Search results for: taxonomic resolution
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1572

Search results for: taxonomic resolution

1062 The Effect of Tip Parameters on Vibration Modes of Atomic Force Microscope Cantilever

Authors: Mehdi Shekarzadeh, Pejman Taghipour Birgani

Abstract:

In this paper, the effect of mass and height of tip on the flexural vibration modes of an atomic force microscope (AFM) rectangular cantilever is analyzed. A closed-form expression for the sensitivity of vibration modes is derived using the relationship between the resonant frequency and contact stiffness of cantilever and sample. Each mode has a different sensitivity to variations in surface stiffness. This sensitivity directly controls the image resolution. It is obtained an AFM cantilever is more sensitive when the mass of tip is lower and the first mode is the most sensitive mode. Also, the effect of changes of tip height on the flexural sensitivity is negligible.

Keywords: atomic force microscope, AFM, vibration analysis, flexural vibration, cantilever

Procedia PDF Downloads 380
1061 Radar-Based Classification of Pedestrian and Dog Using High-Resolution Raw Range-Doppler Signatures

Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 234
1060 Analysis of Composite Health Risk Indicators Built at a Regional Scale and Fine Resolution to Detect Hotspot Areas

Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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1059 Development of Academic Software for Medial Axis Determination of Porous Media from High-Resolution X-Ray Microtomography Data

Authors: S. Jurado, E. Pazmino

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Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

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1058 Strategic Communication in Turkish Independence War

Authors: Özkan Özgenç, Serdar Hacisalihoğlu, Murat Yanik

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History has shown that quantitative and qualitative supremacy in terms of military and economic power has been inadequate to reach the desired results. In addition, public support has been a crucial requirement for the success of the any struggle. As a leader seeking ways for the independence of the country, Ataturk comprehended that the only solution was possible with the help of public will and determination. Ataturk needed an impeccable communication strategy to combine efforts by establishing a united notion and action; to convince the world and Turkish nation of the legitimacy and sacredness of Independence struggle; and to show the resolution and determination of Turkish nation against the invaders. To emancipate the Turkish nation, Ataturk shaped the nation's emotions, ideas, and behaviors by using the most appropriate tools at the best time and place since the start of Independence War in May 19, 1919.

Keywords: Atatürk, Turkish independence struggle, strategic communication, independence war

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1057 Off-Grid Sparse Inverse Synthetic Aperture Imaging by Basis Shift Algorithm

Authors: Mengjun Yang, Zhulin Zong, Jie Gao

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In this paper, a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids; otherwise, their reconstruction performance dropped significantly. In this processing algorithm, several basis shifts are utilized to achieve the same effect as grid refinement does. The detailed implementation of the basis shift algorithm is presented in this paper. From the simulation we can see that using the basis shift algorithm, imaging precision can be improved. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

Keywords: ISAR imaging, sparse reconstruction, off-grid, basis shift

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1056 Introduction of the Fluid-Structure Coupling into the Force Analysis Technique

Authors: Océane Grosset, Charles Pézerat, Jean-Hugh Thomas, Frédéric Ablitzer

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This paper presents a method to take into account the fluid-structure coupling into an inverse method, the Force Analysis Technique (FAT). The FAT method, also called RIFF method (Filtered Windowed Inverse Resolution), allows to identify the force distribution from local vibration field. In order to only identify the external force applied on a structure, it is necessary to quantify the fluid-structure coupling, especially in naval application, where the fluid is heavy. This method can be decomposed in two parts, the first one consists in identifying the fluid-structure coupling and the second one to introduced it in the FAT method to reconstruct the external force. Results of simulations on a plate coupled with a cavity filled with water are presented.

Keywords: aeroacoustics, fluid-structure coupling, inverse methods, naval, turbulent flow

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1055 Improving Predictions of Coastal Benthic Invertebrate Occurrence and Density Using a Multi-Scalar Approach

Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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1054 Speeding-up Gray-Scale FIC by Moments

Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly

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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.

Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block

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1053 An Application-Driven Procedure for Optimal Signal Digitization of Automotive-Grade Ultrasonic Sensors

Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

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In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished through the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: analog to digital conversion, digitization, sampling rate, ultrasonic

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1052 A Comparative Study on Automatic Feature Classification Methods of Remote Sensing Images

Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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1051 Characterizing Nasal Microbiota in COVID-19 Patients: Insights from Nanopore Technology and Comparative Analysis

Authors: David Pinzauti, Simon De Jaegher, Maria D'Aguano, Manuele Biazzo

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The COVID-19 pandemic has left an indelible mark on global health, leading to a pressing need for understanding the intricate interactions between the virus and the human microbiome. This study focuses on characterizing the nasal microbiota of patients affected by COVID-19, with a specific emphasis on the comparison with unaffected individuals, to shed light on the crucial role of the microbiome in the development of this viral disease. To achieve this objective, Nanopore technology was employed to analyze the bacterial 16s rRNA full-length gene present in nasal swabs collected in Malta between January 2021 and August 2022. A comprehensive dataset consisting of 268 samples (126 SARS-negative samples and 142 SARS-positive samples) was subjected to a comparative analysis using an in-house, custom pipeline. The findings from this study revealed that individuals affected by COVID-19 possess a nasal microbiota that is significantly less diverse, as evidenced by lower α diversity, and is characterized by distinct microbial communities compared to unaffected individuals. The beta diversity analyses were carried out at different taxonomic resolutions. At the phylum level, Bacteroidota was found to be more prevalent in SARS-negative samples, suggesting a potential decrease during the course of viral infection. At the species level, the identification of several specific biomarkers further underscores the critical role of the nasal microbiota in COVID-19 pathogenesis. Notably, species such as Finegoldia magna, Moraxella catarrhalis, and others exhibited relative abundance in SARS-positive samples, potentially serving as significant indicators of the disease. This study presents valuable insights into the relationship between COVID-19 and the nasal microbiota. The identification of distinct microbial communities and potential biomarkers associated with the disease offers promising avenues for further research and therapeutic interventions aimed at enhancing public health outcomes in the context of COVID-19.

Keywords: COVID-19, nasal microbiota, nanopore technology, 16s rRNA gene, biomarkers

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1050 Subdural Hematoma: A Rare Complication of ITP

Authors: Muhammad Faisal Khilji, Rana Shoaib Hamid

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Subdural hematoma (SDH) is an extremely rare complication of immune thrombocytopenic purpura (ITP). We present a case of a 34 years old female who presented to the Emergency department of a tertiary care hospital with complaints of headache, on and off gums bleeding and upper respiratory tract symptoms for the last two weeks. Examination was unremarkable except some purpura over limbs. Investigations revealed zero platelets and peripheral film suggestive of ITP. Computerized tomography (CT) brain revealed bilateral SDH in the frontal areas extending into Falx cerebri. Impression of ITP with SDH was made. Patient was treated with intravenous immunoglobulin (IVIg), methyl prednisolone and initial Platelets transfusion. Patient recovered uneventfully with platelets reaching normal levels within a few days and resolution of SDH without surgery.

Keywords: headache, immune thrombocytopenia, purpura, subdural hematoma

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1049 If You Can't Teach Yourself, No One Can

Authors: Timna Mayer

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This paper explores the vast potential of self-directed learning in violin pedagogy. Based in practice and drawing on concepts from neuropsychology, the author, a violinist and teacher, outlines five learning principles. Self-directed learning is defined as an ongoing process based on problem detection, definition, and resolution. The traditional roles of teacher and student are reimagined within this context. A step-by-step guide to applied self-directed learning suggests a model for both teachers and students that realizes student independence in the classroom, leading to higher-level understanding and more robust performance. While the value of self-directed learning is well-known in general pedagogy, this paper is novel in applying the approach to the study of musical performance, a field which is currently dominated by habit and folklore, rather than informed by science.

Keywords: neuropsychology and musical performance, self-directed learning, strategic problem solving, violin pedagogy

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1048 Conflict Resolution in Fuzzy Rule Base Systems Using Temporal Modalities Inference

Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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1047 Long-Term Subcentimeter-Accuracy Landslide Monitoring Using a Cost-Effective Global Navigation Satellite System Rover Network: Case Study

Authors: Vincent Schlageter, Maroua Mestiri, Florian Denzinger, Hugo Raetzo, Michel Demierre

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Precise landslide monitoring with differential global navigation satellite system (GNSS) is well known, but technical or economic reasons limit its application by geotechnical companies. This study demonstrates the reliability and the usefulness of Geomon (Infrasurvey Sàrl, Switzerland), a stand-alone and cost-effective rover network. The system permits deploying up to 15 rovers, plus one reference station for differential GNSS. A dedicated radio communication links all the modules to a base station, where an embedded computer automatically provides all the relative positions (L1 phase, open-source RTKLib software) and populates an Internet server. Each measure also contains information from an internal inclinometer, battery level, and position quality indices. Contrary to standard GNSS survey systems, which suffer from a limited number of beacons that must be placed in areas with good GSM signal, Geomon offers greater flexibility and permits a real overview of the whole landslide with good spatial resolution. Each module is powered with solar panels, ensuring autonomous long-term recordings. In this study, we have tested the system on several sites in the Swiss mountains, setting up to 7 rovers per site, for an 18 month-long survey. The aim was to assess the robustness and the accuracy of the system in different environmental conditions. In one case, we ran forced blind tests (vertical movements of a given amplitude) and compared various session parameters (duration from 10 to 90 minutes). Then the other cases were a survey of real landslides sites using fixed optimized parameters. Sub centimetric-accuracy with few outliers was obtained using the best parameters (session duration of 60 minutes, baseline 1 km or less), with the noise level on the horizontal component half that of the vertical one. The performance (percent of aborting solutions, outliers) was reduced with sessions shorter than 30 minutes. The environment also had a strong influence on the percent of aborting solutions (ambiguity search problem), due to multiple reflections or satellites obstructed by trees and mountains. The length of the baseline (distance reference-rover, single baseline processing) reduced the accuracy above 1 km but had no significant effect below this limit. In critical weather conditions, the system’s robustness was limited: snow, avalanche, and frost-covered some rovers, including the antenna and vertically oriented solar panels, leading to data interruption; and strong wind damaged a reference station. The possibility of changing the sessions’ parameters remotely was very useful. In conclusion, the rover network tested provided the foreseen sub-centimetric-accuracy while providing a dense spatial resolution landslide survey. The ease of implementation and the fully automatic long-term survey were timesaving. Performance strongly depends on surrounding conditions, but short pre-measures should allow moving a rover to a better final placement. The system offers a promising hazard mitigation technique. Improvements could include data post-processing for alerts and automatic modification of the duration and numbers of sessions based on battery level and rover displacement velocity.

Keywords: GNSS, GSM, landslide, long-term, network, solar, spatial resolution, sub-centimeter.

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1046 Brief Solution-Focused Negotiation: Theory and Application

Authors: Sapir Handelman

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Brief Solution Focused Negotiation is a powerful conflict resolution tool. It can be applied in almost all dimensions of our social life, from politics to family. The initiative invites disputing parties to negotiate practical solutions to their conflict. The negotiation is conducted in a framework of rules, structure, and timeline. The paper presents a model of Brief Solution Focused Negotiation that rests on three pillars: Transformation – turning opposing parties into a negotiating cooperative; Practicality – focusing on practical solutions to a negotiable problem; Discovery – discovering key game changers. This paper introduces these three building blocks. It demonstrates the potential contribution of each one of them to negotiation success. It shows that an effective combination of these three elements has the greatest potential to build, maintain and successfully conclude Brief Solution Focused Negotiation.

Keywords: conflict, negotiation, negotiating cooperative, game changer

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1045 Development of Ultrasounf Probe Holder for Automatic Scanning Asymmetric Reflector

Authors: Nabilah Ibrahim, Hafiz Mohd Zaini, Wan Fatin Liyana Mutalib

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Ultrasound equipment or machine is capable to scan in two dimensional (2D) areas. However there are some limitations occur during scanning an object. The problem will occur when scanning process that involving the asymmetric object. In this project, the ultrasound probe holder for asymmetric reflector scanning in 3D image is proposed to make easier for scanning the phantom or object that has asymmetric shape. Initially, the constructed asymmetric phantom that construct will be used in 2D scanning. Next, the asymmetric phantom will be interfaced by the movement of ultrasound probe holder using the Arduino software. After that, the performance of the ultrasound probe holder will be evaluated by using the various asymmetric reflector or phantom in constructing a 3D image

Keywords: ultrasound 3D images, axial and lateral resolution, asymmetric reflector, Arduino software

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1044 Microfabrication and Non-Invasive Imaging of Porous Osteogenic Structures Using Laser-Assisted Technologies

Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

Abstract:

A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

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1043 Presentation of International Military Intervention Correlates (IMIC) Database

Authors: Daniil Chernov

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In the modern world, the number of conventional interstate wars is declining while the number of military interventions is rising. States no longer initiate conflicts by declaring war but actively intervene in existing military confrontations, often using a comparable number of coercive means. According to existing scholarly understanding, the decision to use force in international relations (in any form) is influenced by roughly the same set of factors: the dynamics of domestic political processes, national interests, international law, and ethical considerations. In the database on armed intervention to be presented in the report, the multifactor model of decision-making is developed. The database describes more than 200 different parameters for armed interventions between 1992 and 2022. The report will present the structure of the database, descriptive statistics, and its key advantages over other sources.

Keywords: conflict resolution, international relations, military intervention, database

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1042 The Relationship between Organizational Culture and the Establishment of Knowledge Management in the Central Insurance of Iran

Authors: Alireza Assareh, Fatemeh Havas Beigi, Mohammad Vafaee Yeganeh

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The present study is conducted to investigate the relationship between organizational culture and the establishment of knowledge management in the Central Insurance of Iran. The research results revealed that there is a significant positive relationship between organizational culture and its elements that include management support, organizational belonging, individual innovation, and leadership style and the establishment of knowledge management in the central insurance of Iran and that there isn’t any significant relationship between conflict resolution and the establishment of knowledge management in the central insurance of Iran.

Keywords: organizational culture, knowledge management, central insurance of Iran, individual innovation

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1041 A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based on WorldView-2 Satellite Imagery

Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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1040 Simple and Effective Method of Lubrication and Wear Protection

Authors: Buddha Ratna Shrestha, Jimmy Faivre, Xavier Banquy

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By precisely controlling the molecular interactions between anti-wear macromolecules and bottle-brush lubricating molecules in the solution state, we obtained a fluid with excellent lubricating and wear protection capabilities. The reason for this synergistic behavior relies on the subtle interaction forces between the fluid components which allow the confined macromolecules to sustain high loads under shear without rupture. Our results provide rational guides to design such fluids for virtually any type of surfaces. The lowest friction coefficient and the maximum pressure that it can sustain is 5*10-3 and 2.5 MPa which is close to the physiological pressure. Lubricating and protecting surfaces against wear using liquid lubricants is a great technological challenge. Until now, wear protection was usually imparted by surface coatings involving complex chemical modifications of the surface while lubrication was provided by a lubricating fluid. Hence, we here research for a simple, effective and applicable solution to the above problem using surface force apparatus (SFA). SFA is a powerful technique with sub-angstrom resolution in distance and 10 nN/m resolution in interaction force while performing friction experiment. Thus, SFA is used to have the direct insight into interaction force, material and friction at interface. Also, we always know the exact contact area. From our experiments, we found that by precisely controlling the molecular interactions between anti-wear macromolecules and lubricating molecules, we obtained a fluid with excellent lubricating and wear protection capabilities. The reason for this synergistic behavior relies on the subtle interaction forces between the fluid components which allow the confined macromolecules to sustain high loads under shear without rupture. The lowest friction coefficient and the maximum pressure that it can sustain in our system is 5*10-3 and 2.5 GPA which is well above the physiological pressure. Our results provide rational guides to design such fluids for virtually any type of surfaces. Most importantly this process is simple, effective and applicable method of lubrication and protection as until now wear protection was usually imparted by surface coatings involving complex chemical modifications of the surface. Currently, the frictional data that are obtained while sliding the flat mica surfaces are compared and confirmed that a particular mixture of solution was found to surpass all other combination. So, further we would like to confirm that the lubricating and antiwear protection remains the same by performing the friction experiments in synthetic cartilages.

Keywords: bottle brush polymer, hyaluronic acid, lubrication, tribology

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1039 Impairments Correction of Six-Port Based Millimeter-Wave Radar

Authors: Dan Ohev Zion, Alon Cohen

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In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.

Keywords: radar, FMCW Radar, IQ mismatch, six port

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1038 Antifungal Potential of Higher Basidiomycetes Mushrooms

Authors: Tamar Khardziani, Violeta Berikashvili, Mariam Rusitashvili, Eva Kachlishvili, Vladimir Elisashvili, Mikheil Asatiani

Abstract:

Last years, the search for natural sources of novel and effective antifungal substances became a scientific and technological challenge. In the present research, thirty basidiomycetes isolated from various ecological niches of Georgia and belonging to different taxonomic groups were screened for their antifungal activities against pathogenic fungi such as Aspergillus, Fusarium, and Guignardia bidwellii. Among mushroom tested, several potential producers of antifungal substances have been revealed, such as Schizophyllum commune, Lentinula edodes, Ganoderma abietinum, Fomes fomentarius, Hericium erinaceus, and Trametes versicolor. For mushroom cultivation and expression of antifungal potential, submerged and solid-state fermentations of different plant raw materials were performed and various approaches and strategies have been exploited. Sch. commune appeared as a most promising producer of antifungal compounds. It was established that among different agro-industrial wastes, the presence of mandarin juice production waste in a nutrient medium, causing the significant increase of antifungal activity Sch. commune (growth inhibition: Aspergillus – 59 %, Fusarium – 55 %, G. bidwellii – 78 %, after 3, 2 and 4 days of cultivation, respectively). Besides this, Sch. commune demonstrate similar antifungal activities in the presence of glucose, glycerol, maltose, mannitol, and xylose, and growth inhibition of Fusarium ranged in 41 % - 49 % during 6 days of cultivation. Inhibition of Aspergillus growth inhibition varied in 27 % - 36 %, and inhibition of G. bidwellii was in the range 49 % - 61 %, respectively. Sch. commune under solid-state fermentation of mandarin peels at 13 days of cultivation demonstrates powerful growth inhibition of pathogenic fungi (growth inhibition: Aspergillus – 50 %, Fusarium – 61 %, G. bidwellii – 68 %, after 3, 4, and 4 days of cultivation, respectively) as well as at 20 days old mushroom (growth inhibition: Aspergillus – 41 %, Fusarium – 54 %, G. bidwellii – 66 %, after 3 days of cultivation). It was established that Sch. commune was effective as a producer of antifungal compounds in submerged as well as in solid-state fermentation. Finally, performed study confirms that the higher basidiomycetes possess antifungal potential, which strongly depends on the physiological factors of growth. Acknowledgments: The work was implemented with the financial support of fundamental science project FR-19-3719 by the Shota Rustaveli National Science Foundation of Georgia.

Keywords: antifungal potential, higher basidiomycetes, pathogenic fungi, submerged and solid-state fermentation

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1037 Performance of Hybrid Image Fusion: Implementation of Dual-Tree Complex Wavelet Transform Technique

Authors: Manoj Gupta, Nirmendra Singh Bhadauria

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Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR.

Keywords: image fusion, DWT, DT-CWT, PSNR, average image fusion, hybrid image fusion

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1036 Slope Instability Study Using Kinematic Analysis and Lineament Density Mapping along a Part of National Highway 58, Uttarakhand, India

Authors: Kush Kumar, Varun Joshi

Abstract:

Slope instability is a major problem of the mountainous region, especially in parts of the Indian Himalayan Region (IHR). The on-going tectonic, rugged topography, steep slope, heavy precipitation, toe erosion, structural discontinuities, and deformation are the main triggering factors of landslides in this region. Besides the loss of life, property, and infrastructure caused by a landslide, it also results in various environmental problems, i.e., degradation of slopes, land use, river quality by increased sediments, and loss of well-established vegetation. The Indian state of Uttarakhand, being a part of the active Himalayas, also faces numerous cases of slope instability. Therefore, the vulnerable landslide zones need to be delineated to safeguard various losses. The study area is focused in Garhwal and Tehri -Garhwal district of Uttarakhand state along National Highway 58, which is a strategic road and also connects the four important sacred pilgrims (Char Dham) of India. The lithology of these areas mainly comprises of sandstone, quartzite of Chakrata formation, and phyllites of Chandpur formation. The greywacke and sandstone rock of Saknidhar formation dips northerly and is overlain by phyllite of Chandpur formation. The present research incorporates the lineament density mapping using remote sensing satellite data supplemented by a detailed field study via kinematic analysis. The DEM data of ALOS PALSAR (12.5 m resolution) is resampled to 10 m resolution and used for preparing various thematic maps such as slope, aspect, drainage, hill shade, lineament, and lineament density using ARCGIS 10.6 software. Furthermore, detailed field mapping, including structural mapping, geomorphological mapping, is integrated for kinematic analysis of the slope using Dips 6.0 software of Rockscience. The kinematic analysis of 40 locations was carried out, among which 15 show the planar type of failure, five-show wedge failure, and rest, 20 show no failures. The lineament density map is overlapped with the location of the unstable slope inferred from kinematic analysis to infer the association of the field information and remote sensing derived information, and significant compatibility was observed. With the help of the present study, location-specific mitigation measures could be suggested. The mitigation measures would be helping in minimizing the probability of slope instability, especially during the rainy season, and reducing the hampering of road traffic.

Keywords: Indian Himalayan Region, kinematic analysis, lineament density mapping, slope instability

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1035 Monitoring of Forest Cover Dynamics in the High Atlas of Morocco (Zaouit Ahansal) Using Remote Sensing Techniques and GIS

Authors: Abdelaziz Moujane, Abedelali Boulli, Abdellah Ouigmane

Abstract:

The present work focuses on the assessment of forestlandscape changes in the region of ZaouitAhansal, usingmultitemporal satellite images at high spatial resolution.Severalremotesensingmethodswereappliednamely: The supervised classification algorithm and NDVI whichwerecombined in a GIS environment to quantify the extent and change in density of forest stands (holmoak, juniper, thya, Aleppo pine, crops, and others).The resultsobtainedshowedthat the forest of ZaouitAhansal has undergonesignificantdegradationresulting in a decrease in the area of juniper, cedar, and zeenoak, as well as an increase in the area of baresoil and agricultural land. The remotesensing data providedsatisfactoryresults for identifying and quantifying changes in forestcover. In addition, thisstudycould serve as a reference for the development of management strategies and restoration programs.

Keywords: remote sensing, GIS, satellite image, NDVI, deforestation, zaouit ahansal

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1034 Separation of Some Pyrethroid Insecticides by High-Performance Liquid Chromatography

Authors: Fairouz Tazerouti, Samira Ihadadene

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Pyrethroids are synthetic pesticides that originated from the modification of natural pyrethrins to improve their biological activity and stability. They are a family of chiral pesticides with a large number of stereoisomers. Enantiomers of synthetic pyretroids present different insecticidal activity, toxicity against aquatic invertebrates and persistence in the environment so the development of rapid and sensitive chiral methods for the determination of different enantiomers is necessary. In this study, the separation of enantiomers of pyrethroid insecticides has been systematically studied using three commercially chiral high-performance liquid chromatography columns. Useful resolution was obtained for compounds with a variety of acid and alcohol moieties, and containing one to four chiral centres. The chromatographic behaviour of the diastereomers of some of these insecticides by using normal, polar and reversed mobile phase mode were also examined.

Keywords: pesticides, analysis, liquid chromatography, pyrethroids

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1033 Metagenomics Analysis on Microbial Communities of Sewage Sludge from Nyeri-Kangemi Wastewater Treatment Plant, Nyeri County-Kenya

Authors: Allan Kiptanui Kimisto, Geoffrey Odhiambo Ongondo, Anastasia Wairimu Muia, Cyrus Ndungu Kimani

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The major challenge to proper sewage sludge treatment processes is the poor understanding of sludge microbiome diversities. This study applied the whole-genome. shotgun metagenomics technique to profile the microbial composition of sewage sludge in two active digestion lagoons at the Nyeri-Kangemi Wastewater Treatment Plant in Nyeri County, Kenya. Total microbial community DNA was extracted from samples using the available ZymoBIOMICS™ DNA Miniprep Kit and sequenced using Shotgun metagenomics. Samples were analyzed using MG-RAST software (Project ID: mgp100988), which allowed for comparing taxonomic diversity before β-diversities studies for Bacteria, Archaea and Eukaryotes. The study identified 57 phyla, 145 classes, 301 orders, 506 families, 963 genera, and 1980 species. Bacteria dominated the microbes and comprised 28 species, 51 classes, 110 orders, 243 families, 597 genera, and 1518 species. The Bacteroides(6.77%) were dominant, followed by Acinetobacter(1.44%) belonging to the Gammaproteobacteria and Acidororax (1.36%), Bacillus (1.24%) and Clostridium (1.02%) belonging to Betaproteobacteria. Archaea recorded 5 phyla, 13 classes, 19 orders, 29 families, 60 genera,and87 species, with the dominant genera being Methanospirillum (16.01%), methanosarcina (15.70%), and Methanoregula(14.80%) and Methanosaeta (8.74%), Methanosphaerula(5.48%) and Methanobrevibacter(5.03%) being the subdominant group. The eukaryotes were the least in abundance and comprised 24 phyla, 81 classes, 301 orders, 506 families, 963 genera, and 980 species. Arabidopsis (4.91%) and Caenorhabditis (4.81%) dominated the eukaryotes, while Dityostelium (3.63%) and Drosophila(2.08%) were the subdominant genera. All these microbes play distinct roles in the anaerobic treatment process of sewage sludge. The local sludge microbial composition and abundance variations may be due to age difference differences between the two digestion lagoons in operation at the plant and the different degradation rales played by the taxa. The information presented in this study can help in the genetic manipulation or formulation of optimal microbial ratios to improve their effectiveness in sewage sludge treatment. This study recommends further research on how the different taxa respond to environmental changes over time and space.

Keywords: shotgun metagenomics, sludge, bacteria, archaea, eukaryotes

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