Deep learning has been a catalyst for a transformative revo-lution in machine learning and computer vision in the past decade.Within these research domains,methods grounded in deep learning have exhibited exceptional ...Deep learning has been a catalyst for a transformative revo-lution in machine learning and computer vision in the past decade.Within these research domains,methods grounded in deep learning have exhibited exceptional performance across a spectrum of tasks.The success of deep learning methods can be attributed to their capability to derive potent representations from data,integral for a myriad of downstream applications.These representations encapsulate the intrinsic structure,fea-tures,or latent variables characterising the underlying statistics of visual data.Despite these achievements,the challenge per-sists in effectively conducting representation learning of visual data with deep models,particularly when confronted with vast and noisy datasets.This special issue is a dedicated platform for researchers worldwide to disseminate their latest,high-quality articles,aiming to enhance readers'comprehension of the principles,limitations,and diverse applications of repre-sentation learning in computer vision.展开更多
The viability of the indium phosphide(InP)Gunn diode as a source for low-THz band applications is analyzed based on a notch-δ-doped structure using the Monte Carlo modeling.The presence of theδ-doped layer could enh...The viability of the indium phosphide(InP)Gunn diode as a source for low-THz band applications is analyzed based on a notch-δ-doped structure using the Monte Carlo modeling.The presence of theδ-doped layer could enhance the current harmonic amplitude(A0)and the fundamental operating frequency(f0)of the InP Gunn diode beyond 300 GHz as compared with the conventional notch-doped structure for a 600-nm length device.With its superior electron transport properties,the notch-δ-doped InP Gunn diodes outperform the corresponding gallium arsenide(GaAs)diodes with up to 1.35 times higher in f0 and 2.4 times larger in A0 under DC biases.An optimized InP notch-δ-doped structure is estimated to be capable of generating 0.32-W radio-frequency(RF)power at 361 GHz.The Monte Carlo simulations predict a reduction of 44%in RF power,when the device temperature is increased from 300 K to 500 K;however,its operating frequency lies at 280 GHz which is within the low-THz band.This shows that the notch-δ-doped InP Gunn diode is a highly promising signal source for low-THz sensors,which are in a high demand in the autonomous vehicle industry.展开更多
The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease(COVID-19)pandemic,globalization,technology advancement in Indu...The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease(COVID-19)pandemic,globalization,technology advancement in Industry 4.0,and other contributing factors.The pervasiveness of the issue poses a huge challenge to improving the occupational safety and health(OSH)of workers in various industries,especially in the digital industry.The emergence of the innovative industry is evident mainly due to the rapid development of Industry 4.0 and the rele-vant demands of multiple businesses in the digital transformation.Nonetheless,limited studies and academic dis-cussions were conducted on the OSH topic of digital employees.Hence,the current study serves tofill the existing gap and provide academic contributions by scrutinising the perceptions of digital workers regarding their work-place well-being,mental health literacy,and the impression of employing e-mental health.The objectives of this study are:1)To examine the mental health literacy and workplace wellness of digital workers,2)to explore the e-mental health usage intention and actual e-mental health utilization,and 3)to identify digital workers’feedback on e-mental health.In the current context,e-mental health focuses on three dimensions,namely,1)“health in our hand(HIOH)”,2)“interacting for health(IFH)”,and 3)“data enabling health(DEH)”.The present study employed an online cross-sectional survey and received 326 digital workers’completed responses.Variables,such as“mental health literacy(MHL)”,“workplace wellness(WW)”,and e-mental health intention and usage were explicated by analysing the data through descriptive statistics.The study results indicated a moderate to a high level of the MHL and the WW.More than half of the workers possessed a high intention level to employ e-mental health,with the HIOH dimension being the most prevalent domain.Nevertheless,the actual e-mental health usage was very low,owing to the online resources being a new concept amongst digital employees.Numerous confounding factors also existed in affecting the low usage,such as privacy concerns,data security levels,and health verification issues.In addition,the mental health issue has not been openly and widely discussed in Malay-sian workplaces due to stigmatisation.As such,the currentfindings could provide additional insights into the OSH literature;it could serve as a guideline for the OSH decision-makers,employers,and eHealth developers when establishing a feasible framework for the practical adoption of e-mental health services by digital workers.展开更多
The existence of several non-symmetric balanced incomplete block designs (BIBDs) is still unknown. This is because the non-existence property for non-symmetric BIBDs is still not known and also the existing constructi...The existence of several non-symmetric balanced incomplete block designs (BIBDs) is still unknown. This is because the non-existence property for non-symmetric BIBDs is still not known and also the existing construction methods have not been able to construct these designs despite their design parameters satisfying the necessary conditions for the existence of BIBD. The study aimed to bridge this gap by introducing a new class of non-symmetric BIBDs. The proposed class of BIBDs is constructed through the combination of disjoint symmetric BIBDs. The study was able to determine that the total number of disjoint symmetric BIBDs (n) with parameters (v = b, r = k, λ) that can be obtained from an un-reduced BIBD with parameters (v, k) is given by n = r - λ. When the n symmetric disjoint BIBDs are combined, then a new class of symmetric BIBDs is formed with parameters v<sup>*</sup><sup> </sup>= v, b<sup>*</sup><sup> </sup>= nb, r<sup>*</sup><sup> </sup>= nr, k<sup>*</sup><sup> </sup>= k, λ<sup>*</sup><sup> </sup>= λ, where 2≤ n ≤ r - λ. The study established that the non-existence property of this class of BIBD was that when is not a perfect square then v should be even and when v<sup>*</sup><sup> </sup>is odd then the equation should not have a solution in integers x, y, z which are not all simultaneously zero. In conclusion, the study showed that this construction technique can be used to construct some non-symmetric BIBDs. However, one must first construct the disjoint symmetric BIBDs before one can construct the non-symmetric BIBD. Thus, the disjoint symmetric BIBDs must exist first before the non-symmetric BIBDs exist.展开更多
Concrete is the most widely used construction material in the world. The situation in the country is not an exception as most of the infrastructures in Kenya such as buildings, bridges, concrete drainage among others,...Concrete is the most widely used construction material in the world. The situation in the country is not an exception as most of the infrastructures in Kenya such as buildings, bridges, concrete drainage among others, are constructed using concrete. Sadly, the failure of buildings and other concrete structures is very common in Kenya. Blended Portland cement type 32.5 N/mm<sup>2</sup> is the most widely used concrete binder material and is found in all parts of the country. Despite blended cement CEM 32.5 being the most commonly used cement type in construction industry in Kenya and most developing countries as a result of its low price and availability locally, its strength gain has been proven to be lower compared to when other types of cement are used due to quantity of pozzolanic material added to the blend. This paper outlines findings of an experimental investigation on the use of cypress tree extract as an accelerator to enhance rate of gain of strength on Kenyan blended cements. Six different blended cement brands locally available were used during the study. Cement chemical analysis was done using X-ray diffraction method while for the cypress extract, Atomic Absorption Spectrometer machine was used. Physical and mechanical properties were checked based on the British standards. The generation of the concrete mix design was done using the British DOE method and concrete was tested for the compressive strength at 7, 14, 21, 28, 56 and 90 days. It was observed that 15% dosage of the extract expressed as a mass percentage of the cement content gives the most improved compressive strength of concrete, 10.4% at 7 days and 9.5% at 28 days hence the optimum. It was further noted that when Cypress tree extract is used as an accelerator in the mix, the blended cement concrete achieves the design strength at 27 days saving 10 days of the project duration compared to when no accelerator is used while the ultimate strength is achieved at 67 days. The study therefore recommends the use of the cypress tree bark extract at a dosage of 15%, by mass, of the cement content as an accelerator when the structure is to be loaded at 28 days and waiting up to 39 days before loading the structure if no accelerator is used for blended cement concrete.展开更多
本文提出了光码多分址(CDMA)和光密集波分复用(DWDM)的混合系统,全面研究了四波混频(FWM)的影响。在这个系统中,主要存在两个四波混频问题:包括多址干扰(MAI)和码间干扰(ISI)的帧间四波混频和信道内四波混频。结果表明,综合考虑信道间...本文提出了光码多分址(CDMA)和光密集波分复用(DWDM)的混合系统,全面研究了四波混频(FWM)的影响。在这个系统中,主要存在两个四波混频问题:包括多址干扰(MAI)和码间干扰(ISI)的帧间四波混频和信道内四波混频。结果表明,综合考虑信道间和信道内四波混频的影响,最佳发射功率可选为18 d Bm。当发射功率大于18 d Bm时,混合系统的误码率(BER)将增加。基于此,本文提出了一种电光相位调制器(EOPM)模块,将其放置在波分复用器之后,通过抑制信道内四波混频的影响,同时调制所有波长信号的相位,从而增加混合系统的非线性容限,这极大地改善了基于OOK传输的光学CDMA-DWDM混合系统的性能。此外,由于多对角线(MD)结构具有零互相关特性,通过使用多对角线识别序列码可以减少多址干扰的影响。结果还表明,CDMA技术与色散相结合有助于降低信道间四波混频的影响。此外,识别序列码间隔在减轻码间干扰中起着至关重要的作用,如结果所示,当识别序列码间隔压缩至比特持续时间的25%时,可以避免码间干扰,此时所提出的混合系统的性能最佳。展开更多
The principal component analysis (PCA) is a kind of algorithms in biometrics. It is a statistics technical and used orthogonal transformation to convert a set of observations of possibly correlated variables into a se...The principal component analysis (PCA) is a kind of algorithms in biometrics. It is a statistics technical and used orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables. PCA also is a tool to reduce multidimensional data to lower dimensions while retaining most of the information. It covers standard deviation, covariance, and eigenvectors. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.展开更多
Design of a robust production facility layout with minimum handling cost(MHC) presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly ch...Design of a robust production facility layout with minimum handling cost(MHC) presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly change in each planning period. The objective of the design is to find the robust facility layout with minimum total material handling cost over the entire multiperiod planning horizon. This paper proposes a new mathematical model for designing robust machine layout in the stochastic dynamic environment of manufacturing systems using quadratic assignment problem(QAP) formulation. In this investigation, product demands are assumed to be normally distributed random variables with known expected value, variance, and covariance that randomly change from period to period. The proposed model was verified and validated using randomly generated numerical data and benchmark examples. The effect of dependent product demands and varying interest rate on the total cost function of the proposed model has also been investigated. Sensitivity analysis on the proposed model has been performed. Dynamic programming and simulated annealing optimization algorithms were used in solving the modeled example problems.展开更多
The naïve Bayes classifier is one of the commonly used data mining methods for classification.Despite its simplicity,naïve Bayes is effective and computationally efficient.Although the strong attribute indep...The naïve Bayes classifier is one of the commonly used data mining methods for classification.Despite its simplicity,naïve Bayes is effective and computationally efficient.Although the strong attribute independence assumption in the naïve Bayes classifier makes it a tractable method for learning,this assumption may not hold in real-world applications.Many enhancements to the basic algorithm have been proposed in order to alleviate the violation of attribute independence assumption.While these methods improve the classification performance,they do not necessarily retain the mathematical structure of the naïve Bayes model and some at the expense of computational time.One approach to reduce the naïvetéof the classifier is to incorporate attribute weights in the conditional probability.In this paper,we proposed a method to incorporate attribute weights to naïve Bayes.To evaluate the performance of our method,we used the public benchmark datasets.We compared our method with the standard naïve Bayes and baseline attribute weighting methods.Experimental results show that our method to incorporate attribute weights improves the classification performance compared to both standard naïve Bayes and baseline attribute weighting methods in terms of classification accuracy and F1,especially when the independence assumption is strongly violated,which was validated using the Chi-square test of independence.展开更多
In order to develop an automated segmentation system for Computed Tomography(CT)brain images,a new approach which consists of several unsupervised segmentation techniques was introduced. The system segments the CT bra...In order to develop an automated segmentation system for Computed Tomography(CT)brain images,a new approach which consists of several unsupervised segmentation techniques was introduced. The system segments the CT brain images into three partitions,i.e.,abnor malities,cerebrospinal fluid(CSF) ,and brain matter. Our approach consists of two phase-segmentation methods.In the first phase segmentation,k-means and fuzzy c-means(FCM)methods were implemented to segment and transform the images into the binary images. Based on the connected component in binary images,a decision tree was employed for the annotation of normal or abnormal regions. In the second phase segmentation,the modified FCM with population-diameter independent(PDI)segmentation was applied to segment the images into CSF and brain matter. The experimental results have shown that our proposed systemis feasible and yield satisfactory results.展开更多
Ever since the COVID-19 pandemic started in Wuhan,China,much research work has been focusing on the clinical aspect of SARS-CoV-2.Researchers have been leveraging on various Artificial Intelligence techniques as an al...Ever since the COVID-19 pandemic started in Wuhan,China,much research work has been focusing on the clinical aspect of SARS-CoV-2.Researchers have been leveraging on various Artificial Intelligence techniques as an alternative to medical approach in understanding the virus.Limited studies have,however,reported on COVID-19 transmission pattern analysis,and using geography features for prediction of potential outbreak sites.Predicting the next most probable outbreak site is crucial,particularly for optimizing the planning of medical personnel and supply resources.To tackle the challenge,this work proposed distance-based similarity measures to predict the next most probable outbreak site together with its magnitude,when would the outbreak likely to happen and the duration of the outbreak.The work began with preprocessing of 1365 patient records from six districts in the most populated state named Selangor in Malaysia.The dataset was then aggregated with population density information and human elicited geography features that might promote the transmission of COVID-19.Empirical findings indicated that the proposed unified decision-making approach outperformed individual distance metric in predicting the total cases,next outbreak location,and the time interval between start dates of two similar sites.Such findings provided valuable insights for policymakers to perform Active Case Detection.展开更多
Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple ...Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple Fuzzy ARTMAP with Dynamic Decay Adjustment(PMFAMDDA),for accurate discrimination between normal and faulty operating conditions of a Circulating Water(CW)system in a power generation plant is proposed.The decisions of PMFAMDDA are reached through a probabilistic plurality voting strategy that is in agreement with the Bayesian theorem.The results of the proposed PMFAMDDA model are compared with those from an ensemble of Probabilistic Multiple Fuzzy ARTMAP(PMFAM)classifiers.The outcomes reveal that PMFAMDDA,in general,outperforms PMFAM in discriminating operating conditions of the CW system.展开更多
Analytical solutions of temperature distributions and the Nusselt numbers in forced convection are reported for flow through infinitely long parallel plates, where the upper plate moves in the flow direction with cons...Analytical solutions of temperature distributions and the Nusselt numbers in forced convection are reported for flow through infinitely long parallel plates, where the upper plate moves in the flow direction with constant velocity and the lower plate is kept stationary. The flow is assumed to be laminar, both hydro-dynamically and thermally fully developed, taking into account the effect of viscous dissipation of the flowing fluid. Both the plates being kept at specified and at different constant heat fluxes are considered as thermal boundary conditions. The solutions obtained from energy equation are in terms of Brinkman number, dimensionless velocity and heat flux ratio. These parameters greatly influence and give complete understanding on heat transfer rates that has potentials for designing and analyzing energy equipment and processes.展开更多
In this paper,a unit cell of a single-negative metamaterial structure loaded with a meander line and defected ground structure(DGS)is investigated as the principle radiating element of an antenna.The unit cell antenna...In this paper,a unit cell of a single-negative metamaterial structure loaded with a meander line and defected ground structure(DGS)is investigated as the principle radiating element of an antenna.The unit cell antenna causes even or odd mode resonances similar to the unit cell structure depending on the orientation of the microstrip feed used to excite the unit cell.However,the orientation which gives low-frequency resonance is considered here.The unit cell antenna is then loaded with a meander line which is parallel to the split bearing side and connects the other two sides orthogonal to the split bearing side.This modified structure excites another mode of resonance at high frequency when a meander line defect is loaded on the metallic ground plane.Specific parameters of the meander line structure,the DGS shape,and the unit cell are optimized to place these two resonances at different frequencies with proper frequency intervals to enhance the bandwidth.Finally,the feed is placed in an offset position for better impedance matching without affecting the bandwidth The compact dimension of the antenna is 0.25λL×0.23λL×0.02λL,whereλL is the free space wavelength with respect to the center frequency of the impedance bandwidth.The proposed antenna is fabricated and measured.Experimental results reveal that the modified design gives monopole like radiation patterns which achieves a fractional operating bandwidth of 26.6%,from 3.26 to 4.26 GHz for|S11|<−10 dB and a pick gain of 1.26 dBi is realized.In addition,the simulated and measured crosspolarization levels are both less than−15 dB in the horizontal plane.展开更多
The general characteristic equation is derived for the helically cladded step-index optical fiber. The dispersion curves are drawn for the different pitch angles Ψ and mode order ν = 1. The effect of helix pitch ang...The general characteristic equation is derived for the helically cladded step-index optical fiber. The dispersion curves are drawn for the different pitch angles Ψ and mode order ν = 1. The effect of helix pitch angle on the dispersion characteristics and also on the modal cut-off condition is examined. Except for the lowest order mode, all the modes appear in pairs. The lowest order mode displays the negative dispersion for the some value of normalized frequency V and depends on the helix pitch angle Ψ.展开更多
文摘Deep learning has been a catalyst for a transformative revo-lution in machine learning and computer vision in the past decade.Within these research domains,methods grounded in deep learning have exhibited exceptional performance across a spectrum of tasks.The success of deep learning methods can be attributed to their capability to derive potent representations from data,integral for a myriad of downstream applications.These representations encapsulate the intrinsic structure,fea-tures,or latent variables characterising the underlying statistics of visual data.Despite these achievements,the challenge per-sists in effectively conducting representation learning of visual data with deep models,particularly when confronted with vast and noisy datasets.This special issue is a dedicated platform for researchers worldwide to disseminate their latest,high-quality articles,aiming to enhance readers'comprehension of the principles,limitations,and diverse applications of repre-sentation learning in computer vision.
文摘The viability of the indium phosphide(InP)Gunn diode as a source for low-THz band applications is analyzed based on a notch-δ-doped structure using the Monte Carlo modeling.The presence of theδ-doped layer could enhance the current harmonic amplitude(A0)and the fundamental operating frequency(f0)of the InP Gunn diode beyond 300 GHz as compared with the conventional notch-doped structure for a 600-nm length device.With its superior electron transport properties,the notch-δ-doped InP Gunn diodes outperform the corresponding gallium arsenide(GaAs)diodes with up to 1.35 times higher in f0 and 2.4 times larger in A0 under DC biases.An optimized InP notch-δ-doped structure is estimated to be capable of generating 0.32-W radio-frequency(RF)power at 361 GHz.The Monte Carlo simulations predict a reduction of 44%in RF power,when the device temperature is increased from 300 K to 500 K;however,its operating frequency lies at 280 GHz which is within the low-THz band.This shows that the notch-δ-doped InP Gunn diode is a highly promising signal source for low-THz sensors,which are in a high demand in the autonomous vehicle industry.
基金This research is supported by the Malaysia Ministry of Higher Education’s Fundamental Research Grant Scheme(FRGS)[FRGS/1/2019/SS09/MMU/02/3]MMUE/190073 led by the second author.
文摘The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease(COVID-19)pandemic,globalization,technology advancement in Industry 4.0,and other contributing factors.The pervasiveness of the issue poses a huge challenge to improving the occupational safety and health(OSH)of workers in various industries,especially in the digital industry.The emergence of the innovative industry is evident mainly due to the rapid development of Industry 4.0 and the rele-vant demands of multiple businesses in the digital transformation.Nonetheless,limited studies and academic dis-cussions were conducted on the OSH topic of digital employees.Hence,the current study serves tofill the existing gap and provide academic contributions by scrutinising the perceptions of digital workers regarding their work-place well-being,mental health literacy,and the impression of employing e-mental health.The objectives of this study are:1)To examine the mental health literacy and workplace wellness of digital workers,2)to explore the e-mental health usage intention and actual e-mental health utilization,and 3)to identify digital workers’feedback on e-mental health.In the current context,e-mental health focuses on three dimensions,namely,1)“health in our hand(HIOH)”,2)“interacting for health(IFH)”,and 3)“data enabling health(DEH)”.The present study employed an online cross-sectional survey and received 326 digital workers’completed responses.Variables,such as“mental health literacy(MHL)”,“workplace wellness(WW)”,and e-mental health intention and usage were explicated by analysing the data through descriptive statistics.The study results indicated a moderate to a high level of the MHL and the WW.More than half of the workers possessed a high intention level to employ e-mental health,with the HIOH dimension being the most prevalent domain.Nevertheless,the actual e-mental health usage was very low,owing to the online resources being a new concept amongst digital employees.Numerous confounding factors also existed in affecting the low usage,such as privacy concerns,data security levels,and health verification issues.In addition,the mental health issue has not been openly and widely discussed in Malay-sian workplaces due to stigmatisation.As such,the currentfindings could provide additional insights into the OSH literature;it could serve as a guideline for the OSH decision-makers,employers,and eHealth developers when establishing a feasible framework for the practical adoption of e-mental health services by digital workers.
文摘The existence of several non-symmetric balanced incomplete block designs (BIBDs) is still unknown. This is because the non-existence property for non-symmetric BIBDs is still not known and also the existing construction methods have not been able to construct these designs despite their design parameters satisfying the necessary conditions for the existence of BIBD. The study aimed to bridge this gap by introducing a new class of non-symmetric BIBDs. The proposed class of BIBDs is constructed through the combination of disjoint symmetric BIBDs. The study was able to determine that the total number of disjoint symmetric BIBDs (n) with parameters (v = b, r = k, λ) that can be obtained from an un-reduced BIBD with parameters (v, k) is given by n = r - λ. When the n symmetric disjoint BIBDs are combined, then a new class of symmetric BIBDs is formed with parameters v<sup>*</sup><sup> </sup>= v, b<sup>*</sup><sup> </sup>= nb, r<sup>*</sup><sup> </sup>= nr, k<sup>*</sup><sup> </sup>= k, λ<sup>*</sup><sup> </sup>= λ, where 2≤ n ≤ r - λ. The study established that the non-existence property of this class of BIBD was that when is not a perfect square then v should be even and when v<sup>*</sup><sup> </sup>is odd then the equation should not have a solution in integers x, y, z which are not all simultaneously zero. In conclusion, the study showed that this construction technique can be used to construct some non-symmetric BIBDs. However, one must first construct the disjoint symmetric BIBDs before one can construct the non-symmetric BIBD. Thus, the disjoint symmetric BIBDs must exist first before the non-symmetric BIBDs exist.
文摘Concrete is the most widely used construction material in the world. The situation in the country is not an exception as most of the infrastructures in Kenya such as buildings, bridges, concrete drainage among others, are constructed using concrete. Sadly, the failure of buildings and other concrete structures is very common in Kenya. Blended Portland cement type 32.5 N/mm<sup>2</sup> is the most widely used concrete binder material and is found in all parts of the country. Despite blended cement CEM 32.5 being the most commonly used cement type in construction industry in Kenya and most developing countries as a result of its low price and availability locally, its strength gain has been proven to be lower compared to when other types of cement are used due to quantity of pozzolanic material added to the blend. This paper outlines findings of an experimental investigation on the use of cypress tree extract as an accelerator to enhance rate of gain of strength on Kenyan blended cements. Six different blended cement brands locally available were used during the study. Cement chemical analysis was done using X-ray diffraction method while for the cypress extract, Atomic Absorption Spectrometer machine was used. Physical and mechanical properties were checked based on the British standards. The generation of the concrete mix design was done using the British DOE method and concrete was tested for the compressive strength at 7, 14, 21, 28, 56 and 90 days. It was observed that 15% dosage of the extract expressed as a mass percentage of the cement content gives the most improved compressive strength of concrete, 10.4% at 7 days and 9.5% at 28 days hence the optimum. It was further noted that when Cypress tree extract is used as an accelerator in the mix, the blended cement concrete achieves the design strength at 27 days saving 10 days of the project duration compared to when no accelerator is used while the ultimate strength is achieved at 67 days. The study therefore recommends the use of the cypress tree bark extract at a dosage of 15%, by mass, of the cement content as an accelerator when the structure is to be loaded at 28 days and waiting up to 39 days before loading the structure if no accelerator is used for blended cement concrete.
基金Supported by Multimedia University(Malaysia),project SAP ID(MMUI/160092)
文摘本文提出了光码多分址(CDMA)和光密集波分复用(DWDM)的混合系统,全面研究了四波混频(FWM)的影响。在这个系统中,主要存在两个四波混频问题:包括多址干扰(MAI)和码间干扰(ISI)的帧间四波混频和信道内四波混频。结果表明,综合考虑信道间和信道内四波混频的影响,最佳发射功率可选为18 d Bm。当发射功率大于18 d Bm时,混合系统的误码率(BER)将增加。基于此,本文提出了一种电光相位调制器(EOPM)模块,将其放置在波分复用器之后,通过抑制信道内四波混频的影响,同时调制所有波长信号的相位,从而增加混合系统的非线性容限,这极大地改善了基于OOK传输的光学CDMA-DWDM混合系统的性能。此外,由于多对角线(MD)结构具有零互相关特性,通过使用多对角线识别序列码可以减少多址干扰的影响。结果还表明,CDMA技术与色散相结合有助于降低信道间四波混频的影响。此外,识别序列码间隔在减轻码间干扰中起着至关重要的作用,如结果所示,当识别序列码间隔压缩至比特持续时间的25%时,可以避免码间干扰,此时所提出的混合系统的性能最佳。
文摘The principal component analysis (PCA) is a kind of algorithms in biometrics. It is a statistics technical and used orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables. PCA also is a tool to reduce multidimensional data to lower dimensions while retaining most of the information. It covers standard deviation, covariance, and eigenvectors. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.
基金Supported by the Ministry of Higher Education of Malaysia through the Foundation Research(Grant Scheme no.FRGS/1/2012/TK01/MMU/02/2)
文摘Design of a robust production facility layout with minimum handling cost(MHC) presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly change in each planning period. The objective of the design is to find the robust facility layout with minimum total material handling cost over the entire multiperiod planning horizon. This paper proposes a new mathematical model for designing robust machine layout in the stochastic dynamic environment of manufacturing systems using quadratic assignment problem(QAP) formulation. In this investigation, product demands are assumed to be normally distributed random variables with known expected value, variance, and covariance that randomly change from period to period. The proposed model was verified and validated using randomly generated numerical data and benchmark examples. The effect of dependent product demands and varying interest rate on the total cost function of the proposed model has also been investigated. Sensitivity analysis on the proposed model has been performed. Dynamic programming and simulated annealing optimization algorithms were used in solving the modeled example problems.
文摘The naïve Bayes classifier is one of the commonly used data mining methods for classification.Despite its simplicity,naïve Bayes is effective and computationally efficient.Although the strong attribute independence assumption in the naïve Bayes classifier makes it a tractable method for learning,this assumption may not hold in real-world applications.Many enhancements to the basic algorithm have been proposed in order to alleviate the violation of attribute independence assumption.While these methods improve the classification performance,they do not necessarily retain the mathematical structure of the naïve Bayes model and some at the expense of computational time.One approach to reduce the naïvetéof the classifier is to incorporate attribute weights in the conditional probability.In this paper,we proposed a method to incorporate attribute weights to naïve Bayes.To evaluate the performance of our method,we used the public benchmark datasets.We compared our method with the standard naïve Bayes and baseline attribute weighting methods.Experimental results show that our method to incorporate attribute weights improves the classification performance compared to both standard naïve Bayes and baseline attribute weighting methods in terms of classification accuracy and F1,especially when the independence assumption is strongly violated,which was validated using the Chi-square test of independence.
文摘In order to develop an automated segmentation system for Computed Tomography(CT)brain images,a new approach which consists of several unsupervised segmentation techniques was introduced. The system segments the CT brain images into three partitions,i.e.,abnor malities,cerebrospinal fluid(CSF) ,and brain matter. Our approach consists of two phase-segmentation methods.In the first phase segmentation,k-means and fuzzy c-means(FCM)methods were implemented to segment and transform the images into the binary images. Based on the connected component in binary images,a decision tree was employed for the annotation of normal or abnormal regions. In the second phase segmentation,the modified FCM with population-diameter independent(PDI)segmentation was applied to segment the images into CSF and brain matter. The experimental results have shown that our proposed systemis feasible and yield satisfactory results.
文摘Ever since the COVID-19 pandemic started in Wuhan,China,much research work has been focusing on the clinical aspect of SARS-CoV-2.Researchers have been leveraging on various Artificial Intelligence techniques as an alternative to medical approach in understanding the virus.Limited studies have,however,reported on COVID-19 transmission pattern analysis,and using geography features for prediction of potential outbreak sites.Predicting the next most probable outbreak site is crucial,particularly for optimizing the planning of medical personnel and supply resources.To tackle the challenge,this work proposed distance-based similarity measures to predict the next most probable outbreak site together with its magnitude,when would the outbreak likely to happen and the duration of the outbreak.The work began with preprocessing of 1365 patient records from six districts in the most populated state named Selangor in Malaysia.The dataset was then aggregated with population density information and human elicited geography features that might promote the transmission of COVID-19.Empirical findings indicated that the proposed unified decision-making approach outperformed individual distance metric in predicting the total cases,next outbreak location,and the time interval between start dates of two similar sites.Such findings provided valuable insights for policymakers to perform Active Case Detection.
基金supported by the Fundamental Research Grant Scheme of Ministry of Higher Education,Malaysia(No.6711195)Multi media University and University of Science Malaysia
文摘Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple Fuzzy ARTMAP with Dynamic Decay Adjustment(PMFAMDDA),for accurate discrimination between normal and faulty operating conditions of a Circulating Water(CW)system in a power generation plant is proposed.The decisions of PMFAMDDA are reached through a probabilistic plurality voting strategy that is in agreement with the Bayesian theorem.The results of the proposed PMFAMDDA model are compared with those from an ensemble of Probabilistic Multiple Fuzzy ARTMAP(PMFAM)classifiers.The outcomes reveal that PMFAMDDA,in general,outperforms PMFAM in discriminating operating conditions of the CW system.
文摘Analytical solutions of temperature distributions and the Nusselt numbers in forced convection are reported for flow through infinitely long parallel plates, where the upper plate moves in the flow direction with constant velocity and the lower plate is kept stationary. The flow is assumed to be laminar, both hydro-dynamically and thermally fully developed, taking into account the effect of viscous dissipation of the flowing fluid. Both the plates being kept at specified and at different constant heat fluxes are considered as thermal boundary conditions. The solutions obtained from energy equation are in terms of Brinkman number, dimensionless velocity and heat flux ratio. These parameters greatly influence and give complete understanding on heat transfer rates that has potentials for designing and analyzing energy equipment and processes.
文摘In this paper,a unit cell of a single-negative metamaterial structure loaded with a meander line and defected ground structure(DGS)is investigated as the principle radiating element of an antenna.The unit cell antenna causes even or odd mode resonances similar to the unit cell structure depending on the orientation of the microstrip feed used to excite the unit cell.However,the orientation which gives low-frequency resonance is considered here.The unit cell antenna is then loaded with a meander line which is parallel to the split bearing side and connects the other two sides orthogonal to the split bearing side.This modified structure excites another mode of resonance at high frequency when a meander line defect is loaded on the metallic ground plane.Specific parameters of the meander line structure,the DGS shape,and the unit cell are optimized to place these two resonances at different frequencies with proper frequency intervals to enhance the bandwidth.Finally,the feed is placed in an offset position for better impedance matching without affecting the bandwidth The compact dimension of the antenna is 0.25λL×0.23λL×0.02λL,whereλL is the free space wavelength with respect to the center frequency of the impedance bandwidth.The proposed antenna is fabricated and measured.Experimental results reveal that the modified design gives monopole like radiation patterns which achieves a fractional operating bandwidth of 26.6%,from 3.26 to 4.26 GHz for|S11|<−10 dB and a pick gain of 1.26 dBi is realized.In addition,the simulated and measured crosspolarization levels are both less than−15 dB in the horizontal plane.
文摘The general characteristic equation is derived for the helically cladded step-index optical fiber. The dispersion curves are drawn for the different pitch angles Ψ and mode order ν = 1. The effect of helix pitch angle on the dispersion characteristics and also on the modal cut-off condition is examined. Except for the lowest order mode, all the modes appear in pairs. The lowest order mode displays the negative dispersion for the some value of normalized frequency V and depends on the helix pitch angle Ψ.
