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پہلی بات

    سیالکوٹ ایک تاریخی اور ادبی خطہ رہا ہے۔ اس کی تاریخ پانچ ہزار سال پر محیط ہے۔ سیالکوٹ تاریخی ، جغرافیائی ، ثقافتی،سماجی،تہذیبی،علمی اور ادبی لہاظ سے دوسرے عالمی ادبی شہروں سے کم نہیں۔سیالکوٹ کو اقبال و فیض کے مولد ہونے کا بھی لازوال فخر حاصل ہے۔ بقول گوپی چند نارنگ :
    ’’ بیسویں صدی کے اردو ادب کو سیالکوٹ کھا گیا نصف اوّل اقبال اور نصف دوم فیض‘‘۔
    سیالکوٹ کی مٹی بڑی زرخیز اور مردم خیز ہے ۔ سر زمینِ سیالکوٹ نے علم و ادب اور فنونِ لطیفہ کے میدانوں میں گراں قدر خدمات سر انجام دی ہیں۔ داغ دہلوی اور اقبال کے کئی شاگرد سیالکوٹ کے رہنے والے تھے۔ اقبال و فیض کے علاوہ ارض اقبال میں متعدد مشاہیر پیدا ہوئے جن کے شعری و نثری سرمائے میں آ فاقی موضوعات ، اصناف اور اسالیب موجود ہیں۔ اس طرح خطہء سیالکوٹ کا تخلیقی ادب عالمی ادب کے ہم پلہ ہے۔ راقم الحروف نے اپنی تخلیق بعنوان’’ ارضِ اقبال ۔ آ فاقیت کے آ ئینے میں‘‘ سیالکوٹ سے منسلک مختلف شعرا و ادبا کی ادبی خدمات کا تحقیقی و تنقیدی جائزہ لیا ہے۔ یہ تحقیقی وتنقیدی جائزہ ادبی خدمات کے علاوہ ادبی رجحانات، ادبی اصناف، اسالیب اور اقبال شناسی کے حوالے سے بھی ہے۔
     یہ تصنیف پندرہ مقالات پر مشتمل ہے ۔ جس میں حوالہ جات ، حواشی اور تعلیقات کا خاص خیال رکھا گیا ہے۔ یہ مقالات ہائر ایجوکیشن کمیشن اسلام آباد ،پاکستان کے منظور شدہ ریسرچ جرنلز میں شائع ہو چکے ہیں۔
 ڈاکٹر نصیر احمد اسد
سیالکوٹ، پنجاب، پاکستان

الحكمة في شعر محمود سامي البارودي

Muḥmood Sami al Barodi is a famous poet who was named the Resurrector of poetry in the early times when many poets of the old era were the cause of the decline in poetry. His poems had been studied from many aspects and by many scholars but no one ever spoke about al Barodi’s writings about wisdom. This article is focusing on the verses and poems that focus on the meaning of wisdom and everything that relate to it. He talked about the importance of wisdom in the poems as he encouraged the other poets to give attention to this meaning. Some published books and articles helped me write this article but I haven’t found any of them that gave this point enough significance though his poetry is full of verses about wisdom and so I chose to write about it.

Laser Cutting Optimization of Non-Metallic Materials Overall Quality

As the global stock of natural resources depletes the need of electricity efficient processes emerges. Laser cutting, an advance non-contact processing technique, outweighs the old methods such as hotwire and milling due to the requirement of retightening and replacement of cutting tools with time. Orthogonal array and Factorial design are selected as a design of experiment for modelling and optimization of Laser cutting process. The range adjustment of laser machine requires knowledge of experimental design, laser cutting process and material properties, otherwise missing values generate due to unsuccessful cutting. For this reason, many universities are unable to utilize these machines effectively. It is essential to formulate a technique which allows modelling the data with some missing values, consequently, it enhance the utilization of laser machines for research and other purposes. Initially, the qualities of output characteristic were modelled by Statistical and Neural network without missing values and then by supervised and novel Semi-supervised learning algorithms with missing values. The Statistical modelling results using one and two way analysis of variance with replication were better than other data mining techniques like linear and nonlinear regression, however, it is difficult to use these methods with missing values. Therefore, supervised neural network modelling is carried out and the effects of its parametric change are observed along the datasets size to model the orthogonal array. The neural network modelling results in edge quality and kerf width signal to noise ratio, it is acceptable, the edge quality indicates that modelling improves by pre-normalization, further improvement was made by increasing training data size to factorial design. It is observed that for the artificial neural network, supervised learning is not sufficient associated to orthogonal array, only due to edge quality mean modelling, average error were higher than the acceptable limit. The average error with factorial design was under 10%. The vast modelling experience of supervised learning engenders the development of novel Semi-Supervised learning algorithm. Consequently, the average error was reduced by utilizing the systematic randomize techniques to initialize the neural network weights and increase the number of initialization by using orthogonal array design of experiment, with up to 22% missing values. This algorithm reduces modelling time and cost thus reduces electricity consumption. The average error in Perspex sheet did not exceed 8.0% and 11.5% for edge quality and kerf width respectively. The overall quality was calculated by aggregation technique of data mining and a more generous and better aggregation is carried out by the novel combination of Fuzzy logic which provides overall quality for the customer while saving cost, time and Electricity.
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