Tribolium confusum is one of the most common pests of many commodities, especially cereals and their products. These pests are known for being the most destructive insect pests attacking and infesting stored flour and grain in soil, warehouses, grocery stores, and homes. Therefore, this study aims to control these pests with an environmentally friendly, healthier, and cost-effective pesticide instead of the common artificial chemicals to practice the current management of cereal storage pest control in the Kurdistan Region of Iraq. For this to be achieved, the toxicity effect of crude plant extracts from five different parts of Melia azedarach in tap water with concentrations of 50%, 60%, 70%, 80%, and 90% at different times (2, 4, 6, 8, and 10 h) against stored-product insect was tested. The toxicity effect of these extracts varied based on the crude plant part extracts, concentrations, and exposure period according to the SAS system investigation on the mortality rate of T. confusum adults (Duncan test). The extracts’ compatibility with treated adults of T. confusum in the clear petri dish was noted. Besides, the number of dead adults was measured by loss of motion.
{"title":"Effects of Crude Plant Extracts from Five Parts of Melia azedarach on Tribolium confusum","authors":"Muzafar K. Omar, H. A. Muhammad, Sawan M. Mirkhan","doi":"10.14500/aro.11038","DOIUrl":"https://doi.org/10.14500/aro.11038","url":null,"abstract":"Tribolium confusum is one of the most common pests of many commodities, especially cereals and their products. These pests are known for being the most destructive insect pests attacking and infesting stored flour and grain in soil, warehouses, grocery stores, and homes. Therefore, this study aims to control these pests with an environmentally friendly, healthier, and cost-effective pesticide instead of the common artificial chemicals to practice the current management of cereal storage pest control in the Kurdistan Region of Iraq. For this to be achieved, the toxicity effect of crude plant extracts from five different parts of Melia azedarach in tap water with concentrations of 50%, 60%, 70%, 80%, and 90% at different times (2, 4, 6, 8, and 10 h) against stored-product insect was tested. The toxicity effect of these extracts varied based on the crude plant part extracts, concentrations, and exposure period according to the SAS system investigation on the mortality rate of T. confusum adults (Duncan test). The extracts’ compatibility with treated adults of T. confusum in the clear petri dish was noted. Besides, the number of dead adults was measured by loss of motion.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79547398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Agriculture crops are highly significant for the sustenance of human life and act as an essential source for national income development worldwide. Plant diseases and pests are considered one of the most imperative factors influencing food production, quality, and minimize losses in production. Farmers are currently facing difficulty in identifying various plant diseases and pests, which are important to prevent plant diseases effectively in a complicated environment. The recent development of deep learning techniques has found use in the diagnosis of plant diseases and pests, providing a robust tool with highly accurate results. In this context, this paper presents a comprehensive review of the literature that aims to identify the state of the art of the use of convolutional neural networks (CNNs) in the process of diagnosing and identification of plant pest and diseases. In addition, it presents some issues that are facing the models performance, and also indicates gaps that should be addressed in the future. In this regard, we review studies with various methods that addressed plant disease detection, dataset characteristics, the crops, and pathogens. Moreover, it discusses the commonly employed five-step methodology for plant disease recognition, involving data acquisition, preprocessing, segmentation, feature extraction, and classification. It discusses various deep learning architecture-based solutions that have a faster convergence rate of plant disease recognition. From this review, it is possible to understand the innovative trends regarding the use of CNN’s algorithms in the plant diseases diagnosis and to recognize the gaps that need the attention of the research community.
{"title":"Plant Disease Diagnosing Based on Deep Learning Techniques","authors":"Saman M. Omer, K. Ghafoor, Shavan K. Askar","doi":"10.14500/aro.11080","DOIUrl":"https://doi.org/10.14500/aro.11080","url":null,"abstract":"Agriculture crops are highly significant for the sustenance of human life and act as an essential source for national income development worldwide. Plant diseases and pests are considered one of the most imperative factors influencing food production, quality, and minimize losses in production. Farmers are currently facing difficulty in identifying various plant diseases and pests, which are important to prevent plant diseases effectively in a complicated environment. The recent development of deep learning techniques has found use in the diagnosis of plant diseases and pests, providing a robust tool with highly accurate results. In this context, this paper presents a comprehensive review of the literature that aims to identify the state of the art of the use of convolutional neural networks (CNNs) in the process of diagnosing and identification of plant pest and diseases. In addition, it presents some issues that are facing the models performance, and also indicates gaps that should be addressed in the future. In this regard, we review studies with various methods that addressed plant disease detection, dataset characteristics, the crops, and pathogens. Moreover, it discusses the commonly employed five-step methodology for plant disease recognition, involving data acquisition, preprocessing, segmentation, feature extraction, and classification. It discusses various deep learning architecture-based solutions that have a faster convergence rate of plant disease recognition. From this review, it is possible to understand the innovative trends regarding the use of CNN’s algorithms in the plant diseases diagnosis and to recognize the gaps that need the attention of the research community.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80951189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Technology has dominated a huge part of human life. Furthermore, technology users use language continuously to express feelings and sentiments about things. The science behind identifying human attitudes toward a particular product, service,or topic is one of the most active fields of research, and it is called sentiment analysis. While the English language is making real progress in sentiment analysis daily, other less-resourced languages, such as Kurdish, still suffer from fundamental issues and challenges in Natural Language Processing (NLP). This paper experimentswith the recently published medical corpus using the classical machine learning method and the latest deep learning tool in NLP and Bidirectional Encoder Representations from Transformers (BERT). We evaluated the findings of both machine learning and deep learning. The outcome indicates that BERT outperforms all the machine learning classifiers by scoring (92%) in accuracy, which is by two points higher than machine learning classifiers.
{"title":"Using Multilingual Bidirectional Encoder Representations from Transformers on Medical Corpus for Kurdish Text Classification","authors":"Soran S. Badawi","doi":"10.14500/aro.11088","DOIUrl":"https://doi.org/10.14500/aro.11088","url":null,"abstract":"Technology has dominated a huge part of human life. Furthermore, technology users use language continuously to express feelings and sentiments about things. The science behind identifying human attitudes toward a particular product, service,or topic is one of the most active fields of research, and it is called sentiment analysis. While the English language is making real progress in sentiment analysis daily, other less-resourced languages, such as Kurdish, still suffer from fundamental issues and challenges in Natural Language Processing (NLP). This paper experimentswith the recently published medical corpus using the classical machine learning method and the latest deep learning tool in NLP and Bidirectional Encoder Representations from Transformers (BERT). We evaluated the findings of both machine learning and deep learning. The outcome indicates that BERT outperforms all the machine learning classifiers by scoring (92%) in accuracy, which is by two points higher than machine learning classifiers.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86584059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This process of this paper is carried out using thechemical spraying method to produce homogeneous thin films ofpure cadmium sulfide-doped with silver at different percentagesof 1%, 3%, and 5% on glass and polyimide plastic substrates at300°C. The aim is to study the optical and structural properties of the samples and the effect of the silver doping rate on films producedwith these properties. Due to X-ray diffraction studies, all filmscreated had a hexagonal phase, and it was noticed that they had avery precise structure free of holes or cracks. The obtained crystalsize ranged between 22.74 nm and 55.05 nm for different substrates, and the prominent plane was (002). From the optical properties, all films exhibited transmission higher than 60%, thus showing a lowabsorption, which makes them be used as light-permeable layers in the Solar Cell system. In addition, emission peaks were revealed by photo luminescence spectra examination at wavelengths ranging between (542.94 nm) and (546.02 nm), which led to calculate the energy gap (Eg). of the produced films, ranged between (2.27 eV) and (2.28 eV) for the different substrates.
{"title":"Structural and Optical Properties of Cadmium Sulfide-doped Silver Deposited on Glass and Polymer Substrates by Chemical Spray Pyrolysis","authors":"Niaz H. Hamad, M. Faraj, Akram H. Taha","doi":"10.14500/aro.11097","DOIUrl":"https://doi.org/10.14500/aro.11097","url":null,"abstract":"This process of this paper is carried out using thechemical spraying method to produce homogeneous thin films ofpure cadmium sulfide-doped with silver at different percentagesof 1%, 3%, and 5% on glass and polyimide plastic substrates at300°C. The aim is to study the optical and structural properties of the samples and the effect of the silver doping rate on films producedwith these properties. Due to X-ray diffraction studies, all filmscreated had a hexagonal phase, and it was noticed that they had avery precise structure free of holes or cracks. The obtained crystalsize ranged between 22.74 nm and 55.05 nm for different substrates, and the prominent plane was (002). From the optical properties, all films exhibited transmission higher than 60%, thus showing a lowabsorption, which makes them be used as light-permeable layers in the Solar Cell system. In addition, emission peaks were revealed by photo luminescence spectra examination at wavelengths ranging between (542.94 nm) and (546.02 nm), which led to calculate the energy gap (Eg). of the produced films, ranged between (2.27 eV) and (2.28 eV) for the different substrates.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89003183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this paper is to assess the mutagenicand genotoxic potentials of avocado oil made from the fruit pulp of Persea Americana, a member of the Lauraceae family.Michigan Cancer Foundation-7 (MCF-7) cells are used in the 3-4,5 dimethylthiazol-2yl-2,5-diphenyl tetrazolium bromide (MTT) test to examine the possible antiproliferative and cytostatic qualities of different doses of avocado oil, and MCF-7 cells are used in the comet assay to examine the potential cytostatic effects of avocado oil extracted from the avocado fruit. DNA in human breast cancer cells is partially damaged by avocado oil. However, DNA damage at low, medium, and high levels was discovered in the positive control. Without positive control, the DNA damage level falls in the low, middle, and high ranges. The MTT assay shows that avocado oil exerts a dose-dependent cytostatic impact on human breast cancer MCF-7 cells with an IC50 value of 379.2 μg/mL, which is the IC50 value that causes genotoxicity in the comet assay.
{"title":"Cytostatic Effects of Avocado Oil Using Single-cell Gel Electrophoresis (Comet Assay)","authors":"Subasini Uthirapathy","doi":"10.14500/aro.11073","DOIUrl":"https://doi.org/10.14500/aro.11073","url":null,"abstract":"The goal of this paper is to assess the mutagenicand genotoxic potentials of avocado oil made from the fruit pulp of Persea Americana, a member of the Lauraceae family.Michigan Cancer Foundation-7 (MCF-7) cells are used in the 3-4,5 dimethylthiazol-2yl-2,5-diphenyl tetrazolium bromide (MTT) test to examine the possible antiproliferative and cytostatic qualities of different doses of avocado oil, and MCF-7 cells are used in the comet assay to examine the potential cytostatic effects of avocado oil extracted from the avocado fruit. DNA in human breast cancer cells is partially damaged by avocado oil. However, DNA damage at low, medium, and high levels was discovered in the positive control. Without positive control, the DNA damage level falls in the low, middle, and high ranges. The MTT assay shows that avocado oil exerts a dose-dependent cytostatic impact on human breast cancer MCF-7 cells with an IC50 value of 379.2 μg/mL, which is the IC50 value that causes genotoxicity in the comet assay.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88266315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Type II diabetes has been on the rise for the past few decades and the current management plan of diabetes is challenging to individuals in keeping their blood glucose levels within normal limits. There is a constant search of new ways to tackle these challenges. Cinnamon is suggested to have antihyperglycemic and lipid lowering effect and has been proposed to be utilized in type II diabetes. The aim behind this review is to explore the role of cinnamon in improving the glycemic status, lipid profile, and weight status of patients with type II diabetes. PubMed and ScienceDirect databases have been searched for eligible studies conducted until February 2022, the outcomes measured were glycemic markers as primary outcome and lipid profile and weight status as secondary outcomes. A total of ten trials involving 861 patients were included in the study. Five studies have demonstrated reductions in glycemic markers (ranging between −0.56 and −1.9 mmol/L for fasting blood sugar and between −0.21% and −0.93% for glycated hemoglobin) whereas the remaining four did not show any significant reduction. The most improvements in glycemic markers are seen in patients with poorly controlled diabetes and patients with higher body mass index (BMI) values. The majority of the studies did not record improvement in lipid profile. Changes in weight status are only observed in overweight patient category (BMI between 25 and 30). Overall, there is no coherent evidence to decide about antihyperglycemic, lipid lowering, and weight reducing effects of cinnamon in type II diabetes.
{"title":"Role of Cinnamon Supplementation on Glycemic Markers, Lipid Profile and Weight Status in Patients with Type II Diabetes","authors":"Sazan M. Talaat","doi":"10.14500/aro.11041","DOIUrl":"https://doi.org/10.14500/aro.11041","url":null,"abstract":"Type II diabetes has been on the rise for the past few decades and the current management plan of diabetes is challenging to individuals in keeping their blood glucose levels within normal limits. There is a constant search of new ways to tackle these challenges. Cinnamon is suggested to have antihyperglycemic and lipid lowering effect and has been proposed to be utilized in type II diabetes. The aim behind this review is to explore the role of cinnamon in improving the glycemic status, lipid profile, and weight status of patients with type II diabetes. PubMed and ScienceDirect databases have been searched for eligible studies conducted until February 2022, the outcomes measured were glycemic markers as primary outcome and lipid profile and weight status as secondary outcomes. A total of ten trials involving 861 patients were included in the study. Five studies have demonstrated reductions in glycemic markers (ranging between −0.56 and −1.9 mmol/L for fasting blood sugar and between −0.21% and −0.93% for glycated hemoglobin) whereas the remaining four did not show any significant reduction. The most improvements in glycemic markers are seen in patients with poorly controlled diabetes and patients with higher body mass index (BMI) values. The majority of the studies did not record improvement in lipid profile. Changes in weight status are only observed in overweight patient category (BMI between 25 and 30). Overall, there is no coherent evidence to decide about antihyperglycemic, lipid lowering, and weight reducing effects of cinnamon in type II diabetes. ","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82545168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, several types of microstrip couplers are investigated in terms of structure, performance and design methods. These planar 4-ports passive devices transmit a signal through two different channels. Designers' competition has always been in miniaturizing and improving performance of couplers. Some couplers have been offered with a novel structure, which is a special feature. A high-performance coupler should have high isolation and low losses at both channels. The channels are usually overlapped so that the common port return loss in these channels should be low. Among the couplers, those with balanced amplitude and phase are more popular. The popular mathematical analysis methods are even/odd mode analysis, extracting the information from the ABCD matrix and analyzing the equivalent LC circuit of a simple resonator. According to the phase shift value, couplers are classified as 90º and correct multiples of 90º, where a microstrip 0º coupler can be used as a power divider. Some couplers have filtering and harmonic elimination features that are superior to other couplers. However, few designers paid attention to suppressing the harmonics. If the operating frequency is set in according to the type of application, the coupler becomes particularly valuable.ABCD Matrix
{"title":"A Comprehensive Review on Microstrip Couplers","authors":"A. Rezaei, S. Yahya, Leila Nouri","doi":"10.14500/aro.11108","DOIUrl":"https://doi.org/10.14500/aro.11108","url":null,"abstract":"In this work, several types of microstrip couplers are investigated in terms of structure, performance and design methods. These planar 4-ports passive devices transmit a signal through two different channels. Designers' competition has always been in miniaturizing and improving performance of couplers. Some couplers have been offered with a novel structure, which is a special feature. A high-performance coupler should have high isolation and low losses at both channels. The channels are usually overlapped so that the common port return loss in these channels should be low. Among the couplers, those with balanced amplitude and phase are more popular. The popular mathematical analysis methods are even/odd mode analysis, extracting the information from the ABCD matrix and analyzing the equivalent LC circuit of a simple resonator. According to the phase shift value, couplers are classified as 90º and correct multiples of 90º, where a microstrip 0º coupler can be used as a power divider. Some couplers have filtering and harmonic elimination features that are superior to other couplers. However, few designers paid attention to suppressing the harmonics. If the operating frequency is set in according to the type of application, the coupler becomes particularly valuable.ABCD Matrix","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84190288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Early accurate burn depth diagnosis is crucial for selecting the appropriate clinical intervention strategies and assessing burn patient prognosis quality. However, with limited diagnostic accuracy, the current burn depth diagnosis approach still primarily relies on the empirical subjective assessment of clinicians. With the quick development of artificial intelligence technology, integration of deep learning algorithms with image analysis technology can more accurately identify and evaluate the information in medical images. The objective of the work is to detect and classify burn area in medical images using an unsupervised deep learning algorithm. The main contribution is to developing computations using one of the deep learning algorithm. To demonstrate the effectiveness of the proposed framework, experiments are performed on the benchmark to evaluate system stability. The results indicate that, the proposed system is simple and suits real life applications. The system accuracy was 75%, when compared with some of the state-of-the-art techniques.
{"title":"Burning Skin Detection System in Human Body","authors":"Noor M. Abdulhadi, N. A. Ibraheem, M. Hasan","doi":"10.14500/aro.10976","DOIUrl":"https://doi.org/10.14500/aro.10976","url":null,"abstract":"Early accurate burn depth diagnosis is crucial for selecting the appropriate clinical intervention strategies and assessing burn patient prognosis quality. However, with limited diagnostic accuracy, the current burn depth diagnosis approach still primarily relies on the empirical subjective assessment of clinicians. With the quick development of artificial intelligence technology, integration of deep learning algorithms with image analysis technology can more accurately identify and evaluate the information in medical images. The objective of the work is to detect and classify burn area in medical images using an unsupervised deep learning algorithm. The main contribution is to developing computations using one of the deep learning algorithm. To demonstrate the effectiveness of the proposed framework, experiments are performed on the benchmark to evaluate system stability. The results indicate that, the proposed system is simple and suits real life applications. The system accuracy was 75%, when compared with some of the state-of-the-art techniques.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78996827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information security, being one of the corner stones of network and communication technology, has been evolving tremendously to cope with the parallel evolution of network security threats. Hence, cipher algorithms in the core of the information security process have more crucial role to play here, with continuous need for new and unorthodox designs to meet the increasing complexity of the applications environment that keep offering challenges to the current existing cipher algorithms. The aim of this review is to present symmetric cipher main components, the modern and lightweight symmetric cipher algorithms design based on the components that utilized in cipher design, highlighting the effect of each component and the essential component among them, how the modern cipher has modified to lightweight cipher by reducing the number and size of these components, clarify how these components give the strength for symmetric cipher versus asymmetric of cipher. Moreover, a new classification of cryptography algorithms to four categories based on four factors is presented. Finally, some modern and lightweight symmetric cipher algorithms are selected, presented with a comparison between them according to their components by taking into considerations the components impact on security, performance, and resource requirements.
{"title":"Modern and Lightweight Component-based Symmetric Cipher Algorithms","authors":"Samar A. Qassir, M. Gaata, A. Sadiq","doi":"10.14500/aro.11007","DOIUrl":"https://doi.org/10.14500/aro.11007","url":null,"abstract":"Information security, being one of the corner stones of network and communication technology, has been evolving tremendously to cope with the parallel evolution of network security threats. Hence, cipher algorithms in the core of the information security process have more crucial role to play here, with continuous need for new and unorthodox designs to meet the increasing complexity of the applications environment that keep offering challenges to the current existing cipher algorithms. The aim of this review is to present symmetric cipher main components, the modern and lightweight symmetric cipher algorithms design based on the components that utilized in cipher design, highlighting the effect of each component and the essential component among them, how the modern cipher has modified to lightweight cipher by reducing the number and size of these components, clarify how these components give the strength for symmetric cipher versus asymmetric of cipher. Moreover, a new classification of cryptography algorithms to four categories based on four factors is presented. Finally, some modern and lightweight symmetric cipher algorithms are selected, presented with a comparison between them according to their components by taking into considerations the components impact on security, performance, and resource requirements.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87936260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively.
{"title":"Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Voice Recognition","authors":"S. Jasim, A. A. Abdul Hassan, Scott Turner","doi":"10.14500/aro.11000","DOIUrl":"https://doi.org/10.14500/aro.11000","url":null,"abstract":"Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77924582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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