bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel approach for software defect prediction using CNN and GRU based on SMOTE Tomek method
Authors: Khleel Nasraldeen Alnor Adam , Nehéz Károly 
Published: May 2023

Abstract
Software defect prediction (SDP) plays a vital role in enhancing the quality of software projects and reducing maintenance-based risks through the ability to detect defective software components. SDP refers to using historical defect data to construct a relationship between software metrics and defects via diverse methodologies. Several prediction models, such as machine learning (ML) and deep learning (DL), have been developed and adopted to recognize software module defects, and many methodologies and frameworks have been presented. Class imbalance is one of the most challenging problems these models face in binary classification. However, When the distribution of classes is imbalanced, the accuracy may be high, but the models cannot recognize data instances in the minority class, leading to weak classifications. So far, little research has been done in the previous studies that address the problem of class imbalance in SDP. In this study, the data sampling method is introduced to address the class imbalance problem and improve the performance of ML models in SDP. The proposed approach is based on a convolutional neural network (CNN) and gated recurrent unit (GRU) combined with a synthetic minority oversampling technique plus the Tomek link (SMOTE Tomek) to predict software defects. To establish the efficiency of the proposed models, the experiments have been conducted on benchmark datasets obtained from the PROMISE repository. The experimental results have been compared and evaluated in terms of accuracy, precision, recall, F-measure, Matthew’s correlation coefficient (MCC), the area under the ROC curve (AUC), the area under the precision-recall curve (AUCPR), and mean square error (MSE). The experimental results showed that the proposed models predict the software defects more effectively on the balanced datasets than the original datasets, with an improvement of up to 19% for the CNN model and 24% for the GRU model in terms of AUC. We compared our proposed approach with existing SDP approaches based on several standard performance measures. The comparison results demonstrated that the proposed approach significantly outperforms existing state-of-the-art SDP approaches on most datasets.
The Impact of La Substitution on the Structural, Molecular, Morphological, and Thermal Properties of Mn0.6Zn0.4Fe2O4
Authors: Mostafa M. , Khalaf A. , El-Maghraby E. M. , Dagher R. A. , Hemeda O. M. 
Published: May 2023

Abstract
The current work involves the use of flash auto combustion procedure to synthesize nano-ferrites Mn0.6Zn0.4LaxFe2-xO4, (x = 0.00, 0.02, 0.04, 0.06, 0.08, and 0.10) annealing at 500 °C for 4 h. X-ray Diffraction (XRD), Fourier transition infrared spectroscopy (FTIR), and high-resolution transmission electron microscopy (HRTEM) were used to characterize the structural properties of produced samples. Scanning electron microscopy (SEM) was utilized to examine the surface morphology of the samples at various Lanthanum concentrations. From XRD, the spinel cubic structure for all samples with few traces of secondary phase at high La concentrations is assured. The crystallite size is estimated to be in the nanoscale range of 13.16–18.13 nm using the Debye–Scherrer formula. The appearance of characteristic vibrational bands near 460 cm−1 and 563 cm−1, which correspond to the octahedral and tetrahedral sites, respectively, confirms the formation of the spinel structure. SEM micrographs show that the grains are nearly irregular in shape, and the accumulation of La+3 ions at the grain boundaries exerts tensile strength and pressure on the grain itself, reducing the grain size. The particle size estimated by TEM coincides well with the crystallite size determined by XRD. The thermogravimetric analysis, (TGA), was used to investigate the thermal properties of the nanoferrites from room temperature to 1000 °C. In comparison to the other samples, the sample with x = 0.04 has greater thermal stability and the TEM measurement indicates that this sample has the smallest particle size. Therefore, we can assert that the thermal stability improves as the particle size decreases. The magnetic permeability was measured in the temperature range 303–773 K at a fixed frequency of 10 kHz and at various La contents. The sample with x = 0.04 has a minimal permeability value, showing that the separation brought on by La ions has diminished the super exchange contact between magnetic ions.
Classifier calibration: a survey on how to assess and improve predicted class probabilities
Authors: Silva Filho Telmo , Song Hao , Perello-Nieto Miquel , Santos-Rodriguez Raul , Kull Meelis , Flach Peter 
Published: May 2023

AbstractThis paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of uncertainty or confidence associated with its instance-wise predictions. This is essential for critical applications, optimal decision making, cost-sensitive classification, and for some types of context change. Calibration research has a rich history which predates the birth of machine learning as an academic field by decades. However, a recent increase in the interest on calibration has led to new methods and the extension from binary to the multiclass setting. The space of options and issues to consider is large, and navigating it requires the right set of concepts and tools. We provide both introductory material and up-to-date technical details of the main concepts and methods, including proper scoring rules and other evaluation metrics, visualisation approaches, a comprehensive account of post-hoc calibration methods for binary and multiclass classification, and several advanced topics.
An effective text plagiarism detection system based on feature selection and SVM techniques
Authors: El-Rashidy Mohamed A. , Mohamed Ramy G. , El-Fishawy Nawal A. , Shouman Marwa A. 
Published: May 2023

AbstractText plagiarism has greatly spread in the recent years, it becomes a common problem in several fields such as research manuscripts, textbooks, patents, academic circles, etc. There are many sentence similarity features were used to detect plagiarism, but each of them is not discriminative to differentiate the similarity cases. This causes the discovery of lexical, syntactic and semantic text plagiarism types to be a challenging problem. Therefore, a new plagiarism detection system is proposed to extract the most effective sentence similarity features and construct hyperplane equation of the selected features to distinguish the similarity cases with the highest accuracy. It consists of three phases; the first phase is used to preprocess the documents. The second phase is depended on two paths, the first path is based on traditional paragraph level comparison, and the second path is based on the computed hyperplane equation using Support Vector Machine (SVM) and Chi-square techniques. The third phase is used to extract the best plagiarized segment. The proposed system is evaluated on several benchmark datasets. The experimental results showed that the proposed system obtained a significant superiority in the performance compared to the systems with a higher ranking in the recent years. The proposed system achieved the best values 89.12% and 92.91% of the Plagdet scores, 89.34% and 92.95% of the F-measure scores on the complete test corpus of PAN 2013 and PAN 2014 datasets, respectively.
Volumetric hippocampal changes in glioblastoma: a biomarker for neuroplasticity?
Authors: Zilioli Alessandro , Misirocchi Francesco , Mutti Carlotta , Pancaldi Beatrice , Mannini Elisa , Spallazzi Marco , Parrino Liborio , Cerasti Davide , Michiara Maria , Florindo Irene 
Published: May 2023

Abstract
Purpose
The pleiotropic effect of gliomas on the development of cognitive disorders and structural brain changes has garnered increasing interest in recent years. While it is widely accepted that multimodal therapies for brain cancer can foster cognitive impairment, the direct effect of gliomas on critical cognitive areas before anti-tumor therapies is still controversial. In this study, we focused on the effect of IDH1 wild-type glioblastoma on the human hippocampus volume.

Methods
We carried out a case-control study using voxel-based morphometry assessment, analyzed with the Computational Anatomy Toolbox software. Glioblastoma diagnosis was performed according to the latest 2021 WHO classification. Due to stringent inclusion criteria, 15 patients affected by IDH1 wild type glioblastoma were included and compared to 19 age-matched controls.

Results
We observed a statistically significant increase in the absolute mean hippocampal volume (p = 0.017), as well as in the ipsilateral (compared to the lesion, p = 0.027) and the contralateral hippocampal volumes (p = 0.014) in the group of patients. When the data were normalized per total intracranial volume, we confirmed a statistically significant increase only in the contralateral hippocampal volume (p = 0.042).

Conclusions
To the best of our knowledge, this is the first study to explore hippocampal volumetric changes in a cohort of adult patients affected by IDH1 wild-type glioblastoma, according to the latest WHO classification. We demonstrated an adaptive volumetric response of the hippocampus, which was more pronounced on the side contralateral to the lesion, suggesting substantial integrity and resilience of the medial temporal structures before the initiation of multimodal treatments.
Splitting of the Effective Rabi Frequencies for the Coherent Plasmonic Fields in the Semiconductor Quantum Dot–Metal Nanospheres Hybrids
Authors: Abd-Elnabi Somia , Ali Hagar M. 
Published: May 2023

AbstractSplitting of the effective Rabi frequencies for plasmonic fields when the interaction occurs between semiconductor quantum dot and three metallic nanospheres in the presence of three electromagnetic fields is examined. We study theoretically the role of the dipole–dipole interactions in creating many Multipoles. Then, we split the effective Rabi frequencies into three parts according to the quantitative Multipoles of the plasmonic fields. The density matrix equations are derived for the description of the optical properties of the SQD-MNPs nanosystem. We investigate the influence of each part of the effective Rabi frequencies and compare them with each other individually. The three parts of the effective Rabi frequency for the probe field are affected by changing the angles, the strong probe field and other parameters for the hybrid system.
The Mechanical and Tribological Properties of Cold-Sprayed Cermet Coatings—Al Alloy Substrate Systems
Authors: Trelka Anna , Góral Anna , Żórawski Wojciech , Gancarz Tomasz , Petrzak Paweł 
Published: May 2023

AbstractThe article describes the influence of a solid lubricant such as graphite on the coating-substrate adhesion, susceptibility to cracking during three-point bending tests and tribological properties of the cermet coating-substrate systems. Two types of deposits Cr3C2-25(Ni20Cr) and (Cr3C2-25(Ni20Cr))-5(Ni25C), cold-sprayed on the Al 7075 alloy substrate, were analyzed. The Cr3C2-25(Ni20Cr) coatings showed a homogeneous microstructure with evenly distributed ceramic particles in a Ni20Cr matrix. The (Cr3C2-25(Ni20Cr))-5(Ni25C) deposits also contained graphite placed both between metallic particles and near the crushed ceramic Cr3C2 particles. The force required for the crack that appeared in the coating-substrate system during the three-point bending test under constant velocity was significantly higher in the case of (Cr3C2-25(Ni20Cr))-5(Ni25C) deposit than in that without the solid lubricant. The cracks were observed perpendicular to the coating-substrate interface. The graphite embedded in the cermet coating structure prevented the formation of crack nuclei during three-point bending test under cyclic load at room temperature and reduced the size of cracks in the deposit at 200 °C. Both cermet coatings revealed the same adhesion. The addition of graphite not only did not deteriorate the adhesion of the deposits and thus their quality but also improved their other properties, such as flexural strength and wear resistance. Coatings containing the solid lubricant showed a lower wear index than the Cr3C2-25(Ni20Cr) deposits examined at both room and elevated temperatures. This recommends their use in industry as deposit working in heavy wear conditions. The presented results of mechanical tests effectively fill the gap regarding the properties of the cold-sprayed cermet coatings.
Fatal gastric volvulus: forensic pathology considerations and postmortem CT findings
Authors: Littlewood Marcus , O’Donnell Chris , Parsons Sarah , Archer Melanie S. , de Boer Hans H. 
Published: May 2023

Abstract
Gastric volvulus is a rare cause of gastric obstruction, due to the rotation of the stomach by more than 180°. It is a rare but life-threatening medical emergency that is considered difficult to diagnose at the initial clinical presentation. Forensic pathologists may be presented with gastric volvulus in several ways, for instance, as a cause of sudden and unexpected death or in the context of suspected clinical errors. The post-mortem examination of gastric volvulus may be challenging, due to the specific technical issues it presents and the various mechanisms by which volvulus may cause death. We therefore present five cases of gastric volvulus that in combination represent almost the entire spectrum of presentations and post-mortem findings, to discuss how gastric volvulus may come to the attention of a forensic pathologist, the approach and findings at post-mortem examination (including post-mortem CT), and the variety of mechanisms by which gastric volvulus may result in death.
Parental exhaustion during COVID-19 pandemic: links to relationship outcomes and dyadic coping
Authors: Carvalho Matilde , Matias Marisa 
Published: May 2023

AbstractThe COVID-19 pandemic and lockdown altered families? routines, from telework imposition to performing additional childcare, as children started studying at home. Adapting to these demands can have effects on couples’ relationships. This study aimed to analyze couples? experiences of parental exhaustion during the lockdown and to understand its links to relationship satisfaction and conflict frequency. It also explored how couples’ internal resources (e.g., dyadic coping) buffered these effects. We examined data from 210 individuals in a romantic relationship who were cohabiting with their partners, teleworking, and had children under 18. Absolute values of parental exhaustion and relationship quality were not severe, but there was evidence that parental exhaustion contributed to decreasing relationship satisfaction and increasing conflict. Positive forms of dyadic coping were found to moderate only the adverse effects on conflict frequency. Implications of these results to couple’s support under stressful events are provided.
Improving Detection of Changepoints in Short and Noisy Time Series with Local Correlations: Connecting the Events in Pixel Neighbourhoods
Authors: Rajala Tuomas , Packalen Petteri , Myllymäki Mari , Kangas Annika 
Published: May 2023

AbstractDetecting changepoints in time series becomes difficult when the series are short and the observation variance is high. In the context of time series of environmental resource maps, it is often safe to assume that the abrupt events are spatially continuous, and so are the changepoints. We propose to utilise this assumption by means of hierarchical models where the changepoints are modelled using a spatial model. We demonstrate utility of the approach by constructing a Bayesian model based on the Potts model, with additional assumptions relevant to changepoint detection in national multi-source forest inventory maps. We discuss implementation issues and demonstrate the idea’s performance using a simulation study. We then apply the model to forest resource maps in order to detect felling events.
Nonsingular fixed-time sliding mode control for synchronization of chaotic reaction systems; a case study of Willamowski–Rossler reaction model
Authors: Soltani Sharif Abadi Ali , Hosseinabadi Pooyan Alinaghi , Dehkordi Pouya Heidarpoor 
Published: May 2023

AbstractNonsingular Fixed-time Sliding Mode Control (NFSMC) method is one of the nonlinear control methods which is robust against uncertainties and external disturbances. This paper presents an NFSMC method to synchronize two similar Willamowski–Rossler reaction chaotic systems. The proposed control method is robust against uncertainties and external disturbances; also, it is an accurate and fast control method. The proposed control method is compared with a Nonsingular Terminal Sliding Mode Control. The comparison results show that the proposed control method provides a better control solution for this system.
Handwritten Arabic Character Recognition for Children Writing Using Convolutional Neural Network and Stroke Identification
Authors: Alheraki Mais , Al-Matham Rawan , Al-Khalifa Hend 
Published: May 2023

AbstractAutomatic Arabic handwritten recognition is one of the recently studied problems in the field of Machine Learning. Unlike Latin languages, Arabic is a Semitic language that forms a harder challenge, especially with the variability of patterns caused by factors such as the writer’s age. Most studies have focused on adults, with only one recent study on children. Moreover, many recent machine-learning methods have focused on using Convolutional Neural Networks (CNNs), a powerful class of neural networks that can extract complex features from images. In this paper, we propose a convolutional neural network (CNN) model that recognizes children’s handwriting with an accuracy of 91% on the Hijja dataset, a recent dataset built by collecting images of Arabic characters written by children, and 97% on the Arabic Handwritten Character Dataset. The results showed a good improvement over the proposed model from the Hijja dataset authors, yet it revealed a bigger challenge to solve for children’s Arabic handwritten character recognition. Moreover, we proposed a new approach using multiple models instead of a single model based on the number of strokes in a character and merged Hijja with AHCD, which achieved an average prediction accuracy of 96%.
Joint mediation of psychological empowerment and work–life balance between transformational leadership and in-role performance of accounting personnel: 360-degree feedback
Authors: Ugwoke Ernest O. , Edeh Nathaniel Ifeanyi , Nwokike Felicia Ogonnia , Ugwunwoti Emeka Promise , Emmanuel Wama Binga , Idris Benuh Adama , Odey Clement , Samson Joshua , Nnamani Victoria Obiageli , Yaro Joseph Tunga , Eya Gloria Mgboyibo , Arua Gold Chiamaka , Guma Elisha Terkuma , Kingsley Joseph Bonglo 
Published: May 2023

Abstract
The study determined whether psychological empowerment and work–life balance jointly mediate between transformational leadership and in-role performance of employees in Nigerian not-for-profit (NFP) universities using data collected through a 360-degree performance review of employees. Data were collected from the employees, their supervisors, colleagues, and customers. A sample of 360 comprising 36 faculty finance officers (the employees), 36 assistant faculty finance officers (colleagues), 36 deans of faculties (supervisors), 36 finance supervisors (supervisors), 108 undergraduate and 108 postgraduate students (customers) from Nigerian universities were surveyed using Multifactor Leadership Questionnaire, employees' in-role performance questionnaire, four dimensions of psychological empowerment questionnaire, and work–life balance questionnaire. The reliabilities of the questionnaires were estimated using Cronbach's α technique. Data collected were analyzed using descriptive statistics and correlations at the preliminary level, while three separate Hierarchical Multiple Regression and 5000 re-samples BC bootstrapping method on PROCESS macro were used to test the hypotheses to determine the total, direct, and indirect effects of the study variables. The study established that psychological empowerment and work–life balance jointly and significantly mediated the high relationship between transformational leadership and the in-role performance of the faculty finance officers. The implications for researchers and organizational practitioners, limitations, and suggestions for future research were discussed.
Hammer or Measuring Tape? Artificial Intelligence and Justice in Healthcare
Authors: Heinrichs Jan-Hendrik 
Published: May 2023

AbstractArtificial intelligence (AI) is a powerful tool for several healthcare tasks. AI tools are suited to optimize predictive models in medicine. Ethical debates about AI’s extension of the predictive power of medical models suggest a need to adapt core principles of medical ethics. This article demonstrates that a popular interpretation of the principle of justice in healthcare needs amendment given the effect of AI on decision-making. The procedural approach to justice, exemplified with Norman Daniels and James Sabin’s accountability for reasonableness conception, needs amendment because, as research into algorithmic fairness shows, it is insufficiently sensitive to differential effects of seemingly just principles on different groups of people. The same line of research generates methods to quantify differential effects and make them amenable for correction. Thus, what is needed to improve the principle of justice is a combination of procedures for selecting just criteria and principles and the use of algorithmic tools to measure the real impact these criteria and principles have. In this article, the author shows that algorithmic tools do not merely raise issues of justice but can also be used in their mitigation by informing us about the real effects certain distributional principles and criteria would create.
Early Evolution of the Stratospheric Aerosol Plume Following the 2022 Hunga Tonga‐Hunga Ha'apai Eruption: Lidar Observations From Reunion (21°S, 55°E)
Authors: Baron A. , Chazette P. , Khaykin S. , Payen G. , Marquestaut N. , Bègue N. , Duflot V. 
Published: May 2023

AbstractThe exceptionally violent eruption of the Hunga Tonga‐Hunga Ha'apai volcano (HTHH) of 15 January 2022, in the South Pacific, was associated with a powerful blast that injected gases, steam and aerosol to unprecedentedly high altitudes. This article details unique observations of the young volcanic plume from ground‐based lidars at Reunion (21°S, 55°E). Two lidars, operating at wavelengths of 355 and 532 nm, recorded the plume overhead from 19 January until 28 January providing the vertical structure and the optical properties of the plume. A series of thick stratospheric plumes between 36 and 18 km altitude have been characterized along time, with aerosol optical depth as high as 0.84 at 532 nm and negative Angström exponents for the main layers down to −0.8 ± 0.8. The diversity of plumes properties is explained by the injection heights of the volcanic material as well as stratospheric dynamics and chemistry.