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2016 8th International Conference on Knowledge and Smart Technology (KST)最新文献

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Category specific knowledge modulate capacity limitations of visual short-term memory 类别特定知识对视觉短期记忆调节能力的限制
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-04-05 DOI: 10.1109/KST.2016.7440508
Jonas Olsen Dall, Katsumi Watanabe, T. Sørensen
{"title":"Category specific knowledge modulate capacity limitations of visual short-term memory","authors":"Jonas Olsen Dall, Katsumi Watanabe, T. Sørensen","doi":"10.1109/KST.2016.7440508","DOIUrl":"https://doi.org/10.1109/KST.2016.7440508","url":null,"abstract":"We explore whether expertise can modulate the capacity of visual short-term memory, as some seem to argue that training affects capacity of short-term memory [13] while others are not able to find this modulation [12]. We extend on a previous study [3] by demonstrating expertise effects by investigating different groups of healthy adults. In a whole report paradigm [5] we investigate performance on standardized pictures [11], Latin letters, and Japanese hiragana. Expertise was modulated between groups of novice (Danish university students), trained (Danish university students studying Japanese), and expert observers (Japanese university students). For both the picture and the letter condition we find no performance difference in memory capacity, however, in the critical hiragana condition we demonstrate a systematic difference relating expertise differences between the groups. These results are in line with the theoretical interpretation that visual short-term memory is the sum of the reverberating feedback loops to representations in long-term memory.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Hybrid ensembles of decision trees and Bayesian network for class imbalance problem 类失衡问题的决策树与贝叶斯网络混合集成
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440523
Pumitara Ruangthong, S. Jaiyen
{"title":"Hybrid ensembles of decision trees and Bayesian network for class imbalance problem","authors":"Pumitara Ruangthong, S. Jaiyen","doi":"10.1109/KST.2016.7440523","DOIUrl":"https://doi.org/10.1109/KST.2016.7440523","url":null,"abstract":"Class imbalance problem is the main issue causing unsatisfactory outcome in classification. Any type of classification used still cannot improve the result. Therefore, in this research we propose a new hybrid ensemble model based on AdaBoost.M2 and adopt SMOTE algorithm to solve the class imbalance problem in order to predict the probability of term deposit from bank customers. The proposed hybrid ensemble model consist of diverse based classifiers which are Bayesian Network, Alternating Decision Tree, Tree-J48, and REPTree (Reduced-Error Pruning). From the experimental results, the proposed model can achieve the highest performance comparing to normal ensemble models and ensemble models that use majority class reduction, and finally generates the results of 91.5% sensitivity, 100% specificity, and 96.3% accuracy.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116447074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Study on data center and data librarian role for reuse of research data 研究数据中心和数据馆员在研究数据重用中的作用
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440517
Suntae Kim, Myung-Seok Choi
{"title":"Study on data center and data librarian role for reuse of research data","authors":"Suntae Kim, Myung-Seok Choi","doi":"10.1109/KST.2016.7440517","DOIUrl":"https://doi.org/10.1109/KST.2016.7440517","url":null,"abstract":"There are new demands for data centers and data librarians to manage and reuse data. In this study, trends of advanced research institutions were investigated and analyzed and implications were derived, in relation to the environment establishment for management, preservation and reuse of research data generated from research processes. New roles required of data centers and data librarians and 5 roles of data librarians that should be performed as a data scientist were proposed: 1) IDR Manager, 2) Policy Maker, 3) DMP Consultant, 4) Data Consultant and 5) Data Publisher.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127679948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Human learning and machine learning: Building bridges or integration? 人类学习和机器学习:搭建桥梁还是整合?
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440538
S. Russ
{"title":"Human learning and machine learning: Building bridges or integration?","authors":"S. Russ","doi":"10.1109/KST.2016.7440538","DOIUrl":"https://doi.org/10.1109/KST.2016.7440538","url":null,"abstract":"Summary form only given. At the core of Empirical Modelling is an activity we call `making construals'. A construal is a software artefact that embodies how we think about something, or make sense of something. For example, it might be a visualisation of a car engine with gears and controls that behaves - through interaction - like the physical car. We shall show a construal of MENACE : an early example of a simple machine (made with matchboxes) that learns to improve its own performance at playing noughts and crosses. Some experts in machine learning contrast the `big data' methods of training networks with the use of explanatory models. It is proving difficult, but desirable, to integrate these approaches. We'll suggest why Empirical Modelling might offer some useful insights into this problem.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127968918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Human computing: A new smart technology for learning and life 人机计算:一种用于学习和生活的新型智能技术
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440472
S. Russ
{"title":"Human computing: A new smart technology for learning and life","authors":"S. Russ","doi":"10.1109/KST.2016.7440472","DOIUrl":"https://doi.org/10.1109/KST.2016.7440472","url":null,"abstract":"Summary form only given. Empirical Modelling (EM) is an approach to computing which includes, but is much broader than, traditional computer science. It occupies a territory where experience is more prominent than abstractions, where state has priority over pre-conceived behaviours and where the agencies behind state change (human or otherwise) are first identified. Extensive research, and teaching of this approach to final year computer science students, over many years under the leadership of Meurig Beynon at the University of Warwick has resulted in a large body of artefacts, environments and publications. They can be found at http://go.warwick.ac.uk/em At the core of EM is an activity we call `making construals'. By a `construal of X' we mean `what we think of X' or `how we make sense of X'. As well as being a personal product of the maker it is at the same time an interactive computer artefact. The development method we adopt allows passage from the mere contemplation of a phenomenon or problem to the crafting of a program-like behaviour that is useful. We shall demonstrate this and explain the advantages of the approach, in at least some domains such as learning, when compared with existing programming paradigms. We have called the approach `human computing' in recognition that its `programs' - in both development and ways of use - have much more of the human qualities of flexibility, and multiple viewpoints, than is usual in a computing environment. It promotes closer collaboration between the human and computer. We shall report on the progress and challenges of the EU Project CONSTRUIT! which is half-way through its three-year duration. With its six European partners CONSTRUIT! seeks to promote the making of construals among teachers and students (at all levels) and to evaluate the effectiveness of this activity for learning across many subjects. See http://go.warwick.ac.uk/em/welcome We hope also to have a practical workshop on making contruals at KST2016 so we look forward to welcoming you to that and seeing what new construals you can help us make!","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130187373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An adjustment strategy on multi-session EEG data for online left/right hand imagery classification 基于多会话脑电数据的左/右手图像在线分类调整策略
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440528
Sitthiphong Muthong, P. Vateekul, M. Sriyudthsak
{"title":"An adjustment strategy on multi-session EEG data for online left/right hand imagery classification","authors":"Sitthiphong Muthong, P. Vateekul, M. Sriyudthsak","doi":"10.1109/KST.2016.7440528","DOIUrl":"https://doi.org/10.1109/KST.2016.7440528","url":null,"abstract":"In this research, electroencephalography (EEG) is used as an interface to communicate between patients and doctors. The signals from two electrodes (C3 and C4) are captured and used to classify Left/Right hand imagery representing YES/NO answers of the patients. In online applications, the training model mostly cannot be applied to the testing sessions due to a variation of the signals. Although some prior works employed a normalization technique, the parameters were still derived from all sessions, not just the training sessions, resulting in low prediction accuracy in real-world online systems. In this paper, we propose an adjustment strategy that can be applied online to all features by subtracting \"estimated mean\" and dividing \"estimated interquartile rage\" (IQR) or \"estimated standard deviation\" (SD), which are obtaining by using exponentially weighted moving average (EWMA). In our system, the features are extracted by applying the wavelet transformation, and Neural Network is chosen as our classifier. The experiment was conducted on the BCI IV data set and compared to four existing techniques: (i) non-normalized wavelet, (ii) Z-transform, (iii) CSP, and (iv) CSP with Morlet wavelet, in terms of accuracy. The results showed that our proposed method significantly outperformed the first three works and it is comparable to the last one, but ours employed the less number of electrodes.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130916521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Automated detection of plasmodium falciparum from Giemsa-stained thin blood films 吉氏染色血膜恶性疟原虫的自动检测
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440501
Wongsakorn Preedanan, M. Phothisonothai, W. Senavongse, S. Tantisatirapong
{"title":"Automated detection of plasmodium falciparum from Giemsa-stained thin blood films","authors":"Wongsakorn Preedanan, M. Phothisonothai, W. Senavongse, S. Tantisatirapong","doi":"10.1109/KST.2016.7440501","DOIUrl":"https://doi.org/10.1109/KST.2016.7440501","url":null,"abstract":"This paper investigates automated detection of malaria parasites in images of Giemsa-stained thin blood films. We aim to determine parasitemia based on automatic segmentation, feature extraction and classification methods. Segmentation relies on adaptive thresholding and watershed methods. Statistical features are then computed for each cell and classified using SVM binary classifier. Accuracy of classification is validated based on the leave-one-out cross-validation technique. This processing pipeline is applied on total 15 images of Giemsa-stained thin blood films and yields 92.71% sensitivity, 97.35% specificity and 97.17% accuracy.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114863849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Motor insurance knowledge management in AIML format using tree structured dictionary mechanism and conceptual graph 采用树状字典机制和概念图实现AIML格式的车险知识管理
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440524
Wilailuk Sukfong, S. Nakkrasae, Preecha Panpipat
{"title":"Motor insurance knowledge management in AIML format using tree structured dictionary mechanism and conceptual graph","authors":"Wilailuk Sukfong, S. Nakkrasae, Preecha Panpipat","doi":"10.1109/KST.2016.7440524","DOIUrl":"https://doi.org/10.1109/KST.2016.7440524","url":null,"abstract":"Nowadays, information providers of car insurance through the site are not effective enough for consumers needs. Thus, this paper presents a motor insurance knowledge management based on Artificial Intelligence Markup Language (AIML). In the part of knowledge management, tree structure dictionary mechanism method is used for word segmentation and the conversion technique to correct grammatical sentences (Pattern Normalization) utilizes conceptual graphs. Motor insurance enquiry intelligent system via mobile devices is then implemented. It is analyzed and designed by using object-oriented approach with UML (Unified Modeling Language). The result shows that the developed system can be used for answer questions and works more efficiently.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130369632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A coefficient comparison of weighted similarity extreme learning machine for drug screening 加权相似极值学习机在药物筛选中的系数比较
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440525
Wasu Kudisthalert, Kitsuchart Pasupa
{"title":"A coefficient comparison of weighted similarity extreme learning machine for drug screening","authors":"Wasu Kudisthalert, Kitsuchart Pasupa","doi":"10.1109/KST.2016.7440525","DOIUrl":"https://doi.org/10.1109/KST.2016.7440525","url":null,"abstract":"Machine learning techniques are becoming popular in drug discovery process. It can be used to predict the biological activities of compounds. This paper focuses on virtual screening task. We proposed the Weighted Similarity Extreme Learning Machine algorithm (WELM). It is based on Single Layer Feedforward Neural Network. The algorithm is powerful, iteratively free, and easy to program. In this work, we compared the performance of 17 different types of coefficients with WELM on a well-known dataset in the area of virtual screening named Maximum Unbiased Validation dataset. Moreover, the WELM with different types of coefficients were also compared with the conventional technique-similarity searching. WELM together with Jaccard/Tanimoto were able to achieve the best results on average in most of the activity classes.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133311047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
How people perceive different robot types: A direct comparison of an android, humanoid, and non-biomimetic robot 人们如何看待不同类型的机器人:机器人、人形机器人和非仿生机器人的直接比较
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-03-24 DOI: 10.1109/KST.2016.7440504
Kerstin S Haring, David Silvera Tawil, Tomotaka Takahashi, Katsumi Watanabe, Mari Velonaki
{"title":"How people perceive different robot types: A direct comparison of an android, humanoid, and non-biomimetic robot","authors":"Kerstin S Haring, David Silvera Tawil, Tomotaka Takahashi, Katsumi Watanabe, Mari Velonaki","doi":"10.1109/KST.2016.7440504","DOIUrl":"https://doi.org/10.1109/KST.2016.7440504","url":null,"abstract":"During first encounters and short-term interaction with robots, the robot's appearance and initial behavior plays a major role. In this paper we compare the outcome of three human-robot interaction studies using three different robot types in two different countries, Japan and Australia. The participants' perception of an android robot, a humanoid robot and a non-biomimetic robot are compared before and after interacting with the robots. The experimental results show significant differences in the way people perceive the robots based on appearance alone, and based on appearance and behavior after a short interaction.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121042825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 33
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