排序方式： 共有26条查询结果，搜索用时 15 毫秒
1.
Fadi Aloul Imran Zualkernan Ghaleb Husseini Ayman El-Hag Yousef Al-Assaf 《European Journal of Engineering Education》2015,40(1):32-51
Introductory engineering courses are either programme specific or expose students to engineering as a broad discipline by including materials from various engineering programmes. A common introductory engineering course that spans different engineering programmes raises challenges, including the high cost of resources as well as the lack of background courses of first-year students. This paper presents the design, implementation and evaluation of a first-year common engineering course that uses low-cost materials to expose students to a structured engineering design process. The course is explicitly designed to satisfy the Accreditation Board for Engineering and Technology criteria for engineering programmes. Our experience with the course shows that not only students are able to follow a structured design process successfully but we also believe that most of the ABET criteria are being delivered through the course. 相似文献
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Imran Ghous Zhaoxia Duan Jahanzeb Akhtar Muhammad Jawad 《Journal of The Franklin Institute》2019,356(16):9407-9431
This paper aims to solve the problem of sliding mode control for an uncertain two-dimensional (2-D) systems with states having time-varying delays. The uncertainties in the system dynamics are constituted of mismatched uncertain parameters and the unknown nonlinear bounded function. The proposed problem utilizes the model transformation approach. By segregating the proper Lyapunov–Krasovskii functional in concert with the improved version of Wirtinger-based summation inequality, sufficient solvability conditions for the existence of linear switching surfaces have been put forward, which ensure the asymptotical stability of the reduced-order equivalent sliding mode dynamics. Then, we solve the controller synthesis problem by extending the recently proposed reaching law to 2-D systems, whose proportional part is appropriately scaled by the factor that does not depend on some constant terms but rather on current switching surface’s value, which in turn ensures the faster convergence and better robustness against uncertainties. Finally, the proposed results have been validated through an implementation to a suitable physical system. 相似文献
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We report physicochemical characteristics of various kinds of liquid milk commercially available in Pakistan in comparison with those of fresh natural milk from animals. Milk samples were collected from local markets at Peshawar, Pakistan,and analyzed for their physical features, including moisture, total solids, specific gravity, conductivity, viscosity and titratable acidity (lactic acid equivalent), and chemical components and macro-minerals, including total protein, casein, lactose, ash and minerals (Na, K and Mg). These items were compared with the physicochemical characteristics of the fresh natural milk samples from buffalo, cow and goat. The results were also compared with reported nutritional quality of milk from various countries and World Health Organization (WHO) standards. We found that all the physical features and chemical components of commercially available milk in Pakistan markets meet WHO's requirements, except for Na, K, Ca and Mg, which are below the standards. 相似文献
4.
Learning materials recommendation using good learners’ ratings and content-based filtering 总被引：1，自引：0，他引：1
Khairil Imran Ghauth Nor Aniza Abdullah 《Educational technology research and development : ETR & D》2010,58(6):711-727
The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials
for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim
to address this need by proposing a novel e-learning recommender system framework that is based on two conceptual foundations—peer
learning and social learning theories that encourage students to cooperate and learn among themselves. Our proposed framework
works on the idea of recommending learning materials with a similar content and indicating the quality of learning materials
based on good learners’ ratings. A comprehensive set of experiments were conducted to measure the system accuracy and its
impact on learner’s performance. The obtained results show that the proposed e-learning recommender system has a significant
improvement in the post-test of about 12.16% with the effect size of 0.6 and 13.11% with the effect size of 0.53 when compared
to the e-learning with a content-based recommender system and the e-learning without a recommender system, respectively. Furthermore,
the proposed recommender system performed better in terms of having a small rating deviation and a higher precision as compared
to e-learning with a content-based recommender system. 相似文献
5.
Amer M. Magableh Osamah S. Badarneh Imran Shafique Ansari Taimour Aldalgamouni 《Journal of The Franklin Institute》2018,355(14):6877-6888
Transmit antenna selection with maximal ratio combining at the receiver (TAS/MRC) is a promising technique that can be used to avoid the hardware complexity of multiple input multiple output (MIMO) system without jeopardizing the diversity gain. The generalized Gaussian distribution (GGD) is used to model different kinds of additive noise including Gaussian, Laplacian, uniform, and impulsive. In this paper, we study the bit error performance of TAS/MRC system assuming flat Rayleigh fading channels perturbed by additive white generalized Gaussian noise (AWGGN). To this end, we provide a closed form expression for the average bit error rate of coherent modulation techniques in terms of Mejier’s G function that is readily available in many commercial mathematical software packages like MATLAB and Mathematica. Moreover, we study the asymptotic behavior of the BER at high signal to noise ratio (SNR). Analytical results are verified by simulation. 相似文献
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Zenun Kastrati Ali Shariq Imran Sule Yildirim Yayilgan 《Information processing & management》2019,56(5):1618-1632
This paper presents a semantically rich document representation model for automatically classifying financial documents into predefined categories utilizing deep learning. The model architecture consists of two main modules including document representation and document classification. In the first module, a document is enriched with semantics using background knowledge provided by an ontology and through the acquisition of its relevant terminology. Acquisition of terminology integrated to the ontology extends the capabilities of semantically rich document representations with an in depth-coverage of concepts, thereby capturing the whole conceptualization involved in documents. Semantically rich representations obtained from the first module will serve as input to the document classification module which aims at finding the most appropriate category for that document through deep learning. Three different deep learning networks each belonging to a different category of machine learning techniques for ontological document classification using a real-life ontology are used.Multiple simulations are carried out with various deep neural networks configurations, and our findings reveal that a three hidden layer feedforward network with 1024 neurons obtain the highest document classification performance on the INFUSE dataset. The performance in terms of F1 score is further increased by almost five percentage points to 78.10% for the same network configuration when the relevant terminology integrated to the ontology is applied to enrich document representation. Furthermore, we conducted a comparative performance evaluation using various state-of-the-art document representation approaches and classification techniques including shallow and conventional machine learning classifiers. 相似文献
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Shahzad Fakhar Xiu GuoYi Khan Imran Shahbaz Muhammad Riaz Muhammad Usman Abbas Adnan 《Asia Pacific Education Review》2020,21(1):121-141
Asia Pacific Education Review - In the provision of massive open online courses (MOOCs), cloud computing services enable students to synchronize their study materials anywhere, anytime, and using... 相似文献
10.
Natural biological systems are constantly developing efficient mechanisms to counter adverse effects of increasing human population and depleting energy resources. Their intelligent mechanisms are characterized by the ability to detect changes in the environment, store and evaluate information, and respond to external stimuli. Bio-inspired replication into man-made functional materials guarantees enhancement of characteristics and performance. Specifically, butterfly architectures have inspired the fabrication of sensor and energy materials by replicating their unique micro/nanostructures, light-trapping mechanisms and selective responses to external stimuli. These bio-inspired sensor and energy materials have shown improved performance in harnessing renewable energy, environmental remediation and health monitoring. Therefore, this review highlights recent progress reported on the classification of butterfly wing scale architectures and explores several bio-inspired sensor and energy applications. 相似文献