مولانا طفیل احمد منگلوری
سب سے آخر میں رنج واندوہ کے گہرے جذبات کے ساتھ ہمیں اپنے مخدوم اوربزرگ مولانا سید طفیل احمدصاحب منگلوری کے حادثۂ وفات کاماتم کرنا ہے جو ۳۰؍ مارچ کو پیش آیا، مولانا کی عمر اس وقت تقریباً اسّی ۸۰ برس کی تھی۔ سرسید کے زمانہ میں مدرسۃ العلوم علی گڑھ میں تعلیم پائی تھی۔عربی کی استعداد معمولی تھی لیکن انگریزی اوراردو دونوں زبانوں میں بے تکلف تحریر وتقریر کی قدرت رکھتے تھے ۔مطالعہ نہایت وسیع تھا۔قومی اورسیاسی مسائل میں بڑی بصیرت رکھتے تھے ۔چھوٹے بڑے سینکڑوں مقالات اوررسائل کے علاوہ مرحوم کی ایک عظیم الشان تصنیفی یادگار ’’مسلمانوں کاروشن مستقبل ‘‘ہے۔انگریزی تعلیم یافتہ طبقہ سے تعلق رکھنے کے باوصف صورت وسیرت اوروضع قطع کے اعتبارسے بالکل ٹھیٹ مُلّا معلوم ہوتے تھے۔مزاج میں انتہا درجہ سادگی اورانکساری تھی۔ ساری عمر مسلمانوں کے لیے نہایت ٹھوس اور تعمیری کام کرتے رہے لیکن خودنمائی اور شہرت طلبی کاکہیں آس پاس بھی گزر نہ ہوا تھا۔اخلاق وعادات کے لحاظ سے اسلامی شرافت ونیک نفسی کے پیکر تھے۔ حقیقت یہ ہے کہ اس اخلاق کے بزرگ ہماری نظروں سے بہت کم گزرے ہیں۔ایک زمانہ میں جوازِ سود کے قائل تھے لیکن بعدمیں اس سے رجوع کرکے علمائے حق کے ہی ساتھی ہوگئے تھے ۔ایک عرصہ سے چند درچند امراض کاشکار تھے لیکن اپنے فرائض وواجباتِ زندگی کو ادا کرنے میں آخردم تک جوانوں سے بھی زیادہ باہمت اورمستعدرہے۔ دعاہے کہ اﷲ تعالیٰ ان کی قبر کو عنبریں کرے اور نعمائے جنت سے بہرہ اندوز فرمائے۔ آمین۔ [مئی ۱۹۴۶ء]
The aim of this research is to determine the influence of underwriter reputation, financial leverage, profitability and company size on the underpricing of IPO shares on the Indonesian Stock Exchange (BEI) for the period 2022. This research is quantitative research that uses secondary data. The population in this study was 59 companies that will IPO in 2022. The total sample was 46 companies using purposive sampling techniques. Data analysis uses time series data regression with the help of SPSS 25. The research results show that the underwriter's reputation influences share underpricing with a significant value of 0.046 < 0.05. Financial leverage influences stock underpricing with a significant value of 0.049 <0.05. Profitability influences stock underpricing with a significant value of 0.003 < 0.05. Company size has no effect on stock underpricing with a significant value of 0.913 > 0.05.
Soft Computing Based MIMO Self-tuning Adaptive Control Paradigms for Multiple HVDC Links and FACTS This research work presents an intelligent nonlinear supplementary damping controller for line-commutated converters (LCC) based high voltage direct current (HVDC) transmission system and flexible AC transmission systems (FACTS) Controllers to enhance the damping of the power system oscillations. Especially, the damping of electromechanical inter-area low-frequency oscillations (LFOs) is one of the major barriers to improve the secure and stable operation of an inter-interconnected power system. The fast and flexible power modulation aspect of LCC-HVDC transmission system is exploited through supplementary damping control to suppress LFOs with a support of two FACTS controllers i.e. thyristor controlled series capacitor (TCSC) and static synchronous compensator (STATCOM) in a large-scale AC/DC power system. An adaptive NeuroFuzzy feedback linearization control (ANFFBLC) approach based on feedback linearization control (FBLC) is proposed to design an adaptive damping control structure. First, the nonlinear dynamics of AC/DC power system are online identified on the basis of measured signals of the power system including speed deviations of generators, power flow through a transmission line, and bus voltage. Intelligent adaptive NeuroFuzzy network is used for online approximation of nonlinear dynamic model of the power system. The measured signals of the power system are input to the NeuroFuzzy identification network and output is the nonlinear dynamic model of the power system. Six different conjugate gradient-based iterative algorithms are employed for online adjustment of the NeuroFuzzy network parameters to correctly approximate the nonlinear power system model by minimizing the identification error between actual power system model and estimated model. The ANFFBLC scheme transforms the nonlinear model of the power system into linear one and derives an appropriate damping control law using a well established linear control techniques. The coefficient vector in the FBLC design is self-tuned on the basis of the filter tracking error that is the error between desired and actual power system model. The normalized least mean squares (nLMS) algorithm based FBLC parameters tuning scheme ensures the effective performance of ANFFBLC over a wide range of operating conditions of the power system. Next, ANFFBLC derives an appropriate damping control signals that modulate the HVDC power flow, TCSC impedance, and STATCOM voltage after the disturbance has occurred. The research work presents the ANFFBLC schemes for both multi-inputmulti-output (MIMO) and single-input-single-output (SISO) power systems performing under different operating conditions and equipped with combinations of HVDC systems and FACTS controllers. The main features of the proposed control approach are 1) it entails minimal apriori knowledge of the power system to achieve the control objectives. 2) The adaptive nature of the proposed nonlinear control design ensures improved damping performance at different operating conditions. 3) The real-time optimization of adaptive parameters ensures an accurate approximation of nonlinear dynamics and appropriate damping law to provide improved damping of LFOs. The damping performance evaluation of the proposed controllers is based on the observation of the overshoot and settling time of LFOs and speed deviation error based performance indexes. A performance comparison of ANFFBLC schemes with a conventional proportional-integral-derivative (PID) controller and non-conventional direct intelligent NeuroFuzzy controller and adaptive PID is also provided to highlight its merits. The supplementary damping control approaches are tested on the two different test systems. One is two-area multi-machines test power system with one HVDC link or one FACTS controller installed in parallel with AC tie and another is multiarea multi-machine test power system with multiple HVDC systems and FACTS controllers. Disturbance stability studies are performed with different operating scenarios to demonstrate and compare the performances of the proposed control and benchmark control methodologies including conventional and non-conventional controllers. The study results show the effective and superior performance of the ANFFBLC strategy for improved transient and steady-state stability of the AC/DC power system.