2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)最新文献

{"title":"Optimal Power Splitters' Locations and Cables' Routing in Distributed Antenna System","authors":"Marwa Zamzam, M. Ashour, T. el-Shabrawy","doi":"10.1109/ICACCE.2018.8441695","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441695","url":null,"abstract":"Due to the exponential growth in the demand of higher data rates in wireless systems, ensuring signal strength and efficient coverage has become a challenge facing any network operator. Distributed Antenna System is the solution deployed in this paper because when a sufficient number of distributed antennas is placed inside the building the coverage is improved, as radio signals can successfully reach any point in the building. Since improving the coverage increases the deployment cost due to the need of more antennas and equipment that will lead to more maintenance and installation cost, and minimizing the cost will actually lower the coverage, the aim of the paper is to formulate and solve the problem of finding the optimal cables' routing and the optimal power splitters' locations that connect all the antennas with the base station producing the minimum cost and satisfying the power requirements for each antenna at the same time. Problem solution delivers the tree topology of Distributed Antenna System components connection producing the minimum cost. The base station is considered the root of the tree while the antennas are the leaves. Power splitters are the nodes connecting the base station with the antennas. The objective function is minimizing the cost, it consists of linear terms as the cost of the cables and nonlinear terms as the installation cost of cables as there are two variables multiplied together. First, the variable that checks if the cable connects two components or not, and second, the variable that checks if the cable is installed before or not. The problem is simplified first to be solved without the nonlinear terms using integer linear programming tool and then a hybrid approach of integer linear programming and add heuristic algorithm is proposed to be solved with. Exhaustive algorithm was used as a reference for both algorithms. By comparing the integer linear algorithm and the hybrid approach, it was found that the hybrid approach delivers optimal solution in small buildings and near optimal solutions in large buildings. Second, after the nonlinear terms are included, the problem is solved at the beginning linear without considering the cable installation as a variable then the whole problem including the cable installation variable is solved using the proposed hybrid approach. Results show that the hybrid approach gives better solution than the linear solution after cable installation variable is considered in the formulation.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123535735","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":"End-to-End Delay Minimization in Multi-Channel, TDMA Wireless Sensor Networks by Particle Swarm Optimization","authors":"Muhammad A. Hussain, Myung-Joon Lee","doi":"10.1109/ICACCE.2018.8441732","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441732","url":null,"abstract":"Many Smart City, Internet of Things (IoT) applications would require wireless multi-hop, data collecting networks with low latency and high throughput. Optimal use of multi-channels and timeslots has the potential to achieve such network performance. Finding scheduling allocation of multiple channels and time slots for optimal end-to-end delay in multihop networks is an NP-complete problem. Particle Swarm Optimization (PSO) is a fast, scalable technique to find near-optimal scheduling solution for this problem. This paper addresses some deficiencies of the existing PSO based end-to-end delay minimization problem in wireless sensor networks. An upgraded PSO modeling is proposed and the performance improvements are presented through simulations. Two other capacity enhancement solutions (Non-Orthogonal Multiple Access, Multiple Interfaces) are also simulated using proposed approach and their corresponding performance results are investigated.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129812758","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":"Pan Evaporation Estimation Using Artificial Neural Network","authors":"A. Yarar","doi":"10.1109/ICACCE.2018.8441753","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441753","url":null,"abstract":"Artificial Neural Network (ANN) model's performance was investigated on evaporation estimation at GÕolbasI region. For this aim monthly mean temperature, monthly total rainfall and monthly mean evaporation data of Golbaöl were used. 213 data set were used for the modeling. 150 of all data set were selected for training and other 63 data set were selected for testing. The performance of the ANN model was evaluated according to the graphs and R2 value. It was seen that the coefficient of determination, between measured and estimation, is around 0.89. This modeling study showed that ANN is usable method in estimation of evaporation at Golbasl.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117031003","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":"Evaluation of Diet for Stroke Patients through Soft Computing Algorithm","authors":"P. Sagar, T. Choudhury, G. Raj, Hemant Kumar Gianey","doi":"10.1109/ICACCE.2018.8441704","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441704","url":null,"abstract":"This research is basically about the diet which is to be given to the stroke patients for saving them from adverse effects of stroke. This includes study about the problems and personalized diet matching with each problem. Stroke patients face many problems like dysphagia, high blood pressure, high sugar and disabilities in body parts. This research is about giving them personalized care and expertise diet through soft computing algorithms. It will require a inputs to be filled by patient daily and based on their answers. The diet would be given to them.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134402255","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":"Evaluating the Performance of Deep Learning Techniques on Classification Using Tensor Flow Application","authors":"Suresh Kallam, S. M. Basha, Dharmendra Singh Rajput, Rizwan Patan, B. Balamurugan, Sk. Abdul Khalandar Basha","doi":"10.1109/ICACCE.2018.8441674","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441674","url":null,"abstract":"In Deep Learning, Artificial intelligence is the overall bigger domain, in which machines given the capability to learn new instances of data and then adapt to the basic domain of Machine Learning. Deep Learning is a subset of it, which goes into further accuracy that uses neural networking technology to go in and enable more complex situational data to come in and make more precise decisions. The objective of this research is to find out the details like Ratio of training data, Noise, Batch Size, Properties of features, learning rate, Type of Activation function, Level of Regularization, Rate of Regularization in constructing Neural Network on four different Classification Datasets after directly manipulating design providing in Tensor flow playground application. The Evaluation parameters consider in our experiments are Test loss and Training lose. The findings in our research is to specify that, how many hidden layers and number of neurons in each hidden layer are needed, for each type of classification problem. These findings help the researchers to fix the Maximum number of neurons and hidden layers needed in solving the four different types of classification problems by achieving test loss less than 0.005.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134308875","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":"Interactive Voice Response using Sentiment Analysis in Automatic Speech Recognition Systems","authors":"Rohit Raj Sehgal, Shubham Agarwal, Gaurav Rai","doi":"10.1109/ICACCE.2018.8441741","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441741","url":null,"abstract":"In previous days, Dual Tone Multi-Frequency Signaling technique was used to obtain inputs from the keypad. In this unique frequencies are sent over the audio channel for computer to understand. Speech recognition and artificial intelligence powers the automatic speech recognition systems, these systems can be applied in the call center environments. This paper explains the use of sentiment analysis to identify if the customer are satisfied the ASR system's performance. This paper presents approaches and techniques for how sentiment analysis can be used in call centre environments to recognize user emotions.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133386623","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":"Useinator Requirements Collection Automation","authors":"Kamal El Dahshan, Nora Aboalanin, Ahmed Tomoum, M. Sameh","doi":"10.1109/ICACCE.2018.8441693","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441693","url":null,"abstract":"Useinator is a system in which takes the requirements as an input from a questionnaire that the user required to fill and process the input using advanced methods and decision tree to figure out the requirements efficiently. This helps in building and drawing a well and efficient use case in a timely manner. On the other hand, Useinator will make system analysts gain much time in analysis phase.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115286773","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":"Efficient Cohort Nearest Neighbor (CNN) Technique to leverage Recommender Systems","authors":"B. B. Sinha, R. Dhanalakshmi","doi":"10.1109/ICACCE.2018.8441755","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441755","url":null,"abstract":"The long tail of diverse consumption of resources online by the customers raise a challenge for the e-commerce websites and service providers. Recommender system offers a vigorous way to cope up with the aforementioned challenge. With the advent of the internet, these systems have achieved widespread success in e-commerce applications. The most widely used recommender system technique is collaborative filtering which guides users in a personalized way to suggest items from a large set of possible options. In this paper, we have proposed a cohort nearest neighbour (CNN) recommender system which relies on high cohort users to make predictions. In our work, we have used MovieLens dataset to perform our experiments and measurement of accuracy with Root Mean Square Error (RMSE) technique. This approach significantly improves the retention of recommender system by more than 1.09 times when the granularity of data space increases.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124841159","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 fully comprehensive & relative study of Human Brain-Computer Interface Algorithms","authors":"Abhinav Das, S. Gupta, T. Choudhury, Suraj Sachan","doi":"10.1109/ICACCE.2018.8441706","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8441706","url":null,"abstract":"BCI (Interface for Brain Computer Interaction) can be viewed as a permanent solution and also the best approach of communication through which the patients with physical movement disability will be able to control electronic devices with max. capacity of the person & easily interact with the system. BCI (Interface for Brain Computer Interaction) do not require any outer physical movement to work on, so we can use the device and regulate it with brain activities (using waves) using Brain Computer Interface Using a method called EEG. In this paper, the different types of Interface for Human Brain Interaction is being discussed.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127336339","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":"Continuous and Integrated Software Development using DevOps","authors":"Aayush Agarwal, S. Gupta, T. Choudhury","doi":"10.1109/ICACCE.2018.8458052","DOIUrl":"https://doi.org/10.1109/ICACCE.2018.8458052","url":null,"abstract":"Devops is all about culture, automation, measurement and sharing (CAMS). It is gaining popularity because of its continuous approach - continuous integration(CI), continuous deployment (CD) and software delivery. CI requires the developer to commit the code several times in a day followed by automatic build and test and immediate feedback to the developer whenever any bug is encountered. If no bug is encountered, the committed code is pushed to the production. According to the 2017 State Of Devops Report, high performance companies like Amazon and Netflix deploy thousands of times per day. Configuration management allows the rollback of previous code for the developer. However several factors prevent the organizations from adopting these approaches like lack of fully automated acceptance test, poor rollback methodology, manually driven quality check etc. This research paper provides various methodologies and tools that can constitute an effective CD/CI pipeline.","PeriodicalId":214619,"journal":{"name":"2018 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116515415","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}