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Effect of Microwave Power and Clamping Pressure on the Microwave Welding of Polypropylene Using Silicon Carbide Nanowhiskers as Microwave Susceptor

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Chinese Journal of Polymer Science 2022年第11期40卷 1466-1481页

作者： Phey Yee Foong Chun Hong Voon Bee Ying Lim Pei Leng Teh mohd Afendi Bin Rojan Nor Azizah Parmin Subash C.B.Gopinath mohd khairuddin md arshad Foo Wah Low Savisha Mahalingam Abreeza Manap Ruslinda A.Rahim Uda Hashim Institute of Nano Electronic Engineering Universiti Malaysia PerlisSeriabKangarPerlis01000Malaysia Faculty of Chemical Engineering Technology Universiti Malaysia PerlisJejawiPerlis Arau02600Malaysia Faculty of Mechanical Engineering Technology Universiti Malaysia PerlisPauhPerlis Arau02600Malaysia Department of Electrical&Electronic Engineering Lee Kong Chian Faculty of Engineering&ScienceUniversiti Tunku Abdul RahmanBandar Sungai LongKajangSelangor43000Malaysia Institute of Sustainable Energy Universiti Tenaga NasionalJalan IKRAM-UNITENKajangSelangor43000Malaysia

Due to their excellent dielectric properties and the rapid response to microwave irradiation,silicon carbide nanowhiskers(SiCNWs)were employed as microwave susceptor in this study to absorb microwave and locally melt the surrounding polypropylene(PP)substrates for the joining of PP *** welded joint is formed after the melted PP was cooled and *** than microwave susceptor,SiCNWs also acted as the nanofillers in strengthening the welded joint through the formation of SiCNWs reinforced PP nanocomposite at the interface of PP ***,the effect of microwave power on the microwave welding of PP substrates using SiCNWs as susceptor was studied and *** was found that the tensile strength and modulus of elasticity of the welded joint improved as microwave power ***,it deteriorates the flexibility of the welded joint as high stiffness SiCNWs were incorporated deeper into the PP matrix which restricted the PP chain *** from microwave power,clamping pressure is also critical in determining the mechanical properties of a welded *** compared to unclamped welded joint,the tensile strength,modulus of elasticity and flexibility of welded joint subjected to clamping pressure improved ***,the tensile strength of welded joint increased when the clamping pressure was increased from P1 to P3,but decreased when the clamping pressure was further increased to P4 due to the occurrence of flashing at welded *** formation mechanism of SiCNWs reinforced PP welded joint was also proposed in this *** to conventional welding,this welding process is easy,straightforward and is able to produce welded joint with outstanding mechanical properties via precise controlling of the processing ***,microwave welding is thought to offer an option for the joining of thermoplastics and other applications.

关键词： Microwave welding Silicon carbide Nanowhiskers Joining Susceptor

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Calf Posture Recognition Using Convolutional Neural Network

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Computers, Materials & Continua 2023年第1期74卷 1493-1508页

作者： Tan Chen Tung Uswah khairuddin mohd Ibrahim Shapiai Norhariani md Nor Mark Wen Han Hiew Nurul Aisyah mohd Suhaimie Malaysia-Japan International Institute of Technology Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia Faculty of Veterinary Medicine Universiti Putra MalaysiaSelangor43400Malaysia Faculty of Bioresources and Food Industry Besut22200Malaysia

Dairy farm management is crucial to maintain the longevity of the farm,and poor dairy youngstock or calf management could lead to gradually deteriorating calf health,which often causes premature *** was found to be the most neglected part among the management workflows in Malaysia and has caused continuous loss over the recent *** posture recognition is one of the effective methods to monitor calf behaviour and health state,which can be achieved by monitoring the calf behaviours of standing and lying where the former depicts active calf,and the latter,passive *** posture recognition module is an important component of some automated calf monitoring systems,as the system requires the calf to be in a standing posture before proceeding to the next stage of monitoring,or at the very least,to monitor the activeness of the *** posture such as standing or resting can easily be distinguished by human eye,however,to be recognized by a machine,it will require more complicated frameworks,particularly one that involves a deep learning neural networks *** number of highquality images are required to train a deep learning model for such *** this paper,multiple ConvolutionalNeuralNetwork(CNN)architectures were compared,and the residual network(ResNet)model(specifically,ResNet-50)was ultimately chosen due to its simplicity,great performance,and decent inference *** ResNet-50 models having the exact same architecture and configuration have been trained on two different image datasets respectively sourced by separate cameras placed at different *** were two camera placements to use for comparison because camera placements can significantly impact the quality of the images,which is highly correlated to the deep learning model *** model training,the performance for both CNN models were 99.7%and 99.99%accuracies,respectively,and is adequate for a real-time calf monitoring system.

关键词： Calf posture machine vision deep learning transfer learning

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Optimized Gated Recurrent Unit for Mid-Term Electricity Price Forecasting

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Computer Systems Science & Engineering 2022年第11期43卷 817-832页

作者： Rashed Iqbal Hazlie Mokhlis Anis Salwa mohd khairuddin Syafiqah Ismail Munir Azam Muhammad Department of Electrical Engineering Faculty of EngineeringUniversiti Malaya50603Malaysia Department of Electrical Engineering Main CampusIqra UniversityKarachi75300Pakistan

Electricity price forecasting(EPF)is important for energy system operations and management which include strategic bidding,generation scheduling,optimum storage reserves scheduling and systems ***,accurate EPF is crucial for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity ***,accurate time-series prediction of electricity price is very challenging due to complex nonlinearity in the trend of electricity *** work proposes a mid-term forecasting model based on the demand and price data,renewable and non-renewable energy supplies,the seasonality and peak and off-peak hours of working and nonworking *** optimized Gated Recurrent Unit(GRU)which incorporates Bagged Regression Tree(BTE)is developed in the Recurrent Neural Network(RNN)architecture for the mid-term *** layer is employed to optimize the hyperparameters of the heterogeneous GRU with the aim to improve the model’s performance,error reduction and predict the *** this work,the proposed framework is assessed using electricity market data of five major economical states in Australia by using electricity market data from August 2020 to May *** results showed significant improvement when adopting the proposed prediction framework compared to previous works in forecasting the electricity price.

关键词： Deep learning energy management machine learning prediction

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Generating Type 2 Trapezoidal Fuzzy Membership Function Using Genetic Tuning

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Computers, Materials & Continua 2022年第4期71卷 717-734页

作者： Siti Hajar khairuddin mohd Hilmi Hasan Emilia Akashah P.Akhir Manzoor Ahmed Hashmani Centre for Research in Data Science Department of Computer and Information SciencesUniversiti Teknologi PETRONASPerakMalaysia

Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified *** system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the *** are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational *** paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani *** the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system *** novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and *** approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM *** result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA *** is shown that the proposed approach is able to outperform the mentioned benchmarked *** work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.

关键词： Fuzzy inference system membership function genetic tuning lateral adjustment trapezoidal MF fuzzy C means

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An Exploratory Study of University X＇s State of Readiness： Scholarship of Teaching, Shared Governance and Change Management

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Sociology Study 2012年第5期2卷 362-375页

作者： Hamzah Bin md.Omar mohd khairuddin Abdullah Universiti Malaysia Sabah Malaysia

In this paper we first explore what scholarship of teaching （SOT）, shared governance and change management means, both in terms of the way that is represented in the literature and the way that is understood by academic staff themselves. From this information we derive qualitative and quantitative interpretation which captures the variations found in the literature and empirical studies. In the final section we illustrate how the state of readiness in the three areas is in place for the development of the SoT, shared governance, and change management in University X.

关键词： University scholarship of teaching (SOT) shared governance change management readiness

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A Stacked Ensemble Deep Learning Approach for Imbalanced Multi-Class Water Quality Index Prediction

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Computers, Materials & Continua 2023年第8期76卷 1361-1384页

作者： Wen Yee Wong Khairunnisa Hasikin Anis Salwa mohd khairuddin Sarah Abdul Razak Hanee Farzana Hizaddin mohd Istajib Mokhtar Muhammad Mokhzaini Azizan Department of Biomedical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia Institute of Biological Sciences Faculty of ScienceUniversity of MalayaKuala Lumpur50603Malaysia Department of Chemical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia Department of Science and Technology Studies Faculty of ScienceUniversity of MalayaKuala Lumpur50603Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering and Built EnvironmentUniversiti Sains Islam MalaysiaNilaiNegeri Sembilan71800Malaysia

A common difficulty in building prediction models with real-world environmental datasets is the skewed distribution of *** are significantly more samples for day-to-day classes,while rare events such as polluted classes are ***,the limited availability of minority outcomes lowers the classifier’s overall *** study assesses the capability of machine learning(ML)algorithms in tackling imbalanced water quality data based on the metrics of precision,recall,and F1 *** intends to balance the misled accuracy towards the majority of ***,10 ML algorithms of its performance are *** classifiers included are AdaBoost,SupportVector Machine,Linear Discriminant Analysis,k-Nearest Neighbors,Naive Bayes,Decision Trees,Random Forest,Extra Trees,Bagging,and the Multilayer *** study also uses the Easy Ensemble Classifier,Balanced Bagging,andRUSBoost algorithm to evaluatemulti-class imbalanced learning *** comparison results revealed that a highaccuracy machine learning model is not always good in recall and *** paper’s stacked ensemble deep learning(SE-DL)generalization model effectively classifies the water quality index(WQI)based on 23 input *** proposed algorithm achieved a remarkable average of 95.69%,94.96%,92.92%,and 93.88%for accuracy,precision,recall,and F1 score,*** addition,the proposed model is compared against two state-of-the-art classifiers,the XGBoost(eXtreme Gradient Boosting)and Light Gradient Boosting Machine,where performance metrics of balanced accuracy and g-mean are *** experimental setup concluded XGBoost with a higher balanced accuracy and ***,the SE-DL model has a better and more balanced performance in the F1 *** SE-DL model aligns with the goal of this study to ensure the balance between accuracy and completeness for each water quality *** proposed algorithm is also capable of higher efficiency at a lower computa

关键词： Water quality classification imbalanced data SMOTE stacked ensemble deep learning sensitivity analysis

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Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features

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Computer Modeling in Engineering & Sciences 2022年第9期132卷 1011-1038页

作者： Wen Yee Wong Ayman Khallel Ibrahim Al-Ani Khairunnisa Hasikin Anis Salwa mohd khairuddin Sarah Abdul Razak Hanee Farzana Hizaddin mohd Istajib Mokhtar Muhammad Mokhzaini Azizan Department of Biomedical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Electrical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Institute of Biological Sciences Faculty of ScienceUniversiti MalayaKuala Lumpur50603Malaysia Department of Chemical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Science and Technology Studies Faculty of ScienceUniversiti MalayaKuala Lumpur50603Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering and Built EnvironmentUniversiti Sains Islam MalaysiaBandar Baru NilaiNilaiNegeri Sembilan71800Malaysia

Water quality analysis is essential to understand the ecological status of aquatic *** water quality index(WQI)assessment methods are limited to features such as water acidic or basicity(pH),dissolved oxygen(DO),biological oxygen demand(BOD),chemical oxygen demand(COD),ammoniacal nitrogen(NH3-N),and suspended solids(SS).These features are often insufficient to represent the water quality of a heavy metal–polluted ***,this paper aims to explore and analyze novel input features in order to formulate an improved *** this work,prospective insights on the feasibility of alternative water quality input variables as new discriminant features are *** new discriminant features are a step toward formulating adaptive water quality parameters according to the land use activities surrounding the *** results and analysis obtained from this study have proven the possibility of predicting WQI using new input *** work analyzes 17 new input features,namely conductivity(COND),salinity(SAL),turbidity(TUR),dissolved solids(DS),nitrate(NO3),chloride(Cl),phosphate(PO4),arsenic(As),chromium(Cr),zinc(Zn),calcium(Ca),iron(Fe),potassium(K),magnesium(Mg),sodium(Na),***,and total coliform,in predicting WQI using machine learning *** regression algorithms-random forest(RF),AdaBoost,support vector regression(SVR),decision tree regression(DTR),and multilayer perception(MLP)-are applied for preliminary model *** results show that the RF algorithm exhibits better prediction performance,with R2 of ***,this work proposes a modified RF by incorporating the synthetic minority oversampling technique(SMOTE)into the conventional RF *** proposed modified RF method is shown to achieve 77.68%,74%,69%,and 71%accuracy,precision,recall,and F1-score,*** addition,the sensitivity analysis is included to highlight the importance of the turbidity variable in WQI *** results of sensitivity analysis high

关键词： Artificial intelligence random forest environmental modeling alternative inputs SMOTE

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Colour Features Extraction Techniques and Approaches for Content-Based Image Retrieval (CBIR) System

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Journal of Materials Science and Chemical Engineering 2021年第7期9卷 29-34页

作者： Muhammad Naim Abdullah mohd Afizi mohd Shukran mohd Rizal mohd Isa Nor Suraya Mariam Ahmad Mohammad Adib khairuddin mohd Sidek Fadhil mohd Yunus Fatimah Ahmad Universiti Pertahanan Nasional Malaysia (UPNM) Kuala Lumpur Malaysia University Malaysia of Computer Science and Engineering (UNIMY) Selangor Malaysia Universiti Pendidikan Sultan Idris (UPSI) Perak Malaysia

An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and colour similarity. Retrieving images based on the contents which are colour, texture, and shape is called content-based image retrieval (CBIR). This paper discusses and describes about the colour features technique for image retrieval systems. Several colour features technique and algorithms produced by the previous researcher are used to calculate the similarity between extracted features. This paper also describes about the specific technique about the colour basis features and combined features (hybrid techniques) between colour and shape features.

关键词： Content-Based Image Retrieval Colour Features CBIR

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Survey on Clustering Techniques for Image Categorization Dataset

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Journal of Computer and Communications 2022年第6期10卷 177-185页

作者： mohd Afizi mohd Shukran mohd Sidek Fadhil mohd Yunus Muhammad Naim Abdullah mohd Rizal mohd Isa Mohammad Adib khairuddin Kamaruzaman Maskat Suhaila Ismail Abdul Samad Shibghatullah Universiti Pertahanan Nasional Malaysia Kuala Lumpur Malaysia University Malaysia of Computer Science & Engineering (UNIMY) Cyberjaya Malaysia UCSI University Kuala Lumpur Malaysia

Content Based Image Retrieval, CBIR, performed an automated classification task for a queried image. It could relieve a user from the laborious and time-consuming metadata assigning for an image while working on massive image collection. For an image, user’s definition or description is subjective where it could belong to different categories as defined by different users. Human based categorization and computer-based categorization might produce different results due to different categorization criteria that rely on dataset structure and the clustering techniques. This paper is aimed to exhibit an idea for planning the dataset structure and choosing the clustering algorithm for CBIR implementation. There are 5 sections arranged in this paper;CBIR and QBE concepts are introduced in Section 1, related image categorization research is listed in Section 2, the 5 type of image clustering are described in Section 3, comparative analysis in Section 4, and Section 5 conclude this study. Outcome of this paper will be benefiting CBIR developer for various applications.

关键词： Categorization CBIR Classifications Clustering Dataset

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Colour Features Extraction Techniques and Approaches for Content-Based Image Retrieval（CBIR） System

Colour Features Extraction Techniques and Approaches for Con...

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An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and colour similarity. Retrieving images based on the contents which are colour, texture, and shape is called content-based image retrieval（CBIR）. This paper discusses and describes about the colour features technique for image retrieval systems. Several colour features technique and algorithms produced by the previous researcher are used to calculate the similarity between extracted features. This paper also describes about the specific technique about the colour basis features and combined features（hybrid techniques） between colour and shape features.

关键词： Content-Based Image Retrieval Colour Features CBIR

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