پروفیسر میاں مقبول احمد کی
’’مقبول ضرب الامثال‘‘
کسی علاقے کی زبان خصوصاََ اس کے محاورے اور ضرب الامثال علاقے کی تہذیب و ثقافت،دانش،معیشت و معاشرت کی بھرپور عکاسی کرتے ہیں۔اس کے علاوہ ان میں سموئے ہوئے صدیوں کے معاشرتی رویے اور تجربے آنے والی نسلوں کیلئے مشعل راہ کا کام کرتے ہیں۔وہ حقائق و واقعات جن کے اظہار کیلئے ایک دفتر کی ضرورت ہوتی ہے۔ضرب الامثال انہیں چند لفظوں میں سمیٹ کر گویا دریا کو کوزے میں بند کر دیتے ہیں۔ان سے معاشرتی،ثقافتی،مذہبی اور سیاسی رحجانات کا بھرپور اظہار ہوتا ہے۔دنیا میں جتنی زبانیں بولی یا پڑھی جاتی ہیں۔یہ ان میں موجود ہوتے ہیں۔زبان کا حسن بھی یہی ہے کہ اس میں ضرب الامثال شامل ہوں۔دو یا دو سے زیادہ الفاظ کے مجموعے کو جو اپنے مجازی معنوں میں استعمال ہوں محاورہ کہتے ہیں۔اسی طرح ضرب المثل بھی اپنے مجازی معنوں میں استعمال ہوتی ہے۔یہ ایک طرح کے جملے ہیں جو انسانی تجربات و مشاہدات کو ظاہر کرتے ہیں، یا کسی خاص واقعے کا عکس ہوتے ہیں۔
’’مقبول ضرب الامثال‘‘ بے شمار خوبیوں کی حامل کتاب ہے۔اس کی ایک خوبی یہ ہے کہ اس میں بے شمار تہذیبیں اور ثقافتیں گلے ملتی نظر آتی ہیں اور یہ خوبی اس موضوع کی کسی دوسری کتاب میں خال خال ہی نظر آتی ہے۔میرے خیال میں پروفیسر صاحب نے وسعت نظری کا ثبوت دیتے ہوئے ایک اہم اور بے مثال تصنیف کی ہے۔بعض ضرب الامثال ایسی نظر آئیں گی جو معمولی سے فرق کے ساتھ اس دھرتی کے بہت سے علاقوں میں بولی جاتی ہیں۔
دوسری خوبی یہ ہے کہ پروفیسر صاحب نے اپنے مواد کی تشریح میں جگہ جگہ پنجابی ،اردو اور انگریزی کہاوتوں اور اقوال کو بھی اس میں شامل کرکے اسے...
Long COVID or post-COVID problems are long-term effects of COVID-19 infection that certain people who have contracted the virus can experience. This may result in having persistent symptoms for 3 months or more, such as those who had tiredness, malaise, changed smell and taste, dyspnea, and cognitive deficits three or more months after their initial COVID-19 diagnosis. However, some people may still have inferior work performance and a lower quality of life due to the long COVID episodes. From October 2021 to April 2022, cross-sectional research was conducted in Karachi, utilizing an electronic questionnaire to record sociodemographic data, current comorbidities, and previous episodes of acute COVID-19, post-COVID symptoms, and job performance among COVID survivors. The study's findings revealed that more than 35% of individuals surveyed claimed to have had COVID symptoms for six weeks or more, with approximately 20% to 30% of those reporting frequent coughing and appetite loss. Planning prevention, rehabilitation, and clinical treatment need an awareness of long-term COVID and its related components in order to maximize recovery and long-term COVID-19 outcomes. DOI: https: //doi. Org/10.59564/amrj/01.01/007
Computer vision is an important field in which techniques are developed to study and understand the properties and structure of a 3D scene present in a digital image (2D scene) and output is just some descriptive information. While an intermediate step to computer vision is field of image processing in which input and output are both images and has five main components, i.e image segmentation, detection, tracking, registration and shape analysis. Image segmentation is main concern of this research work in context of the theory of fuzzy sets [97]. The key to fuzzy sets is fuzzy membership (FMB) u obeys the constraint 0 6 u 6 1. Level set method (LSM) [66] which naturally handles splitting and merging of the evolving curve C, is a well established technique for performing image segmentation. In this thesis, to solve a partial differential equation numerically, a pseudo level set expression [38] relied on u alike LSM is used and the curve C is considered as pseudo zero level set of u. Fuzzy set is generalization to crisp set and is more generalized approach towards image domain classification based on idea of partial membership of belonging described by a FMB function. Therefore, in many real situations in images, issues like poor contrast, limited spatial resolution, overlapping intensities, noise and inhomogeneities produces fuzziness in the object boundaries and hence fuzzy set theoretic approach is an ultimate option to utilize. Utilizing such approach, we have developed five models for segmentation of variety of images. First model (see Chapter 4) is developed for segmenting images having multiobjects with variable intensities and background having maximum, minimum, average or cluttered intensities. For such achievements generalized averages are merged in kernel metric and FMB is utilized as region descriptor. Second model (see Chapter 5) developed uses approximate image in kernel metric obtained by multi scale filtering technique to ensure segmentation of images consisting of less or severe inhomogeneity. To tackle more complicated task of segmenting images having noise, texture and inhomogeneity at the same time our third model (see Chapter 6) is developed utilizing idea of measure of relative variability i.e coefficient of variation (COV), which is further extended to multiphase image segmentation model (see Chapter 7). Extraction of particular features in medical images is another very challenging task, to solve we have developed our selective segmentation model (SSM) (see Chapter 8) by utilizing idea of multi scale difference image with COV. Overall in this thesis, our main focuss is on the development of variational models in fuzzy sets framework. Evaluation of the proposed approach on a number of datasets and benchmark validate its superiority over other existing models in terms of accuracy and efficiency.