Search results for: location based alarm

Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

Procedia PDF Downloads 168

Authors: Juliet F. Poujol, Jeff John Tanner, Christophe Fournier

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Employers desire a favorable brand as an employer. This research considers whether motivation theory is applied to identify universally desirable employer brand elements. Based on data from a website where employees give their opinion about their employer (N=200), this research examines what salespeople found positive and negative about their job. Results show that traditional motivators like opportunities of advancement, and 'hygiene' factors such as benefits and work conditions are a source of satisfaction for salespeople. We also found differences by sectors. Implications are related to sales force recruitment and management.

Keywords: employer brand, motivation, qualitative study, salespeople

Procedia PDF Downloads 372

Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 266

Authors: Aaron Zhang, Alimire Kahaer, Gerald Weber, Nalin Arachchilage

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Access control is an essential safeguard for the security of enterprise data, which controls users’ access to information resources and ensures the confidentiality and integrity of information resources [1]. Research shows that the more common types of access control now have shortcomings [2]. In this direction, to improve the existing access control, we have studied the current technologies in the field of data security, deeply investigated the previous data access control policies and their problems, identified the existing deficiencies, and proposed a new extension structure of SPBAC. SPBAC extension proposed in this paper aims to combine Policy-Based Access Control (PBAC) with semantics to provide logically connected, real-time data access functionality by establishing associations between enterprise data through semantics. Our design combines policies with linked data through semantics to create a "Semantic link" so that access control is no longer per-database and determines that users in each role should be granted access based on the instance policy, and improves the SPBAC implementation by constructing policies and defined attributes through the XACML specification, which is designed to extend on the original XACML model. While providing relevant design solutions, this paper hopes to continue to study the feasibility and subsequent implementation of related work at a later stage.

Keywords: access control, semantic policy-based access control, semantic link, access control model, instance policy, XACML

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Nasar Aldian Ambark Shashoa

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Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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Authors: M. R. Akbari , H. Yousefnia, E. Mirrezaei

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Range uncertainties of protons are currently a topic of interest in proton therapy. Two of the parameters that are often used to specify proton range are water equivalent thickness (WET) and water equivalent ratio (WER). Since WER values for a specific material is nearly constant at different proton energies, it is a more useful parameter to compare. In this study, WER values were calculated for different proton energies in polymethyl methacrylate (PMMA), polystyrene (PS) and aluminum (Al) using FLUKA and TRIM codes. The results were compared with analytical, experimental and simulated SEICS code data obtained from the literature. In FLUKA simulation, a cylindrical phantom, 1000 mm in height and 300 mm in diameter, filled with the studied materials was simulated. A typical mono-energetic proton pencil beam in a wide range of incident energies usually applied in proton therapy (50 MeV to 225 MeV) impinges normally on the phantom. In order to obtain the WER values for the considered materials, cylindrical detectors, 1 mm in height and 20 mm in diameter, were also simulated along the beam trajectory in the phantom. In TRIM calculations, type of projectile, energy and angle of incidence, type of target material and thickness should be defined. The mode of 'detailed calculation with full damage cascades' was selected for proton transport in the target material. The biggest difference in WER values between the codes was 3.19%, 1.9% and 0.67% for Al, PMMA and PS, respectively. In Al and PMMA, the biggest difference between each code and experimental data was 1.08%, 1.26%, 2.55%, 0.94%, 0.77% and 0.95% for SEICS, FLUKA and SRIM, respectively. FLUKA and SEICS had the greatest agreement (≤0.77% difference in PMMA and ≤1.08% difference in Al, respectively) with the available experimental data in this study. It is concluded that, FLUKA and TRIM codes have capability for Bragg curves simulation and WER values calculation in the studied materials. They can also predict Bragg peak location and range of proton beams with acceptable accuracy.

Keywords: water equivalent ratio, dosimetric materials, proton therapy, Monte Carlo simulations

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: Liang Qin, Hanan M. D. Habbi

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A robust sensorless speed for permanent magnet synchronous motor (PMSM) has been presented for estimation of stator flux components and rotor speed based on The Extended Kalman Filter (EKF). The model of PMSM and its EKF models are modeled in Matlab /Sirnulink environment. The proposed EKF speed estimation method is also proved insensitive to the PMSM parameter variations. Simulation results demonstrate a good performance and robustness.

Keywords: DTC, Extended Kalman Filter (EKF), PMSM, sensorless control, anti-windup PI

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Authors: Olga Mironiuk, Małgorzata Kossowska

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The aim of the present study was to investigate the influence of Situational Attribution Training on reducing automatic in-group stereotyping in females. The experiment was conducted with the control of age and level of prejudice. 90 female participants were randomly assigned to two conditions: experimental and control group (each group was also divided into younger- and older-aged condition). Participants from the experimental condition were subjected to more extensive training. In the first part of the experiment, the experimental group took part in the first session of Situational Attribution Training while the control group participated in the Grammatical Training Control. In the second part of the research both groups took part in the Situational Attribution Training (which was considered as the second training session for the experimental group and the first one for the control condition). The training procedure was based on the descriptions of ambiguous situations which could be explained using situational or dispositional attributions. The participant’s task was to choose the situational explanation from two alternatives, out of which the second one presented the explanation based on neutral or stereotypically associated with women traits. Moreover, the experimental group took part in the third training session after two- day time delay, in order to check the persistence of the training effect. The main hypothesis stated that among participants taking part in the more extensive training, the automatic in-group stereotyping would be less frequent after having finished training sessions. The effectiveness of the training was tested by measuring the response time and the correctness of answers: the longer response time for the examples where one of two possible answers was based on the stereotype trait and higher correctness of answers was considered to be a proof of the training effectiveness. As the participants’ level of prejudice was controlled (using the Ambivalent Sexism Inventory), it was also assumed that the training effect would be weaker for participants revealing a higher level of prejudice. The obtained results did not confirm the hypothesis based on the response time: participants from the experimental group responded faster in case of situations where one of the possible explanations was based on stereotype trait. However, an interesting observation was made during the analysis of the answers’ correctness: regardless the condition and age group affiliation, participants made more mistakes while choosing the situational explanations when the alternative was based on stereotypical trait associated with the dimension of warmth. What is more, the correctness of answers was higher in the third training session for the experimental group in case when the alternative of situational explanation was based on the stereotype trait associated with the dimension of competence. The obtained results partially confirm the effectiveness of the training.

Keywords: female, in-group stereotyping, prejudice, situational attribution training

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Authors: Kathryn Watson

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In 2020 North Carolina passed legislation mandating all educators be trained in identifying, referring, and supporting students showing signs of mental health issues, drug use, suicidal ideation, and sex trafficking. This study collected survey responses from 226 educators in North Carolina to better understand their perspectives on the legislation and their self-efficacy in supporting student mental health needs. Key findings of the study reveal that the mandated trainings increased educator awareness of student mental health, and higher awareness was linked to higher self-efficacy in supporting student mental health needs. Additionally, the results showed that educators who identify as Black had lower levels of self-efficacy in supporting student mental health. Additionally, rural educators were least likely to support the legislation in comparison to their urban and suburban counterparts. These findings can help inform policymakers in evaluating the policy and district decision-makers in selecting and implementing school-based mental health training.

Keywords: school-based mental health, education policy, student health, North Carolina, K-12 education

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Authors: Akbar Farahani, Afsaneh Hassani, Peyman M. Farkhondeh

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Human Resource Management as one of the core processes of the project-based companies, despite its key role in the success and competitive advantage, is relatively unknown. In the project-based companies, due to the accelerated movement of knowledge in the work activities and the temporary nature of the project, the need to develop mechanisms for achieving optimal management of this issues is very challenging. Approach to human resource management in these companies evolves with goals, strategies, and operational processes. Therefore, the need for appropriate tools to facilitate implementation of the optimized human resource management in the project is more than before,Which currently with the development of information technology and modern communication, appropriate to address the optimal approach for dynamic management of human resources in the project have been provided.This is done by using the referral system implemented in Mahab GCE that provides 1: the ability to use humans in projects without geographic limitation and 2:information on the activities and outcomes of referrals.Furthermore, by using this system, recording the lessons learned after any particular activity on projects,accessing quantitative information, procedures, documentation of learned practices that have been stored in the data base as well as using them in future projects is provided.

Keywords: human resource management, project base company, ERP, referrals system

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Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

Procedia PDF Downloads 263

Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

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Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

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Authors: Katherine Y. Barragan-Fonseca, Joop J. A. Van Loon, Marcel Dicke, Dani Lucas-Barbosa

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Flowering plants use different traits to attract pollinators, which indicate flower location and reward quality. Visual and olfactory cues are among the most important floral traits exploited by pollinating insects. Pollination can alter physical and chemical cues of flowers, which can subsequently influence the behaviour of flower visitors. We investigated the main cues exploited by the syrphid fly Episyrphus balteatus and the butterfly Pieris brassicae when visiting flowers of Brassica nigra and Raphanus sativus plants. We studied post-pollination changes and their effects on the behaviour of flower visitors and flower volatile emission. Preference of pollinators was investigated by offering visual and olfactory cues simultaneously as well as separately in two-choice bioassays. We also assessed whether pollen is used as a cue by pollinating insects. In addition, we studied whether behavioural responses could be correlated with changes in plant volatile emission, by collecting volatiles from flower headspace. P. brassicae and E. balteatus did not use pollen as a cue in either of the two plant species studied. Interestingly, pollinators showed a strong bias for visual cues over olfactory cues when exposed to B. nigra plants. Flower visits by pollinators were influenced by post-pollination changes in B. nigra. In contrast, plant responses to pollination did not influence pollinator preference for R. sativus flowers. These results correlate well with floral volatile emission of B. nigra and R. sativus; pollination influenced the volatile profile of B. nigra flowers but not that of R. sativus. Collectively, our data show that different pollinators exploit different visual and olfactory traits when searching for nectar or pollen of flowers of two close related plant species. Although the syrphid fly consumes mostly pollen from brassicaceous flowers, it cannot detect pollen from a distance and likely associates other flower traits with quantity and quality of pollen.

Keywords: plant volatiles, pollinators, post-pollination changes, visual and odour cues

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Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

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A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

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Authors: Chao Xu

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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

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Authors: Sourabh Harihar, Henk Jan Verhagen

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The nurturing of a mangrove ecosystem requires a protected coastal environment with adequate drainage of the soil substratum. In a conceptual design undertaken for a mangrove rejuvenation project along the eastern coast of Mumbai (India), various engineering alternatives have been thought of as a protective coastal structure and drainage system. One such design uses bamboo-pile walls in creating shielded compartments in the form of various layouts, coupled with bamboo drains. The bamboo-based design is found to be environmentally and economically advantageous over other designs like sand-dikes which are multiple times more expensive. Moreover, employing a natural material such as bamboo helps the structure naturally blend with the developing mangrove habitat, allaying concerns about dismantling the structure post mangrove growth. A cost-minimising and eco-friendly bamboo structure, therefore, promises to pave the way for large rehabilitation projects in future. As mangrove ecosystems in many parts of the world increasingly face the threat of destruction due to urban development and climate change, protective nature-based designs that can be built in a short duration are the need of the hour.

Keywords: bamboo, environment, mangrove, rehabilitation

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Authors: Ho-Hsin Lee, Yue-Min Jiang, Shu-Hui Tsai, Jian-Ren Chen, Mei-Yu XU, Wen-Tien Wu

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This project presents an AI-based method and system for wound status analysis. The system uses a three-in-one sensor device to analyze wound status, including color, temperature, and a 3D sensor to provide wound information up to 2mm below the surface, such as redness, heat, and blood circulation information. The system has a 90% accuracy rate, requiring only one manual correction in 70% of cases, with a one-second delay. The system also provides an offline application that allows for manual correction of the wound bed range using color-based guidance to estimate wound bed size with 96% accuracy and a maximum of one manual correction in 96% of cases, with a one-second delay. Additionally, AI-assisted wound bed range selection achieves 100% of cases without manual intervention, with an accuracy rate of 76%, while AI-based wound tissue type classification achieves an 85.3% accuracy rate for five categories. The AI system also includes similar case search and expert recommendation capabilities. For AI-assisted wound range selection, the system uses WIFI6 technology, increasing data transmission speeds by 22 times. The project aims to save up to 64% of the time required for human wound record keeping and reduce the estimated time to assess wound status by 96%, with an 80% accuracy rate. Overall, the proposed AI method and system integrate multiple sensors to provide accurate wound information and offer offline and online AI-assisted wound bed size estimation and wound tissue type classification. The system decreases delay time to one second, reduces the number of manual corrections required, saves time on wound record keeping, and increases data transmission speed, all of which have the potential to significantly improve wound care and management efficiency and accuracy.

Keywords: wound status analysis, AI-based system, multi-sensor integration, color-based guidance

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Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov

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Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IP-protocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.

Keywords: quality of communication, IP-telephony, fuzzy set, fuzzy implication, neural network

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Authors: Lukasz Szydlowski, Jiri Ehlich, Igor Goryanin

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We demonstrate a single chamber, 96-well-plated based Microbial Fuel Cell (MFC) with printed, electronic components. This invention is aimed at robust selection of electrogenic microbial community under specific conditions, e.g., electrode potential, pH, nutrient concentration, salt concentration that can be altered within the 96 well plate array. This invention enables robust selection of electrogenic microbial community under the homogeneous reactor, with multiple conditions that can be altered to allow comparative analysis. It can be used as a standalone technique or in conjunction with other selective processes, e.g., flow cytometry, microfluidic-based dielectrophoretic trapping. Mobile conductive elements, like carbon paper, carbon sponge, activated charcoal granules, metal mesh, can be inserted inside to increase the anode surface area in order to collect electrogenic microorganisms and to transfer them into new reactors or for other analytical works. An array of 96-well plate allows this device to be operated by automated pipetting stations.

Keywords: bioengineering, electrochemistry, electromicrobiology, microbial fuel cell

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Authors: M. R. Zaman, M. S. Bari, M. Kajal

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A field experiment was conducted at the Agroforestry and Environment Research Field, Hajee Mohammad Danesh Science and Technology University, Dinajpur during 2013 to investigate the potentiality of three napier fodder varieties under Litchi orchard. The experiment was consisted of 2 factors RCBD with 3 replications. Among the two factors, factor A was two production systems; S1= Litchi + fodder and S2 = Fodder (sole crop); another factor B was three napier varieties: V1= BARI Napier -1 (Bazra), V2= BARI Napier - 2 (Arusha) and V3= BARI Napier -3 (Hybrid). The experimental results revealed that there were significant variation among the varieties in terms of leaf growth and yield. The maximum number of leaf plant -1 was recorded in variety Bazra (V1) whereas the minimum number was recorded in hybrid variety (V3).Significantly the highest (13.75, 14.53 and14.84 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was also recorded in variety Bazra whereas the lowest (5.89, 6.36 and 9.11 tha-1 at 1st, 2nd v and 3rd harvest respectively) yield was in hybrid variety. Again, in case of production systems, there were also significant differences between the two production systems were founded. The maximum number of leaf plant -1 was recorded under Litchi based AGF system (T1) whereas the minimum was recorded in open condition (T2). Similarly, significantly the highest (12.00, 12.35 and 13.31 tha-1 at 1st, 2nd and 3rd harvest respectively) yield of napier was recorded under Litchi based AGF system where as the lowest (9.73, 10.47 and 11.66 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was recorded in open condition i.e. napier in sole cropping. Furthermore, the interaction effect of napier variety and production systems were also gave significant deviation result in terms of growth and yield. The maximum number of leaf plant -1 was recorded under Litchi based AGF systems with Bazra variety whereas the minimum was recorded in open condition with hybrid variety. The highest yield (14.42, 16.14 and 16.15 tha-1 at 1st, 2nd and 3rd harvest respectively) of napier was found under Litchi based AGF systems with Bazra variety. Significantly the lowest (5.33, 5.79 and 8.48 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was found in open condition i.e. sole cropping with hybrid variety. In case of the quality perspective, the highest nutritive value (DM, ASH, CP, CF, EE, and NFE) was found in Bazra (V1) and the lowest value was found in hybrid variety (V3). Therefore, the suitability of napier production under Litchi based AGF system may be ranked as Bazra > Arusha > Hybrid variety. Finally, the economic analysis showed that maximum BCR (5.20) was found in the Litchi based AGF systems over sole cropping (BCR=4.38). From the findings of the taken investigation, it may be concluded that the cultivation of Bazra napier varieties in the floor of Litchi orchard ensures higher revenue to the farmers compared to its sole cropping.

Keywords: potentiality, Litchi, fodder, agroforestry

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Authors: Young Gil Kim, Hye Min Park, Chan Jong Park, Koan Sik Joo

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A personal gamma spectrometer has to be sensitive, pocket-sized, and carriable on the users. To serve these requirements, we developed the SiPM-based portable radiation detectors. The prototype uses a Ce:GAGG scintillator coupled to a silicon photomultiplier and a radio frequency(RF) module to measure gamma-ray, and can be accessed wirelessly or remotely by mobile equipment. The prototype device consumes roughly 4.4W, weighs about 180g (including battery), and measures 5.0 7.0. It is able to achieve 5.8% FWHM energy resolution at 662keV.

Keywords: Ce:GAGG, gamma-ray, radio frequency, silicon photomultiplier

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Mohammad Ashraful Alam, Biro Judit

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Fear of gender-based crime and fear of crime victimization for women is a major concern in the urban areas of Bangladesh. Based on the recent data from various human rights organizations and international literature the study found that gender-based crime especially sexual assault and rape are increasing in Bangladesh at a significant rate in comparison to other countries. The major focus of the study was to identify the relationship between fear of gender-based crime and women empowerment. To explore the fact the study followed the mixed methodological approach comprising with quantitative and qualitative methods and used secondary information from national and international sources. Corresponding global pictures the present study found that gender, age, complexion, social position, and ethnicity were more common factors of sexual assault and victimization in Bangladesh which lead to women become more fearful about crime victimization than men. Fear of gender-based crime traumatizes women which leads to withdrawal of their non-essential everyday works and some time from the essential works based on their social position, financial status, and social honor in the society. The increasing crime rate also increases the propensity to fear of criminal victimization, traumatization, and feeling of helplessness which make them vulnerable. The patriarchal culture and practices in Bangladesh based on religious culture and established social norms women always feel defenseless therefore they withdraw themselves from various social activities and own interest. Women who have already victimized feel more fear and become traumatized, and who do not victimize yet but know the severity of victimization from the media and others’ have the feeling of fear of crime. Women who find themselves as weak bonding and low networks with their neighbors and living for a short duration have a feeling of more fear and avoid visiting a certain place in a certain time and avoid some social activities. The study found the young women have more possibilities to become victimized through the feeling of fear of crime is higher among elderly women than young. Though women feel fear of all kinds of crime but usually all aged women are more fearful of sexual assault and rape than other violent crimes. Therefore, elderly women and another person in the family does not allow younger girls to go and involve outside activities to secure their family status. On the other hand, fear of crime in public transport is more common to all aged women at a higher level and sometimes they compromise their freedom, independence, financial opportunities, the job only to avoid the perceived threat, and save their social and cultural honor. The study also explores that fear of crime does not always depend on crime rate but the crime news, the severity of the crime, delay justice, the ineffectiveness of police, bail of criminals, corruption and political favoritism, etc. Finally, the study shows that the fear of gender-based crime and violence is working as a potential barrier to ensuring women's empowerment in Bangladesh.

Keywords: compromise personal freedom, fear of crime, fear of gender-based crime, fear of violent crime victimization, rape, sexual assaults, withdrawal from regular activities, women empowerment

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Pratishtha Singh

Abstract:

Gender-based violence (GBV) or gendered violence refers to violence inflicted on a person because of their gender. Majority of men who perpetrate gender-based violence, first do so during their teenage years. Further, the first sexual experience of most girls is coerced. In order to reduce the widespread occurrence of GBV, it is vital to intervene and reach people, especially boys, when their attitudes and beliefs about sexuality and gender are developing. This study aims to understand GBV through an adolescent lens, focusing on their knowledge, attitudes and experiences regarding gendered abuse. This is a cross-sectional, qualitative study. The respondents are Delhi based students in grades 11th and 12th, recruited via snowball sampling. Sixteen in-depth, telephonic interviews were carried out in the month of April, 2020. The data was transcribed verbatim into MS Word and qualitative coding was undertaken in Atlas.ti 8. Twelve out of sixteen respondents admitted experiencing sexual GBV. Out of these, a little more than half of the victims reported it to somebody. Thematic analysis revealed key themes of: (i) Introduction and reinforcement of a patriarchal structure (ii) Violence in teen dating (iii) Acceptability and normalization of violence and (iv) Justice System. Findings reflect a process wherein GBV becomes an intricate part of adolescents’ lives. Participants showed a moderately well-informed understanding of gendered abuse whereas attitudes reflected a complex combination of internalized patriarchy and a desire to bring positive societal reform. The results of this study highlight a need for health promoting, gender-equitable interventions.

Keywords: adolescents, gender, health, violence

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Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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