WSC2008Chair’s Welcome Message Dear Colleague, The World Soft Computing (WSC) conference is an annual international online conference on applied and theoretical soft computing technology. This WSC 2008 is the thirtee...
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ISBN:
(数字)9783540896197
ISBN:
(纸本)9783540896180
WSC2008Chair’s Welcome Message Dear Colleague, The World Soft Computing (WSC) conference is an annual international online conference on applied and theoretical soft computing technology. This WSC 2008 is the thirteenth conference in this series and it has been a great success. We received a lot of excellent paper submissions which were peer-reviewed by an international team of experts. Only60 papers out of111 submissions were selected for online publication. This assured a high quality standard for this online conference. The corresponding online statistics are a proof of the great world-wide interest in the WSC 2008 conference. The conference website had a total of33,367di?erent human user accessesfrom43 countries with around100 visitors every day,151 people signed up to WSC to discuss their scienti?c disciplines in our chat rooms and the forum. Also audio and slide presentations allowed a detailed discussion of the papers. The submissions and discussions showed that there is a wide range of soft computing applications to date. The topics covered by the conference range from applied to theoretical aspects of fuzzy, neuro-fuzzy and rough sets over to neural networks to single and multi-objective optimisation. Contributions aboutparticleswarmoptimisation,geneexpressionprogramming,clustering, classi?cation,supportvectormachines,quantumevolutionandagentsystems have also been received. One whole session was devoted to soft computing techniques in computer graphics, imaging, vision and signal processing.
The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the commun...
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ISBN:
(数字)9783540304814
ISBN:
(纸本)9783540238928
The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the communication media such as email and threaded discussion. Although, we could have easily learned the impact of mobile devices in learning if we divided the subjects to use different hardware such as p- sonal computers, personal digital assistant, or mobile phones, we believe our findings will still be able to provide useful insights on the difficulties that the mobile learners will face in solving problems as a group. Our analysis result will also provide ba- line information on whether the traits of the successful or failed online groups are applicable to the mobile learners. For example, we expect the SMS will be a better medium to overcome the major problem of instant communication or the rapid propagation of the information as the mobile phones have built-in mechanism to remind the users of the incoming new messages and also the mobile phone users are expected to be interrupted for the incoming messages. However, we need further investigation of other problems, which hinder the optimum online group work. For example, ‘accuracy of the transferred information’ was identified as one of the pr- lems of using emails as the communication medium. Personal Digital Assistant (PDA) or SMS are more apt to deliver shorter messages than the typical emails.
Welcome to the 3rd International Conference on Wired/Wireless Internet C- munications (WWIC). After a successful start in Las Vegas and a selective c- ference in Germany, this year’s WWIC demonstrated the event’s ma...
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ISBN:
(数字)9783540321040
ISBN:
(纸本)9783540258995
Welcome to the 3rd International Conference on Wired/Wireless Internet C- munications (WWIC). After a successful start in Las Vegas and a selective c- ference in Germany, this year’s WWIC demonstrated the event’s maturity. The conference was supported by several sponsors, both international and local, and became the o?cial venue for COST Action 290. That said, WWIC has now been established as a top-quality conference to promote research on the convergence of wired and wireless networks. This year we received 117 submissions, which allowed us to organize an - citing program with excellent research results, but required more e?ort from the 54 members of the international Program Committee and the 51 additional reviewers. For each of the 117 submitted papers we asked three independent - viewers to provide their evaluation. Based on an online ballot phase and a TPC meeting organized in Colmar (France), we selected 34 high-quality papers for presentation at the conference. Thus, the acceptance rate for this year was 29%.
Drug-drug interactions (DDIs) are an important biological phenomenon which can result in medical errors from medical practitioners. Drug interactions can change the molecular structure of interacting agents which may ...
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Drug-drug interactions (DDIs) are an important biological phenomenon which can result in medical errors from medical practitioners. Drug interactions can change the molecular structure of interacting agents which may prove to be fatal in the worst case. Finding drug interactions early in diagnosis can be pivotal in side-effect prevention. The growth of big data provides a rich source of information for clinical studies to investigate DDIs. We propose a hierarchical classification model which is double-pass in nature. The first pass predicts the occurrence of an interaction and then the second pass further predicts the type of interaction such as effect, advice, mechanism, and int. We applied different deep learning algorithms with Convolutional Bi-LSTM (ConvBLSTM) proving to be the best. The results show that pre-trained vector embeddings prove to be the most appropriate features. The F1-score of the ConvBLSTM algorithm turned out to be 96.39% and 98.37% in Russian and English language respectively which is greater than the state-of-the-art systems. According to the results, it can be concluded that adding a convolution layer before the bi-directional pass improves model performance in the automatic classification and extraction of drug interactions, using pre-trained vector embeddings such as Fasttext and Bio-Bert.
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