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This work introduces a hard clustering algorithm based on Particle Swarm Optimization metaheuristic that is able to partition objects considering their relational descriptions given by a single dissimilarity matrix. The PSO is a metaheuristic based on population which is well known for its simplicity, good performance and it was already designed as clustering algorithm for vector data. The proposed...
In this study, we propose a hybrid knowledge-based framework for author name disambiguation. The developed approach helps incrementally identify authors of documents in data acquired from various sources. The nature of the problem calls for an orchestrated use of several methods; thus, the framework is composed of two levels. The first level contains a rule-based disambiguation algorithm. The second...
Our emotion estimation refers to estimation of a reader's sentiments and feelings after they read a narrative (i.e., post-reading emotion types). The emotion types manifest in a reader's feelings combine to form diverse and various patterns. To elicit this phenomenon, we here attempt to estimate readers' emotional patterns based on their cognitive appraisals of the work. This paper describes our cognitive...
It is an important measure for China to implement the strategy of major functional area (MFA) to promote the optimization and upgrading of the industry and the development of regional integration. In order to study spatial correlation structure between optimization development zone and key development zone, the paper chooses Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) and Ha-Chang City Group...
Multitask learning methods facilitate learning multiple related tasks together and improvise results as compared to the schemes where each task is considered independently. In order to incorporate the shared information in multiple tasks, various regularizers have been integrated in pre-existing techniques. In this paper, we explore the problem of convex formulations of multitask learning with sparsity...
Researchers create larger networks of contacts through research collaboration, known as collaboration networks of researchers. In order to promote and to have effective collaboration among researchers, the collaboration patterns need to be accessed and analysed to elevate research and publication (R&P) performance. However, the collaboration patterns have not been accessed in the context of Universiti...
In this paper, we propose a multiversion index utilizing key features of SSDs (solid state drives). SSDs have many advantages, e.g., fast read/write performance, high energy efficiency, and non-volatility. Thus, SSDs have been considered for several years as a promising alternative to HDDs (hard disk drives). Many studies have made progress in optimizing and modifying HDD-based database management...
This paper describes a method for extracting relevant tokens of entity from semi-structured administrative documents. This method is used for mislabeling correction by employing the entity tokens physically close in a document. Firstly, the entities are labeled. Secondly, each entity is modeled by a tokens structure graph in which the nodes represent the tokens and the arcs represent the distances...
In-silico modeling is an important part of biomedical engineering. Advanced controllers providing high quality control can be validated through it checking if the available mathematical model of the given biomedical process produces the desired output. However, due to high patient variability the advanced linear control methods applied on linearized models could produce several distortions compared...
Eye gaze patterns or scanpaths of subjects looking at art while answering questions related to the art have been used to decode those tasks with the use of certain classifiers and machine learning techniques. Some of these techniques require the artwork to be divided into several Areas or Regions of Interest. In this paper, two ways of clustering the static visual stimuli - k-means and the density...
This paper considers a problem of highly compressing the data called “Digital-Ink” which is a sequence of position data sampled from the traced curve at a sampling rate. We here suppose that a set of digital-ink is measured and stored as two-dimensional position data by electronic device (e.g. smart-phone and pen-tablet PC, etc.). Then, we develop a method of digital-ink compression using B-spline...
With fuzzy set theory, the uncertainty nonlinear systems can be modeled with fuzzy equations or fuzzy differential equations (FDEs). The solutions of them are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this paper, the solutions of FDEs are approximated by two type of Bernstein neural networks. We first transform the FDE into four ordinary...
Naive users often perceive calibration of a Sensory Motor Rhythm (SMR) based Brain-Computer Interfaces (BCI) as tedious and lengthy. The lack of feedback during training is assumed to be a major cause. I.e. if one had already a reasonable model to start with, feedback training could be started immediately. One concept to address this issue is learning a general model and adapting it to new observations...
The biclustering method is a useful co-clustering technique to identify biologically relevant gene modules. In this paper, we propose a novel method to find not only functionally-related gene modules but also state specific gene modules by applying a genetic algorithm to gene expression data. To identify these gene modules, the proposed method finds biclusters in which genes are statistically overexpressed...
An active system (AS) is a network of communicating automata. A complex active system (CAS) is a hierarchy of communicating active systems. By inspiration of biological systems, organized in a hierarchy of subsystems, the interaction between automata in an AS gives rise to an emergent behavior at a superior AS, which is unpredictable from a knowledge of the behavior of the communicating automata only...
This paper addresses a single-period dual sourcing problem with real option under uncertain supply and demand. A retailer, who faces the uncertain market demand, can source from a low-price but unreliable supplier and an expensive but reliable supplier. In order to manage the supply uncertainties and decrease the cost, the retailer orders product from the unreliable supplier and buys option from the...
The market of light-emitting devices (LED) is growing dramatically over these years. To test the quality of LEDs, lots of LED probes are required. Therefore, it is important to develop an effective method to measure the angle (around 10 degrees) and the radius (15 µm ∼ 30 µm) of a produced LED probe. In this study, we propose a new subpixel edge detection for LED probes. The proposed method mainly...
Equirectangular panoramas are popular tools for achieving 360 degree immersed viewing experiences. A panorama captures a scene from one point and panoramic viewers allow the user to control the viewing direction, but the viewer is not allowed to move around. This study proposes a strategy for transforming equirectangular panoramic images with the effect of moving freely in three dimensions. The strategy...
Multi-robot systems (MRS) working in open and dynamic environments are expected to deal with uncertain arrival of new tasks and environment changes, by repeatedly adapting the current task allocation and schedule, in order to maintain its performance (e.g., total utility, balance, etc.). This paper presents an adaptive approach to multi-robot task allocation (MRTA), which combines two adaptive measures...
We study a house allocation problem where there are both existing tenants and new applicants. The NH4 mechanism is a real-world allocation mechanism which satisfies individual rationality, fairness and strategy-proofness. But it fails Pareto efficiency. We propose an efficiency-adjusted NH4 mechanism that allows each student to consent a certain priority violation that has no effect on her own assignment...
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