Search results for: real time simulator

Authors: Tauha Hussain Ali, Shabir Hussain Khahro, Nafees Ahmed Memon

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Accurate prediction of project time for planning and bid preparation stage should contain realistic dates. Constructors use their experience to estimate the project duration for the new projects, which is based on intuitions. It has been a constant concern to both researchers and constructors to analyze the accurate prediction of project duration for bid preparation stage. In Pakistan, such study for time cost relationship has been lacked to predict duration performance for the construction projects. This study is an attempt to explore the time cost relationship that would conclude with a mathematical model to predict the time for the drainage rehabilitation projects in the province of Sindh, Pakistan. The data has been collected from National Engineering Services (NESPAK), Pakistan and regression analysis has been carried out for the analysis of results. Significant relationship has been found between time and cost of the construction projects in Sindh and the generated mathematical model can be used by the constructors to predict the project duration for the upcoming projects of same nature. This study also provides the professionals with a requisite knowledge to make decisions regarding project duration, which is significantly important to win the projects at the bid stage.

Keywords: BTC Model, project time, relationship of time cost, regression

Procedia PDF Downloads 368

Authors: T. Elrazaz

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This paper examines accrual and real earnings management by publicly listed targets around mergers and acquisitions. Prior literature shows that earnings management around mergers and acquisitions can have a significant economic impact because of the associated wealth transfers among stakeholders. More importantly, acting on behalf of their shareholders or pursuing their self-interests, managers of both targets and acquirers may be equally motivated to manipulate earnings prior to an acquisition to generate higher gains for their shareholders or themselves. Building on the grounds of information asymmetry, agency conflicts, stewardship theory, and the revelation principle, this study addresses the question of whether takeover targets employ accrual and real earnings management in the periods prior to the announcement of Mergers and Acquisitions (M&A). Additionally, this study examines whether acquirers are able to detect targets’ earnings management, and in response, adjust the acquisition premium paid in order not to face the risk of overpayment. This study uses an aggregate accruals approach in estimating accrual earnings management as proxied by estimated abnormal accruals. Additionally, real earnings management is proxied for by employing widely used models in accounting and finance literature. The results of this study indicate that takeover targets manipulate their earnings using accruals in the second year with an earnings release prior to the announcement of the M&A. Moreover, in partitioning the sample of targets according to the method of payment used in the deal, the results are restricted only to targets of stock-financed deals. These results are consistent with the argument that targets of cash-only or mixed-payment deals do not have the same strong motivations to manage their earnings as their stock-financed deals counterparts do additionally supporting the findings of prior studies that the method of payment in takeovers is value relevant. The findings of this study also indicate that takeover targets manipulate earnings upwards through cutting discretionary expenses the year prior to the acquisition while they do not do so by manipulating sales or production costs. Moreover, in partitioning the sample of targets according to the method of payment used in the deal, the results are restricted only to targets of stock-financed deals, providing further robustness to the results derived under the accrual-based models. Finally, this study finds evidence suggesting that acquirers are fully aware of the accrual-based techniques employed by takeover targets and can unveil such manipulation practices. These results are robust to alternative accrual and real earnings management proxies, as well as controlling for the method of payment in the deal.

Keywords: accrual earnings management, acquisition premium, real earnings management, takeover targets

Procedia PDF Downloads 100

Authors: Diamant Irene, Dar Tamar

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Burnout, conceptualized within the framework of stress research, is to a large extent a result of a threat on resources of time or a feeling of time shortage. In reaction to numerous tasks, deadlines, high output, management of different duties encompassing work-home conflicts, many individuals experience ‘time pressure’. Time pressure is characterized as the perception of a lack of available time in relation to the amount of workload. It can be a result of local objective constraints, but it can also be a chronic attribute in coping with life. As such, time pressure is associated in the literature with general stress experience and can therefore be a direct, contributory burnout factor. The present study examines the relation of chronic time pressure – feeling of time shortage and of being rushed, with another central aspect in subjective temporal experience - time perspective. Time perspective is a stable personal disposition, capturing the extent to which people subjectively remember the past, live the present and\or anticipate the future. Based on Hobfoll’s Conservation of Resources Theory, it was hypothesized that individuals with chronic time pressure would experience a permanent threat on their time resources resulting in relatively increased burnout. In addition, it was hypothesized that different time perspective profiles, based on Zimbardo’s typology of five dimensions – Past Positive, Past Negative, Present Hedonistic, Present Fatalistic, and Future, would be related to different magnitudes of chronic time pressure and of burnout. We expected that individuals with ‘Past Negative’ or ‘Present Fatalist’ time perspectives would experience more burnout, with chronic time pressure being a moderator variable. Conversely, individuals with a ‘Present Hedonistic’ - with little concern with the future consequences of actions, would experience less chronic time pressure and less burnout. Another temporal experience angle examined in this study is the difference between the actual distribution of time (as in a typical day) versus desired distribution of time (such as would have been distributed optimally during a day). It was hypothesized that there would be a positive correlation between the gap between these time distributions and chronic time pressure and burnout. Data was collected through an online self-reporting survey distributed on social networks, with 240 participants (aged 21-65) recruited through convenience and snowball sampling methods from various organizational sectors. The results of the present study support the hypotheses and constitute a basis for future debate regarding the elements of burnout in the modern work environment, with an emphasis on subjective temporal experience. Our findings point to the importance of chronic and stable temporal experiences, as time pressure and time perspective, in occupational experience. The findings are also discussed with a view to the development of practical methods of burnout prevention.

Keywords: conservation of resources, burnout, time pressure, time perspective

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Authors: Chien-Wei Hung, Fu-Hau Hsu, Chuan-Sheng Wang, Chia-Hao Lee

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Nowadays, the abuse of keyloggers is one of the most widespread approaches to steal sensitive information. In this paper, we propose an On-Screen Prompts Approach to Keyloggers (OSPAK) and its analysis, which is installed in public computers. OSPAK utilizes a canvas to cue users when their keystrokes are going to be logged or ignored by OSPAK. This approach can protect computers against recoding sensitive inputs, which obfuscates keyloggers with letters inserted among users' keystrokes. It adds a canvas below each password field in a webpage and consists of three parts: two background areas, a hit area and a moving foreground object. Letters at different valid time intervals are combined in accordance with their time interval orders, and valid time intervals are interleaved with invalid time intervals. It utilizes animation to visualize valid time intervals and invalid time intervals, which can be integrated in a webpage as a browser extension. We have tested it against a series of known keyloggers and also performed a study with 95 users to evaluate how easily the tool is used. Experimental results made by volunteers show that OSPAK is a simple approach.

Keywords: authentication, computer security, keylogger, privacy, information leakage

Procedia PDF Downloads 105

Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Haiyang Su, Kun Qian

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We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

Procedia PDF Downloads 196

Authors: Ernesto Ghini

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Workplace accidents are an unfortunate reality. However, they are also predictable and avoidable. We conducted research into a variety of legislation covering lone working, and conducted a study into the use of connected technology and how it can help improve the safety of lone workers in Latin America. We implemented quantitative research into regulations coupled with case study research into a real-life scenario that demonstrated the benefits of technology, and discuss our findings in this paper. Connected safety solutions can improve the bottom line, delivering significant return on investment in terms of improved efficiency and the avoidance of cost associated with worker injury. And, most importantly, such solutions, as demonstrated through our research, make the difference between life and death in time-critical incident situations.

Keywords: ione worker, legislation, technology, connected safety, connectivity

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Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Vitalijs Lusis, Andrejs Krasnikovs

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Fiber reinforced concrete is important material for load bearing structural elements. Usually fibers are homogeneously distributed in a concrete body having arbitrary spatial orientations. At the same time, in many situations, fiber concrete with oriented fibers is more optimal. Is obvious, that is possible to create constructions with oriented short fibers in them, in different ways. Present research is devoted to one of such approaches- fiber reinforced concrete prisms having dimensions 100 mm×100 mm×400 mm with layers of non-homogeneously distributed fibers inside them were fabricated. Simultaneously prisms with homogeneously dispersed fibers were produced for reference as well. Prisms were tested under four point bending conditions. During the tests vertical deflection at the center of every prism and crack opening were measured (using linear displacements transducers in real timescale). Prediction results were discussed.

Keywords: fiber reinforced concrete, 4-point bending, steel fiber, construction engineering

Procedia PDF Downloads 355

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

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In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

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Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

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In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

Procedia PDF Downloads 193

Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

Procedia PDF Downloads 171

Authors: Caridad Maylin-Aguilar, Beatriz Duarte-Monedero

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Problem-based learning (PBL) is a useful tool for adult and practice oriented audiences, as University students. As a consequence of the huge disruption caused by the COVID pandemic in the hospitality industry, hotels of all categories closed down in Spain from March 2020. Since that moment, the luxury segment was blooming with optimistic prospects for new openings. Hence, Hospitality students were expecting a positive situation in terms of employment and career development. By the beginning of the 2020-21 academic year, these expectations were seriously harmed. By October 2020, only 9 of the 32 hotels in the luxury segment were opened with an occupation rate of 9%. Shortly after, the evidence of a second wave affecting especially Spain and the homelands of incoming visitors bitterly smashed all forecasts. In accordance with the situation, a team of four professors and practitioners, from four different subject areas, developed a real case, inspired in one of these hotels, the 5-stars Emperatriz by Barceló. Students in their 2nd course were provided with real information as marketing plans, profit and losses and operational accounts, employees profiles and employment costs. The challenge for them was to act as consultants, identifying potential courses of action, related to best, base and worst case. In order to do that, they were organized in teams and supported by 4th course students. Each professor deployed the problem in their subject; thus, research on the customers behavior and feelings were necessary to review, as part of the marketing plan, if the current offering of the hotel was clear enough to guarantee and to communicate a safe environment, as well as the ranking of other basic, supporting and facilitating services. Also, continuous monitoring of competitors’ activity was necessary to understand what was the behavior of the open outlets. The actions designed after the diagnose were ranked in accordance with their impact and feasibility in terms of time and resources. Also they must be actionable by the current staff of the hotel and their managers and a vision of internal marketing was appreciated. After a process of refinement, seven teams presented their conclusions to Emperatriz general manager and the rest of professors. Four main ideas were chosen, and all the teams, irrespectively of authorship, were asked to develop them to the state of a minimum viable product, with estimations of impacts and costs. As the process continues, students are nowadays accompanying the hotel and their staff in the prudent reopening of facilities, almost one year after the closure. From a professor’s point of view, key learnings were 1.- When facing a real problem, a holistic view is needed. Therefore, the vision of subjects as silos collapses, 2- When educating new professionals, providing them with the resilience and resistance necessaries to deal with a problem is always mandatory, but now seems more relevant and 3.- collaborative work and contact with real practitioners in such an uncertain and changing environment is a challenge, but it is worth when considering the learning result and its potential.

Keywords: problem-based learning, hospitality recovery, collaborative learning, resilience

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Authors: A. Bouloufa, F. Khaled, K. Djessas

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This paper presents a new structure of solar cell based on p-type microcrystalline silicon as an absorber and n-type aluminum doped zinc oxide (ZnO:Al) transparent conductive oxide as an optical window. The ZnO:Al layer deposited by rf-magnetron sputtering at room temperature yields a low resistivity about 7,64.10-2Ω.cm and more than 85% mean optical transmittance in the VIS–NIR range, with an optical band gap of 3.3 eV. These excellent optical properties of this layer in combination with an optimal contact at the front surface result in a superior light trapping yielding to efficiencies about 20%. In order to improve efficiency, we have used a p+-µc-Si thin layer highly doped as a back surface field which minimizes significantly the impact of rear surface recombination velocity on voltage and current leading to a high efficiency of 24%. Optoelectronic parameters were determined using the current density-voltage (J-V) curve by means of a numerical simulation with Analysis of Microelectronic and Photonic Structures (AMPS-1D) device simulator.

Keywords: optical window, thin film, solar cell, efficiency

Procedia PDF Downloads 276

Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

Procedia PDF Downloads 343

Authors: Waqas A. Toor, Anis U. Baig, Nuaman Shafqat, Raafia Irfan, Muhammad Ashraf

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A 2.45GHz microwave plasma system and its few applications have been developed. Argon and helium plasma is produced by metallic nozzle and also in a quartz tube at atmospheric pressure, using WR-340 waveguide and its tapered version. The waveguide applicator is also simulated in HFSS and field patterns are analyzed for maximum power absorption in the load. The system is tuned to operate at less than 10% reflected power. Various experimental techniques are used to initiate and sustain the plasma at atmospheric pressure. Plasma of atmospheric air is also produced without using any other shielding gas. The plasma flame is also characterized by its spectrum. Spectral analyses of plasma flame can be used for online analysis of combustion gases produced in industry. The applications of the system include glass and quartz processing, vitrification, emission spectroscopy, plasma coating. Low pressure plasma applications of the system include intense UV light for water purification and ozone generation.

Keywords: HFSS high frequency structure simulator, Microwave plasma, UV ultraviolet, WR rectangular waveguide

Procedia PDF Downloads 253

Authors: Sean Hall

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Prior to COVID-19, the world was preoccupied with opioids, effectiveness versus risk, and specifically toxicity versus abuse. Historically underpinning opioid use was a concept of safety. As use over time and real-world data evolved, a pursuit for efficacy associated with non-opioid alternatives became mainstream. On January 8, 2021, the US signed back into the opioid problem, with these two fundamental questions still unresolved. The author will share the current progression of a lead non-opioid cancer bone pain candidate, NanaBis™. NanaBis™ represents two innovative factors: The active ingredients are from cannabinoids; these ingredients are in a proprietary sub-micron delivery platform, NanoCelle®. The author will offer an opinion piece, potentiating the future role of delivery platforms in medicine to increase both patient safety and compliance.

Keywords: NanaBis, nanoCelle, opioids, toxicity

Procedia PDF Downloads 79

Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Samaila Bawa Muazu

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Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a novel plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.

Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, setting time, simulation

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Authors: Afef Dridi, Salah Mezlini

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Since experimental devices cannot calculate stress and deformation of complex structures. The Finite Element Method FEM has been widely used in several fields of research. One of these fields is orthodontics. The advantage of using such a method is the use of an accurate and non invasive method that allows us to have a sufficient data about the physiological reactions can happening in soft tissues. Most of researches done in this field were interested in the study of stresses and deformations induced by orthodontic apparatus in soft tissues (alveolar tissues). Only few studies were interested in the distribution of stress and strain in the orthodontic brackets. These studies, although they tried to be as close as possible to real conditions, their models did not reproduce the clinical cases. For this reason, the model generated by our research is the closest one to reality. In this study, a numerical model was developed to explore the stress and strain distribution under the application of real conditions. A comparison between different material properties was also done.

Keywords: visco-hyperelasticity, FEM, orthodontic treatment, inverse method

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Aïda C. Terblanché-Greeff

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Afro-polychronism is a unique amalgamated cultural value of social self-construal and time orientation. As such, the construct Afro-polychronism is conceptually analysed by focusing on the aspects of Ubuntu as collectivism and African time as polychronism. It is argued that these cultural values have a reciprocal and thus inseparable relationship. As it is general practice to measure cultural values empirically, the author conducted empirically engaged philosophy and aimed to develop a scale to measure Afro-polychronism based on its two dimensions of Ubuntu as social self-construal and African time as time orientation. From the scale’s psychometric properties, it was determined that the scale was, in fact, not reliable and valid. It was found that the correlation between the Ubuntu dimension and the African time is moderate (albeit statistically significant). In conclusion, the author abduced why this cultural value cannot be empirically measured based on its theoretical definition and indicated which different path would be more promising.

Keywords: African time, Afro-polychronism, empirically engaged African philosophy, Ubuntu

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Authors: Yu-Cheng Chen, Tzu-Ping Lin, Feng-Yi Lin, Chih-Yu Chen

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Due to the urban heat island effect caused by highly development of city, the heat stress increased in recent year rapidly. Resulting in a sharp raise of the energy used in urban area. The heat stress during summer time exacerbated the usage of air conditioning and electric equipment, which caused more energy consumption and anthropogenic heat. Therefore, an accurate and simple method to measure energy used in urban area can be helpful for the architectures and urban planners to develop better energy efficiency goals. This research applies the combination of airborne LiDAR data and thermal imager to provide an innovate method to estimate energy consumption. Owing to the high resolution of remote sensing data, the accurate current volume and total floor area and the surface temperature of building derived from LiDAR and thermal imager can be herein obtained to predict energy used. In the estimate process, the LiDAR data will be divided into four type of land cover which including building, road, vegetation, and other obstacles. In this study, the points belong to building were selected to overlay with the land use information; therefore, the energy consumption can be estimated precisely with the real value of total floor area and energy use index for different use of building. After validating with the real energy used data from the government, the result shows the higher building in high development area like commercial district will present in higher energy consumption, caused by the large quantity of total floor area and more anthropogenic heat. Furthermore, because of the surface temperature can be warm up by electric equipment used, this study also applies the thermal image of building to find the hot spots of energy used and make the estimation method more complete.

Keywords: urban heat island, urban planning, LiDAR, thermal imager, energy consumption

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Authors: Ajay Kadam, Ramesh Kagalkar

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The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

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Authors: Wanwisa Deenin, Abdulhadee Yakoh, Chahya Kreangkaiwal, Orawon Chailapakul, Kanitha Patarakul, Sudkate Chaiyo

Abstract:

LipL32 is an outer membrane protein present only on pathogenic Leptospira species, which are the causative agent of leptospirosis. Leptospirosis symptoms are often misdiagnosed with other febrile illnesses as the clinical manifestations are non-specific. Therefore, an accurate diagnostic tool for leptospirosis is indeed critical for proper and prompt treatment. Typical diagnosis via serological assays is generally performed to assess the antibodies produced against Leptospira. However, their delayed antibody response and complicated procedure are undoubtedly limited the practical utilization especially in primary care setting. Here, we demonstrate for the first time an early-stage detection of LipL32 by an integrated lateral-flow immunoassay with electrochemical readout (eLFIA). A ferrocene trace tag was monitored via differential pulse voltammetry operated on a smartphone-based device, thus allowing for on-field testing. Superior performance in terms of the lowest detectable limit of detection (LOD) of 8.53 pg/mL and broad linear dynamic range (5 orders of magnitude) among other sensors available thus far was established. Additionally, the developed test strip provided a straightforward yet sensitive approach for diagnosis of leptospirosis using the collected human sera from patients, in which the results were comparable to the real-time polymerase chain reaction technique.

Keywords: leptospirosis, electrochemical detection, lateral flow immunosensor, point-of-care testing, early-stage detection

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Authors: A. S. Lunev, A. A. Larenkov, O. E. Klementyeva, G. E. Kodina

Abstract:

Background and aims: 68Ga-citrate is one of prospective radiopharmaceutical for PET-imaging of inflammation and infection. 68Ga-citrate is 67Ga-citrate analogue using since 1970s for SPECT-imaging. There's known rebinding reaction occurs past Ga-citrate injection and gallium (similar iron Fe3+) binds with blood transferrin. Then radiolabeled protein complex is delivered to pathological foci (inflammation/infection sites). But excessive gallium bindings with transferrin are cause of slow blood clearance, long accumulation time in foci (24-72 h) and exception of application possibility of the short-lived gallium-68 (T½ = 68 min). Injection of additional chemical agents (e.g. Fe3+ compounds) competing with radioactive gallium to the blood transferrin joining (blocking of its metal binding capacity) is one of the ways to solve formulated problem. This phenomenon can be used for correction of 68Ga-citrate pharmacokinetics for increasing of the blood clearance and accumulation in foci. The aim of real studying is research of effect of stable Fe-citrate on 68Ga-citrate tissue distribution. Materials and methods: 68Ga-citrate without/with extra injection of stable Fe-citrate (III) was injected nonlinear mice with inflammation models (aseptic soft tissue inflammation, lung infection, osteomyelitis). PET/X-RAY Genisys4 (Sofie Bioscience, USA) was used for non-invasive PET imaging (for 30, 60, 120 min past injection 68Ga-citrate) with subsequent reconstruction of imaging and their analysis (value of clearance, distribution volume). Scanning time is 10 min. Results and conclusions: I. v. injection of stable Fe-citrate blocks the metal-binding capability of transferrin serum and allows decreasing gallium-68 radioactivity in blood significantly and increasing accumulation in inflammation (3-5 time). It allows receiving more informative PET-images of inflammation early (for 30-60 min after injection). Pharmacokinetic parameters prove it. Noted there is no statistically significant difference between 68Ga-citrate accumulation for different inflammation model because PET imaging is indication of pathological processes and is not their identification.

Keywords: 68Ga-citrate, Fe-citrate, PET imaging, mice, inflammation, infection

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

Abstract:

The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: Catarina Cruz, Ana Breda

Abstract:

In the early years, until the children’s entrance at the elementary school, they are stimulated by their educators, through rich and attractive contexts, to explore and develop skills in different domains, from the socio-emotional to the cognitive. Many of these contexts trigger real or imaginary situations, familiar or not, through resources or pedagogical practices that incite children's curiosity, questioning, expression of ideas or emotions, social interaction, among others. Later, when children enter at the elementary school, their activity at school becomes more focused on developing skills in the cognitive domain, namely acquiring learning from different subject areas, such as Mathematics, Natural Sciences, History, among others. That is, to ensure that children develop the standardized learning recommended in the guiding curriculum documents, they spend part of their time applying formulas, memorizing information, following instructions, and so on, and in this way not much time is left to listen children, to learn about their interests and likes, as well as their perspective and questions about the surround world. In Elementary School, especially in the 1st Cycle, children are naturally curious, however, sometimes this skill is subtly conditioned by adults. Curious children learn more, since they have an intrinsic desire to know more, especially about what is unknown. When children think on subjects or themes that they are interested in or curious about, they attribute more meaning to this learning and retain it for longer. Therefore, it is important to approach subjects in the classroom that seduce or captivate children's attention, trigger them curiosity, and allow to hear their ideas. There are several resources, strategies and pedagogical practices to awaken children's curiosity, to explore their knowledge, to understand their perspectives and their way of thinking, to know a little more about their personality and to provide space for dialogue. The storytelling, its narrative’s exploration and interpretation is one of those pedagogical practices. Children’s literature, about real or imaginary subjects, stimulate children’s insights supported into their experiences, emotions, learnings and personality, and promote opportunities for children express freely their feelings and thoughts. This work focuses on a session developed with children in the 3rd year of schooling, from a Portuguese 1st Cycle Basic School, in which the story "From the Outside In and From the Inside Out" was presented. The story’s presentation was mainly centred on children’s activity, who read excerpts and interpreted/explored them through a dialogue led by one of the authors. The study presented here intends to show an example of how an exploration of a children's story can trigger ideas, thoughts, emotions or attitudes in children in the 3rd year of elementary school. To answer the research question, this work aimed to: identify ideas, thoughts, emotions or attitudes that emerged from the exploration of story; analyse aspects of the story and the orchestration/conduction of dialogue with/between children that facilitated or inhibited the emergence of ideas, thoughts, emotions or attitudes by children,

Keywords: storytelling, children’s perspectives, soft skills, non-formal learning contexts, orchestration

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Authors: Guillaume Richard, Sarra Zaied

Abstract:

Marine waste quantities increase more and more, 5 million tons of plastic waste enter the ocean every year. Their spatiotemporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment, as well as the size and location of the waste. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. In this context, diverse studies have been dedicated to describing waste behavior in order to identify its accumulation in ocean areas. None of the existing tools which track objects at sea had the objective of tracking down a slick of waste. Moreover, the applications related to marine waste are in the minority compared to rescue applications or oil slicks tracking applications. These approaches are able to accurately simulate an object's behavior over time but not during the collection mission of a waste sheet. This paper presents numerical modeling of a boat’s wake impact on the floating marine waste behavior during a collection mission. The aim is to predict the trajectory of a marine waste slick to optimize its collection using meteorological data of ocean currents, wind, and possibly waves. We have made the choice to use Ocean Parcels which is a Python library suitable for trajectoring particles in the ocean. The modeling results showed the important role of advection and diffusion processes in the spatiotemporal distribution of floating plastic litter. The performance of the proposed method was evaluated on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). The results of the evaluation in Cape of Good Hope (South Africa) prove that the proposed approach can effectively predict the position and velocity of marine litter during collection, which allowed for optimizing time and more than $90\%$ of the amount of collected waste.

Keywords: marine litter, advection-diffusion equation, sea current, numerical model

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