International Journal of Engineering Research and最新文献

{"title":"A Survey Paper on Machine Learning Approaches to Intrusion Detection","authors":"Oyeyemi Osho, S. Hong","doi":"10.17577/IJERTV10IS010040","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010040","url":null,"abstract":"This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. For any nation, government, or cities to compete favorably in today’s world, it must operate smart cities and e-government. As trendy as it may seem, it comes with its challenges, which is cyber-attacks. A lot of data is generated due to the communication of technologies involved and lots of data are produced from this interaction. Initial attacks aimed at cyber city were for destruction, this has changed dramatically into revenue generation and incentives. Cyber-attacks have become lucrative for criminals to attack financial institutions and cart away with billions of dollars, led to identity theft and many more cyber terror crimes. This puts an onus on government agencies to forestall the impact or this may eventually ground the economy. The dependence on cyber networked systems is impending and this has brought a rise in cyber threats, cyber criminals have become more inventive in their approach. This proposed dissertation discusses various security attacks classification and intrusion detection tools which can detect intrusion patterns and then forestall a break-in, thereby protecting the system from","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85209190","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":"Flood Modeling of Jemo River Catchement in Addis Ababa City, Ethiopia","authors":"Getnet Adugna, B. Abate","doi":"10.17577/IJERTV10IS010035","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010035","url":null,"abstract":"Flood affects lives and livelihoods in parts of Ethiopia. The flood from the Jemo river is causing damages to river side houses, infrastructures and displacement of affected population that resulted overflow on the surface following heavy rains and inundated lowland areas in the Nifas Silk Lafto district of Addis Ababa city, Ethiopia. This research involves the integration of Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Hydrologic Engineering Center-River Analysis System (HEC-RAS) to develop a twodimensional (2D) river model for flood inundation determination and mapping. The model Nash-Sutcliffe efficiency (ENS) was found to be 0.751 during calibration and 0.79 during validation and the coefficient of determination (R) was found to be 0.786 during calibration and 0.801 during validation. The HEC -RAS model was calibrated by comparing the results of the water level in each selected cross section obtained by the model with the observed historic flood mark levels of the year 2010 and 2013. The peak estimated time series discharge of HEC HMS model result was used to simulate the unsteady state of flow to determine flood extent, water depth and velocity of the study river. Flood hazard vulnerable areas both left and right side of the Jemo river delineated for the return periods 2, 5, 10, 25, 50 and 100 years. The research showed community houses ranging from mud houses to regular story buildings can be affected during each return period maximum flooding event. Jemo river flow capacity also checked at different cross sections and less carrying capacity sections identified for recommended flood protection measures like dyke and retaining masonry walls construction to tackle the flooding impact and avoid possible erosion of the river banks.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73845167","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":"Imputing Missing Data in Hydrology using Machine Learning Models","authors":"V. Sharma, Kezang Yuden","doi":"10.17577/IJERTV10IS010011","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010011","url":null,"abstract":"Missing data has been a common problem and has been confronted by many researchers in the field of hydrology. Rainfall and Temperature time series data are often found missing and such missingness have huge implication on hydrological modelling, flood frequency analysis, trend analysis and dam operation schemes. Owing to the presence of missing data it hinders the performance analysis of the data and inhibits in concluding the correct inferences from the data. In this study, missing data in the rainfall and temperature has been imputed using kNN model and Tree-based model and subsequently these imputed data have been used as predictors to predict the river flow data using Artificial Neural Network (ANN). Uncertainty from kNN imputation model has been found with bootstrapping techniques, while the tree based and ANN model were assessed by Root Mean Square Error (RMSE) and Mean Absolute Error","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73972474","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":"Separation Process of Tobacco Dust from Sand Impurities by Fluidized Fixed Bed","authors":"Arief Rahmatulloh, S. Santosa, Anang Takwanto, Atika Nabilla","doi":"10.17577/IJERTV10IS010019","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010019","url":null,"abstract":"Tobacco dust is by-product of cigarette factory. The existence of impurities on tobacco dust in the form of iron sand (magnetite) and silica for about 10 – 20% (wt%) makes tobacco dust belong to hazardous material. The threshold of sand impurities concentration on Tobacco dust is less than 5% (wt%). One of the methods able to reduce the impurities of tobacco dust is separation process using fluidized fixed bed. Tobacco dusts before and after fluidized were analyzed with gravimetric method to find out the effect of separation process on the sand impurities concentration. The sand impurities concentrations on raw material of tobacco dusts are 28.47; 32.38; and 35.32% (wt%). Further, the optimum gas flow velocity for separation process using fluidized fixed bed was achieved at 0.61 m/s. That velocity generated tobacco dust with the smallest sand impurities at 4% (wt%) in 120 minutes time operation. The subtraction of FTIR wavenumber after separation process (497 cm to 493 cm and 939 cm to 925 cm ) was denoted as the decrement of sand impurities concentration. Moreover, the loss of Fe-O-Si interaction indicated that the sand impurities concentration was successful to be reduced from the tobacco dust. Keywords—Tobacco dust; Magnetite; Silica; Separation; Fluidized bed fixed.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88412697","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":"Tuning PID Controller Bases on Random Search Algorithms","authors":"Dung Vuong Quoc, Thuy Tran Thi, N. D. Minh, Minh Nguyen Quang, Loi Nguyen Tien, Binh Nguyen Thi Thanh","doi":"10.17577/IJERTV10IS010038","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010038","url":null,"abstract":"In this paper, we present two well known random search algorithms which are Genetic algorithm (GA) and Particle Swarm optimization (PSO) to find optimal parameters for PID controller for a model of DC motor is used as a plant. To test performance of GA and PSO algorithms, we compare them with the traditional Ziegler-Nichols method in term of performance indices. The simulation results show that Proportional Integral and Derivative controller (PID) designed by GA and PSO algorithms yields better results than the traditional method in terms of the performance index. Keywords—Tuning PID; GA algorithm; PSO algorithm; Ziegler-Nichols method; performance index; optimization.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89988061","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":"3D Finite Element Analysis of Pile Behavior Inside the Deep Excavation in Soft Soil","authors":"N. Le, T. Nguyen","doi":"10.17577/IJERTV10IS010007","DOIUrl":"https://doi.org/10.17577/IJERTV10IS010007","url":null,"abstract":"A large excavation was carried out in the thick soft soil layer to construct the pile cap foundation and the basement floor for the 15 stories-building in Ho Chi Minh City. The soil profile consists of a 25-meter-thick of very soft clay with SPT value of zero laid on an 8.5-meter-thick of soft clay with SPT value of 3 and laid on a 13.9-meter-thick of medium dense fine sand with SPT value of 17. The excavation was supported by the system of 6-meter-depth SP IV steel sheet piles with the tied-back rods on the top of the wall to the 6m H steel piles installed behind the wall. Before the excavation, the spun PHC pile with 600mm diameter and 100mm thick was installed to support the superstructure. As excavation to 3.8 meter depth, four piles with the distance 4.55m, 7.15m, 10.65m and 13.25m from the wall had the top pile displacement 63.5cm, 38.86cm, 19.5cm and 11.4cm, respectively. Furthermore, all these piles were determined to be cracked by using the PIT test. Base on the collected data, back analysis was carried out by using PLAXIS 3D Foundation with Hardening-Soil soil model to determine the response of these piles during excavation. In the results, the maximum bending moment of these piles was over its ultimate value, thereby, we can analyze the reason piles group in this building was failure and use the parameters in PLAXIS for expanding the analysis to other situations. Keywords—Failure, steel sheet piles, excavation, soft clay, bending moment. I. INTRODUTION In Ho Chi Minh City, a large number of high buildings with the basement floors were constructed to supply the living houses and working offices. Ho Chi Minh City lies on a complex stratum with the soft clay layer somewhere is thicker than 30 meters. Therefore, a lot of problems were happened during the excavation process to build the basement floors for the high building. Some works have taken place the failure of inside existing piles due to the deep excavation. In 2007, all the installed piles to support the superstructure of Thao Dien building in District 2 Ho Chi Minh City were tilted during the basement excavation. A 13 stories building in District 7 has the PHC pile top move 0.6 meter when basement construction was carried out [9]. In similarly, the silo cement in Hiep Phuoc industry zone used the spun PHC pile with pile length from 33 to 35 meter through the thick soft soil layer had about 80 percent of piles under the silo were tilted in the same direction. A mumber of 2664 piles among of 7474 piles of the water treatment station in Binh Chanh District had the top horizontal displacement in the excavation process [9]. In 2011, a 15-story building in district 8 built on the ground with 25m deep of soft clay, the piles near the steel sheet pile wall was tilt and beak out during the pit foundation excavation. The maximum top pile horizontal displacement was up to 0.6 meter. Analysing the failure of pile inside deep foundation pit in soft soil is a considered problem. The deep excava","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84286235","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":"Driver Drowsiness Detection using Microservices and Convolutional Neural Network","authors":"Shrut Shah","doi":"10.17577/ijertv9is120230","DOIUrl":"https://doi.org/10.17577/ijertv9is120230","url":null,"abstract":"Road accidents are one of the main contributors to net fatality rates in India. According to a recent survey in 2020, 43% of road accidents come from drowsy driving. Driving over hours and being in the same state makes the driver feel exhausted and fatigue leading them to drowsiness. A report from Road Transport of India stated that on average 5210 tragedies occur each year alone on the highways of India. A primary system to measure and alert the driver must be mandatory for any moving vehicle. In this paper, a modern approach is proposed for real-time drowsiness detection. A production-grade application with microservice architecture is one of the main focus of this paper. The process of building up the data, augmenting it to a desired level and finally labeling is presented. The customized state of art model is proposed that can achieve an accuracy of 83.65%. Keywords—Deeplearning; microservices; drowsiness detection system; real-time application; kubernetes","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85956683","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":"MalariaNet: A Computationally Efficient Convolutional Neural Network Architecture for Automated Malaria Detection","authors":"Rohan Bhansali","doi":"10.17577/ijertv9is120158","DOIUrl":"https://doi.org/10.17577/ijertv9is120158","url":null,"abstract":"— Despite much progress in detection and treatment, malaria remains one of the most prevalent diseases on earth, both in terms of incidence and death rate. Multiple studies have shown that early detection of malaria is paramount to preventing fatal outcomes; however, current testing methods have notable issues involving cost and accessibility. As a result, deep learning algorithms have been developed for malaria detection and have achieved state of the art results in rapid diagnosis; however, it has been noted that the computational expense of running elaborate models makes deep learning based detection methods inaccessible in remote areas of the world. We develop a computationally efficient, relatively shallow neural network architecture that can diagnose malaria from cell images obtained from thin blood smear slides. Specifically, our algorithm, dubbed MalariaNet, is a 7-layer convolutional neural network trained using the Adaptive Moment Estimation algorithm on the open source NIH malaria dataset, containing 27,588 images of parasitized and uninfected cells. We report that MalariaNet achieves an accuracy of 0.968, F1 score of 0.955, precision of 0.946, and recall of 0.974. We hope that our computationally considerate model inspires more research in producing accessible artificial intelligence solutions for disease detection tasks.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75214413","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":"Wireless Control of AC Motor using Mesh Network Standard","authors":"Aritra De","doi":"10.17577/ijertv9is120119","DOIUrl":"https://doi.org/10.17577/ijertv9is120119","url":null,"abstract":"Nowadays it’s very common to use automation in industries. Ac motors are the nerve of many industries. Hence, the automation is much needed for accuracy and reliable operation. This project proposes a system on wireless control and monitoring different parameters of induction motors based on zigbee technology. Due to this, there will be safe data transfer communication in industrial field where the other mode of data transfer communication is more expensive than zigbee or impossible due to some physical conditions. On this design, there will be a set of transducer and sensor monitors the parameters of Induction motor and transmit its data through zigbee. An Arduino based system is used for collecting and storing data and accordingly generating control signal to stop or start the AC machine wireless through computer interface developed with Zigbee. This Techniques has different sensors to monitor and measure different parameters of induction motor and the data is transmitted to control room i.e., drive using zigbee wireless protocol. The overall control like starting and stopping of motor can be done with zigbee that is already interfaced with computer. It also protects motor against some faults such as over current, over heating in winding, under lover voltage, data acquisition system saves all received parameters data of motor in the database.","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75747777","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":"Statistical Study of nCoV-SARS-2 Disorder in Nigeria Social Dynamics using Correlation and Gravity Law","authors":"Ibrahim Abubakar Sadiq","doi":"10.17577/ijertv9is120113","DOIUrl":"https://doi.org/10.17577/ijertv9is120113","url":null,"abstract":": In this study, the populated and production hub Lagos state is compared with the rest of Nigerian thirty-seven states including the federal capital territory (FCT Abuja), and their concerned distance was used to find the gravitational attraction by applying the gravity model in social dynamics. We have applied the correlation analysis to find a relationship between gravitational attraction during the COVID-19 outbreak from the epicenter state and the number of disease cases in the rest of the states (ROS). We have found out, gravity law in social dynamics has no dependence on the COVID-19 outbreak and it's widespread in Nigeria from the epicenter state. We also discovered that the inverse square law has no reliance on the number of COVID-19 cases in terms of gravitational attraction. the gravity model to find the dependence of COVID-19 spread from the pandemic epicenter Lagos state in Nigeria and the rest of the thirty-seven states including FCT Abuja where affected by this outbreak. The data were examined by using a Google map to obtain the actual distance from Lagos as our COVID-19 outbreak epicenter in connection to the rest of the states. The population figures of each state were deeply examined which allowed us to compute","PeriodicalId":13986,"journal":{"name":"International Journal of Engineering Research and","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83735088","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}