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A Machine Learning based Analytical Approach for Envisaging Bugs

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第5期12卷 747-756页

作者： Munde, Anjali Amity Univ Uttar Pradesh Amity Coll Commerce & Finance Noida India

A software imperfection is a shortcoming, virus, defect, mistake, breakdown or glitch in software that initiates it to establish an unsuitable or unanticipated result. The foremost hazardous components connected with a software imperfection that is not identified at an initial stage of software expansion are time, characteristic, expenditure, determination and wastage of resources. Faults appear in any stage of software expansion. Thriving software businesses emphasize on software excellence, predominantly in the early stage of the software advancement. In succession to disable this setback, investigators have formulated various bug estimation methodologies till now. Though, emerging vigorous bug estimation prototype is a demanding assignment and several practices have been anticipated in the text. This paper exhibits a software fault estimation prototype grounded on Machine Learning (ML) Algorithms. The simulation in the paper directs to envisage the existence or non-existence of a fault, employing machine learning classification models. Five supervised ML algorithms are utilized to envisage upcoming software defects established on historical information. The classifiers are Naive Bayes (NB), Support Vector Machine (SVM), K- Nearest Neighbors (KNN), Decision Tree (DT) and Random Forest (RF). The assessment procedure indicated that ML algorithms can be manipulated efficiently with high accuracy rate. Moreover, an association measure is employed to evaluate the propositioned extrapolation model with other methods. The accumulated conclusions indicated that the ML methodology has an improved functioning.

关键词： Software bug prediction prediction model data mining machine learning Naive Bayes (NB) support vector machine (SVM) k-nearest neighbors (KNN) decision tree (DT) random forest (RF) python programming

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PyQBench: A python library for benchmarking gate-based quantum computers

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SOFTWAREX 2023年 24卷

作者： Jalowiecki, Konrad Lewandowska, Paulina Pawela, Lukasz Polish Acad Sci Inst Theoret & Appl Informat Bałtycka 5 PL-44100 Gliwice Poland

We introduce PyQBench, an innovative open-source framework for benchmarking gate-based quantum computers. PyQBench can benchmark NISQ devices by verifying their capability of discriminating between two von Neumann measurements. PyQBench offers a simplified, ready-to-use, command line interface (CLI) for running benchmarks using a predefined family of measurements. For more advanced scenarios, PyQBench offers a way of employing user-defined measurements instead of predefined ones.

关键词： Quantum computing Benchmarking quantum computers Discrimination of quantum measurements Discrimination of von Neumann measurements Open-source python programming

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The Use of Bi-Potentiostat as a Simple and Accurate Electrochemical Approach for the Determination of Orthophosphate in Seawater

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SENSORS 2023年第4期23卷 2123-2123页

作者： Altahan, Mahmoud Fatehy Esposito, Mario Bogner, Boie Achterberg, Eric P. GEOMAR Helmholtz Ctr Ocean Res Chem Oceanog Dept D-24148 Kiel Germany Natl Water Res Ctr Cent Lab Environm Qual Monitoring El Qanater El Khairia 13621 Egypt

Autonomous on-site monitoring of orthophosphate (PO43-), an important nutrient for primary production in natural waters, is urgently needed. Here, we report on the development and validation of an on-site autonomous electrochemical analyzer for PO43- in seawater. The approach is based on the use of flow injection analysis in conjunction with a dual electrochemical cell (i.e., a bi-potentiostat detector (FIA-DECD) that uses two working electrodes sharing the same reference and counter electrode. The two working electrodes are used (molybdate/carbon paste electrode (CPE) and CPE) to correct for matrix effects. Optimization of squarewave voltammetry parameters (including step potential, amplitude, and frequency) was undertaken to enhance analytical sensitivity. Possible interferences from non-ionic surfactants and humic acid were investigated. The limit of quantification in artificial seawater (30 g/L NaCl, pH 0.8) was 0.014 mu M for a linear concentration range of 0.02-3 mu M. The system used a python script for operation and data processing. The analyzer was tested for ship-board PO43- determination during a four-day research cruise in the North Sea. The analyzer successfully measured 34 samples and achieved a good correlation (Pearson' R = 0.91) with discretely collected water samples analyzed using a laboratory-based colorimetric reference analyzer.

关键词： Bi-potentiostat electrochemical sensor orthophosphate sensor python programming phosphomolybdate complex method

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Experimental-numerical study of wrinkling in rotary-draw bending of Tight Fit Pipes

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THIN-WALLED STRUCTURES 2023年 183卷

作者： Naderi, Gholamali Torshizi, Seyed Ebrahim Moussavi Dibajian, Seyed Houssain Azarab Ind Co Boiler Design Dept Arak Iran Shahid Beheshti Univ Fac Mech & Energy Engn Tehran Iran

The paper focuses on tight fit pipe (TFP) wrinkling in rotary-draw bending (RDB), where TFP is a double -walled pipe. To this end, a corrosion-resistant alloy liner is fitted inside an outer carbon steel pipe through a thermal-hydraulic manufacturing process. A 3D elastic-plastic finite element (FE) model (the dynamic explicit FEM code ABAQUS/Explicit) is developed in this study. This model simulates the manufacturing process in the first step of the analysis and proceeds in the rotary-draw bending analysis of the lined pipe. Then, in the third step, the springback of the two-layer pipe is analyzed. This integrated three-stage process considers geometric nonlinearities, geometric and thickness imperfections, inelastic material behavior, and contact between the two pipes. Contact pressure during the process in the presence of various imperfections is monitored by the histogram to predict wrinkling. Furthermore, the best bending angle, with minimum possibility of wrinkling in the inner pipe, is obtained by these histograms. ABAQUS scripting via the python programming language is used to study the effect of various imperfections on RDB. Numerical results on imperfection sensitivity demonstrate the significant influence of imperfections' amplitude on liner wrinkling. The ovality and thinning of the lined pipe via bending angle were investigated. By comparing the experimental results with those of the simulation, an appropriate agreement is observed.

关键词： Tight Fit Pipe Wrinkling Rotary-draw bending Imperfection ABAQUS Explicit python programming

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Design and development of electronic stethoscope for early screening of valvular heart disease prediction

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2023年第PartA期86卷

作者： Roy, Tanmay Sinha Roy, Joyanta Kumar Mandal, Nirupama Haldia Inst Technol Dept Elect Engn Haldia W Bengal India Narula Inst Technol Dept Elect & Commun Engn Kolkata India Indian Inst Technol ISM Dept Elect Engn Dhanbad India

The significant human population of the world is suffering from valvular heart diseases and dies due to the lack of a simple predictive diagnosis system. Identifying the abnormalities in heart sound needs excellent auscultation skills and experience. Thus an electronic stethoscope is designed and developed using different microphonic heads. In this research work, hardware development of an electronic stethoscope interfaced with raspberry pi 4B and software development of the proposed CNN-based deep learning model is carried out. The Bluetooth-enabled electronic stethoscope is used to auscultate the heart sound analyzed with a developed deep learning Con-volutional Neural Network-based Efficient Network model. The developed CNN model is designed with classifiers to predict valvular diseases accurately. The analysis result is almost in real-time processed and stored in the Cloud. The design provides a better way of studying PCG signal analysis, which eventually reduces the cost and makes the system compact. The proposed model has been trained through a standard and validated heart sound bank of normal and abnormal diseases and predicts the abnormality with accuracy. The proposed modified Efficient Net -B3 model scored an accuracy of 99.35 & PLUSMN;0.34% on the test dataset with a sensitivity of 98.84 & PLUSMN;0.07% and specificity of 98.23 & PLUSMN;0.52%. The Selenium Web Driver tool with Google Drive API is used to automate the web application PCG signal analysis. Finally, the SQLite database has been used as a back-end server to store the patient record. The system is low-cost and portable, with data remotely accessible and tested with volunteers. The developed system can be used in rural areas where there is a lack of medical facilities exists and can be used to initiate primary screening of valvular diseases.

关键词： Valvular heart disease prediction Machine learning Convolutional neural network Residual network Electronic stethoscope python programming SQLite Real-time data acquisition Selenium web driver Cloud storage Remote telemedicine Graphical user interface Feature extraction Classification PCG signal

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Creating Instructional Elementary programming Videos for Use in an Adaptive Testing and Remediation System 2024

Creating Instructional Elementary Programming Videos for Use...

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Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2

作者： Abigail Jones Manogya Aryal Justin Selby Seth Adjei Northern Kentucky University Highland Heights KY USA

ISBN: (纸本)9798400704246

In computer science undergraduate programs, the first course often focuses on elementary computer programming. However, students' backgrounds can be diverse, leading to challenges in understanding the course material. We discuss our initial steps to improve elementary programming instruction by using instructional videos. A team of three content creators developed a series of instructional videos, covering forty different programming skills. These videos span various topics, from creating and running basic python programs to understanding and creating functions. To assist elementary programming students, we plan to integrate these videos with PLACEments, an adaptive assessment and remediation system designed to help students bridge knowledge gaps. If a student answers a question incorrectly, a relevant video is provided as support. The three content creators peer reviewed the others' instructional videos according to an educational video assessment framework. These results were also standardized through a z-score to account for any reviewer biases. The initial results from the peer review are promising. However, more information will be collected as the videos are deployed through PLACEments and tested by students currently taking an elementary programming course.

关键词： elementary programming python programming undergraduate education video instruction

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Supervised machine learning classification algorithms for detection of fracture location in dissimilar friction stir welded joints

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FRATTURA ED INTEGRITA STRUTTURALE-FRACTURE AND STRUCTURAL INTEGRITY 2021年第58期15卷 242-253页

作者： Mishra, Akshansh Vats, Apoorv Stir Res Technol Ctr Artificial Intelligent Mfg Syst Maharajganj India Jaypee Univ Informat Technol Dept Comp Sci & Engn Waknaghat India

Machine Learning focuses on the study of algorithms that are mathematical or statistical in nature in order to extract the required information pattern from the available data. Supervised Machine Learning algorithms are further sub-divided into two types i.e. regression algorithms and classification algorithms. In the present study, four supervised machine learning-based classification models i.e. Decision Trees algorithm, K-Nearest Neighbors (KNN) algorithm, Support Vector Machines (SVM) algorithm, and Ada Boost algorithm were subjected to the given dataset for the determination of fracture location in dissimilar Friction Stir Welded AA6061-T651 and AA7075-T651 alloy. In the given dataset, rotational speed (RPM), welding speed (mm/min), pin profile, and axial force (kN) were the input parameters while Fracture location is the output parameter. The obtained results showed that the Support Vector Machine (SVM) algorithm classified the fracture location with a good accuracy score of 0.889 in comparison to the other algorithms.

关键词： Fracture Location Machine Learning Classification Friction Stir Welding Dissimilar Joints python programming

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Empirical Study of the Evolution of python Questions on Stack Overflow

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E-INFORMATICA SOFTWARE ENGINEERING JOURNAL 2023年第1期17卷

作者： Syam, Gopika Lal, Sangeeta Chen, Tao Keele Univ Sch Comp Sci & Math Keele England Loughborough Univ Dept Comp Sci Loughborough England

Background: python is a popular and easy-to-use programming language. It is constantly expanding, with new features and libraries being introduced daily for a broad range of applications. This dynamic expansion needs a robust support structure for developers to effectively utilise the language. Aim: In this study we conduct an in-depth analysis focusing on several research topics to understand the theme of python questions and identify the challenges that developers encounter, using the questions posted on Stack Overflow. Method:We perform a quantitative and qualitative analysis of python questions in Stack Overflow. Topic Modelling is also used to determine the most popular and difficult topics among developers. Results: The findings of this study revealed a recent surge in questions about scientific computing libraries pandas and TensorFlow. Also, we observed that the discussion of Data Structures and Formats is more popular in the python community, whereas areas such as Installation, Deployment, and IDE are still challenging. Conclusion: This study can direct the research and development community to put more emphasis on tackling the actual issues that python programmers are facing.

关键词： python programming Software Development Stack Overflow Topic Modelling

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Analytical analyzing mixed convection flow of nanofluid in a vertical channel using python approach

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RESULTS IN PHYSICS 2023年 52卷

作者： Jalili, Payam Shateri, Amirali Ganji, Ali Mirzagoli Jalili, Bahram Ganji, Davood Domiri Islamic Azad Univ Dept Mech Engn North Tehran Branch Tehran Iran Babol Noshirvani Univ Technol Dept Mech Engn POB 484 Babol Iran

This study uses analytical methods to investigate the impact of parameters on the mixed convection flow of nanofluid in a vertical channel. The research aims to explore the heat transfer characteristics of nanofluids for more efficient heat transfer in devices. The study analyzes the influence of the Reynolds, Grashof, and Prandtl numbers on nanofluid flows. It also examines the effects of temperature and nanoparticle concentration distri-butions on parameters such as Brownian motion (Nb), thermophoresis (Nt), and Lewis number (Le). The presence of nanoparticles significantly enhances the heat transfer characteristics in the flow problem. Reynolds number, Grashof number, and Prandtl number significantly impact flow behavior. Velocity, temperature, and nano-particle volume fraction profile trends are thoroughly investigated and found to vary. Akbari-Ganji's method (AGM) and the homotopy perturbation method (HPM) demonstrate the potential of computational tools in analyzing nanotechnology fluid dynamics. The accuracy and reliability of the proposed analytical techniques are confirmed through comparisons with a numerical method. The novelty of this research lies in its comprehensive analysis of parameter effects on the mixed convection flow of nanofluid, the enhanced heat transfer character-istics in the presence of nanoparticles, and the unique contributions offered by the utilization of python pro-gramming in this field. The outcomes of this study provide insights for designing and optimizing heat transfer systems using nanofluids, contributing to advancements in nanotechnology.

关键词： Mixed convection Heat transfer Vertical channel Nanofluid python programming

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Smart Robotic Personal Assistant Vehicle Using Raspberry Pi and Zero UI Technology 6

Smart Robotic Personal Assistant Vehicle Using Raspberry Pi ...

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6th International Conference for Convergence in Technology (I2CT)

作者： Sunehra, Dhiraj Jhansi, B. Sneha, R. JNTUH Coll Engn Dept ECE Jagtial India

ISBN: (纸本)9781728188768

This paper presents a prototype of a smart robotic personal assistant vehicle based on Raspberry Pi and Zero-UI technology. Zero UI uses sensory experiences such as gestures, voice and movement to control the devices. A voice controlled robot vehicle implemented in this paper performs three functions, viz. movement of the robot is controlled using voice commands;it has the ability to articulate the text from a captured image using optical character recognition and present the equivalent audio to the user by using a built-in speaker or headset;it accepts voice commands from the user and uses Google Assistant API for any query processing and presents information searched on the Internet to the user in audio form using the built-in speaker or headset. This robotic personal assistant vehicle is a substitute to screen-based communication and makes use of Zero UI for its operation. In addition to the Raspberry Pi board, we use two DC motors to form the wheels of the robot, a webcam with built in microphone, a headset and motor driver IC to implement this robotic personal assistant vehicle. This system enables the visually impaired people to have access to useful information in the public domain by giving voice commands to the robot assistant. The robot can be realized as a wheel chair for the physically challenged. python programming language is used for the development of software code.

关键词： Raspberry Pi3 Robotic Personal Assistant Vehicle Zero-UI Technology Optical Character Recognition Tool Google Assistant API python programming

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