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In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots “Pet-Bot”. To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner’s approach on its own. Second, Pet-Bot’s activity is synchronized with the owner’s behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot’s control performance when following or leading a human in real-time.

Device-to-device (D2D) communication is a key enabler to facilitate the realization of the Internet of Things in which direct communication between mobile users is allowed without the intervention of the base station. One of the most challenging issues in the D2D cellular network is a low-complexity and reliable initial synchronization. To solve this issue, an efficient joint detection of integer carrier frequency offset (IFO) and set information (SI) is proposed for D2D communication in a long term evolution (LTE) system. Unlike the conventional approach, the primary sidelink synchronization signal (PSSS) and secondary sidelink synchronization signal (SSSS) transmitted in the LTE-D2D system are used together to remove the effect of channel fading and symbol timing offset (STO). In addition, the conjugate property between two PSSS sequences is utilized. This design facilitates robust sequential detection of the IFO and SI without priori information on two synchronization signals when residual STO is present. It has been demonstrated that the inherent properties of the PSSS and SSSS sequences are effectively used for efficient cell search in the presence of residual STO, compared to existing methods.

Device-to-device (D2D) communication is considered as a major challenge in the long term evolution (LTE) network wherein devices directly communicate with each other. One of the key challenges in D2D sidelink is reliable and reduced-complexity synchronization. To address this issue, a computationally efficient sequential detection scheme for integer carrier frequency offset and sidelink identity is proposed in the LTED2D system. To perform the frequency offset detection without retrieving the sidelink identity, the conjugate relation between two primary sidelink synchronization sequences is exploited, which facilitates the detection tasks of frequency offset and sidelink identity to be decoupled. It is demonstrated from simulation results that the inherent property of the sidelink synchronization sequences is effectively used for joint detection of frequency offset and sidelink identity with significantly reduced complexity, compared to existing estimation schemes.

Increasing popularization of mobile devices has pushed emergence of new services and technologies with convergence of broadcasting and broadband. One of the most striking issues of hybrid broadcasting is synchronization of delivered data over a heterogeneous network. Therefore, we consider a method of synchronization for delivery of hybrid content, as well as between devices using different service platforms. A hybrid delivery architecture and synchronization algorithm for heterogeneous networks in an inter-device environment is developed. In an inter-device system with broadcasting and broadband networks, experimental results verify that the proposed algorithm achieves accurate synchronization performance.

A lot of research has been done on the detection of mental workload (MWL) using various bio-signals. Recently, deep learning has allowed for novel methods and results. A plethora of measurement modalities have proven to be valuable in this task, yet studies currently often only use a single modality to classify MWL. The goal of this research was to classify perceived mental workload (PMWL) using a deep neural network (DNN) that flexibly makes use of multiple modalities, in order to allow for feature sharing between modalities. To achieve this goal, an experiment was conducted in which MWL was simulated with the help of verbal logic puzzles. The puzzles came in five levels of difficulty and were presented in a random order. Participants had 1 h to solve as many puzzles as they could. Between puzzles, they gave a difficulty rating between 1 and 7, seven being the highest difficulty. Galvanic skin response, photoplethysmograms, functional near-infrared spectrograms and eye movements were collected simultaneously using LabStreamingLayer (LSL). Marker information from the puzzles was also streamed on LSL. We designed and evaluated a novel intermediate fusion multimodal DNN for the classification of PMWL using the aforementioned four modalities. Two main criteria that guided the design and implementation of our DNN are modularity and generalisability. We were able to classify PMWL within-level accurate (0.985 levels) on a seven-level workload scale using the aforementioned modalities. The model architecture allows for easy addition and removal of modalities without major structural implications because of the modular nature of the design. Furthermore, we showed that our neural network performed better when using multiple modalities, as opposed to a single modality. The dataset and code used in this paper are openly available.

The paper presents the results of theoretical and experimental research in revealing the influence of form and geometrics of internal chamber of synchronization devices with steel-balls of fluid coupling on loading capability.

After the completion of grid parallel, the device can turn to be UPFC, STATCOM, SSSC, research on the conversion circuit and transform method by corresponding switching operation. Accomplish the grid parallel and comprehensive control of the tie-line and stable operation and control functions of grid after parallel. Defines the function select operation switch matrix and grid parallel system branch variable, forming a switch matrix to achieve corresponding function of the composite system. Formed a criterion of the selection means to choose control strategy according to the switch matrix, and to accomplish corresponding function. Put the grid parallel, STATCOM, SSSC and UPFC together as a system, improve the stable operation and flexible control of the power system.