Search results for: medial temporal atrophy

Authors: Ahmad Aljaafreh

Abstract:

This paper proposes a hierarchical hidden Markov model (HHMM) to model the detection of M vehicles in a wireless sensor network (WSN). The HHMM model contains an extra level of hidden Markov model to model the temporal transitions of each state of the first HMM. By modeling the temporal transitions, only those hypothesis with nonzero transition probabilities needs to be tested. Thus, this method efficiently reduces the computation load, which is preferable in WSN applications.This paper integrates several techniques to optimize the detection performance. The output of the states of the first HMM is modeled as Gaussian Mixture Model (GMM), where the number of states and the number of Gaussians are experimentally determined, while the other parameters are estimated using Expectation Maximization (EM). HHMM is used to model the sequence of the local decisions which are based on multiple hypothesis testing with maximum likelihood approach. The states in the HHMM represent various combinations of vehicles of different types. Due to the statistical advantages of multisensor data fusion, we propose a heuristic based on fuzzy weighted majority voting to enhance cooperative classification of moving vehicles within a region that is monitored by a wireless sensor network. A fuzzy inference system weighs each local decision based on the signal to noise ratio of the acoustic signal for target detection and the signal to noise ratio of the radio signal for sensor communication. The spatial correlation among the observations of neighboring sensor nodes is efficiently utilized as well as the temporal correlation. Simulation results demonstrate the efficiency of this scheme.

Keywords: Classification, decision fusion, fuzzy logic, hidden Markov model

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Authors: Sallama Athab, Hala Bahjat, Zhang Yinghui

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Background detection is essential in video analyses; optimization is often needed in order to achieve real time calculation. Information gathered by dual cameras placed in the front and rear part of an Autonomous Vehicle (AV) is integrated for background detection. In this paper, real time calculation is achieved on the proposed technique by using Priority Regions (PR) and Parallel Processing together where each frame is divided into regions then and each region process is processed in parallel. PR division depends upon driver view limitations. A background detection system is built on the Temporal Difference (TD) and Gaussian Filtering (GF). Temporal Difference and Gaussian Filtering with multi threshold and sigma (weight) value are be based on PR characteristics. The experiment result is prepared on real scene. Comparison of the speed and accuracy with traditional background detection techniques, the effectiveness of PR and parallel processing are also discussed in this paper.

Keywords: Autonomous Vehicle, Background Detection, Dual Camera, Gaussian Filtering, Parallel Processing.

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Authors: Arnab Bandyopadhyay, Anubhab Pal, Subhajit Debnath

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Climate change is a cumulative change in weather patterns over a period of time. Trend analysis using non-parametric Mann-Kendall test may help to determine the existence and magnitude of any statistically significant trend in the climatic data. Another index called Sen slope may be used to quantify the magnitude of such trends. A toolbar extension to ESRI ArcGIS named Arc Trends has been developed in this study for performing the above mentioned tasks. To study the temporal trend of meteorological parameters, 32 years (1971-2002) monthly meteorological data were collected for 133 selected stations over different agro-ecological regions of India. Both the maximum and minimum temperatures were found to be rising. A significant increasing trend in the relative humidity and a consistent significant decreasing trend in the wind speed all over the country were found. However, a general increase in rainfall was not found in recent years.

Keywords: Temporal trend, climate change, ArcGIS, Mann- Kendall test, Sen slope

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Authors: Tao Dai, Andy Adler, Behnam Shahrrava

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This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Keywords: Adaptive signal processing, affine projection algorithms, variable step-size adaptive algorithms, regularization.

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Authors: Muhammad Arslan Usman, Muhammad Rehan Usman, Soo Young Shin

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Live video streaming is one of the most widely used service among end users, yet it is a big challenge for the network operators in terms of quality. The only way to provide excellent Quality of Experience (QoE) to the end users is continuous monitoring of live video streaming. For this purpose, there are several objective algorithms available that monitor the quality of the video in a live stream. Subjective tests play a very important role in fine tuning the results of objective algorithms. As human perception is considered to be the most reliable source for assessing the quality of a video stream subjective tests are conducted in order to develop more reliable objective algorithms. Temporal impairments in a live video stream can have a negative impact on the end users. In this paper we have conducted subjective evaluation tests on a set of video sequences containing temporal impairment known as frame freezing. Frame Freezing is considered as a transmission error as well as a hardware error which can result in loss of video frames on the reception side of a transmission system. In our subjective tests, we have performed tests on videos that contain a single freezing event and also for videos that contain multiple freezing events. We have recorded our subjective test results for all the videos in order to give a comparison on the available No Reference (NR) objective algorithms. Finally, we have shown the performance of no reference algorithms used for objective evaluation of videos and suggested the algorithm that works better. The outcome of this study shows the importance of QoE and its effect on human perception. The results for the subjective evaluation can serve the purpose for validating objective algorithms.

Keywords: Objective evaluation, subjective evaluation, quality of experience (QoE), video quality assessment (VQA).

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Authors: Melissa C. LaDuke

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The use of new literacies within science classrooms needs to be balanced by teachers to both teach different forms of communication while assessing content area proficiency. Using new literacies such as Twitter and Facebook needs to be incorporated into science content area literacy studies in addition to continuing to use generally-accepted forms of scientific content area presentation which include scientific papers and textbooks. The research question this literature review seeks to answer is “What are some ways in which new forms of literacy are better suited to teach scientific content area literacy to 21st century learners?” The research question is addressed through a literature review that highlights methods currently being used to educate the next wave of learners in the world of science content area literacy. Both temporal discourse analysis (TDA) and critical discourse analysis (CDA) were used to determine the need to use new literacies to teach science content area literacy. Increased use of digital technologies and a change in science content area pedagogy were explored.

Keywords: Science content area literacy, new literacies, critical discourse analysis, temporal discourse analysis.

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Authors: Moumita Palchaudhuri, Sujata Biswas

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Drought is universally acknowledged as a phenomenon associated with scarcity of water. The Standardized Precipitation Index (SPI) expresses the actual rainfall as standardized departure from rainfall probability distribution function. In this study severity and spatial pattern of meteorological drought was analyzed in the Puruliya District, West Bengal, India using multi-temporal SPI. Daily gridded data for the period 1971-2005 from 4 rainfall stations surrounding the study area were collected from IMD, Pune, and used in the analysis. Geographic Information System (GIS) was used to generate drought severity maps for the different time scales and months of the year. Temporal SPI graphs show that the maximum SPI value (extreme drought) occurs in station 3 in the year 1993. Mild and moderate droughts occur in the central portion of the study area. Severe and extreme droughts were mostly found in the northeast, northwest and the southwest part of the region.

Keywords: Standardized Precipitation Index, Meteorological Drought, Geographical Information System, Drought severity.

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Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

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The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: Frame freezing, mean opinion score, objective assessment, subjective evaluation.

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Authors: Shun Hattori

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In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services with the Web-mined knowledge have begun to be developed for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, this paper introduces the simplest Web Sensor and spatiotemporallynormalized Web Sensor to extract spatiotemporal data about a target phenomenon from weblogs searched by keyword(s) representing the target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity analyses of coefficient correlation with temperature, rainfall, snowfall, and earthquake statistics per day by region of Japan Meteorological Agency as physical-world data: spatial granularity (region-s population density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and media granularity (weblogs vs. microblogs such as Tweets).

Keywords: Granularity analysis, knowledge extraction, spatiotemporal data mining, Web credibility, Web mining, Web sensor.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Copy detection, Adjacent pixel intensity difference quantization (APIDQ), DC image, Histogram feature.

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Authors: Yimeng Deng, Klarissa T.T. Chang

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The proliferation of user-generated content (UGC) results in huge opportunities to explore event patterns. However, existing event recommendation systems primarily focus on advanced information technology users. Little work has been done to address novice and low-literacy users. The next billion users providing and consuming UGC are likely to include communities from developing countries who are ready to use affordable technologies for subsistence goals. Therefore, we propose a design framework for providing event recommendations to address the needs of such users. Grounded in information integration theory (IIT), our framework advocates that effective event recommendation is supported by systems capable of (1) reliable information gathering through structured user input, (2) accurate sense making through spatial-temporal analytics, and (3) intuitive information dissemination through interactive visualization techniques. A mobile pest management application is developed as an instantiation of the design framework. Our preliminary study suggests a set of design principles for novice and low-literacy users.

Keywords: Event recommendation, iconic interface, information integration, spatial-temporal clustering, user-generated content, visualization techniques

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: Neural networks, motion detection, signature detection, convolutional neural network.

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Authors: Mohammed Saleem Tariq

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The enthusiasm for gluten avoidance in a growing market is met by improvements in sensitive detection methods for analysing gluten content. Paradoxically, manufacturers employ no such systems in the production process but continue to market their product as gluten free, a significant risk posed to an undetermined coeliac population. This paper resonates with an immunological response that causes gastrointestinal scarring and villous atrophy with the conventional description of personal injury. This thesis divulges into evaluating potential inadequacies of gluten labelling laws which not only present a diagnostic challenge for general practitioners in the UK but it also exposes a less than adequate form of available legal protection to those who suffer adverse reactions as a result of gluten digestion. Central to this discussion is whether a claim brought in misrepresentation, negligence and/or under the Consumer Protection Act 1987 could be sustained. An interesting comparison is then made with the legal regimes of neighboring jurisdictions furthering the theme of a legally un-catered for gluten kingdom.

Keywords: Coeliac, litigation, misrepresentation, negligence.

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Authors: Abegunde Linda, Adedeji Oluwatola

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It has become an increasing evident that large development influences the climate. There are concerns that rising temperature over developed areas could have negative impact and increase living discomfort within city boundaries. Temperature trends in Ibadan city have received little attention, yet the area has experienced heavy urban expansion between 1972 and 2014. This research aims at examining the impact of landuse change on surface temperature knowing that the built-up environment absorb and store solar energy, resulting into the Urban Heat Island (UHI) effect. The Landsat imagery was used to examine the landuse change for a period of 42 years (1972-2014). Land Surface Temperature (LST) was obtained by converting the thermal band to a surface temperature map and zonal statistic analyses was used to examine the relationship between landuse and temperature emission. The results showed that the settlement area increased to a large extent while the area covered by vegetation reduced during the study period. The spatial and temporal trends of surface temperature are related to the gradual change in urban landuse/landcover and the settlement area has the highest emission. This research provides useful insight into the temporal behavior of the Ibadan city.

Keywords: Landuse, LST, Remote sensing, UHI.

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Authors: Ritu Ahlawat

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Among all geo-hydrological relationships, rainfallrunoff relationship is of utmost importance in any hydrological investigation and water resource planning. Spatial variation, lag time involved in obtaining areal estimates for the basin as a whole can affect the parameterization in design stage as well as in planning stage. In conventional hydrological processing of data, spatial aspect is either ignored or interpolated at sub-basin level. Temporal variation when analysed for different stages can provide clues for its spatial effectiveness. The interplay of space-time variation at pixel level can provide better understanding of basin parameters. Sustenance of design structures for different return periods and their spatial auto-correlations should be studied at different geographical scales for better management and planning of water resources. In order to understand the relative effect of spatio-temporal variation in hydrological data network, a detailed geo-hydrological analysis of Betwa river catchment falling in Lower Yamuna Basin is presented in this paper. Moreover, the exact estimates about the availability of water in the Betwa river catchment, especially in the wake of recent Betwa-Ken linkage project, need thorough scientific investigation for better planning. Therefore, an attempt in this direction is made here to analyse the existing hydrological and meteorological data with the help of SPSS, GIS and MS-EXCEL software. A comparison of spatial and temporal correlations at subcatchment level in case of upper Betwa reaches has been made to demonstrate the representativeness of rain gauges. First, flows at different locations are used to derive correlation and regression coefficients. Then, long-term normal water yield estimates based on pixel-wise regression coefficients of rainfall-runoff relationship have been mapped. The areal values obtained from these maps can definitely improve upon estimates based on point-based extrapolations or areal interpolations.

Keywords: Catchment's runoff estimates, influence area regional regression coefficients, runoff yield series,

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: Lina Galinskaitė, Gytautas Ignatavičius

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Animal vehicle collisions (AVCs) affect human safety, cause property damage and wildlife welfare. The number of AVCs are increasing and creating serious implications for the animal conservation and management. Roe deer (Capreolus capreolus) and other large ungulates (moose, wild boar, red deer) are the most frequently collided ungulate with vehicles in Europe. Therefore, we analyzed temporal patterns of roe deer vehicle collisions (RDVC) occurring in Lithuania. Using a comprehensive dataset, consisting of 15,891 data points, we examined the influence of different time units (i.e. time of the day, day of week, month, and season) on RDVC. We identified accident periods within the analyzed time units. Highest frequencies of RDVC occurred on Fridays. Highest frequencies of roe deer-vehicle accidents occurred in May, November and December. Regarding diurnal patterns, most of RDVC occur after sunset and before sunset (during dark hours). Since vehicle collisions with animals showed temporal variation, these should be taken into consideration in developing statistical models of spatial AVC patterns, and also in planning strategies to reduce accident risk.

Keywords: Animal vehicle collision, diurnal patterns, road safety, roe deer, statistical analysis.

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Authors: Cecilia Nugraheni, Luciana Abednego

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Sudoku is a kind of logic puzzles. Each puzzle consists of a board, which is a 9×9 cells, divided into nine 3×3 subblocks and a set of numbers from 1 to 9. The aim of this puzzle is to fill in every cell of the board with a number from 1 to 9 such that in every row, every column, and every subblock contains each number exactly one. Sudoku puzzles belong to combinatorial problem (NP complete). Sudoku puzzles can be solved by using a variety of techniques/algorithms such as genetic algorithms, heuristics, integer programming, and so on. In this paper, we propose a new approach for solving Sudoku which is by modelling them as block-world problems. In block-world problems, there are a number of boxes on the table with a particular order or arrangement. The objective of this problem is to change this arrangement into the targeted arrangement with the help of two types of robots. In this paper, we present three models for Sudoku. We modellized Sudoku as parameterized multi-agent systems. A parameterized multi-agent system is a multi-agent system which consists of several uniform/similar agents and the number of the agents in the system is stated as the parameter of this system. We use Temporal Logic of Actions (TLA) for formalizing our models.

Keywords: Sudoku puzzle, block world problem, parameterized multi agent systems modelling, Temporal Logic of Actions.

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Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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Authors: N. Norazlimi, R. Ramli

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A study was conducted to determine the diversity and abundance of shorebird species habituating the mudflat area of Jeram Beach and Remis Beach, Selangor, Peninsular Malaysia. Direct observation technique (using binoculars and video camera) was applied to record the presence of bird species in the sampling sites from August 2013 until July 2014. A total of 32 species of shorebird were recorded during both migratory and non-migratory seasons. Of these, eleven species (48%) are migrants, six species (26%) have both migrant and resident populations, four species (17%) are vagrants and two species (9%) are residents. The compositions of the birds differed significantly in all months (χ2 = 84.35, p < 0.001). There is a significant difference in avian abundance between migratory and non-migratory seasons (Mann-Whitney, t = 2.39, p = 0.036). The avian abundance were differed significantly in Jeram and Remis Beaches during migratory periods (t = 4.39, p = 0.001) but not during non-migratory periods (t = 0.78, p = 0.456). Shorebird diversity was also affected by tidal cycle. There is a significance difference between high tide and low tide (Mann-Whitney, t = 78.0, p < 0.005). Frequency of disturbance also affected the shorebird distribution (Mann-Whitney, t = 57.0, p = 0.0134). Therefore, this study concluded that tides and disturbances are two factors that affecting temporal distribution of shorebird in mudflats area.

Keywords: Biodiversity, distribution, migratory birds, direct observation.

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Authors: E. B. Quarcoo, I. Yakubu, K. J. Appau

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Current land use and land cover (LULC) dynamics in Ghana have revealed considerable changes in settlement spaces. As a result, this study is intended to merge the cellular automata and Markov chain models using remotely sensed data and Geographical Information System (GIS) approaches to monitor, map, and detect the spatio-temporal LULC change in state lands within Cape Coast Metropolis. Multi-temporal satellite images from 1986-2020 were pre-processed, geo-referenced, and then mapped using supervised maximum likelihood classification to investigate the state’s land cover history (1986-2020) with an overall mapping accuracy of approximately 85%. The study further observed the rate of change for the area to have favored the built-up area 9.8 (12.58 km2) to the detriment of vegetation 5.14 (12.68 km2), but on average, 0.37 km2 (91.43 acres, or 37.00 ha.) of the landscape was transformed yearly. Subsequently, the CA-Markov model was used to anticipate the potential LULC for the study area for 2030. According to the anticipated 2030 LULC map, the patterns of vegetation transitioning into built-up regions will continue over the following ten years as a result of urban growth.

Keywords: LULC, cellular automata, Markov Chain, state lands, urbanisation, public lands, cape coast metropolis.

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Authors: Johan Segeborn, Johan S. Carlson, Robert Bohlin, Rikard Söderberg

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This paper presents a method to support dynamic packing in cases when no collision-free path can be found. The method, which is primarily based on path planning and shrinking of geometries, suggests a minimal geometry design change that results in a collision-free assembly path. A supplementing approach to optimize geometry design change with respect to redesign cost is described. Supporting this dynamic packing method, a new method to shrink geometry based on vertex translation, interweaved with retriangulation, is suggested. The shrinking method requires neither tetrahedralization nor calculation of medial axis and it preserves the topology of the geometry, i.e. holes are neither lost nor introduced. The proposed methods are successfully applied on industrial geometries.

Keywords: Dynamic packing, path planning, shrinking.

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Authors: Fatahian Dehkordi RF., Parchami A.

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Design of experiments made for correlated the hormonal activity of steroids and their effect on the vaginal structure properties. Vaginal wall consists of distinct layers of cells which strongly differ regarding growth in answer to steroid hormones. The presence study carried out for functional evaluation and sustained replacement effect of the reproductive hormones on the vaginal morphometry in the rabbit. Rabbits were maintained control (Co) or ovariectomized (Ovz) and continuously treated with estradiol (Ovz E) and estradiol mixture with testosterone (Ovz ET). Relative to control rabbits with the distinct tissue distribution pattern, ovariectomized animals displayed declined epithelial thickness and atrophy of the muscularis layer that cause the vaginal wall thinning. Estradiol treatment of Orz rabbits inverted these changes to status of the preovariectomy. Histometric measurements in Ovz ET group completely including of thickness of the epithelial and muscular layers was greater in comparison to that of control animals.

Keywords: Vagina, Ovariectomy, Rabbit, Morphometry

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Authors: Olfa.Ben Ahmed, Mahmoud. Mejdoub, Chokri. Ben Amar

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Recognizing human action from videos is an active field of research in computer vision and pattern recognition. Human activity recognition has many potential applications such as video surveillance, human machine interaction, sport videos retrieval and robot navigation. Actually, local descriptors and bag of visuals words models achieve state-of-the-art performance for human action recognition. The main challenge in features description is how to represent efficiently the local motion information. Most of the previous works focus on the extension of 2D local descriptors on 3D ones to describe local information around every interest point. In this paper, we propose a new spatio-temporal descriptor based on a spacetime description of moving points. Our description is focused on an Accordion representation of video which is well-suited to recognize human action from 2D local descriptors without the need to 3D extensions. We use the bag of words approach to represent videos. We quantify 2D local descriptor describing both temporal and spatial features with a good compromise between computational complexity and action recognition rates. We have reached impressive results on publicly available action data set

Keywords: Accordion, Bag of Features, Human action, Motion, Moving point, Space-Time Descriptor, SIFT, Video.

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Authors: Mustafa S. Fawad, Wang Wencheng, Wu Enhua

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Shadows add great amount of realism to a scene and many algorithms exists to generate shadows. Recently, Shadow volumes (SVs) have made great achievements to place a valuable position in the gaming industries. Looking at this, we concentrate on simple but valuable initial partial steps for further optimization in SV generation, i.e.; model simplification and silhouette edge detection and tracking. Shadow volumes (SVs) usually takes time in generating boundary silhouettes of the object and if the object is complex then the generation of edges become much harder and slower in process. The challenge gets stiffer when real time shadow generation and rendering is demanded. We investigated a way to use the real time silhouette edge detection method, which takes the advantage of spatial and temporal coherence, and exploit the level-of-details (LOD) technique for reducing silhouette edges of the model to use the simplified version of the model for shadow generation speeding up the running time. These steps highly reduce the execution time of shadow volume generations in real-time and are easily flexible to any of the recently proposed SV techniques. Our main focus is to exploit the LOD and silhouette edge detection technique, adopting them to further enhance the shadow volume generations for real time rendering.

Keywords: LOD, perception, Shadow Volumes, SilhouetteEdge, Spatial and Temporal coherence.

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Authors: Samuel Olajide Babawale, O. O. Ogunkoya

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The study mapped selected wells in Inisa town, Osun state, in the guinea savanna region of southwest Nigeria, and determined the water quality considering certain elements. It also assessed the variation in the elevation of the water table surface to depth of the wells in the months of August and November. This is with a view to determine the level of contamination of the water with respect to land use and anthropogenic activities, and also to determine the variation that occurs in the quantity of well water in the rainy season and the start of the dry season. Results show a random pattern of the distribution of the mapped wells and shows that there is a shallow water table in the study area. The temporal changes in the elevation show that there are no significant variations in the depth of the water table surface over the period of study implying that there is a sufficient amount of water available to the town all year round. It also shows a high concentration of sodium in the water sample analyzed compared to other elements that were considered, which include iron, copper, calcium, and lead. This is attributed majorly to anthropogenic activities through the disposal of waste in landfill sites. There is a low concentration of lead which is a good indication of a reduced level of pollution.

Keywords: Water quality, temporal changes, elevation, water table surface, land use, anthropogenic activities.

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular disease resulting from hypertension poses a significant threat to human health, and early detection of hypertension can potentially save numerous lives. Traditional methods for detecting hypertension require specialized equipment and are often incapable of capturing continuous blood pressure fluctuations. To address this issue, this study starts by analyzing the principle of heart rate variability (HRV) and introduces the utilization of sliding window and power spectral density (PSD) techniques to analyze both temporal and frequency domain features of HRV. Subsequently, a hypertension prediction network that relies on HRV is proposed, combining Resnet, attention mechanisms, and a multi-layer perceptron. The network leverages a modified ResNet18 to extract frequency domain features, while employing an attention mechanism to integrate temporal domain features, thus enabling auxiliary hypertension prediction through the multi-layer perceptron. The proposed network is trained and tested using the publicly available SHAREE dataset from PhysioNet. The results demonstrate that the network achieves a high prediction accuracy of 92.06% for hypertension, surpassing traditional models such as K Near Neighbor (KNN), Bayes, Logistic regression, and traditional Convolutional Neural Network (CNN).

Keywords: Feature extraction, heart rate variability, hypertension, residual networks.

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Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

Abstract:

A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: Brain activity, dense EEG, evoked responses, spatiotemporal analysis, SVM, perception.

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

Abstract:

22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: Catchment management, drinking water reservoir, multivariate curve resolution alternating least squares, thermal stratification, water quality.

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Authors: Chansheng He, Carlo DeMarchi

Abstract:

A physically based, spatially-distributed water quality model is being developed to simulate spatial and temporal distributions of material transport in the Great Lakes Watersheds of the U.S. Multiple databases of meteorology, land use, topography, hydrography, soils, agricultural statistics, and water quality were used to estimate nonpoint source loading potential in the study watersheds. Animal manure production was computed from tabulations of animals by zip code area for the census years of 1987, 1992, 1997, and 2002. Relative chemical loadings for agricultural land use were calculated from fertilizer and pesticide estimates by crop for the same periods. Comparison of these estimates to the monitored total phosphorous load indicates that both point and nonpoint sources are major contributors to the total nutrient loads in the study watersheds, with nonpoint sources being the largest contributor, particularly in the rural watersheds. These estimates are used as the input to the distributed water quality model for simulating pollutant transport through surface and subsurface processes to Great Lakes waters. Visualization and GIS interfaces are developed to visualize the spatial and temporal distribution of the pollutant transport in support of water management programs.

Keywords: Distributed Large Basin Runoff Model, Great LakesWatersheds, nonpoint source pollution, and point sources.

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