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17,455 results on '"Iqra ."'

304. Influence of Mg2+ substitution on structural, electrical polarization, and magnetic properties of Sr-based R-type hexagonal ferrites

Author

Iqra Ijaz, Sana Muhammad din, Raja Hamza Arshad, Samreen Saeed, Imran Sadiq, Farhan Sadiq, Mishal Idrees, Sajjad Hussain, Muhammad Shahbaz, Sadaf Naz, Muhammad Jamshaid Shabbir, Saira Riaz, Shahzad Naseem, and Farooq Ahmad

Subjects
Industrial electrochemistry, TP250-261
Abstract

Substitutional effects of Mg2⁺ proceeding the structural, Fourier-transform infrared spectroscopy, scanning electron microscopy, and vibrating sample magnetometer characteristics of Sr₁₋ₓMgₓMn₂Fe₄O₁₁ R-type hexaferrite were systematically investigated for different concentrations (x = 0, 0.25, 0.75, 1.0). Sol-gel technique was adopted to fabricate the material. X-ray diffraction analysis confirmed samples exhibit a single-phase structure of MgMn₂Fe₄O₁₁. Lattice parameters (a and c) and V (unit cell volume) decreased with increasing Mg concentration. Also, a rise in dislocation density was observed, while crystallite size varied. FTIR spectra further corroborated the single-phase hexagonal structure of the manufactured samples. The electric polarization (P-E) loops demonstrated that saturation and Pr remanent polarization increased with Mg substitution, while lossy behavior decreased. Magnetic measurements revealed that substituting Mg2⁺ directed toward an initial escalation in saturation magnetization, retentivity, and coercivity, followed by a subsequent decline. Furthermore, VSM analysis indicated that all samples exhibited a combination of ferrimagnetic and paramagnetic behavior.

Published
2024
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305. Impact of Knowledge Sharing on Employee Performance in Higher Education: Moderating Role of Employee Motivation and Employee Engagement

Author

Iqra Bibi, Asad Tufail, and Haider Ali Shah

Subjects
employee engagement, employee motivation, employee performance, knowledge sharing, Management. Industrial management, HD28-70, Business, HF5001-6182
Abstract

The objective is to assess the impact of knowledge sharing, employee motivation, and employee engagement on overall performance. The quantitative research method is used to collect primary data through an adoptive structured questionnaire based on a 5-Likert scale. The responses are recorded from 322 respondents through the method of sampling in many stages. Using SmartPLS software, recorded responses are examined using statistical tests (such as regression and correlation). The results indicate a positive relationship among knowledge sharing, employee engagement, motivation, and performance. All hypotheses (H1, H2, H3) were accepted with t-values exceeding 1.96. This study elaborates on how knowledge sharing along with the moderating effects of motivation and engagement, improves employee performance, particularly in the academic sector. It also adds to the existing literature on these relationships.

Published
2024
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307. Hausdorff dimension of Besicovitch sets of Cantor graphs

Author

Altaf, Iqra, Csörnyei, Marianna, and Héra, Kornélia

Subjects
Mathematics - Metric Geometry
Abstract

We consider the Hausdorff dimension of planar Besicovitch sets for rectifiable sets $\Gamma$, i.e. sets that contain a rotated copy of $\Gamma$ in each direction. We show that for a large class of Cantor sets $C$ and Cantor-graphs $\Gamma$ built on $C$, the Hausdorff dimension of any $\Gamma$-Besicovitch set must be at least $\min\left(2-s^2,\frac{1}{s}\right)$, where $s=\dim C$.

Published
2022

308. Job Offers Classifier using Neural Networks and Oversampling Methods

Author

Ortiz, Germán, Enguix, Gemma Bel, Gómez-Adorno, Helena, Ameer, Iqra, and Sidorov, Grigori

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Both policy and research benefit from a better understanding of individuals' jobs. However, as large-scale administrative records are increasingly employed to represent labor market activity, new automatic methods to classify jobs will become necessary. We developed an automatic job offers classifier using a dataset collected from the largest job bank of Mexico known as Bumeran https://www.bumeran.com.mx/ Last visited: 19-01-2022.. We applied machine learning algorithms such as Support Vector Machines, Naive-Bayes, Logistic Regression, Random Forest, and deep learning Long-Short Term Memory (LSTM). Using these algorithms, we trained multi-class models to classify job offers in one of the 23 classes (not uniformly distributed): Sales, Administration, Call Center, Technology, Trades, Human Resources, Logistics, Marketing, Health, Gastronomy, Financing, Secretary, Production, Engineering, Education, Design, Legal, Construction, Insurance, Communication, Management, Foreign Trade, and Mining. We used the SMOTE, Geometric-SMOTE, and ADASYN synthetic oversampling algorithms to handle imbalanced classes. The proposed convolutional neural network architecture achieved the best results when applied the Geometric-SMOTE algorithm., Comment: 13 pages, 2 figures, 8th World Conference On Soft Computing

Published
2022

309. Mental Illness Classification on Social Media Texts using Deep Learning and Transfer Learning

Author

Ameer, Iqra, Arif, Muhammad, Sidorov, Grigori, Gòmez-Adorno, Helena, and Gelbukh, Alexander

Subjects
Computer Science - Machine Learning, Computer Science - Computation and Language, Computer Science - Computers and Society
Abstract

Given the current social distance restrictions across the world, most individuals now use social media as their major medium of communication. Millions of people suffering from mental diseases have been isolated due to this, and they are unable to get help in person. They have become more reliant on online venues to express themselves and seek advice on dealing with their mental disorders. According to the World health organization (WHO), approximately 450 million people are affected. Mental illnesses, such as depression, anxiety, etc., are immensely common and have affected an individuals' physical health. Recently Artificial Intelligence (AI) methods have been presented to help mental health providers, including psychiatrists and psychologists, in decision making based on patients' authentic information (e.g., medical records, behavioral data, social media utilization, etc.). AI innovations have demonstrated predominant execution in numerous real-world applications broadening from computer vision to healthcare. This study analyzes unstructured user data on the Reddit platform and classifies five common mental illnesses: depression, anxiety, bipolar disorder, ADHD, and PTSD. We trained traditional machine learning, deep learning, and transfer learning multi-class models to detect mental disorders of individuals. This effort will benefit the public health system by automating the detection process and informing appropriate authorities about people who require emergency assistance., Comment: 11 pages, 2 figures, 8th World Conference On Soft Computing

Published
2022

310. Unwilling Co-Wives and the Law of Polygamy in Pakistan

Author

Khan, Iqra Saleem

Abstract

This paper is a legal realist endeavor that seeks to uncover a thorough and exhaustive description of Polygamy Law in Pakistan before moving on to a prescriptive analysis. Having an understanding of the stakes involved, background rules at play and the inadequacies within the law can be immensely useful in identifying the harm and redressing it. Thus, in first separating the “Is” from the “Ought”, Part I describes Pakistani polygamy Law and the limited legal remedies available to unwilling cowives. In Part II, the “background rules” driving the bargain amongst the parties’ to enter (or leave) polygamous marriages is discussed. Thereafter in Part III, a distributive analysis is conducted using “ideal-types” to uncover polygamy’s dual nature as a security or a threat for all the parties impacted by the law. Here I rely on the idea that marital partners “bargain in the shadow of the law” with bargaining endowments created in part by the legal rules. By comparing four typical but contrasting marriages and examining the rules about the formation and breakup of polygamous marriages, the role of the pre-existing and new wife’s consent (or not) and the economic consequences of poly-formation in ongoing and divorcing marriages, I demonstrate that the surpluses generated and distributions currently in place can both benefit and harm the cowives. Finally, Part IV will prescribe a restorative justice approach to the situation of unwilling cowives, arguing that the solution ought to be focused on redressing the social, emotional and economic harm caused to unwilling cowives than simply punishing the perpetrator. Monetary restoration, victim-focused circles, and involvement of the wider community are proposed as alternatives to punishment. My goal with this project is to provide a nuanced and theoretically informed understanding of a topic over which much ink has already been spilled. By using analytical techniques from the legal realist toolkit, I seek to recast the case of polygamy in Pakistan as more than just a “ban it” or “allow it” issue.

Published
2023

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