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Trading Frequency in KSE – 100 Index Using Pastor and Stambaugh Model Ahmed, Farhan; Ali, Mudassir; Raza, Muhammad; Sibghat, Muhammad
Indonesian Capital Market Review Vol. 11, No. 1
Publisher : UI Scholars Hub

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Abstract

The study aims to asses Pastor & Stambaugh model on Pakistan Stock Exchange (KSE-100 Index) from 2007 to 2017. Four commonly asset pricing factors are tested including market risk, size, value and liquidity premium. Except for the value premium, all factors are statistically found significant. Pertinent to mention that liquidity factor is initially found insignificant since annual returns are calculated. However, after taking most liquid sector during the period (Chemical Sector) the liquidity measure is derived through monthly returns. The result of the study is backed with Utility preference theory because it is observed that investors do prefer more liquid stocks and as a result when pricing securities liquidity factor holds an important position.
Analytical computation of arm inductor for minimizing MMC circulating current using passive method Aslam, Amna; Raza, Muhammad
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60466

Abstract

The study of circulating currents in modular multilevel converters is vital for improving their efficiency and reliability. The circulating current may arise from capacitor voltage unbalancing, modulation imperfections, load variations, and transient conditions. Such currents typically induce distortions in arm currents, exhibiting second-order harmonics that lead to power losses and negatively impact the ratings of converter components as well as the amplitudes of capacitor voltage ripples. Despite ongoing research, effective strategies to mitigate circulating currents are limited. This paper aims to systematically address this issue by selecting key design parameters specifically arm inductance and capacitor values, to suppress circulating currents. The methodology incorporates harmonic analysis and instantaneous power theory to derive expressions for arm inductance. Initial modelling includes common mode and differential mode analyses, leading to an examination of harmonic content. Analysis reveals that the selection of the arm inductor value is mainly influenced by the second-order harmonic component, whereas the capacitor value is determined by the fundamental harmonic component. By adopting this methodology, the boundary limit for arm inductor selection can be determined. This article proposes a novel expression for arm inductor selection. The proposed expression mainly depends on factors such as load, submodule capacitor voltages, submodule capacitor, and differential current. By selecting an appropriate inductor value based on converter-rated parameters, circulating current within the system can be effectively suppressed. The methodology offers a practical framework for arm inductor selection. Simulation results validation shows strong alignment with analytical results with the error margin of less than 1%, hereby the MMC parameter can be determined with better accuracy through analytic method.
Analisis Hukum Islam Terhadap Sinkretisme Pernikahan Berbasis Weton di Desa Wates Yogyakarta Aini, As Syifa Nurul; Azro, Tiara Dzahwani; Khopipah, Siti; Raza, Muhammad
Tahkim (Jurnal Peradaban dan Hukum Islam) Vol 8, No 1 (2025)
Publisher : Prodi Hukum Keluarga Islam (Ahwal Asy-Syakhsiyyah) Fakultas Syariah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/tahkim.v8i1.14622

Abstract

Pernikahan merupakan suatu perjanjian suci yang kuat dan kokoh untuk hidup bersama-sama secara sah antara seorang laki-laki dengan seorang Perempuan untuk membentuk keluarga yang kekal, santun,menyantuni,kasih sayang, aman tentram dan bahagia. Negara Indonesia merupakan negara yang kaya akan kebudayaan dan tradisi yang masih dijalankan sampai saat ini. Salah satu tradisi atau kebudayaan itu adalah perhitungan weton. Penelitian ini menggunakan pendekatan kualitatif yaitu dengan metode studi kasus dan pengumpulan data yang meliputi wawancara mendalam, jurnal ilmiah, dan artikel yang membahas perhitungan weton dalam pernikahan masyrakat Jawa. Wawancara dilakukan dengana informan kunci, seperti tokoh Masyarakat, dan warga yang memiliki pengetahuan tentang weton. Penelitian ini bertujuan untuk menganalisis secara mendalam konsep perhitungan weton dalam pernikahan menurut perspektif Hukum Islam. Berdasarkan kajian terhadap sumber hukum Islam, mempercayai weton secara mutlak, yakni dengan meyakini bahwa perhitungan tersebut menentukan baik buruknya kehidupan seseorang, termasuk dalam kategori syirik. Dalam Islam, keyakinan terhadap takdir mutlak berada di tangan Allah SWT. Oleh karena itu, menjadikan weton sebagai pedoman utama dalam pengambilan keputusan hidup tidak diperbolehkan. Marriage is a sacred and strong agreement to live togother lawfully between a man and a woman to form an eternal family respect, care, affection, peace, and happiness. Indonesia is a country rich in culture and traditions that are still practiced today. One of these traditional is the calculation of weton. This research uses a qualitative approach, specifically, a case study method, and data collection that includes in-depth interviews,scientific journals and article discussing the weton calculation in Javanese marriage. Interviews were conducted with key informants, such asa community leaders and individuals with knowledge of weton. This study aims to deeply analyze the concept of weton calculation in marriage from the perspective of Islam Law. Based on the study of Islami legal sources, believing in weton absolutely, with the conviction that this calculation determines the good or bad a person’s life , is considered a form of shirk. In Islam, the belief in absolute fate is solely in the hands of Allah SWT. Therefore, using weton as the primary guide for making life decisions is not allowed.
Strategic Human Resource Management in Higher Education: An AMO Framework Analysis of Lahore University of Management Sciences Raza, Muhammad; Nasrulloh, Ahmad; Meghwar, Qeemat Rai
Jurnal Akuntabilitas Manajemen Pendidikan Vol. 13 No. 2 (2025): September
Publisher : Faculty of Educational Sciences, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jamp.v13i2.89047

Abstract

This study examine the strategic human resource management (HRM) practices at Lahore university of management sciences (LUMS) Pakistan, focusing on their alignment with institutional goals and their impact on faculty development and students success. Using a qualitative research approach, the study explores four key HRM pillars: recruitment, training and development, performance evaluation and organizational culture. LUMS implements a merit-based and inclusive recruitment model, attracting highly qualified faculty to promote academic excellence. Training initiatives like the peer-driven facilitators training programs and learning institute reflect a strong commitment to pedagogical development. Performances management is structures through SAP success factors, facilitating goals alignment, regular appraisal and feedback. LUMS foster a people-centered organizational culture based on diversity, trust, and growth. Grounded in the Ability-Motivation-Opportunity (AMO) theory and strategic HRM framework, the findings underscore how LUMS's integrated HRM model enhances academic staff performance and plays a vital role in promoting educational innovation, quality and improved students outcomes.
LSKD: Lightweight Self-Knowledge Distillation Framework for Fast and Robust Crowd Counting Raza, Muhammad; Ling, Miaogen; Ur Rahman, Atta; Pallewatta, Pandula; Hersi, Aboubakar Abdinur; Beruwalage, Shehan Maxwell; Kannangara, Deshan Sachintha
Scientific Journal of Engineering Research Vol. 2 No. 2 (2026): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v2i2.2026.436

Abstract

Crowd counting plays an important role in the surveillance of the safety of the people, traffic, and intelligent surveillance systems. However, the exact density estimations remain hard to achieve in highly congested scenes due to the tough occlusion, large-scale variance, and complicated background. Although the recent deep-learning methods have high performance, several of them do not need computationally efficient underlying backbone networks, and rather, they employ an external teacher-student distillation architecture, which can limit their use in resource-constrained applications. To avoid this problem, we introduce LSKD, a lightweight self-knowledge distillation network that is density map regression-specific. Unlike other conventional teacher-dependent processes, LSKD can also independently carry out internal multi-level feature alignment within a single small network that is not in need of an external teacher model. The structure integrates a Feature Matching Block (FMB) and a Context Fusion (CoFuse) block to enhance the hierarchical match of features and global awareness of context. The large experiments demonstrate that LSKD obtain competitive performance using the number of parameters as 2.65 million and GFLOPs as 10.23. Particularly, it has 63.17 MAE on ShanghaiTech Part A, 8.94 on ShanghaiTech Part B, 143.7 on UCF-QNRF, and 223.88 on UCF-CC-50, which is a good ratio between the accuracy and the efficiency of the calculations. Such results indicate that LSKD has an implementable and efficient solution to the real-time counting of crowds at the edge devices.
Parameter-Efficient Fine-Tuning for Sonar Shipwreck Segmentation: A Seed Averaged Study with SegFormer and LoRA Beruwalage, Shehan Maxwell; Yin, Chunyong; Raza, Muhammad; Kannangara, Deshan Sachintha; Hendavitharana, Sachini Amani
Scientific Journal of Engineering Research Vol. 2 No. 2 (2026): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v2i2.2026.454

Abstract

Accurate segmentation of shipwreck targets in sonar imagery is important for underwater archaeology, marine monitoring, and search operations, but the task remains difficult because labeled sonar masks are scarce and full adaptation of transformer models can be computationally expensive. This study evaluates whether parameter-efficient fine-tuning can provide a practical alternative for binary sonar shipwreck segmentation. Using SegFormer-B0 initialized from a pretrained checkpoint, three adaptation strategies were compared under a consistent protocol: full fine-tuning of all model parameters (FullFT), training only the segmentation head (Head-only), and LoRA-based adaptation of selected linear layers together with head training (LoRA-A+Head). Models were selected by the best validation epoch and evaluated on a held-out test set. Across three random seeds, FullFT achieved the best performance, with a Dice score of 0.614 ± 0.008 and IoU of 0.487 ± 0.007. LoRA-A+Head achieved a Dice score of 0.546 ± 0.010 and IoU of 0.401 ± 0.008 while updating only 1.57% of the parameters, whereas Head-only reached 0.494 ± 0.010 Dice and 0.354 ± 0.008 IoU. These results show a clear accuracy efficiency trade off, full fine-tuning gives the highest accuracy, whereas LoRA-A+Head offers a practical option when reducing the number of updated parameters is important. The findings support the use of parameter-efficient adaptation for sonar segmentation in compute-limited settings.
NRCC-LC: Noise-Robust Crowd Counting with Dynamic Label Correction under Noisy Supervision Hersi, Abubakar Abdinur; Ling, Miaogen; Raza, Muhammad; Hassan, Abdirahman Mohamed; Hussien, Idris Aweis
Scientific Journal of Engineering Research Vol. 2 No. 3 (2026): September (in Process)
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v2i3.2026.494

Abstract

Crowd counting remains a challenge within computer vision due to many factors that affect the performance of available methods such as occlusion, scale variability, and perspective distortion. Additionally, many labels associated with crowd counting systems have high levels of noise caused by various real-world conditions. Although crowd counting methodologies have improved accuracy over recent years, the majority of crowd counting models still rely on clean real-time supervision and lack systems that can correct for dynamically corrupted labels, resulting in low robustness for crowd counting models when deployed in real-world applications. In this work we present a Noise-Robust Crowd Counting with Label Correction (NRCC-LC) framework to obtain reliable density estimates from noisy supervision. To accomplish this, our approach uses a combined CNN-Transformer architecture to capture both locally- and globally-relevant visual information (i.e., image content and context), along with a Noise-Robust Module (NRM) and a Dynamic Label Correction (DLC) mechanism. Our principle experimental results evaluated across four benchmark datasets: ShanghaiTech Part A, ShanghaiTech Part B, NWPU-Crowd, and JHU-Crowd++, indicate that the NRCC-LC exhibits competitive performance with respect to existing state-of-the-art crowd-counting methods; most notably, producing per-image MAEs of 97.8 and 392.3 on NWPU-Crowd. These experimental results additionally have real-world implications for improving public safety and urban planning; thus, through our novel method of noise-aware feature learning combined with iterative label correction, we can establish the potential of automated monitoring systems in complex, real-world environments to be significantly more reliable.