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| 1 | A method for release and multiple strand amplification of small quantities of DNA from endospores of the fastidious bacterium Pasteuria penetrans显示文摘 | T.H.Mauchline S.Mohan K.G.Davies J.E.Schaff C.H.Opperman B.R.Kerry P.R.Hirsch | 2010 | Letters in Applied Microbiology2010，，5： | 2 |
| 2 | Effect of Substrate and Annealing Temperatures on Mechanical Properties of Ti-rich NiTi Films显示文摘The effect of substrate and annealing temperatures on mechanical properties of Ti-rich NiTi films deposited on Si (100) substrates by DC magnetron sputtering was studied by nanoindentation.NiTi films were deposited at two substrate temperatures viz.300 and 400 ℃.NiTi films deposited at 300 ℃ were annealed for 4 h at four different temperatures,i.e.300,400,500 and 600 C whereas films deposited at 400 ℃ were annealed for 4 h at three different temperatures,i.e.400,500 and 600 ℃.The elastic modulus and hardness of the films were found to be the same in the as-deposited as well as annealed conditions for both substrate temperatures.For a given substrate temperature,the hardness and elastic modulus were found to remain unchanged as long as the films were amorphous.However,both elastic modulus and hardness showed an increase with increasing annealing temperature as the films become crystalline.The results were explained on the basis of the change in microstructure of the film with change in annealing temperature. | A.Kumar S.K.Sharma S.Bysakh S.V.Kamat S.Mohan | 2010 | Journal of Materials Science & Technology2010，26，11： | 2 |
| 3 | Skin Lesion Classification System Using Shearlets显示文摘The main cause of skin cancer is the ultraviolet radiation of the sun.It spreads quickly to other body parts.Thus,early diagnosis is required to decrease the mortality rate due to skin cancer.In this study,an automatic system for Skin Lesion Classification(SLC)using Non-Subsampled Shearlet Transform(NSST)based energy features and Support Vector Machine(SVM)classifier is proposed.Atfirst,the NSST is used for the decomposition of input skin lesion images with different directions like 2,4,8 and 16.From the NSST’s sub-bands,energy fea-tures are extracted and stored in the feature database for training.SVM classifier is used for the classification of skin lesion images.The dermoscopic skin images are obtained from PH^(2) database which comprises of 200 dermoscopic color images with melanocytic lesions.The performances of the SLC system are evaluated using the confusion matrix and Receiver Operating Characteristic(ROC)curves.The SLC system achieves 96%classification accuracy using NSST’s energy fea-tures obtained from 3^(rd) level with 8-directions. | S.Mohan Kumar T.Kumanan | 2023 | Computer Systems Science & Engineering2023，44，1： | 0 |
| 4 | Optimal and Effective Resource Management in Edge Computing显示文摘Edge computing is a cloud computing extension where physical compu-ters are installed closer to the device to minimize latency.The task of edge data cen-ters is to include a growing abundance of applications with a small capability in comparison to conventional data centers.Under this framework,Federated Learning was suggested to offer distributed data training strategies by the coordination of many mobile devices for the training of a popular Artificial Intelligence(AI)model without actually revealing the underlying data,which is significantly enhanced in terms of privacy.Federated learning(FL)is a recently developed decentralized profound learning methodology,where customers train their localized neural network models independently using private data,and then combine a global model on the core server together.The models on the edge server use very little time since the edge server is highly calculated.But the amount of time it takes to download data from smartphone users on the edge server has a significant impact on the time it takes to complete a single cycle of FL operations.A machine learning strategic planning system that uses FL in conjunction to minimise model training time and total time utilisation,while recognising mobile appliance energy restrictions,is the focus of this study.To further speed up integration and reduce the amount of data,it implements an optimization agent for the establishment of optimal aggregation policy and asylum architecture with several employees’shared learners.The main solutions and lessons learnt along with the prospects are discussed.Experiments show that our method is superior in terms of the effective and elastic use of resources. | Darpan Majumder S.Mohan Kumar | 2023 | Computer Systems Science & Engineering2023，44，2： | 0 |
| 5 | 生物工程在大麦育种上的应用显示文摘引言栽培大麦是人类所共知的最古老谷类之一,其产量居世界谷类作物产量的第四位。目前世界上仍有10亿多人口以大麦为主食。近年来以大麦为材料的研究正在不断深入,将生物工程技术引入大麦育种的研究也日益受到重视。 | S.Mohan Jain 邵宏波 初立业 | 1990 | 世界科学1990，12，4： | 0 |
| 6 | Soft Computing Based Discriminator Model for Glaucoma Diagnosis显示文摘In this study, a Discriminator Model for Glaucoma Diagnosis (DMGD)using soft computing techniques is presented. As the biomedical images such asfundus images are often acquired in high resolution, the Region of Interest (ROI)for glaucoma diagnosis must be selected at first to reduce the complexity of anysystem. The DMGD system uses a series of pre-processing;initial cropping by thegreen channel’s intensity, Spatially Weighted Fuzzy C Means (SWFCM), bloodvessel detection and removal by Gaussian Derivative Filters (GDF) and inpaintingalgorithms. Once the ROI has been selected, the numerical features such as colour, spatial domain features from Local Binary Pattern (LBP) and frequencydomain features from LAWS are generated from the corresponding ROI forfurther classification using kernel based Support Vector Machine (SVM). TheDMGD system performances are validated using four fundus image databases;ORIGA, RIM-ONE, DRISHTI-GS1, and HRF with four different kernels;LinearKernel (LK), Polynomial Kernel (PK), Radial Basis Function (RBFK) kernel,Quadratic Kernel (QK) based SVM classifiers. Results show that the DMGD system classifies the fundus images accurately using the multiple features and kernelbased classifies from the properly segmented ROI. | Anisha Rebinth S.Mohan Kumar | 2022 | Computer Systems Science & Engineering2022，42，9： | 0 |
| 7 | Natural Hazard-Induced Disasters and Production Efficiency:Moving Closer to or Further from the Frontier?显示文摘Production efficiency is a key determinant of economic growth and demonstrates how a country uses its resources by relating the quantity of its inputs to its outputs. When a natural hazard-induced disaster strikes, it has a devastating impact on capital and labor, but at the same time provides an opportunity to upgrade capital and increase labor demand and training opportunities, thereby potentially boosting production efficiency. We studied the impact of natural hazard-induced disasters on countries’ production efficiency, using the case study of hurricanes in the Caribbean. To this end we built a country-specific,time-varying data set of hurricane damage and national output and input indicators for 17 Caribbean countries for the period 1940–2014. Our results, using a stochastic frontier approach, show that there is a short-lived production efficiency boost, and that this can be large for very damaging storms. | Preeya S.Mohan Nekeisha Spencer Eric Strobl | 2019 | International Journal of Disaster Risk Science2019，10，2： | 0 |
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