{"title":"UCM-AODV: Utility-based Cache Management for AODV Vehicular Ad Hoc Networks","authors":"Ayat Nabieh, M. Sharaf, S. Ramadan, M. Marie","doi":"10.1109/ICICIS46948.2019.9014718","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014718","url":null,"abstract":"Data access is a crucial topic that has drawn a big attention in VANETs. One can attribute this to the prevalent network segmentation introduced by the node's mobility. Hence, cooperative cache scheme has been introduced to minimize network latency. Consequently, cooperative caching (CC) improves the data access performance in a VANETs environment. CC mandates multiple caching vehicles to share and manage cached contents. This work provides a novel system model in which cache replacement can be greatly avoided if the overheard data item (DI) is of no utility. The proposed caching scheme measures the popularity of a DI according to its utility as either high or low, based on relevant parameters. A DI is prefetched when its utility is high. Otherwise, overhearing nodes simply discard a DI if it is of low utility. The performance of the proposed scheme has been evaluated using NS2 simulator and is compared with other cooperative caching schemes. Performance analysis shows that the proposed model outperforms caching strategies found in literature. In addition, it shows a serious mitigation in delay and control overhead compared with the standard AODV.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122903043","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":"Classical and Intelligent Multivariable Controllers for Aerosonde UAV","authors":"E. N. Mobarez, A. Sarhan, M. Ashry","doi":"10.1109/ICICIS46948.2019.9014824","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014824","url":null,"abstract":"In this treatise four control methods were proposed for Aerosonde UAV in both lateral and longitudinal trajectory. Two classical and two intelligent control techniques are used. The four methods are proposed to improve the autopilot response of Aerosonde. The strength and durability of the autopilot system to incomplete model (knowledge), the repudiation of wind disorder, and handle with effect of sensor's noise are theorize as essential section for Comparison analysis of the various control technicality. The 1st classical autopilot, the PID genetically tuned is proposed. Fractional order PID (FOPID) is considered as the 2nd classical control autopilot. Fuzzy controller is suggested as the 1st intelligent control technique. The 2nd intelligent control technique is adaptive neuro fuzzy inference system controller. The proposed controllers are utilized to the nonlinear and MIMO UAV model. The main substantial in this paper is stratify FOPID controller for the first time on UAV's. The comparison simulation consequence affirms the influence of this controllers in different scenario and also the effective of the ANFIS controller over the other controllers.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122907161","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}
O. Elsayed, Noura Ahmed Mohamed Marzouky, Esraa Atef, M. Salem
{"title":"Abnormal Action detection in video surveillance","authors":"O. Elsayed, Noura Ahmed Mohamed Marzouky, Esraa Atef, M. Salem","doi":"10.1109/ICICIS46948.2019.9014712","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014712","url":null,"abstract":"The growing number of anomalies happening in indoor and outdoor environments calls for accurate and robust action recognition systems. These anomalies could vary from theft, destruction of public property or even fighting innocents. The aim of this paper is to introduce a new algorithm based on machine learning paradigm to detect human actions and to label them as normal or abnormal. The algorithm starts by testing two different human detectors, cascade object detector and Faster Region Convolutional Neural Network for Human Detection (FRCNNHD). Both detectors were trained using widely available datasets. Afterwards, detected human figures are ex-tracted to form a video patch that represents human motion. For action recognition, we applied the Motion History Image to extract static features of motion. The actions are then classified using the Support Vector Machine (SVM). Finally, actions with low recognition confidence are labeled as “abnormal actions”. Experimental results on two datasets show the accuracy of our algorithm on learned actions.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123416250","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":"Examining Hyperparameters of Neural Networks Trained Using Local Search","authors":"Ahmed Aly, G. Guadagni, J. Dugan","doi":"10.1109/ICICIS46948.2019.9014658","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014658","url":null,"abstract":"Deep neural networks (DNNs) have been found useful for many applications. However, training and designing those networks can be challenging and is considered more of an art or an engineering process than rigorous science. In this regard, the important process of choosing hyperparameters is relevant. In addition, training neural networks with derivative-free methods is somewhat understudied. Particularly, with regards to hyperparameter selection. The paper presents a small-scale study of 3 hyperparameters choice for convolutional neural networks (CNNs). The networks were trained with two single-candidate optimization algorithms: Stochastic Gradient Descent (derivative-based) and Local Search (derivative-free). The CNN is trained on a subset of the FashionMNIST dataset. Experimental results show that hyperparameter selection can be detrimental for Local Search, especially regarding network parametrization. Moreover, the best hyperparameter choices didn't match for both algorithms. Future investigation into the training dynamics of Local Search is likely needed.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129168571","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":"Forecast and Manipulation of HCV Eradication in Egypt based on its National Screening Project","authors":"Norhan Khallaf, Nancy El-Hcfnawv, Osama Abd-El-Raouf","doi":"10.1109/ICICIS46948.2019.9014654","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014654","url":null,"abstract":"The availability of effective direct-acting antiviral therapy for hepatitis C virus (HCV) has led to a need for inclusive screening pathways. Since 2016, the World Health Organization (WHO) has advocated for the elimination of hepatitis C virus (HCV) as a public health threat by 2030. Some research also predicted the elimination of virus c by this year. In 2017 there was a screening project in nine Upper Egypt Provinces including Giza, Fayoum, Beni-Suef, Minya, Assiut, Sohag, Qena, Luxor and Aswan with a total number of two million citizens screened. As this was a limited screening, we had to forecast the prevalence in the other provinces. Now there is a new screening program which gave us new accurate data. Based on the new data, this paper proposed sufficient attributes and statistics about the rate of HCV infection and capability of healthcare servers. These attributes include gender, Socioeconomic and education characteristic in different age groups in each province. The new screening strategic plan will cover all of Egyptian citizens aging from 15 to 79; and it's done in three phases. The first and second phases of the screening are completed but the third phase is not finished yet. So, we predicted the remaining data in the third phase by using artificial neural network, as it is an accurate prediction machine-learning tool. The artificial neural network helped to train the data of some phases and test the prediction data of the other phases with higher performance. As the data collected from two phases were not sufficient to the neural network to predict the number of HCV patients in the third phase, we had to use the Interpolating Methods to increase the data. Using the artificial neural network and queuing mathematical model, will predict which year virus C will be eliminated. According to treatment protocol of HCV will be expected the total cost of HCV patient waited in the queue.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121276176","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":"Secure Multiparty Computation via Homomorphic Encryption Library","authors":"S. Ghanem, I. Moursy","doi":"10.1109/ICICIS46948.2019.9014698","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014698","url":null,"abstract":"Secure multiparty computation (MPC) is required when individuals want to privately evaluate a function over their inputs. While evaluating a common function, the participants do not reveal their inputs to each other. A homomorphic encryption (HE) scheme allows the evaluation of arbitrary computations on encrypted data without decrypting it. In theory, realizing MPC through a HE scheme is a simple and efficient approach. However, despite its promising theoretical power, the practical side of the approach remains underdeveloped. In this work, motivated by the rising MPC applications, e.g. cloud computation, a HE library is extended to provide the necessary methods for MPC. In particular HElib that implements Brakerski-Gentry-Vaikuntanathan (BGV), a HE scheme, is extended to support MPC protocols. This extension provides a broadcast protocol for the generation of a global public key by $N$ parties, where each party maintains a share of the corresponding private key. In addition, the homomorphic evaluation of functions on ciphertexts encrypted by the public key is extended. Furthermore, a decryption broadcast protocol is provided where ciphertexts are decrypted using the individual shares of the private key. The proposed extension can be adapted to other HE libraries. A second contribution of this work, is a $2^{n}$ factorial experimental design and analysis to study the memory, computation, and communication costs of HElib and the proposed extension. Four main factors are identified: the security parameter, the plaintext space, the number of levels of the evaluation function, and the number of parties. The proposed extensions are shown to be effective and efficient. On the experimented setup, it takes about 0.2 sec for multiparty key generation and 0.06 sec for multiparty decryption.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128418256","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":"OA18: A New Office Actions Benchmark","authors":"Bassel S. Chawkv, M. Marey, Howida A. Shedeed","doi":"10.1109/ICICIS46948.2019.9014841","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014841","url":null,"abstract":"Action recognition is one of the current hot topics in the literature due to its important applications. To better evaluate the existing models, several datasets are publicly available and range in scale from synthetic datasets to complex realistic datasets. However, it seems that very few datasets are domain specific. This paper publishes a new recorded dataset that studies 18 domain specific human actions, specifically, actions performed by employees inside an office. This is the first published dataset in the literature for the office domain. Moreover, a python-based software is developed and used for labeling the recoded videos and presented for future usages. The recorded dataset is designed not only to study several existing challenges in the literature which include the variation of viewpoints for the same class and the issue of shaky videos, but we also cover the usage of deep learning techniques on this small dataset by performing data augmentation and transfer learning.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131227348","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":"2019 IEEE Ninth International Conference on Intelligent Computing and Information Systems","authors":"","doi":"10.1109/icicis46948.2019.9014771","DOIUrl":"https://doi.org/10.1109/icicis46948.2019.9014771","url":null,"abstract":"","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115510952","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":"Road Surface Quality Detection using Smartphone Sensors: Egyptian Roads Case Study","authors":"Aya El-Kady, Karim Emara, M. ElEliemy, E. Shaaban","doi":"10.1109/ICICIS46948.2019.9014721","DOIUrl":"https://doi.org/10.1109/ICICIS46948.2019.9014721","url":null,"abstract":"Road anomalies have significant negative effects on both passengers and vehicles such as traffic congestion and accidents. Nowadays, smartphones are ubiquitous and used by so many drivers, at least to know the driving directions to their destination. Several studies utilized this observation and used the smartphone embedded sensors to detect road anomalies. In this paper, we evaluate the effectiveness of this methodology with sensor readings obtained while driving in Egyptian roads. An android application is developed to record sensor readings while driving over the road anomalies. Four datasets are collected for different streets in Cairo of total duration of 80 minutes and about 50K records. To automatically label these datasets, two clustering techniques (K-Means and DBSCAN) are evaluated to give the ground truth for the sensor readings if they represent road anomalies or normal road surface. It is noticed that DBSCAN can accurately cluster sensor readings than K-Means can do. Finally, a classification model is built to classify unseen sensor readings and identify the road surface quality. An accuracy of 96% can be obtained from the built classifier confirming the effectiveness of the adopted methodology in evaluating the road surface quality in Egypt.","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125173919","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":"Conference Steering Committee","authors":"R. Cook","doi":"10.1109/icicis46948.2019.9014794","DOIUrl":"https://doi.org/10.1109/icicis46948.2019.9014794","url":null,"abstract":"","PeriodicalId":200604,"journal":{"name":"2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073719","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}