{"title":"Predicting Computer Network Traffic: A Time Series Forecasting Approach Using DWT, ARIMA and RNN","authors":"Rishabh Madan, Parthasarathi Mangipudi","doi":"10.1109/IC3.2018.8530608","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530608","url":null,"abstract":"This paper proposes the Discrete Wavelet Transform (DWT), Auto Regressive Integrated Moving Averages (ARIMA) model and Recurrent Neural Network (RNN) based technique for forecasting the computer network traffic. Computer network traffic is sampled on computer networking device connected to the internet. At first, discrete wavelet transform is used to decompose the traffic data into non-linear (approximate) and linear (detailed) components. After that, detailed and approximate components are reconstructed using inverse DWT and predictions are made using Auto Regressive Moving Average (ARIMA) and Recurrent Neural Networks (RNN), respectively. Internet traffic is a time series which can be used to predict the future traffic trends in a computer network. Numerous computer network management tasks depend heavily on the information about the network traffic. This forecasting is very useful for numerous applications, such as congestion control, anomaly detection, and bandwidth allocation. Our method is easy to implement and computationally less expensive which can be easily applied at the data centers, improving the quality of service (QoS) and reducing the cost.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"13 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126104357","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}
Prajwala Tm, A. Pranathi, Kandiraju SaiAshritha, Nagaratna B. Chittaragi, S. Koolagudi
{"title":"Tomato Leaf Disease Detection Using Convolutional Neural Networks","authors":"Prajwala Tm, A. Pranathi, Kandiraju SaiAshritha, Nagaratna B. Chittaragi, S. Koolagudi","doi":"10.1109/IC3.2018.8530532","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530532","url":null,"abstract":"The tomato crop is an important staple in the Indian market with high commercial value and is produced in large quantities. Diseases are detrimental to the plant's health which in turn affects its growth. To ensure minimal losses to the cultivated crop, it is crucial to supervise its growth. There are numerous types of tomato diseases that target the crop's leaf at an alarming rate. This paper adopts a slight variation of the convolutional neural network model called LeNet to detect and identify diseases in tomato leaves. The main aim of the proposed work is to find a solution to the problem of tomato leaf disease detection using the simplest approach while making use of minimal computing resources to achieve results comparable to state of the art techniques. Neural network models employ automatic feature extraction to aid in the classification of the input image into respective disease classes. This proposed system has achieved an average accuracy of 94–95 % indicating the feasibility of the neural network approach even under unfavourable conditions.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125435236","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 Lip Reading Model Using CNN with Batch Normalization","authors":"Saquib Nadeem Hashmi, Harsh Gupta, Dhruv Mittal, Kaushtubh Kumar, Aparajita Nanda, Sarishty Gupta","doi":"10.1109/IC3.2018.8530509","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530509","url":null,"abstract":"The goal of Lip-reading is to decode and analyze the lip movements of a speaker for a said word or phrase. Variation in speaking speed, intensity and same lip sequence of distinct characters have been the challenging aspects of lip reading. In this paper we present a lip reading model for an audio-less video data of variable-length sequence frames. First, we extract the lip region from each face image in the video sequence and concatenate them to form a single image. Next, we design a twelve-layer Convolutional Neural Network with two layer of batch normalization for training the model and to extract the visual features end-to-end. Batch normalization helps to reduce the internal and external variances in various attributes like speaker's accent, lighting and quality of image frames, pace of the speaker and posture of speaking etc. We validate the performance of ourmodel on a standard audio-less video MIRACLE-VC1 dataset and compare with an existing model whichuses 16 layers CNN or more. A training accuracy of 96% and a validation accuracy of 52.9% have been attained on the proposed lip reading model.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115666561","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":"Moedor Cleaning Robot","authors":"Anmol Taneja, G. Bansal, R. Setia, N. Hema","doi":"10.1109/IC3.2018.8530503","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530503","url":null,"abstract":"With technologies moving par the normal human effort and thinking, humans try to integrate technology into every aspect of their lives. For a healthy and nutritious lifestyle, cleanliness and hygiene are one of the most important requirements. In this paper, we implemented automated cleaning system called Moedor Robot for the indoor as well as an outdoor application such as office, corridor, garden, room, etc. In metropolitan cities people are forced to work for a long duration to sustain city life and expenses. In such a situation, people will look forward to save the time and in a secure way. The requirement of the automated cleaning system is the need of the hour in such situation. The proposed system is fully autonomous and decision making are based on the three inputs i. e. LDR sensors, ultrasonic sensors and video processing. LDR sensors are used to identify the dirt area, ultrasonic sensors are used to find the proximity of the object and video processing is used to identify the trash type for trash management.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124260640","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":"Identification of Relevant Contextual Dimensions Using Regression Analysis","authors":"Anu Taneja, Anuja Arora","doi":"10.1109/IC3.2018.8530565","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530565","url":null,"abstract":"The tremendous growth of information on the web has necessitated the need for recommendation systems. Although users' preferences used to vary under different situations which urge the requisite of context-aware recommendation systems. But the major issue to be addressed in context-aware recommendation systems is an efficient utilization of contextual dimensions, under which an item is consumed, are not equally important. Therefore, in this study, the determinants are analyzed that influences the user decision and their satisfaction towards watching movies. Thus a logistic regression model is developed to induce out the foremost factors that prevail the user satisfaction. The key findings of the study indicate that dominantEmo, endEmo, interaction, and weather are the most relevant contextual dimensions which integrated into the model would boost the performance of the model.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116993643","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":"Parameter Estimation in a Biological System Using Differential Evolution Algorithm","authors":"S. Panda, R. Das","doi":"10.1109/IC3.2018.8530508","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530508","url":null,"abstract":"Tumours generally involve high rates of metabolic heat generation and blood perfusion. In this paper, we present an inverse method involving the differential evolution algorithm for predicting the blood perfusion rate from the knowledge of transient temperature response of the skin. The interesting aspect of this work is to demonstrate that mere prediction of blood perfusion rate can characterize a tumorous tissue without any prior knowledge of the rate of metabolic heat generation. This is done by the incorporation of the initial temperature in the governing forward method itself and eliminating the metabolic heat generation from the pertinent expressions. Due to the nonhomogenous nature of biological tissues, the thermal relaxation time of such systems is considerably higher than other materials. Thus, unlike conventionally-studied Pennes bioheat transfer model, the present study addresses a non-Fourier heat conduction-based bioheat transfer model. The effect of random noise is also accounted in the present study and it is finally observed that the present work satisfactorily deciphers the malignant melanoma and other related subsurface abnormalities using a non-invasive inverse method aided by the skin's transient thermal signatures.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124851342","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":"Characterization Study of Developers in Non-Reproducible Bugs","authors":"Anjali Goyal, Neetu Sardana","doi":"10.1109/IC3.2018.8530641","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530641","url":null,"abstract":"Software bugs are inevitable. Increasing size and complexity of software systems makes bug handling a cumbersome and time-consuming task. In such scenarios, Non-Reproducible (NR) bug reports are an additional overhead for software developers as these bugs are hard-to-reproduce. This difficulty in reproducing NR bugs is due to varied reasons such as the absence of information required to create the same test environment, resource and time constraints, inability of the assigned developer to fix the issue, etc. However, when NR marked bug reports are reconsidered, a few percentages of these bug reports get Fixed (NRF). This fixation occurs either due to the trial of new solutions to reproduce the bug or due to the assignment of a different developer for the bug report. To find whether a change in developer helps in resolving NR bugs, this paper investigates the developers associated with NR bug reports. We gauged developer similarity (in terms of developer marking bug report as NR and Fix), tossing trends, presence of isBack and expertise level of developers who marked NRF bug reports as NR and Fix. We studied the change history of 24, 995 NR bug reports of Mozilla Firefox project. Our results show that 87.34% NRF bug reports are fixed by a developer who had not marked the bug report initially as NR. Also, we found that average tossing path length in NRF bug reports is three times higher than tossing path length in NR bug reports. This higher rate of bug tossing results in higher fixation probability of NR bug reports. It has also been observed that developers who fix NR bugs possess higher expertise than developers who marks bug reports as NR.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129163378","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 IoT Systems: An Energy Efficient Perspective","authors":"Vinita Tahiliani, Mavuri Dizalwar","doi":"10.1109/IC3.2018.8530550","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530550","url":null,"abstract":"The Internet of Things (IoT) is an emerging paradigm that has gained popularity in recent years. The large number of high performance and sophisticated devices connected to the IoT system consumes huge amount of energy. Thus, the issue of energy consumption in IoT based systems is an important research focus. Green IoT represents the issue of reducing energy consumption of IoT devices which achieves a sustainable environment for IoT systems. This paper presents the current state of the art research on energy optimization in IoT. We investigated the literature, categorized the existing energy efficient techniques and presented the open challenges and research opportunities that can assist the research community. The main contribution of this paper is that it systematically summarizes and analyzes the existing energy aware techniques in tabular form on the basis of different layers and components of IoT.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130568233","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":"Importance of Non-Technical Skills for Employment Opportunities: A Gap Analysis of Students and Employers Perception Importance of Non-Technical Skills","authors":"Suhail M. Ghouse, Monica Chaudhary, S. Garg","doi":"10.1109/IC3.2018.8530663","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530663","url":null,"abstract":"In this paper, an attempt has been made to examine the gap between the perceptions of the employers and the engineering students about the importance of Non-Technical Skills for better employment opportunities. Data was collected through a structured questionnaire-based survey targeting the students and the employers. Responses were collected from 104 students and 50 employers based in the National Capital Region, India. The results obtained showed that there is significant difference in the skill set that are highly prioritized by the employers when hiring young engineering graduates and in the skill set which an engineering student ranks higher. The findings are insightful and beneficial to students, employers and Universities also. There is need for universities also to understand the various parameters where the students and the employers share the same view and the universities can act as a catalyst in giving more focus on some particular non-technical skills like oral and written communication along with good presentation and soft skills for the overall value addition to the personality of a young engineering graduate.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131947995","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":"Detection and Mitigation of DDoS in SDN","authors":"Bhavika Pande, G. Bhagat, S. Priya, H. Agrawal","doi":"10.1109/IC3.2018.8530551","DOIUrl":"https://doi.org/10.1109/IC3.2018.8530551","url":null,"abstract":"The authors have modelled a DDoS prevention mechanism for DDoS attacks occurring in same or different domains, with help of controller in Software Defined Networking. The controllers are implemented using Ryu and Open Flow protocol. The topology for our framework consisting of controllers, switches and hosts is implemented using Mininet which emulates the network effectively. Controllers are programmed to identify victims and attackers and apply defense mechanism accordingly. The defense mechanisms used are ingress, egress and pushback after validating packet legitimacy. Ingress filtering is applied if the attacker is found to be in the same domain while egress followed by ingress is applied when the attacker is found to be of the other domain, after receiving a pushback request. The model proves to give fairly accurate results.","PeriodicalId":118388,"journal":{"name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130243544","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}