51 research outputs found
DJI Company / Muhammad Mustaqeem Mashasan
No full textTechnological development can be defined as the application of information intended to design and use the goods and services. The study of technology entrepreneurship serves an important function beyond satisfying intellectual curiosity. This case study reports the findings of a thorough study of a company use technology in the business. This case study reports that the results of a comprehensive study of companies using technology in business are very high. Furthermore, this case study purposely to find the innovation of technology used in entrepreneurship which can be developed in business whether it is a global or small business. Besides, this study intends to innovate the use of technology in business to become effective and interesting. Therefore, this study case intends to make improvement of existing drone by implementing technological solution. In this case study, the idea is to improve the existing spy drone is developing an autopilot spy drone integrated with artificial intelligence. This case study targeted DJI company for company analysis which require to analyse their company background, their products which is a drone and how their business, marketing and operational are done. This case study also had analysed company by using SWOT analysis to define their strengths, weakness, opportunities, and threats
sj-docx-1-jbf-10.1177_22808000221134988 – Supplemental material for Studying in vivo and in vitro effects of a novel polyvinyl benzyl chloride-D-glucaro-1, 4-lactonate polymer-coated bile duct stent for anti-biliary mud deposition
No full textSupplemental material, sj-docx-1-jbf-10.1177_22808000221134988 for Studying in vivo and in vitro effects of a novel polyvinyl benzyl chloride-D-glucaro-1, 4-lactonate polymer-coated bile duct stent for anti-biliary mud deposition by Weixing Zhang, Fariha Kanwal, Aima Iram Batool, Muhammad Mustaqeem, Muhammad Fayyaz ur Rehman and Xinjian Wan in Journal of Applied Biomaterials & Functional Materials</p
Quran, a Lighthouse for the Humanity: A Research Review
No full textThe first surah of the Holy Quran is described as the “Prologue of the Holy Quran”. Surah Fateha is a perfect whole, complete and flawless it provide us truth and wisdom of life and every phrase high light the importance of rightness. It is known as an epitome of the Holy Quran and the Mother of Book. In the first five verses of this surah all the praises are done for Allah Almighty who is the Most Gracious and Ever Merciful. He is the Creator and the Master of the Day of Judgment. For all are desires, wishes, sorrows and problems we only seeks His guidance. In the six verse “Ih’dina,As-sirat,Al-Mustaqeem” ,we seek Allah’s help to guidance along the straight path. Human beings are weak and for their every worldly affair seek Divine help and support. Man confesses and acknowledges his weakness and summits his self through prayers to his Creator. This particular verse of surah Fateha embodies a humble request to Allah to show the right path which finally leads him to the fulfillment of his purpose and objective his life. This verse is the voice of human conscience appeals to God to reveal the purpose of human life. This Quranic verse provides complete guidance right from and awareness the purpose of human existence up to the actual realization of this purpose.
Keywords: Lord; Guidance; Right path; Soul; Purpose; Human’s life;Ih’dina,As-sirat,Al-Mustaqeem;Quranic knowledge; Man’s creation; Individual; National and international leve
Hydrogen Revolution: Advances in Catalytic Ammonia Decomposition
No full textThe simple storage of ammonia combined with the tendency to liberate hydrogen without carbon dioxide emissions has made ammonia breakdown popular among the research community in recent years. This review article has discussed the current advances in ammonia breakdown technology for hydrogen generation, focusing on new materials and mechanical designs for catalysis. Moreover, it would help to update the knowledge about the catalytic reaction processes and emphasize the benefits and drawbacks of each strategy. Furthermore, the significance of discovering a cost-effective metal catalyst with better efficiency and higher reliability is also debated. This article may serve as a fundamental resource to scale up information about the catalytic production of hydrogen from ammonia
Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants
No full textArrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixteen subclasses, among which one class represents absence of disease and the other fifteen classes represent electrocardiogram records of various subtypes of arrhythmias. The research is carried out on the dataset taken from the University of California at Irvine Machine Learning Data Repository. The dataset contains a large volume of feature dimensions which are reduced using wrapper based feature selection technique. For multiclass classification, support vector machine (SVM) based approaches including one-against-one (OAO), one-against-all (OAA), and error-correction code (ECC) are employed to detect the presence and absence of arrhythmias. The SVM method results are compared with other standard machine learning classifiers using varying parameters and the performance of the classifiers is evaluated using accuracy, kappa statistics, and root mean square error. The results show that OAO method of SVM outperforms all other classifiers by achieving an accuracy rate of 81.11% when used with 80/20 data split and 92.07% using 90/10 data split option.</jats:p
Automated Wheat Diseases Classification Framework Using Advanced Machine Learning Technique
No full textAround the world, agriculture is one of the important sectors of human life in terms of food, business, and employment opportunities. In the farming field, wheat is the most farmed crop but every year, its ultimate production is badly influenced by various diseases. On the other hand, early and precise recognition of wheat plant diseases can decrease damage, resulting in a greater yield. Researchers have used conventional and Machine Learning (ML)-based techniques for crop disease recognition and classification. However, these techniques are inaccurate and time-consuming due to the unavailability of quality data, inefficient preprocessing techniques, and the existing selection criteria of an efficient model. Therefore, a smart and intelligent system is needed which can accurately identify crop diseases. In this paper, we proposed an efficient ML-based framework for various kinds of wheat disease recognition and classification to automatically identify the brown- and yellow-rusted diseases in wheat crops. Our method consists of multiple steps. Firstly, the dataset is collected from different fields in Pakistan with consideration of the illumination and orientation parameters of the capturing device. Secondly, to accurately preprocess the data, specific segmentation and resizing methods are used to make differences between healthy and affected areas. In the end, ML models are trained on the preprocessed data. Furthermore, for comparative analysis of models, various performance metrics including overall accuracy, precision, recall, and F1-score are calculated. As a result, it has been observed that the proposed framework has achieved 99.8% highest accuracy over the existing ML techniques
Chromogenic and fluorogenic detection of copper ions in the solution and intracellular media
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