Search results for: temporal encoding

Authors: Andrzej Wałęga, Marta Cebulska, Agnieszka Ziernicka-Wojtaszek, Wojciech Młocek, Agnieszka Wałęga, Tommaso Caloiero

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Drought is one of the natural phenomena influencing many aspects of human activities like food production, agriculture, industry, and the ecological conditions of the environment. In the area of the Polish Carpathians, there are periods with a deficit of rainwater and an increasing frequency in dry months, especially in the cold half of the year. The aim of this work is a spatial and temporal analysis of drought, expressed as SPI in a heterogenous area of the Polish Carpathian and of the highland Region in the Central part of Europe based on long-term precipitation data. Also, to our best knowledge, for the first time in this work, drought characteristics analyzed via the SPI were discussed based on the atmospheric circulation calendar. The study region is the Upper Vistula Basin, located in the southern and south-eastern part of Poland. In this work, monthly precipitation from 56 rainfall stations was analysed from 1961 to 2022. The 3-, 6-, 9-, and 12-month Standardized Precipitation Index (SPI) were used as indicators of meteorological drought. For the 3-month SPI, the main climatic mechanisms determining extreme droughts were defined based on the calendar of synoptic circulations. The Mann-Kendall test was used to detect the trend of extreme droughts. Statistically significant trends of SPI were observed on 52.7% of all analyzed stations, and in most cases, a positive trend was observed. Statistically significant trends were more frequently observed in stations located in the western part of the analyzed region. Long-term droughts, represented by the 12-month SPI, occurred in all stations but not in all years. Short-term droughts (3-month SPI) were most frequent in the winter season, 6 and 9-month SPI in winter and spring, and 12-month SPI in winter and autumn, respectively. The spatial distribution of drought was highly diverse. The most intensive drought occurred in 1984, with the 6-month SPI covering 98% of the analyzed region and the 9 and 12-month SPI covering 90% of the entire region. Droughts exhibit a seasonal pattern, with a dominant 10-year periodicity for all analyzed variants of SPI. Additionally, Fourier analysis revealed a 2-year periodicity for the 3-, 6-, and 9-month SPI and a 31-year periodicity for the 12-month SPI. The results provide insights into the typical climatic conditions in Poland, with strong seasonality in precipitation. The study highlighted that short-term extreme droughts, represented by the 3-month SPI, are often caused by anticyclonic situations with high-pressure wedges Ka and Wa, and anticyclonic West as observed in 52.3% of cases. These findings are crucial for understanding the spatial and temporal variability of short and long-term extreme droughts in Central Europe, particularly for the agriculture sector dominant in the northern part of the analyzed region, where drought frequency is highest.

Keywords: atmospheric circulation, drought, precipitation, SPI, the Upper Vistula Basin

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Authors: Yichin Chen

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Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.

Keywords: aerial photogrammetry, landslide, landform change, Taiwan

Procedia PDF Downloads 134

Authors: M. Mansouri, P. Jaklitsch, E. Teiniker

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SQL injection on web applications is a very popular kind of attack. There are mechanisms such as intrusion detection systems in order to detect this attack. These strategies often rely on techniques implemented at high layers of the application but do not consider the low level of system calls. The problem of only considering the high level perspective is that an attacker can circumvent the detection tools using certain techniques such as URL encoding. One technique currently used for detecting low-level attacks on privileged processes is the tracing of system calls. System calls act as a single gate to the Operating System (OS) kernel; they allow catching the critical data at an appropriate level of detail. Our basic assumption is that any type of application, be it a system service, utility program or Web application, “speaks” the language of system calls when having a conversation with the OS kernel. At this level we can see the actual attack while it is happening. We conduct an experiment in order to demonstrate the suitability of system call analysis for detecting SQL injection. We are able to detect the attack. Therefore we conclude that system calls are not only powerful in detecting low-level attacks but that they also enable us to detect high-level attacks such as SQL injection.

Keywords: Linux system calls, web attack detection, interception, SQL

Procedia PDF Downloads 333

Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Why is it that Canada has not shared the same fate as the US (and many other nations) that have realized much worse outcomes relative to the COVID-19 pandemic? Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal healthcare is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, Canada, GIS, temporal analysis, ESRI

Procedia PDF Downloads 133

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

Procedia PDF Downloads 242

Authors: Ricardo Godoy, Herbert Venthur, Hector Jimenez, Andres Quiroz, Ana Mutis

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In agriculture, grape production has great economic importance at global level, considering that in 2013 it reached 7.4 million hectares (ha) covered by plantations of this fruit worldwide. Chile is the number one exporter in the world with 800,000 tons. However, these values have been threatened by the attack of the grapevine moth, Lobesia botrana (Denis & Schiffermuller) (Lepidoptera: Tortricidae), since its detection in 2008. Nowadays, the use of semiochemicals, in particular the major component of the sex pheromone, (E,Z)-7.9-dodecadienil acetate, are part of mating disruption methods to control L. botrana. How insect pests can recognize these molecules, is being part of huge efforts to deorphanize their olfactory mechanism at molecular level. Thus, an interesting group of proteins has been identified in the antennae of insects, where odorant-binding proteins (OBPs) are known by transporting molecules to odorant receptors (ORs) and a co-receptor (ORCO) causing a behavioral change in the insect. Other proteins such as chemosensory proteins (CSPs), ionotropic receptors (IRs), odorant degrading enzymes (ODEs) and sensory neuron membrane proteins (SNMPs) seem to be involved, but few studies have been performed so far. The above has led to an increasing interest in insect communication at a molecular level, which has contributed to both a better understanding of the olfaction process and the design of new pest management strategies. To date, it has been reported that the ORs can detect one or a small group of odorants in a specific way. Therefore, the objective of this study is the identification of genes that encode these ORs using the antennal transcriptome of L. botrana. Total RNA was extracted for females and males of L. botrana, and the antennal transcriptome sequenced by Next Generation Sequencing service using an Illumina HiSeq2500 platform with 50 million reads per sample. Unigenes were assembled using Trinity v2.4.0 package and transcript abundance was obtained using edgeR. Genes were identified using BLASTN and BLASTX locally installed in a Unix system and based on our own Tortricidae database. Those Unigenes related to ORs were characterized using ORFfinder and protein Blastp server. Finally, a phylogenetic analysis was performed with the candidate amino acid sequences for LbotORs including amino acid sequences of other moths ORs, such as Bombyx mori, Cydia pomonella, among others. Our findings suggest 61 genes encoding ORs and one gene encoding an ORCO in both sexes, where the greatest difference was found in the OR6 because of the transcript abundance according to the value of FPKM in females and males was 1.48 versus 324.00. In addition, according to phylogenetic analysis OR6 is closely related to OR1 in Cydia pomonella and OR6, OR7 in Epiphyas postvittana, which have been described as pheromonal receptors (PRs). These results represent the first evidence of ORs present in the antennae of L. botrana and a suitable starting point for further functional studies with selected ORs, such as OR6, which is potentially related to pheromonal recognition.

Keywords: antennal transcriptome, lobesia botrana, odorant receptors (ORs), phylogenetic analysis

Procedia PDF Downloads 177

Authors: Thomas Weber, Nina Strobel, Thomas Kohne, Eberhard Abele

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In context of the energy transition in Germany, the importance of so-called virtual power plants in the energy supply continues to increase. The progressive dismantling of the large power plants and the ongoing construction of many new decentralized plants result in great potential for optimization through synergies between the individual plants. These potentials can be exploited by mathematical optimization algorithms to calculate the optimal application planning of decentralized power and heat generators and storage systems. This also includes linear or linear mixed integer optimization. In this paper, procedures for reducing the number of decision variables to be calculated are explained and validated. On the one hand, this includes combining n similar installation types into one aggregated unit. This aggregated unit is described by the same constraints and target function terms as a single plant. This reduces the number of decision variables per time step and the complexity of the problem to be solved by a factor of n. The exact operating mode of the individual plants can then be calculated in a second optimization in such a way that the output of the individual plants corresponds to the calculated output of the aggregated unit. Another way to reduce the number of decision variables in an optimization problem is to reduce the number of time steps to be calculated. This is useful if a high temporal resolution is not necessary for all time steps. For example, the volatility or the forecast quality of environmental parameters may justify a high or low temporal resolution of the optimization. Both approaches are examined for the resulting calculation time as well as for optimality. Several optimization models for virtual power plants (combined heat and power plants, heat storage, power storage, gas turbine) with different numbers of plants are used as a reference for the investigation of both processes with regard to calculation duration and optimality.

Keywords: CHP, Energy 4.0, energy storage, MILP, optimization, virtual power plant

Procedia PDF Downloads 150

Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

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This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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Authors: H. Sakamoto, Y. Nakagawara, S. Oguri

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Drought stress is a critical environmental factor that adversely affects crop productivity and quality. Because of their immobile nature, plants have evolved mechanisms to sense and respond to drought stress. We identified a novel locus of Arabidopsis, designated DRA1 (drought responsive ankyrin 1), whose disruption leads to increased drought stress tolerance. DRA1 encodes a transmembrane protein with an ankyrin repeat motif that has been implicated in diverse cellular processes such as signal transduction. RT-PCR analysis revealed that there were at least two splicing variants of DRA1 transcripts in wild type plants. In response to drought stress, the levels of DRA1 transcripts retaining second and third introns were increased, whereas these introns were removed under unstressed conditions. These results suggest that DRA1 protein may negatively regulate plant drought tolerance and that the expression of DRA1 is regulated in response to drought stress by alternative splicing.

Keywords: alternative splicing, ankyrin repeat, Arabidopsis, drought tolerance

Procedia PDF Downloads 299

Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

Procedia PDF Downloads 295

Authors: S. J. Kim, Y. J. Yoo

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Slack-tide sampling was carried out at seven stations at high and low tides for a tidal cycle, in summer (7, 8, 9) and fall (10), 2016 to determine the differences of water quality according to tides in Masan Bay. The data were analyzed by Pearson correlation and factor analysis. The mixing state of all the water quality components investigated is well explained by the correlation with salinity (SAL). Turbidity (TURB), dissolved silica (DSi), nitrite and nitrate nitrogen (NNN) and total nitrogen (TN), which find their way into the bay from the streams and have no internal source and sink reaction, showed a strong negative correlation with SAL at low tide, indicating the property of conservative mixing. On the contrary, in summer and fall, dissolved oxygen (DO), hydrogen sulfide (H2S) and chemical oxygen demand with KMnO4 (CODMn) of the surface and bottom water, which were sensitive to an internal source and sink reaction, showed no significant correlation with SAL at high and low tides. The remaining water quality parameters showed a conservative or a non-conservative mixing pattern depending on the mixing characteristics at high and low tides, determined by the functional relationship between the changes of the flushing time and the changes of the characteristics of water quality components of the end-members in the bay. Factor analysis performed on the concentration difference data sets between high and low tides helped in identifying the principal latent variables for them. The concentration differences varied spatially and temporally. Principal factors (PFs) scores plots for each monitoring situation showed high associations of the variations to the monitoring sites. At sampling station 1 (ST1), temperature (TEMP), SAL, DSi, TURB, NNN and TN of the surface water in summer, TEMP, SAL, DSi, DO, TURB, NNN, TN, reactive soluble phosphorus (RSP) and total phosphorus (TP) of the bottom water in summer, TEMP, pH, SAL, DSi, DO, TURB, CODMn, particulate organic carbon (POC), ammonia nitrogen (AMN), NNN, TN and fecal coliform (FC) of the surface water in fall, TEMP, pH, SAL, DSi, H2S, TURB, CODMn, AMN, NNN and TN of the bottom water in fall commonly showed up as the most significant parameters and the large concentration differences between high and low tides. At other stations, the significant parameters showed differently according to the spatial and temporal variations of mixing pattern in the bay. In fact, there is no estuary that always maintains steady-state flow conditions. The mixing regime of an estuary might be changed at any time from linear to non-linear, due to the change of flushing time according to the combination of hydrogeometric properties, inflow of freshwater and tidal action, And furthermore the change of end-member conditions due to the internal sinks and sources makes the occurrence of concentration difference inevitable. Therefore, when investigating the water quality of the estuary, it is necessary to take a sampling method considering the tide to obtain average water quality data.

Keywords: conservative mixing, end-member, factor analysis, flushing time, high and low tide, latent variables, non-conservative mixing, slack-tide sampling, spatial and temporal variations, surface and bottom water

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Authors: Shyamli Singh, Ishupinder Kaur, Vinod K. Sharma

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Climate Change refers to the change in climate for extended period of time. Climate is changing from the past history of earth but anthropogenic activities accelerate this rate of change and which is now being a global issue. Increase in greenhouse gas emissions is causing global warming and climate change related issues at an alarming rate. Increasing temperature results in climate variability across the globe. Changes in rainfall patterns, intensity and extreme events are some of the impacts of climate change. Rainfall variability refers to the degree to which rainfall patterns varies over a region (spatial) or through time period (temporal). Temporal rainfall variability can be directly or indirectly linked to climate change. Such variability in rainfall increases the vulnerability of communities towards climate change. Increasing urbanization and unplanned developmental activities, the air quality is deteriorating. This paper mainly focuses on the rainfall variability due to increasing level of greenhouse gases. Rainfall data of 65 years (1951-2015) of Safdarjung station of Delhi was collected from Indian Meteorological Department and analyzed using Mann-Kendall test for time-series data analysis. Mann-Kendall test is a statistical tool helps in analysis of trend in the given data sets. The slope of the trend can be measured through Sen’s slope estimator. Data was analyzed monthly, seasonally and yearly across the period of 65 years. The monthly rainfall data for the said period do not follow any increasing or decreasing trend. Monsoon season shows no increasing trend but here was an increasing trend in the pre-monsoon season. Hence, the actual rainfall differs from the normal trend of the rainfall. Through this analysis, it can be projected that there will be an increase in pre-monsoon rainfall than the actual monsoon season. Pre-monsoon rainfall causes cooling effect and results in drier monsoon season. This will increase the vulnerability of communities towards climate change and also effect related developmental activities.

Keywords: greenhouse gases, Mann-Kendall test, rainfall variability, Sen's slope

Procedia PDF Downloads 177

Authors: Ali Reza Vaezi, Naser Fakori Ivand, Fereshteh Azarifam

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Interrill erosion is the detachment and transfer of soil particles between the rills due to the impact of raindrops and the shear stress of shallow surface runoff. This erosion can be affected by some soil properties such as texture, amount of organic matter and stability of soil aggregates. Information on the temporal variation of interrill erosion during a rainfall event and the effect soil properties have on it can help in understanding the process of runoff production and soil loss between the rills in hillslopes. The importance of this study is especially grate in semi-arid regions, where the soil is weakly aggregated and vegetation cover is mostly poor. Therefore, this research was conducted to investigate the temporal variation of surface flow and interrill erosion and the effect of soil properties on it in some semi-arid soils. A field experiment was done in eight different soil textures under simulated rainfalls with uniform intensity. A total of twenty four plots were installed for eight study soils with three replicates in the form of a random complete block design along the land. The plots were 1.2 m (length) × 1 m (width) in dimensions which designed with a distance of 3 m from each other across the slope. Then, soil samples were purred into the plots. The plots were surrounded by a galvanized sheet, and runoff and soil erosion equipment were placed at their outlets. Rainfall simulation experiments were done using a designed portable simulator with an intensity of 60 mm per hour for 60 minutes. A plastic cover was used around the rainfall simulator frame to prevent the impact of the wind on the free fall of water drops. Runoff production and soil loss were measured during 1 hour time with 5-min intervals. In order to study soil properties, such as particle size distribution, aggregate stability, bulk density, ESP and Ks were determined in the laboratory. Correlation and regression analysis was done to determine the effect of soil properties on runoff and interrill erosion. Results indicated that the study soils have lower booth organic matter content and aggregate stability. The soils, except for coarse textured textures, are calcareous and with relatively higher exchangeable sodium percentages (ESP). Runoff production and soil loss didn’t occur in sand, which was associated with higher infiltration and drainage rates. In other study soils, interrill erosion occurred simultaneously with the generation of runoff. A strong relationship was found between interrill erosion and surface runoff (R2 = 0.75, p< 0.01). The correlation analysis showed that surface runoff was significantly affected by some soil properties consisting of sand, silt, clay, bulk density, gravel, hydraulic conductivity (Ks), lime (calcium carbonate), and ESP. The soils with lower Ks such as fine-textured soils, produced higher surface runoff and more interrill erosion. In the soils, Surface runoff production temporally increased during rainfall and finally reached a peak after about 25-35 min. Time to peak was very short (30 min) in fine-textured soils, especially clay, which was related to their lower infiltration rate.

Keywords: erosion plot, rainfall simulator, soil properties, surface flow

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Authors: Sheetal Sharma

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Urban planning is associated with land transformation from natural areas to modified and developed ones which leads to modification of natural environment. The basic knowledge of relationship between both should be ascertained before proceeding for the development of natural areas. Changes on land surface due to build up pavements, roads and similar land cover, affect surface water flow. There is a gap between urban planning and basic knowledge of hydrological processes which should be known to the planners. The paper aims to identify these variations in surface flow due to urbanization for a temporal scale of 40 years using Storm Water Management Mode (SWMM) and again correlating these findings with the urban planning guidelines in study area along with geological background to find out the suitable combinations of land cover, soil and guidelines. For the purpose of identifying the changes in surface flows, 19 catchments were identified with different geology and growth in 40 years facing different ground water levels fluctuations. The increasing built up, varying surface runoff are studied using Arc GIS and SWMM modeling, regression analysis for runoff. Resulting runoff for various land covers and soil groups with varying built up conditions were observed. The modeling procedures also included observations for varying precipitation and constant built up in all catchments. All these observations were combined for individual catchment and single regression curve was obtained for runoff. Thus, it was observed that alluvial with suitable land cover was better for infiltration and least generation of runoff but excess built up could not be sustained on alluvial soil. Similarly, basalt had least recharge and most runoff demanding maximum vegetation over it. Sandstone resulted in good recharging if planned with more open spaces and natural soils with intermittent vegetation. Hence, these observations made a keystone base for planners while planning various land uses on different soils. This paper contributes and provides a solution to basic knowledge gap, which urban planners face during development of natural surfaces.

Keywords: runoff, built up, roughness, recharge, temporal changes

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Authors: Numtana Ladplee, Cherif Haberih

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The value of service evaluation depends critically on guests’ understanding of the evaluation objectives and their roles. The present research presents a three-phase investigation of the impact of evaluating participants’ theories about their roles: (a) identifying the theories, (b) testing the process consequences of participants’ role theories, and (c) gaining insights into the impact of participants’ role theories by testing key moderator/s. The findings of this study will hopefully indicate that (a) when forewarned of an upcoming evaluation task, consumers tend to believe that the evaluation objective is to identify aspects that need improvement, (b) this expectation produces a conscious attempt to identify negative aspects, although the encoding of attribute information is not affected, and (c) cognitive load during the evaluation experience greatly decreases the negativity of expected evaluations. The present study can be applied to other market research techniques and thereby improve our understanding of consumer inputs derived from market research. Such insights can help diminish biases produced by participants’ correct or incorrect theories regarding their roles.

Keywords: fulfillment, hotel guests, service, Thailand

Procedia PDF Downloads 254

Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

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Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

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Authors: Farshid Hajati, Soheila Gheisari, Ali Cheraghian, Yongsheng Gao

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This paper presents a new Surface Geodesic Derivative Pattern (SGDP) for matching textured deformable 3D surfaces. SGDP encodes micro-pattern features based on local surface higher-order derivative variation. It extracts local information by encoding various distinctive textural relationships contained in a geodesic neighborhood, hence fusing texture and range information of a surface at the data level. Geodesic texture rings are encoded into local patterns for similarity measurement between non-rigid 3D surfaces. The performance of the proposed method is evaluated extensively on the Bosphorus and FRGC v2 face databases. Compared to existing benchmarks, experimental results show the effectiveness and superiority of combining the texture and 3D shape data at the earliest level in recognizing typical deformable faces under expression, illumination, and pose variations.

Keywords: 3D face recognition, pose, expression, surface matching, texture

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Laura Bickel

Abstract:

This paper aims to investigate to what extent Merleau-Ponty’s philosophy of body memory serves as a viable resource for the enactive approach to cognitive science and its first-person experience-based research on ‘recurrent depressive disorder’ coded F33 in ICD-10. In pursuit of this goal, the analysis begins by revisiting the neuroreductive paradigm. This paradigm serves biological psychiatry to explain the condition of vital contact in terms of underlying neurophysiological mechanisms. It is demonstrated that the neuroreductive model cannot sufficiently account for the depressed person’s episodical withdrawal in causal terms. The analysis of the irregular loss of vital resonance requires integrating the body as the subject of experience and its phenomenological time. Then, it is shown that the enactive approach to depression as disordered sense-making is a promising alternative. The enactive model of perception implies that living beings do not register pre-existing meaning ‘out there’ but unfold ‘sense’ in their action-oriented response to the world. For the enactive approach, Husserl’s passive synthesis of inner time consciousness is fundamental for what becomes perceptually present for action. It seems intuitive to bring together the enactive approach to depression with the long-standing view in phenomenological psychopathology that explains the loss of vital contact by appealing to the disruption of the temporal structure of consciousness. However, this paper argues that the disruption of the temporal structure is not justified conceptually. Instead, one may integrate Merleau-Ponty’s concept of the past as the unconscious into the enactive approach to depression. From this perspective, the living being’s experiential and biological past inserts itself in the form of habit and bodily skills and ensures action-oriented responses to the environment. Finally, it is concluded that the depressed person’s withdrawal indicates the impairment of this application process. The person suffering from F33 cannot actualize sedimented meaning to respond to the valences and tasks of a given situation.

Keywords: depression, enactivism, neuroreductionsim, phenomenology, temporality

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

Abstract:

Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: S. Pesina, T. Solonchak

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Phenomenological analysis is not based on natural language, but ideal language which is able to be a carrier of ideal meanings – eidos representing typical structures or essences. For this purpose, it’s necessary to release from the spatio-temporal definiteness of a subject and then state its noetic essence (eidos) by means of free fantasy generation. Herewith, as if a totally new objectness is created - the universal, confirming the thesis that thinking process takes place in generalizations passing by numerous means through the specific to the general and from the general through the specific to the singular.

Keywords: lexical eidos, phenomenology, noema, polysemantic word, semantic core

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Authors: Mei Chen, Yingping Hou, Michelle Hao, Soheil Aghamohammadzadeh, Esteban Terzo, Roger Clark, Vijay Modur

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Background: Recessive Dystrophic Epidermolysis Bullosa (RDEB) is a genetic skin condition characterized by skin tearing and unremitting blistering upon minimal trauma. Repeated blistering, fibrosis, and scarring lead to aggressive squamous cell carcinoma later in life. RDEB is caused by mutations in the COL7A1 gene encoding collagen type VII (C7), the major component of anchoring fibrils mediating epidermis-dermis adherence. Nonsense mutations in the COL7A1 gene of a subset of RDEB patients leads to premature termination codons (PTC). Similarly, most Junctional Epidermolysis Bullosa (JEB) cases are caused by nonsense mutations in the LAMB3 gene encoding the β3 subunit of laminin 332. Currently, there is an unmet need for the treatment of RDEB and JEB. Zikani Therapeutics has discovered an array of macrocyclic compounds with ring structures similar to macrolide antibiotics that can facilitate readthrough activity of nonsense mutations in the COL7A1 and LAMB3 genes by acting as Ribosome Modulating Agents (RMAs). The medicinal chemistry synthetic advancements of these macrocyclic compounds have allowed targeting the human ribosome while preserving the structural elements responsible for the safety and pharmacokinetic profile of clinically used macrolide antibiotics. Methods: C7 expression was used as a measure of readthrough activity by immunoblot assays in two primary human fibroblasts from RDEB patients (R578X/R578X and R163X/R1683X-COL7A1). Similarly, immunoblot assays in C325X/c.629-12T > A-LAMB3 keratinocytes were used to measure readthrough activity for JEB. The relative readthrough activity of each compound was measured relative to Gentamicin. An imaging-based fibroblast migration assay was used as an assessment of C7 functionality in RDEB-fibroblasts over 16-20 hrs. The incubation period for the above experiments was 48 hrs for RDEB fibroblasts and 72 hours for JEB keratinocytes. Results: 9 RMAs demonstrated increased protein expression in both patient RDEB fibroblasts. The highest readthrough activity at tested concentrations without cytotoxicities increased protein expression up to 179% of Gentamicin (400 µg/ml), with favored readthrough activity in R163X/R1683X-COL7A1 fibroblasts. Concurrent with protein expression, fibroblast hypermotility phenotype observed in RDEB was rescued by reducing motility by ~35% to WT levels (the same level as 690 µM Gentamicin treated cells). Laminin β3 expression was also shown to be increased by 6 RMAs in keratinocytes to 33-83% of (400 µg/ml) Gentamicin. Conclusions: To date, 9 RMAs have been identified that enhance the expression of functional C7 in a mutation-dependent manner in two different RDEB patient fibroblast backgrounds (R578X/R578X and R163X/R1683X-COL7A1). A further 6 RMAs have been identified that enhance the readthrough of C325X-LAMB3 in JEB patient keratinocytes. Based on the clinical trial conducted by us with topical gentamycin in 2017, Zikani’s RMAs achieve clinically significant levels of read-through for the treatment of recessive dystrophic and Junctional Epidermolysis Bullosa.

Keywords: epidermolysis bullosa, nonsense mutation, readthrough, ribosome modulation

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya

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The theoretical analysis is carried out to get the relation between the ultrasonic wave velocity and the value of residual stresses. The laser-ultrasonic method is developed to evaluate the residual stresses and subsurface defects in metals. The method is based on the laser thermooptical excitation of longitudinal ultrasonic wave sand their detection by a broadband piezoelectric detector. A laser pulse with the time duration of 8 ns of the full width at half of maximum and with the energy of 300 µJ is absorbed in a thin layer of the special generator that is inclined relative to the object under study. The non-uniform heating of the generator causes the formation of a broadband powerful pulse of longitudinal ultrasonic waves. It is shown that the temporal profile of this pulse is the convolution of the temporal envelope of the laser pulse and the profile of the in-depth distribution of the heat sources. The ultrasonic waves reach the surface of the object through the prism that serves as an acoustic duct. At the interface ‚laser-ultrasonic transducer-object‘ the conversion of the most part of the longitudinal wave energy takes place into the shear, subsurface longitudinal and Rayleigh waves. They spread within the subsurface layer of the studied object and are detected by the piezoelectric detector. The electrical signal that corresponds to the detected acoustic signal is acquired by an analog-to-digital converter and when is mathematically processed and visualized with a personal computer. The distance between the generator and the piezodetector as well as the spread times of acoustic waves in the acoustic ducts are the characteristic parameters of the laser-ultrasonic transducer and are determined using the calibration samples. There lative precision of the measurement of the velocity of longitudinal ultrasonic waves is 0.05% that corresponds to approximately ±3 m/s for the steels of conventional quality. This precision allows one to determine the mechanical stress in the steel samples with the minimal detection threshold of approximately 22.7 MPa. The results are presented for the measured dependencies of the velocity of longitudinal ultrasonic waves in the samples on the values of the applied compression stress in the range of 20-100 MPa.

Keywords: laser-ultrasonic method, longitudinal ultrasonic waves, metals, residual stresses

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression.

Keywords: image compression, arithmetic coding, Run Length Coding, RLC, Sorted Run Length Coding, SRLC, Meteosat Second Generation, MSG

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Authors: Xinyuan Liu, Xiaojun Jing, Yuan He, Junsheng Mu

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Aspect-based Sentiment Analysis (ABSA) has attracted much attention due to its capacity to determine the sentiment polarity of the certain aspect in a sentence. In previous works, great significance of the interaction between aspect and sentence has been exhibited in ABSA. In consequence, a Multi-Level Attentional Networks (MLAN) is proposed. MLAN consists of four parts: Embedding Layer, Encoding Layer, Multi-Level Attentional (MLA) Layers and Final Prediction Layer. Among these parts, MLA Layers including Aspect Level Attentional (ALA) Layer and Interactive Attentional (ILA) Layer is the innovation of MLAN, whose function is to focus on the important information and obtain multiple levels’ attentional weighted representation of aspect and sentence. In the experiments, MLAN is compared with classical TD-LSTM, MemNet, RAM, ATAE-LSTM, IAN, AOA, LCR-Rot and AEN-GloVe on SemEval 2014 Dataset. The experimental results show that MLAN outperforms those state-of-the-art models greatly. And in case study, the works of ALA Layer and ILA Layer have been proven to be effective and interpretable.

Keywords: deep learning, aspect-based sentiment analysis, attention, natural language processing

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Authors: Pei-Chih Wu, Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Hsien-Chang Wang

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The impact of climate change to health has always been well documented. Amongst them, water-borne infectious diseases, chronic adverse effects or cancer risks due to chemical contamination in flooding or drought events are especially important in river basin. This study therefore utilizes GIS and different models to integrate demographic, land use, disaster prevention, social-economic factors, and human health assessment in the Erren River basin. Therefore, through the collecting of climatic, demographic, health surveillance, water quality and other water monitoring data, potential risks associated with the Erren River Basin are established and to understand human exposure and vulnerability in response to climate extremes. This study assesses the temporal and spatial patterns of melioidosis (2000-2015) and various cancer incidents in Tainan and Kaohsiung cities. The next step is to analyze the spatial association between diseases incidences, climatic factors, land uses, and other demographic factors by using ArcMap and GeoDa. The study results show that amongst all melioidosis cases in Taiwan, 24% cases (115) residence occurred in the Erren River basin. The relationship between the cases and in Tainan and Kaohsiung cities are associated with population density, aging indicator, and residence in Erren River basin. Risks from flooding due to heavy rainfall and fish farms in spatial lag regression are also related. Through liver cancer, the preliminary analysis in temporal and spatial pattern shows an increases pattern in annual incidence without clusters in Erren River basin. Further analysis of potential cancers connected to heavy metal contamination from water pollution in Erren River is established. The final step is to develop an assessment tool for human exposure from water contamination and vulnerability in response to climate extremes for the second year.

Keywords: climate change, health impact, health adaptation, Erren River Basin

Procedia PDF Downloads 287

Authors: Masoud Abedi, Abbas Malekpour, Peter Luksch, Mohammad Reza Mojtabaei

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The use of short texts in communication has been greatly increasing in recent years. Applying different languages in short texts has led to compulsory use of Unicode strings. These strings need twice the space of common strings, hence, applying algorithms of compression for the purpose of accelerating transmission and reducing cost is worthwhile. Nevertheless, other compression methods like gzip, bzip2 or PAQ due to high overhead data size are not appropriate. The Huffman algorithm is one of the rare algorithms effective in reducing the size of short Unicode strings. In this paper, an algorithm is proposed for compression of very short Unicode strings. At first, every new character to be sent to a destination is inserted in the proposed mapping table. At the beginning, every character is new. In case the character is repeated for the same destination, it is not considered as a new character. Next, the new characters together with the mapping value of repeated characters are arranged through a specific technique and specially formatted to be transmitted. The results obtained from an assessment made on a set of short Persian and Arabic strings indicate that this proposed algorithm outperforms the Huffman algorithm in size reduction.

Keywords: Algorithms, Data Compression, Decoding, Encoding, Huffman Codes, Text Communication

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Authors: Sharein El-Tourky, Sharon Smith, Gary Hitchcock

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Effective fisheries management is necessarily dependent on the accuracy of fisheries models, which can be limited if they omit critical elements. One critical element in the formulation of these models is the trophic interactions at the larval stage of fish development. At this stage, fish mortality rates are at their peak and survival is often determined by resource limitation. Thus it is crucial to identify and quantify essential prey resources and determine how they vary in abundance and availability. The main resources larval fish consume are mesozooplankton. In the Straits of Florida, little is known about temporal and spatial variability of the mesozooplankton community despite its importance as a spawning ground for fish such as the Blue Marlin. To investigate mesozooplankton distribution patterns in the Straits of Florida, a transect of 16 stations from Miami to the Bahamas was sampled once a month in 2003 and 2004 at four depths. We found marked temporal and spatial variability in mesozooplankton biomass, diversity, and depth distribution. Mesozooplankton biomass peaked on the western boundary of the SOF and decreased gradually across the straits to a minimum at eastern stations. Midcurrent stations appeared to be a region of enhanced year-round variability, but limited seasonality. Examination of dominant zooplankton groups revealed groups could be parsed into 6 clusters based on abundance. Of these zooplankton groups, copepods were the most abundant zooplankton group, with the 20 most abundant species making up 86% of the copepod community. Copepod diversity was lowest at midcurrent stations and highest in the Eastern SOF. Interestingly, one copepods species, previously identified to compose up to 90% of larval blue marlin and sailfish diets in the SOF, had a mean abundance of less than 7%. However, the unique spatial and vertical distribution patterns of this copepod coincide with peak larval fish spawning periods and larval distribution, suggesting an important relationship requiring further investigation.

Keywords: mesozooplankton biodiversity, larval fish diet, food web, Straits of Florida, vertical distribution, spatiotemporal variability, cross-current comparisons, Gulf Stream

Procedia PDF Downloads 533

Authors: Dan Kanmegne

Abstract:

Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: Ritvik Chauhan, Vijay Kumar Baraik

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Crime is a rare event on earth surface. It is not simple but a complex event occurring in a spatio- temporal environment. Crime is one of the most serious security threats to human environments as it may result in harm to the individuals through the loss of property, physical and psychological injuries. The conventional studies done on different nature crime was mostly related to laws, psychological, social and political themes. The geographical areas are heterogeneous in their environmental conditions, associations between structural conditions, social organization which contributing specific crimes. The crime pattern analysis is made through theories in which criminal events occurs in persistent, identifiable patterns in a particular space and time. It will be the combined analysis of spatial factors and rational factors to the crime. In this study, we are analyzing the combined factors for the origin of crime against children. Children have always been vulnerable to victimization more because they are silent victims both physically and mentally to crimes and they even not realize what is happening with them. Their trusting nature and innocence always misused by criminals to perform crimes. The nature of crime against children is changed in past years like child rape, kidnapping &abduction, selling & buying of girls, foeticide, infanticide, prostitution, child marriage etc turned to more cruel and inhuman. This study will focus on understanding the space-time pattern of crime against children during the period 2001-2012. It also makes an attempt to explore and ascertain the association of crimes categorised against children, its rates with various geographical and socio-demographic factors through causal analysis using selected indicators (child sex-ratio, education, literacy rate, employment, income, etc.) obtained from the Census of India and other government sources. The outcome of study will help identifying the high crime regions with specified nature of crimes. It will also review the existing efforts and exploring the new plausible measure for tracking, monitoring and minimization of crime rate to meet the end goal of protecting the children from crimes committed against them.

Keywords: crime against children, geographic profiling, spatio-temporal analysis, hotspot

Procedia PDF Downloads 197