Search results for: presence metrics

Authors: Hooshmand Kalayeh

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The human brain consists of reptilian, mammalian, and thinking brain. And mind consists of conscious, subconscious, and unconscious parallel neural-net programs. The primary objective of this paper is to propose a methodology for quantitative analysis of neural-nets associated with these mental activities in the neocortex. The secondary objective of this paper is to suggest a methodology for quantitative analysis of presence; the proposed methodologies can be used as a first-step to measure, monitor, and understand consciousness and presence. This methodology is based on Neural-Networks (NN), number of neuron in each NN associated with consciousness, subconsciouness, and unconsciousness, and number of neurons in neocortex. It is assumed that the number of neurons in each NN is correlated with the associated area and volume. Therefore, online and offline visualization techniques can be used to identify these neural-networks, and online and offline measurement methods can be used to measure areas and volumes associated with these NNs. So, instead of the number of neurons in each NN, the associated area or volume also can be used in the proposed methodology. This quantitative analysis and associated online and offline measurements and visualizations of different Neural-Networks enable us to rewire the connections in our brain for a more balanced living.

Keywords: brain, mind, consciousness, presence, sub-consciousness, unconsciousness, skills, concentrations, attention

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Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

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Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

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Authors: E. Lacasa, J. L. Santolaya, I. Millán

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The progress toward sustainability implies maintaining and preferably improving both, human and ecosystem well-being, according to a triple bottom line that includes the environmental, economic and social dimensions. The life cycle assessment (LCA) is a method applicable to all production sectors that aims to quantify the environmental pressures and the benefits related to goods and services, as well as the trade-offs and the scope for improving areas of the production process. While using LCA to measure the environmental dimension of sustainability is widespread, similar approaches for the economic and the social dimensions still have limited application worldwide and there is a need for consistent and robust methods and indicators. This paper focuses on the milk production process and presents the analysis of the flows exchanged by an industrial installation through accounting all the energy and material inputs and the associated emissions and waste outputs at this stage of its life cycle. The functional unit is one litre of milk produced. Different metrics and indicators are used to assess the three dimensions of sustainability. Metrics considered useful to assess the production activities are the total water and energy consumptions and the milk production volume of each cow. The global warming, the value added and the working hours are indicators used to measure each sustainability dimension. The study is performed with two types of feeding of the cows, which includes a change in percentages of components as well. Nutritional composition of the milk obtained is almost kept. It is observed that environmental and social improvements involve high economic costs.

Keywords: milk production, sustainability, indicators, life cycle assessment

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Authors: Harman Dwi R., Alwin Mugiyantoro, Heppy Chintya P.

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The location of this research is a part of Geoheritage that located in Nglipar, Gunung Kidul Regency, Yogyakarta Special Region. Whereas in this location, the carbonate sandstone of Sambipitu Formation (early-middle Miocene) is well exposed along Ngalang River, also there are ichnofossil presence which causes this formation to be interesting. The determination of paleobathymetry is particularly important in determining paleoenvironment and paleogeographic. Paleobathymetry can be determined by identifying the presence of Foraminifera bentonik fossil and parasequence emerge. The methods that used in this study are spatial method of field observation with systematic sampling, descriptive method of paleontology, biostratigraphy analysis, geometrical analysis of Ichnofossil, and study literature. The result obtained that paleobathymetry of this location is bathyal zone with maximum regression known by Bulliminoides williamsonianus showing depth 17 fathoms at the age of N3-N5 (Oligocenne-Early Miocene) and the maximum transgression is known by Cibicides pseudoungarianus showing depth 862 fathoms at the age of N8-N9 (Early-Middle Miocene). Where the obtained paleobathymetry supported of the presence and formed the pattern of ichnofossil that found in the study area.

Keywords: paleobathymetry, biostratigraphy, ichnofossil, Ngalang river

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Apostolos Lagarias, Anastasia Stratigea

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Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growth

Keywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics

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Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

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In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

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Authors: Beena Sethi

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This work involves the degradation of plastic waste in the presence of three different nanocatalysts. A thin film of LLDPE was formed with all three nanocatalysts separately in the solvent. Thermo Gravimetric Analysis (TGA) and Differential Scanning Calorimetric (DSC) analysis of polymers suggest that the presence of these catalysts lowers the degradation temperature and the change mechanism of degradation. Gas chromatographic analysis was carried out for two films. In gas chromatography (GC) analysis, it was found that degradation of pure polymer produces only 32% C3/C4 hydrocarbons and 67.6% C5/C9 hydrocarbons. In the presence of these catalysts, more than 80% of polymer by weight was converted into either liquid or gaseous hydrocarbons. Change in the mechanism of degradation of polymer was observed therefore more C3/C4 hydrocarbons along with valuable feedstock are produced. Adjustment of dose of nanocatalyst, use of nano-admixtures and recycling of catalyst can make this catalytic feedstock recycling method a good tool to get sustainable environment. The obtained products can be utilized as fuel or can be transformed into other useful products. In accordance with the principles of sustainable development, chemical recycling i.e. tertiary recycling of polymers along with the reuse (zero order recycling) of plastics can be the most appropriate and promising method in this direction. The tertiary recycling is attracting much attention from the viewpoint of the energy resource.

Keywords: degradation, differential scanning calorimetry, feedstock recycling, gas chromatography, thermogravimetric analysis

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Authors: Ali Gharib, Leila Vojdanifard, Nader Noroozi Pesyan

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Different Pyrazoline derivatives were synthesized by cyclization of substituted chalcone derivatives in presence of hydrazine hydrate. A series of novel 1,3,5-triaryl pyrazoline derivatives has been synthesized by the reaction of chalcone and phenylhydrazine in the presence of the Fe3O4 NPs, in high yields. The structures of compounds obtained were determined by IR and 1H NMR spectra. Fe3O4 NPs was recycled and no appreciable change in activity was noticed after three cycles.

Keywords: pyrazoline, chalcone, nanoparticles, Fe3O4, catalyst, synthesis

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Authors: Randolf Von N. Salindo

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The study was conducted to measure the logistics integration capabilities of selected companies in the Bahrain construction industry using the Supply Chain 2000 framework; and, determine the extent and direction of influence of these logistics capabilities and integration competencies on the supply chain performance of the firm. A total of 50 executive respondents (from supervisor to managing director level) from 22 construction and construction supplier firms participated in the study from September to November 2014. The results reveal that respondent Bahraini construction firms have significantly lower levels of logistics capabilities, but higher levels of logistics integration competencies compared to international benchmarks. Using stepwise multiple regression analysis, eight logistics capabilities of Bahraini constructions firms were identified to be positively associated with firm performance; with comprehensive metrics as the most positively dominant influential logistics capability. Activity based and total cost methodology is found to be the most negatively dominant influential logistics capability. In terms of logistics integration competencies, the study revealed that that customer integration, internal integration, and, measurement integration are negatively associated with firm performance. There was no logistics integration competency found to be positively associated with the supply chain performance among the companies who participated in the study. The research reveals that there are areas for improvement in supply chain capabilities and logistics integration competencies of the construction firms in the Kingdom of Bahrain to improve their supply chain performance to a global level.

Keywords: comprehensive metrics, customer integration, logistics integration capabilities, logistics integration competencies

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: F. Javier Benitez, Juan L. Acero, Francisco J. Real, Elena Rodriguez

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Five selected pollutants which are frequently present in waters and wastewaters have been degraded by the advanced oxidation process constituted by UV radiation activated with the additional presence of persulfate (UV/PS). These pollutants were 1H-benzotriazole (BZ), N,N-diethyl-m-toluamide or DEET (DT), chlorophene (CP), 3-methylindole (ML), and nortriptyline hydrochloride (NH).While UV radiation alone almost not degraded these substances, the addition of PS generated the very reactive and oxidizing sulfate radical SO₄⁻. The kinetic study provided the second order rate constants for the reaction between this radical and each pollutant. An increasing dose of PS led to an increase in the degradation rate, being the highest results obtained at near neutral pH. Several water matrices were tested, and the presence of bicarbonate showed different effects: a decrease in the elimination of DT, BZ, and NH; and an increase in the oxidation of CP and ML. The additional presence of humic acids (AH) decreased this degradation, because of several effects: light screening and radical scavenging. The presence of several natural substances in waters (both types, inorganic and organic matter) usually diminishes the oxidation rates of organic pollutants, but this combination UV/PS process seems to be an efficient solution for the removal of the selected contaminants when are present in contaminated waters.

Keywords: water purification, UV activated persulfate, kinetic study, sulfate radicals

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Authors: Haiming Wen

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Grain growth is an important and consequential phenomenon that generally occurs in the presence of thermal and/or stress/strain fields. Thermally activated grain growth has been extensively studied and similarly, there are numerous experimental and theoretical studies published describing stress-induced grain growth in single-phase materials. However, studies on grain growth during the simultaneous presence of an elevated temperature and an external stress are very limited, and moreover, grain growth phenomena in materials containing second-phase particles and solute segregation at GBs have received limited attention. This lecture reports on a study of grain growth in the presence of second-phase particles and solute/impurity segregation at grain boundaries (GBs) during high-temperature deformation of an ultra-fine grained (UFG) Al alloy synthesized via consolidation of mechanically milled powders. The mechanisms underlying the grain growth were identified as GB migration and grain rotation, which were accompanied by dynamic recovery and geometric dynamic recrystallization, while discontinuous dynamic recrystallization was not operative. A theoretical framework that incorporates the influence of second-phase particles and solute/impurity segregation at GBs on grain growth in presence of both elevated temperature and external stress is formulated and discussed. The effect of second-phase particles and solute/impurity segregation at GBs on GB migration and grain rotation was quantified using the proposed theoretical framework, indicating that both second-phase particles and solutes/impurities segregated GBs reduce the velocities of GB migration and grain rotation as compared to those in commercially pure Al. Our results suggest that grain growth predicted by the proposed theoretical framework is in agreement with experimental results. Hence, the developed theoretical framework can be applied to quantify grain growth in simultaneous presence of external stress, elevated temperature, GB segregation and second-phase particles, or in presence of one or more of the aforementioned factors.

Keywords: nanocrystalline materials, ultra-fine grained materials, grain growth, grain boundary migration, grain rotation

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Authors: Fern Baedyananda, Arkom Chaiwongkot, Somchai Niruthisard, Nakarin Kitkumthorn, Parvapan Bhattarakosol

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High-risk human papillomavirus (HPV) infections cause transformation of the host cells by down-regulating and inhibiting host regulatory proteins such as p53 and pRb by overexpressing the viral oncoproteins E6 and E7. However, the E1 protein which is the only enzyme encoded by HPV has also been shown to cause DNA instability leading to the integration of the virus into the host genome and triggering carcinogenic events. A 63bp duplication in the E1 helicase region has been detected in European patients. However, the clinical prognosis of these patients is still controversial. This study was performed to determine the presence of the HPV-16 E1 63bp duplication in patient cervical samples in Thai women and determine the sequence of the variant in the Thai population. Detection of the HPV-16 E1 duplication in the helicase region was performed in 90 patient cell samples across normal, cervical intraepithelial neoplasia I-III, and squamous cervical carcinoma stages by PCR. The PCR products were purified and sequenced to determine the presence of duplication variants.The variant form was found in 10% of all CIN 1 patients. In this study, the presence of the 63 bp duplication variant in the Thai population was found to be present and was further characterized. Interestingly, all samples that exhibited the variant form of HPV-16 E1 were classified as CIN I. Presence of the variant, constricted to mild dysplasia signifies the importance of HPV-16 E1 in carcinogenesis.

Keywords: carcinogenesis, cervical cancer, human papillomavirus, HPV-16 E1

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Authors: Tagore Sai Priya Nunna, Ankhi Banerjee

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The rapid growth of the tourism industry in India in the last few years after the economic crisis in 2009 has been one of the significant causes that led to the Land Use Land Cover change (LULC) of most tourism destinations. The tourist regions are subjected to significant increase in built-up due to increased construction activities for developing accommodation facilities further boosting tourism demand. This research attempts to analyse the changing LULC and the growth pattern of the built-up area within tourist destinations. Four popular tourist destinations, which promises various types of tourism activity and which are significantly dependent on tourism for economic growth, are selected for the study. The study uses remotely sensed data for analysis of land use change through supervised segmentation into five broad classes. Further, the landuse map is reclassified into binary classes to extract the built-up area. The growth patterns of the built-up are analysed in terms of size, shape, direction and form of growth, through a set of spatial metrics. Additionally, a detailed analysis of the existing development pattern corresponding to planned development zones was performed to identify unplanned growth spots in the study regions. The findings of the study provide insights into how tourism has contributed to significant changes in LULC around tourist sites. Also, the study highlights the growth pattern of built-up areas with respect to the type of tourism activity and geographical characteristics. The research attempts to address the need of integrating spatial metrics for the development of sustainable tourism plans as part of the goals of sustainable development.

Keywords: built-up, growth, patterns, tourism, sustainable

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Authors: Arianna Sacerdoti

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This paper is original and fills, to our best Knowledge, a gap in secondary literature. It analyzes the presence of treatises in Silius Italicus’ Punica and what happens in the plot when a struggle ends. As a result, we will understand if treatises are stipulated or broken, and which narrative devices go with the presence of treatises and the end of the battles. Methodology will be text-oriented, and all the passages will be presented in the Latin language and discussed. In concluding, it is important to understand – in a poem based on war – the role of treatises and the end of battles in Silius Italicus.

Keywords: Flavian Epic, Silius Italicus, Punica, treatises

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Authors: Yee Hui Lim, Elena Gusareva, Irvan Luhung, Yulia Frank, Stephan Christoph Schuster

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Environmental pollution from microplastics (MPs) is an emerging concern worldwide. While the presence of microplastics has been well established in the marine and terrestrial environments, the prevalence of microplastics in the atmosphere is still poorly understood. Wet depositions such as rain or snow scavenge impurities from the atmosphere as it falls to the ground. These wet depositions serve as a useful tool in the removal of airborne particles that are suspended in the air. Therefore, the aim of this study is to investigate the presence of atmospheric microplastics and fibres through the analysis of air, rainwater and snow samples. Air samples were collected with filter-based air samplers from outdoor locations in Singapore. The sampling campaigns were conducted during and after each rain event. Rainwater samples from Singapore and Siberia were collected as well. Snow samples were also collected from Siberia as part of the ongoing study. Genomic DNA was then extracted from the samples and sequenced with shotgun metagenomics approach. qPCR analysis was conducted to quantify the total bacteria and fungi in the air, rainwater and snow samples. The results compared the bioaerosol profiles of all the samples. To observe the presence of microplastics, scanning electron microscope (SEM) was used. From the preliminary results, microplastics were detected. It can be concluded that there is a significant amount of atmospheric microplastics present, and its occurrence should be investigated in greater detail.

Keywords: atmospheric microplastics, metagenomics, scanning electron microscope, wet deposition

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Authors: Shailendra Kumar Mishra

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In this paper, we focus on how contextual factors like the physical presence of other perceivers and then developed induced emotional empathy towards a person with disabilities may reduce the automatic negative stereotypes and then response towards that person. We demonstrated in study 1 that negative attitude based on negative stereotypes assessed on ATDP-test questionnaires on five points Linkert-scale are significantly less negative when participants were tested with a group of perceivers and then tested alone separately by applying 3 (positive, indifferent, and negative attitude levels) X 2 (physical presence condition and alone) factorial design of ANOVA test. In the second study, we demonstrate, by applying regression analysis, in the presence of other perceivers, whether in a small group, participants showed more induced emotional empathy through stronger prosociality towards a high distress target like a person with disabilities in comparison of that of other stigmatized persons such as racial biased or gender-biased people. Thus results show that automatic affective response in the form of induced emotional empathy in perceiver and contextual factors like the presence of other perceivers automatically activate stronger prosocial norms and egalitarian goals towards physically challenged persons in comparison to other stigmatized persons like racial or gender-biased people. This leads to less negative attitudes and behaviour towards a person with disabilities.

Keywords: contextual factors, high distress target, induced emotional empathy, stronger prosociality

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Authors: Yi-Ting Wang, Wen-Shu Lai

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The subject of this paper is the photography in the 1983 film Paris, Texas, directed by Wim Wenders. Wenders is well known as a film director as well as a photographer. We have found that photography is shown as a photographic element in many of his films. Some of these photographs serve as details within the films, while others play important roles that are relevant to the story. This paper aims to consider photographs in film as a specific type of text, which is the output of both still photography and the film itself. In the film Paris, Texas, three sets of important photographs appear whose symbolic meanings are as dialectical as their text types. The relationship between the existence of these photos and the storyline is both dependent and isolated. The film’s images fly by and progress into other images, while the photos in the film serve a unique narrative function by stopping the continuously flowing images thus provide the viewer a space for imagination and contemplation. They are more than just artistic forms; they also contained multiple meanings. The photographs in Paris, Texas play the role of both presence and absence according to their shifting meanings. There are references to their presence: photographs exist between film time and narrative time, so in terms of the interaction between the characters in the film, photographs are a common symbol of the beginning and end of the characters’ journeys. In terms of the audience, the film’s photographs are a link in the viewing frame structure, through which the creative motivation of the film director can be explored. Photographs also point to the absence of certain objects: the scenes in the photos represent an imaginary map of emotion. The town of Paris, Texas is therefore isolated from the physical presence of the photograph, and is far more abstract than the reality in the film. This paper embraces the ambiguous nature of photography and demonstrates its presence and absence in film with regard to the meaning of text. However, it is worth reflecting that the temporary nature of the interpretation of the film’s photographs is far greater than any other type of photographic text: the characteristics of the text cause the interpretation results to change along with the variations in the interpretation process, which makes their meaning a dynamic process. The photographs’ presence or absence in the context of Paris, Texas also demonstrates the presence and absence of the creator, time, the truth, and the imagination. The film becomes more complete as a result of the revelation of the photographs, while the intertextual connection between these two forms simultaneously provides multiple possibilities for the interpretation of the photographs in the film.

Keywords: film, Paris, Texas, photography, Wim Wenders

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

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Authors: Manel Bouloudenine, Karima Djeddou, Hadjer Ben Manser, Hana Soualah Alila, Mohmed Bououdina

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This survey research involves the elaboration and characterization of silver nanoparticles for therapeutic and environmental applications. The silver nanoparticles "Ag NPs" were synthesized by reducing AgNO3 with microwaves. The characterization of nanoparticles was done by using Transmission Electron Microscopy " TEM ", Energy Dispersive Spectroscopy "EDS", Selected Area Electron Diffraction "SEAD", UV-Visible Spectroscopy and Dynamic Light Scattering "DLS". Transmission Electron Microscopy and Electron Diffraction have confirmed the nanoscale, the shape, and the crystalline quality of as synthesized silver nanoparticles. Elementary analysis has proved the purity of Ag NPs and the presence of the Surface Plasmon Resonance phenomenon "SPR". A strong absorption shift was observed in the visible range of the UV-visible spectrum of as synthesized Ag NPs, which indicates the presence of metallic silver. When the strong absorption in the ultraviolet range of the spectrum has revealed the presence of ionic Ag NPs ionic Ag aggregates species. The autocorrelation function measured by the Dynamic Light Scattering has shown a strong monodispersed character of Ag NPs, which is indicated by the presence of a single size population, with a minima and a maxima laying between 40 and 111 nm. Related to other research, our results confirm the performance properties of as synthesized Ag NPs, which allows them to be performing in many technological applications, including therapeutic and environmental ones.

Keywords: silvers nanoparticles, microwaves, EDS, TEM

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Authors: Ahmed Nour El Islam Ayad, Wafa Krika, Abdelghani Ayad, Moulay Larab, Houari Boudjella, Farid Benhamida

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The purpose of this study is to evaluate the magnetic emission of underground electric cable of high voltage, because these power lines generate electromagnetic interaction with other objects near to it. The aim of this work shows a numerical simulation of the magnetic field of buried 400 kV line in three cases: permanent and transient states of short circuit and the last case with the presence of the harmonics at different positions as a function of time variation, with finite element resolution using Comsol Multiphysics software. The results obtained showed that the amplitude and distribution of the magnetic flux density change in the transient state and the presence of harmonics. The results of this work calculate the magnetic field generated by the underground lines in order to evaluate and know their impact on ecology and health.

Keywords: underground, electric power cables, cables crossing, harmonic, emission

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Authors: M. S. M. Yusof, R. Ramli, S. K. C. Soh, N. Ismail, N. Ngah

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This study presents the synthesis of a series of methoxybenzoylthiourea amino acid derivatives. The compounds were obtained from the reactions between 2/3/4-methoxybenzoyl isothiocyanate with threonine. All of the compounds were characterized via mass spectrometry, ¹H and ¹³C NMR spectrometry, UV-Vis spectrophotometer and FT-IR spectroscopy. Mass spectra for all of the compounds showed the presence of molecular ion [M]⁺ peaks at m/z 312, which are in agreement to the calculated molecular weight. For ¹H NMR spectra, the presence of OCH₃, C=S-NH and C=O-NH protons were observed within range of δ_H 3.8-4.0 ppm, 11.1-11.5 ppm and 10.0-11.5 ppm, respectively. ¹³C NMR spectra in all compounds displayed the presence of OCH₃, C=O-NH, C=O-OH and C=S carbon resonances within range of δ_C 55.0-57.0 ppm, 165.0-168.0 ppm, 170.0-171.0 ppm and 180.0-182.0 ppm, respectively. In UV spectra, two absorption bands have been observed and both were assigned to the n-π* and π-π* transitions. Six vibrational modes of v(N-H), v(O-H), v(C=O-OH), v(C=O-NH), v(C=C) aromatic and v(C=S) appeared in the FT-IR spectra within the range of 3241-3467 cm^-1, 2976-3302 cm^-1, 1720-1768 cm^-1, 1655-1672 cm^-1, 1519-1525 cm^-1 and 754-763 cm^-1, respectively. The antibacterial activity for all of the compounds was screened against Staphylococcus aureus, Staphylococcus epidermidis, Salmonella typhimurium and Escherichia coli. However, no activity was observed.

Keywords: methoxybenzoyl isothiocyanate, amino acid, threonine, antibacterial

Procedia PDF Downloads 308

Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

Procedia PDF Downloads 32

Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

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Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. The existence of influential users who have developed a reputation for their knowledge and experience of specific topics is a major factor contributing to this impact. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is related to the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: Twitter, influencers, structured mechanism, Saudi Arabia

Procedia PDF Downloads 96

Authors: Radnoosh Mirzajani, Ebrahim Mirzajani, Heshmatollah Ebrahimi-Najafabadi

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Introduction: Hydrogen peroxide can be produced over the interaction of sodium dodecyl sulfate (SDS) with hemoglobin which would facilitate the oxidation process of hemoglobin. The presence of ascorbic acid (AA) can hinder the extreme oxidation of oxyhemoglobin. Methods: Hemoglobin was purified from blood samples according to the method of Williams. UV-V is spectra of Hb solutions mixed with different concentrations of SDS and AA were recorded. Chemical components, concentration, and spectral profiles were estimated using MCR-ALS techniques. Results: The intensity of soret band of OxyHb decreased due to the interaction of Hb with SDS. Furthermore, changes were also observed for peaks at 575 and 540. Subspace plots confirm the presence of OxyHb, MetHb, and Hemichrom in each mixture. The resolved concentration profiles using MCR-ALS reveal that the mole fraction of OxyHb increased upon the presence of AA up to a concentration level of 3 mM. The higher concentration of AA shows a reverse effect. AA demonstrated a dual effect on the interaction of hemoglobin with SDS. AA disturbs the interaction of SDS and hemoglobin and exhibits an antioxidative effect. However, it caused a tiny decrease in the mole fraction of OxyHb. Conclusions: H2O2 produces upon the interaction of OxyHb with SDS. Oxidation of OxyHb facilitates due to overproduction of H2O2. Ascorbic acid interacts with H2O2 to form dehydroascorbic acid. Furthermore, the available free SDS was reduced because the Gibbs free energy for micelle production of SDS became more negative in the presence of AA.

Keywords: hemoglobin, ascorbic acid, sodium dodecyl sulfate, multivariate curve resolution, antioxidant

Procedia PDF Downloads 86

Authors: Yogendra K. Karna, Lauren T. Bennett

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Fire-tolerant eucalypt forests are one of the major forest ecosystems of south-eastern Australia and thought to be highly resistant to frequent high severity wildfires. However, the impact of different severity wildfires on the canopy structure of fire-tolerant forest type is under-studied, and there are significant knowledge gaps in relation to the assessment of tree and stand level canopy structural dynamics and recovery after fire. Assessment of canopy structure is a complex task involving accurate measurements of the horizontal and vertical arrangement of the canopy in space and time. This study examined the utility of multitemporal, small-footprint lidar data to describe the changes in the horizontal and vertical canopy structure of fire-tolerant eucalypt forests seven years after wildfire of different severities from the tree to stand level. Extensive ground measurements were carried out in four severity classes to describe and validate canopy cover and height metrics as they change after wildfire. Several metrics such as crown height and width, crown base height and clumpiness of crown were assessed at tree and stand level using several individual tree top detection and measurement algorithm. Persistent effects of high severity fire 8 years after both on tree crowns and stand canopy were observed. High severity fire increased the crown depth but decreased the crown projective cover leading to more open canopy.

Keywords: canopy gaps, canopy structure, crown architecture, crown projective cover, multi-temporal lidar, wildfire severity

Procedia PDF Downloads 140