Human action localization and recognition in videos is one of the most studied and active research area in computer vision. In this thesis we elaborate two main questions; First when and where is the action performed in the video and what type of action is performed. When and where localize the action spatially in a time series visual data, while what type of action determine the action category/class. The output of action localization is a sub-volume consists of the action of interest. Action localization is more challenging as compared to the action classi cation, because it is the process of extracting a speci c part of the spatio-temporal volume in a visual data. We address the problem of automatic extraction of foreground objects in videos and then determine the category of action performed in the localized region. Action localization and recognition deal with understanding when, where and what happens in a video sequence. In the last decade, some of the proposed methods addressed the problem of simultaneous recognition and localization of actions. Action recognition addresses the questionWhat type of action is performed in the video? , while action localization aims to answer the questionWhere in the video? . These methods are termedaction detectionoraction localization and recognition . The human action recognition and localization is greatly motivated by the wide range of applications in variouselds of computer vision like human perceptual segmentation, tracking human in a video sequence, recovering the body structure, medical diagnosis, monitoring the human activities in security-sensitive areas like airports, buildings (universities, hospitals, schools), border crossings and elderly daily activity recognition (related to elderly health issues). It is one of the hardest problems due to enormous variations in visual data, appearance of actors, motion patterns, changes in camera viewpoints, illumination variations, moving and cluttered backgrounds, occlusions of actors, intra-and inter-class variations, noise, moving cameras and the availability of extensive amount of visual data. Local features based action recognition methods have been extensively studied in the last two decades. These systems have numerous limitations and far enough from the real time scenario. Every phase of the system has its own importance for the next phase, such as the success and accuracy of local feature based methods depend on the accurate encoding of visual data i.e. feature extraction method, dimensionality reduction of the extracted features and compact representation, localizing the action and training a learning model (classi er) for the classi cation of action sequences (Main parts of the system should be: (1) Feature extraction, (2) Feature representation, (3) localization of the region of interest, and (4) classi cation of the action video). First of all we study, investigate, evaluate and compare the well known state-of-the-art and prominent approaches proposed for action recognition and localization. The methods proposed for action localization are too complex and computationally expensive. We have proposed a novel saliency map computation based on local and global features toll the gap between the two types of features and hence provide promising results very e ciently for salient object detection. Then the motion features are fused intelligently with the detected salient object to extract the moving object in each frame of the sequence. The object proposal algorithms normally use computationally expensive segmentation methodologies to extract di erent non-overlapping objects/regions in a frame. Our proposed methods exploit very limited spatio-temporal neighborhood to extract a compact action region based on the compensated motion information. Finally, classi er is trained on the local features to recognize/label the action sequence. We have evaluated two types of learning models, extreme learning machine (ELM) and deep neural networks (DNNs). ELM is fast, while the computationally intensive classi ers such as Deep Neural Networks (DNNs) produce comparatively better action recognition accuracy. The experimental evaluation reveals that our local features based human action recognition and localization system improves the existing systems in many aspects such as computational complexity and performance. Finally it is concluded that the proposed algorithms obtain better or very similar action recognition and localization performance/accuracy as compared to the state-of-the-art approaches on realistic, unconstrained and challenging human action recognition and localization datasets such as KTH, MSR-II, JHMDB21 and UCF Sports. Besides, to evaluate the e ectiveness of localization of proposed algorithms a number of segmentation data sets have been used such as MOViCs, I2R, SegTrack v 1 & 2, ObMiC and Wall owers. Though the approaches proposed in the thesis obtain promising and impressive results as compared to the prominent state-of-the-art methods, further research and investigations are required to get enhanced or comparable results on more challenging realistic videos encountered in practical life. The future directions are discussed in conclusions and future work section of the thesis.
مولانا عبدالرزاق ملیح آبادی افسوس ہے کہ گذشتہ مہینہ ہماری جماعت کے ممتاز رکن اور ندوہ کے نامور فرزند مولانا عبدالرزاق صاحب ملیح آبادی نے وفات پائی، انھوں نے متوسطات تک ندوہ میں تعلیم پائی، اور تکمیل جامعہ ازہر مصر میں کی تھی، علامہ رشید رضا کے خاص شاگردوں میں تھے، ان کا ذوق ابتدا سے سیاسی بلکہ انقلابی تھا، چنانچہ مصر کے قیام کے زمانہ میں قسطنطنیہ جاکر انور پاشا سے ملے، ان کی ملاقات نے سیاست اور آزادی کا نشہ اور تیز کردیا، پہلی جنگ عظیم کے بعد ہندوستان واپس آئے، اور کچھ دنوں تک مولانا عبدالباری فرنگی محلی رحمتہ اﷲ علیہ کے ساتھ رہے، جن کی ذات اس زمانہ میں مسلمانوں کی سیاست کا مرکز تھی، مگر مولانا عبدالرزاق کے خیالات اس زمانہ کی سیاست سے بہت آگے تھے، اس لئے زیادہ دنوں تک یہ ساتھ نہ رہ سکا۔ حسن اتفاق سے اسی زمانہ میں مولانا ابوالکلام کو ایک علمی و سیاسی رفیق کار کی تلاش تھی، اس کے لئے ان کی نگاہ انتخاب مولانا عبدالرزاق پر پڑی اور ان کو انھوں نے کلکتہ بلالیا، اس وقت سے وہ مولانا کے دامن سے ایسے وابستہ ہوئے کہ مرتے دم تک ان کا ساتھ نہ چھوڑا، وہ برسوں مولانا ابوالکلام کے سیاسی اور علمی کاموں میں ان کے دست راست رہے، چنانچہ دوسرے دور کے البلاغ اور ۱ مشہور عربی اخبار الجامعہ کے اڈیٹر مولانا ابوالکلام برائے نام تھے، ان کا پورا کام مولانا عبدالرزاق انجام دیتے رہے، الجامعہ ہندوستان میں عربی کا پہلا معیاری اخبار تھا، جس کی شہرت عرب ملکوں تک تھی، ہندوستان کے مسلمانوں میں عربی ادب و انشاء کا صحیح ذوق پیدا کرنے اور عرب ملکوں سے ان کا رابطہ استوار کرنے میں اس اخبار کا بڑا حصہ ہے، ان علمی و صحافتی مشاغل کے ساتھ سیاسی تحریکوں میں بھی علمی...
Islam is a way of life and it does not allow betray of any kind to anyone especially in trade and business. Islam does not allow to buy or sell any type of commodity by any means in which there is a chance of betray, and along with it Islam also does not allow jugglery, betting, selling of item before purchasing and selling a commodity without having a possession. In Islamic Jurisprudence these conditional trade is known asGhararIt is then divided in two types of which the first type is prohibited by all school of thoughts and the other type is allowed by some school of thoughts
Allograft rejection remains a major hurdle in successful transplantation despite improved immunosuppressive drugs and clinical care. The molecular changes in the renal allograft that lead to graft rejection need to be investigated. In the present work, polymorphisms in chemokine receptors and urinary chemokine levels were investigated for association with rejection. This study includes; (a) gene polymorphisms of chemokine receptors of CCR2 and CCR5 (CCR2V64I and CCR5-59029G>A and CCR5Δ32), (b) urinary levels of interferon induced protein-10 (IP-10), (c) urinary levels of monokine induced by interferon-gamma (MIG) and (d) urinary levels of monocyte chemotactic protein-1 (MCP-1). This is the first study on chemokine receptor polymorphisms and the urinary chemokine levels (IP-10, MIG and MCP-1) in cohorts of Pakistani renal transplant patients. The project was approved by the Institutional Ethical Review Committee and informed consent was taken from all the participants. Briefly, the gene polymorphisms CCR2V64I, CCR5-59029G>A and CCR5Δ32 were investigated in 606 renal transplant patients and their donors by amplified fragments length polymorphisms (RFLP). The results showed that the G/G genotype of CCR2V64I was associated with a high frequency of allograft rejection (P=0.009). The Kaplan-Meier curve also indicated a significant reduction in the overall time to rejection-free allograft survival for patients with the G/G genotype of CCR2V64I as compared to the A/A or G/A genotype (59.2±1.4 vs. 68±2.6 weeks, P=0.008) showing that individuals with the A allele, either in the homozygous or heterozygous state, have a greater chance to accept the graft. ix Human IP-10 is classified as the CXC chemokine sub-family. A total of 206 urine samples of (a) rejection (n=96), (b) non-rejection (n=22) and (c) controls (n=88) were quantified for IP-10 by enzyme-linked immunosorbent assay (ELISA) for association with rejection. The results showed statistically significant differences in the urinary IP-10 levels between the rejection vs. non-rejection groups (P=0.004). The Receiver operating characteristic curve (ROC) of IP-10 showed area under the curve (AUC) of 0.70±0.06 with 72% sensitivity and 64% specificity, at a cut-off value of 27pg/ml. Human MIG also belongs to the CXC chemokine sub-family. A total of 266 urine samples from (a) rejection (n=108), (b) non-rejection (n=70), (c) stable grafts (n=42) and (d) control groups (n=46) were quantified for MIG and analyzed for association with rejection. The results indicated that although urinary MIG levels were higher in patients with rejection the association was not statistically significant (P>0.05). The ROC curve also showed AUC of 0.54±0.04 with low sensitivity (46%) and specificity (55%) at cut-off value of 6pg/ml. Human MCP-1 belongs to the CC chemokine sub-family. A total of 409 urine samples of (a) rejection (n=165), (b) non-rejection (n=93), (c) stable grafts (n=42) and (d) controls (n=109) were quantified for urinary level of MCP-1 by ELISA. The results showed that MCP-1 levels were different between the rejection and other groups (P<0.05). The ROC curve illustrated the area under curve of 0.83±0.04 with a sensitivity and specificity of 84% and 74% respectively, at a cut-off value of 214pg/ml. In conclusion, this work shows the usefulness of chemokine receptor CCR2V64I polymorphism as a marker for the increased possibility of an x immune response against an allograft. Urinary levels of MCP-1, the ligand of CCR2, and IP-10 were increased and show good correlation with rejection. While urinary MIG did not show any association with rejection. These findings may help in developing new therapeutic strategies in renal transplantation based on patient genetic makeup. Additionally, non-invasive screening tests based on urinary levels of IP-10 and MCP-1 would help in the assessment of the immune status of the graft