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Flexible and stretchable circuit is the key element for the upcoming flexible hybrid electronics in addition to high performance silicon based active devices and passive components. The circuitry and structure design of the circuit carrier have to be able to withstand the stress and tolerate biometric signal variation induced by external force. These circuit carriers can be fabricated by use of the flexible display technologies and facilities. In this study, we integrated ICs, passive components and sensors to form a system upon flexible/plastic circuit carrier. Bendable and/or stretchable smart textiles and patches were successful demonstrated with the functionality of electromyography (EMG) and electrocardiography (ECG).

This paper presents a new volume-occupancy-based actuated signal control system for a diamond interchange, where a two-way arterial street intersects two one-way streets on each side of a freeway, aiming to approximately capture vehicle platoons and thus to improve the traffic by adaptively adjusting the plan. As a sponsored project aiming at immediate implementation, this system had to be designed based on conventional loop detectors and Econolite ASC/3-2100 Controller, which are currently used by the Texas Department of Transportation (TxDOT). Loop detectors placed in the pavement at each approach were used to collect real-time traffic volume and occupancy every 1 min. These data were then aggregated into 15-min flow and 15-min average occupancy, used in the proposed control logic to help vehicle platoons more smoothly passing through a diamond interchange. Based on onsite observations and data from loop detectors, it shows that the proposed system works well when the traffic flow is higher than 400 veh/h/ln. For arterial roads in the morning peak hours, the occupancy can be reduced by over 10% with a similar or even higher flow rate. The findings exhibit a low-cost method to improve traffic flow at a diamond interchange by using widely used conventional loop detectors.

3D display has become increasingly popular in many fields. It can provide incredible immersion compared with 2D display. There are many researches referring to the change of user about no matter subjective experience or objective physiology signal while watching 3D content. Similarly, in this paper, we study the variation of user’s EEG when the user watched 3D content. However, we only focus on parallax cue and avoid other cues of 3D content by using Random Dot Stereogram(RDS) as visual stimulus. We designed an experiment which asked the subject to watch RDS with nine kinds of parallaxes(0,±0.5,±1.1,±1.3,±1.7). The users watched one RDS for 1 minute and then closed eyes and rest for 1 minute every time. During watching, EEG signal with 30‐channel was recorded. The result suggests that significant variation of the user’s EEG data occurred in the Alpha (8–13Hz) and Beta(14–30Hz) frequency band by different parallax’s comparison. And we found not only parallax but also electrode position can impact the user’s EEG data significantly. Accurately, the EEG data has a significant change in six electrodes position in both frequency bands including CZ, PZ, OZ, O2 in international 10–20 system. It means those electrode positions we detect can be regarded as typical positions where we record EEG signal. It will simplify the process of EEG signal acquisition when we need to study the relationship between parallax cue of 3D display and the user further.

In this paper, we designed an experiment to observe changes for different fatigue level in human brain when watching random dot stereogram (RDS) using the method of EEG. The subjects were asked to watch 3D content for 30 minutes and the disparity of RDS changed every 10 seconds. During this watching task, subjects should rate their extent of fatigue during the experiment on the scale of one to five only when they felt worse or better. 30 channels electroencephalogram (EEG) signals were recorded through the experiment. Finally, the relationship between various fatigue levels and disparities which revealed by EEG signals were investigated. Our results show that the power of waveband, namely alpha increased with the fatigue level increasing from one to four during watching RDS, but decreased in level five. We have employed logistic regression to model fatigue level and achieved classification accuracy of 94.18%. Our research has important implications for the continuous monitoring of user's fatigue in the future.

In computer vision and pattern recognition applications, there are usually a vast number of unlabelled data whereas the labelled data are very limited. Active learning is a kind of method that selects the most representative or informative examples for labelling and training; thus, the best prediction accuracy can be achieved. A novel active learning algorithm is proposed here based on one-versus-one strategy support vector machine (SVM) to solve multi-class image classification. A new uncertainty measure is proposed based on some binary SVM classifiers and some of the most uncertain examples are selected from SVM output. To ensure that the selected examples are diverse from each other, Gaussian kernel is adopted to measure the similarity between any two examples. From the previous selected examples, a batch of diverse and uncertain examples are selected by the dynamic programming method for labelling. The experimental results on two datasets demonstrate the effectiveness of the proposed algorithm.

The human hand along with its fingers possess one of the highest numbers of nerve endings in the human body. It thus has the capacity for the richest tactile feedback for positioning capabilities. This article shares a new technique of controlling slippage. The sensing system used for the detection of slippage is a modified force sensing resistor (FSR®). The control system is a fuzzy logic control algorithm with multiple rules that is designed to be processed on a mobile handheld computing platform and integrated/working alongside a traditional Electromyography (EMG) or Electroencephalography (EEG) based control system used for determining position of the fingers. A 5 Degrees of Freedom (DOF) hand, was used to test the slippage control strategy in real time. First a reference EMG signal was used for getting the 5 DOF hand to grasp an object, using position control. Then a slip was introduced to see the slippage control strategy at work. The results based on the plain tactile sensory feedback and the modified sensory feedback are discussed.

This paper addresses a field technician scheduling problem faced by many service providers in telecommunication industry. The problem is to assign a set of jobs, at different locations with time windows, to a group of field technicians with different job skills. Such a problem can be viewed as a generalization of the well-known vehicle routing problem with time windows since technician skills need to be matched with job types. We designed and tested several heuristic procedures for solving the problem, namely a greedy heuristic, a local search algorithm, and a greedy randomized adaptive search procedure (GRASP). Our computational results indicate that GRASP is the most effective among them but requires more CPU time. However, the unique structure of GRASP allows us to exploit parallelism to achieve linear speed-up with respect to the number of machines used.

This paper presents a tabu search approach for optimizing the link capacities in a dynamic routing telecommunications network. The traffic between any two nodes in the network is routed over a one‐link direct path or, if no direct capacity is available, over a two‐link alternate path. The alternate routing paths can be changed dynamically from hour to hour as the traffic between pairs of nodes may vary with the time of day. The problem is to determine the optimal capacity level for each link in the network to minimize cost while satisfying the grade‐of‐service constraints. Although the problem can be formulated as a nonlinear integer programming problem, no efficient solution procedures are available. In this paper, we develop a two‐level tabu search heuristic for solving the problem that utilizes probabilistic move selection and coordinated solution recovery strategies. The macro level of the algorithm iteratively determines an hour for possible improvement and then the micro level seeks to optimize the routing paths for that hour. Our computational experience with both real and simulated problems indicates that significant savings can be obtained by this approach over the conventional network designs.

We present a study of using tabu search to solve a specific network design problem arising in the telecommunication industry. We develop a tabu search heuristic for this problem that incorporates long-term memory and probabilistic move selections. Computational results show that the new heuristic consistently outperforms the best local search currently available, with significantly increased performance differences on more difficult problems.