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In order to balance the number of outbound and inbound tasks of each aisle and improve the working efficiency of the multi-tier shuttle system, three principles of storage location assignment were put forward: the principle of minimum correlation degree, the principle of equalization of product items and the principle of equalization of tasks, which were expected to be followed when storing products...
Content-Centric Networking (CCN) proposals rethink the communication model around named data. In-network caching is a fundamental feature to distinguish the CCN from the current host-centric IP network. In this paper, we have proposed a hybrid caching scheme which combines the on-path one and the off-path one. We leverage the ISOMAP manifold learning algorithm to distinguish the importance of nodes...
The ability to discover patterns of interest in criminal networks can support and ease the investigation tasks by security and law enforcement agencies. By considering criminal networks as a special case of social networks, we can properly reuse most of the state-of-the-art techniques to discover patterns of interests, i.e., hidden and potential links. Nevertheless, in time-sensible scenarios, like...
The efficiency of current aero-engine remaining life prediction methods has room for improvement. This paper focuses on analysis of aero-engine exhaust gas temperature margin (EGTM) time-series data and introduces a pattern mining method of aero-engine performance degradation based on Empirical Mode Decomposition (EMD) and k-nearest neighbors optimized clustering by fast search and find of density...
Latent Dirichlet Allocation has been developed as topic-based method which uses reasoning to determine the topics of a document. There are many methods of reasoning used for Latent Dirichlet Allocation, including the Gibbs Sampling and Mean Variational Inference, the most widely used in research. However, there have not been many studies that discuss the implementation of these methods on the Indonesian...
Understanding the function of software code is the basis for software reuse. Topic modeling technologies can mine functional topics from source code and help developers comprehend the functional concerns about a software system and the corresponding implementations in source code. However, lacking clear explanations makes these functional topics hard to be understood by the developers. Furthermore,...
Unplanned hospital readmission is a costly problem in the United States. Patients treated and readmitted within 30 days cost tax payers up to $26 billion annually. In 2013 the U.S. federal government began to reduce payments to hospitals with excessive patient readmissions. Predictive modeling using machine learning can be a useful tool to help identify patients most likely to need readmission. However,...
Through investigating the status of information management of laboratory equipment in a certain aerospace scientific research unit, analyzing the backwardness of its equipment information management mode, low efficiency and high error rate, this paper puts forward the application of RFID(Radio Frequency Identification) technology in the laboratory, combining visualization, data mining technology and...
The recent years have witnessed a sharp increase in the use of smart phones for internet applications, video calling, social networking and emails, etc. resulting in an unprecedented increase in the worldwide wireless network traffic. During the deployment of the wireless network topologies the prime focus has to be given towards the requirement for the bandwidth, user capacities and provision of...
Semiconductor wafer fabrication companies rely on continuously improving cycle time for agile manufacturing to maintain their competitive advantages. This study has illustrated how to apply data mining techniques, Back-Propagation Neural Networks (BPNN), to optimize the allocation of production resources in semiconductor wafer fabrication. The results in the empirical study have demonstrated significant...
The first publications on sentiment analysis and opinion mining were published roughly a decade ago. Now it is time to lookback on the achievements so far. This paper presents statistics on the evolution of sentiment analysis. What kind of topics have beendiscussed? How has their popularity changed over time? Who have been the leading researchers? Answers to these questions areprovided by statistical...
With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue...
This paper proposes a method for proper names extraction from Myanmar text by using latent Dirichlet allocation (LDA). Our method aims to extract proper names that provide important information on the contents of Myanmar text. Our method consists of two steps. In the first step, we extract topic words from Myanmar news articles by using LDA. In the second step, we make a post-processing, because the...
Geosocial networks like Yelp and Foursquare have been rapidly growing and accumulating plenty of data such as social links between users, user check-ins to venues, venue geographical locations, venue categories, and user textual comments on venues. These data contain rich knowledge on the user's social interactions in communities, geographical mobility patterns between regions, categorical preferences...
The growing demand for smarter high-performance embedded systems leads to the integration of multiple functionalities in on-chip systems with tens (even hundreds) of cores. This trend opens a very challenging question about the optimal resource allocation in those manycore systems. Answering this question is key to meet the performance and energy requirements. This paper deals with a learning technique...
A well product-to-shelf assignment strategy can help customers easily find product items and dramatically increase the retailing store profit. Previous studies in this area usually applied the space elasticity to optimize product assortment and space allocation models. However, a well product-to-shelf assignment strategy should not only consider product assortment and space elasticity. Thus, this...
As for the majority methods of Pseudo Relevance Feedback (PRF), the document in pseudo relevant set is generally divided into the relevant and the non-relevant according to user query. It is so coarse that the lower robustness of PRF, because there is still some relevant information in the non-relevant document and non-relevant information in the relevant document. A novel ranking scheme is proposed...
The growth in the packaged food industry has created pressure on the packaged food warehouse to enhance the order-picking efficiency. The decision support system (DSS) for stock keeping units (SKUs) allocation thus has to make quality decisions for shortening the order-picking time. In order to improve the decision making ability of the DSS, the determinant factors of the major input variable - the...
The topic detection of university BBS (Bulletin Board System) plays an important role in studying university students' hottest attention, and it presents the trend of campus opinion. Existing topic model use word probability distribution to represent topic, which lacks of interpretability, and it's difficult to express an unified meaning. What's more, university BBS has its own characteristics and...
Crowdclustering clusters data items in a crowdsourcing manner, which makes discovered item categories more consistent with human perception. However, due to diversity of crowdsourcing workers and fluctuation of the number of tasks assigned to each worker, inferring stable and reliable clusters is challenging. Moreover, an item may be associated with multiple attributes, and such items should be put...
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