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The long-tail phenomenon tells us that there are many items in the tail. However, not all tail items are the same. Each item acquires different kinds of users. Some items are loved by the general public, while some items are consumed by eccentric fans. In this paper, we propose a novel metric, item eccentricity, to incorporate this difference between consumers of the items. Eccentric items are defined...
Brain-state drifts could significantly impact on the performance of machine-learning algorithms in brain computer interface (BCI). However, less is understood with regard to how brain transition states influence a model and how it can be represented for a system. Herein we are interested in the hidden information of brain state-drift occurring in both simulated and real-world human-system interaction...
This paper reviews the literature of technology assessment published over 1977 to 2016 to identify the major research themes over the past four decades. We retrieve 5493 articles from the Web of Science database and construct the citation network among them. By applying the edge-betweenness clustering technique to the citation network and splitting the data into groups, 4 major groups with more than...
In sensor clouds environments, the provisioning process is a crucial task since it is responsible for selecting physical sensors nodes that will be allocated to compose virtual sensors. In literature, most works consider the allocation of all sensors within the region of interest. However, this approach causes serious problems such as wasted energy consumption. Therefore, the objective of this paper...
This paper deals with ship scheduling and inventory management by considering both shipping costs and demurrage costs with hourly precision. First, the formulation of an optimization model of the problem is described. Then, a hierarchical scheduling approach is newly introduced, which enables us to get a schedule close to the optimal within reasonable computational time. Moreover, through some computational...
Skin resistance is one of the important indexes in psychological affective researches, and it can reflect the change of emotion by recording its changes. Generally, the skin resistance measurement method is connecting the electrode sensor to the two adjacent fingers of the object to record the resistance signal, and then amplifying, collecting and recording the signal by amplification circuit. However,...
Monitoring the evolution phases of real-time event including occurrence, development, climax, decline and ending is crucial for management department to intuitively and comprehensively understand the event and then make better decisions. However, there have been very few studies on performing phase evolution analysis of event using the number of posts at the specific time unit. The challenge of this...
Functional connectomes (FCs) are powerful in characterizing brain conditions. Temporal FC metrics can index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior. However, time-varying properties of temporal brain networks in general mental disorders have been less investigated. In this paper, FCs derived from resting-state fMRI (R-fMRI) data are temporally...
TrapFetch is trained by monitoring the read requests issued by an application. It detects bursts of disk reads, determines the appropriate addresses at which breakpoints should be inserted in the application and library codes prior to the bursts of reads, and then logs this information with the data requested during the interval between each consecutive pair of breakpoints. When the application and...
The combination of Device-to-Device (D2D) Communication in 5G Cellular Networks and vehicular networks will not only increase the performance of vehicular networks, but also increase the revenues for network operators and services providers. This paper proposes a 5G D2D routing method oriented to vehicular networks, which can increase the connectivity and scalability of vehicular networks while alleviating...
Cognitive radio (CR) is a promising method suitable for solving inefficiency spectrum policy by opportunistically identifying the vacant portions of the spectrum that are used by primary users (PUs). In cognitive radio ad hoc networks (CRAHNs), secondary users (SUs) can opportunistically utilize the spectrum that is available from PUs. In this paper, we propose a neighbor-aware distance estimated...
An incentive design method is proposed for incentive-based demand response programs targeting residential consumers. Consumers are modelled as decision-makers and their models represent, unlike existing models, dynamical nature of power consumption behaviors. The design is done based on inverse optimization. The degree of freedom that exists in the solution can be effectively utilized to make the...
In this paper, we propose a scale-invariant framework based on Convolutional Neural Networks (CNNs). The network exhibits robustness to scale and resolution variations in data. Previous efforts in achieving scale invariance were made on either integrating several variant-specific CNNs or data augmentation. However, these methods did not solve the fundamental problem that CNNs develop different feature...
The strong abilities of deep learning models have been shown in the area of text detection in natural scene images. In this paper, we introduce a new method called deep metric learning for scene text detection. We use the triplet loss [1] to replace the traditional loss function (Softmax) and learn a mapping from image regions to a compact Euclidean space where distances correspond to a measure of...
Unmanned aerial vehicles (UAVs) have been applied for both civilian and military applications; scientific research involving UAVs has encompassed a wide range of scientific study. However, communication with unmanned vehicles are subject to attack and compromise. Such attacks have been reported as early as 2009, when a Predator UAV's video stream was compromised. Since UAVs extensively utilize autonomous...
The increase in the use of mobile devices from the first decade of this century has enabled users to perform several activities previously only possible through personal computers. However, the use of these devices is impacted by their known computational limitations, such as data processing, RAM memory, storage, and energy autonomy limitations. Considering this context, to measure the impact of the...
In this paper, driver intention estimation near a road intersection is presented, using discrete hidden Markov models (HMM) and the Hybrid State System (HSS) framework as basis. The development of Advanced Driver Assistance Systems (ADAS) has assisted drivers in many driving scenarios and resulted in safe driving. Developing techniques to estimate driver's intention leads to the advancement of ADAS...
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...
In this paper, the problem of developing a model for signal control system with transit priority using Colored Petri Nets (CPNs) is considered. In a regular four phases signal lights control model, transit detection and two kinds of transit priority strategies are integrated to obtain Colored Petri Nets based transit priority signal control model. The resulting model ensures that transit can pass...
One of the greatest challenges for computer science in education is the capacity to provide environments that are intelligent and adaptable to the real needs of students. In order to create efficient adaptive mechanisms for educational content, student models are proposed to identify and to predict the real knowledge level of students. Such models are useful not only for computer systems but also...
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