Using tuple-spaces to manage the storage and dissemination of spatial–temporal content

Structured, spatial–temporal content arises in application areas such as mobile computing, intelligent transportation, urban mobility, and ubiquitous sensing. For the distributed storage and dissemination of such content, peer-to-peer solutions appear to be the natural choice. However, a closer analysis shows that distributed hash tables (DHT) alone are not enough: firstly, they do not maintain the original data structure needed to efficiently access the comprising attributes, and secondly, they lead to high signaling traffic when the data is short lived, such as in high mobility scenarios. In order to address these two problems we propose a novel content dissemination architecture based on an overlay of space-based containers. Furthermore, we apply the proposed concept to realize a concrete application in the field of intelligent transportation, and present the results of the performance evaluation conducted with the system prototype.     

Animated visualization of spatial–temporal trajectory data for air-traffic analysis

With increasing numbers of flights worldwide and a continuing rise in airport traffic, air-traffic management is faced with a number of challenges. These include monitoring, reporting, planning, and problem analysis of past and current air traffic, e.g., to identify hotspots, minimize delays, or to optimize sector assignments to air-traffic controllers. To cope with these challenges, cyber worlds can be used for interactive visual analysis and analytical reasoning based on aircraft trajectory data. However, with growing data size and complexity, visualization requires high computational efficiency to process that data within real-time constraints. This paper presents a technique for real-time animated visualization of massive trajectory data. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearance, and (3) real-time rendering within 3D virtual environments such as virtual 3D airport or 3D city models. Different visualization metaphors can be efficiently built upon this technique such as temporal focus+context, density maps, or overview+detail methods. As a general-purpose visualization technique, it can be applied to general 3D and 3+1D trajectory data, e.g., traffic movement data, geo-referenced networks, or spatio-temporal data, and it supports related visual analytics and data mining tasks within cyber worlds.     

Mutual information-based selection of optimal spatial–temporal patterns for single-trial EEG-based BCIs

The common spatial pattern (CSP) algorithm is effective in decoding the spatial patterns of the corresponding neuronal activities from electroencephalogram (EEG) signal patterns in brain–computer interfaces (BCIs). However, its effectiveness depends on the subject-specific time segment relative to the visual cue and on the temporal frequency band that is often selected manually or heuristically. This paper presents a novel statistical method to automatically select the optimal subject-specific time segment and temporal frequency band based on the mutual information between the spatial–temporal patterns from the EEG signals and the corresponding neuronal activities. The proposed method comprises four progressive stages: multi-time segment and temporal frequency band-pass filtering, CSP spatial filtering, mutual information-based feature selection and naïve Bayesian classification. The proposed mutual information-based selection of optimal spatial–temporal patterns and its one-versus-rest multi-class extension were evaluated on single-trial EEG from the BCI Competition IV Datasets IIb and IIa respectively. The results showed that the proposed method yielded relatively better session-to-session classification results compared against the best submission.     

Estimation of states and parameters for a discrete-time system using quasilinearization†

An attempt is made here to demonstrate the usefulness of quasilinearization technique for the estimation of states and parameters of a discrete-time system. The estimation problem is viewed as a least-squared-errors problem which is then transformed into a Two Point Boundary Value (TPBV) problem by the use of the Discrete Maximum Principle. The TPBV problem is then solved by the quasilinearization technique.     

Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognition

Pattern Analysis and Applications - The skeleton data convey significant information for action recognition since they can robustly against cluttered backgrounds and illumination variation. In...     

Landsat-satellite-based analysis of spatial–temporal dynamics and drivers of CyanoHABs in the plateau Lake Dianchi

ABSTRACT

Dianchi Lake, located in southwest China’s Yungui plateau, is facing severe eutrophication and frequent outbreaks of harmful cyanobacteria blooms (CyanoHABs). It is of great significance to monitor the occurrence and development of CyanoHABs in Dianchi Lake over a long period and analyse the main influences. Based on Landsat Thematic Mapper/Enhanced Thematic Mapper Plus/Operational Land Imager 1986–2016 data, we derived the distribution of the CyanoHABs in Dianchi Lake, and analysed spatial–temporal dynamics of the CyanoHABs by correlation with nutrition, meteorological, and humanities data. The results showed that the first outbreak of CyanoHABs in Dianchi Lake occurred in 1987, which is likely to be influenced by a rapid increase of nutrients in the lake, while the weather conditions also have some impact on the CyanoHABs occurrence. After 1990, the frequency of CyanoHABs is relatively high in the water near Longmen village, Fubao Bay, Hui Bay, and the lake inlet of the Panlong River to the north of Waihai in Dianchi Lake from June to November every year. Moreover, the CyanoHABs increased year by year until 2000. This is closely related to population growth and economic development. Furthermore, a large amount of precipitation and small wind speeds can also promote the occurrence of CyanoHABs. After 2000, the frequency of CyanoHABs decreased, as the large-scale management of water pollution in Dianchi Lake achieved certain effects. The area and frequency of CyanoHABs from 2011 to 2014 are the smallest in the last 20 years, which may be related to the large-scale planting of Eichhornia crassipes in the north of Dianchi Lake.     

Dynamics of quantum correlation for a qubit–qutrit system in the presence of the dephasing environments

We analytically study the dynamic behaviors of quantum correlation measured by three kinds of measures including quantum discord (QD), geometric quantum discord (GQD) and one-norm GQD for a qubit–qutrit system under the influence of dephasing environments with Ohmic-like spectral densities at nonzero temperature. It is shown that the similar evolution behaviors may be obtained for sub-Ohmic and Ohmic reservoirs. By properly choosing the system’s initial states and reservoir temperature, quantum correlation can take on some interesting results, such as the frozen and double sudden transition as well as the “revival” phenomenon, etc. Meanwhile, the remarkable similarities and differences among these correlation measures are also analyzed in detail and some significant results are presented. Our results provide some important information for the application of quantum correlation in hybrid qubit–qutrit systems in quantum information.     

Designing information fusion for the encoding of visual–spatial information

In a simulated aircraft navigation task, a fusion technique known as triangulation was used to improve the accuracy and onscreen availability of location information from two separate radars. Three experiments investigated whether the reduced cognitive processing required to extract information from the fused environment led to impoverished retention of visual–spatial information. Experienced pilots and students completed various simulated flight missions and were required to make a number of location estimates. Following a retention interval, memory for locations was assessed. Experiment 1 demonstrated, in an applied setting, that the retention of fused information was problematic and Experiment 2 replicated this finding under laboratory conditions. Experiment 3 successfully improved the retention of fused information by limiting its availability within the interface, which it is argued, shifted participants' strategies from over-reliance on the display as an external memory source to more memory-dependent interaction. These results are discussed within the context of intelligent interface design and effective human–machine interaction.     

Algorithm to determine the optimal parameters of a polynomial Wiener filter–extrapolator for nonstationary stochastic processes observed with errors

The apparatus of canonical expansions of stochastic processes is used to obtain an algorithm to determine the optimal parameters of a discrete polynomial Wiener filter–extrapolator for nonstationary stochastic processes with errors.     

Development of a functional model for a master–slave combined manipulator for laparoscopic surgery

Minimally invasive surgery helps patients by accelerating postoperative recovery. However, its application is impeded because it is necessary for the surgeons performing such surgery to possess surgical skills of a high order. Therefore, a master-slave combined manipulator (MCM) has been proposed as a robotic tool that enhances the surgeon's skill in laparoscopic surgery. The master grip and the slave hand are combined through the manipulator body, and a surgeon can operate the tool near the patient. The slave hand is controlled electrically by the master grip and its position is directly controlled by the surgeon. A prototype model of the MCM has been developed. The functions of the MCM have been verified by basic evaluation tests and the MCM has been used in a preliminary animal experiment. This paper describes the concept, the basic performance and the validation of the MCM.     

Applying fuzzy arithmetic to the system dynamics for the customer–producer–employment model

This paper presents a system dynamics analysis based on the application of fuzzy arithmetic. Traditional crisp system dynamics observe that some variables/parameters may belong to the uncertain factors. It is necessary to extend the system dynamics to treat also the vague variables/parameters. The evaluation of fuzzy system dynamics may provide the decision-maker information regarding the system's behavior uncertainties. In this paper, the customer–producer–employment model is examined with the fuzzy system dynamics in two types of fuzzy arithmetic, α-cut fuzzy arithmetic and T_ω weakest t-norm operator. Symmetrical and nonsymmetrical triangular fuzzy number (TFN), varied amount of fuzzy inputs’ fuzziness, and length of the system time delay are examined with useful results provided. Particularly, it is revealed that (1) both types of fuzzy arithmetic can provide the steady-state analysis of the system's variables as their counterpart, the crisp arithmetic analysis. (2) The α-cut arithmetic realizes the fuzziness of the model interactive variables fuzzier than that of the T_ω fuzzy arithmetic due to the accumulating phenomenon of fuzziness of the α-cut arithmetic. The fuzzier the inputs, the higher the level and/or oscillation of the cyclically steady or stable pattern of the stability of these variables exhibit with the α-cut arithmetic. (3) The T_ω arithmetic gives a smaller fuzziness and defuzzified values due to the concept that it takes only the maximal fuzziness encountered and calculated in the operation. In this case, the T_ω arithmetic provides more stable (or conversely less sensitive) results to the amount of fuzziness and nonsymmetricity (fuzziness) of input.     

Bifurcation diagrams for the moments of a kinetic type model of keloid–immune system competition

The mathematical modelling of the keloid disease triggered by a virus has been recently investigated by one of the authors, Bianca (2011) [5], where it was shown that the model is able to depict the emerging behaviours which occur during the keloid formation.This paper deals with further numerical investigations of that model related to the bifurcation analysis of the measurable macroscopic variables associated to each functional subsystem. It is shown that there exists a critical value of a bifurcation parameter separating situations where the immune system controls the keloid formation from those where malignant effects are not contrasted.     

A lightweight model with spatial–temporal correlation for cellular traffic prediction in Internet of Things

The Journal of Supercomputing - Accurate cellular traffic prediction becomes more and more critical for efficient network resource management in the Internet of Things (IoT). However, high-accuracy...     

STTG-TTE: spatial–temporal gated multi-modality approach for travel time estimation based on temporal convolutional networks

Neural Computing and Applications - Travel time forecasting has become a core component of smart transportation systems, which assists both travelers and traffic organizers with route planning,...     

Computing the regularization of a linear differential–algebraic system

We study the regularization problem for linear differential–algebraic systems. As an improvement of former results we show that any system can be regularized by a combination of state-space and input-space transformations, behavioral equivalence transformations and a reorganization of variables. The additional state feedback which is needed in earlier publications is shown to be superfluous. We provide an algorithmic procedure for the construction of the regularization and discuss computational aspects.     

Development and application of a model for analysis and design phases of Web-based system development

The major characteristics of Web systems that shall be taken into account can be summarized as follows: First, the implementation of Web systems shall have a beneficial effect. To meet the requirements of Internet business system, the Web systems shall enable businesses to provide customers with something valuable through the Internet and profit from this process in return[1]. Second, the way to express the contents on the Web matters. To express the contents, Web systems shall introduce mu…     

A novel type of a microfluidic system using ferrofluids for an application of μ-TAS

This paper shows the novel type of microfluidic system for the purpose of applications to delivery systems, which is the core device of -TAS (micro Total Analysis System) in medicine and biology. The proposed microfluidic control device in this work has been designed for precisely actuating and fast sampling in submicroliter range. Also, the biological liquids have not been contaminated since they have been isolated from the ferrofluids. The magnetic dipoles in ferrofluids line up with the applied field due to the permanent magnet with surface gauss 3400. The maximum net pressure by ferrofluid flows in the rounded microchannel was more than 2 kPa. The device was fabricated by MEMS technology with silicon wafer. The stepping motor with 20 steps was used for the control of delivering the liquids. One step makes the permanent magnet move 18° in the circumferential direction and the liquids can be sampled in nanoliter level. This study presents a significant point that a microfluidic delivery system for sampling biological liquids with high pressure in a microchannels can be integrated in -TAS.This work was supported by the Korea Research Fundation Grant (KRF-2002–005-D00003).