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Self-Admitted Technical Debt classification using LSTM neural network 17th

Self-Admitted Technical Debt classification using LSTM neura...

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17th international conference on Information technology: New Generations, ITNG 2020

作者： Santos, Rafael Meneses Junior, Methanias Colaço Rodrigues de Mendonça Neto, Manoel Gomes Department of Computer Science Federal University of Bahia Salvador Brazil Department of Information Systems Federal University of Sergipe Aracaju Brazil

ISBN: (纸本)9783030430191

Context: In software development, new functionalities and bug fixes are required to ensure a better user experience. Sometimes developers need to implement quick changes to meet deadlines rather than a better solution that would take longer. these easy choices, known as Technical Debts, can cause long-term negative impacts because they can bring extra effort to the team in the future. One way to detect technical debts is through source code comments. Developers often insert comments in which they admit that there is a need to improve that part of the code later. this is known as Self-Admitted Technical Debt (SATD). Objective: Evaluate a Long short-term memory (LSTM) neural network model to identify design and requirement SATDs from comments in source code. Method: We performed a controlled experiment to evaluate the quality of the model compared with two language models from literature in a labeled dataset. Results: Our model results outperformed the other models in precision, improving average precision in approximately 8% compared to auto-sklearn and 19% compared to maximum entropy approach, however, the LSTM model achieved worse results in recall and f-measure. Conclusion: We found that the LSTM model can classify with better precision but needs a larger training, so it can improve on the detection of negative cases. © Springer Nature Switzerland AG 2020.

关键词： Long short-term memory

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A Multiclass Depression Detection in Social Media Based on Sentiment Analysis 17th

A Multiclass Depression Detection in Social Media Based on S...

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17th international conference on Information technology: New Generations, ITNG 2020

作者： Mustafa, Raza Ul Ashraf, Noman Ahmed, Fahad Shabbir Ferzund, Javed Shahzad, Basit Gelbukh, Alexander Department of Computer Science COMSATS University Islamabad Islamabad Pakistan IPN - Computing Research Center Mexico City Mexico Yale School of Medicine New HavenCT United States Deptartment of Software Engineering National University of Modern Languages NUML Islamabad Pakistan

ISBN: (纸本)9783030430191

Depression is a common mental health disorder. Despite its high prevalence, the only way of diagnosing depression is through self-reporting. However, 70% of the patients would not consult doctors at an early stage of depression. Meanwhile people increasingly relying on social media for sharing emotions, and daily life activities thus helpful for detecting their mental health. Inspired by these a total of 179 depressive individuals selected from Twitter, who have reported depression and they are on medical treatment. A sample of their recent tweets collected ranges from (200 to 3200) tweets per person. From their tweets, we selected 100 most frequently used words using Term Frequency-Inverse Document Frequency (TF-IDF). Later, we used the 14 psychological attributes in Linguistic Inquiry and Word Count (LIWC) to classify these words into emotions. Moreover, weights were assigned to each word from happy to unhappy after classification by LIWC and trained machine learning classifiers to classify the users into three classes of depression High, Medium, and Low. According to our study, better features selections and their combination will help to improve performance and accuracy of classifiers. © Springer Nature Switzerland AG 2020.

关键词： Sentiment analysis

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Adaptive access mechanism based on network state detection in multi-rate IEEE802.11 WLANs 7th

Adaptive access mechanism based on network state detection i...

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7th computer science On-line conference, CSOC 2018

作者： Lei, Jianjun Peng, Shengjie Dai, Yu School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9783319911915

this paper addresses the problem of channel access in multi-rates IEEE802.11 WLANs (Wireless Local Area Networks). Unlike some current solutions for performance anomaly only aiming to the saturated network, we propose a fine-grain channel access mechanism that takes the saturated and unsaturated network into account simultaneously. Meanwhile, we present a model to detect the network state under different network density. this novel framework can detect the network state by collision rate for the dynamic network scenarios and perform more efficient channel access by combining the legacy IEEE802.11 DCF (Distributed Coordination Function) and airtime fairness algorithm. the simulations show that our algorithm can improve the aggregate throughput and reduce the collision rate during channel access compared to the legacy DCF mechanism. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Wireless local area networks (WLAN)

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Framework for capturing the intruders in wireless adhoc network using zombie node 7th

Framework for capturing the intruders in wireless adhoc netw...

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7th computer science On-line conference, CSOC 2018

作者： Neeli, Jyoti Cauvery, N.K. Department of Information Science and Engineering Global Academy of Technology Bengaluru India Department of Information Science and Engineering RV College of Engineering Bengaluru India

ISBN: (纸本)9783319911915

Wireless Adhoc Network has a bigger range of application where some are already in commercial market and majority of them are still under roof of investigation. the degree of vulnerability of wireless adhoc network is quite high irrespective of presence of various existing techniques, which are too much specific to attack or orchestrated scenario of attack. therefore, the proposed study introduces a framework that introduces a zombie node to capture the attention of attacker by advertising possession of many hops. the study also introduces broker node that is meant for balancing transmission demands along with robust security requirements. the message of zombie node is registered in hop table which makes the virtual zombie node to look like original node. An algorithm is constructed for identifying the malicious node and the study outcome is found to excel better performance with respect to the existing system. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Routing protocols

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the concept of the method for dynamic control of traffic flows on multi-lane roads based on configurable information systems 7th

The concept of the method for dynamic control of traffic flo...

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7th computer science On-line conference, CSOC 2018

作者： Kucherov, Sergey Rogozov, Yuri Lipko, Julia Elkin, Dmitry Institute of Computer Technology and Information Security Southern Federal University Taganrog Russia

ISBN: (纸本)9783319911915

the random nature of the occurrence of road congestion has a negative impact on the capacity of the road network. Such congestion occurs at the delay points-sections of the road network on which the vehicle has to stop or slow down. Effective control of the capacity of delay points, thus, can be considered an important and urgent scientific problem. Despite the variety of effective methods of assessing the road situation, traffic routing, and road network planning, the task of dynamic control of capacity is not solved in a complex manner. Also an important aspect is the lack of effective means of mass informing the participants of road traffic on ways to avoid congestion. the random character (both spatial and temporal) of the appearance of delay points, in turn, requires the creation of automated control methods based on configurable information systems. the article presents the concept of a method for managing the movement of traffic flows, based on the elimination of the delay point by means of information technology. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Information systems

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A mixed hybrid conjugate gradient method for unconstrained engineering optimization problems 7th

A mixed hybrid conjugate gradient method for unconstrained e...

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7th computer science On-line conference, CSOC 2018

作者： Oladepo, David A. Adeleke, Olawale J. Ako, Churchill T. Department of Petroleum Engineering College of Engineering Covenant University PMB 1023 Ota Nigeria Department of Mathematics College of Science and Technology Covenant University PMB 1023 Ota Nigeria Johannesburg South Africa

ISBN: (纸本)9783319911915

A new hybrid of the conjugate gradient (CG) method that combines the features of five different CG methods is proposed. the corresponding CG algorithm generated descent directions independent of line search procedures. With the standard Wolfe line search conditions, the algorithm was shown to be globally convergent. Based on numerical experiments with selected large-scale benchmark test functions and comparison with classical methods, the method is very promising and competitive. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Conjugate gradient method

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DSP-IR: Delay sensitive protocol for intelligent routing with medium access control 7th

DSP-IR: Delay sensitive protocol for intelligent routing wit...

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7th computer science On-line conference, CSOC 2018

作者： Yogeesh, A.C. Patil, Shantakumar B. Patil, Premajyothi Roopashree, H.R. Department of Computer Science and Engineering Nagarjuna College of Engineering and Technology VTU Bengaluru India Publicis Sapient Consulting Pvt. Ltd. Bengaluru India

ISBN: (纸本)9783319911915

the wireless sensor network has been positioned itself from a complete network system to a sub-net of future internet namely Internet of things, where a communications among anything to anything is possible. the extensible use of wireless sensor network makes it more risky if the security threats are not handled wisely. the conventional methods adopted for securing the WSN vulnerability based attacks introduces delay, which brings congestion in the routing flow as well as influence the quality of service. the proposed DSP-IR is a secure routing algorithm to handle security with delay sensitivity. the DSP-IR framework evaluates MAC protocols including S-MAC, Q-MAC and IH-MAC along with RSA, AES and DSP-IR encrypt process. For all the three combinations performance evaluation is done by simulating the model to know the behavior of residual energy, energy consumption and average packet delay with varying interval of message arrival time and it is found that the proposed IH-MAC with DSP-IR exhibits better performance. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Wireless sensor networks

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Classification, clustering and association rule mining in educational datasets using data mining tools: A case study 7th

Classification, clustering and association rule mining in ed...

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7th computer science On-line conference, CSOC 2018

作者： Hussain, Sadiq Atallah, Rasha Kamsin, Amirrudin Hazarika, Jiten Dibrugarh University Assam India Faculty of Computer Science and IT University of Malaya Kuala Lumpur Malaysia Department of Computer System and Technology University of Malaya Kuala Lumpur Malaysia Department of Statistics Dibrugarh University Assam India

ISBN: (纸本)9783319911915

Educational Data Mining is an emerging field in the data mining domain. In this competitive world scenario, the quality of education needs to improve. Unfortunately most of the students’ data are becoming data tombs for not analyzing the hidden knowledge. the educational data mining tries to uncover the hidden knowledge by discovering relationships between student learning characteristics and behavior. With this educational data modeling, the educators may plan for future learning pedagogy to support the student’s learning style. this knowledge may be applied by the academic planners to improve the quality of education and decrease the failure rate. In this paper, we had collected real dataset containing 666 instances with 11 attributes. the data is from the Common Entrance Examination (CEE) data of a particular year for admission to medical colleges of Assam, India conducted by Dibrugarh University. We tried to find out the association rules using the data. Various clustering and classification methods were also used to compare the suitable one for the dataset. the data mining tools applied in the educational data were Orange, Weka and R Studio. © 2019, Springer international Publishing AG, part of Springer Nature.

关键词： Association rules

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Performance analysis of convolutional neural network models 9

Performance analysis of convolutional neural network models

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9th international conference on advances in Computing and Communication, ICACC 2019

作者： Kala, S. Paul, Debdeep Jose, Babita R. Mathew, Jimson Nalesh, S. Cochin University of Science and Technology Department of Electronics Kerala682 022 India IIT Patna Department of Electrical Engineering India IIT Patna Department of Computer Science and Engineering India

ISBN: (纸本)9781728155234

Deep Neural Networks (DNNs) have become a promising solution for numerous machine learning tasks, which include object detection, classification, weather forecasting, video surveillance and safety management. Convolutional Neural Network (CNN) is a class of DNN, which can achieve state-of-art accuracy and high performance for most of the computer vision tasks. Training of CNNs is computationally intensive and may take multiple days for completion. In this work we have performed the feed forward path implementation and training of AlexNet, VGG-16 and ResNet models on Nvidia GeForce GTX 1080 Ti GPU with 3584 CUDA Cores, 1582 MHz, 11GB GDDR5X, using Caffe framework. Inference and training of these models are also performed on Nvidia Jetson TX2 hardware platform. We also present a detailed analysis of graphics processing unit (GPU) and general purpose processor (GPP) implementations of AlexNet, VGG-16 and ResNet-50 network models. A hardware architecture for performing convolution operations in feed forward path of CNN has also been implemented in Virtex-7 XC7VX690T FPGA, with throughput of 184 GFLOPS for AlexNet, 172 GFLOPS for VGG-16 and 197 GFLOPS for ResNet-50 model. © 2019 IEEE.

关键词： Graphics processing unit

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Mobile and wearable computing in patagonian wilderness 7th

Mobile and wearable computing in patagonian wilderness

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7th international conference on Cloud Computing and Big Data, JCC and BD 2019

作者： Almonacid, Samuel Klagges, María R. Navarro, Pablo Morales, Leonardo Pazos, Bruno Puigbó, Alexandra Contreras Firmenich, Diego Facultad de Ingeniería Universidad Nacional de la Patagonia San Juan Bosco TrelewChubut Argentina Puerto MadrynProvincia de Chubut Argentina Puerto MadrynProvincia de Chubut Argentina Puerto MadrynProvincia de Chubut Argentina Departamento de Biología Universidad Autónoma de Santo Domingo Santo Domingo Dominican Republic

ISBN: (纸本)9783030277123

Recent advances in mobile and wearable technology in the last few years have made the optimization of data collection processes possible in diverse fields. Users currently have access to small portable devices that are not only sensitive to their activity, but also to their interaction with their environment. these growing technological advances are in constant development, and have given way to the study and redesign of processes that can be tailored to fit any particular needs. Even users that are far from urbanization, without access to electricity can make use of these possibilities. these technologies can substantially improve their productivity, by allowing them to concentrate solely on their own tasks instead of on the interactions with the computational method used to support their activities. this study presents results and indicators relating to the application these tools within the field of Flora information retrieval, in areas far from urban centers. © Springer Nature Switzerland AG 2019.

关键词： Wearable technology

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