Search results for: temporal gravity variations

Authors: Priya Varma, Denis John McKeown

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Psychological time, unlike physical time, is believed to be ‘compressive’ in the sense that the mental representations of a series of events may be internally arranged with ever decreasing inter-event spacing (looking back from the most recently encoded event). If this is true, the record within immediate memory of recent events is severely temporally distorted. Although this notion of temporal distortion of the memory record is captured within some theoretical accounts of human forgetting, notably temporal distinctiveness accounts, the way in which the fundamental nature of the distortion underpins memory and forgetting broadly is barely recognised or at least directly investigated. Our intention here was to manipulate the spacing of items for recall in order to ‘reverse’ this supposed natural compression within the encoding of the items. In Experiment 1 three schedules of presentation (expanding, contracting and fixed irregular temporal spacing) were created using logarithmic spacing of the words for both free and serial recall conditions. The results of recall of lists of 7 words showed statistically significant benefits of temporal isolation, and more excitingly the contracting word series (which we may think of as reversing the natural compression within the mental representation of the word list) showed best performance. Experiment 2 tested for effects of active verbal rehearsal in the recall task; this reduced but did not remove the benefits of our temporal scheduling manipulation. Finally, a third experiment used the same design but with Chinese characters as memoranda, in a further attempt to subvert possible verbal maintenance of items. One change to the design here was to introduce a probe item following the sequence of items and record response times to this probe. Together the outcomes of the experiments broadly support the notion of temporal compression within immediate memory.

Keywords: memory, serial position curves, temporal isolation, temporal schedules

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Authors: Yumei Wu, Xiaoyan Dang, Shenglong Yang, Shengmao Zhang

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The East China Sea is one of four main seas in China, where there are many fishery resources. Some important fishing grounds, such as Zhousan fishing ground important to society. But the eco-environment is destroyed seriously due to the rapid developing of industry and economy these years. In this paper, about twenty-year satellite data from MODIS and the statistical information of marine environment from the China marine environmental quality bulletin were applied to do the research. The chlorophyll-a concentration data from MODIS were dealt with in the East China Sea and then used to analyze the features and variations of plankton biomass in recent years. The statistics method was used to obtain their spatial and temporal features. The plankton biomass in the Yangtze River estuary and the Taizhou region were highest. The high phytoplankton biomass usually appeared between the 88th day to the 240th day (end-March - August). In the peak time of phytoplankton blooms, the Taizhou islands was the earliest, and the South China Sea was the latest. The intensity and period of phytoplankton blooms were connected with the global climate change. This work give us confidence to use satellite data to do more researches about the China Sea, and it also provides some help for us to know about the eco-environmental variation of the East China Sea and regional effect from global climate change.

Keywords: the East China Sea, phytoplankton biomass, temporal and spatial variation, phytoplankton bloom

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Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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Authors: Zongjie Wang, Zhizhong Guo

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While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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The aim of the paper is to analyze the characteristics of winter fog in terms of its trend and spatial-temporal variability over Indo-Gangetic plains. The study reveals that during last four and half decades (1971-2015), an alarming increasing trend in fog frequency has been observed during the winter months of December and January over the study area. The frequency of fog has increased by 118.4% during the peak winter months of December and January. It has also been observed that on an average central part of IGP has 66.29% fog days followed by west IGP with 41.94% fog days. Further, Empirical Orthogonal Function (EOF) decomposition and Mann-Kendall variation analysis are used to analyze the spatial and temporal patterns of winter fog. The findings have significant implications for the further research of fog over IGP and formulate robust strategies to adapt the fog variability and mitigate its effects. The decision by Delhi Government to implement odd-even scheme to restrict the use of private vehicles in order to reduce pollution and improve quality of air may result in increasing the alarming increasing trend of fog over Delhi and its surrounding areas regions of IGP.

Keywords: fog, climatology, spatial variability, temporal variability

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Authors: Jisun Lee, Jay Hyoun Kwon

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As an alternative way to compensate the INS (inertial navigation system) error in non-GNSS (Global Navigation Satellite System) environment, geophysical database referenced navigation is being studied. In this study, both gravity gradient and terrain data were combined to complement the weakness of sole geophysical data as well as to improve the stability of the positioning. The main process to compensate the INS error using geophysical database was constructed on the basis of the EKF (Extended Kalman Filter). In detail, two type of combination method, centralized and decentralized filter, were applied to check the pros and cons of its algorithm and to find more robust results. The performance of each navigation algorithm was evaluated based on the simulation by supposing that the aircraft flies with precise geophysical DB and sensors above nine different trajectories. Especially, the results were compared to the ones from sole geophysical database referenced navigation to check the improvement due to a combination of the heterogeneous geophysical database. It was found that the overall navigation performance was improved, but not all trajectories generated better navigation result by the combination of gravity gradient with terrain data. Also, it was found that the centralized filter generally showed more stable results. It is because that the way to allocate the weight for the decentralized filter could not be optimized due to the local inconsistency of geophysical data. In the future, switching of geophysical data or combining different navigation algorithm are necessary to obtain more robust navigation results.

Keywords: Extended Kalman Filter, geophysical database referenced navigation, gravity gradient, terrain

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Authors: Said Elkassimi, Said Safi, B. Manaut

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This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

Keywords: adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF

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Authors: Faroudja Meziani, Amar Kahil

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In order to study the variation in settlement of soil under a dyke dam, the modelisation in our study consists of applying an imposed displacement at the base of the mass of soil (consisting of a saturated sand). The imposed displacement follows the evolution of acceleration of the earthquake of Boumerdes 2003 in Algeria. Moreover, the gravity load is taken into consideration by taking account the specific weight of the materials constituting the dyke. The results obtained show that the gravity loads have a direct influence on the evolution of settlement, especially at the center of the dyke where these loads are higher.

Keywords: settlement, dynamic analysis, rockfill dam, effect of earthquake, soil dynamics

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: G. Sarwar, C. Mateus, N. Todorovic

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The paper examines the asymmetries in size, value and momentum premium over the economic cycles in the UK and their macroeconomic determinants. Using Markov switching approach we find clear evidence of cyclical variations of the three premiums, most noticeably variations in size premium. We associate Markov switching regime 1 with economic upturn and regime 2 with economic downturn as per OECD’s Composite Leading Indicator. The macroeconomic indicators prompting such cyclicality the most are interest rates, term structure and credit spread. The role of GDP growth, money supply and inflation is less pronounced in our sample.

Keywords: macroeconomic determinants, Markorv Switching, size, value

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Authors: Ping Li, Bing Feng, Junpu Zhao, Xudong Xie, Dangpeng Xu, Kuixing Zheng, Qihua Zhu, Xiaofeng Wei

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In laser driven inertial confinement fusion (ICF), the control of the temporal shape of the laser pulse is a key point to ensure an optimal interaction of laser-target. One of the main difficulties in controlling the temporal shape is the foot part control accuracy of high contrast pulse. Based on the analysis of pulse perturbation in the process of amplification and frequency conversion in high power lasers, an approach of beam spatio-temporal multiplexing is proposed to improve the control precision of high contrast pulse. In the approach, the foot and peak part of high contrast pulse are controlled independently, which propagate separately in the near field, and combine together in the far field to form the required pulse shape. For high contrast pulse, the beam area ratio of the two parts is optimized, and then beam fluence and intensity of the foot part are increased, which brings great convenience to the control of pulse. Meanwhile, the near field distribution of the two parts is also carefully designed to make sure their F-numbers are the same, which is another important parameter for laser-target interaction. The integrated calculation results show that for a pulse with a contrast of up to 500, the deviation of foot part can be improved from 20% to 5% by using beam spatio-temporal multiplexing approach with beam area ratio of 1/20, which is almost the same as that of peak part. The research results are expected to bring a breakthrough in power balance of high power laser facility.

Keywords: inertial confinement fusion, laser pulse control, beam spatio-temporal multiplexing, power balance

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Hanaa A. S. Oraby, Amal A. M. Hassan, Mahmoud M. Sakr, Atef A. A. Haiba

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Applying the profiling approach for the assessment of proteomic variations due to genetic modification of the Egyptian tomato cultivar "Edkawy", three complementary approaches were used. These methods are amino acids analysis, gel electrophoresis, and Gas chromatography coupled with mass spectrometry (GC/MS). The results of the present study Show evidence of proteomic variations between both modified tomato and its non-modified counterpart. Amino acids concentrations, and the protein patterns separation on the 1D SDS-PAGE were not similar in the case of transformed tomato compared to that of the non-transformed counterpart. These detected differences are most likely derived from the process of transformation. Results also revealed that the efficiency of GC/MS approach to identify a mixture of unknown proteins is limited. GC/MS analysis was only able to identify few number of protein molecules. Therefore, more advanced and specific technologies like MALDI-TOF-MS are recommended to be employed.

Keywords: GMOs, unintended effects, proteomic variations, 1D SDS-PAGE, GC/MS

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Authors: Sameena Tarannum, S. Pranesh

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The effect of linear stability analysis of triple diffusive convection in a vertically oscillating viscoelastic liquid of Oldroyd-B type is studied. The correction Rayleigh number is obtained by using perturbation method which gives prospect to control the convection. The eigenvalue is obtained by using perturbation method by adopting Venezian approach. From the study, it is observed that gravity modulation advances the onset of triple diffusive convection.

Keywords: gravity modulation, Oldroyd-b liquid, triple diffusive convection, venezian approach

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Shield B. Lin, Ziraguen O. Williams

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In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.

Keywords: control, counterweight, isolation, vibration

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatio-temporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web mapping, indicator of drought

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Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: multi-temporal satellite image, urban growth, non-stationary, stochastic model

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Authors: Ya-Mei Chang

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This research is intended to apply spatio-temporal point process methods to the dengue fever data in Tainan. The spatio-temporal intensity function of the dataset is assumed to be separable. The kernel estimation is a widely used approach to estimate intensity functions. The intensity function is very helpful to study the relation of the spatio-temporal point process and some covariates. The covariate effects might be nonlinear. An nonparametric smoothing estimator is used to detect the nonlinearity of the covariate effects. A fitted parametric model could describe the influence of the covariates to the dengue fever. The correlation between the data points is detected by the K-function. The result of this research could provide useful information to help the government or the stakeholders making decisions.

Keywords: dengue fever, spatial point process, kernel estimation, covariate effect

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Authors: Faisal Alsaaq

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Hydrographic surveys have traditionally relied on the availability of tide information for the reduction of sounding observations to a common datum. In most cases, tide information is obtained from tide gauge observations and/or tide predictions over space and time using local, regional or global tide models. While the latter often provides a rather crude approximation, the former relies on tide gauge stations that are spatially restricted, and often have sparse and limited distribution. A more recent method that is increasingly being used is Global Navigation Satellite System (GNSS) positioning which can be utilised to monitor height variations of a vessel or buoy, thus providing information on sea level variations during the time of a hydrographic survey. However, GNSS heights obtained under the dynamic environment of a survey vessel are affected by “non-tidal” processes such as wave activity and the attitude of the vessel (roll, pitch, heave and dynamic draft). This research seeks to examine techniques that separate the tide signal from other non-tidal signals that may be contained in GNSS heights. This requires an investigation of the processes involved and their temporal, spectral and stochastic properties in order to apply suitable recovery techniques of tide information. In addition, different post-mission and near real-time GNSS positioning techniques will be investigated with focus on estimation of height at ocean. Furthermore, the study will investigate the possibility to transfer the chart datums at the location of tide gauges.

Keywords: hydrography, GNSS, datum, tide gauge

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Authors: Md. Najiur Rahman

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This hypothesis reveals a profound and symmetrical connection that goes beyond the boundaries of quantum physics and cosmology, revolutionizing our understanding of the fundamental building blocks of the cosmos, given its name ‘The Theory of the Mystery’. This theory has an elegantly simple equation, “R = ∆r / √∆m” which establishes a beautiful and well-crafted relationship between the radius (R) of an elementary particle or galaxy, the relative change in radius (∆r), and the mass difference (∆m) between related entities. It is fascinating to note that this formula presents a super synchronization, one which involves the convergence of every basic particle and any single celestial entity into perfect alignment with its respective mass and radius. In addition, we have a Supporting equation that defines the mass-radius connection of an entity by the equation: R=√m/N, where N is an empirically established constant, determined to be approximately 42.86 kg/m, representing the proportionality between mass and radius. It provides precise predictions, collects empirical evidence, and explores the far-reaching consequences of theories such as General Relativity. This elegant symmetry reveals a fundamental principle that underpins the cosmos: each component, whether small or large, follows a precise mass-radius relationship to exert gravity by a universal law. This hypothesis represents a transformative process towards a unified theory of physics, and the pursuit of experimental verification will show that each particle and galaxy is bound by gravity and plays a unique but harmonious role in shaping the universe. It promises to reveal the great symphony of the mighty cosmos. The predictive power of our hypothesis invites the exploration of entities at the farthest reaches of the cosmos, providing a bridge between the known and the unknown.

Keywords: unified theory, quantum gravity, mass-radius relationship, dark matter, uniform gravity

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Authors: Elsie L. Echeverri-Carroll

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Entrepreneurial ecosystems have become an important concept to explain the birth and sustainability of technology-based entrepreneurship within regions. However, as a theoretical concept, the temporal evolution of entrepreneurship systems remain underdeveloped, making it difficult to understand their dynamic contributions to entrepreneurs. This paper argues that successful technology-based ecosystems go over three cumulative spawning stages: corporate spawning, entrepreneurial spawning, and community spawning. The importance of corporate incubation in vibrant entrepreneurial ecosystems is well documented in the entrepreneurial literature. Similarly, entrepreneurial spawning processes for venture capital-backed startups are well documented in the financial literature. In contrast, there is little understanding of both the third stage of entrepreneurial spawning (when a community of entrepreneurs become a source of firm spawning) and the temporal sequence in which spawning effects occur in a region. We test this three-stage model of entrepreneurial spawning using data from two large databases on firm births—the Secretary of State (160,000 observations) and the National Establishment Time Series (NEST with 150,000 observations)—and information collected from 60 1½-hour interviews with startup founders and representatives of key entrepreneurial organizations. This temporal model is illustrated with case study of Austin, Texas ranked by the Kauffman Foundation as the number one entrepreneurial city in the United States in 2015 and 2016. The 1½-year study founded by the Kauffman Foundation demonstrates the importance of taken into consideration the temporal contributions of both large and entrepreneurial firms in understanding the factors that contribute to the birth and growth of technology-based entrepreneurial regions. More important, these learnings could offer an important road map for regions that pursue to advance their entrepreneurial ecosystems.

Keywords: entrepreneurial ecosystems, entrepreneurial industrial clusters, high-technology, temporal changes

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Authors: Najla Kamergi

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In a world context of increasing interest in environmental issues, this paper investigates the effect of agri-environmental regulations heterogeneity on the volume of crop commodities’ exports using a theoretically justified gravity model of Anderson and van Wincoop (2003) for the 2003–2013 period. Our findings show that the difference in exporter and importer environmental regulations is more relevant to agricultural trade than trade agreements. In fact, the environmental gap between the two partners is decreasing slightly but significantly crop commodities’ exports according to our results. We also note that the sector of fruit and vegetables is more sensitive to this determinant, unlike cereals that remain relatively less affected. Furthermore, high-income countries have more tendency to trade with countries characterized by similar environmental stringency. Further results show that the BRICS are clearly importing from developed countries where the environmental difference is relatively important. It is likely that emerging countries are witnessing a growing demand for high-quality and “green” crop commodities captured by high-income exporters. Surprisingly, our results suggest that low and middle-income countries with the same level of environmental stringency are more likely to trade crop commodities.

Keywords: agricultural trade, environment, gravity model, food crops, agri-environmental efficiency, DEA

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Authors: Cunyu Zhang

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Through literature review about studies related to tense, it is found that there exist disagreements on the definition and existence of Chinese tense. Influenced by some researches on English language which regard tense as a grammatical category based on the verbal inflections of English, some Chinese researchers claim that there is no tense in Chinese language as there are no verbal inflections involved. Meanwhile, other Chinese researchers hold that Chinese still has tense although its verbs are non-inflectional based on the fact that Chinese lexical expressions can imply temporal meaning. We assume that the reasons for the above disagreements in terms of Chinese tense lie in the fact that all the previous studies prefer to view language “from the below” which means expressions of tense are the core part of these studies. However, there are about 6,000 languages with distinct expressions all over the world. Hence, if the language studies only concentrate on expressions, it must become more difficult to understand the nature of language. By contrast, functions of languages are similar; otherwise, the human beings could not communicate with each other. Therefore, we believe that it is necessary for us to have a theoretical study on Chinese tense within the framework of SFL which holds that language is a system where meaning is the core part while form is just the realization of meaning. In addition, SFL is a general linguistic providing a universal framework for languages all over the world. Therefore, based on Systemic Functional Linguistics, the paper firstly redefines tense as a deictic semantic category for describing the speaker’s temporal location of processes and relevant temporal relations. With reference to this definition, this study explores the meaning system of tense. It is proposed that tense expresses four kinds of meaning, namely interpersonal, experiential, logical and textual meanings. From the interpersonal angle, tense helps to exchange temporal information between the speaker and the listener, and the temporal information refers to the anchoring of a concerned process in the past, present or future by the speaker. From the experiential angle, tense plays a role in the temporal locating of material, mental, relational, existential, behavioral and verbal processes by the speaker. From the logical angle, tense denotes the temporal relations at the two levels of clause and clause complex, and such relations fall into simultaneity, anteriority and posteriority. From the textual angle, tense refers to the temporal relations at the level of text, and the temporal relations in question concern linear serial relations and synchronous serial relations.

Keywords: Chinese, meaning system, Systemic Functional Linguistics, tense

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Authors: O. Maklouf, Ahmed Abdulla

Abstract:

A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers are looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.

Keywords: GPS, ParIMU, INS, Kalman filter

Procedia PDF Downloads 498

Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

Abstract:

Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

Procedia PDF Downloads 75

Authors: Sijo Varghese

Abstract:

A space craft (E. M. Tractor) which is intended to deflect or tug the asteroids which possesses threat towards the planets is the whole idea behind this paper. In this case "Electro Magnetic Induction" is used where it is known that when two separate circuits are connected to the electro magnet and on application of electric current through the one circuit in to the coil induces magnetic fields which repels the other circuit.( Faraday's law of Electromagnetic Induction). Basically a Spacecraft is used to attach a large sheet of aluminum on to the surface of the asteroid, the Spacecraft acts as an electro magnet and the induced magnetic field would eventually repel the aluminum intern repelling the asteroid. This method would take less time as compared to use of gravity( which requires a larger spacecraft and process will take a long time).

Keywords: asteroids, electro magnetic induction, gravity, electro magnetic tractor

Procedia PDF Downloads 474

Authors: Ehssan M. R. Nassef

Abstract:

De-waxing of vacuum distillates by using solvent was investigated in the present study. The present work deals with studying solvent dewaxing system which have been developed to give better dewaxing performance with respect to the important factors in the choice of solvents which are good solubility of oil in the solvent and low solubility of wax in the solvent. In this study, solvent dewaxing process using Methyl Ethyl Ketone (MEK) and toluene are used for Egyptian vacuum distillates using two types of distillates. The effect of varying the composition of(MEK to toluene) on the percent yield of the oil, percent of wax, pour point, refractive index at 20 and 70°C, viscosity at 40 and 100°C, viscosity index and specific gravity of the oil produced for the two types of distillates (I & II) were evaluated. In the present study, the operating conditions of solvent dewaxing using MEK toluene mixture achieved the best pour point at -15°C for distillate I at (1:1) solvent composition mixture. At the same ratio of MEK to toluene the best specific gravity of oil produced changed from 0.871 to 0.8802, with refractive index of 1.84. Percent yield of 65% for oil was obtained. The results for distillate II, of higher specific gravity, are comparatively higher than those for distillate I. The effect of temperature was also investigated and the best temperature was -20°C.

Keywords: dewaxing, solvent dewaxing, pour point, lubricating oil production, wax

Procedia PDF Downloads 517