Shisham (Dalbergia sissoo) is an important tree of Pakistan and is widely grown in different areas of the country mainly for furniture, timber and fuel. Dieback is a serious threat to this tree and has caused huge damage not only in Pakistan but also in India, Nepal and Bangladesh. A nursery experiment of sexually (seedlings) and asexually (cuttings) propagated D. sissoo was conducted during 2009 and 2010. Both seedlings and cuttings were inoculated with the most commonly found fungi in the dieback affected trees i.e Fusarium solani, Botryodiplodia theobromae, Curvularia lunata and Ganoderma lucidum. Overall highest disease incidence was observed in plants inoculated with F. solani (31.39%). In seedlings F. solani caused 46.18% disease while in cuttings it was only 16.61%. No disease was recorded in controlled conditions. A significant (P<0.05) correlation of seedlings and cuttings was observed with climatic variables. Good association of seedlings (r= 0.734) and cuttings (r=0.629) was observed with maximum temperature. Disease predictive models of seedlings and cuttings were developed with climatic variables; Y = -58.3 +7.58x 1 +0.0054x 2 -1.14x 3 +2.47x 4 -1.09x 5 R 2 = 0.62 (2 years data) Where Y= Disease in cuttings, x 1 = Rainfall, x 2 = Relative humidity, x 3 = Minimum temperature, x 4 = Maximum temperature and x 5 = Wind velocity R 2 =0.48 (2 years data) Y = -134 +15x 1 +0.158 x 2 -2.32 x 3 +5.27 x 4 -3.70x 5 Where Y= Disease in seedlings, x 1 = Rainfall, x 2 = Relative humidity, x 3 = Minimum temperature, x 4 = Maximum temperature and x 5 = Wind velocity A comprehensive survey of shisham was carried out in four agro-ecological zones (Sandy deserts, Northern irrigated plains, Barani areas and Sulaiman piedmont) of Punjab province. For survey eleven districts were selected being the most productive and shisham frequenting districts from the above said zones. Trees were divided into age classes and on the basis of disease severity into healthy, partially affected and fully affected trees. Age class one (1-20 years old trees) was observed as the healthiest while age class three (above 40 years) was found to be the most affected in all zones and districts. Maximum number of healthy trees was observed in age class one of Barani areas (92.16%) Maximum number of partially affected trees was seen in Sulaiman piedmont (22.89%) and less number was in Barani areas. Maximum number of dead or fully affected trees was found in class three of Northern irrigated palins (23.60%) and only 4.68% dead trees were recorded in age class one of Barani areas. In selected districts maximum number of healthy trees was in class one of Rawalpindi district (95%) and maximum partially affected trees were in age class three in Dera Ghazi Khan (22.89%). Maximum number of dead trees (33%) was found in age class three of Toba Tek Singh. Rawalpindi was the least affected district with only 5 % dead trees in class one. Water table between 15-20 feet of depth was considered as the most suitable depth where less number of dead trees were recorded in all age classes. Significant (P<0.05) correlation was observed between age class, relative humidity, minimum temperature, maximum temperature and wind velocity. Correlation was non significant with rainfall and water table. Good association was observed between tree age and dieback disease in Healthy (r=0.626), partially affected (r=0.539) and fully affected trees (r=0.613). A disease predictive model based on two years disease survey data was developed: FA = 2.51 + 4.15 x 1 + 5.25 x 2 + 0.00866 x 3 - 0.113 x 4 - 0.0611 x 5 - 0.0115 x 6 - 0.0092 x 7 + 0.541 x8 R 2 = 0.89 Where FA= Fully affected, x 1 = Age, x 2 = Year, x 3 = Water table, x 4 = Rainfall, x 5 = Relative humidity, x 6 = Minimum temperature, x 7 = Maximum temperature, x 8 = Wind velocity
ڈاکٹر خورشید احمد فارق (مختارالدین احمد) دو شنبہ، ۱۸؍ شعبان المعظم ۱۴۲۲ھ مطابق ۵؍ نومبر ۲۰۰۱ء کی صبح کو عربی زبان و ادب کے استاد، تاریخ اسلام کے ماہر اور ممتاز مصنف ڈاکٹر خورشید احمد فارق کوئی ۸۵ سال کی عمر میں طویل علالت کے بعد دہلی میں وفات پاگئے۔ وہ ۱۹۱۶ء میں بریلی میں پیدا ہوئے۔ فارسی و عربی کی متد اول کتابیں انھوں نے گھر پر اپنے والد ماجد سے پڑھیں۔ کالج کی تعلیم انھوں نے بریلی میں حاصل کی۔ ایم۔اے اور پی۔ایچ۔ڈی انھوں نے مسلم یونیورسٹی علی گڑھ سے کیا۔ ریسرچ کے دوران وہ شعبہ عربی میں کچھ کلاسیں بھی لیتے رہے۔ ۱۹۴۳ء کے اواخر میں وہ اینگلو عربک کالج دہلی میں لکچرر، ۱۹۵۳ء کے اواخر میں دہلی یونیورسٹی میں ریڈر مقرر ہوئے۔ اکتوبر ۱۹۵۶ء میں حکومت ہند کے ایک وظیفے پر ایک سال کے لیے وہ مصر گئے۔ وہاں دارلکتب المصریہ کے مخطوطات کے مطالعے کا انہیں اچھا موقع ملا۔ ریاض الرحمن خاں صاحب شروانی اور عبدالحلیم ندوی صاحب کو بھی اسی سال یہ وظیفہ ملا تھا۔ قاہرہ میں ان تینوں کا خوب ساتھ رہا۔ فروری ۱۹۶۹ء میں وہ دہلی یونیورسٹی میں پروفیسر اور صدر شعبہ مقرر ہوئے۔ جولائی ۱۹۸۵ء میں وہ متقاعد ہو کر علی گڑھ آگئے اور سر سید نگر میں اپنے تعمیر کردہ مکان ’’بانس کلی‘‘ میں مقیم ہوکر علمی و ادبی کاموں میں مصروف ہوگئے۔ آخر عمر میں وہ اپنے بچوں کے پاس دہلی چلے گئے تھے، وہیں ان کی وفات ہوئی۔ جامعہ ملیہ اسلامیہ کے قبرستان میں ان کی تدفین عمل میں آئی۔ ڈاکٹر فارق نے اردو، انگریزی اور عربی میں عربی اور تاریخ اسلام کے موضوعات پر متعدد کتابیں لکھیں اور کثرت سے مضامین سپرد قلم کیے جو زیادہ تر رسالہ ’’برہان‘‘ دہلی میں شائع ہوئے۔ ان کی تصانیف حسب ذیل ہیں: قاضی شریح اور دیگر...
Penelitian ini bertujuan untuk mengetahui peningkatan keaktifan dan hasil belajar siswa pada mata pelajaran Pendidikan Agama Islam (PAI) setelah diterapkannya metode pembelajaran demonstration berbasis discussion process. Metode penelitian yang digunakan dalam penelitian ini adalah Penelitian Tindakan Kelas (PTK). Penelitian dilakukan di SMA EKASAKTI Padang pada kelas XI. Metode pengumpulan data yang dilakukan pada penelitian ini adalah: observasi, wawancara, dokumentasi, dan tes. Analisis data dalam penelitian ini dilakukan secara deskriptif kuantitatif dan kualitatif. Hasil dari penelitian ini adalah: (1). Kesiapan siswa dalam menerima pelajaran sebelum dilakukan tindakan 39, 06%, setelah siklus I 70, 31%, dan setelah siklus II 86, 23%. (2). Keaktifan siswa dalam proses pembelajaran sebelum dilakukan tindakan 23, 18%, setelah siklus I 67, 97%, dan setelah siklus II 85, 41%. (3). Persentase siswa yang mendapatkan nilai tuntas di atas 70 sebelum dilakukan tindakan 31, 75%, setelah siklus I 68, 25%, dan setelah siklus II 87, 75%. (4). Terdapat peningkatan yang signifikan antara masing-masing indikator pada setiap siklus, hal tersebut dapat di lihat dari peningkatan kesiapan, keaktifan, dan hasil belajar siswa pada saat sebelum dilakukan tindakan, pada siklus I dan pada siklus II. Pada siklus II semua indikator telah melampaui target persentase indikator keberhasilan yang telah ditetapkan. Sehingga siklus penelitian dapat dihentikan pada siklus II dan dapat di tarik kesimpulan bahwa metode pembelajaran demonstration berbasis discussion process berhasil serta lebih efektif dibandingkan dengan metode ceramah.
Time-aligned and labeled speech at sub-word level is required to develop spoken language technology components. Determining time boundaries of sub word units of speech and labelling those, is the speech segmentation problem. Manual human-labeling is considered to be the most accurate, which however requires significant amount of time when large amount of speech has to be dealt. The evidences which humans employ are based on knowledge of acoustic-phonetics and at very basic level works on spectrograms based techniques. Based on a hypothesis that computers can also segment speech automatically if evidence which human experts utilizes are used, leads us towards time effective automatic speech segmentation. In this thesis unsupervised automatic time-alignment of speech at sub-word level is carried out based on the pieces of information which spectrograms carry. The speech spectrogram engineered in this thesis does not possess information of vocal excitations and capture dynamics of vocal tract only. The novel feature is found suitable for segmentation problem and utilizes both forward and inverse characteristics of vocal tract (FICV). Additionally to evaluate the suitability of a feature extraction technique for speech segmentation task, a framework has also been developed. In the thesis, speech segmentation is carried out on indigenously developed Classical Arabic (CA) dataset and therefore becomes first scheme of its kind for CA which is an under resourced language in speech technology. The performance of FICV based speech segmentation scheme is compared and shown to be significantly better than standard unsupervised and supervised techniques both in terms of error-rates and alignment accuracies. Reduction of 12.29% in error rates is achieved with FICV based feature when compared with standard unsupervised technique. Carrying out supervised segmentation requires a basic sub-word level recognizer, which labels and aligns speech. In this connection a Hidden Markov Model (HMM) based speech recognizer is trained. The acoustic modeling is carried using a discriminative technique which shows better recognition accuracies of up to 4% than the non-discriminative technique. Thesis also verifies that using manually-labeled data for training acoustic models can further improve recognition accuracies by 3-4%. In this regard, thesis carries details of experimental steps which can also serve as guideline for developing an automatic speech recognizer for CA.