An Experimental Study on the Meaning of Urdu Universal Quantifiers

( Saima Hassan ) 서울대학교 인지과학연구소 2010 Journal of Cognitive Science Vol.11 No.2

The virtually universal opinion of semanticists is that the collective or distributive construal of English quantified statements results from the collective and distributive properties of different quantifiers with necessarily collective or distributive predicate types. The evidence adduced to support such analyses is based almost exclusively on previous research on English quantifiers (Vendler, 1967; Hogg, 1977; Dowty, 1987; Szabolcsi, 1997; Beghelli and Stowell, 1997; Kearns, 2000; Tunstall, 1998 among many others). It is generally assumed that adults are essentially error-free in their comprehension of sentences containing universal quantifiers, although they are not as sensitive to semantic anomalies as they are to syntactic violations or do not consider them as serious (Ni et al., 1998; Pearlmutter et al., 1999; Braze et al., 2002; Angrilli et al., 2002; Hagoort, 2003; Sorace and Keller, 2005). The aim of this paper is to subject these beliefs to cross-linguistic scrutiny. I begin by reviewing the evidence that the English universal quantifier all has a bias towards a collective interpretation, while each/every is biased towards a distributive interpretation. Pursuing this idea for the analysis of Urdu, I present a simple questionnaire study carried out on native speakers of Urdu. The questionnaire was designed to explore whether native speakers of Urdu are sensitive to the collective/distributive properties of Urdu universal quantifiers, and whether they are differentially sensitive to semantic/syntactic anomalies in quantified statements. I discuss the implications of this for the cross-linguistic analysis of universal quantifiers.

A novel nonsense mutation in NPR2 gene causing Acromesomelic dysplasia, type Maroteaux in a consanguineous family in Southern Punjab (Pakistan)

Saima Mustafa,Zafrin Akhtar,Muhammad Latif,Mubashir Hassan,Muhammad Faisal,Furhan Iqbal 한국유전학회 2020 Genes & Genomics Vol.42 No.8

Background Acromesomelic dysplasia, type Maroteaux (AMDM) is a rare skeletal dysplasia following autosomal recessive mode of inheritance and characterized by abnormal growth plates, short and abnormal bones in the extremities and spine. Objective Present study was designed to report the molecular basis of AMDM in enrolled consanguineous family from Pakistan. Methods A consanguineous family from Vehari District in Pakistan having multiple siblings suffering from AMDM was enrolled in present study. Whole exome sequencing (WES) approach was adopted to identify causative agent of AMDM. Human full length NPR2 gene and sequence with nonsense mutation was amplified by using Myc-tagged pXN vector and transformed in E. coli DH5α cells to confirm mutation. SDS-PAGE and Western blotting were done to confirm the production of truncated protein. Computational three dimensional structure generation through homology modeling approach was done to compare protein structure between patients and controls. Results WES reveled a nonsense mutation (c.613 C>T, p.R205X) in exon 1 of NPR2 gene leading to premature termination codon in mRNA of NPR2 gene resulting in a truncated protein with 204 amino acid residues that was confirmed by SDSPAGE and Western blotting. Sanger sequencing confirmed that mutation in all subjects and mutation followed Mendalian pattern of inheritance. Multiple sequence alignment by ClustalW revealed that mutated domain of NPR2 is conserved region. Proetin structure comparison revealed a significant structural part of NPR2 was missing in truncated protein as compared to control. Conclusion We are reporting that a novel nonsense mutation (c.613 C>T, p.R205X) in exon 1 of NPR2 gene is causing AMDM in a consanguineous Pakistani family.

Adsorption Kinetics of Acid Red on Activated Carbon Web Prepared from Acrylic Fibrous Waste

M. Salman Naeem,Saima Javed,Vijay Baheti,Jakub Wiener,M. Usman Javed,Syed Zameer Ul Hassan,Adnan Mazari,Jawad Naeem 한국섬유공학회 2018 Fibers and polymers Vol.19 No.1

In this work, activated carbon (AC) web was prepared using physical activation under the layer of charcoal in high temperature furnace. The carbonization of acrylic fibrous waste was performed at different temperatures (800 ℃, 1000 ℃, and 1200 ℃) with heating rate of 300 oC/h and at different holding time. At 1200 ℃, the heating rate of 300 ℃/h and no holding time provided better results of surface area as compared to carbonization at 800 ℃ and 1000 ℃. The activated carbonweb (AC) prepared at 1200 oC was used for removal of Acid Red 27 dye from aqueous media by varying different parameters like initial concentration of dye, stirring speed, adsorbent dosage, and pH. The results were evaluated using non-linear forms of Langmuir and Freundlich isotherms. The Freundlich isotherm was found to describe the results more effectively because of non-homogenous surface of activated carbon web. Further, the kinetics of adsorption was examined using linear and nonlinearforms of pseudo 1st order and pseudo 2nd order.

SkelGAN: A Font Image Skeletonization Method

( Debbie Honghee Ko ),( Ammar Ul Hassan ),( Saima Majeed ),( Jaeyoung Choi ) 한국정보처리학회 2021 Journal of information processing systems Vol.17 No.1

In this research, we study the problem of font image skeletonization using an end-to-end deep adversarial network, in contrast with the state-of-the-art methods that use mathematical algorithms. Several studies have been concerned with skeletonization, but a few have utilized deep learning. Further, no study has considered generative models based on deep neural networks for font character skeletonization, which are more delicate than natural objects. In this work, we take a step closer to producing realistic synthesized skeletons of font characters. We consider using an end-to-end deep adversarial network, SkelGAN, for font-image skeletonization, in contrast with the state-of-the-art methods that use mathematical algorithms. The proposed skeleton generator is proved superior to all well-known mathematical skeletonization methods in terms of character structure, including delicate strokes, serifs, and even special styles. Experimental results also demonstrate the dominance of our method against the state-of-the-art supervised image-to-image translation method in font character skeletonization task.

Enhancing feature selection with GMSMFO: A global optimization algorithm for machine learning with application to intrusion detection

Hussein Nazar K,Qaraad Mohammed,Amjad Souad,Farag M.A.,Hassan Saima,Mirjalili Seyedali,Elhosseini Mostafa A 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4

The paper addresses the limitations of the Moth-Flame Optimization (MFO) algorithm, a meta-heuristic used to solve optimization problems. The MFO algorithm, which employs moths' transverse orientation navigation technique, has been used to generate solutions for such problems. However, the performance of MFO is dependent on the flame production and spiral search components, and the search mechanism could still be improved concerning the diversity of flames and the moths' ability to find solutions. The authors propose a revised version called GMSMFO, which uses a Novel Gaussian mutation mechanism and shrink MFO to enhance population diversity and balance exploration and exploitation capabilities. The study evaluates the performance of GMSMFO using the CEC 2017 benchmark and 20 datasets, including a high-dimensional intrusion detection system dataset. The proposed algorithm is compared to other advanced metaheuristics, and its performance is evaluated using statistical tests such as Friedman and Wilcoxon rank-sum. The study shows that GMSMFO is highly competitive and frequently superior to other algorithms. It can identify the ideal feature subset, improving classification accuracy and reducing the number of features used. The main contribution of this research paper includes the improvement of the exploration/exploitation balance and the expansion of the local search. The ranging controller and Gaussian mutation enhance navigation and diversity. The research paper compares GMSMFO with traditional and advanced metaheuristic algorithms on 29 benchmarks and its application to binary feature selection on 20 benchmarks, including intrusion detection systems. The statistical tests (Wilcoxon rank-sum and Friedman) evaluate the performance of GMSMFO compared to other algorithms. The algorithm source code is available at https://github.com/MohammedQaraad/GMSMFO-algorithm.