Search results for: process model

Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: land use change, urbanization, Kigali City, Landsat

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Authors: R. Unnikrishnan, K. Shankar

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In the case of high-speed fighter aircrafts, seat ejection is designed mainly for the safety of the pilot in case of an emergency. Strong windblast due to the high velocity of flight is one main difficulty in clearing the tail of the aircraft. Excessive G-forces generated, immobilizes the pilot from escape. In most of the cases, seats are ejected out of the aircrafts by explosives or by rocket motors attached to the bottom of the seat. Ejection forces are primarily in the vertical direction with the objective of attaining the maximum possible velocity in a specified period of time. The safe ejection parameters are studied to estimate the critical time of ejection for various geometries and velocities of flight. An equivalent analytical 2-dimensional biomechanical model of the human spine has been modelled consisting of vertebrae and intervertebral discs with a lumped mass approach. The 24 vertebrae, which consists of the cervical, thoracic and lumbar regions, in addition to the head mass and the pelvis has been designed as 26 rigid structures and the intervertebral discs are assumed as 25 flexible joint structures. The rigid structures are modelled as mass elements and the flexible joints as spring and damper elements. Here, the motions are restricted only in the mid-sagittal plane to form a 26 degree of freedom system. The equations of motions are derived for translational movement of the spinal column. An ejection force with a linearly increasing acceleration profile is applied as vertical base excitation on to the pelvis. The dynamic vibrational response of each vertebra in time-domain is estimated.

Keywords: biomechanical model, lumped mass, seat ejection, vibrational response

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

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Authors: Mahmoud F. Mohamadin, Ahmed Abdel Malek, Wessam Said

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Achieving energy efficient architecture in general, and in emerging countries in particular, is a challenging process that requires the contribution of various governmental, institutional, and individual entities. The rule of architectural design is essential in this process as it is considered as one of the earliest steps on the road to sustainability. Architectural firms have a moral and professional responsibility to respond to these challenges and deliver buildings that consume less energy. This study aims to evaluate the design processes and tools in practice of Egyptian architectural firms based on a limited survey to investigate if their processes and methods can lead to projects that meet the Egyptian Code of Energy Efficiency Improvement. A case study of twenty architectural firms in Cairo was selected and categorized according to their scale; large-scale, medium-scale, and small-scale. A questionnaire was designed and distributed to the firms, and personal meetings with the firms’ representatives took place. The questionnaire answered three main points; the design processes adopted, the usage of performance-based simulation tools, and the usage of BIM tools for energy efficiency purposes. The results of the study revealed that only little percentage of the large-scale firms have clear strategies for building energy efficiency in their building design, however the application is limited to certain project types, or according to the client request. On the other hand, the percentage of medium-scale firms is much less, and it is almost absent in the small-scale ones. This demonstrates the urgent need of enhancing the awareness of the Egyptian architectural design community of the great importance of implementing these methods starting from the early stages of the building design. Finally, the study proposed recommendations for such firms to be able to create a healthy built environment and improve the quality of life in emerging countries.

Keywords: architectural firms, emerging countries, energy efficiency, performance-based simulation tools

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Maher Z. Mohammed, Barry G. Clarke

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As an alternative to stone column in fine grained soils, it is possible to create stiffened columns of soils using electroosmosis (electroosmotic piles). This program of this research is to establish the effectiveness and efficiency of the process in different soils. The aim of this study is to assess the capability of electroosmosis treatment in a range of composite soils. The combined electroosmotic and preloading equipment developed by Nizar and Clarke (2013) was used with an octagonal array of anodes surrounding a single cathode in a nominal 250mm diameter 300mm deep cylinder of soil and 80mm anode to cathode distance. Copper coiled springs were used as electrodes to allow the soil to consolidate either due to an external vertical applied load or electroosmosis. The equipment was modified to allow the temperature to be monitored during the test. Electroosmotic tests were performed on China Clay Grade E kaolin and calcium bentonite (Bentonex CB) mixed with sand fraction C (BS 1881 part 131) at different ratios by weight; (0, 23, 33, 50 and 67%) subjected to applied voltages (5, 10, 15 and 20). The soil slurry was prepared by mixing the dry soil with water to 1.5 times the liquid limit of the soil mixture. The mineralogical and geotechnical properties of the tested soils were measured before the electroosmosis treatment began. In the electroosmosis cell tests, the settlement, expelled water, variation of electrical current and applied voltage, and the generated heat was monitored during the test time for 24 osmotic tests. Water content was measured at the end of each test. The electroosmotic tests are divided into three phases. In Phase 1, 15 kPa was applied to simulate a working platform and produce a uniform soil which had been deposited as a slurry. 50 kPa was used in Phase 3 to simulate a surcharge load. The electroosmotic treatment was only performed during Phase 2 where a constant voltage was applied through the electrodes in addition to the 15 kPa pressure. This phase was stopped when no further water was expelled from the cell, indicating the electroosmotic process had stopped due to either the degradation of the anode or the flow due to the hydraulic gradient exactly balanced the electroosmotic flow resulting in no flow. Control tests for each soil mixture were carried out to assess the behaviour of the soil samples subjected to only an increase of vertical pressure, which is 15kPa in Phase 1 and 50kPa in Phase 3. Analysis of the experimental results from this study showed a significant dewatering effect on the soil slurries. The water discharged by the electroosmotic treatment process decreased as the sand content increased. Soil temperature increased significantly when electrical power was applied and drops when applied DC power turned off or when the electrode degraded. The highest increase in temperature was found in pure clays at higher applied voltage after about 8 hours of electroosmosis test.

Keywords: electrokinetic treatment, electrical conductivity, electroosmotic consolidation, electroosmosis permeability ratio

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Authors: Poojan Kothari, Yash Madhani, Chayan Jani, Bharti Saini

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The requirements for quality drinking and industrial water are increasing and water resources are depleting. Moreover large amount of wastewater is being generated and dumped into water bodies without treatment. These have made improvement in water treatment efficiency and its reuse, an important agenda. Membrane technology for wastewater treatment is an advanced process and has become increasingly popular in past few decades. There are many traditional methods for tertiary treatment such as chemical coagulation, adsorption, etc. However recent developments in membrane technology field have led to manufacturing of better quality membranes at reduced costs. This along with the high costs of conventional treatment processes, high separation efficiency and relative simplicity of the membrane treatment process has made it an economically viable option for municipal and industrial purposes. Ultrafiltration polymeric membranes can be used for wastewater treatment and drinking water applications. The proposed work focuses on preparation of one such UF membrane - Polyvinylidene fluoride (PVDF) doped with LiBr for wastewater treatment. Majorly all polymeric membranes are hydrophobic in nature. This property leads to repulsion of water and hence solute particles occupy the pores, decreasing the lifetime of a membrane. Thus modification of membrane through addition of small amount of salt such as LiBr helped us attain certain characteristics of membrane, which can then be used for wastewater treatment. The membrane characteristics are investigated through measuring its various properties such as porosity, contact angle and wettability to find out the hydrophilic nature of the membrane and morphology (surface as well as structure). Pure water flux, solute rejection and permeability of membrane is determined by permeation experiments. A study of membrane characteristics with various concentration of LiBr helped us to compare its effectivity.

Keywords: Lithium bromide (LiBr), morphology, permeability, Polyvinylidene fluoride (PVDF), solute rejection, wastewater treatment

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Authors: Donald G. Danmeier, Gian Marco Pizzo, Matthew Brennan

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Although wetlands have been proposed as a green alternative to manage coastal flood hazards because of their capacity to adapt to sea level rise and provision of multiple ecological and social co-benefits, they are often overlooked due to challenges in quantifying the uncertainty and naturally, variability of these systems. This objective of this study was to quantify wave attenuation provided by a natural marsh surrounding a large oil refinery along the US Gulf Coast that has experienced steady erosion along the shoreward edge. The vegetation module of the SWAN was activated and coupled with a hydrodynamic model (DELFT3D) to capture two-way interactions between the changing water level and wavefield over the course of a storm event. Since the marsh response to relative sea level rise is difficult to predict, a range of future marsh morphologies is explored. Numerical results were examined to determine the amount of wave attenuation as a function of marsh extent and the relative contributions from white-capping, depth-limited wave breaking, bottom friction, and flexing of vegetation. In addition to the coupled DELFT3D-SWAN modeling of a storm event, an uncoupled SWAN-VEG model was applied to a simplified bathymetry to explore a larger experimental design space. The wave modeling revealed that the rate of wave attenuation reduces for higher surge but was still significant over a wide range of water levels and outboard wave heights. The results also provide insights to the minimum marsh extent required to fully realize the potential wave attenuation so the changing coastal hazards can be managed.

Keywords: green infrastructure, wave attenuation, wave modeling, wetland

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Authors: Vladimir A. Vinnikov

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The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied by a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: degree of rock disturbance, non-destructive testing, thermally induced acoustic emission memory effects, structure and texture of rocks

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: Grandmother Roberta Oshkawbewisens, Elder Isabelle Meawasige, Lynne Groulx, Chloë Hamilton, Lee Allison Clark, Dana Hickey, Wansu Qiu, Jared Leedham, Nishanthini Mahendran, Cameron Maclaine

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In March of 2020, the world suddenly shifted with the onset of the COVID-19 pandemic; in-person programs and services were unavailable and a scramble to shift to virtual service delivery began. The Native Women’s Association of Canada (NWAC) established virtual programming through the Resiliency Lodge model and connected with Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people across Turtle Island and Inuit Nunangat through programs that provide a safe space to slow down and reflect on their lives, environment, and well-being. To continue to grow the virtual Resiliency Lodge model, NWAC needed to develop an understanding of three questions: how COVID-19 affects Elder-led support services, how Elder-led support services have adapted during the pandemic, and what Wise Practices need to be implemented to continue to develop, refine, and evaluate virtual Elder-led support services specifically for Indigenous women, girls, two-Spirit, transgender, and gender-diverse people. Through funding from the Canadian Institute of Health Research (CIHR), NWAC gained deeper insight into these questions and developed a series of key findings and recommendations that are outlined throughout this report. The goals of this project are to contribute to a more robust participatory analysis that reflects the complexities of Elder-led virtual cultural responses and the impacts of COVID-19 on Elder-led support services; develop culturally and contextually meaningful virtual protocols and wise practices for virtual Indigenous-led support; and develop an Evaluation Strategy to improve the capacity of the Resiliency Lodge model. Significant findings from the project include Resiliency Lodge programs, especially crafting and business sessions, have provided participants with a sense of community and contributed to healing and wellness; Elder-led support services need greater and more stable funding to offer more workshops to more Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people; and Elder- and Indigenous-led programs play a significant role in healing and building a sense of purpose and belonging among Indigenous people. Ultimately, the findings and recommendations outlined in this research project help to guide future Elder-led virtual support services and emphasize the critical need to increase access to Elder-led programming for Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people.

Keywords: indigenous women, traditional healing, virtual programs, covid-19

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Authors: Joel Niklaus, Matthias Sturmer

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The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

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Authors: Richard Harrison

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Developing competency in mathematics and related critical thinking skills is essential to the education of undergraduate students of Science, Technology, Engineering and Mathematics (STEM). Recently, the HE sector has been impacted by a seemingly widening disconnect between the mathematical competency of incoming first-year STEM students and their entrance qualification tariffs. Despite relatively high grades in A-Level Mathematics, students may initially lack fundamental skills in key areas such as algebraic manipulation and have limited capacity to apply problem solving strategies. Compounded by compensatory measures applied to entrance qualifications during the pandemic, there has been an associated decline in student performance on introductory university mathematics modules. In the UK, a number of online resources have been developed to help scaffold the transition to university mathematics. However, in general, these do not offer a structured learning journey focused on individual developmental needs, nor do they offer an experience coherent with the teaching and learning characteristics of the destination institution. In order to address some of these issues, a bespoke framework has been designed and implemented on our VLE in the Faculty of Engineering & Physical Sciences (FEPS) at the University of Surrey. Called the FEPS Maths Support Framework, it was conceived to scaffold the mathematical development of individuals prior to entering the university and during the early stages of their transition to undergraduate studies. More than 90% of our incoming STEM students voluntarily participate in the process. Students complete a set of initial diagnostic questions in the late summer. Based on their performance and feedback on these questions, they are subsequently guided to self-select specific mathematical topic areas for review using our proprietary resources. This further assists students in preparing for discipline related diagnostic tests. The framework helps to identify students who are mathematically weak and facilitates early intervention to support students according to their specific developmental needs. This paper presents a summary of results from a rich data set captured from the framework over a 3-year period. Quantitative data provides evidence that students have engaged and developed during the process. This is further supported by process evaluation feedback from the students. Ranked performance data associated with seven key mathematical topic areas and eight engineering and science discipline areas reveals interesting patterns which can be used to identify more generic relative capabilities of the discipline area cohorts. In turn, this facilitates evidence based management of the mathematical development of the new cohort, informing any associated adjustments to teaching and learning at a more holistic level. Evidence is presented establishing our framework as an effective early intervention strategy for addressing the sector-wide issue of supporting the mathematical development of STEM students transitioning to HE

Keywords: competency, development, intervention, scaffolding

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Authors: Petros Gkotsis, Giorgos Stratidis, Manassis Mitrakas, Anastasios Zouboulis

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This study investigates the use of original and pre-polymerized iron (Fe) reagents compared to the commonly applied polyaluminum chloride (PACl) coagulant for surface water treatment. Applicable coagulants included both ferric chloride (FeCl₃) and ferric sulfate (Fe₂(SO₄)₃) and their pre-polymerized Fe reagents, such as polyferric sulfate (PFS) and polyferric chloride (PFCl). The efficiency of coagulants was evaluated by the removal of natural organic matter (NOM) and suspended solids (SS), which were determined in terms of reducing the UV absorption at 254 nm and turbidity, respectively. The residual metal concentration (Fe and Al) was also measured. Coagulants were added at five concentrations (1, 2, 3, 4 and 5 mg/L) and three pH values (7.0, 7.3 and 7.6). Experiments were conducted in a jar-test device, with two types of synthetic surface water (i.e., of high and low organic strength) which consisted of humic acid (HA) and kaolin at different concentrations (5 mg/L and 50 mg/L). After the coagulation/flocculation process, clean water was separated with filters of pore size 0.45 μm. Filtration was also conducted before the addition of coagulants in order to compare the ‘net’ effect of the coagulation/flocculation process on the examined parameters (UV at 254 nm, turbidity, and residual metal concentration). Results showed that the use of PACl resulted in the highest removal of humics for both types of surface water. For the surface water of high organic strength (humic acid-kaolin, 50 mg/L-50 mg/L), the highest removal of humics was observed at the highest coagulant dosage of 5 mg/L and at pH=7. On the contrary, turbidity was not significantly affected by the coagulant dosage. However, the use of PACl decreased turbidity the most, especially when the surface water of high organic strength was employed. As expected, the application of coagulation/flocculation prior to filtration improved NOM removal but slightly affected turbidity. Finally, the residual Fe concentration (0.01-0.1 mg/L) was much lower than the residual Al concentration (0.1-0.25 mg/L).

Keywords: coagulation/flocculation, iron and aluminum coagulants, metal salts, pre-polymerized coagulants, surface water treatment

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Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Fares A. Mayia, Mahmoud A. Yamany, Mushabbab A. Asiri

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In recent years, non-invasive Focused Ultrasound (FU) has been utilized for generating bubbles (cavities) to ablate target tissue by mechanical fractionation. Intensities >10 kW/cm² are required to generate the inertial cavities. The generation, rapid growth, and collapse of these inertial cavities cause tissue fractionation and the process is called Histotripsy. The ability to fractionate tissue from outside the body has many clinical applications including the destruction of the tumor mass. The process of tissue fractionation leaves a void at the treated site, where all the affected tissue is liquefied to particles at sub-micron size. The liquefied tissue will eventually be absorbed by the body. Histotripsy is a promising non-invasive treatment modality. This paper presents a technique for generating inertial cavities at lower intensities (< 1 kW/cm²). The technique (patent pending) is based on amplitude modulation (AM), whereby a low frequency signal modulates the amplitude of a higher frequency FU wave. Cavitation threshold is lower at low frequencies; the intensity required to generate cavitation in water at 10 kHz is two orders of magnitude lower than the intensity at 1 MHz. The Amplitude Modulation technique can operate in both continuous wave (CW) and pulse wave (PW) modes, and the percentage modulation (modulation index) can be varied from 0 % (thermal effect) to 100 % (cavitation effect), thus allowing a range of ablating effects from Hyperthermia to Histotripsy. Furthermore, changing the frequency of the modulating signal allows controlling the size of the generated cavities. Results from in vitro work demonstrate the efficacy of the new technique in fractionating soft tissue and solid calcium carbonate (Chalk) material. The technique, when combined with MR or Ultrasound imaging, will present a precise treatment modality for ablating diseased tissue without affecting the surrounding healthy tissue.

Keywords: focused ultrasound therapy, histotripsy, inertial cavitation, mechanical tissue ablation

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Authors: Amessalu Atenafu Gelaw, Nele Rath

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Currently, laser hardening process is becoming among the most efficient and effective hardening technique due to its significant advantages. The source where heat is generated, the absence of cooling media, self-quenching property, less distortion nature due to localized heat input, environmental friendly behavior and less time to finish the operation are among the main benefits to adopt this technology. This day, a variety of injection machines are used in plastic, textile, electrical and mechanical industries. Due to the fast growing of composite technology, fiber reinforced polymer matrix becoming optional solution to use in these industries. Due, to the abrasion nature of fiber reinforced polymer matrix composite on the injection components, many parts are outdated before the design period. Niko, a company specialized in injection molded products, suffers from the short lifetime of the injection nozzles of the molds, due to the use of fiber reinforced and, therefore, more abrasive polymer matrix. To prolong the lifetime of these molds, hardening the susceptible component like the injecting nozzles was a must. In this paper, the laser hardening process is investigated on Unimax, a type of stainless steel. The investigation to get optimal results for the nozzle-case was performed in three steps. First, the optimal parameters for maximum possible hardenability for the investigated nozzle material is investigated on a flat sample, using experimental testing as well as thermal simulation. Next, the effect of an inclination on the maximum temperature is analyzed both by experimental testing and validation through simulation. Finally, the data combined and applied for the nozzle. This paper describes possible strategies and methods for laser hardening of the nozzle to reach hardness of at least 720 HV for the material investigated. It has been proven, that the nozzle can be laser hardened to over 900 HV with the option of even higher results when more precise positioning of the laser can be assured.

Keywords: absorptivity, fiber reinforced matrix, laser hardening, Nd:YAG laser

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Harry G. Segal

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The idea of the “self” has been essential ever since the early modern period in western culture, especially since the development of psychotherapy, but advances in neuroscience and cognitive theory challenge traditional notions of the self. More specifically, neuroanatomists have found no location of “the self” in the brain; instead, consciousness has been posited to be a rapid combination of perception, memory, anticipation of future events, and judgment. In this paper, a theoretical model is presented to address these neuroanatomical findings and to revise the historical understanding of “selfhood” in the practice of psychotherapy.

Keywords: the self, psychotherapy, the self and the brain

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Authors: Patrizia Frontera, Anastasia Macario, Sebastiano Candamano, Fortunato Crea, Pierluigi Antonucci

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The increasing of the world energy demand makes today biomass an attractive energy source, based on the minimizing of CO2 emission and on the global warming reduction purposes. Recently, COP-21, the international meeting on global climate change, defined the roadmap for sustainable worldwide development, based on low-carbon containing fuel. Hydrogen is an energy vector able to substitute the conventional fuels from petroleum. Ethanol for hydrogen production represents a valid alternative to the fossil sources due to its low toxicity, low production costs, high biodegradability, high H2 content and renewability. Ethanol conversion to generate hydrogen by a combination of partial oxidation and steam reforming reactions is generally called auto-thermal reforming (ATR). The ATR process is advantageous due to the low energy requirements and to the reduced carbonaceous deposits formation. Catalyst plays a pivotal role in the ATR process, especially towards the process selectivity and the carbonaceous deposits formation. Bimetallic or trimetallic catalysts, as well as catalysts with doped-promoters supports, may exhibit high activity, selectivity and deactivation resistance with respect to the corresponding monometallic ones. In this work, NiMoCo/GDC, NiMoCu/GDC and NiMoRe/GDC (where GDC is Gadolinia Doped Ceria support and the metal composition is 60:30:10 for all catalyst) have been prepared by impregnation method. The support, Gadolinia 0.2 Doped Ceria 0.8, was impregnated by metal precursors solubilized in aqueous ethanol solution (50%) at room temperature for 6 hours. After this, the catalysts were dried at 100°C for 8 hours and, subsequently, calcined at 600°C in order to have the metal oxides. Finally, active catalysts were obtained by reduction procedure (H2 atmosphere at 500°C for 6 hours). All sample were characterized by different analytical techniques (XRD, SEM-EDX, XPS, CHNS, H2-TPR and Raman Spectorscopy). Catalytic experiments (auto-thermal reforming of ethanol) were carried out in the temperature range 500-800°C under atmospheric pressure, using a continuous fixed-bed microreactor. Effluent gases from the reactor were analyzed by two Varian CP4900 chromarographs with a TCD detector. The analytical investigation focused on the preventing of the coke deposition, the metals sintering effect and the sulfur poisoning. Hydrogen productivity, ethanol conversion and products distribution were measured and analyzed. At 600°C, all tri-metallic catalysts show the best performance: H2 + CO reaching almost the 77 vol.% in the final gases. While NiMoCo/GDC catalyst shows the best selectivity to hydrogen whit respect to the other tri-metallic catalysts (41 vol.% at 600°C). On the other hand, NiMoCu/GDC and NiMoRe/GDC demonstrated high sulfur poisoning resistance (up to 200 cc/min) with respect to the NiMoCo/GDC catalyst. The correlation among catalytic results and surface properties of the catalysts will be discussed.

Keywords: catalysts, ceria, ethanol, gadolinia, hydrogen, Nickel

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Authors: A. Čelan, M. Ćosić, D. Rušić, N. Kuzmanić

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Conducting crystallization in an agitated vessel requires a proper selection of mixing parameters that would result in a production of crystals of specific properties. In dual impeller systems, which are characterized by a more complex hydrodynamics due to the possible fluid flow interactions, revealing a clear link between mixing parameters and crystallization kinetics is still an open issue. The aim of this work is to establish this connection by investigating how fluid flow patterns, generated by two impellers mounted on the same shaft, reflect on metastable zone width of borax decahydrate, one of the most important parameters of the crystallization process. Investigation was carried out in a 15-dm³ bench scale batch cooling crystallizer with an aspect ratio (H/T) equal to 1.3. For this reason, two radial straight blade turbines (4-SBT) were used for agitation. Experiments were conducted at different impeller spacings at the state of complete suspension. During the process of an unseeded batch cooling crystallization, solution temperature and supersaturation were continuously monitored what enabled a determination of the metastable zone width. Hydrodynamic conditions in the vessel achieved at different impeller spacings investigated were analyzed in detail. This was done firstly by measuring the mixing time required to attain the desired level of homogeneity. Secondly, fluid flow patterns generated in a described dual impeller system were both photographed and simulated by VisiMix Turbulent software. Also, a comparison of these two visualization methods was performed. Experimentally obtained results showed that metastable zone width is definitely affected by the hydrodynamics in the crystallizer. This means that this crystallization parameter can be controlled not only by adjusting the saturation temperature or cooling rate, as is usually done, but also by choosing a suitable impeller spacing that will result in a formation of crystals of wanted size distribution.

Keywords: dual impeller crystallizer, fluid flow pattern, metastable zone width, mixing time, radial impeller

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Authors: Naava Dihi, Jon Anson

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Love, so it appears, is not socially blind. We show that partner selection is socially constrained, and the freedom to choose is limited by at least two major factors or capitals: on the one hand, material resources and education, locating the partners on a scale of personal achievement and economic independence. On the other, the partners' ascriptive belonging to particular ethnic, or origin, groups, differentiated by the groups' social prestige, as well as by their culture, history and even physical characteristics. However, the relative importance of achievement and ascriptive factors, as well as the overlap between them, varies from society to society, depending on the society's structure and the factors shaping it. Israeli social structure has been shaped by the waves of new immigrants who arrived over the years. The timing of their arrival, their patterns of physical settlement and their occupational inclusion or exclusion have together created a mosaic of social groups whose principal common feature has been the country of origin from which they arrived. The analysis of marriage patterns helps illuminate the social meanings of the groups and their borders. To the extent that ethnic group membership has meaning for individuals and influences their life choices, the ascriptive factor will gain in importance relative to the achievement factor in their choice of marriage partner. In this research, we examine Jewish Israeli marriage patterns by looking at the marriage choices of 5,041 women aged 15 to 49 who were single at the census in 1983, and who were married at the time of the 1995 census, 12 years later. The database for this study was a file linking respondents from the 1983 and the 1995 censuses. In both cases, 5 percent of household were randomly chosen, so that our sample includes about 4 percent of women in Israel in 1983. We present three basic analyses: (1) Who was still single in 1983, using personal and household data from the 1983 census (binomial model), (2) Who married between 1983 and a1995, using personal and household data from the 1983 census (binomial model), (3) What were the personal characteristics of the womens’ partners in 1995, using data from the 1995 census (loglinear model). We show (i) that material and cultural capital both operate to delay marriage and to increase the probability of remaining single; and (ii) while there is a clear association between ethnic group membership and education, endogamy and homogamy both operate as separate forces which constraint (but do not determine) the choice of marriage partner, and thus both serve to reproduce the current pattern of relationships, as well as identifying patterns of proximity and distance between the different groups.

Keywords: Israel, nuptiality, ascription, achievement

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Jingwen Shi, Qi Wu

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We study the role played interest rate risk in carry trade return in order to understand the forward premium puzzle. In this study, our goal is to investigate to what extent carry trade return is indeed due to compensation for risk taking and, more important, to reveal the nature of these risks. Using option data not only on exchange rates but also on interest rate swaps (swaptions), our first finding is that, besides the consensus currency risks, interest rate risks also contribute a non-negligible portion to the carry trade return. What strikes us is our second finding. We find that large downside risks of future exchange rate movements are, in fact, priced significantly in option market on interest rates. The role played by interest rate risk differs structurally from the currency risk. There is a unique premium associated with interest rate risk, though seemingly small in size, which compensates the tail risks, the left tail to be precise. On the technical front, our study relies on accurately retrieving implied distributions from currency options and interest rate swaptions simultaneously, especially the tail components of the two. For this purpose, our major modeling work is to build a new international asset pricing model where we use an orthogonal setup for pricing kernels and specify non-Gaussian dynamics in order to capture three sets of option skew accurately and consistently across currency options and interest rate swaptions, domestic and foreign, within one model. Our results open a door for studying forward premium anomaly through implied information from interest rate derivative market.

Keywords: carry trade, forward premium anomaly, FX option, interest rate swaption, implied volatility skew, uncovered interest rate parity

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Loren S. Bernal., Catalina Castillo, Carel E. Carvajal, José F. Ibla

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Plastic pollution, specifically microplastics, has become a significant issue in aquatic ecosystems worldwide. The large amount of plastic waste carried by water tributaries has resulted in the accumulation of microplastics in water bodies. The polymer aging process caused by environmental influences such as photodegradation and chemical degradation of additives leads to polymer embrittlement and properties change that require degradation or reduction procedures in rivers. However, there is a lack of such procedures for freshwater entities that develop over extended periods. The aim of this study is evaluate the potential of Pleurotus ostreatus a fungus, in reducing lowdensity polyethylene microplastics present in freshwater samples collected from the middle basin of the Magdalena River in Colombia. The study aims to evaluate this process both in vitro and in silico by identifying the growth capacity of Pleurotus ostreatus in the presence of microplastics and identifying the most likely interactions of Pleurotus ostreatus enzymes and their affinity energies. The study follows an engineering development methodology applied on an experimental basis. The in vitro evaluation protocol applied in this study focused on the growth capacity of Pleurotus ostreatus on microplastics using enzymatic inducers. In terms of in silico evaluation, molecular simulations were conducted using the Autodock 1.5.7 program to calculate interaction energies. The molecular dynamics were evaluated by using the myPresto Portal and GROMACS program to calculate radius of gyration and Energies.The results of the study showed that Pleurotus ostreatus has the potential to degrade low-density polyethylene microplastics. The in vitro evaluation revealed the adherence of Pleurotus ostreatus to LDPE using scanning electron microscopy. The best results were obtained with enzymatic inducers as a MnSO4 generating the activation of laccase or manganese peroxidase enzymes in the degradation process. The in silico modelling demonstrated that Pleurotus ostreatus was able to interact with the microplastics present in LDPE, showing affinity energies in molecular docking and molecular dynamics shown a minimum energy and the representative radius of gyration between each enzyme and its substract. The study contributes to the development of bioremediation processes for the removal of microplastics from freshwater sources using the fungus Pleurotus ostreatus. The in silico study provides insights into the affinity energies of Pleurotus ostreatus microplastic degrading enzymes and their interaction with low-density polyethylene. The study demonstrated that Pleurotus ostreatus can interact with LDPE microplastics, making it a good agent for the development of bioremediation processes that aid in the recovery of freshwater sources. The results of the study suggested that bioremediation could be a promising approach to reduce microplastics in freshwater systems.

Keywords: bioremediation, in silico modelling, microplastics, Pleurotus ostreatus

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Authors: Shivani Sharma, Prashant Saxena, Inamul Hasan Madar

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Since the time of Darwin, it has been considered that genetic change is the direct indicator of variation in phenotype. But a few studies in system biology in the past years have proposed that epigenetic developmental processes also affect the phenotype thus shifting the focus from a linear genotype-phenotype map to a non-linear G-P map. In this paper, we attempt at explaining the evolution of colour vision in mammals by taking LWS/ Long-wave sensitive gene under consideration.

Keywords: evolution, phenotypes, epigenetics, LWS gene, G-P map

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Authors: Bouanati Sidi Mohammed, N. E. Chabane Sari, Mostefa Kara Selma

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It is well-known that Organic light emitting diodes (OLEDs) are attracting great interest in the display technology industry due to their many advantages, such as low price of manufacturing, large-area of electroluminescent display, various colors of emission included white light. Recently, there has been much progress in understanding the device physics of OLEDs and their basic operating principles. In OLEDs, Light emitting is the result of the recombination of electron and hole in light emitting layer, which are injected from cathode and anode. For improve luminescence efficiency, it is needed that hole and electron pairs exist affluently and equally and recombine swiftly in the emitting layer. The aim of this paper is to modeling polymer LED and OLED made with small molecules for studying the electrical and optical characteristics. The first simulation structures used in this paper is a mono layer device; typically consisting of the poly (2-methoxy-5(2’-ethyl) hexoxy-phenylenevinylene) (MEH-PPV) polymer sandwiched between an anode usually an indium tin oxide (ITO) substrate, and a cathode, such as Al. In the second structure we replace MEH-PPV by tris (8-hydroxyquinolinato) aluminum (Alq3). We choose MEH-PPV because of it's solubility in common organic solvents, in conjunction with a low operating voltage for light emission and relatively high conversion efficiency and Alq3 because it is one of the most important host materials used in OLEDs. In this simulation, the Poole-Frenkel- like mobility model and the Langevin bimolecular recombination model have been used as the transport and recombination mechanism. These models are enabled in ATLAS -SILVACO software. The influence of doping and thickness on I(V) characteristics and luminescence, are reported.

Keywords: organic light emitting diode, polymer lignt emitting diode, organic materials, hexoxy-phenylenevinylene

Procedia PDF Downloads 550