Pub Date : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043262
Rukayya Umar, M. Olalere, I. Idris, Raji Abdullahi Egigogo, G. Bolarin
As this paper has expounded, the techniques against DDoS attacks borrow greatly from the already tested traditional techniques. However, no technique has proven to be perfect towards the full detection and prevention of DDoS attacks. Intrusion detection system (IDS) using machine learning approach is one of the implemented solutions against harmful attacks. However, achieving high detection accuracy with minimum false positive rate remains issue that still need to be addressed. Consequently, this study carried out an experimental evaluation on various machine learning algorithms such as Random forest J48, Naïve Bayes, IBK and Multilayer perception on HTTP DDoS attack dataset. The dataset has a total number of 17512 instances which constituted normal (10256) and HTTP DDoS (7256) attack with 21 features. The implemented Performance evaluation revealed that Random Forest algorithm performed best with an accuracy of 99.94% and minimum false positive rate of 0.001%.
{"title":"Performance Evaluation of Machine Learning Algorithms for Hypertext Transfer Protocol Distributed Denial of Service Intrusion Detection","authors":"Rukayya Umar, M. Olalere, I. Idris, Raji Abdullahi Egigogo, G. Bolarin","doi":"10.1109/ICECCO48375.2019.9043262","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043262","url":null,"abstract":"As this paper has expounded, the techniques against DDoS attacks borrow greatly from the already tested traditional techniques. However, no technique has proven to be perfect towards the full detection and prevention of DDoS attacks. Intrusion detection system (IDS) using machine learning approach is one of the implemented solutions against harmful attacks. However, achieving high detection accuracy with minimum false positive rate remains issue that still need to be addressed. Consequently, this study carried out an experimental evaluation on various machine learning algorithms such as Random forest J48, Naïve Bayes, IBK and Multilayer perception on HTTP DDoS attack dataset. The dataset has a total number of 17512 instances which constituted normal (10256) and HTTP DDoS (7256) attack with 21 features. The implemented Performance evaluation revealed that Random Forest algorithm performed best with an accuracy of 99.94% and minimum false positive rate of 0.001%.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","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":"130056487","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043283
F. I. Lawan, L. Ismaila, Steve A. Adeshina, H. I. Muhammed, L. Csató
In effort to productively utilize the exponential growth of image analysis and learning capability of Neural Networks (NN), we present our work which is dedicated to developing and training a deep neural network to extract meaningful patterns from a set of labeled data i.e. making generalizations. We show that Deep Neural Networks (DNNs) can learn feature representations that can be successfully applied in a wide spectrum of application domains. We showed how DNNs are applied to classification problems, grading of fresh tomato fruits based on their physical qualities using supervised learning approach. We achieved a result of about 60% accuracy using our local dataset which is quiet reasonable than using other standardized dataset as in the case of other researchers. Additionally, we are very sure of getting better result by fine-tuning some of our parameters because out network learns to generalize as the number iterations increases and so also the accuracy of predictions.
{"title":"Deep Learning Methods for Filter Extraction in Tomato fruits","authors":"F. I. Lawan, L. Ismaila, Steve A. Adeshina, H. I. Muhammed, L. Csató","doi":"10.1109/ICECCO48375.2019.9043283","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043283","url":null,"abstract":"In effort to productively utilize the exponential growth of image analysis and learning capability of Neural Networks (NN), we present our work which is dedicated to developing and training a deep neural network to extract meaningful patterns from a set of labeled data i.e. making generalizations. We show that Deep Neural Networks (DNNs) can learn feature representations that can be successfully applied in a wide spectrum of application domains. We showed how DNNs are applied to classification problems, grading of fresh tomato fruits based on their physical qualities using supervised learning approach. We achieved a result of about 60% accuracy using our local dataset which is quiet reasonable than using other standardized dataset as in the case of other researchers. Additionally, we are very sure of getting better result by fine-tuning some of our parameters because out network learns to generalize as the number iterations increases and so also the accuracy of predictions.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"1645 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":"115832774","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043290
Godwin Aboi, Nyangwarimam Obadiah Ali, Ezechukwu Kalu Ukiwe, Sadiq Thomas, Omotayo Oshiga, D. B. Jonathan
Water makes up about seventy (70) percent of the universe. This singular statistic implies that water is readily available; hence it has been put to numerous uses for the betterment of the human race. Hydroelectricity generation is has many advantages, which includes its flexibility in use, low maintenance cost, and availability. Although hydroelectricity poses less climate risk when compared to other methods, the equipment and machinery used together with the dam constructed have several associated environmental hazards. The problems include loss of habitat, flooding, degradation of water quality, loss of aquatic life, shortage of water. If the Government does not address the prevailing dangers by enacting legislative policies, resettlement of people affected by those areas and through other social interventions, the effects will keep hitting harder on the communities to an extent that it may be uninhabitable [1]. This paper reviews the environmental impact of hydroelectricity generation in Nigeria. It talks about the benefits derived and various ways it affects our habitat. It also proposes ways of reducing these effects to maximize the positive potentials derived from this method of power generation.
{"title":"Hydroelectricity In Nigeria: A Review Of The Associated Environmental Impact","authors":"Godwin Aboi, Nyangwarimam Obadiah Ali, Ezechukwu Kalu Ukiwe, Sadiq Thomas, Omotayo Oshiga, D. B. Jonathan","doi":"10.1109/ICECCO48375.2019.9043290","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043290","url":null,"abstract":"Water makes up about seventy (70) percent of the universe. This singular statistic implies that water is readily available; hence it has been put to numerous uses for the betterment of the human race. Hydroelectricity generation is has many advantages, which includes its flexibility in use, low maintenance cost, and availability. Although hydroelectricity poses less climate risk when compared to other methods, the equipment and machinery used together with the dam constructed have several associated environmental hazards. The problems include loss of habitat, flooding, degradation of water quality, loss of aquatic life, shortage of water. If the Government does not address the prevailing dangers by enacting legislative policies, resettlement of people affected by those areas and through other social interventions, the effects will keep hitting harder on the communities to an extent that it may be uninhabitable [1]. This paper reviews the environmental impact of hydroelectricity generation in Nigeria. It talks about the benefits derived and various ways it affects our habitat. It also proposes ways of reducing these effects to maximize the positive potentials derived from this method of power generation.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"270 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":"122834906","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043288
Joseph Yisa Ndagi, J. Alhassan
Exponential growth experienced in Internet usage has paved the way to exploit users of the Internet, a phishing attack is one of the means that can be used to obtained victim confidential details unwittingly across the Internet. A high false-positive rate and low accuracy have been a setback in phishing detection. In this research 17 different supervised learning techniques such as RandomForest, Systematically Developed Forest (SysFor), Spectral Areas and Ratios Classifier (SPAARC), Reduces Error Pruning Tree (RepTree), RandomTree, Logic Model Tree (LMT), Forest by Penalizing Attributes (ForestPA), JRip, PART, Nearest Neighbor with Generalization (NNge), One Rule (OneR), AdaBoostM1, RotationForest, LogitBoost, RseslibKnn, Library for Support Vector Machine (LibSVM), and BayesNet were employed to achieve the comparative analysis of machine classifier. The performance of the classifier algorithms was rated using Accuracy, Precision, Recall, F-Measure, Root Mean Squared Error, Receiver Operation Characteristics Area, Root Relative Squared Error False Positive Rate and True Positive Rate using WEKA data mining tool. The research revealed that quite several classifiers also exist which if properly explored will yield more accurate results for phishing detection. RandomForest was found to be an excellent classifier that gives the best accuracy of 0.9838 and a false positive rate of 0.017. The comparative analysis result indicates the achievement of low false-positive rate for phishing classification which suggests that anti-phishing application developer can implement the machine learning classification algorithm that was discovered to be the best in this study to enhance the feature of phishing attack detection and classification.
{"title":"Machine Learning Classification Algorithms for Adware in Android Devices: A Comparative Evaluation and Analysis","authors":"Joseph Yisa Ndagi, J. Alhassan","doi":"10.1109/ICECCO48375.2019.9043288","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043288","url":null,"abstract":"Exponential growth experienced in Internet usage has paved the way to exploit users of the Internet, a phishing attack is one of the means that can be used to obtained victim confidential details unwittingly across the Internet. A high false-positive rate and low accuracy have been a setback in phishing detection. In this research 17 different supervised learning techniques such as RandomForest, Systematically Developed Forest (SysFor), Spectral Areas and Ratios Classifier (SPAARC), Reduces Error Pruning Tree (RepTree), RandomTree, Logic Model Tree (LMT), Forest by Penalizing Attributes (ForestPA), JRip, PART, Nearest Neighbor with Generalization (NNge), One Rule (OneR), AdaBoostM1, RotationForest, LogitBoost, RseslibKnn, Library for Support Vector Machine (LibSVM), and BayesNet were employed to achieve the comparative analysis of machine classifier. The performance of the classifier algorithms was rated using Accuracy, Precision, Recall, F-Measure, Root Mean Squared Error, Receiver Operation Characteristics Area, Root Relative Squared Error False Positive Rate and True Positive Rate using WEKA data mining tool. The research revealed that quite several classifiers also exist which if properly explored will yield more accurate results for phishing detection. RandomForest was found to be an excellent classifier that gives the best accuracy of 0.9838 and a false positive rate of 0.017. The comparative analysis result indicates the achievement of low false-positive rate for phishing classification which suggests that anti-phishing application developer can implement the machine learning classification algorithm that was discovered to be the best in this study to enhance the feature of phishing attack detection and classification.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"65 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":"116316654","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043286
Muhammad Kabir Idris, Moussa Mahamat Boukar, Steve A. Adeshina
Developing nations are faced with a lot of bad roads with potholes of different debt ranges, the maintenance and rehabilitation process by government agencies is an ongoing effort that requires periodic bad road inventory to guarantee safety. Bad roads are either identified by government agency’s survey teams or individual who volunteer to report these conditions to the authorities. Our research provided a simple but effective solution to aid in automatically reporting bad roads using smart-phones through measuring the pavement profile based on the vibration of a moving vehicle. In this article, we will explain how we used some a smart-phone in reading the vibration pattern, GPS location, speed and direction of a vehicle that drives through a pothole, these parameters are periodically streamed to a cloud application. We used standard deviation to measure the level of dispersion around a segmented set of streamed vehicle vibration to identify potholes of different sizes, we also used Artificial Intelligence - supervised learning algorithm (classification) to reduce the false positive error rates due to human behaviors. The final results show a distinct vibration levels between small pot-holes, speed bumps and big pot-holes, these values are displayed on map application to visualize the geographical locations of these pot-holes (Google maps)
{"title":"Analysis of Bad Roads Using Smart phone","authors":"Muhammad Kabir Idris, Moussa Mahamat Boukar, Steve A. Adeshina","doi":"10.1109/ICECCO48375.2019.9043286","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043286","url":null,"abstract":"Developing nations are faced with a lot of bad roads with potholes of different debt ranges, the maintenance and rehabilitation process by government agencies is an ongoing effort that requires periodic bad road inventory to guarantee safety. Bad roads are either identified by government agency’s survey teams or individual who volunteer to report these conditions to the authorities. Our research provided a simple but effective solution to aid in automatically reporting bad roads using smart-phones through measuring the pavement profile based on the vibration of a moving vehicle. In this article, we will explain how we used some a smart-phone in reading the vibration pattern, GPS location, speed and direction of a vehicle that drives through a pothole, these parameters are periodically streamed to a cloud application. We used standard deviation to measure the level of dispersion around a segmented set of streamed vehicle vibration to identify potholes of different sizes, we also used Artificial Intelligence - supervised learning algorithm (classification) to reduce the false positive error rates due to human behaviors. The final results show a distinct vibration levels between small pot-holes, speed bumps and big pot-holes, these values are displayed on map application to visualize the geographical locations of these pot-holes (Google maps)","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","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":"126709327","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043193
Fauwzziyyah O. Umar, L. Ismaila, I. Umar
Despite the regulatory measures, effective blood transfusion services still remain sadly unavailable to one of the world’s poorest and dense populations. Among other African countries that fail to meet World Health Organization (WHO) blood requirement in recent years, Our Experience in Nigeria and other convincing remarks show that blood is not in good circulation, especially for the needy who are in most cases exploited and eventually faced with serious health challenges due to unsafe blood transfusion leading to deadly infections and consequently death and other times, blood is totally unavailable. In view of this, we proposed and implemented a working system of blood bank service which ensures patients get quick access to blood donors of any type whether volunteer donors, replacement donors (family or friends), or compensated donors, in each case, mutual interest is protected. This system is designed to thrive even in the remotest of areas and easy for both young and old because it adopts the use of Unstructured Supplementary Service Data or USSD code, Short Message Service (SMS) and free toll line which makes the system available for both online and offline database queries. Our initial results show that, if this system is fully implemented, effective blood transfusion services will be in quick improvement in Nigeria and by extension Africa.
{"title":"The Prospect and Significance of Lifeline: An E-blood bank System","authors":"Fauwzziyyah O. Umar, L. Ismaila, I. Umar","doi":"10.1109/ICECCO48375.2019.9043193","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043193","url":null,"abstract":"Despite the regulatory measures, effective blood transfusion services still remain sadly unavailable to one of the world’s poorest and dense populations. Among other African countries that fail to meet World Health Organization (WHO) blood requirement in recent years, Our Experience in Nigeria and other convincing remarks show that blood is not in good circulation, especially for the needy who are in most cases exploited and eventually faced with serious health challenges due to unsafe blood transfusion leading to deadly infections and consequently death and other times, blood is totally unavailable. In view of this, we proposed and implemented a working system of blood bank service which ensures patients get quick access to blood donors of any type whether volunteer donors, replacement donors (family or friends), or compensated donors, in each case, mutual interest is protected. This system is designed to thrive even in the remotest of areas and easy for both young and old because it adopts the use of Unstructured Supplementary Service Data or USSD code, Short Message Service (SMS) and free toll line which makes the system available for both online and offline database queries. Our initial results show that, if this system is fully implemented, effective blood transfusion services will be in quick improvement in Nigeria and by extension Africa.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"36 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":"127305843","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043265
Oyekele Olusenu, A. Obadiah, M. Hamid, Sadiq Thomas, I. Orikumhi, Omotayo Oshiga
This paper proposes a reconfigurable Vivaldi antenna with bandwidth control. The Vivaldi antenna is incorporated with two pairs of circular slot resonator for the purpose of switching. Pin diodes are used to switch ON/OFF the circular slot resonators one pair at a time. The bandwidth of the Vivaldi antenna can be controlled from a wideband (1. 08GHz to 3GHz) to two different narrower bandwidths at a fixed center frequency of 2. 6GHz. A DC biasing network is formed around the antenna to aid switching. The design is simulated in CST microwave studio using FR4 substrate and has been confirmed through fabrication and measurement in an anechoic chamber. This antenna is good for applications requiring bandwidth control such as Long Term Evolution (LTE).
{"title":"A Reconfigurable Vivaldi Antenna with bandwidth control","authors":"Oyekele Olusenu, A. Obadiah, M. Hamid, Sadiq Thomas, I. Orikumhi, Omotayo Oshiga","doi":"10.1109/ICECCO48375.2019.9043265","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043265","url":null,"abstract":"This paper proposes a reconfigurable Vivaldi antenna with bandwidth control. The Vivaldi antenna is incorporated with two pairs of circular slot resonator for the purpose of switching. Pin diodes are used to switch ON/OFF the circular slot resonators one pair at a time. The bandwidth of the Vivaldi antenna can be controlled from a wideband (1. 08GHz to 3GHz) to two different narrower bandwidths at a fixed center frequency of 2. 6GHz. A DC biasing network is formed around the antenna to aid switching. The design is simulated in CST microwave studio using FR4 substrate and has been confirmed through fabrication and measurement in an anechoic chamber. This antenna is good for applications requiring bandwidth control such as Long Term Evolution (LTE).","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"210 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":"132839880","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043183
N. C. Onyemachi, O. Nonyelum
The amount of data being generated in the healthcare industry is growing at a very fast rate. This has generated immense interest in leveraging the availability of healthcare data to improve health outcomes and reduce costs. Big data analytics has earned a remarkable interest in the health sector as it could be used in the diagnosis and prediction of diseases. This paper is a review of current big data analytics techniques in healthcare, their applications, challenges and solutions to those challenges.
{"title":"Big Data Analytics in Healthcare: A Review","authors":"N. C. Onyemachi, O. Nonyelum","doi":"10.1109/ICECCO48375.2019.9043183","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043183","url":null,"abstract":"The amount of data being generated in the healthcare industry is growing at a very fast rate. This has generated immense interest in leveraging the availability of healthcare data to improve health outcomes and reduce costs. Big data analytics has earned a remarkable interest in the health sector as it could be used in the diagnosis and prediction of diseases. This paper is a review of current big data analytics techniques in healthcare, their applications, challenges and solutions to those challenges.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","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":"116985334","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043216
Salisu Ibrahim Yusuf, Steve Adeshina Ph.D, Moussa Mahamat Boukar
Analysis of human walking behavior gait analysis is being used for identification, recognition, behavioral analysis in various fields such as medicine, bio mechanical, robotics, through the application of signal processing, machine learning and computer visions methods. The human gait analysis is done by extracting features from the body, analyzing behavior of interest. In this survey we identify several features and methods considered by researchers, identifying strength and limitations, the survey found that the upper body is a better data source for gait analysis.
{"title":"Parameters for Human Gait Analysis: A Review","authors":"Salisu Ibrahim Yusuf, Steve Adeshina Ph.D, Moussa Mahamat Boukar","doi":"10.1109/ICECCO48375.2019.9043216","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043216","url":null,"abstract":"Analysis of human walking behavior gait analysis is being used for identification, recognition, behavioral analysis in various fields such as medicine, bio mechanical, robotics, through the application of signal processing, machine learning and computer visions methods. The human gait analysis is done by extracting features from the body, analyzing behavior of interest. In this survey we identify several features and methods considered by researchers, identifying strength and limitations, the survey found that the upper body is a better data source for gait analysis.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"36 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":"132547149","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043291
Abubakar Umar Turaki, Gokhan Koyunlu, Nyangwarimam Obadiah Ali, Abubakar Idrissa, G. Sani, Omotayo Oshiga
Atmospheric propagation faces signal degradation in satellite communication services operating in frequencies of Ku-band, Ka-band and above. This effect is caused by rain, storms, and other unfavorable atmospheric conditions that bring about losses along the entire link path from space to earth. This study examined the impact of rain and predicts its induced attenuation on broadband satellite links in Abuja Nigeria. The point rainfall data was collected for a period of four years, and 1-min rainfall rate extracted. Annual rainfall rate was quantified to fall within 120mm/h and the effect of rain on broadband satellite link operating on Ku band frequency was evaluated to an average induced attenuation of17 dB.
{"title":"Rain Induced Attenuation Prediction in the Ku Band of Nigerian Communication Satellite over Abuja Earth Station","authors":"Abubakar Umar Turaki, Gokhan Koyunlu, Nyangwarimam Obadiah Ali, Abubakar Idrissa, G. Sani, Omotayo Oshiga","doi":"10.1109/ICECCO48375.2019.9043291","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043291","url":null,"abstract":"Atmospheric propagation faces signal degradation in satellite communication services operating in frequencies of Ku-band, Ka-band and above. This effect is caused by rain, storms, and other unfavorable atmospheric conditions that bring about losses along the entire link path from space to earth. This study examined the impact of rain and predicts its induced attenuation on broadband satellite links in Abuja Nigeria. The point rainfall data was collected for a period of four years, and 1-min rainfall rate extracted. Annual rainfall rate was quantified to fall within 120mm/h and the effect of rain on broadband satellite link operating on Ku band frequency was evaluated to an average induced attenuation of17 dB.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"65 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":"132929017","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：