Search results for: temporal splitting

Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: Elie Awwad, Bilal Hamad, Mounir Mabsout, Helmi Khatib

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The paper reports test results on the long-term behavior of sustainable hemp-concrete material prepared in research work conducted at the American University of Beirut. The tests results are in terms of compressive and splitting tensile tests conducted on standard 150x300 mm cylinders. A control mix without fibers, one polypropylene-concrete mix, and ten hemp-concrete mixes were prepared with different percentages of industrial hemp fibers and reduced coarse aggregate contents. The objective was to investigate the strength properties of hemp-reinforced concrete at 1.5 years age as compared with control mixes. The results indicated that both the compressive strength and the splitting tensile strength results of all tested cylinders increased as compared with the 28-days values. Also, the difference between the hemp-concrete samples and the control samples at 28 days was maintained at 1.5 years age indicating that hemp fibers did not exhibit any negative effect on the long-term strength properties of concrete.

Keywords: hemp-reinforced concrete, natural fibers, compressive strength, splitting tensile strength

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Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Lai Yi-Hsiu

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The present paper aims to examine the language processing of Chinese-speaking seniors with Alzheimer’s disease (AD) from the perspective of temporal cues. Twenty healthy adults, 17 healthy seniors, and 13 seniors with AD in Taiwan participated in this study to tell stories based on two sets of pictures. Nine temporal cues were fetched and analyzed. Oral productions in Mandarin Chinese were compared and discussed to examine to what extent and in what way these three groups of participants performed with significant differences. Results indicated that the age effects were significant in filled pauses. The dementia effects were significant in mean duration of pauses, empty pauses, filled pauses, lexical pauses, normalized mean duration of filled pauses and lexical pauses. The findings reported in the current paper help characterize the nature of language processing in seniors with or without AD, and contribute to the interactions between the AD neural mechanism and their temporal parameters.

Keywords: language processing, Alzheimer’s disease, Mandarin Chinese, temporal cues

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Souâad Boudebza, Omar Nouali, Faiçal Azouaou

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Social networks have recently gained a growing interest on the web. Traditional formalisms for representing social networks are static and suffer from the lack of semantics. In this paper, we will show how semantic web technologies can be used to model social data. The SemTemp ontology aligns and extends existing ontologies such as FOAF, SIOC, SKOS and OWL-Time to provide a temporal and semantically rich description of social data. We also present a modeling scenario to illustrate how our ontology can be used to model social networks.

Keywords: ontology, semantic web, social network, temporal modeling

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Authors: S. U. Khan, T. Ayub, N. Shafiq

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The properties of locally produced metakaolin (MK) as cement replacing material and the comparison of reactivity with commercially available micro-silica have been investigated. Compressive strength, splitting tensile strength, and load-deflection behaviour under bending are the properties that have been studied. The amorphous phase of MK with micro-silica was compared through X-ray diffraction (XRD) pattern. Further, interfacial transition zone of concrete with micro-silica and MK was observed through Field Emission Scanning Electron Microscopy (FESEM). Three mixes of concrete were prepared. One of the mix is without cement replacement as control mix, and the remaining two mixes are 10% cement replacement with micro-silica and MK. It has been found that MK, due to its irregular structure and amorphous phase, has high reactivity with portlandite in concrete. The compressive strength at early age is higher with MK as compared to micro-silica. MK concrete showed higher splitting tensile strength and higher load carrying capacity as compared to control and micro-silica concrete at all ages respectively.

Keywords: metakaolin, compressive strength, splitting tensile strength, load deflection, interfacial transition zone

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Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

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In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

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Authors: Feng Yin

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Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: Evrim Colak, Andriy E. Serebryannikov, Pavel V. Usik, Ekmel Ozbay

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Working with a dielectric photonic crystal (PC) structure which does not include surface corrugations, unidirectional transmission and dual-beam splitting are observed under normal incidence as a result of the strong diffractions caused by the embedded defect layer. The defect layer has twice the period of the regular PC segments which sandwich the defect layer. Although the PC has even number of rows, the structural symmetry is broken due to the asymmetric placement of the defect layer with respect to the symmetry axis of the regular PC. The simulations verify that efficient splitting and occurrence of strong diffractions are related to the dispersion properties of the Floquet-Bloch modes of the photonic crystal. Unidirectional and bi-directional splitting, which are associated with asymmetric transmission, arise due to the dominant contribution of the first positive and first negative diffraction orders. The effect of the depth of the defect layer is examined by placing single defect layer in varying rows, preserving the asymmetry of PC. Even for deeply buried defect layer, asymmetric transmission is still valid even if the zeroth order is not coupled. This transmission is due to evanescent waves which reach to the deeply embedded defect layer and couple to higher order modes. In an additional selected performance, whichever surface is illuminated, i.e., in both upper and lower surface illumination cases, incident beam is split into two beams of equal intensity at the output surface where the intensity of the out-going beams are equal for both illumination cases. That is, although the structure is asymmetric, symmetric bidirectional transmission with equal transmission values is demonstrated and the structure mimics the behavior of symmetric structures. Finally, simulation studies including the examination of a coupled-cavity defect for two different permittivity values (close to the permittivity values of GaAs or Si and alumina) reveal unidirectional splitting for a wider band of operation in comparison to the bandwidth obtained in the case of a single embedded defect layer. Since the dielectric materials that are utilized are low-loss and weakly dispersive in a wide frequency range including microwave and optical frequencies, the studied structures should be scalable to the mentioned ranges.

Keywords: asymmetric transmission, beam deflection, blazing, bi-directional splitting, defect layer, dual beam splitting, Floquet-Bloch modes, isofrequency contours, line defect, oblique incidence, photonic crystal, unidirectionality

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Authors: Špela Hajduk, Sean P. Berglund, Matejka Podlogar, Goran Dražić, Fatwa F. Abdi, Zorica C. Orel, Menny Shalom

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Graphitic carbon nitride materials (g-CN) have emerged as an attractive photocatalyst and electrocatalyst for photo and electrochemical water splitting reaction, due to their environmental benignity nature and suitable band gap. Many approaches were introduced to enhance the photoactivity and electronic properties of g-CN and resulted in significant changes in the electronic and catalytic properties. Here we demonstrate the synthesis of thin and homogenous g-CN layer on highly ordered ZnO nanowire (NW) substrate by growing a seeding layer of small supramolecular assemblies on the nanowires. The new synthetic approach leads to the formation of thin g-CN layer (~3 nm) without blocking all structure. Two different deposition methods of carbon nitride were investigated and will be presented. The amount of loaded carbon nitride significantly influences the PEC activity of hybrid material and all the ZnO/g-CNx electrodes show great improvement in photoactivity. The chemical structure, morphology and optical properties of the deposited g-CN were fully characterized by various techniques as X-ray powder spectroscopy (XRD), scanning electron microscopy (SEM), focused ion beam scanning electron microscopy (FIB-SEM), high-resolution scanning microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS).

Keywords: carbon nitride, photoanode, solar water splitting, zinc oxide

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: R. Vidyasagar, G. L. S. Vilela, B. M. Guiraldelli, A. B. Henriques, J. Moodera

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Nano-scaled magnetic systems that can have both magnetic and optical transitions controlled and manipulated by external means have received enormous research attention for their potential applications in magneto-optics and spintronic devices. Among several ferrimagnetic insulators, the Tm₃Fe₅O₁₂ (TmIG) has become a prototype material displaying huge perpendicular magnetic anisotropy. Nevertheless, the optical properties of nano-scale TnIG films have not yet been investigated. We report the observation of giant splitting in the optical transitions of high-quality thin films of Tm₃Fe₅O₁₂ (TmIG) grown by rf sputtering on gadolinium gallium garnet substrates (GGG-111) substrate. The optical absorbance profiles measured with optical absorption spectroscopy show a dual optical transition in visible frequency regimes attributed to the transitions of electrons from the O-2p valence band to the Fe-3d conduction band and from the O-2p valence band to the Fe-2p⁵3d⁶ excitonic states at the Γ-symmetric point of the TmIG Brillouin zone. When the thickness of the film is reduced from 120 nm to 7.5 nm, the 1st optical transition energy shifted from 2.98 to 3.11 eV ( ~130 meV), and the 2nd transition energy shifted from 2.62 to 2.56 eV (~ 60 meV). The giant band splitting of both transitions can be attributed to the population of excited states associated with the atomic modification pertaining to the compressive or tensile strains.

Keywords: optical transitions, thin films, ferrimagnetic insulator, strains

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Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Tzu-I Chiang

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A central question for finite-nonfinite distinction in Mandarin Chinese is how does Mandarin encode temporal information without the grammatical contrast between past and present tense. Moreover, how do L2 learners of Mandarin whose native language is English and whose L1 system has tense morphology, acquire the temporal encoding system in L2 Mandarin? The current study reports preliminary findings on the relationship between topic prominence and the temporal encoding in L1 and L2 Chinese. Oral narratives data from 30 natives and learners of Mandarin Chinese were collected via a film-retell task. In terms of coding, predicates collected from the narratives were transcribed and then coded based on four major verb types: n-degree Statives (quality-STA), point-scale Statives (status-STA), n-atom EVENT (ACT), and point EVENT (resultative-ACT). How native speakers and non-native speakers started retelling the story was calculated. Results of the study show that native speakers of Chinese tend to express Topic Time (TT) syntactically at the topic position; whereas L2 learners of Chinese across levels rely mainly on the default time encoded in the event types. Moreover, as the proficiency level of the learner increases, learners’ appropriate use of the event predicates increased, which supports the argument that L2 development of temporal encoding is affected by lexical aspect.

Keywords: topic prominence, temporal encoding, lexical aspect, L2 acquisition

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Authors: A. Hegazy, Ahmed Elsayed, Essam El Shenawy, N. Allam, Hala Handal, K. R. Mahmoud

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Highly crystalline, TiO₂ pristine sub-10 nm anatase nanocrystals were fabricated at low temperatures by post hydrothermal treatment of the as-prepared TiO₂ nanoparticles. This treatment resulted in bandgap narrowing and increased photocurrent density value (3.8 mA/cm²) when this material was employed in water splitting systems. The achieved photocurrent values are among the highest reported ones so far for the fabricated nanoparticles at this low temperature. This might be explained by the increased surface defects of the prepared nanoparticles. It resulted in bandgap narrowing that was further investigated using positron annihilation experiments by measuring positron lifetime and Doppler broadening. Besides, homogeneous spherical TiO₂ nanoparticles were synthesized in large diameter and high surface area and the high percentage of (001) facet by sol-gel method using potassium persulfate (K₂S₂O₈) as an oxidizing agent. The fabricated particles exhibited high exposed surface area, high photoactivity and reduced band gap. Enhanced performance for water splitting applications was displayed by formed TiO₂ nanoparticles. Their morphological and structural properties were studied to optimize their synthesis parameters in an attempt to construct more applicable fuel cells in the industry for hydrogen fuel production.

Keywords: positron annihilation, solar energy, TiO2 nanoparticles, water splitting

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Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh

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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.

Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography

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Authors: Pallavi Roe

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Violent crime is a significant public safety concern in urban areas across the United States, and Washington, DC, is no exception. This research discusses the prevalence and types of crime, particularly violent crime, in Washington, DC, along with the factors contributing to the high rate of violent crime in the city, including poverty, inequality, access to guns, and racial disparities. The organizations working towards ensuring safety in neighborhoods are also listed. The proposal to perform spatial and temporal analysis on violent crime and the use of guns in crime analysis is presented to identify patterns and trends to inform evidence-based interventions to reduce violent crime and improve public safety in Washington, DC. The stakeholders for crime analysis are also discussed, including law enforcement agencies, prosecutors, judges, policymakers, and the public. The anticipated result of the spatial and temporal analysis is to provide stakeholders with valuable information to make informed decisions about preventing and responding to violent crimes.

Keywords: crime analysis, spatial analysis, temporal analysis, violent crime

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Authors: Okike Benjamin, E. J. D. Garba

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The protection of sensitive information against unauthorized access or fraudulent changes has been of prime concern throughout the centuries. Modern communication techniques, using computers connected through networks, make all data even more vulnerable to these threats. The researchers in this work propose a new encryption technique to be known as Merged Irregular Transposition Cipher. In this proposed encryption technique, a message to be encrypted will first of all be split into multiple parts depending on the length of the message. After the split, different keywords are chosen to encrypt different parts of the message. After encrypting all parts of the message, the positions of the encrypted message could be swapped to other position thereby making it very difficult to decrypt by any unauthorized user.

Keywords: information security, message splitting, pattern, sequence

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Authors: Alasdair Stanton

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What makes for a good explanation? Twenty years after Wendt’s important treatment of constitution and causation, non-causal explanations (sometimes referred to as ‘understanding’, or ‘descriptive inference’) have become, if not mainstream, at least accepted within International Relations. This article proceeds in two parts: firstly, it examines closely Wendt’s constitutional claims, and while it agrees there is a difference between causal and constitutional, rejects the view that constitutional explanations lack temporality. In fact, this author concludes that a constitutional argument is only possible if it relies upon a more foundational, causal argument. Secondly, through theoretical analysis of the constitutional argument, this research seeks to delineate temporal and non-temporal ways of explaining within International Relations. This article concludes that while the constitutional explanation, like other logical arguments, including comparative, and counter-factual, are not truly non-causal explanations, they are not bound as tightly to the ‘real world’ as temporal arguments such as cause-effect, process tracing, or even interpretivist accounts. However, like mathematical models, non-temporal arguments should aim for empirical testability as well as internal consistency. This work aims to give clear theoretical grounding to those authors using non-temporal arguments, but also to encourage them, and their positivist critics, to engage in thoroughgoing empirical tests.

Keywords: causal explanation, constitutional understanding, empirical, temporality

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Authors: B.Shukir, H.Woo, P.Barzo, D.Kis

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Preoperative brain mapping in tumors involving the speech areas has an important role to reduce surgical risks. Functional magnetic resonance imaging (fMRI) is the gold standard method to localize cortical speech areas preoperatively, but its availability in clinical routine is difficult. Diffusion MRI based probabilistic tractography is available in head MRI. It’s used to segment cortical subregions by their structural connectivity. In our study, we used probabilistic tractography to localize the frontal and temporal cortical speech areas. 15 patients with left frontal tumor were enrolled to our study. Speech fMRI and diffusion MRI acquired preoperatively. The standard automated anatomical labelling atlas 3 (AAL3) cortical atlas used to define 76 left frontal and 118 left temporal potential speech areas. 4 types of tractography were run according to the structural connection of these regions to the left arcuate fascicle (FA) to localize those cortical areas which have speech functions: 1, frontal through FA; 2, frontal with FA; 3, temporal to FA; 4, temporal with FA connections were determined. Thresholds of 1%, 5%, 10% and 15% applied. At each level, the number of affected frontal and temporal regions by fMRI and tractography were defined, the sensitivity and specificity were calculated. At the level of 1% threshold showed the best results. Sensitivity was 61,631,4% and 67,1523,12%, specificity was 87,210,4% and 75,611,37% for frontal and temporal regions, respectively. From our study, we conclude that probabilistic tractography is a reliable preoperative technique to localize cortical speech areas. However, its results are not feasible that the neurosurgeon rely on during the operation.

Keywords: brain mapping, brain tumor, fMRI, probabilistic tractography

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Wen Cai Ng, Saman Ilankoon, Meng Nan Chong

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The vast increase in global energy demand, coupled with the growing concerns on environmental issues, has triggered the search for cleaner alternative energy sources. In view of this, the photoelectrochemical (PEC) water splitting offers a sustainable hydrogen (H2) production route that only requires solar energy, water, and PEC system operating in an ambient environment. However, the current advancement of PEC water splitting technologies is still far from the commercialization benchmark indicated by the solar-to-H2 (STH) efficiency of at least 10 %. This is largely due to the shortcomings of photoelectrodes used in the PEC system, such as the rapid recombination of photogenerated charge carriers and limited photo-responsiveness in the visible-light spectrum. Silver orthophosphate (Ag3PO4) possesses many desirable intrinsic properties for the fabrication into photoanode used in PEC systems, such as narrow bandgap of 2.4 eV and low valence band (VB) position. Hence, in this study, a highly efficient Ag3PO4-based photoanode was synthesized and characterized. The surface of the Ag foil substrate was directly oxidized to fabricate a top layer composed of {111}-bound Ag3PO4 tetrahedrons layer with a porous structure, forming the dual-layer Ag/Ag3PO4 photoanode. Furthermore, the key synthesis parameters were systematically investigated by varying the concentration ratio of capping agent-to-precursor (R), the volume ratio of hydrogen peroxide (H2O2)-to-water, and reaction period. Results showed that the optimized dual-layer Ag/Ag3PO4 photoanode achieved a photocurrent density as high as 4.19 mA/cm2 at 1 V vs. Ag/AgCl for the R-value of 4, the volume ratio of H2O2-to-water of 3:5 and 20 h reaction period. The current work provides a solid foundation for further nanoarchitecture modification strategies on Ag3PO4-based photoanodes for more efficient PEC water splitting applications. This piece of information needs to be backed up by evidence; therefore, you need to provide a reference. As the abstract should be self-contained, all information requiring a reference should be removed. This is a fact known to the area of research, and not necessarily required a reference to support.

Keywords: solar-to-hydrogen fuel, photoelectrochemical water splitting, photoelectrode, silver orthophosphate

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Authors: Sofia Barbosa, Mariana Pinto, José António Almeida, Edgar Carvalho, Catarina Diamantino

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The aim of this work was to test a methodology able to generate spatial-temporal maps that can synthesize simultaneously the trends of distinct hydrochemical indicators in an old radium-uranium tailings dam deposit. Multidimensionality reduction derived from principal component analysis and subsequent data aggregation derived from clustering analysis allow to identify distinct hydrochemical behavioural profiles and to generate synthetic evolutionary hydrochemical maps.

Keywords: Contamination plume migration, K-means of PCA scores, groundwater and mine water monitoring, spatial-temporal hydrochemical trends

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Authors: Hristina Šalipur, Jasmina Dostanić, Davor Lončarević, Matej Huš

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Photocatalytic water splitting/alcohol photoreforming has been used for the conversion of sunlight energy in the process of hydrogen production due to its sustainability, environmental safety, effectiveness and simplicity. Titanate nanotubes are frequently studied materials since they combine the properties of photo-active semiconductors with the properties of layered titanates, such as the ion-exchange ability. Platinum (Pt) doping into titanate structure has been considered an effective strategy in better separation efficiency of electron-hole pairs and lowering the overpotential for hydrogen production, which results in higher photocatalytic activity. In our work, Pt doped titanate catalysts were synthesized via simple alkaline hydrothermal treatment, incipient wetness impregnation method and temperature-programmed reduction. The structural, morphological and optical properties of the prepared catalysts were investigated using various characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), N2 physisorption, and diffuse reflectance spectroscopy (DRS). The activities of the prepared Pt-doped titanate photocatalysts were tested for hydrogen production via photocatalytic water splitting/alcohol photoreforming process under simulated solar light irradiation. Characterization of synthesized Pt doped titanate catalysts showed crystalline anatase phase, preserved nanotubular structure and high specific surface area. The result showed enhancement of activity in photocatalytic water splitting/alcohol photoreforming in the following order 2-butanol>1-butanol>tert-butanol, with obtained maximal hydrogen production rate of 7.5, 5.3 and 2 mmol g-1 h-1, respectively. Different possible factors influencing the hole scavenging ability, such as hole scavenger redox potential and diffusivity, adsorption and desorption rate of the hole scavenger on the surface and stability of the alcohol radical species generated via hole scavenging, were investigated. The theoretical evaluation using density functional theory (DFT) further elucidated the reaction kinetics and detailed mechanism of photocatalytic water splitting/alcohol photoreforming.

Keywords: hydrogen production, platinum, semiconductor, water splitting, density functional theory

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Authors: Alper Serdar Anli

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Analysis of temporal variation of reference evapotranspiration (ET0) is important in arid and semi-arid regions where water resources are limited. In this study, temporal variation of reference evapotranspiration (ET0) and meteorological drought analysis through SPEI (Standardized Precipitation Evapotranspiration Index) method have been carried out in provinces of Central Anatolia Region, Turkey. Reference evapotranspiration of concerning provinces in the region has been estimated using Penman-Monteith method and one calendar year has been split up four periods as r1, r2, r3 and r4. Temporal variation of reference evapotranspiration according to four periods has been analyzed through parametric Dickey-Fuller test and non-parametric Mann-Whitney U test. As a result, significant increasing trends for reference evapotranspiration have been detected and according to SPEI method used for estimating meteorological drought in provinces, mild drought has been experienced in general, and however there have been also a significant amount of events where moderate and severely droughts occurred.

Keywords: central Anatolia region, drought index, Penman-Monteith, reference evapotranspiration, temporal variation

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Authors: Hamad Almohamadi, Nabeel H. Alharthi, Abdulrahman Aljabri

Abstract:

In this study, two-dimensional CuFeOx is deposited on nickel foam for the fabrication of electrocatalyst for oxygen evolution reaction (OER). The in-situ hydrothermal synthesis of CuFeOx in presence of aloe vera extract was found to yield unique nano-rose-like morphology which aided to improve the electrochemical surface area of the electrode. The phytochemical assisted synthesis of CuFeOx using 75% aloe vera extract resulted in improved OER electrocatalytic performance by attaining the overpotential of 310 mV for 50 mA cm−2 and 410 mV for 100 mA cm−2. The electrode also sustained robust stability throughout the 50 h of chronopotentiometry studies under alkaline electrolyte conditions, thus proving to be prospective electrode material for efficient OER in electrochemical water splitting.

Keywords: water splitting, phytochemicals, oxygen evaluation reaction, Tafel's slope, stability

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

Abstract:

Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Nazanin Naderi, Milton Smith

Abstract:

Since worldwide demand for renewable energy is increasing rapidly because of the climate problem and the limitation of fossil fuels, technologies of alternative energy sources have been developed and the electric power network now includes renewable energy resources such as wind energy. Because of the huge advantages that wind energy has, like reduction in natural gas use, price pressure, emissions of greenhouse gases and other atmospheric pollutants, electric sector water consumption and many other contributions to the nation’s economy like job creation it has got too much attention these days from different parts of the world especially in the United States which is trying to provide 20% of the nation’s energy from wind by 2030. This study is trying to evaluate the effect of splitting wind farms on power output. We are trying to find if we can get more output by installing wind turbines in different sites rather than installing all wind turbines in one site. Five potential sites in Texas have been selected as a case study and two years wind data has been gathered for these sites. Wind data are analyzed and effect of correlation between sites on power output has been evaluated. Standard deviation and autocorrelation effect has also been considered for this study. The paper has been organized as follows: After the introduction the second section gives a brief overview of wind analysis. The third section addresses the case study and evaluates correlation between sites, auto correlation of sites and standard deviation of power output. In section four we describe the results.

Keywords: auto correlation, correlation between sites, splitting wind farms, power output, standard deviation

Procedia PDF Downloads 586