Present experiments were conducted to determine the possibility of artificial culture with various sawdust of P. gilvus. The pH value was 6.0 of oak sawdust, 6.5 of mulberry sawdust, 6.6 of elm sawdust, 6.3 of acacia sawdust and 6.1 of apple tree sawdust. Mycelial density on elm sawdust and acacia sawdust were lower than those of oak sawdust, and apple sawdust. Weight of fresh fruiting body sho...

This paper discusses the problems of developing versatile adaptive and intelligent learning systems that can be used in the context of practical Web-based education. We argue that versatility is an important feature of successful Web-based education systems. We introduce ELM-ART, an intelligent interactive educational system to support learning programming in LISP. ELM-ART provides all learning...

Important brain parts like hippocampal usually being manually segmented by doctors. But with the introduction of hybrid between machine learning along with neuroimaging technique, it has proved to shows some promising results regarding on segmenting subcortical structures. However, it is known that Extreme Learning Machine (ELM) is to be superior machine learning technique. This study will inve...

Our paper emphasizes the relevance of Extreme Learning Machine (ELM) in Bioinformatics applications by addressing the problem of predicting the disulfide connectivity from protein sequences. We test different activation functions of the hidden neurons and we show that for the task at hand the Radial Basis Functions are the best performing. We also show that the ELM approach performs better than...

Dutch elm disease is caused by the fungal pathogen Ophiostoma novo-ulmi which is transmitted by the native elm bark beetle, Hylurgopinus rufipes. We have found that four semiochemicals (the monoterpene (-)-beta-pinene and the sesquiterpenes (-)-alpha-cubebene, (+)-spiroaxa-5,7-diene and (+)-delta-cadinene) from diseased American elms, Ulmus americana, synergistically attract H. rufipes, and tha...

Abstract Backbreak (BB) is one of the serious adverse blasting consequences in open-pit mines, because it frequently reduces economic benefits and seriously affects safety mines. Therefore, rapid accurate prediction BB great significance to mine design other production activities. For this purpose, six different swarm intelligence optimization (SIO) algorithms were proposed optimize extreme lea...

Extreme learning machine (ELM) as a new learning algorithm has been proposed for single-hidden layer feed-forward neural networks, ELM can overcome many drawbacks in the traditional gradient-based learning algorithm such as local minimal, improper learning rate, and low learning speed by randomly selecting input weights and hidden layer bias. However, ELM suffers from instability and over-fitti...

Type-I edge-localized modes (ELMs) have been mitigated at the JET tokamak using a static external n=1 perturbation field generated by four error field correction coils located far from the plasma. During the application of the n=1 field the ELM frequency increased by a factor of 4 and the amplitude of the D(alpha) signal decreased. The energy loss per ELM normalized to the total stored energy, ...

In this paper, a novel learning algorithm termed Hybrid Online Sequential Extreme Learning Machine (HOSELM) is proposed. The proposed HOS-ELM algorithm is a fusion of the Online Sequential Extreme Learning Machine (OS-ELM) and the Minimal Resource Allocation Network (MRAN). It is capable of reducing the number of hidden nodes in Single-hidden Layer Feed-forward Neural Networks (SLFNs) with Radi...

The impact of edge localized modes (ELMs) carrying energies of up to 450 kJ on carbon erosion in the JET inner divertor is assessed by means of time resolved measurements using an in situ quartz microbalance diagnostic. The inner target erosion is strongly nonlinearly dependent on the ELM energy: a single 400 kJ ELM produces the same carbon erosion as ten 150 kJ events. The ELM-induced enhanced...