Time-space Matrix Research Articles

Biomedical, Biopsychosocial, and Biocognitive: A Point-to-Point Comparison of Models in Psychiatry

Mainstream psychiatry claims scientific status, relying on two essentially incompatible models to justify that claim. The first, the reductionist biomedical model, is based on the physicalist ontology that there is nothing in the universe beyond matter and energy interacting in the time–space matrix. The second, the biopsychosocial model, is dualist in that it allows room for causally significant psychological events to play a part in the etiology of mental disorders. More recently, the biocognitive model, a formal model of dualist interaction, offers a third path. This article sets out criteria for models and shows that neither the biomedical nor the biopsychosocial model satisfy those criteria, not least because they do not exist in a form recognizable as a scientific model. The biocognitive model is the only model available today that can provide a valid basis for psychiatry as a nonreductionist science.

A surveillance system for urban buried pipeline subject to third-party threats based on fiber optic sensing and convolutional neural network

Third-party threats, such as construction activities and man-made sabotage, have become the main cause of pipeline accidents in recent years. This article proposes a surveillance system for protecting the buried municipal pipelines from third-party damage based on distributed fiber optic sensing and convolutional neural network (CNN). Due to the ability of detecting very small perturbation, the phase-sensitive optical time-domain reflectometry (φ-OTDR) is employed for distributed vibration measurements along the pipelines. A two-layer classifier based on CNN is developed: one layer is used to discriminate the third-party activities from the environmental disturbance; the other is to determine the specific type of the third-party events. Meanwhile, a time-space matrix is introduced to reduce the false alarm and correct possible errors by taking into account the continuity of the signals in time and space. Field tests are carried out to validate the effectiveness of the proposed surveillance system. The recognition results show that the CNN-based classifiers achieve the accuracy of over 97%, which is 14.8% higher than that of the traditional feature-based machine learning method using random forest (RF) algorithm. It also indicates that the time-space matrix can dramatically reduce the false alarm and enhance the recognition accuracy.

RETRACTED ARTICLE: Prediction architecture of deep learning assisted short long term neural network for advanced traffic critical prediction system using remote sensing data

ABSTRACT This paper presents a Neural Convolutional Network (NCN) based approach for learning traffic as images and predicting high accuracy network-wide broad traffic speed. In the recent past, images describe time and space of traffic flow, where a 2-dimensional time-space matrix is used to convert space dynamics. In recent years, neural networks have been widely used for the prediction of short term traffic, where the description is covered by an NCN in two consecutive steps: abstract data extraction and network-wide traffic forecast. This paper proposes Prediction Architecture of Neural Convolutional Short Long Term Network (PANCSLTN) for the purpose of effectively capturing dynamic nonlinear traffic systems with deep learning assistance. The PANCSLTN can resolve the problem of backdated decay error via memory blocks and shows superior prediction capacity for time series with long-time dependency. Moreover, PANCSLTN can determine the optimum time laggards automatically and the travel data from Beijing microwave traffic detectors which are used for model the training and testing to validate the effective PANCSLTN using remote sensing technique. PANCSLTN can deliver the most accurate and stable prediction performance compared to different topologies in dynamical neural resealing networks or other dominant parametric and nonparametric algorithms during experimental analysis.

From Rivers to Confetti: Reconfigurations of Time through New Media Narratives

From Rivers to Confetti: Reconfigurations of Time through New Media Narratives

On the nonlinear transformation of breaking and non-breaking waves induced by a weakly submerged shelf

The interaction of regular quasi-monochromatic waves with a weakly submerged rectangular shelf is studied by means of CFD simulations. The fundamental incident wave frequency is kept constant for the full set of simulated cases, while the incident wave amplitude is made increase progressively, so that the interaction with the shelf is dominated by almost inviscid non-linear flow for the smallest and by breaking for the highest incident waves. A parameter identification (PI) procedure is used to adapt a reduced model to the highly resolved time-space matrix of wave elevations obtained from the numerical simulations, on the weather and lee side respectively. In particular the wave number and the frequency of the component waves in the reduced model are left uncoupled, thus computed by the PI independently. The comparison of simulated data with experiments generally shows a very good agreement. Free/locked, incident/reflected, first/higher order wave components are quantified accurately by the PI and the energy transfer to super-harmonics is clearly evidenced. Moreover the results of the PI show clearly a very large increase in the phase speed of the higher order free waves on the lee side of the shelf, with increasing deviation from the linear behavior with increasing incident wave amplitude.

A continuous gas leakage localization method based on an improved beamforming algorithm

A continuous gas leakage localization method based on an improved beamforming algorithm is proposed and experimentally demonstrated. The ultrasonic signals excited by the leakage are collected by the contact-coupled piezoelectric ultrasonic sensor array, afterward, the time-space matrix of the leakage signal is calculated, and through analyzing the matrix, the position of the leakage hole can be obtained. The measured phase velocity is taken into account in the method to compensate the effect of frequency dispersion. Localization experiments were carried out on a flat plate and a stiffened plate, demonstrating that the proposed method can successfully locate the continuous gas leakage in both the near and far field cases. In addition, the experiment results indicate that frequency dispersion compensation can reduce the localization error efficiently. The method is demonstrated to achieve the mean errors of 3.74mm and 8.59mm, for an area of 1m×1m on the flat and stiffened plates, respectively.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

Mining the time-space matrix

This article examines turn-of-the-twentieth-century US world’s fairs and the postage stamps that were issued in their honor. The fairs celebrated the progress of industrial civilization, in part by anchoring themselves to a historical origin point (such as Columbus’ voyages), and the post office designed the accompanying stamps to commemorate a historical story deemed to be nationally significant. Both the origin point and the history associated with it were located within a time-space matrix defined by prior processes of mapping the national territory and standardizing time reckoning within it. The commemorative stamps were sold on the fairgrounds, where they could be postmarked to locate them precisely in time and space as souvenirs of what would become past events that would have value in the future. These overlain commemorative practices reveal how the raw materials of history—time and space—have to be manipulated before the history-making practices of modern societies can even begin.

The dialogical self as a time–space matrix: Personal chronotopes and ambiguous signifiers

Dialogical self theory makes explicit use of spatial metaphors. The self is conceptualized as a ‘landscape’ of decentralized ‘I-positions’. While this captures the flux of our experience, our ‘positioning’ also has continuities over time – a requirement for the telling of history. Hence the dialogical self in its extension might be better conceived as a time–space matrix. Bakhtin called this matrix the “chronotope” and he used it to analyze literary forms. Here, I adapt the concept as a means to study the development of the dialogical self. A model for ‘personal chronotopes’ is proposed using ‘dialogical triads’. Triads are comprised of an I-position, a counter-position, and an ambiguous signifier from the social domain (e.g., a powerful person). Ambiguous signifiers promote decentralizing movements in the self. I propose that personal chronotopes are comprised of a temporally organized string or sequence of dialogical triads. Their emergence is illustrated here using case material.

The Supply Chain Strategy Conundrum: To be Lean Or Agile or To be Lean And Agile?

There has been a tendency recently to see "lean" and "agile" as two distinct models of business operations. In this paper, the authors seek to reconcile the two paradigms and through case study examples show how they may successfully be combined. A fundamental requirement is that supply chain design be linked to corporate strategy and the needs of the market-place. Lean and agile principles are then juxtaposed according to the requisite business strategy via a time-space matrix. This determines whether the lean-agile principles are separated by time, by space or by both space and time.

Estimating the incubation period of raccoon rabies: a time–space clustering approach

We used a time–space clustering approach to estimate the incubation period of raccoon rabies in the wild using data from the 1999–2001 invasion of raccoon rabies into eastern Ontario from northern New York State. The time differences and geographical distances between all possible pairs of rabies cases were computed, classified and assembled into a time–space matrix. The rows of that matrix represented differences in cases in weeks and the columns represent distances between cases in kilometers and the values in the cells of the matrix represent the counts of cases at specific time and distance intervals. There was a significant cluster of pairs 5 weeks apart with apparent harmonics at additional 5-week intervals. These results are explained by assuming the incubation period of raccoon rabies had a mode of 5 weeks. The time clusters appeared consistently at distance intervals of 5 km. We discuss the possibility that the spatial intervals were influenced by the 5 km radius of the point infection control depopulation process used in 1999 and the 10–15 km radial areas used in 2000. With the practical limits of those radii, there was an intensive effort to eliminate raccoons. Our procedure is easy to implement and provides an estimate of the shape of the distribution of incubation periods for raccoon rabies.

Spatial patterns of the yellowfin tuna (Thunnus albacares) in the Eastern Pacific Ocean: an exploration of concentration profiles

The spatial distribution of the yellowfin tuna (Thunnus albacares) abundance in the Eastern Pacific Ocean was studied from commercial catches by the Mexican tuna-fishing fleet. Concentration profiles were carried out as indicators of a realtionship between catch-per-unit effort (CPUE) and fish abundance for the period from 1992 to 1996. Spatial and temporal resolution "units" were defined by means of a semi-variogram and serial correlation analyses, respectively. The unit resolutions obtained for catch data were 1 × 1 degree (spatial) and monthly (temporal). Catch values were standardized by means of robust regression. Fish resource spatial distribution patterns were identified and estimated catch-values were obtained with Generalized Additive Models. From these estimates, a CPUE time-space matrix CPUE was defined with 60 months and 1029 locations. Nine timespace patterns explained more than 80% of the variability. Individual spatial patterns were analyzed and spatial regions were defined with homogeneous CPUE values. Similarities between the CPUE and the concentration profiles (covered area) suggest that the CPUE-relative abundance relationship is not directly proportional which indicates hyperdepletion processes. Fishery management implications are also discussed in this study.

ITER Test Program: Key Technical Aspects

ITER is envisioned to operate in two phases: the Physics Phase, ∼ 6 yrs, is devoted to the physics issues followed by the Technology Phase, ∼ 8 yrs, used mainly for technology testing. The nuclear testing program of ITER is intended to provide powerful, albeit partial, demonstration of the ultimate potential of a fusion blanket. The ITER test group, which consists of a number of ITER designers and experts from the home teams concerned with the long-term development of fusion technology, has carried out several tasks, including: 1) Definition of the testing requirements on the major parameters of ITER; 2) Definition of the test program (time-space matrix and priorities of tests); 3) Engineering design of test modules; 4) Ancillary equipment to support test module operation and 5) Allocation of available test space among countries. Recommended ITER parameters are: neutron wall load ∼ 1 MW/M2, lifetime neutron fluence ∼ 3 MW y/m2 and several periods of continuous operation (∼ 100% availability with back to back pulses or steady state) of ∼ 1 to 2 weeks each. The requirements on plasma burn and dwell times are quantified. Steady state operation is a desirable goal. If this goal cannot be achieved, a burn time of ∼ 1 to 3 hours, depending on the breeder temperature, is needed for tritium release tests in solid breeders. The requirements for ancillary equipment outside the torus, required to support the test modules (e.g., heat rejection systems, tritium processing, etc.) are extensive and they substantially influence the overall design engineering. The space available for testing in ITER is not sufficient for 4 complete programs (one for each country). An effective strategy for allocation of test ports among countries is being evolved. It involves a combination of collaboration on some tests, and allocation of testing space and time by party.

Reconstruction of diffusion processes at local scales: the 1846, 1882 and 1904 measles epidemics in northwest Iceland

Because medical records of individuals contracting measles were not kept in northwest lceland for epidemics before 1904, the spread of the disease in 1846 and 1882 has been traced from notifications of death recorded in burial registers and census returns. Using this evidence, a time-space matrix of measles deaths has been constructed and the dynamics of the diffusion process through a necklace of small communities strung along the coast has been analysed. In each of the three epidemics the mortality curve corresponded closely to an S-shaped logistic model, each new epidemic passing through the area more rapidly than its predecessor. The operation of a neighbourhood effect from a single point of introduction implies that the disease should move in a wave-like form through the area. Whereas the 1882 epidemic advanced steadily as a wave-front progression characteristic of the neighbourhood effect, those of 1846 and 1904 had strong spatial biases towards the parish of Eyri. The intense localization of the outbreaks in 1846 and 1904 appears not to be related directly to distinctive features in the demography or form of the settlement. In 1904 a confirmation service held in Eyri church brought many victims into contact with a measles carrier, but no special circumstances have been reported or can be deduced for 1846.