Search results for: contention resolution

Authors: Thusitha B. Abeysekara, M. A. Nihal Chandrathilake

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The aim of this research is to examine the legal mechanism of resolving maritime disputes by arbitration, and it would be a reference point on the analysis of USA approaches. In doing so, the research aims to analyse the relevant legal principles in the context of current maritime arbitration practices in selected jurisdictions. The research also aims to analyse the advantages and applicability of arbitration in maritime dispute settlements over the litigation and further approaches the role of specialist maritime arbitration institutes in the USA and the position of international merchant organizations in maritime arbitration. Further, research values the legislative aspects of maritime arbitration. The study would evaluate the contemporary issues in maritime arbitration practices in the USA and further analyses the statistical information on maritime arbitration. Finally, the research made remarks to often parallel consequence in USA legal systems in maritime arbitration and despite the fundamental divergences of the applicable principles and practices of maritime arbitration. The research finally suggests the doctrine should reshape with equitable remedies and international maritime arbitration practices with its institutional impact rather than using as statutory rules related maritime arbitration.

Keywords: arbitration, international shipping, maritime dispute, New York convention

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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: Reshma Raskar-Phule, Makarand Landge, Saurabh Singh, Vijay Singh, Jash Saparia, Shivam Tripathi

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For any construction project, slope calculations are necessary in order to evaluate constructability on the site, such as the slope of parking lots, sidewalks, and ramps, the slope of sanitary sewer lines, slope of roads and highways. When slopes and grades are to be determined, designers are concerned with establishing proper slopes and grades for their projects to assess cut and fill volume calculations and determine inverts of pipes. There are several established instruments commonly used to determine slopes, such as Dumpy level, Abney level or Hand Level, Inclinometer, Tacheometer, Henry method, etc., and surveyors are very familiar with the use of these instruments to calculate slopes. However, they have some other drawbacks which cannot be neglected while major surveying works. Firstly, it requires expert surveyors and skilled staff. The accessibility, visibility, and accommodation to remote hilly terrain with these instruments and surveying teams are difficult. Also, determination of gentle slopes in case of road and sewer drainage constructions in congested urban places with these instruments is not easy. This paper aims to develop a method that requires minimum field work, minimum instruments, no high-end technology or instruments or software, and low cost. It requires basic and handy surveying accessories like a plane table with a fixed weighing machine, standard weights, alidade, tripod, and ranging rods should be able to determine the terrain slope in congested areas as well as in remote hilly terrain. Also, being simple and easy to understand and perform the people of that local rural area can be easily trained for the proposed method. The idea for the proposed method is based on the principle of resolution of weight components. When any object of standard weight ‘W’ is placed on an inclined surface with a weighing machine below it, then its cosine component of weight is presently measured by that weighing machine. The slope can be determined from the relation between the true or actual weight and the apparent weight. A proper procedure is to be followed, which includes site location, centering and sighting work, fixing the whole set at the identified station, and finally taking the readings. A set of experiments for slope determination, mild and moderate slopes, are carried out by the proposed method and by the theodolite instrument in a controlled environment, on the college campus, and uncontrolled environment actual site. The slopes determined by the proposed method were compared with those determined by the established instruments. For example, it was observed that for the same distances for mild slope, the difference in the slope obtained by the proposed method and by the established method ranges from 4’ for a distance of 8m to 2o15’20” for a distance of 16m for an uncontrolled environment. Thus, for mild slopes, the proposed method is suitable for a distance of 8m to 10m. The correlation between the proposed method and the established method shows a good correlation of 0.91 to 0.99 for various combinations, mild and moderate slope, with the controlled and uncontrolled environment.

Keywords: surveying, plane table, weight component, slope determination, hilly terrain, construction

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Authors: Huiwu Yu, Xiangyou Li, Xiaoyan Zeng

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Porous spheres have been widely used in many fields due to their attractive features. In this work, an approach for fabricating porous spheres of nanoparticles was presented, in which the nanoparticles were welded together to form micro spheres by simply irradiating the nanoparticles in liquid medium by a picosecond laser. As an example, anatase titanium dioxide was chosen as a typical material on account of its metastability. The structure and morphologies of the products were characterised by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman, and high-resolution transmission electron microscopy (HRTEM), respectively. The results showed that, anatase titanium dioxide micro spheres (2-10 μm) with macroporous (10-100 nm) were prepared from nano-anatase titanium dioxide nanoparticles (10-100 nm). The formation process of polycrystalline anatase titanium dioxide microspheres was investigated with different liquid mediums and the input laser fluences. Thus, this facile laser irradiation approach might provide a way for the fabrication of porous microspheres without phase-transition.

Keywords: titanium dioxide, porous microspheres, picosecond laser, nano-welding

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Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks

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Metal-enhanced luminescence of silicon nano crystals (SiNCs) was determined using two different particle sizes of silver nano particles (AgNPs). SiNCs have been characterized by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR) and X-ray photo electron spectroscopy (XPS). It is found that the SiNCs are crystalline with an average diameter of 65 nm and FCC lattice. AgNPs were synthesized using photochemical reduction of AgNO3 with sodium dodecyl sulphate (SDS). The enhanced luminescence of SiNCs by AgNPs was evaluated by confocal Raman microspectroscopy. Enhancement up to ×9 and ×3 times were observed for SiNCs that mixed with AgNPs which have an average particle size of 100 nm and 30 nm, respectively. Silver NPs-enhanced luminescence of SiNCs occurs as a result of the coupling between the excitation laser light and the plasmon bands of AgNPs; thus this intense field at AgNPs surface couples strongly to SiNCs.

Keywords: silver nanoparticles, surface enhanced raman spectroscopy (SERS), silicon nanocrystals, luminescence

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Authors: Luisa Carrer, Lorenzo De Masi

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In this paper, we exploit the massive amount of information from Facebook to build a measure of gender attitudes in Italy at a previously impossible resolution—the municipal level. We construct our index via a machine learning method to replicate a benchmark region-level measure. Interestingly, we find that most of the variation in our Gender Norms Index (GNI) is across towns within narrowly defined geographical areas rather than across regions or provinces. In a second step, we show how this local variation in norms can be leveraged for identification purposes. In particular, we use our index to investigate whether these differences in norms carry over to the policy activity of politicians elected in the Italian Parliament. We document that females are more likely to sit in parliamentary committees focused on gender-sensitive matters, labor, and social issues, but not if they come from a relatively conservative town. These effects are robust to conditioning the legislative term and electoral district, suggesting the importance of social norms in shaping legislators’ policy activity.

Keywords: gender equality, gender norms index, Facebook, machine learning, politics

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Seyed Mahdi Rafiaei

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In this investigation, firstly Eu3+ doped YVO4 phosphor was synthesized using solid-state method. Then silica was coated on the surface of particles via sol-gel method. To study the influence of SiO2 addition on microstructure and photoluminescence characteristics of YVO4:4% Eu3+ phosphor materials, we employed X-ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM), High-Resolution Transmitted Electron Microscope (HRTEM), Focused Ion Beam (FIB), Brunauer Emmett Teller (BET), Inductively coupled plasma (ICP), Electron Spin Resonance (ESR) and Photoluminescence (PL) equipments. The XPS characterization confirmed the formation of Y–O–Si and V-O-Si bondings between YVO4:Eu3+ phosphor particle and SiO2 coating. In addition, it was found that although the amounts of added SiO2 were not remarkable, but it resulted in enhancement of emission intensity of the phosphors. Finally by employing ESR analysis, it was shown that surface oxygen vacancies, result in reduction of V5+ to the lower valence state of V4+.

Keywords: solid state, sol-gel, silica, coating, photoluminescence

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Authors: Parveen Kundu, Zile Singh, Kunika Kundu, Swaran Kaur

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Context: Tuberculous osteomyelitis is a relatively uncommon condition that can present with various clinical and radiological features, often mimicking bone tumors or tumor-like lesions. In endemic countries like India, tuberculosis should be considered as a potential differential diagnosis for lytic bone lesions. This study aimed to highlight the different presentations of tuberculosis that can mimic tumors or tumor-like lesions in bone and emphasize the successful outcome of antitubercular therapy (ATT) in treating these cases. Research Aim: The main objective of this research was to explore the varied presentations of tuberculosis that mimic bone tumors or tumor-like lesions both clinically and radiologically, focusing on different bones. The study aimed to raise awareness among clinicians about this possibility and highlight the importance of histopathological confirmation before initiating treatment for lytic bone lesions. Methodology: This study utilized a retrospective review of 22 patients with suspected lytic bone lesions, who were subsequently diagnosed with tuberculous osteomyelitis through histopathological examination. The cases were collected over a period of ten years. Eleven cases required curettage for extensive lesions with sequestrations, while all 22 patients received 12 months of antitubercular therapy. Findings: The study included 14 male and 8 female patients, ranging in age from 3 to 61 years, with an average age of 22.05. The clinical and radiological presentations varied, with examples including bone cysts in the metaphyseal area of long bones, lesions resembling chondroblastomas, giant cell tumors, and osteoid osteoma, as well as multifocal lytic lesions resembling metastasis or multiple myeloma. One patient had lesions in both the clavicle and hand. Lesions mimicking chondromas were also observed in the phalanges of the hand and foot metatarsal. All patients showed resolution of the lesions and no residual disability following ATT. Theoretical Importance: This study highlights the importance of considering tuberculosis as a potential differential diagnosis for lytic bone lesions, particularly in endemic regions. It emphasizes the need for histopathological confirmation to accurately diagnose tuberculous osteomyelitis, as this is considered the gold standard. Data Collection and Analysis Procedures: Data for this study were collected retrospectively from medical records and radiological images of the 22 patients. The cases were analyzed based on clinical presentation, radiological findings, and histopathological confirmation. The outcomes of antitubercular therapy were also assessed. The data were summarized and presented descriptively. Question Addressed: This study aimed to address the question of how tuberculosis can mimic different bone tumors and tumor-like lesions clinically and radiologically. It also aimed to assess the successful outcome of antitubercular therapy in treating these cases. Conclusion: Tuberculous osteomyelitis can present with varied clinical and radiological features, often mimicking bone tumors or tumor-like lesions. Clinicians should consider tuberculosis as a potential diagnosis for lytic bone lesions, especially in endemic areas. Histopathological confirmation is essential for accurate diagnosis. Antitubercular therapy is an effective treatment for tuberculous osteomyelitis, leading to the resolution of the lesions with no residual disability.

Keywords: tuberculosis, tumor, curettage, bone

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Authors: Bong Keun Kang, Sung Suk Oh, Jeong-Woo Sohn, Jong-Ryul Choi, Young Ho Kim

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In this paper, we describe two-step micro-pattering by using laser cutting and wax printing. Wax printing is performed only on the bridges for hydrophobic barriers. We prepared 405nm blue-violet laser module and wax pencil module. And, this two modules combine x-y plot. The hollow microstructure formed by laser patterning define the hydrophilic flowing paths. However, bridges are essential to avoid the cutting area being the island. Through the support bridges, microfluidic solution spread out to the unnecessary areas. Chromatography blotting paper was purchased from Whatman. We used 20x20 cm and 46x57 cm of chromatography blotting paper. Axis moving speed of x-y plot was the main parameter of optimization. For aligning between the two patterning, the paper sheet was taped at the bottom. After the two-step patterning, temperature curing step was done at 110-130 °C. The resolution of the fabrication and the potential of the multiplex detection were investigated.

Keywords: µPADs, microfluidic, biosensor, mass-fabrication

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Authors: K. Santacruz-Gomez, E. Silva-Campa, S. Álvarez-García, V. Mata-Haro, D. Soto-Puebla, M. Pedroza-Montero

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Blood gamma irradiation is the only available method to prevent transfusion-associated graft versus host disease (TA-GVHD). However, when blood is irradiated, determine blood shelf time is crucial. Non-irradiated blood has a self-time from 21 to 35 days when is preserved with an anticoagulated solution and stored at 4°C. During their storage, red blood cells (RBC) undergo a series of biochemical, biomechanical and molecular changes involving what is known as storage lesion (SL). SL include loss of structural integrity of RBC, a decrease of 2,3-diphosphatidylglyceric acid levels, and an increase of both ion potassium concentration and hemoglobin (Hb). On the other hand, Atomic force Microscopy (AFM) represents a versatile tool for a nano-scale high-resolution topographic analysis in biological systems. In order to evaluate SL in irradiated and non-irradiated blood, RBC topography and morphometric parameters were obtained from an AFM XE-BIO system. Cell viability was followed using flow cytometry. Our results showed that early markers as nanoscale roughness, allow us to evaluate blood quality since another perspective.

Keywords: AFM, blood γ-irradiation, roughness, storage lesion

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Authors: Marilyn Painagan

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This study was conducted to predict the potential geographical distribution of the banana aphid (Pentalonia negronervosa) in North Cotabato through climate envelope approach of DIVA-GIS, a software for analyzing the distribution of organisms to elucidate geographic and ecological patterns. A WorldClim database that was based on weather conditions recorded last 1950 to 2000 with a spatial resolution of approximately 1x1 km. was used in the bioclimatic modelling, this database includes temperature, precipitation, evapotranspiration and bioclimatic variables which was measured at many different locations, a bioclimatic modelling was done in the study. The study revealed that the western part of Magpet and Arakan and the municipality of Antipas are at high potential risk of occurrence of banana aphid while it is not likely to occur in the municipalities of Aleosan, Midsayap, Pikit, M’lang and Tulunan. The result of this study can help developed strategies for monitoring and managing this serious pest of banana and to prepare a mitigation measures on those areas that are potential for future infestation.

Keywords: banana aphid, bioclimatic model, bunchy top, climatic envelope approach

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Authors: Nader Habibzadeh

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Developing effective and well-targeted conservation strategies is dependent upon fully understanding the complexities of the local situation. We attempted to discern the main likely wolf-human conflict contributing variables in households of Shabestar county’s villages. Data were collected through questions in 53 semi-structured interviews in 36 villages across Shabestar district in summer 2014. The results suggested that people who have reportedly suffered livestock depredation and who have alternative income sources to livestock, are likely to be particularly hostile toward wildlife. With rapid assessment of households using these few key variables we are able to identify likely conflict hotspots and target conflict resolution efforts in those villages. Based on these results, the most important initial strategies for reducing conflict would be reducing the number of livestock killed by wolf, increasing opportunities to generate income only from livestock holdings rather than alternative income sources.

Keywords: human-wildlife conflict, wolf (Canis lupus), Shabestar, Iran

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Authors: Alak Kumar Patra, Nilanjan Mitra

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Interface fracture toughness of glass-epoxy (G/E) PVC core sandwich composite with and without MWCNT has been investigated through experimental methods. Results demonstrate an improvement in interface fracture toughness values (GC) of samples with a certain percentages of MWCNT. In addition, dispersion of MWCNT in epoxy resin through sonication followed by mixing of hardener and vacuum assisted resin transfer method (VARTM) used in this study is an easy and cost effective methodology in comparison to previously adopted other methods limited to laminated composites. The study also identifies the optimum weight percentage of MWCNT addition in the resin system for maximum performance gain in interfacial fracture toughness. The results are supported by high resolution transmission electron microscope (HRTEM) analysis and fracture micrograph of field emission scanning electron microscope (FESEM) investigation.

Keywords: carbon nanotube, foam, glass-epoxy, interfacial fracture, sandwich composite

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: McClain Thiel

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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

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Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. With the emergence of blockchain technology, a new research area has been explored which helps bring this multi-utility service provider concept to a much higher level. This study aims at introducing a breakthrough system architecture where smart metering technology in water, energy, and gas (WEG) are combined with blockchain technology to provide customer a novel real-time consumption report and decentralized resource trading platform. A pilot study on 4 properties in Australia has been undertaken to demonstrate this system, where benefits for customers and utilities are undeniable.

Keywords: blockchain, digital multi-utility, end use, demand forecasting

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: A. Mohammed, R. Lewis, M. Marshall

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Commonly used coatings to protect tools in die casting were used. A heat treatment and then surface coating can have a large effect on erosion damage. Samples have been tested to evaluate their resistances to erosive wear and to assess how this compares with behaviour seen for untreated material. Five commercial (PN + TiN), (PN + TiAlCN), (TiN X 2), (TiN), and (TiAlCN) coatings have been evaluated for their wear resistance. The objective was to permit an optimized selection of coatings to be used to give good resistance to erosive wear. A test-Rig has been developed to study the erosive wear in aluminium die casting and provide an environment similar to industrial operation that is more practical than using actual machines. These surfaces were analysed using a Scanning Electron Microscope (SEM) and Optical Microscopes each with a different level of resolution. Examination of coating materials revealed an important parameter associated with the failure of the coating materials.This was adhesion of the coating material to the substrate surface. A well-adhered coating withstands wear much better compared to the poorest-adhering coating.

Keywords: solid particle erosion, PVD-coatings, steel, erosion testing

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Authors: S. Nasri, H. Bouziri

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Disasters are quite experienced in our days. They are caused by floods, landslides, and building fires that is the main objective of this study. To cope with these unexpected events, precautions must be taken to protect human lives. The emphasis on disposal work focuses on the resolution of the evacuation problem in case of no-notice disaster. The problem of evacuation is listed as a dynamic network flow problem. Particularly, we model the evacuation problem as an earliest arrival flow problem with load dependent transit time. This problem is classified as NP-Hard. Our challenge here is to propose a metaheuristic solution for solving the evacuation problem. We define our objective as the maximization of evacuees during earliest periods of a time horizon T. The objective provides the evacuation of persons as soon as possible. We performed an experimental study on emergency evacuation from the tunisian children’s hospital. This work prompts us to look for evacuation plans corresponding to several situations where the network dynamically changes.

Keywords: dynamic network flow, load dependent transit time, evacuation strategy, earliest arrival flow problem, tabu search metaheuristic

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Authors: Dhanuj M. Gandikota

Abstract:

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: S. Ali, M. Baccar

Abstract:

In this work, numerical simulations were carried out using a specific CFD code in order to study the performance of an innovative Scraped Surface Heat Exchanger (SSHE) with helical ribbons for Bingham fluids (threshold fluids). The resolution of three-dimensional form of the conservation equations (continuity, momentum and energy equations) was carried out basing on the finite volume method (FVM). After studying the effect of dimensionless numbers (axial Reynolds, rotational Reynolds and Oldroyd numbers) on the hydrodynamic and thermal behaviors within SSHE, a parametric study was developed, by varying the width of the helical ribbon, the clearance between the stator wall and the tip of the ribbon and the number of turns of the helical ribbon, in order to improve the heat transfer inside the exchanger. The effect of these geometrical numbers on the hydrodynamic and thermal behaviors was discussed.

Keywords: heat transfer, helical ribbons, hydrodynamic behavior, parametric study, SSHE, thermal behavior

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Authors: Wenliang Song, Yu Zhang, Hua Jin, Il Kim

Abstract:

The self-assembly of the polypeptide (PP) into well-defined structures at different length scales is both biomimetic relevant and fundamentally interesting. Although there are various reports of nanostructures fabricated by the self-assembly of various PPs, directed self-assembly of PP into three-dimensional (3D) hierarchical structure has proven to be difficult, despite their importance for biological applications. Herein, an efficient method has been developed through living polymerization of phenylalanine N-Carboxy anhydride (NCA) towards the linear and cyclic polyphenylalanine, and the new invented swelling methodology can form diverse hierarchical polypeptide crystals. The solvent-dependent self-assembly behaviors of these homopolymers were characterized by high-resolution imaging tools such as atomic force microscopy, transmission electron microscopy, scanning electron microscope. The linear and cyclic polypeptide formed 3D nano hierarchical shapes, such as a sphere, cubic, stratiform and hexagonal star in different solvents. Notably, a crystalline packing model was proposed to explain the formation of 3D nanostructures based on the various diffraction patterns, looking forward to give an insight for their dissimilar shape inflection during the self-assembly process.

Keywords: self-assembly, polypeptide, bio-polymer, crystalline polymer

Procedia PDF Downloads 234

Authors: M. D. Fontana, I. Bejaoui Ouni, D. Chapron, H. Aroui

Abstract:

BaTiO3 (BT) is a well known ferroelectric material which has been thoroughly studied during several decades since it undergoes successive cubic-tetragonal-orthorhombic-rhombohedral phase transitions on cooling. It has several ferroelectric properties that allow it to be a good material for electronic applications such as the design of ferroelectric memories and pyroelectric elements. In the present work, we report the analysis of temperature dependence of Raman frequency and damping of the A1 modes polarized along the FE c axis as well as the optical phonons E corresponding to the ionic motions in the plane normal to c. Measurements were carried out at different temperatures ranging from 298 to 408 K (tetragonal phase) within different scattering configurations. Spectroscopic parameters of BT have determined using a high resolution Raman spectrometer and a fitting program. All the first order frequency modes exhibit a quasi linear decrease as function of the temperature, except for the A1[TO1], E[TO2] and E[TO4] lines which reveal a parabolic dependence illustrating an anharmonic process. The phonon frequency downshifts and damping evolutions are interpreted in terms of normal volume expansion and third- and fourth-order anharmonic potentials.

Keywords: BaTiO3, Raman spectroscopy, frequency, damping, anharmonic potential

Procedia PDF Downloads 295

Authors: Sokol Isaraj, Lorela Bendo

Abstract:

Botulinum toxin is the most commonly used treatment to reduce the appearance of dynamic facial wrinkles. It can smooth out wrinkles and restore a more youthful appearance. Although allergic reactions after botox injection are rare, care should be taken by the physician to diagnose the condition and provide suitable treatment in time. The authors report a case of allergic reaction with angioedema to abobotulinumtoxin A. A 50-year-old woman complaining of dynamic wrinkles was injected in a private clinic with Dysport. After two weeks, she returned to the clinic for the touch-up session. Thirty minutes after the completion of the injections in the crow’s feet area, she described the feeling of mild pain and warmth in the injected area, followed by angioedema. The symptoms couldn’t be controlled by IM corticosteroid, and the patient was referred to a hospital center. After adequate systemic treatment for four days, there was a resolution of the symptoms. Despite the reported safety of abobotulinumtoxin A, this case warns practitioners of unpredictably adverse reactions, which require rapid recognition and intravenous support.

Keywords: botulinum toxin, side effects, angioedema, injections

Procedia PDF Downloads 99

Authors: Dila Ram Bhandari

Abstract:

Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Honorio Salmeron Valdivieso, Andy Keane, David Toal

Abstract:

In the area of mechanical reverse engineering, processes often encounter difficulties capturing small, highly localized surface information. This could be the case if a physical turbine was 3D scanned for lifecycle management or robust design purposes, with interest on eroded areas or scratched coating. The limitation partly is due to insufficient automated frameworks for handling -localized - surface information during the reverse engineering pipeline. We have developed a tool for blending surface patches with arbitrary irregularities into a base body (e.g. a CAD solid). The approach aims to transfer small surface features while preserving their shape and relative placement by using a multi-resolution scheme and rigid deformations. Automating this process enables the inclusion of outsourced surface information in CAD models, including samples prepared in mesh handling software, or raw scan information discarded in the early stages of reverse engineering reconstruction.

Keywords: application lifecycle management, multiresolution deformation, reverse engineering, robust design, surface blending

Procedia PDF Downloads 136

Authors: Stefan W. Kienzle

Abstract:

The increasing number of occurrences of extreme weather and climate events have significant impacts on society and are the cause of continued and increasing loss of human and animal lives, loss or damage to property (houses, cars), and associated stresses to the public in coping with a changing climate. A climate index breaks down daily climate time series into meaningful derivatives, such as the annual number of frost days. Climate indices allow for the spatially consistent analysis of a wide range of climate-dependent variables, which enables the quantification and mapping of historical and future climate change across regions. As trends of phenomena such as the length of the growing season change differently in different hydro-climatological regions, mapping needs to be carried out at a high spatial resolution, such as the 10km by 10km Canadian Climate Grid, which has interpolated daily values from 1950 to 2017 for minimum and maximum temperature and precipitation. Climate indices form the basis for the analysis and comparison of means, extremes, trends, the quantification of changes, and their respective confidence levels. A total of 39 temperature indices and 16 precipitation indices were computed for the period 1951 to 2017 for the Province of Alberta. Temperature indices include the annual number of days with temperatures above or below certain threshold temperatures (0, +-10, +-20, +25, +30ºC), frost days, and timing of frost days, freeze-thaw days, growing or degree days, and energy demands for air conditioning and heating. Precipitation indices include daily and accumulated 3- and 5-day extremes, days with precipitation, period of days without precipitation, and snow and potential evapotranspiration. The rank-based nonparametric Mann-Kendall statistical test was used to determine the existence and significant levels of all associated trends. The slope of the trends was determined using the non-parametric Sen’s slope test. The Google mapping interface was developed to create the website albertaclimaterecords.com, from which beach of the 55 climate indices can be queried for any of the 6833 grid cells that make up Alberta. In addition to the climate indices, climate normals were calculated and mapped for four historical 30-year periods and one future period (1951-1980, 1961-1990, 1971-2000, 1981-2017, 2041-2070). While winters have warmed since the 1950s by between 4 - 5°C in the South and 6 - 7°C in the North, summers are showing the weakest warming during the same period, ranging from about 0.5 - 1.5°C. New agricultural opportunities exist in central regions where the number of heat units and growing degree days are increasing, and the number of frost days is decreasing. While the number of days below -20ºC has about halved across Alberta, the growing season has expanded by between two and five weeks since the 1950s. Interestingly, both the number of days with heat waves and cold spells have doubled to four-folded during the same period. This research demonstrates the enormous potential of using climate indices at the best regional spatial resolution possible to enable society to understand historical and future climate changes of their region.

Keywords: climate change, climate indices, habitat risk, regional, mapping, extremes

Procedia PDF Downloads 88