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Wireless sensor Network-based Detection of Poisonous Gases Using Principal Component Analysis

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Computer systems science & Engineering 2023年第1期44卷 249-264页

作者： N.Dharini Jeevaa Katiravan s.M.Udhaya sankar Easwari Engineering College Chennai600089India Velammal Engineering College Chennai600066India Velammal Institute of Technology Chennai601204India

This work utilizes a statistical approach of Principal Component Ana-lysis(PCA)towards the detection of Methane(CH_(4))-Carbon Monoxide(CO)Poi-soning occurring in coal mines,forestfires,drainage systems *** the CH_(4) and CO emissions are very high in closed buildings or confined spaces during oxi-dation *** methane and carbon monoxide are highly toxic,colorless and odorless *** of the gases have their own toxic levels to be *** during their combined presence,the toxicity of the either one goes unidentified may be due to their low levels which may lead to an *** using PCA,the correlation of CO and CH_(4) data is carried out and by identifying the areas of high correlation(along the principal component axis)the explosion suppression action can be triggered earlier thus avoiding adverse effects of massive ***-less sensor Network is deployed and simulations are carried with heterogeneous sensors(Carbon Monoxide and Methane sensors)in Ns-2 Mannasim *** rise in the value of CO even when CH_(4) is below the toxic level may become hazardous to the people *** our proposed methodology will detect the combined presence of both the gases(CH_(4) and CO)and provide an early warning in order to avoid any human losses or toxic effects.

关键词： Wireless sensor network principal component analysis carbon monoxide-methane poisoning confined spaces

Tuna classification using super learner ensemble of region-based CNN-grouped 2D-LBP models

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Information Processing in Agriculture 2022年第1期9卷 68-79页

作者： Jisha Anu Jose C.sathish Kumar s.sureshkumar Rajiv Gandhi Institute of Technology KottayamIndia Government Engineering College IdukkiIndia Kerala University of Fisheries and Ocean studies KochiIndia

Tuna is superior among the marine fishes that are exported in the forms of raw fish and processed *** of Tuna into their species is done in industries manually,and the process is *** work proposes an automated system for classifying Tuna spe-cies based on their *** ensemble of region-based deep neural networks is used.A sub region contrast stretching operation is applied to enhance the *** fish image is then divided into three regions and is augmented before giving as input to pre-trained convolutional neural networks(CNN).After fine-tuning the models,the output from the last convolutional layer is given to a grouped 2D-local binary pattern descriptor(G2DLBP).statistical features from the descriptor are applied to different classifiers,and the best clas-sifier for each image region model is *** ensemble methods are subse-quently used to combine the three CNN-G2DLBP *** the ensemble techniques,super learner ensemble method with random forest(RF)classifier using 5-fold cross-validation shows the highest classification accuracy of 97.32%.The perfor-mance of different ensemble methods is analyzed in terms of accuracy,precision,recall,and *** proposed system shows an accuracy of 93.91% when evaluated with an independent test *** ensemble of region-based CNN with textural features from G2DLBP is applied for the first time for fish classification.

关键词： Tuna classification Convolutional neural network Grouped 2D-local binary pattern super learner ensemble

Biological performance,water absorption,and swelling of wood treated with nano-particles combined with the application of Paraloid B72~

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Journal of Forestry Research 2017年第2期28卷 381-394页

作者： Damla Muhcu Evren Terzi s.Nami Kartal Tsuyoshi Yoshimura Department of Forest Biology and Wood Protection Technology Faculty of ForestryIstanbul University Laboratory of Innovative Humano-habitability Research Institute for Sustainable Humanosphere (RISH)Kyoto University

We evaluated fungal decay and mold resistance,leaching, and water absorption of nano-compounds and Paraloid B72-（PB72） in treated wood specimens to develop new methods of consolidation by combining nanoparticles and consolidants. scots pine wood specimens were treated with dispersions of nano-Cu O, nano-Zn O,nano-B2O3, nano-Ti O2, and nano-Ce O2. PB72 treatments of nano-particle-treated wood specimens were then carried out by either vacuum or immersion for 24 h. Previously,decayed wood specimens were also consolidated with the nano-compounds and PB72. PB72 treatments reduced element release from treated wood specimens. Nearly all nano-compounds ？ PB72 treatments increased the biological performance of treated wood specimens against decay fungi tested. PB72-only treated wood specimens had the highest weight losses in decay tests. No improvements were obtained in mold resistance tests when the nanocompounds and PB72 were combined. In nano-compoundonly treatments, unleached specimens showed slightly lower water absorption values compared to untreated control specimens. Incorporation of PB72 into nano-compound-treated wood specimens resulted in considerably lower water absorption and volumetric swell. In previously decayed specimens treated with the nano-compounds and PB72 solution, water absorption after 2-h immersion declined compared to control specimens.

关键词： leaching declined untreated retention fungi versicolor fungal fungus leached decay

InGaN/GaN laser diode characterization and quantum well number effect

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Chinese Optics Letters 2009年第3期7卷 226-230页

作者： s.M.Thahab H.Abu Hassan Z.Hassan Nano-Optoelectronics Research and Technology Laboratory School of PhysicsUniversiti Sains Malaysia

The effect of quantum well number on the quantum efficiency and temperature characteristics of In- GaN/GaN laser diodes （LDs） is determined and investigated. The 3-nm-thick In0.13Ca0.87N wells and two 6-am-thick GaN barriers are selected as an active region for Fabry-Perot （FP） cavity waveguide edge emitting LD. The internal quantum efficiency and internal optical loss coefficient are extracted through the simulation software for single, double, and triple InGaN/GaN quantum wells. The effects of device temperature on the laser threshold current, external differential quantum efficiency （DQE）, and output wavelength are also investigated. The external quantum efficiency and characteristic temperature are improved significantly when the quantum well number is two. It is indicated that the laser structures with many quantum wells will suffer from the inhomogeneity of the carrier density within the quantum well itself which affects the LD performance.

关键词： Computer software Efficiency Fabry Perot interferometers Quantum well lasers semiconductor lasers semiconductor quantum wells

Analysis of lattices with non-linear interphases

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Acta Mechanica sinica 2006年第4期22卷 323-330页

作者： s. Haq A. B. Movchan G. J. Rodin Faculty of Engineering sciences GIK Institute Topi 23640 NWFP Pakistan Department of Mathematical sciences University of Liverpool Liverpool L69 3BX UK Institute for Computational Engineering and sciences The University of Texas at Austin Austin TX 78712 USA

Anti-plane deformation of square lattices containing interphases is analyzed. It is assumed that lattices are linear elastic but not necessarily isotropic, whereas interphases exhibit non-linear elastic behavior. It is demonstrated that such problems can be treated effectively using Green＇s functions, which allow to eliminate the degrees of freedom outside of the interphase. Illustrative numerical examples focus on the determination of applied stresses leading to lattice instability.

关键词： Interphases in lattices stability Green's functions Evolution algroithm

Localized CO_2 laser bonding process for MEMs packaging

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中国有色金属学会会刊：英文版 2006年第B2期16卷 577-581页

作者： sUN Li A. P. MALsHE s. CUNNINGHAM A. MORRIs Department of Mechanical Engineering University of Arkansas Fayetteville AR 72701 USA wispry Inc. Irvine CA 92618 USA wispry Inc. Cary NC 27513 USA

The packaging poses a critical challenge for commercialization of MEMs products. Major problems with the packaging process include degraded reliability caused by the excess stress due to thermal mismatch and altered performance of the MEMs device after packaging caused by thermal exposure. The localized laser bonding technique for ceramic MEMs packaging to address above-mentioned challenges was investigated. A continuous wave CO2 laser was used to locally heat sealing material for ceramic MEMs package lid to substrate bonding. To determine the laser power density and scanning speed, finite element analysis thermal models were constructed to simulate the localized laser bonding process. Further, the effect of external pressure at sealing ring on the bonding formation was studied. Pull testing results show that the scanning speed and external pressure have significant influence on the pull strength at the bonding interface. Cross-sectional microscopy of the bonding interface indicates that the packages bonded with relatively low scanning speed and external pressure conditions have higher bonding quality. This research demonstrates the potential of localized laser bonding process for ceramic MEMs packaging.

关键词：微电子机械系统 MEMs 封装局部激光焊接过程有限元分析

Collaborative learning via social computing

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Frontiers of Information Technology & Electronic Engineering 2019年第2期20卷 265-282页

作者： Ricardo s.ALONsO Javier PRIETO óscar GARCíA Juan M.CORCHADO BIsITE Research Group University of Salamanca

Educational innovation is a field that has been greatly enriched by using technology in its processes, resulting in a learning model where information comes from numerous sources and collaboration takes place among multiple students. One attractive challenge within educational innovation is the design of collaborative learning activities from the social computing point of view, where collaboration is not limited to student-to-student relationships, but includes student-to-machine interactions. At the same time, there is a great lack of tools that give support to the whole learning process and are not restricted to specific aspects of the educational task. In this paper, we present and evaluate context-aware framework for collaborative learning applications(CAFCLA) as a solution to these problems. CAFCLA is a flexible framework that covers the entire process of developing collaborative learning activities, taking advantage of contextual information and social interactions. Its application in the experimental case study of a collaborative WebQuest within a museum has shown that, among other benefits, the use of social computing improves the learning process, fosters collaboration, enhances relationships, and increases engagement.

关键词： Context-awareness Collaborative learning social computing Virtual organizations Wireless sensor networks Real time location system

Predicting the effect of climate change on a range-restricted lizard in southeastern Australia

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Current Zoology 2018年第2期64卷 165-171页

作者： Bezeng s. BEZENG solomon G. TEsFAMICHAEL Buddhi DAYANANDA African Centre for DNA Barcoding Department of Botany and Plant Biotechnology University of Johannesburg P0Box 524 APK Campus 2006 Johannesburg South Africa Department of Geography Environmental Managementand Energy Studies University of Johannesburg P0 Box 524 APK Campus 2006 Johannesburg South Africa school of Life sciences University of Technology Sydney Broadway NSW 2007 Australia

Climate change is ranked as one of the most severe threats to global biodiversity. This global phenomenon is particularly true for reptiles whose biology and ecology are closely linked to climate. In this study, we used over 1,300 independent occurrence points and different climate change emission scenarios to evaluate the potential risk of changing climatic conditions on the current and future potential distribution of a rock-dwelling lizard; the velvet gecko. Furthermore, we investigated if the current extent of protected area networks in Australia captures the full range distribution of this species currently and in the future. Our results show that climate change projections for the year 2075 have the potential to alter the distribution of the velvet gecko in southeastern Australia. specifically, climate change may favor the range expansion of this species to encompass more suitable habitats. The trend of range expansion was qualitatively similar across the different cli- mate change scenarios used. Additionally, we observed that the current network of protected areas in southeast Australia does not fully account for the full range distribution of this species currently and in the future. Ongoing climate change may profoundly affect the potential range distribution of the velvet gecko population. Therefore, the restricted habitat of the velvet geckos should be the focus of intensive pre-emptive management efforts. This management prioritization should be extended to encompass the increases in suitable habitats observed in this study in order to maximize the microhabitats available for the survival of this species.

关键词： bioclirnatic variables climate change environmental niche models range expansion reptiles.

An Efficient stacked-LsTM Based User Clustering for 5G NOMA systems

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Computers, Materials & Continua 2022年第9期72卷 6119-6140页

作者： s.Prabha Kumaresan Chee Keong Tan Yin Hoe Ng Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia school of Information Technology Monash UniversitySubang Jaya47500Malaysia

Non-orthogonal multiple access(NOMA)has been a key enabling technology for the fifth generation(5G)cellular *** on the NOMA principle,a traditional neural network has been implemented for user clustering(UC)to maximize the NOMA system’s throughput performance by considering that each sample is independent of the prior and the subsequent ***,the prediction of UC for the future ones is based on the current clustering information,which is never used again due to the lack of memory of the ***,to relate the input features of NOMA users and capture the dependency in the clustering information,time-series methods can assist us in gaining a helpful insight into the *** its mathematical complexity,the essence of time series comes down to examining past behavior and extending that information into the ***,in this paper,we propose a novel and effective stacked long short term memory(s-LsTM)to predict the UC formation of NOMA users to enhance the throughput performance of the 5G-based NOMA *** the proposed strategy,the s-LsTM is modelled to handle the time-series input data to improve the predicting accuracy of UC of the NOMA users by implementing multiple LsTM layers with hidden *** implemented LsTM layers have feedback connections that help to capture the dependency in the clustering information as it propagates between the ***,we develop,train,validate and test the proposed model to predict the UC formation for the futures ones by capturing the dependency in the clustering information based on the time-series *** results demonstrate that the proposed scheme effectively predicts UC and thereby attaining near-optimal throughput performance of 98.94%compared to the exhaustive search method.

关键词： Non-orthogonal multiple access(NOMA) deep neural network(DNN) long short term memory(LsTM) temporal channel user clustering