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IEEE-Uttar-Pradesh-Section International Conference on Electrical, Computer, and Electronics Engineering (UPCON)

作者： Baghel, Manoj Ghosh, Abir Singh, Navneet Kumar Singh, Asheesh Kumar MNNIT Allahabad Elect Engn Dept Allahabad 211004 Uttar Pradesh India

ISBN: (纸本)9781509053841

Electrical load forecasting is an important topic within the electrical market which has been done by a machine learning methodology: Support Vector Machines (SVM). Load forecasting with SVM will form the non-linear relations with the parameters that have an effect on the load;additionally to the correct modeling of the load curve on weekends and holidays. The past information is used as a sample for the applying and therefore holidays associated demand as an important factor inprediction. The LibSVM package and python codeis usedfor modeling the SVM. Resultsare obtainedand comparison is made for the two methods.

关键词： Kernel functions LIBSVM package python code Support Vector Machine (SVM)

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A python code For Maximum Likelihood Estimation Of The Location And Scale Parameters Of The Truncated Normal Distribution

A Python Code For Maximum Likelihood Estimation Of The Locat...

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Medical Technologies Congress (TIPTEKNO'21)

作者： Ogutcen, Melih Yilmaz Kocaturk, Mehmet Okatan, Murat Istanbul Tech Univ Inst Informat Istanbul Turkey Istanbul Medipol Univ Dept Biomed Engn Istanbul Turkey

ISBN: (纸本)9781665436632

Extracellular neural recordings obtained from chronically implanted microelectrode arrays are widely used in behavioral neurophysiology and invasive brain-machine interfaces. After the raw recordings are band-pass filtered within a frequency band suitable for spike detection, spikes are often detected by amplitude thresholding. Developing principled methods for computing amplitude thresholds is an active research area. `Truncation thresholds' are a pair of amplitude thresholds that are computed using a recently proposed algorithm. As part of an effort that aims to integrate this algorithm into a real-time data acquisition and spike detection system, here we present a python code for maximum likelihood estimation of the location and scale parameters of the truncated Normal distribution, which is one of the steps involved in the computation of truncation thresholds.

关键词： truncated Normal distribution maximum likelihood estimation python code truncation thresholds

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Pablo and Pyrite: Helping Novices Debug python code Through Data-Driven Fault Localization and Repair

Pablo and Pyrite: Helping Novices Debug Python Code Through ...

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作者： Cosman, Benjamin University of California San Diego

学位级别：Ph.D., Doctor of Philosophy

As dynamically-typed languages grow in popularity, especially among beginning programmers, novices have an increased need for scalable, helpful feedback for fixing their *** and repair can be ambiguous: not all repairs which prevent the program from crashing are equally useful for beginners. We propose scalable approaches for fault localizationand repair for dynamic languages that are helpful for debugging and generalize to handle a wide variety of errors commonly faced by novice programmers. We base our approach on acombination of static, dynamic, and contextual features, guided by machine learning. We evaluate on over 980,000 diverse real user interactions across four years from the popular *** website, which is used both in classes and by non-traditional learners. We find that our approach isscalable, general, and quite accurate: up to 77% of these historical novice users would have been helped by our top-three localization responses, compared to 45% for the default interpreter, and we successfully synthesize repairs to 76% of our historical buggy programs. We also conducted two human studies. Participants preferred our localization approach to the baseline (p = 0.018), and found it additionally useful for bugs meriting multiple edits. Participants found our repairs to contain helpful information beyond the baseline in 45% of programs.

关键词： python code Programming languages Debug Data-driven Fault localization

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Is the Corpus Ready for Machine Translation? A Case Study with python to Pseudo-code Corpus

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023年第2期48卷 1845-1858页

作者： Rai, Sawan Belwal, Ramesh Chandra Gupta, Atul PDPM Indian Inst Informat Technol Design & Mfg Jabalpur 482005 India

The availability of data is the driving force behind most of the state-of-the-art techniques for machine translation tasks. Understandably, this availability of data motivates researchers to propose new techniques and claim about the superiority of their techniques over the existing ones by using suitable evaluation measures. However, the performance of underlying learning algorithms can be greatly influenced by the correctness and the consistency of the corpus. We present our investigations for the relevance of a publicly available python to pseudo-code parallel corpus for automated documentation task, and the studies performed using this corpus. We found that the corpus had many visible issues like overlapping of instances, inconsistency in translation styles, incompleteness, and misspelled words. We show that these discrepancies can significantly influence the performance of the learning algorithms to the extent that they could have caused previous studies to draw incorrect conclusions. We performed our experimental study using statistical machine translation and neural machine translation models. We have recorded a significant difference (similar to 10% on BLEU score) in the models' performance after removing the issues from the corpus.

关键词： Parallel corpus python code Pseudo-code Statistical machine translation Neural machine translation

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Guest Editorial:Special Section on SC22 Student Cluster Competition

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2025年第5期36卷 803-803页

作者： Rana, Omer Spillner, Josef Leak, Stephen Lofstead II, Gerald F. Calasanz, Rafael Tolosana Cardiff Univ Cardiff CF14 4XY England Zurich Univ Appl Sci CH-8401 Winterthur Switzerland Natl Energy Res Sci Comp Ctr Berkeley CA 94720 USA Sandia Natl Labs Livermore CA 94551 USA Univ Zaragoza Zaragoza 50018 Spain

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Detecting and Explaining python Name Errors

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INFORMATION AND SOFTWARE TECHNOLOGY 2025年 178卷

作者： Wang, Jiawei Li, Li Liu, Kui Du, Xiaoning Monash Univ Fac Informat Technol Melbourne 3168 Australia Beihang Univ Sch Software Beijing 100191 Peoples R China Huawei Software Engn Applicat Technol Lab Hangzhou Peoples R China Monash Univ Fac Informat Technol Melbourne 3800 Australia

python has become one of the most popular programming languages nowadays but has not received enough attention from the software engineering community. Many errors, either fixed or not yet, have been scattered in the lifetime of python projects, including popular python libraries that have already been reused. NameError is among one of those errors that are widespread in the python community, as confirmed in our empirical study. Yet, our community has not put effort into helping developers mitigate its introductions. To fill this gap, we propose in this work a static analysis-based approach called DENE (short for D etecting and E xplaining N ame E rrors) to automatically detect and explain name errors in python projects. To this end, DENE builds control-flow graphs for python projects and leverages a scope-aware reaching definition analysis to locate identifiers that may cause name errors at runtime and report their locations. Experimental results on carefully crafted ground truth demonstrate that DENE is effective in detecting name errors in real-world python projects. The results also confirm that unknown name errors are still widely presented in popular python projects and libraries, and the outputs of DENE can indeed help developers understand why the name errors are flagged as such.

关键词： Static analysis python code Tools Empirical studies

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Exploring topological indices and entropy measures of phenylacetone monooxygenase by using python coding

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JOURNAL OF MOLECULAR GRAPHICS & MODELLING 2025年 137卷 108981页

作者： Ismail, Rashad Noreen, Rimsha Hanif, Muhammad Farhan Hanif, Muhammad Faisal Siddiqui, Muhammad Kamran King Khalid Univ Fac Sci & Arts Dept Math Abha 61913 Mahayl Assir Saudi Arabia COMSATS Univ Islamabad Dept Math Lahore Campus Lahore Pakistan Univ Lahore Dept Math & Stat Lahore Campus Lahore Pakistan

Topological indices are essential for evaluating a compound's physicochemical characteristics. Computing the various topological indices of any molecular structure helps to comprehend their physical characteristics and they are also extremely useful for predicting the properties of chemical and biological compounds in QSPR and QSAR ***, Shanon entropy idea a bit different but provide the structural properties of a molecular graph. The atom in the molecular graph of PAMO are considered as a nodes and bonds are weighted edges. For computing the topological indices and edge weight based entropy for phenylacetone monooxygenase enzyme python has been utilized.

关键词： Zagreb type index Forgotten index Balaban index Redefined first Second and third zagreb index Phenylacetone monooxygenase (PAMO) python code

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Environmental and health risk assessment of polycyclic aromatic hydrocarbons and toxic elements in the red sea using Monte Carlo simulation

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SCIENTIFIC REPORTS 2025年第1期15卷 1-20页

作者： Sayed, F. Alshaima Eid, Mohamed Hamdy El-Sherbeeny, Ahmed M. Abdel-Gawad, Gouda Ismail Mohamed, Essam A. Abukhadra, Mostafa R. Beni Suef Univ Fac Earth Sci Bani Suwayf 62511 Egypt Shenzhen Univ Shenzhen Key Lab Green Efficient & Intelligent Con Shenzhen Peoples R China Univ Miskolc Inst Environm Management Fac Earth Sci H-3515 Miskolc Hungary Beni Suef Univ Fac Sci Geol Dept Bani Suwayf Egypt King Saud Univ Coll Engn Ind Engn Dept POB 800 Riyadh 11421 Saudi Arabia

This research evaluates the environmental and health risks linked to potentially toxic elements (PTEs) and PAHs along the western coast of the Gulf of Suez, Egypt. This study investigated the concentration of 16 PAH compounds in the Suez Gulf, revealing significantly higher levels than the EU (0.20 mu g/L) and US (0.030 mu g/L) standards. The average total PAH concentration across eight locations was significantly higher, with the Suez area having the highest concentration at 479 mu g/L. Pyrene (Pyr) was the dominant PAH with a concentration of 443 mu g/L in Suez, while acenaphthylene (Ace) had the lowest concentration at 0.120 mu g/L in Northern Zaafarana. Carcinogenic PAHs (CAR) ranged from 8.67 mu g/L at Ras Gharib to 29.62 mu g/L at Suez, highlighting the urgent need for regulatory measures. Confirmatory ratios pointed to industrial and shipping influences as petrogenic sources. Elevated total organic carbon (TOC) levels in Suez Bay indicated aggravated organic pollution, exacerbated by oil rigs and refineries. The ecological risk assessment highlighted substantial risks, particularly in Suez, necessitating immediate interventions to combat PAH contamination and preserve the environmental balance of the Red Sea. The dominant metals in water samples were arranged in descending order as follows: Pb > Fe > Cr > Cu > Zn > Mn > Cd > Ni. The study evaluated environmental and human health risks using a multifaceted approach, including cluster analysis, principal component analysis, and various indices (HPI, RI, MI, HQ, HI, and CR). Most water samples exhibited high pollution risks, surpassing permissible limits for HPI (> 100) and MI (> 6). Notably, HI oral values indicated significant non-carcinogenic risks for adults and children. While HI values for adults suggested low-risk dermal contact, those for children showed a substantial proportion in the high-risk category. Most water samples displayed CR values exceeding 1 x 10(-4) for Cd, Cr, and Pb, indicating vulnerabi

关键词： PTE pollution indices Carcinogenic and non-carcinogenic risk Monte Carlo simulation python code PAHs Red Sea

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Introduction to python Dynamic Diffraction Toolkit (PyDDT): structural refinement of single crystals via X-ray phase measurements

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JOURNAL OF APPLIED CRYSTALLOGRAPHY 2023年第5期56卷 1574-1584页

作者： Penacchio, Rafaela F. S. Estradiote, Mauricio B. Remedios, Claudio M. R. Calligaris, Guilherme A. Torikachvili, Milton S. Kycia, Stefan W. Morelhao, Sergio L. Univ Sao Paulo Inst Phys Sao Paulo SP Brazil Univ Fed Para Fac Fis Belem Para Brazil CNPEM Brazilian Synchrotron Light Lab SIRIUS Campinas SP Brazil San Diego State Univ Dept Phys San Diego CA 92182 USA Univ Guelph Dept Phys Guelph ON Canada

PyDDT is a free python package of computer codes for exploiting X-ray dynamic multiple diffraction in single crystals. A wide range of tools are available for evaluating the usefulness of the method, planning feasible experiments, extracting phase information from experimental data and further improving model structures of known materials. Graphical tools are also useful in analytical methodologies related to the three-dimensional aspect of multiple diffraction. For general X-ray users, the PyDDT tutorials provide the insight needed to understand the principles of phase measurements and other related methodologies. Key points behind structure refinement using the current approach are presented, and the main features of PyDDT are illustrated for amino acid and filled skutterudite single crystals.

关键词： X-ray dynamic diffraction single crystals triplet phase determination python code

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A New Autonomous Program Customized for Computing Surface Cracks in an Unsaturated Soil in a 1-D Column

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JOURNAL OF TESTING AND EVALUATION 2019年第5期47卷 3822-3835页

作者： Anangsha, A. Gadi, Vinay Kumar Bordoloi, Sanandam Kothapalli, Sai Krishna Sreedeep, S. Mei Guoxiong Garg, Ankit Indian Inst Technol Guwahati Dept Civil Engn Gauhati 781039 India Indian Inst Technol Guwahati Dept Comp Sci & Engn Gauhati 781039 India Guangxi Univ Sch Civil Engn & Architecture Nanning 530005 Peoples R China Shantou Univ Dept Civil & Environm Engn Shantou 515063 Peoples R China

The quantification of soil surface cracks is important, as it is useful in analyzing water infiltration and overall water balance in any green infrastructure, such as slopes, agricultural fields, green roofs, etc. In previously reported studies, the approaches for quantifying cracks mainly used manual processing of images through the public domain image analysis tool ImageJ. Such software is not customized for quantifying cracks in an unsaturated soil surface, as this results in relatively higher noise (i.e., lower resolution) in the processed image. Furthermore, manual processing makes processing of images in large quantities (usually captured through unmanned aerial vehicle (UAV) surveying) cumbersome. This technical note introduces an autonomous novel image analysismethod for characterizing surface crack patterns that develop in unsaturated soils. A simple experimental setup was developed using a 1-D column containing red soil. The soil was compacted by hand to the desired state of compaction and placed in an environment-controlled chamber where it was allowed to dry. A series of images of the soil sample was captured using a commercially available camera model (Canon EOS 700D) to have photographic representation of the cracking process. A step-by-step strategy using a script coded in python was developed to analyze the images captured during the laboratory tests. It outlines how image analysis can be automated to remove observer-dependent subjectivity (involved inmanual processing of images) and introduces reproducibility of results. In addition, it effectively quantifies cracks in unsaturated soils with a much lower processing time and higher accuracy (less noise).

关键词： surface cracks autonomous customized lower noise python code

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