32 research outputs found
ابراہیم عدیل بطور نعت گو شاعر: IBRAHIM ADEEL AS A POET OF NAAT
No full text(with the special reference in the light of “Harf-E-Sana”)Genre of Naat is related to Seerat Muhammad (PBUH). Naat has been written in Arabic, Persian, Urdu, Punjabi and other languages. Valuable body of Naat is present in Urdu. Molana Hali, Ameer Minaee ,Mohsin Kakorwi, Allama Iqbal, Hafeez Jilahndri, Zafar Ali Khan, Ahmad Raza Brevalvi, Mahr-Ul-Qadri, Abdul Aziz Khalid, Hafeez Taib, Hafiz Ludhyanvee, Muzaffar Warsi, Riaz Majeed are prominent name in this field.Ibrahim Adeel has written Naat in ghazal pattern. He describes the greatness, Superiority, morality, courtesy and glory of the every aspect of the holy life Muhammad (PBUH). He is true lover of Sahaba-E-Karam. He has strong emotional attachment to Madina. Zikray Rasool and Fikray Rasool both are found in his anthology. Harf-E-Sana is imbued with qualities and beauties of poetry: - Vision, imaginary, emotion, music harmony, refinement are present in it. Moreover, figure based on resemblance that is similes, metaphors, association are also found. Although some shortcomings are there but on the whole poet is successful in the field of Naat. This article presents an analytical study of Haraf-E-Sana
Inayatullah, Rubina Saigol, and Pervez Tahir (eds). Social Sciences in Pakistan: A Profile. Islamabad: Council of Social Sciences, 2005. 512 pages. Hardbound. Rs 500.00.
No full textCommissioned by the Council of Social Sciences (COSS), this
volume evaluates the seventeen social sciences departments in the public
universities in Pakistan for a given set of parameters. The social
sciences departments or the topics covered in this volume and their
respective authors include: Teaching of International Relations in
Pakistani Universities (Rasul Bakhsh Rais); Development of the
Discipline of Political Science in Pakistan (Inayatullah); The
Development of Strategic Studies in Pakistan (Ayesha Siddiqa); The State
of Educational Discourse in Pakistan (Rubina Saigol); Development of
Philosophy as a Discipline (Mohammad Ashraf Adeel); The State of the
Discipline of Psychology in Public Universities in Pakistan: A Review
(Muhammad Pervez and Kamran Ahmad); Development of Economics as a
Discipline in Pakistan (Karamat Ali); Sociology in Pakistan: A Review of
Progress (Muhammad Hafeez); Anthropology in Pakistan: The State of [sic]
Discipline (Nadeem Omar Tarar); Development of the Discipline of History
in Pakistan (Mubarak Ali); The Discipline of Public Administration in
Pakistan (Zafar Iqbal Jadoon and Nasira Jabeen); Journalism and Mass
Communication (Mehdi Hasan); Area Studies in Pakistan: An Assessment
(Muhammad Islam); Pakistan Studies: A Subject of the State, and the
State of the Subject (Syed Jaffar Ahmed); The State of the Discipline of
Women’s Studies in Pakistan (Rubina Saigol); Peace and Conflict
Resolution Studies (Moonis Ahmar and Farhan H. Siddiqi); and Linguistics
in Pakistan: A Survey of the Contemporary Situation (Tariq
Rahman)
Rotten-Fruit-Sorting Robotic Arm: (Design of Low Complexity CNN for Embedded System)
No full textIndustrial Automation has revolutionized the processing industry due to its high accuracy, the time it saves, and its ability to work without tiring. Being the most fundamental part of automation machines, robotic arms are being used as a fundamental component in many types of domestic as well as commercial automation units. In this paper, we proposed a low-complexity convolutional neural network (CNN) model and successfully deployed it on a locally generated robotic arm with the help of a Raspberry Pi 4 module. The designed robotic arm can detect, locate, and classify (based on fresh or rotten) between three species of Mangos (Ataulfo, Alphonso, and Keitt), on a conveyor belt. We generated a dataset of about 6000 images and trained a three-convolutional-layer-based CNN. Training and testing of the network were carried out with MatLab, and the weighted network was deployed to an embedded environment (Raspberry Pi 4 module) for real-time classification. We reported a classification accuracy of 98.08% in the detection of fresh mangos and 95.75% in the detection of rotten mangos. For the designed robotic art, the achieved angle accuracy was 93.94% with a minor error of only 2°. The proposed model can be deployed in many food- or object-sorting industries as an edge computing application of deep learning
Recent Progress in Isotropic Magnetorheological Elastomers and Their Properties: A Review
No full textMagnetorheological elastomers (MREs) are magneto-sensitive smart materials, widely used in various applications, i.e., construction, automotive, electrics, electronics, medical, minimally invasive surgery, and robotics. Such a wide field of applications is due to their superior properties, including morphological, dynamic mechanical, magnetorheological, thermal, friction and wear, and complex torsional properties. The objective of this review is to provide a comprehensive review of the recent progress in isotropic MREs, with the main focus on their properties. We first present the background and introduction of the isotropic MREs. Then, the preparation of filler particles, fabrication methods of isotropic MREs, and key parameters of the fabrication process—including types of polymer matrices and filler particles, filler particles size and volume fraction, additives, curing time/temperature, and magnetic field strength—are discussed in a separate section. Additionally, the properties of various isotropic MREs, under specific magnetic field strength and tensile, compressive, or shear loading conditions, are reviewed in detail. The current review concludes with a summary of the properties of isotropic MREs, highlights unexplored research areas in isotropic MREs, and provides an outlook of the future opportunities of this innovative field
Laparoscopic retrieval of two intragastric spoons at least seven years after ingestion
No full textForeign body ingestion is a commonly encountered presentation. The majority of foreign bodies pass in stool spontaneously within one week or are managed endoscopically within the first 24–48 hours. No guidelines are available for management of chronically retained foreign bodies at present. A unique case is presented of two chronically retained teaspoons in the stomach that failed endoscopic retrieval and required laparoscopic surgery. Post operatively, the patient did well with no complications. A large foreign body that is not amenable to endoscopic intervention will benefit from surgery. If expertise is available, laparoscopic intervention is a safe and feasible option to remove large foreign bodies from the stomach that is not amenable to endoscopic retrieval
Brain tumor classification using MRI images and convolutional neural networks
No full textThe brain tumor has become one of the most prominent types of cancers affecting a huge population across the globe every year. It has the lowest life expectancy rate and the risk of death is highly associated with the type, shape, and location of the tumor. The Magnetic Resonance Imaging (MRI) is a strong tool to detect different brain lesions and is extensively used by radiologists and physicians. For the early and accurate diagnosis of the brain tumor using MRI, it is important to consider automated computer-assisted diagnosis which is more flexible and efficient. In this paper, we have proposed a Convolutional Neural Network (CNN) based approach for the classification of three types of brain tumors (meningiomas, gliomas, and pituitary tumors). A publicly available dataset that contains 3064 T1-weighted brain CE-MRI images collected from 233 patients has been used in the study. We propose a 15 layers CNN model for the classification of three types of brain tumors from the mentioned dataset. We obtained an accuracy, precision, recall, and f1-score of 98.6%, 99%, 98.3%, and 98.6% from our proposed model which is higher than previously reported results
Opportunities and Challenges of AC/DC Transmission Network Planning Considering High Proportion Renewable Energy
No full textEvaluation of the effect of high penetration of renewable energy sources (RES) on system frequency regulation using stochastic risk assessment technique (an approach based on improved cumulant)
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