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Key Performance Indicators (KPIs) are used to inspect the performance and progress of businesses. This study introduces a new, integrated approach to manage KPIs in the context of decentralized information efficiently and to address the visual and managerial gaps existing in companies. The proposed Business Indicator Management (BIM) system is essential for any businesses to meet their needs in terms...
This paper proposes a 3D vision based object grasping posture learning system. In this system, the robot recognizes the orientation of the object to decide the grasping posture, whereas selects a feasible grasping point by detecting the surrounding. When the planned posture is not good enough, the proposed learning system adjusts the position of the end effector real time. The learning system is inspired...
The aim of this study is to propose an information system that should help boost cooperation between business and academia and their innovativeness. Its novelty relies on introducing such a system architecture and business processes that allow implementing the paradigm of open innovation easily. More specifically, the proposed system: (i) automatically acquires data from the Internet and extracts...
This research concerned about an online learning algorithm of the group method of data handling based proportional-integral-derivative (GMDH-PID) controller that is effective for nonlinear systems. Although a lot of PID controllers have been mainly used in industrial systems, it is difficult to maintain a desired control performance only by a PID controller with fixed control parameters due to system...
This paper deals with the smart placement of motion sensors in smart homes for Ambient Assisted Living, by considering the sensor technology and cost and respecting specific coverage requirements. The core of the proposed methodology is a decision module that can optimize the sensors placement according to different objectives. More precisely, the main objective is the minimization of costs of the...
E-recruitment sites such as LinkedIn, Reed, and Indeed have a huge number of professional resumes from job seekers and job openings posted by recruiters. In this situation, it is a very time-consuming task for job seekers to find job openings that are well matched to their careers and desired conditions. Accordingly, active studies on job recommendation (JR) have been conducted recently. In this paper,...
The high-level feature representation of deep convo-lutional neural networks (ConvNets) has proven to be superior to hand-crafted low-level features. Thus, this study investigates the effect of fusing such high-level features from multi-deep ConvNets under an application of visual object/scene categorization. In which, three pre-trained ConvNets are exploited as feature extractors, a single hidden...
3D face recognition is a popular research area due to its vast application in biometrics and security. Local feature-based methods gain importance in the recent years due to their robustness under degradation conditions. In this paper, a novel high-order local pattern descriptor in combination with sparse representation based classifier (SRC) is proposed for expression robust 3D face recognition....
This paper presents a new technique using animated texts as the speech features' visualization medium for checking and detecting language learners' pronunciation. The proposed visualization tool will transform learners' speech features such as pitch, tempo or rhythm into animated texts form, and the mispronounce parts can be located by comparing them with the correct sample. In our previous experiments,...
In biology, text-mining is widely used to extract relationships between biological entities. Gene prioritization is also important to analyze diseases, because mutated or dysregulated genes play an important role in pathogenesis. Here, we propose a method to identify disease-related genes using seed genes and network analysis. We constructed an integrating gene network for lung cancer by combining...
In this paper, a method of estimating binding time is proposed for ophthalmological outpatients. Binding time equals the sum of transit time and waiting time at a hospital. It determines the number of outpatients virtually arriving and their arrival time intervals according to the gamma distribution and the exponential distribution. It then assigns examinations to outpatients virtually arriving, referring...
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