Search results for: road multiple countermeasures

Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: C. Angel, S. Asha

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Despite the advances made in various new technologies, application of these technologies for agriculture still remains a formidable task, as it involves integration of diverse domains for monitoring the different process involved in agricultural management. Advances in ambient intelligence technology represents one of the most powerful technology for increasing the yield of agricultural crops and to mitigate the impact of water scarcity, climatic change and methods for managing pests, weeds, and diseases. This paper proposes a GPS-assisted, machine to machine solutions that combine information collected by multiple sensors for the automated management of paddy crops. To maintain the economic viability of paddy cultivation, the various techniques used in agriculture are discussed and a novel system which uses ambient intelligence technique is proposed in this paper. The ambient intelligence based agricultural system gives a great scope.

Keywords: ambient intelligence, agricultural technology, smart agriculture, precise farming

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Authors: Marita Pigłowska, Beata Kurc, Paweł Daszkiewicz

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Railway vehicles are divided into two groups: traction (powered) vehicles and wagons. The traction vehicles include locomotives (line and shunting), railcars (sometimes referred to as railbuses), and multiple units (electric and diesel), consisting of several or a dozen carriages. In vehicles with diesel traction, fuel energy (petrol, diesel, or compressed gas) is converted into mechanical energy directly in the internal combustion engine or via electricity. In the latter case, the combustion engine generator produces electricity that is then used to drive the vehicle (diesel-electric drive or electric transmission). In Poland, such a solution dominates both in heavy linear and shunting locomotives. The classic diesel drive is available for the lightest shunting locomotives, railcars, and passenger diesel multiple units. Vehicles with electric traction do not have their own source of energy -they use pantographs to obtain electricity from the traction network. To determine the competitiveness of the hydrogen propulsion system, it is essential to understand how it works. The basic elements of the construction of a railway vehicle drive system that uses hydrogen as a source of traction force are fuel cells, batteries, fuel tanks, traction motors as well as main and auxiliary converters. The compressed hydrogen is stored in tanks usually located on the roof of the vehicle. This resource is supplemented with the use of specialized infrastructure while the vehicle is stationary. Hydrogen is supplied to the fuel cell, where it oxidizes. The effect of this chemical reaction is electricity and water (in two forms -liquid and water vapor). Electricity is stored in batteries (so far, lithium-ion batteries are used). Electricity stored in this way is used to drive traction motors and supply onboard equipment. The current generated by the fuel cell passes through the main converter, whose task is to adjust it to the values required by the consumers, i.e., batteries and the traction motor. The work will attempt to construct a fuel cell with unique electrodes. This research is a trend that connects industry with science. The first goal will be to obtain hydrogen on a large scale in tube furnaces, to thoroughly analyze the obtained structures (IR), and to apply the method in fuel cells. The second goal is to create low-energy energy storage and distribution station for hydrogen and electric vehicles. The scope of the research includes obtaining a carbon variety and obtaining oxide systems on a large scale using a tubular furnace and then supplying vehicles. Acknowledgments: This work is supported by the Polish Ministry of Science and Education, project "The best of the best! 4.0", number 0911/MNSW/4968 – M.P. and grant 0911/SBAD/2102—B.K.

Keywords: railway, hydrogen, fuel cells, hybrid vehicles

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Authors: Stamatis Zoras, Boris Ceranic, Ashley Redfern

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Green House Gas emissions from domestic properties currently account for a substantial part of the total UK’s carbon emissions and is a priority area for UK to reach zero carbon emissions. However, GHG emissions of urban complexes depend on building, road, structural developments etc surfaces that form urban microclimate. This in turn may further influence renewable energy system power generation that depend on solar or wind potential. Moreover, urban climatic conditions are also influenced by the installation of those power generation systems that may impact their own power generation efficiency. Increased air temperature is attributed to densely installed roof based solar panels that consequently impact their own production efficiency. Installation of roof based solar panels requires adequate guidance to enable housing businesses, councils and organisations to implement sufficient measures for improved power generation in relation to local urban microclimate. How microclimate is affected and how, in return, it affects solar power productivity. Derby Council & Derby Homes have been collecting solar panel power generation data for a large number of properties. The different building areas and system operation performance will be studied against microclimate conditions through time. It is envisaged that the outcomes of the study will support a working up strategy for Derby city to ensure that owned homes would be able to access information and data of solar photo voltaic PV and solar thermal panels potential on social housing, helping residents on low incomes create their own green energy to power their homes and heat their homeshot water.

Keywords: microclimate, solar power, urban climatology, urban morphology

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Authors: Omran Alharbi

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It is difficult to find an aspect of our modern lives that has been untouched by mobile technology. Indeed, the use of mobile learning in Saudi Arabia may enhance students’ learning and increase overall educational standards. However, within tertiary education, the success of e-learning implementation depends on the degree to which students and educators accept mobile learning and are willing to utilise it. Therefore, this research targeted the factors that influence Hail University instructors’ intentions to use mobile learning. An online survey was completed by eighty instructors and it was found that their use of mobile learning was heavily predicted by performance experience, effort expectancy, social influence, and facilitating conditions; the multiple regression analysis revealed that 67% of the variation was accounted for by these variables. From these variables, effort expectancy was shown to be the strongest predictor of intention to use e-learning for instructors.

Keywords: acceptance, faculty member, mobile learning, KSA

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Authors: Rojith K. Balakrishnan

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Plasmablastic lymphoma (PBL) is an uncommon, recently described B-cell derived lymphoma that is most commonly seen in patients with Human Immunodeficiency Virus (HIV) infection. Here we report a case of PBL in a 35 year old man with HIV who presented with multiple subcutaneous swellings all over the body and oral mucosal lesions.The biopsy report was suggestive of Diffuse Large B Cell Lymphoma. Immunohistochemistry was done which showed, lymphoma cells, positive for MUM1, CD 138, and VS 38. The proliferation index (MIB) was 95%. Final report was consistent with the diagnosis of Plasmablastic Lymphoma. The lesion completely regressed after treatment with systemic chemotherapy. Up to date, only a few cases of plasmablastic lymphoma have been reported from India. Increased frequency of this lymphoma in HIV patients and rarity of the tumour, along with rapid response of the same to chemotherapy, make this case a unique one. Hence the knowledge about this new entity is important for clinicians who deal with HIV patients.

Keywords: human immunodeficiency virus (HIV), oral cavity lesion, plasmablastic lymphoma, subcutaneous swelling

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Authors: Rashi Jain

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The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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Authors: Ijaz Ul Haq, Fiorenzo Franceschini

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The distributed manufacturing methodology brings a new concept of decentralized manufacturing operations close to the proximity of end users. A preliminary scale, to measure distributed capacity and evaluate positioning of firms, is developed in this research. In the first part of the paper, a literature review has been performed which highlights the explorative nature of the studies conducted to present definitions and classifications due to novelty of this topic. From literature, five dimensions of distributed manufacturing development stages have been identified: localization, manufacturing technologies, customization and personalization, digitalization and democratization of design. Based on these determinants a conceptual scale is proposed to measure the status of distributed manufacturing of a generic firm. A multiple case study is then conducted in two steps to test the conceptual scale and to identify the corresponding level of distributed potential in each case study firm.

Keywords: distributed manufacturing, distributed capacity, localized production, ordinal scale

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Authors: Leonard Lipovich, Pattaraporn Thepsuwan, Anton-Scott Goustin, Juan Cai, Donghong Ju, James B. Brown

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Two-thirds of human genes do not encode any known proteins. Aside from long non-coding RNA (lncRNA) genes with recently-discovered functions, the ~40,000 non-protein-coding human genes remain poorly understood, and a role for their transcripts as de-facto unconventional messenger RNAs has not been formally excluded. Ribosome profiling (Riboseq) predicts translational potential, but without independent evidence of proteins from lncRNA open reading frames (ORFs), ribosome binding of lncRNAs does not prove translation. Previously, we mass-spectrometrically documented translation of specific lncRNAs in human K562 and GM12878 cells. We now examined lncRNA translation in human MCF7 cells, integrating strand-specific Illumina RNAseq, Riboseq, and deep mass spectrometry in biological quadruplicates performed at two core facilities (BGI, China; City of Hope, USA). We excluded known-protein matches. UCSC Genome Browser-assisted manual annotation of imperfect (tryptic-digest-peptides)-to-(lncRNA-three-frame-translations) alignments revealed three peptides hypothetically explicable by 'stop-to-nonstop' in-frame replacement of stop codons by amino acids in two ORFs of the lncRNA MMP24-AS1. To search for this phenomenon genomewide, we designed and implemented a novel pipeline, matching tryptic-digest spectra to wildcard-instead-of-stop versions of repeat-masked, six-frame, whole-genome translations. Along with singleton putative stop-to-nonstop events affecting four other lncRNAs, we identified 24 additional peptides with stop-to-nonstop in-frame substitutions from multiple positive-strand MMP24-AS1 ORFs. Only UAG and UGA, never UAA, stop codons were impacted. All MMP24-AS1-matching spectra met the same significance thresholds as high-confidence known-protein signatures. Targeted resequencing of MMP24-AS1 genomic DNA and cDNA from the same samples did not reveal any mutations, polymorphisms, or sequencing-detectable RNA editing. This unprecedented apparent gene-specific violation of the genetic code highlights the importance of matching peptides to whole-genome, not known-genes-only, ORFs in mass-spectrometry workflows, and suggests a new mechanism enhancing the combinatorial complexity of the proteome. Funding: NIH Director’s New Innovator Award 1DP2-CA196375 to LL.

Keywords: genetic code, lncRNA, long non-coding RNA, mass spectrometry, proteogenomics, ribo-seq, ribosome, RNAseq

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Authors: S. Shakibaei, P. Alpkokin

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The railway network is one of the major components of a transportation system in a country which may be an indicator of the country’s level of economic improvement. Since 2000s on, revival of national railways and development of High Speed Rail (HSR) lines are one of the most remarkable policies of Turkish government in railway sector. Within this trend, the railway age is to be revived and coming decades will be a golden opportunity. Indubitably, major infrastructures such as road and railway networks require sizeable investment capital, precise maintenance and reparation. Traditionally, governments are held responsible for funding, operating and maintaining these infrastructures. However, lack or shortage of financial resources, risk responsibilities (particularly cost and time overrun), and in some cases inefficacy in constructional, operational and management phases persuade governments to find alternative options. Financial power, efficient experiences and background of private sector are the factors convincing the governments to make a collaboration with private parties to develop infrastructures. Public-Private Partnerships (PPP or 3P or P3) and related regulatory issues are born considering these collaborations. In Turkey, PPP approaches have attracted attention particularly during last decade and these types of investments have been accelerated by government to overcome budget limitations and cope with inefficacy of public sector in improving transportation network and its operation. This study mainly tends to present a comprehensive overview of PPP concept, evaluate the regulatory procedure in Europe and propose a general framework for Turkish State Railways (TCDD) as an outlook on privatization, liberalization and deregulation of railway network.

Keywords: deregulation, high-speed railway, liberalization, privatization, public-private partnership

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Authors: Maheen Zia

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Near the early twenty-first century, LEGO decided to diversify its product range which resulted in more specific and single-outcome sets occupying the store shelves than classic kits having fairly all-purpose bricks. Earlier, LEGOs came with more bricks and lesser instructions. Today, there are more single kits being produced and sold, which come with a strictly defined set of guidelines. If one set is used to make a car, the same bricks cannot be put together to produce any other article. Earlier, multiple bricks gave children a chance to be imaginative, think of new items and construct them (by just putting the same pieces differently). The new products are less open-ended and offer a limited possibility for players in both designing and realizing those designs. The article reviews (in the light of existing research) how classic LEGO sets could help enhance a child’s creativity in comparison with single sets, which allow a player to interact (not experiment) with the bricks.

Keywords: constructive play, creativity, LEGO, play-based learning

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Authors: Yasunori Kobori, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

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In this paper, we study a Pulse-WidthModulation (PWM) controlled Zero-Voltage-Switching (ZVS) for single-inductor dual-output (SIDO) converters. This method can meet the industry demands for high efficiency due to ZVS and small size and low cost, thanks to single-inductor per multiple voltages. We show the single inductor single-output (SISO) ZVS buck converter with its operation and simulation and then the experimental results. Next proposed ZVS-PWM controlled SIDO converters are explained in the simulation. Finally we have proposed EMI reduction method with spread spectrum.

Keywords: DC-DC switching converter, zero-oltage switching control, single-inductor dual-output converter, EMI reduction, spread spectrum

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Soumiya Bhattacharjee, P. K. Champati Ray, Shovan L. Chattoraj, Mrinmoy Dhara

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The entire Himalayan range is globally renowned for rainfall-induced landslides. The prime focus of the study is to determine rainfall based threshold for initiation of landslides that can be used as an important component of an early warning system for alerting stake holders. This research deals with temporal dimension of slope failures due to extreme rainfall events along the National Highway-58 from Karanprayag to Badrinath in the Garhwal Himalaya, India. Post processed 3-hourly rainfall intensity data and its corresponding duration from daily rainfall data available from Tropical Rainfall Measuring Mission (TRMM) were used as the prime source of rainfall data. Landslide event records from Border Road Organization (BRO) and some ancillary landslide inventory data for 2013 and 2014 have been used to determine Intensity Duration (ID) based rainfall threshold. The derived governing threshold equation, I= 4.738D^-0.025, has been considered for prediction of landslides of the study region. This equation was validated with an accuracy of 70% landslides during August and September 2014. The derived equation was considered for further prediction of landslides of the study region. From the obtained results and validation, it can be inferred that this equation can be used for initiation of landslides in the study area to work as a part of an early warning system. Results can significantly improve with ground based rainfall estimates and better database on landslide records. Thus, the study has demonstrated a very low cost method to get first-hand information on possibility of impending landslide in any region, thereby providing alert and better preparedness for landslide disaster mitigation.

Keywords: landslide, intensity-duration, rainfall threshold, TRMM, slope, inventory, early warning system

Procedia PDF Downloads 268

Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

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For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Monika Rezacova

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Radiation-induced breast changes are a consequence of radiotherapy toxicity over the breast tissues either related to targeted breast cancer treatment or other thoracic malignancies (eg. lung cancer). This study has created an overview of different changes and their pathophysiology. The main conditions included were skin thickening, interstitial oedema, fat necrosis, dystrophic calcifications, skin retractions, glandular atrophy, breast fibrosis and radiation induced breast cancer. This study has performed focused literature search through multiple databases including pubmed, medline and embase. The study has reviewed English as well as non English publications. As a result of the literature the study provides comprehensive overview of radiation-induced breast changes and their pathophysiology with small focus on new development and prevention.

Keywords: radiotherapy toxicity, breast tissue changes, breast cancer treatment, radiation-induced breast changes

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Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: A. Miškinytė, A. Dėdelė

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Road traffic is one of the main sources of air pollution in urban areas associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered as traffic-related air pollutant, which concentrations tend to be higher near highways, along busy roads and in city centres and exceedances are mainly observed in air quality monitoring stations located close to traffic. Atmospheric dispersion models can be used to examine emissions from many various sources and to predict the concentration of pollutants emitted from these sources into the atmosphere. The study aim was to compare modelled concentrations of nitrogen dioxide using ADMS-Urban dispersion model with air quality monitoring network in cold and warm seasons in Kaunas city. Modelled average seasonal concentrations of nitrogen dioxide for 2011 year have been verified with automatic air quality monitoring data from two stations in the city. Traffic station is located near high traffic street in industrial district and background station far away from the main sources of nitrogen dioxide pollution. The modelling results showed that the highest nitrogen dioxide concentration was modelled and measured in station located near intensive traffic street, both in cold and warm seasons. Modelled and measured nitrogen dioxide concentration was respectively 25.7 and 25.2 µg/m3 in cold season and 15.5 and 17.7 µg/m3 in warm season. While the lowest modelled and measured NO2 concentration was determined in background monitoring station, respectively 12.2 and 13.3 µg/m3 in cold season and 6.1 and 7.6 µg/m3 in warm season. The difference between monitoring station located near high traffic street and background monitoring station showed that better agreement between modelled and measured NO2 concentration was observed at traffic monitoring station.

Keywords: air pollution, nitrogen dioxide, modelling, ADMS-Urban model

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Husnil Khatimah, Fairol Halim

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This research examines the moderating impact of security on intention to use e-money that adapted from some variables of the TAM (Technology Acceptance Model) and TPB (Theory of Planned Behavior). This study will use security as moderating variable and finds these relationship depends on customer intention to use e-money as payment tools. The conceptual framework of e-money transactions was reviewed to understand behavioral intention of consumers from perceived usefulness, perceived ease of use, perceived behavioral control and security. Quantitative method will be utilized as sources of data collection. A total of one thousand respondents will be selected using quota sampling method in Medan, Indonesia. Descriptive analysis and Multiple Regression analysis will be conducted to analyze the data. The article ended with suggestion for future studies.

Keywords: e-money transaction, TAM & TPB, moderating variable, behavioral intention, conceptual paper

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Authors: Xia Luo, Cheng Zeng

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Under the promotion of the Central Committee of the Communist Party of China and the State Council in 2017, Xiong'an New Area is the third crucial new area in China established after Shenzhen and Shanghai. Its constructions' significance lies in mitigating Beijing's non-capital functions and exploring a new mode of optimizing development in densely populated and economically intensive areas. For this purpose, developing underground logistics can assume the role of goods distribution in the capital, relieve the road transport pressure in Beijing-Tianjin-Hebei Urban Agglomeration, adjust and optimize the urban layout and spatial structure of it. Firstly, the construction planning of Xiong'an New Area and underground logistics development are summarized, especially the development status abroad, the development trend, and bottlenecks of underground logistics in China. This paper explores the technicality, feasibility, and necessity of four modes of transportation. There are pneumatic capsule pipeline (PCP) technology, the CargoCap technology, cable hauled mule, and automatic guided vehicle (AGV). The above technical parameters and characteristics are introduced to relevant experts or scholars. Through establishing an indicator system, carrying out a questionnaire survey with the Delphi method, the final suggestion is obtained: China should develop logistics vehicles similar to CargoCap, adopting rail mode and driverless mode. Based on China's temporal and spatial logistics demand and the geographical pattern of Xiong'an New Area, the construction scale, technical parameters, node location, and other vital parameters of underground logistics are planned. In this way, we hope to speed up the new area's construction and the logistics industry's innovation.

Keywords: the Xiong'an new area, underground logistics, contrastive analysis, CargoCap, logistics planning

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Authors: Elsie L. Echeverri-Carroll

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Entrepreneurial ecosystems have become an important concept to explain the birth and sustainability of technology-based entrepreneurship within regions. However, as a theoretical concept, the temporal evolution of entrepreneurship systems remain underdeveloped, making it difficult to understand their dynamic contributions to entrepreneurs. This paper argues that successful technology-based ecosystems go over three cumulative spawning stages: corporate spawning, entrepreneurial spawning, and community spawning. The importance of corporate incubation in vibrant entrepreneurial ecosystems is well documented in the entrepreneurial literature. Similarly, entrepreneurial spawning processes for venture capital-backed startups are well documented in the financial literature. In contrast, there is little understanding of both the third stage of entrepreneurial spawning (when a community of entrepreneurs become a source of firm spawning) and the temporal sequence in which spawning effects occur in a region. We test this three-stage model of entrepreneurial spawning using data from two large databases on firm births—the Secretary of State (160,000 observations) and the National Establishment Time Series (NEST with 150,000 observations)—and information collected from 60 1½-hour interviews with startup founders and representatives of key entrepreneurial organizations. This temporal model is illustrated with case study of Austin, Texas ranked by the Kauffman Foundation as the number one entrepreneurial city in the United States in 2015 and 2016. The 1½-year study founded by the Kauffman Foundation demonstrates the importance of taken into consideration the temporal contributions of both large and entrepreneurial firms in understanding the factors that contribute to the birth and growth of technology-based entrepreneurial regions. More important, these learnings could offer an important road map for regions that pursue to advance their entrepreneurial ecosystems.

Keywords: entrepreneurial ecosystems, entrepreneurial industrial clusters, high-technology, temporal changes

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Authors: Nana Kojo Ayimadu Baafi, Kwesi Amponsah-Tawiah

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The study investigated the relationship between job-related anxiety and employee creativity. The study further explored the role of job resources in moderating the relationship between job-related anxiety and employee creativity within the oil and gas industries. The study utilized a cross-sectional survey design. A non-probability sampling technique, specifically convenience sampling, was used to sample 1200 participants from multiple companies within the oil and gas industries. The collected data were analyzed using Regression analysis and PROCESS macro for the moderation analysis. The study empirically demonstrated a negative significant relationship between job-related anxiety and employee creativity. It also exhibited that job resources moderated the relationship between job-related anxiety and creativity. This study addresses gaps in previous studies by highlighting the significance of job resources in how job-related anxiety affects employee creativity.

Keywords: employee creativity, job-related anxiety, job resource, human resources

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Authors: Andrea Tonoli, Nicola Amati, Maria Cavatorta, Reza Mirsanei, Behzad Mozaffari, Hamed Ahani, Akbar Karamihafshejani, Mohammad Ghazivakili, Mohammad Abuabiah

Abstract:

The vibrations transmitted to the drivers and passengers through vehicle seat seriously effect on the level of their attention, fatigue and physical health and reduce the comfort and efficiency of the occupants. Recently, some researchers have focused on vibrations at low excitation frequency(0.5-5 Hz) which are considered to be the main risk factors for lumbar part of the backbone but they were not applicable to A and B-segment cars regarding to the size and weight. A semi-active system with two symmetric negative stiffness structures (NSS) in parallel to a positive stiffness structure and actuators has been proposed to attenuate low frequency excitation and makes system flexible regarding to different weight of passengers which is applicable for A and B-Segment cars. Here, the 3 degree of freedom system is considered, dynamic equation clearly is presented, then simulated in MATLAB in order to analysis of performance of the system. The design procedure is derived so that the resonance peak of frequency–response curve shift to the left, the isolating range is increased and especially, the peak of the frequency–response curve is minimized. According to ISO standard different class of road profile as an input is applied to the system to evaluate the performance of the system. To evaluate comfort issues, we extract the RMS value of the vertical acceleration acting on the passenger's body. Then apply the band-pass filter, which takes into account the human sensitivity to acceleration. According to ISO, this weighted acceleration is lower than 0.315 m/s^2, so the ride is considered as comfortable.

Keywords: low frequency excitation, negative stiffness, seat vehicle, vibration isolation

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

Abstract:

This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Adeola Ibukunoluwa Samuel, Afsoon Kazerouni

Abstract:

Industrial mineral kaolin has many favourable properties such as colour, shape, softness, non-abrasiveness, natural whiteness, as well as chemical stability. It occurs extensively in North of Bedford road Grahamstown, South Africa. The relationship between both the physical and chemical properties as lead to its application in the production of certain industrial products which are used by the public; this includes the prospect of production of paper, ceramics, rubber, paint, and plastics. Despite its interesting economic potentials, kaolinite clay mineral remains undermined, and this is threatening its sustainability in the mineral industry. This research study focuses on a detailed evaluation of the kaolinite mineral and possible ways to increase its lifespan in the industry. The methods employed for this study includes petrographic microscopy analysis, X-ray powder diffraction analysis (XRD), and proper field reconnaissance survey. Results emanating from this research include updated geological information on Grahamstown. Also, mineral transformation phases such as quartz, kaolinite, calcite and muscovite were identified in the clay samples. Petrographic analysis of the samples showed that the study area has been subjected to intense tectonic deformation and cement replacement. Also, different dissolution patterns were identified on the Grahamstown kaolinitic clay deposits. Hence incorporating analytical studies and data interpretations, possible ways such as the establishment of processing refinery near mining plants, which will, in turn, provide employment for the locals and land reclamation is suggested. In addition, possible future sustainable industrial applications of the clay minerals seem to be possible if additives, cellulosic wastes are used to alter the clay mineral.

Keywords: kaolinite, industrial use, sustainability, Grahamstown, clay minerals

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Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

Abstract:

In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).

Keywords: network security management, device organization, emergency response, cross-network

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Authors: Adeniran Adetunji, Babalola M. Florence, Akande Ademola

Abstract:

In this paper, we made an overview on the concept of adaptive e-Learning system, enumerates the elements of adaptive learning concepts e.g. A pedagogical framework, multiple learning strategies and pathways, continuous monitoring and feedback on student performance, statistical inference to reach final learning strategy that works for an individual learner by “mass-customization”. Briefly highlights the motivation of this new system proposed for effective learning teaching. E-Review literature on the concept of adaptive e-learning system and emphasises on the Item Response Calibration, which is an important approach to developing an adaptive e-Learning system. This paper write-up is concluded on the justification of item response calibration/estimation towards designing a successful and effective adaptive e-Learning system.

Keywords: adaptive e-learning system, pedagogical framework, item response, computer applications

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Authors: Kathryn McMillan

Abstract:

A recent study of 8500 adult Australians aged 16 and over revealed 62% had experienced childhood maltreatment. In response to multiple recommendations by bodies such as the Australian Law Reform Commission, parliamentary reports and stakeholder input, a number of key initiatives have been developed to grapple with the difficulties of a federal-state system and to screen and triage high-risk families navigating their way through the court system. The Lighthouse Project (LHP) is a world-first initiative of the Federal Circuit and Family Courts in Australia (FCFOCA) to screen family law litigants for major risk factors, including family violence, child abuse, alcohol or substance abuse and mental ill-health at the point of filing in all applications that seek parenting orders. It commenced on 7 December 2020 on a pilot basis but has now been expanded to 15 registries across the country. A specialist risk screen, Family DOORS, Triage has been developed – focused on improving the safety and wellbeing of families involved in the family law system safety planning and service referral, and ¬ differentiated case management based on risk level, with the Evatt List specifically designed to manage the highest risk cases. Early signs are that this approach is meeting the needs of families with multiple risks moving through the Court system. Before the LHP, there was no data available about the prevalence of risk factors experienced by litigants entering the family courts and it was often assumed that it was the litigation process that was fueling family violence and other risks such as suicidality. Data from the 2022 FCFCOA annual report indicated that in parenting proceedings, 70% alleged a child had been or was at risk of abuse, 80% alleged a party had experienced Family Violence, 74 % of children had been exposed to Family Violence, 53% alleged through substance misuse by party children had caused or was at risk of causing harm to children and 58% of matters allege mental health issues of a party had caused or placed a child at risk of harm. Those figures reveal the significant overlap between child protection and family violence, both of which are under the responsibility of state and territory governments. Since 2020, a further key initiative has been the co-location of child protection and police officials amongst a number of registries of the FCFOCA. The ability to access in a time-effective way details of family violence or child protection orders, weapons licenses, criminal convictions or proceedings is key to managing issues across the state and federal divide. It ensures a more cohesive and effective response to family law, family violence and child protection systems.

Keywords: child protection, family violence, parenting, risk screening, triage.

Procedia PDF Downloads 71