{"title":"Intelligent Traffic Management Systems: A review","authors":"Hesham. A. Sakr, Magda I. El-Afifi, plvar team","doi":"10.21608/njccs.2023.321169","DOIUrl":"https://doi.org/10.21608/njccs.2023.321169","url":null,"abstract":"","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145878","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}
Yusuf, Musa, FAKI, Ageebee Silas, Adelaiy e, Ishaya Oluwasegun
{"title":"Honey Algorithm for Securing and Identifying Hackers in a Pervasive Environment","authors":"Yusuf, Musa, FAKI, Ageebee Silas, Adelaiy e, Ishaya Oluwasegun","doi":"10.21608/njccs.2023.321171","DOIUrl":"https://doi.org/10.21608/njccs.2023.321171","url":null,"abstract":"The emergence of the pervasive device has made log-in details more vulnerable to unauthorized access and damage. This is due to frequent changes in users of pervasive devices and the close affinity of many attackers. Most models available only prevent attackers from gaining access to user login details. This study proposed a model that both detects and reveals the attacker's identity using the strength of the Honey Encryption algorithm with the ability to build a randomized message encoding called a Distribution-Transforming Encoder (DTE). The proposed model has the capability of providing a guide to security operatives to track and arrest the suspected perpetrator. An evaluation of the model was carried out which shows a 62% success of revealing attackers. A further examination of the model shows that 21% of the attackers could gain access through close affinity to log-in users. An extension of the proposed model can be achieved by improving the detection rate of the model.","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135145896","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}
{"title":"The Role of data mining in healthcare Sector","authors":"N. Mansour, Hesham Sakr","doi":"10.21608/njccs.2022.279492","DOIUrl":"https://doi.org/10.21608/njccs.2022.279492","url":null,"abstract":"","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126325229","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}
Hegazi. Ibrahim, nesma abdelmawla, nile research lab
{"title":"IoT-Enabled Smart Grid using PV panel","authors":"Hegazi. Ibrahim, nesma abdelmawla, nile research lab","doi":"10.21608/njccs.2022.279508","DOIUrl":"https://doi.org/10.21608/njccs.2022.279508","url":null,"abstract":"","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116622505","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}
Hegazi. Ibrahim, nesma abdelmawla, nile research lab
{"title":"Eco-Friendly Dehydrator Machine for Food Recycling: A Waste Management System","authors":"Hegazi. Ibrahim, nesma abdelmawla, nile research lab","doi":"10.21608/njccs.2022.279497","DOIUrl":"https://doi.org/10.21608/njccs.2022.279497","url":null,"abstract":"","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125511365","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}
{"title":"A Survey of Deep Learning Algorithms and its Applications","authors":"Arwa E. Abulwafa","doi":"10.21608/njccs.2022.139054.1000","DOIUrl":"https://doi.org/10.21608/njccs.2022.139054.1000","url":null,"abstract":"","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"458 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115272158","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}
{"title":"A Fog Based Smart Traffic Management System","authors":"Shaimaa A. Hussein, Ahmed E. Zaki","doi":"10.21608/njccs.2022.244478","DOIUrl":"https://doi.org/10.21608/njccs.2022.244478","url":null,"abstract":"Recently, urban mobility has become one of the most pressing issues in today's cities, and it must be addressed with caution. The exponential increase in the number of cars has a negative influence on the transportation system that most communities rely on. One of the most important aspects of transportation system is traffic control, which is reliant on a series of coordinated traffic lights. Smart traffic lights not only can receive and analyses the real time traffic data but also can help to alleviate traffic congestion by accurately predicting the waiting time for each traffic lane at the intersections. This can help to enhance traffic flow and, as a result, the overall performance of the transportation system. The proposed Smart Traffic System (STS) not only an automated IoT based traffic measuring system but it also calculates the ideal waiting time for each traffic lane. Calculating the optimal waiting time of each lane of the intersections can reduce the average waiting time. The objective is to provide accurately real-time traffic updates on traffic congestion according to the size of vehicles and their location relative to the traffic lights. Urgent cases for emergency vehicles also has been taken into consideration. Ultrasonic sensors and a lateral scanning approach are employed in the proposed STS which is suitable for using on real traffic roads in various roadway environments. STS adjusted to accurately measure traffic volumes according to the size of vehicles and their locations relative to the traffic light in real time. A prototype is implemented to evaluate the feasibility of the model. Simulation results show good accuracy in vehicles detection, low relative error in road occupancy estimation, the least delay, and highest throughput compared to other works.","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122449161","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}
{"title":"Review: Mask R-CNN Models","authors":"Esraa Hassan, Nora El-Rashidy, fatma M. Talaa","doi":"10.21608/njccs.2022.280047","DOIUrl":"https://doi.org/10.21608/njccs.2022.280047","url":null,"abstract":"Instance segmentation is a challenging computer vision task that requires the prediction of object instances and their per-pixel segmentation mask. This makes it a hybrid of semantic segmentation and object detection. It detects and delineates each distinct object of interest appearing in an image. Mask R-CNN model is common for instance segmentation that has several versions for improving this task. We proposed a simple comparison between Fifteenth different version frameworks from Mask-RCNN for object instance segmentation. Our survey representing the difference between the popular versions of Mask R-CNN. The Mask R-CNN method extends Faster R-CNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition. The results in most versions were implemented on of the COCO dataset that created for instance segmentation tasks.","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115579835","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}
{"title":"Green Cloud Computing (GCC), Applications, Challenges and Future Research Directions","authors":"Nesma Abd El-mawla, H. Ibrahim","doi":"10.21608/njccs.2022.244471","DOIUrl":"https://doi.org/10.21608/njccs.2022.244471","url":null,"abstract":"Cloud computing is a rapidly evolving field of communication and information technology, posing new environmental issues. Because cloud computing technologies are scalable, stable, and trustworthy, and provide great performance at a cheap cost, they have a wide range of application fields. The cloud computing revolution is reshaping modern networking and presenting both economic and technological benefits, as well as potential environmental protection prospects. These technologies have the potential to boost energy efficiency while also lowering carbon emissions and e-waste. These characteristics have the potential to turn cloud computing into green cloud computing. The main achievements of green cloud computing are reviewed in this survey. First, a brief introduction to cloud computing is provided. Following that, recent studies and advancements are discussed, with environmental issues being addressed especially. Finally, future research prospects for green cloud computing are discussed, as well as open issues.","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126861815","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}
{"title":"Proposed Model for Sustainable and Scalable Vertical Farm","authors":"Hegazi. Ibrahim, Nesma Abd El-mawla, Green Team","doi":"10.21608/njccs.2022.244469","DOIUrl":"https://doi.org/10.21608/njccs.2022.244469","url":null,"abstract":"This project summarizes the implementation of vertical farming that uses a Wi-Fi network to communicate with sensors and actuators from multiple nodes. It addresses the issue of ordinary vertical farms, which require the user to monitor it occasionally to provide fertilizer and water. The system can be easily configured to automatically control the supply of nutrients, water, and light requirements for various plant types through a mobile application enabled Interface. The mobile application dashboard can further provide a complex analysis of the whole system by collecting values from different sensors. The designed vertical farm system is power efficient, self-sustained, and can be set up easily by the user as each vertical rack acts as a single node or module. The user only needs to plant the seeds and fill up the tanks. Due to the modular approach, the system is also scalable without the requirement of more complicated materials or wiring.","PeriodicalId":277392,"journal":{"name":"Nile Journal of Communication and Computer Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128501431","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}