Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide improvements for many applications. In addition, critical challenges and research issues were provided based on published paper limitations to help researchers distinguish between various analytics techniques to develop highly consistent, logical, and information-rich analyses based on valuable features. Furthermore, the findings of this paper may be used to identify the best methods in each sector used in these publications, assist future researchers in their studies for more systematic and comprehensive analysis and identify areas for developing a unique or hybrid technique for data analysis.
{"title":"Data Analytics and Techniques","authors":"Safa S. Abdul-Jabbar, Alaa K. Farhan","doi":"10.14500/aro.10975","DOIUrl":"https://doi.org/10.14500/aro.10975","url":null,"abstract":"Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide improvements for many applications. In addition, critical challenges and research issues were provided based on published paper limitations to help researchers distinguish between various analytics techniques to develop highly consistent, logical, and information-rich analyses based on valuable features. Furthermore, the findings of this paper may be used to identify the best methods in each sector used in these publications, assist future researchers in their studies for more systematic and comprehensive analysis and identify areas for developing a unique or hybrid technique for data analysis.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76668454","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}
Describing heat transfer in biological organs is absolutely challenging because it is involved with many complex phenomena. Therefore, understanding the optical and thermal properties of living system during external irradiation sources such as laser interstitial thermal therapy (LITT) are too important for therapeutic purposes, especially for hyperthermia treatments. The purpose of this study was to determine a proper laser power and irradiation time for LITT applicator to irradiate liver tissue during hyperthermia treatment. For this aim, bioheat equation in one-dimensional spherical coordinate is solved by Green function method to simulate temperature distribution and rate of damage around irradiated target and how thermal and optical properties such as laser power, laser exposure time, and blood perfusion rate affect the rate of temperature distribution. Guiding equations according to the suggested boundary conditions are written and solved by MATLAB software. The outcomes show that increasing laser exposure time and power increase the temperature, especially at the nearest distance from the center of diffusion. Accordingly, a decrease in blood perfusion rate leads to decrease temperature distribution. The findings show that the model is useful to help the physicians to monitor the amount of heat diffusion by laser power during the treatment to protect healthy cells.
{"title":"A Computational Model for Temperature Monitoring During Human Liver Treatment by Nd:YaG Laser Interstitial Thermal Therapy (LITT)","authors":"Bazhdar N. Mohammed, Dilshad S. Ismael","doi":"10.14500/aro.10949","DOIUrl":"https://doi.org/10.14500/aro.10949","url":null,"abstract":"Describing heat transfer in biological organs is absolutely challenging because it is involved with many complex phenomena. Therefore, understanding the optical and thermal properties of living system during external irradiation sources such as laser interstitial thermal therapy (LITT) are too important for therapeutic purposes, especially for hyperthermia treatments. The purpose of this study was to determine a proper laser power and irradiation time for LITT applicator to irradiate liver tissue during hyperthermia treatment. For this aim, bioheat equation in one-dimensional spherical coordinate is solved by Green function method to simulate temperature distribution and rate of damage around irradiated target and how thermal and optical properties such as laser power, laser exposure time, and blood perfusion rate affect the rate of temperature distribution. Guiding equations according to the suggested boundary conditions are written and solved by MATLAB software. The outcomes show that increasing laser exposure time and power increase the temperature, especially at the nearest distance from the center of diffusion. Accordingly, a decrease in blood perfusion rate leads to decrease temperature distribution. The findings show that the model is useful to help the physicians to monitor the amount of heat diffusion by laser power during the treatment to protect healthy cells.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74347010","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}
Haval A. Ahmed, Peshawa J. Muhammad Ali, Abdulbasit K. Faeq, Saman M. Abdullah
Data normalization can be useful in eliminating the effect of inconsistent ranges in some machine learning (ML) techniques and in speeding up the optimization process in others. Many studies apply different methods of data normalization with an aim to reduce or eliminate the impact of data variance on the accuracy rate of ML-based models. However, the significance of this impact aligning with the mathematical concept of the ML algorithms still needs more investigation and tests. To identify that, this work proposes an investigation methodology involving three different ML algorithms, which are support vector machine (SVM), artificial neural network (ANN), and Euclidean-based K-nearest neighbor (E-KNN). Throughout this work, five different datasets have been utilized, and each has been taken from different application fields with different statistical properties. Although there are many data normalization methods available, this work focuses on the min-max method, because it actively eliminates the effect of inconsistent ranges of the datasets. Moreover, other factors that are challenging the process of min-max normalization, such as including or excluding outliers or the least significant feature, have also been considered in this work. The finding of this work shows that each ML technique responds differently to the min-max normalization. The performance of SVM models has been improved, while no significant improvement happened to the performance of ANN models. It is been concluded that the performance of E-KNN models may improve or degrade with the min-max normalization, and it depends on the statistical properties of the dataset.
{"title":"An Investigation on Disparity Responds of Machine Learning Algorithms to Data Normalization Method","authors":"Haval A. Ahmed, Peshawa J. Muhammad Ali, Abdulbasit K. Faeq, Saman M. Abdullah","doi":"10.14500/aro.10970","DOIUrl":"https://doi.org/10.14500/aro.10970","url":null,"abstract":"Data normalization can be useful in eliminating the effect of inconsistent ranges in some machine learning (ML) techniques and in speeding up the optimization process in others. Many studies apply different methods of data normalization with an aim to reduce or eliminate the impact of data variance on the accuracy rate of ML-based models. However, the significance of this impact aligning with the mathematical concept of the ML algorithms still needs more investigation and tests. To identify that, this work proposes an investigation methodology involving three different ML algorithms, which are support vector machine (SVM), artificial neural network (ANN), and Euclidean-based K-nearest neighbor (E-KNN). Throughout this work, five different datasets have been utilized, and each has been taken from different application fields with different statistical properties. Although there are many data normalization methods available, this work focuses on the min-max method, because it actively eliminates the effect of inconsistent ranges of the datasets. Moreover, other factors that are challenging the process of min-max normalization, such as including or excluding outliers or the least significant feature, have also been considered in this work. The finding of this work shows that each ML technique responds differently to the min-max normalization. The performance of SVM models has been improved, while no significant improvement happened to the performance of ANN models. It is been concluded that the performance of E-KNN models may improve or degrade with the min-max normalization, and it depends on the statistical properties of the dataset.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74052906","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}
Social media is internet-based technology and an electronic form of communication that facilitates sharing of ideas, documents, and personal information. Twitter is a microblogging platform and is the most effective social service for posting microblogs and likings, commenting, sharing, and communicating with others. The problem we are shedding light on in this paper is the misuse of bots on Twitter. The purpose of bots is to automate specific repetitive tasks instead of human interaction. However, bots are misused to influence people’s minds by spreading rumors and conspiracy related to controversial topics. In this paper, we initiate a new benchmark created on a 1.5M Twitter profile. We train different supervised machine learning on our benchmark to detect bots on Twitter. In addition to increasing benchmark scalability, various autofeature selections are utilized to identify the most influential features and remove the less influential ones. Furthermore, over-under-sampling is applied to reduce the imbalance effect on the benchmark. Finally, our benchmark compared with other stateof-the-art benchmarks and achieved a 6% higher area under the curve than other datasets in the case of generalization, improving the model performance by at least 2% by applying over-/undersampling.
{"title":"Machine Learning Algorithms for Detecting and Analyzing Social Bots Using a Novel Dataset","authors":"Niyaz Jalal, K. Ghafoor","doi":"10.14500/aro.101032","DOIUrl":"https://doi.org/10.14500/aro.101032","url":null,"abstract":"Social media is internet-based technology and an electronic form of communication that facilitates sharing of ideas, documents, and personal information. Twitter is a microblogging platform and is the most effective social service for posting microblogs and likings, commenting, sharing, and communicating with others. The problem we are shedding light on in this paper is the misuse of bots on Twitter. The purpose of bots is to automate specific repetitive tasks instead of human interaction. However, bots are misused to influence people’s minds by spreading rumors and conspiracy related to controversial topics. In this paper, we initiate a new benchmark created on a 1.5M Twitter profile. We train different supervised machine learning on our benchmark to detect bots on Twitter. In addition to increasing benchmark scalability, various autofeature selections are utilized to identify the most influential features and remove the less influential ones. Furthermore, over-under-sampling is applied to reduce the imbalance effect on the benchmark. Finally, our benchmark compared with other stateof-the-art benchmarks and achieved a 6% higher area under the curve than other datasets in the case of generalization, improving the model performance by at least 2% by applying over-/undersampling.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84641632","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 paper, a new cooperative classification method called auto-train support vector machine (SVM) is proposed. This new method converts indirectly SVM to an unsupervised classification method. The main disadvantage of conventional SVM is that it needs a priori knowledge about the data to train it. To avoid using this knowledge that is strictly required to train SVM, in this cooperative method, the data, that is, hyperspectral images (HSIs), are first clustered using Fuzzy C-means (FCM); then, the created labels are used to train SVM. At this stage, the image content is classified using the auto-trained SVM. Using FCM, clustering reveals how strongly a pixel is assigned to a class thanks to the fuzzification process. This information leads to gaining two advantages, the first one is that no prior knowledge about the data (known labels) is needed and the second one is that the training data selection is not done randomly (the training data are selected according to their degree of membership to a class). The proposed method gives very promising results. The method is tested on two HSIs, which are Indian Pines and Pavia University. The results obtained have a very high accuracy of the classification and exceed the existing manually trained methods in the literature.
{"title":"Train Support Vector Machine Using Fuzzy C-means Without a Prior Knowledge for Hyperspectral Image Content Classification","authors":"A. Taher","doi":"10.14500/aro.101025","DOIUrl":"https://doi.org/10.14500/aro.101025","url":null,"abstract":"In this paper, a new cooperative classification method called auto-train support vector machine (SVM) is proposed. This new method converts indirectly SVM to an unsupervised classification method. The main disadvantage of conventional SVM is that it needs a priori knowledge about the data to train it. To avoid using this knowledge that is strictly required to train SVM, in this cooperative method, the data, that is, hyperspectral images (HSIs), are first clustered using Fuzzy C-means (FCM); then, the created labels are used to train SVM. At this stage, the image content is classified using the auto-trained SVM. Using FCM, clustering reveals how strongly a pixel is assigned to a class thanks to the fuzzification process. This information leads to gaining two advantages, the first one is that no prior knowledge about the data (known labels) is needed and the second one is that the training data selection is not done randomly (the training data are selected according to their degree of membership to a class). The proposed method gives very promising results. The method is tested on two HSIs, which are Indian Pines and Pavia University. The results obtained have a very high accuracy of the classification and exceed the existing manually trained methods in the literature.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85527708","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 paper presents an efficient theoretical design approach of a very compact microstrip diplexer for modern wireless communication system applications. The proposed basic resonator is made of coupled lines, simple transmission line and a shunt stub. The coupled lines and transmission line make a U-shape resonator while the shunt stub is loaded inside the U-shape cell to save the size significantly, where the overall size of the presented diplexer is only 0.008 λg2 . The configuration of this resonator is analyzed to increase intuitive understanding of the structure and easier optimization. The first and second resonance frequencies are f o1 = 895 MHz and f o2 = 2.2 GHz. Both channels have good properties so that the best simulated insertion loss at the first channel (0.075 dB) and the best simulated common port return losses at both channels (40.3 dB and 31.77 dB) are achieved. The presented diplexer can suppress the harmonics acceptably up to 3 GHz (3.3 fo1 ). Another feature is having 31% fractional bandwidth at the first channel.
{"title":"A New Design Approach for a Compact Microstrip Diplexer with Good Passband Characteristics","authors":"A. Rezaei, S. Yahya","doi":"10.14500/aro.10999","DOIUrl":"https://doi.org/10.14500/aro.10999","url":null,"abstract":"This paper presents an efficient theoretical design approach of a very compact microstrip diplexer for modern wireless communication system applications. The proposed basic resonator is made of coupled lines, simple transmission line and a shunt stub. The coupled lines and transmission line make a U-shape resonator while the shunt stub is loaded inside the U-shape cell to save the size significantly, where the overall size of the presented diplexer is only 0.008 λg2 . The configuration of this resonator is analyzed to increase intuitive understanding of the structure and easier optimization. The first and second resonance frequencies are f o1 = 895 MHz and f o2 = 2.2 GHz. Both channels have good properties so that the best simulated insertion loss at the first channel (0.075 dB) and the best simulated common port return losses at both channels (40.3 dB and 31.77 dB) are achieved. The presented diplexer can suppress the harmonics acceptably up to 3 GHz (3.3 fo1 ). Another feature is having 31% fractional bandwidth at the first channel.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89189664","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}
Abubaker H. Hamad, M. Chawsheen, Ahmed A. Al-Naqshbandi
Silver nanoparticles (Ag NPs) were produced through nanosecond laser in deionized water. These nanoparticles were characterized by UV–VIS spectrometer and transmission electron microscopy. VITEK®2 compact system was used to identify Escherichia coli (ESBL strain) and Staphylococcus aureus (MRSA strain) as multidrug-resistance (MDR) bacteria. The antibacterial activity of Ag NPs, ampicillin (AMP), and their combinations was tested against both bacterial isolates through standard microbiological culturing techniques. Our data show that both of E. coli and S. aureus were highly resistant to AMP. Ag NPs alone reduced growth in both bacterial isolates considerably. Growth declined drastically in both bacteria when AMP was used in combination with Ag NPs. The minimal inhibitory concentration of combined agents for E. coli was 20 µg/ml Ag NPs + 1 mg AMP/ml and for S. aureus was 10 µg/ml Ag NPs + 1 mg AMP/ml. The results show that the Ag NPs have great potentials in enhancing the antimicrobial activities of drugs that used to be ineffective against MDR bacteria. Administering combinations of antibiotic(s) with AgNPs may help in treating patients suffering from infections caused by MDR bacteria. Further in vivo and in vitro investigations are required to evaluate the side effects of these combinations.
采用纳秒激光在去离子水中制备银纳米粒子。采用紫外可见光谱和透射电镜对纳米颗粒进行了表征。VITEK®2紧凑型系统用于鉴定大肠杆菌(ESBL菌株)和金黄色葡萄球菌(MRSA菌株)为多药耐药(MDR)细菌。通过标准微生物培养技术检测Ag NPs、氨苄西林(AMP)及其组合对两种细菌的抑菌活性。我们的数据显示，大肠杆菌和金黄色葡萄球菌都对AMP具有高度耐药性。Ag NPs单独抑制了这两种细菌分离株的生长。当AMP与Ag NPs联合使用时，两种细菌的生长都急剧下降。联合用药对大肠杆菌的最低抑菌浓度为20µg/ml Ag NPs + 1 mg AMP/ml，对金黄色葡萄球菌的最低抑菌浓度为10µg/ml Ag NPs + 1 mg AMP/ml。结果表明，Ag NPs在增强对耐多药细菌无效的药物的抑菌活性方面具有很大的潜力。联合使用抗生素和AgNPs可能有助于治疗耐多药细菌引起的感染患者。需要进一步的体内和体外研究来评估这些组合的副作用。
{"title":"Role of Laser Produced Silver Nanoparticles in Reversing Antibiotic Resistance in Some MultidrugResistant Pathogenic Bacteria","authors":"Abubaker H. Hamad, M. Chawsheen, Ahmed A. Al-Naqshbandi","doi":"10.14500/aro.10877","DOIUrl":"https://doi.org/10.14500/aro.10877","url":null,"abstract":"Silver nanoparticles (Ag NPs) were produced through nanosecond laser in deionized water. These nanoparticles were characterized by UV–VIS spectrometer and transmission electron microscopy. VITEK®2 compact system was used to identify Escherichia coli (ESBL strain) and Staphylococcus aureus (MRSA strain) as multidrug-resistance (MDR) bacteria. The antibacterial activity of Ag NPs, ampicillin (AMP), and their combinations was tested against both bacterial isolates through standard microbiological culturing techniques. Our data show that both of E. coli and S. aureus were highly resistant to AMP. Ag NPs alone reduced growth in both bacterial isolates considerably. Growth declined drastically in both bacteria when AMP was used in combination with Ag NPs. The minimal inhibitory concentration of combined agents for E. coli was 20 µg/ml Ag NPs + 1 mg AMP/ml and for S. aureus was 10 µg/ml Ag NPs + 1 mg AMP/ml. The results show that the Ag NPs have great potentials in enhancing the antimicrobial activities of drugs that used to be ineffective against MDR bacteria. Administering combinations of antibiotic(s) with AgNPs may help in treating patients suffering from infections caused by MDR bacteria. Further in vivo and in vitro investigations are required to evaluate the side effects of these combinations.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88631181","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}
Traffic congestion is a considerable problem in urban arterials, especially at signalized intersections. Signalized intersections are critical elements of the highway system, thus improving their performance would significantly influence the overall operating performance of the system in terms of delay and level of service (LOS). The aim of this study is to assess the capacity performance of two signalized intersections in Duhok city, namely, Zari land intersection and Salahaddin Mosque intersection using the procedure in the Highway Capacity Manual and Synchro software. Total intersection delay, LOS, and volume to capacity ratio (v/c) were the measures of effectiveness used for comparison purposes. Different optimization alternatives have been tested to improve current and future performance. The results have shown that the Zari land intersection is currently operating at LOS F with an average delay of 590 s/veh and high values of v/c at specific movements. Results of optimization show that the scenario of creating an overpass with a change in cycle length and adding one additional lane in each direction is the best alternative to improve its performance to the LOS D with the maximum v/c ratio of 0.86. For Salahaddin Mosque intersection, the delay can be reduced from 544 s/veh (LOS F) with high values of v/c at the major street through movement to an average delay of 70 s/veh (LOS E) and maximum v/c ratio of 1, when cycle length and geometrics are changed, and approaching traffic from the minor street is prohibited.
{"title":"Synchro Software-Based Alternatives for Improving Traffic Operations at Signalized Intersections","authors":"N. Hussein","doi":"10.14500/aro.10915","DOIUrl":"https://doi.org/10.14500/aro.10915","url":null,"abstract":"Traffic congestion is a considerable problem in urban arterials, especially at signalized intersections. Signalized intersections are critical elements of the highway system, thus improving their performance would significantly influence the overall operating performance of the system in terms of delay and level of service (LOS). The aim of this study is to assess the capacity performance of two signalized intersections in Duhok city, namely, Zari land intersection and Salahaddin Mosque intersection using the procedure in the Highway Capacity Manual and Synchro software. Total intersection delay, LOS, and volume to capacity ratio (v/c) were the measures of effectiveness used for comparison purposes. Different optimization alternatives have been tested to improve current and future performance. The results have shown that the Zari land intersection is currently operating at LOS F with an average delay of 590 s/veh and high values of v/c at specific movements. Results of optimization show that the scenario of creating an overpass with a change in cycle length and adding one additional lane in each direction is the best alternative to improve its performance to the LOS D with the maximum v/c ratio of 0.86. For Salahaddin Mosque intersection, the delay can be reduced from 544 s/veh (LOS F) with high values of v/c at the major street through movement to an average delay of 70 s/veh (LOS E) and maximum v/c ratio of 1, when cycle length and geometrics are changed, and approaching traffic from the minor street is prohibited.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84422458","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}
Vertical-cavity semiconductor optical amplifiers (VCSOAs) are interesting devices for optical communication applications. In this work, we have studied the characteristics of gain spectra and amplifier bandwidth in reflection mode at 1300 nm GaInNAs/GaAs hot electron light emission and lasing in semiconductor heterostructure-VCSOA structure using MATLAB program. The device contains 16 Ga0.7In0.3N0.038As0.962 multiple quantum wells (QWs) in its intrinsic region; the active region is bounded between eight pairs of GaAs/AlAs top distributed Bragg reflectors (DBRs) mirror and 25 pairs of AlAs/GaAs bottom DBRs mirror. Simulation results suggest that the resonance cavity of QW of HILLISH-VCSOA is varied with temperature and number of DBRs periods. We compare the relation between the wavelength and gain at a different single-pass gain in both reflection and transmission modes. The highest gain at around 36 dB is observed in reflection mode. Moreover, we calculated the amplifier bandwidth at different periods of top mirror’s reflectivity, in which when the peak reflection gains increases, the amplifier bandwidth decreases.
{"title":"Design, Modeling, and Characterization of Hot Electron Light Emission and Lasing in Semiconductor Heterostructure-VCSOA with Optical Gain up to 36 dB","authors":"Hawro I. Yaba, F. Chaqmaqchee","doi":"10.14500/aro.10969","DOIUrl":"https://doi.org/10.14500/aro.10969","url":null,"abstract":"Vertical-cavity semiconductor optical amplifiers (VCSOAs) are interesting devices for optical communication applications. In this work, we have studied the characteristics of gain spectra and amplifier bandwidth in reflection mode at 1300 nm GaInNAs/GaAs hot electron light emission and lasing in semiconductor heterostructure-VCSOA structure using MATLAB program. The device contains 16 Ga0.7In0.3N0.038As0.962 multiple quantum wells (QWs) in its intrinsic region; the active region is bounded between eight pairs of GaAs/AlAs top distributed Bragg reflectors (DBRs) mirror and 25 pairs of AlAs/GaAs bottom DBRs mirror. Simulation results suggest that the resonance cavity of QW of HILLISH-VCSOA is varied with temperature and number of DBRs periods. We compare the relation between the wavelength and gain at a different single-pass gain in both reflection and transmission modes. The highest gain at around 36 dB is observed in reflection mode. Moreover, we calculated the amplifier bandwidth at different periods of top mirror’s reflectivity, in which when the peak reflection gains increases, the amplifier bandwidth decreases.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85154771","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}
Sarmad N. Mageed, Shukur R. Hamashareef, A. Shallal
Immunoinfertility caused by anti-sperm antibodies (ASAs) represents about 10–20% of infertility among couples, which interfere with sperm motility and ability to penetrate cervical mucus, sperm-oocyte binding, fertilization, and embryo development. In addition, deoxyribonucleic acid (DNA) damages are increasingly found with infertile cases affecting male reproduction potency and progeny. This study aims to assess the semen, presence of ASAs, and DNA fragmentation index in normozoospermic patients. A total number of 116 cases with an average age of 20–51 years old, and duration of infertility at 4.70 ± 2.77 are classified into 77 and 39 primary and secondary types of infertility, respectively. Mixed agglutination reaction test was used to estimate the ASAs in semen (direct method) and in seminal plasma and blood serum (indirect method), for both immunoglobulins IgG and IgA. Acridine orange test was used to detect DNA fragmentation index. The results showed a significant difference (P > 0.05) for those with a secondary type of infertility at means 24.37 and 31.48 for IgG, and 14.46 ± 1.76 and 6.86 ± 0.39 for IgA by both direct and indirect methods, respectively. The direct method showed a significant difference only for the sperm tail, while that for indirect method was in sperm mid-piece. The mean of DFI for all cases was 38.25 ± 2.08, at 41.61 ± 2.19 and 31.63 ± 4.29, for both primary and secondary cases, respectively. The percentage of ASAs revealed no significant difference with DFI, except in some parts of sperm.
{"title":"Detection of Sperm DNA Integrity and Some Immunological Aspects in Infertile Males","authors":"Sarmad N. Mageed, Shukur R. Hamashareef, A. Shallal","doi":"10.14500/aro.10924","DOIUrl":"https://doi.org/10.14500/aro.10924","url":null,"abstract":"Immunoinfertility caused by anti-sperm antibodies (ASAs) represents about 10–20% of infertility among couples, which interfere with sperm motility and ability to penetrate cervical mucus, sperm-oocyte binding, fertilization, and embryo development. In addition, deoxyribonucleic acid (DNA) damages are increasingly found with infertile cases affecting male reproduction potency and progeny. This study aims to assess the semen, presence of ASAs, and DNA fragmentation index in normozoospermic patients. A total number of 116 cases with an average age of 20–51 years old, and duration of infertility at 4.70 ± 2.77 are classified into 77 and 39 primary and secondary types of infertility, respectively. Mixed agglutination reaction test was used to estimate the ASAs in semen (direct method) and in seminal plasma and blood serum (indirect method), for both immunoglobulins IgG and IgA. Acridine orange test was used to detect DNA fragmentation index. The results showed a significant difference (P > 0.05) for those with a secondary type of infertility at means 24.37 and 31.48 for IgG, and 14.46 ± 1.76 and 6.86 ± 0.39 for IgA by both direct and indirect methods, respectively. The direct method showed a significant difference only for the sperm tail, while that for indirect method was in sperm mid-piece. The mean of DFI for all cases was 38.25 ± 2.08, at 41.61 ± 2.19 and 31.63 ± 4.29, for both primary and secondary cases, respectively. The percentage of ASAs revealed no significant difference with DFI, except in some parts of sperm.","PeriodicalId":8398,"journal":{"name":"ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86478080","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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