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Literature survey on automatic bug triaging using machine learning techniques

AIP Conference Proceedings 2022年第1期2555卷

作者： Deepshikha Chhabra Meena Malik Sachin Sharma 1Chandigarh University Gharuan Mohali Punjab India 2Department of Computer Science and Engineering Jaipur India

Amongst all the phases of software development life cycle software testing phase is the most crucial phase. in this phase the errors or bugs are reported by the tester. Any kind of unexpected behavior in the software is referred to bug. the same can be referred as error or flaw. As soon as the bug is reported by the software tester the next step is to fix the bug or we can say that assigning the bug to appropriate developer which is known as bug triaging. the companies spend large amount of costs in bug triaging process. The process of assigning the bug to appropriate developer is based on various factors like severity, priority and risk associated with the bug. The key idea behind the bug triaging process is to search the suitable developer who can fix the bug in short span of time. in this research paper we will address the factors which impact the performance of bug triaging process. in the later section the comparative analysis of various automatic bug triaging processes has been done.

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Recurrence relations on the generelizad poly-Genocchi polynomials

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AIP Conference Proceedings 2017年第1期1863卷

作者： Burak Kurt Secil Bilgic 1Department of Mathematics Faculty of Education University of Akdeniz TR-07058 Antalya-Turkey 2Department of Computer Programming (Distrance Education) Anadolu Bil Vocational School Istanbul Aydin University Turkey

In this work, we introduce and investigate poly-Genocchi numbers and polynomials. We give recurrence relations for the poly-Genocchi numbers. Also, we prove a relation between multi-poly-Genocchi polynomial and multi-...

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Visual-infrared image monitoring system for moving object detection, classification and tracking using deep learning technique

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AIP Conference Proceedings 2023年第1期2651卷

作者： Maad Issa Al Tameemi Bashra Kadhim Oleiwi 1Department of Computer Engineering University of Baghdad Baghdad Iraq 2Department of Control and Systems Engineering University of Technology-Iraq Baghdad Iraq

In this work, the issue of moving object detection, classification, and tracking in both visual-infrared images and video streams is considered. The proposed system utilizing deep learning-based You Look Only Once -version3 (YOLOv3) algorithm as multilayers of CNN model, OpenCV, and CAMEL dataset and collected dataset as video sequence of a visual-infrared dataset. The proposed object detector system pre-trained on the dataset for streaming videos and different sizes and types of images as visual_ thermal as RGB images of different object classes and carried out by Python codes. The first part of the proposed system is to make the object or person detection and surround it by rectangle box, the center of the detected person is then specified in the second part, finally, calculate the relative accuracy of detected person and added it to the rectangle box. The obtained results proved the success of the proposed system in achieving objects detection, classification, and tracking within visual-infrared surveillance scenarios and gave satisfactory results with high accuracy.

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Correlation of experimental damage data for the development of the UT-MARLOWE Monte Carlo ion implant simulator

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AIP Conference Proceedings 1999年第1期475卷 836-840页

作者： M. F. Morris S. Tian Y. Chen A. Tasch S. Baumann J. F. Kirchhoff R. Hummel S. Prussin D. Kamenitsa J. Jackson 0Motorola Mesa Arizona 85202 1Avante! Fremont California 94538 2Department of Electrical and Computer Engineering University of Texas Austin Texas 78723 3Evans Texas Round Rock Texas 78681 4Charles Evans and Assoc. California 94603 5Department of Materials Science and Engineering University of Florida Gainesville Florida 32611 6Electrical Engineering Department UCLA Los Angeles California 90024 7Eaton Corporation Austin Texas 78717 8Eaton Corporation Beverly Massachusetts 01915

The Monte Carlo ion implant simulator UT-MARLOWE has usually been verified using a large array of Secondary Ion Mass Spectroscopy (SIMS) data (∼200 profiles per ion species)(1). A model has recently been developed (1) to explicitly simulate defect production, diffusion, and their interactions during the picosecond ‘defect production stage’ of ion implantation. In order to thoroughly validate this model, both SIMS and various damage measurements were obtained (primarily channeling-Rutherford Backscattering Spectroscopy, Differential Reflectometry and Tapered Groove Profilometry, but supported with SEM and XTEM data). In general, the data from the various experimental techniques was consistent, and the Kinetic Accumulation Damage Model (KADM) was developed and validated using this data. This paper discusses the gathering of damage data in conjunction with SIMS in support of the development of an ion implantation simulator.

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User search keyword based image and video retrival

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AIP Conference Proceedings 2020年第1期2282卷

作者： K. Meenakshi S. Aruna 1Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India

Retrieval of images and videos are based on user's keyword. Video ranking is based on the number of likes and the keyword entered. Then, it will be compared with the maximum matching keywords. A searching algorithm is used in order to rank the images. A search engine is created in which images are retrieved by the keyword entered and the images are ranked according to the keyword and description of an image. All keywords would be stored in the database so that any image could be retrieved. Next, videos are retrieved by the keyword and language, if language is mentioned. The videos are sorted in ascending order of likes.

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Development and performance test of an innovative solar derived intermittent microwave convective food dryer

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AIP Conference Proceedings 2019年第1期2121卷

作者： Mohammad U. H. Joardder M. H. Masud Shayban Nasif Jakaria Abed Plabon Sagit Hasan Chaklader 1Department of Mechanical Engineering Rajshahi University of Engineering & Technology Rajshahi-6204 Bangladesh 2Department of Computer science and Engineering Varendra University Rajshahi Bangladesh

Drying is one of the oldest food preservation techniques associated simultaneous heat and mass transfer in order to extend the shelf-life of food materials. However, it is an energy intensive process and consumes about 20-25% of the energy used in the food processing industries. Developing of innovative drying system such as intermittent convective microwave (IMC) and utilization of renewable energy like solar energy in drying can be the potential solution of minimizing consumption of conventional energy in drying process. In this study, an innovative solar energy driven IMC dryer has been designed and fabricated. In addition to this, the effectiveness of this dryer over conventional drying process has been performed. Overall, the developed renewable energy based IMC drying shows better performance in energy consumption and quality aspect of the finish food product.

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Implementation of AES algorithm to secure data in smart devices

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AIP Conference Proceedings 2020年第1期2282卷

作者： S. Aruna K. Meenakshi 1Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India

This paper presents the idea of securing the smart devices used at our home or work spaces. Smart mirrors are devices which are equipped with peripherals such as a one-way mirror placed on top of LED monitor, Raspberry pi, Microphones and Speakers. Smart mirrors eliminate the need for checking our phones for latest news or updates. It provides the necessary information such as clock, calendar, news, weather reports. It displays all the notifications of our mobile devices which is connected via LAN. It interacts with the user through verbal commands and provides compliments as well. It has a web interface which can be used by the user/owner of the smart mirror to configure, start/stop the service. The data stored in the device is encrypted using 128-bit AES Algorithm. The encryption is done through a USB device which stores the 128-bit long key.

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Kafka based LSTM model for streaming data prediction

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AIP Conference Proceedings 2022年第1期2444卷

作者： S. Geetha V. Kalaivani 1Department of Computer Applications Mepco Schlenk Engineering College Sivakasi Tamil Nadu India 2Department of Computer Science and Engineering National Engineering College Kovilpatti Tamil Nadu India

In the current technological world, the data is getting generated abundantly through various sources. The time dependent data generated through sensors is one among them. The most of the time dependent or time series data is streaming in real-time onfixed flow rates and sometimes, it will be on variation. When there is a change or no change in the flow of data, the existing state of the art prediction models provides low accuracy of prediction. Hence, it is proposed to have better accuracy of prediction on the streaming data with LSTM and Kafka Framework. The Kafka-LSTM model performed much better than the other conventional models. The models were evaluated using mean absolute error and root mean square error. The proposed method performs with better accuracy and reduced error rate than the other conventional models.

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Robust baseline subtraction for ultrasonic full wavefield analysis

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AIP Conference Proceedings 2017年第1期1806卷

作者： K. Supreet Alguri Jennifer E. Michaels Joel B. Harley 1Department of Electrical and Computer Engineering University of Utah USA 3School of Electrical and Computer Engineering Georgia Institute of Technology USA 2Department of Mechanical Engineering University of Utah USA

Full wavefield analysis is used to study and characterize the interaction between waves and structural damage. Yet, as wavefields are measured and as damage evolves in a structure, environmental and operational variations can significantly affect wave propagation. Several approaches, including time-stretching and optimal baseline selection methods, can reduce variations, but these methods are often limited to specific effects, are ineffective for large environmental variations, or require an impractical number of prior baseline measurements. This paper presents a robust methodology for subtracting wavefields and isolating wave-damage interactions. The method is based on dictionary learning. It is robust to multiple types of environmental and operational variations and requires only one initial baseline. We learn the dictionary, which describes wave propagation for a particular wavefield, based on multiple frequencies of a baseline wavefield. We then use the dictionary and sparse regression to create new baselines for measurements with different environmental and operational conditions. The new baseline is then subtracted from the new wavefield to isolate damage wavefield.

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Delaying the occurrence of instability of the HSG-FD-FDTD method using spatial filtering

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AIP Conference Proceedings 2022年第1期2644卷

作者： Atheel Nowfal Alkhayyat Hayder Wathik Altameemi Ruslan Saad Abdulrahman Aymen Jaber Salman 1Department of Computer Engineering College of Engineering Al-Nahrain University Baghdad Iraq 2Department of Electronic Services Industrial Bank Baghdad Iraq

The main goal of Huygens subgridding (HSG) technique is to increase the computational efficiency by decreasing the memory usage and computational time. A high value (larger than ten) of subgridding ratio can be used. However, the HSG method experiences the late-time instability. In this paper, an algorithm was proposed and implemented to overcome the stability problem. 2D frequency dependent (Debye model) simulations were conducted, and the results were analyzed and discussed. In the proposed method, it is discovered that the occurrence of late-time instability was delayed about four times the occurrence of instability in the conventional HSG method. Furthermore, two parameters play a vital role on the occurrence of late-time instability and the selection of their values determines the delay of instability.

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