Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677689
Heba Abdul-Jaleel Al-Asady, sama Qasim Jumah Al-Thahab, Saad Saffa Hreshee
Watermarking is a new technique proposed to protect digital content from intellectual infringement in recent years. It modifies the original text and adds signature extracts as proof of ownership if needed. This paper uses a two-dimensional cubic spline function with the binary image as the third dimension. The cover image breaks down into three hues, red, and converts into three-dimensional binary information. The locations of pixels in the binary image third dimension (z-plain) are determined using 2D-cubic spline interpolation. To hide the watermarking information in the defined regions, we use direct correlations. The results of simulations utilizing PSNR and BER using this technique show excellent fidelity (92.238 dB) and a low bit error rate (0.0003). Watermark detection accomplishes without the use of the source image. Even when subjected to spatial problems, the simulation results suggest obtaining great realism and robustness.
{"title":"2D Cubic Spline Transformation With 3D Binary Image for a New Watermarking Algorithm","authors":"Heba Abdul-Jaleel Al-Asady, sama Qasim Jumah Al-Thahab, Saad Saffa Hreshee","doi":"10.1109/ICCITM53167.2021.9677689","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677689","url":null,"abstract":"Watermarking is a new technique proposed to protect digital content from intellectual infringement in recent years. It modifies the original text and adds signature extracts as proof of ownership if needed. This paper uses a two-dimensional cubic spline function with the binary image as the third dimension. The cover image breaks down into three hues, red, and converts into three-dimensional binary information. The locations of pixels in the binary image third dimension (z-plain) are determined using 2D-cubic spline interpolation. To hide the watermarking information in the defined regions, we use direct correlations. The results of simulations utilizing PSNR and BER using this technique show excellent fidelity (92.238 dB) and a low bit error rate (0.0003). Watermark detection accomplishes without the use of the source image. Even when subjected to spatial problems, the simulation results suggest obtaining great realism and robustness.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116589756","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677730
S.A. Ahmed, S. Ayoob, A. A. Al Janaby
Massive multiple-input multiple-output (MIMO) and Millimeter-wave (mmWave) techniques are the main factors that support modern wireless communications. Use of mmWave technology is a major factor in solving the problem of throttling congestion in the current bandwidth, as the use of mmWave leads to a significant increase in data rate, throughput and capacity. In this paper, we investigated and studied performance of 5G multi-user (MU) massive MIMO mmWave communication and obtained output results (Spectral Efficiency), using three beamforming methods: conjugate beamforming (CB), minimum mean squared error (MMSE), and zero-forcing (ZF) through mm-Wave Channel by using multiple frequencies (28GHz and 38 GHz) and we explained which one of them is better in terms of spectrum efficiency.
{"title":"On The Performance of Multi-User Massive MIMO over mm wave Channels","authors":"S.A. Ahmed, S. Ayoob, A. A. Al Janaby","doi":"10.1109/ICCITM53167.2021.9677730","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677730","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) and Millimeter-wave (mmWave) techniques are the main factors that support modern wireless communications. Use of mmWave technology is a major factor in solving the problem of throttling congestion in the current bandwidth, as the use of mmWave leads to a significant increase in data rate, throughput and capacity. In this paper, we investigated and studied performance of 5G multi-user (MU) massive MIMO mmWave communication and obtained output results (Spectral Efficiency), using three beamforming methods: conjugate beamforming (CB), minimum mean squared error (MMSE), and zero-forcing (ZF) through mm-Wave Channel by using multiple frequencies (28GHz and 38 GHz) and we explained which one of them is better in terms of spectrum efficiency.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134024863","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677773
N. D. Majeed, S. Q. Mahdi, M. Kadhim
The classic interconnection among Intellectual Property (IP) cores in a System on Chip (SoC) became ineffective due to the increase the numbers of processors on single chip. These factors lead to the emergence of Network on Chip (NoC) technology. In this paper, 2D Mesh network for 16 node were implemented with a new proposed router to solve packets conflict problem. This network has low resources, where the network utilization ratio of slices is about 24% from the available resources and the maximum frequency 102.093MHz. The total consumption power is about 150 mW for the network, where the consumption static power is 32 mW only. The router in this network has a schedule with a fixed priority, which leads to data flowing without any conflict among packets. Moreover, the crossbar in this router consists of one multiplexer, counter and without additional inputs buffers unlike traditional crossbar, which consists of five multiplexer with multiple input buffers. This router is implemented and tested on the FPGA Spartan 3A (XC3S700A) kit.
{"title":"Design and Implementation of High Performance 2D Mesh NoC Based On New Proposed Router Using FPGA","authors":"N. D. Majeed, S. Q. Mahdi, M. Kadhim","doi":"10.1109/ICCITM53167.2021.9677773","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677773","url":null,"abstract":"The classic interconnection among Intellectual Property (IP) cores in a System on Chip (SoC) became ineffective due to the increase the numbers of processors on single chip. These factors lead to the emergence of Network on Chip (NoC) technology. In this paper, 2D Mesh network for 16 node were implemented with a new proposed router to solve packets conflict problem. This network has low resources, where the network utilization ratio of slices is about 24% from the available resources and the maximum frequency 102.093MHz. The total consumption power is about 150 mW for the network, where the consumption static power is 32 mW only. The router in this network has a schedule with a fixed priority, which leads to data flowing without any conflict among packets. Moreover, the crossbar in this router consists of one multiplexer, counter and without additional inputs buffers unlike traditional crossbar, which consists of five multiplexer with multiple input buffers. This router is implemented and tested on the FPGA Spartan 3A (XC3S700A) kit.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133027662","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677768
Rand Hussam Ali, A. Khidhir
The aim of this research is to enhance the astronomical image, specifically the crescent image. Millions of Muslims care of monitoring the new crescent to determine the beginning of the fasting month (Ramadan), Eid Al-Fitr(Islamic Eid), and the beginning of the Hijri calendar. These timings are based on the appearance of the crescent in the sky. Because it is very difficult to detect the new crescent during day time, it is important to develop a technique to help detecting it. In the proposed method, the image restoration technique has been used to extract the crescent image from the telescope. The captured image is very noisy due to blurring and weather factors. This noise reduces the quality of the image. In this study, some of crescent images have been captured during the day time, where the crescent age was less than 50 hours before or after the new moon by using a portable digital camera installed on the telescope. Both, the deconvolution and De-Blurring technique with Hanning filter have been used to enhance the crescent's image. This indicates that the Wiener filter is a versatile and powerful technique for de-blurring and noise removal which can be successfully used in taking the crescent's images. In fact, our algorithm's performance was compared with that of the Wiener filter, Blind deconvolution, and Lucy Richardson algorithm. The resulted enhanced images show the crescent's image as can be seen visibly and can be recognized by the human eye. We discovered that and that Wiener filter deconvolution method is better than Lucy Richardson algorithm.
{"title":"Enhancement of Daytime Crescent Image Using Wiener Filter Based De-Blurring Technique","authors":"Rand Hussam Ali, A. Khidhir","doi":"10.1109/ICCITM53167.2021.9677768","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677768","url":null,"abstract":"The aim of this research is to enhance the astronomical image, specifically the crescent image. Millions of Muslims care of monitoring the new crescent to determine the beginning of the fasting month (Ramadan), Eid Al-Fitr(Islamic Eid), and the beginning of the Hijri calendar. These timings are based on the appearance of the crescent in the sky. Because it is very difficult to detect the new crescent during day time, it is important to develop a technique to help detecting it. In the proposed method, the image restoration technique has been used to extract the crescent image from the telescope. The captured image is very noisy due to blurring and weather factors. This noise reduces the quality of the image. In this study, some of crescent images have been captured during the day time, where the crescent age was less than 50 hours before or after the new moon by using a portable digital camera installed on the telescope. Both, the deconvolution and De-Blurring technique with Hanning filter have been used to enhance the crescent's image. This indicates that the Wiener filter is a versatile and powerful technique for de-blurring and noise removal which can be successfully used in taking the crescent's images. In fact, our algorithm's performance was compared with that of the Wiener filter, Blind deconvolution, and Lucy Richardson algorithm. The resulted enhanced images show the crescent's image as can be seen visibly and can be recognized by the human eye. We discovered that and that Wiener filter deconvolution method is better than Lucy Richardson algorithm.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129480487","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677654
Warqaa Hashim, Makram Alkhaled, A. Al-Naji, I. Al-Rayahi
Jaundice or Hyperbilirubinemia is a very common condition that affects newborns in their first few weeks of life. The main cause of jaundice is the high level of bilirubin substance in the blood. As bilirubin is toxic to the brain cells, acute bilirubin encephalopathy can occur in cases of extreme jaundice. This condition can result in brain trauma and lead to Kernicterus. Thus, a timely diagnosis and treatment can help in preventing long-term damage. Many jaundice diagnosis techniques that are based on computer vision and image processing were proposed in literature. In this paper we present a thorough review on most of these techniques, highlight their pros and cons, and compare between them in terms of the method used, advantages, limitations, and the region of interest selected for processing.
{"title":"A Review on Image Processing Based Neonatal Jaundice Detection Techniques","authors":"Warqaa Hashim, Makram Alkhaled, A. Al-Naji, I. Al-Rayahi","doi":"10.1109/ICCITM53167.2021.9677654","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677654","url":null,"abstract":"Jaundice or Hyperbilirubinemia is a very common condition that affects newborns in their first few weeks of life. The main cause of jaundice is the high level of bilirubin substance in the blood. As bilirubin is toxic to the brain cells, acute bilirubin encephalopathy can occur in cases of extreme jaundice. This condition can result in brain trauma and lead to Kernicterus. Thus, a timely diagnosis and treatment can help in preventing long-term damage. Many jaundice diagnosis techniques that are based on computer vision and image processing were proposed in literature. In this paper we present a thorough review on most of these techniques, highlight their pros and cons, and compare between them in terms of the method used, advantages, limitations, and the region of interest selected for processing.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133780654","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677676
M. G. Alfahdawi, K. Alheeti, S. S. Al-Rawi
Object recognition system is an automobile safety system designed for the safety of the autonomous vehicle and other traffic participants and reduces collision risk. Road accidents have long been a significant issue involving loss of life and property. So recent years have seen rapid developments in autonomous and semi-autonomous vehicles. Autonomous vehicles are a comprehensive solution built for safety and comfort on the roads. This solution has many challenges. One of these challenges is to spot and recognize obstacles while navigating. As humans do, the only way to discover and recognize these obstacles is to see them. Therefore, vision systems are an essential part of this type of vehicle. This paper proposed a vision-based system for autonomous vehicles to recognize objects and traffic lights on the road. The proposed system contains three phases: image pre-processing, feature extraction, and classification. In the first phase, some image pre-processing techniques are applied to prepare and improve the input images, consisting of three stages: convert color images to grayscale, histogram equalization, and image resize. In the second phase, extraction of the features from images using Principal Component Analysis (PCA). In the third phase, the extracted features are fed as input to the proposed One-dimensional Convolutional Neural Network (1D-CNN) model for object classification and recognition. The results show that the proposed CNN model achieved a high recognition rate where the classification precision rate reached 100%, and the error rate is 0%. The low number of false alarms and the high precision rate proves that the proposed system performs very well in recognizing the objects.
{"title":"Object Recognition System for Autonomous Vehicles Based on PCA and 1D-CNN","authors":"M. G. Alfahdawi, K. Alheeti, S. S. Al-Rawi","doi":"10.1109/ICCITM53167.2021.9677676","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677676","url":null,"abstract":"Object recognition system is an automobile safety system designed for the safety of the autonomous vehicle and other traffic participants and reduces collision risk. Road accidents have long been a significant issue involving loss of life and property. So recent years have seen rapid developments in autonomous and semi-autonomous vehicles. Autonomous vehicles are a comprehensive solution built for safety and comfort on the roads. This solution has many challenges. One of these challenges is to spot and recognize obstacles while navigating. As humans do, the only way to discover and recognize these obstacles is to see them. Therefore, vision systems are an essential part of this type of vehicle. This paper proposed a vision-based system for autonomous vehicles to recognize objects and traffic lights on the road. The proposed system contains three phases: image pre-processing, feature extraction, and classification. In the first phase, some image pre-processing techniques are applied to prepare and improve the input images, consisting of three stages: convert color images to grayscale, histogram equalization, and image resize. In the second phase, extraction of the features from images using Principal Component Analysis (PCA). In the third phase, the extracted features are fed as input to the proposed One-dimensional Convolutional Neural Network (1D-CNN) model for object classification and recognition. The results show that the proposed CNN model achieved a high recognition rate where the classification precision rate reached 100%, and the error rate is 0%. The low number of false alarms and the high precision rate proves that the proposed system performs very well in recognizing the objects.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133829876","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677691
M. I. H. Al-Janabi, K. Alheeti, A. Alaloosy
Attack detection is important for wireless networks and communications generally. Ship ad hoc networks (SANET) are a subset of wireless networks that are vulnerable to denial of service attacks. These attacks are one of the main challenges facing maritime networks, especially dedicated networks because of their weak infrastructure, which makes it easier for these networks to be exposed to this type of attacks. To maintain a secure connection and increase the durability of that connection, an accurate attack detection system must be built. In this paper, we used deep learning algorithm to classify data as either attack or safe. we generated the dataset by building a scenario for the SANET in the network simulator (ns-2). AODV was used as the routing protocol in this simulation, AODV reduces the burden on the network compared with the other protocols (reduces messages flooding in the network). The Convolutional Neural Network (CNN) model were applied to the dataset. The results show that the Convolutional Neural Network have the ability to detect attacks with higher performance. The experimental results showed that the data set that was generated with CNN model as the base classifier produced the best performance in terms of classification precision by 99%.
{"title":"Classification for SANET Based on Convolutional Neural Networks","authors":"M. I. H. Al-Janabi, K. Alheeti, A. Alaloosy","doi":"10.1109/ICCITM53167.2021.9677691","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677691","url":null,"abstract":"Attack detection is important for wireless networks and communications generally. Ship ad hoc networks (SANET) are a subset of wireless networks that are vulnerable to denial of service attacks. These attacks are one of the main challenges facing maritime networks, especially dedicated networks because of their weak infrastructure, which makes it easier for these networks to be exposed to this type of attacks. To maintain a secure connection and increase the durability of that connection, an accurate attack detection system must be built. In this paper, we used deep learning algorithm to classify data as either attack or safe. we generated the dataset by building a scenario for the SANET in the network simulator (ns-2). AODV was used as the routing protocol in this simulation, AODV reduces the burden on the network compared with the other protocols (reduces messages flooding in the network). The Convolutional Neural Network (CNN) model were applied to the dataset. The results show that the Convolutional Neural Network have the ability to detect attacks with higher performance. The experimental results showed that the data set that was generated with CNN model as the base classifier produced the best performance in terms of classification precision by 99%.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"25 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129493562","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677725
Baraa H. Kareem, W. Bhaya
The amount and diversity of malware keeps growing while the same basic attack techniques are being used. A firewall is a network security key component that filters inbound and outbound network packets as per predefined security rules. Even though firewalls are an effective defense against some attacks, they have security flaws that can be leveraged in other circumstances. In the present work, it is claimed that an ontology-based semantic firewall and machine learning algorithms can effectively enhance the firewall and protect the LAN. This paper proposes an ontology-based model for the semantic firewall as an effort to explore its effectiveness. The method used in this paper is based on Description Logic (DL) Reasoners, Ontology APIs, and Semantic Web Languages (OWL and SWRL). The proposed semantic firewall takes its decisions of anomalies detection based on a set of protection rules of the ontology-based model. As a result, the proposed approach achieves a detection accuracy of 93%. The conclusion is drawn that the presented ontology classifier gives an understandable model of a semantic firewall (SWF) that offers candid and human-interpretable decision rules, as with other machine learning models.
{"title":"The Protection of LAN Using Semantic Firewalls","authors":"Baraa H. Kareem, W. Bhaya","doi":"10.1109/ICCITM53167.2021.9677725","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677725","url":null,"abstract":"The amount and diversity of malware keeps growing while the same basic attack techniques are being used. A firewall is a network security key component that filters inbound and outbound network packets as per predefined security rules. Even though firewalls are an effective defense against some attacks, they have security flaws that can be leveraged in other circumstances. In the present work, it is claimed that an ontology-based semantic firewall and machine learning algorithms can effectively enhance the firewall and protect the LAN. This paper proposes an ontology-based model for the semantic firewall as an effort to explore its effectiveness. The method used in this paper is based on Description Logic (DL) Reasoners, Ontology APIs, and Semantic Web Languages (OWL and SWRL). The proposed semantic firewall takes its decisions of anomalies detection based on a set of protection rules of the ontology-based model. As a result, the proposed approach achieves a detection accuracy of 93%. The conclusion is drawn that the presented ontology classifier gives an understandable model of a semantic firewall (SWF) that offers candid and human-interpretable decision rules, as with other machine learning models.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121643910","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677684
A. M. Jumaa
This paper presents the analytical solution for a mathematical model of heat transfer by free convection which arises from the flowing of fluid on a porous plate. The plate is laid on a horizontal position with temperature source at the surface of the plate that is different from the surrounding atmosphere temperature. The governing mathematical equations, which have been established, consist of partial differential equations with some boundary conditions. The model has been converted into a boundary value problem, and in this case, an analytical solution was adopted by using a perturbation of the functions which are playing the important role in the solution of the system like temperature, velocity. These functions help to find the necessary factor that controls the stability of the problem. The outcome results showed that the wave number has the significant effect in the stability.
{"title":"Analytical Treatment to Find Stability of the System of Partial Equations Arising from Heat Transfer on A porous Plate","authors":"A. M. Jumaa","doi":"10.1109/ICCITM53167.2021.9677684","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677684","url":null,"abstract":"This paper presents the analytical solution for a mathematical model of heat transfer by free convection which arises from the flowing of fluid on a porous plate. The plate is laid on a horizontal position with temperature source at the surface of the plate that is different from the surrounding atmosphere temperature. The governing mathematical equations, which have been established, consist of partial differential equations with some boundary conditions. The model has been converted into a boundary value problem, and in this case, an analytical solution was adopted by using a perturbation of the functions which are playing the important role in the solution of the system like temperature, velocity. These functions help to find the necessary factor that controls the stability of the problem. The outcome results showed that the wave number has the significant effect in the stability.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131601748","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677727
Z. Farej, Azhar W. Talab
with the rise of the Internet of Things (IoT)., wireless mesh networks have gained prominence, and there are already some successful technologies that use low-cost, low-power wireless devices to construct such network topologies. Bluetooth low energy (BLE) has become a recent topic of research in both the Internet and the wireless industry. ABLE wireless mesh network protocol utilizes the broadcasting capability of such wireless transmissions. In this paper, a sample of the BLE mesh network is proposed for smart lighting control and evaluation of the Bluetooth extended range communication. Three nodes for the ESP-32 evaluation board and NRF mesh application for android are used in this sample to provision and configure the BLE mesh nodes. These boards are programmed with the BLE mesh program and the Bluetooth range can be extended by a factor of three according to the node's deployment method. As well as network flexibility and coverage area are increased with more optional lighting control processes.
{"title":"Extended Range Evaluation of a BLE Mesh Network for Control Application","authors":"Z. Farej, Azhar W. Talab","doi":"10.1109/ICCITM53167.2021.9677727","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677727","url":null,"abstract":"with the rise of the Internet of Things (IoT)., wireless mesh networks have gained prominence, and there are already some successful technologies that use low-cost, low-power wireless devices to construct such network topologies. Bluetooth low energy (BLE) has become a recent topic of research in both the Internet and the wireless industry. ABLE wireless mesh network protocol utilizes the broadcasting capability of such wireless transmissions. In this paper, a sample of the BLE mesh network is proposed for smart lighting control and evaluation of the Bluetooth extended range communication. Three nodes for the ESP-32 evaluation board and NRF mesh application for android are used in this sample to provision and configure the BLE mesh nodes. These boards are programmed with the BLE mesh program and the Bluetooth range can be extended by a factor of three according to the node's deployment method. As well as network flexibility and coverage area are increased with more optional lighting control processes.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121673182","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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