient testing approaches and it is known as non-destructive technique for fast detection. This paper also discussed a review of the previous work regarding the different thermal imaging approach for induction motor fault detection. In this work, Histogram-based approach was used to classify the healthy and unhealthy bearing variation temperature behavior of a three-phase induction motor. Eventually, the analysis ...
One of the advantages of transfer learning technique is its capability to learn new dataset using... more One of the advantages of transfer learning technique is its capability to learn new dataset using its finest pre-trained architecture. Other advantages of this technique are small dataset requirements along with faster learning process that could yield high accuracy results. Hence in this paper, anomalous gait detection or also known as forensic gait during housebreaking crime at the gate of residential units is discussed with transfer learning technique based on five popular pre-trained convolution neural networks (CNNs) as classifiers. High accuracy and sensitivity are achieved from remodeled of the pre-trained CNNs for the learning process, offline test, and real-time test. The accuracy attained from remodeled of the pre-trained CNNs have pledged high potential towards developing the forensic intelligent surveillance technique.
Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel c... more Arabic phonemes can be categorised into 28 consonants. The variations in each phoneme and vowel cause difficulties for the non-native Arabic speakers, particularly the Malay speakers, to pronounce these letters correctly. Hence, in this thesis, noise reduction and consonants recognition are conducted among the Malay speakers. The Malay race has been chosen due to the high usage of the Arabic language for reciting Al-Quran. Generally, the study is divided into two parts, namely, the study of noise reduction and consonant recognition. First, two noise removal methods were developed. The first method is based on combining Negative function with Gamma correction function. The second noise reduction method is addressed by utilising 2D Gabor filter. Furthermore, the consonant study was conducted based on Automatic Speech Recognition (ASR) system concept. The ASR composes of feature extraction stage followed by speech recognition. On the other hand, the feature extraction was implemented b...
A binary grammar is a relational grammar with two nonterminal alphabets, two terminal alphabets, ... more A binary grammar is a relational grammar with two nonterminal alphabets, two terminal alphabets, a set of pairs of productions and the pair of the initial nonterminals that generates the binary relation, i.e., the set of pairs of strings over the terminal alphabets. This paper investigates the binary context-free grammars as mutually controlled grammars: two context-free grammars generate strings imposing restrictions on selecting production rules to be applied in derivations. The paper shows that binary context-free grammars can generate matrix languages whereas binary regular and linear grammars have the same power as Chomskyan regular and linear grammars.
Sustainable Engineering and Innovation, ISSN 2712-0562
The previous existing mobile technologies were only limited to voice and short messages, organize... more The previous existing mobile technologies were only limited to voice and short messages, organized between several network operators and service providers. However, recent advancements in technologies, introduction, and development of the smartphones added many features such: high-speed processors, huge memory, multitasking, screens with large-resolution, utile communication hardware, and so on. Mobile devices were evolving into general-purpose computers, which resulted in the development of various technological platforms, operating systems, and platforms for the development of the applications. All these results in the occurrence of various competitive offers on the market. The above-mentioned features, processing speed and applications available on mobile devices are affected by underlying operating systems. In this paper, there will be discussed the mobile operating systems and application development platforms.
Sustainable Engineering and Innovation, ISSN 2712-0562
Internet of Things (IoT) paradigm became particularly popular in the last couple of years in such... more Internet of Things (IoT) paradigm became particularly popular in the last couple of years in such a way that the devices are present in almost every home across the globe. Using cheap components one can connect any device to the internet and enable information collecting from the environment, making everyday life a lot easier. Even though it does bring multiple advantages to the table, at the same time it brings certain challenges and vulnerabilities that need to be addressed. In this paper we focus on Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks and we provide a review of the current architecture of Internet of Things which is prone to these.
Indonesian Journal of Electrical Engineering and Computer Science
This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with com... more This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with complementary split ring resonator (CSRR) for radio frequency identification (RFID). The total size of the antenna is 208 × 208 × 1.6 mm3. The proposed antenna is designed, fabricated and measured in order to verify the proposed concept. The characterization for radiation parameters, like return loss, radiation pattern and antenna gain have been done experimentally. The proposed antenna is operated at 921 MHz for and achieved a gain of 8.285 dBi. All simulations in this work have been carried out by means of the commercial computer simulation technology (CST) software. In compare to the simulated results, the measured outcomes are promised.
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Papers by Ali Almisreb