Search results for: Network Time Protocol

Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: willingness to pay, contingent valuation, time value, city toll

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Authors: Sara Herrero Jaén, José María Santamaría García, María Lourdes Jiménez Rodríguez, Jorge Luis Gómez González, Adriana Cercas Duque, Alexandra González Aguna

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Background: Health concept has evolved throughout history. The health level is determined by the own individual perception. It is a dynamic process over time so that you can see variations from one moment to the next. In this way, knowing the health of the patients you care for, will facilitate decision making in the treatment of care. Objective: To design a technological tool that calculates the people health level in a sequential way over time. Material and Methods: Deductive methodology through text analysis, extraction and logical knowledge formalization and education with expert group. Studying time: September 2015- actually. Results: A computational tool for the use of health personnel has been designed. It has 11 variables. Each variable can be given a value from 1 to 5, with 1 being the minimum value and 5 being the maximum value. By adding the result of the 11 variables we obtain a magnitude in a certain time, the health level of the person. The health calculator allows to represent people health level at a time, establishing temporal cuts being useful to determine the evolution of the individual over time. Conclusion: The Information and Communication Technologies (ICT) allow training and help in various disciplinary areas. It is important to highlight their relevance in the field of health. Based on the health formalization, care acts can be directed towards some of the propositional elements of the concept above. The care acts will modify the people health level. The health calculator allows the prioritization and prediction of different strategies of health care in hospital units.

Keywords: calculator, care, eHealth, health

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Authors: Mohamed T. Faheem Saidahmed, Ahmed M. Attiya Ibrahim, Basma GH. Elkilany

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This paper discusses the application of Time Delay Control (TDC) compensation technique in the juice extraction process in a sugar mill. The objective is to improve the control performance of the process and increase extraction efficiency. The paper presents the mathematical model of the juice extraction process and the design of the TDC compensation controller. Simulation results show that the TDC compensation technique can effectively suppress the time delay effect in the process and improve control performance. The extraction efficiency is also significantly increased with the application of the TDC compensation technique. The proposed approach provides a practical solution for improving the juice extraction process in sugar mills using MATLAB Processes.

Keywords: time delay control (TDC), exact and unique state space model, delay compensation, Smith predictor.

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Authors: Yue Yang, Qiang Wu, Xingyu Gao

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"Organized research units" have always been an important part of academia. According to the type of organization, there are public research units, university research units, and corporate research units. Existing research has explored the research unit in some depth from several perspectives. However, there is a research gap on the closer interaction between the three from a network perspective and the impact of this interaction on their performance as well as originality. Cliques are a special kind of structure under the concept of cohesive subgroups in the field of social networks, representing particularly tightly knit teams in a network. This study develops the concepts of the diversity of clique types and the diversity of clique geography based on cliques, starting from the diversity of collaborative activities characterized by them. Taking research units as subjects and assigning values to their power in cliques based on occupational age, we explore the impact of clique diversity and clique power on their performance as well as originality and the moderating role of clique relationship strength and structural holes in them. By collecting 9094 articles published in the field of quantum communication at WoSCC over the 15 years 2007-2021, we processed them to construct annual collaborative networks between a total of 533 research units and measured the network characteristic variables using Ucinet. It was found that the type and geographic diversity of cliques promoted the performance and originality of the research units, and the strength of clique relationships positively moderated the positive effect of the diversity of clique types on performance and negatively affected the promotional relationship between the geographic diversity of cliques and performance. It also negatively affected the positive effects of clique-type diversity and clique-geography diversity on originality. Structural holes positively moderated the facilitating effect of both types of factional diversity on performance and originality. Clique power promoted the performance of the research unit, but unfavorably affected its performance on novelty. Faction relationship strength facilitated the relationship between faction rights and performance and showed negative insignificance for clique power and originality. Structural holes positively moderated the effect of clique power on performance and originality.

Keywords: research unit, social networks, clique structure, clique power, diversity

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Authors: Abdulameer K. Hussain

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When dealing with a cryptographic system we note that there are many activities performed by parties of this cryptographic system and the most prominent of these activities is the process of agreement between the parties involved in the cryptographic system on how to deal and perform the cryptographic system tasks to be more secure, more confident and reliable. The most common agreement among parties is a key agreement and other types of agreements. Despite the fact that there is an attempt from some quarters to find other effective agreement methods but these methods are limited to the traditional agreements. This paper presents different parameters to perform more effectively the task of the agreement, including the key alternative, the agreement on the encryption method used and the agreement to prevent the denial of the services. To manage and achieve these goals, this method proposes the existence of an control and monitoring entity to manage these agreements by collecting different statistical information of the opinions of the authorized parties in the cryptographic system. These statistics help this entity to take the proper decision about the agreement factors. This entity is called Agreement Manager (AM).

Keywords: agreement parameters, key agreement, key exchange, security management

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Authors: Manasi Roy, Raju Mondal

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During last two decades the synthesis and design of MOFs or novel coordination polymers (CPs) has flourished as an emerging area of research due to their role as functional materials. Accordingly, ten new cobalt-based MOFs have been synthesized using a simple bispyrazole ligand, 4,4′-methylene-bispyrazole (H2MBP), and isophthalic acid (H2IPA) and its four 5-substituted derivatives R-H2IPA (R = COOH, OH, tBu, NH2). The major aim of this study was to validate the mutual influence of temperature and substitutions on the final structural self-assembly. Five different isophthalic acid derivatives were used to study the influence of substituents while each reaction was carried out at two different temperatures to assess the temperature effect. A clear correlation was observed between the reaction temperature and the coordination number of the cobalt atoms which consequently changes the self assembly pattern. Another fact that the periodical change in coordination number did bring about some systematic changes in the structural network via secondary building unit selectivity. With the presence of a tunable cavity inside the network, and unsaturated metal centers, MOFs show highly encouraging photocatalytic degradation of toxic dye with a potential application in waste water purification. Another fascinating aspect of this work is the construction of magnetic coordination polymers with the occurrence of a not-so-common MCE behavior of cobalt-based MOF.

Keywords: MOFs, temperature effect, MCE, dye degradation

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Authors: Manjit Singh

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Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

Procedia PDF Downloads 254

Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

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Authors: Aodai Abdul-Illah Ismail

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Even though the dramatic progress that has been made in traffic safety, but still millions of peoples get killed or injured as a result of traffic crashes, besides the huge amount of economic losses due to these crashes. So traffic safety continues to be one of the most important serious issues worldwide, and it affects everyone who uses the road network system, whether you drive, walk, cycle, or push a pram. One of the most important sides that offers promise for further progress in relation to traffic safety is related to risky groups (special population groups) who may have higher potential to be involved in accidents. Traffic safety needs of risky groups are different from each other and also from the average population. Due to the various limitations between these special groups from each other and from the average population, it is not possible to address all the issues –at the same time- raising the importance ranking among the other safety issues. This paper explains a procedure used to identify the most critical traffic safety issues of five risky groups, which include younger, older and female drivers, people with disabilities and school aged children. Multi criteria used in selecting the critical issues because the single criteria is not sufficient. Highway safety professionals were surveyed to obtain the ranking of importance among the risky groups and then to develop the final ranking among issues by applying weight for each of the criteria.

Keywords: traffic safety, risky groups, old drivers, young drivers

Procedia PDF Downloads 332

Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: M. S. Mahmoud

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This study was conducted to evaluate the manganese removal from aqueous solution using Banana peels activated carbon (BPAC). Batch experiments have been carried out to determine the influence of parameters such as pH, biosorbent dose, initial metal ion concentrations and contact times on the biosorption process. From these investigations, a significant increase in percentage removal of manganese 97.4 % is observed at pH value 5.0, biosorbent dose 0.8 g, initial concentration 20 ppm, temperature 25 ± 2 °C, stirring rate 200 rpm and contact time 2 h. The equilibrium concentration and the adsorption capacity at equilibrium of the experimental results were fitted to the Langmuir and Freundlich isotherm models; the Langmuir isotherm was found to well represent the measured adsorption data implying BPAC had heterogeneous surface. A raw groundwater samples were collected from Baharmos groundwater treatment plant network at Embaba and Manshiet Elkanater City/District-Giza, Egypt, for treatment at the best conditions that reached at first phase by BPAC. The treatment with BPAC could reduce iron and manganese value of raw groundwater by 91.4 % and 97.1 %, respectively and the effect of the treatment process on the microbiological properties of groundwater sample showed decrease of total bacterial count either at 22°C or at 37°C to 85.7 % and 82.4 %, respectively. Also, BPAC was characterized using SEM and FTIR spectroscopy.

Keywords: biosorption, banana peels, isothermal models, manganese

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Apu Kumar Saha, Mrinmoy Majumder

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The increase in the concentration of Green House gases all over the World has induced global warming phenomena whereby the average temperature of the world has aggravated to impact the pattern of climate in different regions. The frequency of extreme event has increased, early onset of season and change in an average amount of rainfall all are engrossing the conclusion that normal pattern of climate is changing. Sophisticated and complex models are prepared to estimate the future situation of the climate in different zones of the Earth. As hydro-energy is directly related to climatic parameters like rainfall and evaporation such energy resources will have to sustain the onset of the climatic abnormalities. The present investigation has tried to assess the impact of climatic abnormalities upon hydropower potential of different regions of the World. In this regard multi-criteria, decision making, and the neural network is used to predict the impact of the change cognitively by an index. The results from the study show that hydro-energy potential of Asian region is mostly vulnerable with respect to other regions of the world. The model results also encourage further application of the index to analyze the impact of climate change on the potential of hydro-energy.

Keywords: hydro-energy potential, neural networks, multi criteria decision analysis, environmental and ecological engineering

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Authors: Hoi-Lam Ma, Sai-Ho Chung

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In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Abdullah Arafat, Ali Al-Farhan, Amir Omair

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Objectives: To review and assess the effectiveness of the implemented modified five-levels triage and acuity scale triage system in AL-Yarmook Urgent Care Center (UCC), King Abdulaziz Residential city, Riyadh, Saudi Arabia. Method: The applied study design was an observational cross sectional design. A data collection sheet was designed and distributed to triage nurses; the data collection was done during triage process and was directly observed by the co-investigator. Triage system was reviewed by measuring three time intervals as quality indicators: time before triage (TBT), time before being seen by physician (TBP) and total length of stay (TLS) taking in consideration timing of presentation and level of triage. Results: During the study period, a total of 187 patients were included in our study. 118 visits were at weekdays and 68 visits at weekends. Overall, 173 patients (92.5%) were seen by the physician in timely manner according to triage guidelines while 14 patients (7.5%) were not seen at appropriate time.Overall, The mean time before seen the triage nurse (TBT) was 5.36 minutes, the mean time to be seen by physician (TBP) was 22.6 minutes and the mean length of stay (TLS) was 59 minutes. The data didn’t showed significant increase in TBT, TBP, and number of patients not seen at the proper time, referral rate and admission rate during weekend. Conclusion: The CTAS is adaptable to countries beyond Canada and worked properly. The applied CTAS triage system in Al-Yarmook UCC is considered to be effective and well applied. Overall, urgent cases have been seen by physician in timely manner according to triage system and there was no delay in the management of urgent cases.

Keywords: CTAS, emergency, Saudi Arabia, triage, urgent care

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Authors: Yadong Liu

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The experimental study on reduction carbonization of coke containing iron respectively with the particle size of <0.3mm, 0.3-0.6mm and 0.6-0.9mm and synthetic sea sand ore smelting reduction titanium-bearing slag as material were studied under the conditions of holding 6h at most at 1500℃. The effects of coke containing iron particle size and heat preservation time on the formation of TiC and the size of TiC crystal were studied by XRD, SEM and EDS. The results show that it is not good for the formation, concentration and growth of TiC crystal when the particle size of coke containing iron is too small or too large. The suitable particle size is 0.3~0.6mm. The heat preservation time of 2h basically ensures that all the component TiO2 in the slag are reduced and carbonized and converted to TiC. The size of TiC crystal will increase with the prolongation of heat preservation time. The thickness of the TiC layer can reach 20μm when the heat preservation time is 6h.

Keywords: coke containing iron, formation and concentration and growth of TiC, reduction and carbonization, titanium-bearing slag

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Authors: Aamna Zafar

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Through linguistic and cultural analysis, this study seeks to trace the development of the English and Urdu languages. Along with examining how the vocabulary and syntax of English and Urdu have evolved over time and the linguistic trends that may be seen in these changes, this study will also look at the historical and cultural influences that have shaped the languages throughout time. The study will also look at how English and Urdu have changed over time, both in terms of language use and communication inside each other's cultures and globally. We'll research how these changes affect social relations and cultural identity, as well as how they might affect the future of these languages.

Keywords: linguistic and cultural analysis, historical factors, cultural factors, vocabulary, syntax, significance

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Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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Authors: M. Fernanda Salgado, Alfonso Tierra, David S. Sandoval, Wilbert G. Aguilar

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Public transportation buses usually vary the speed depending on the places with the number of passengers. They require having efficient travel planning, a plan that will help them choose the fast route. Initially, an estimation tool is necessary to determine the travel time of each route, clearly establishing the possibilities. In this work, we give a practical solution that makes use of a concept that defines as areas of commercial incidence. These areas are based on the hypothesis that in the commercial places there is a greater flow of people and therefore the buses remain more time in the stops. The areas have one or more segments of routes, which have an incidence factor that allows to estimate the times. In addition, initial results are presented that verify the hypotheses and that promise adequately the travel times. In a future work, we take this approach to make an efficient travel planning system.

Keywords: commercial incidence, planning, public transport, speed travel, travel time

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Authors: Mohammad Younus Bhat

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The quaternion offset linear canonical transform (QOLCT), which isa time-shifted and frequency-modulated version of the quaternion linear canonical transform (QLCT), provides a more general framework of most existing signal processing tools. For the generalized QOLCT, the classical Heisenberg’s and Lieb’s uncertainty principles have been studied recently. In this paper, we first define the short-time quaternion offset linear canonical transform (ST-QOLCT) and drive its relationship with the quaternion Fourier transform (QFT). The crux of the paper lies in the generalization of several well-known uncertainty principles for the ST-QOLCT, including Donoho-Stark’s uncertainty principle, Hardy’s uncertainty principle, Beurling’s uncertainty principle, and the logarithmic uncertainty principle.

Keywords: Quaternion Fourier transform, Quaternion offset linear canonical transform, short-time quaternion offset linear canonical transform, uncertainty principle

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Authors: Cory A. Bennett

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Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.

Keywords: discourse, reasoning, secondary mathematics, teacher development

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Authors: Fru Vitalis Akuma, Jenna Koenen

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The science education community is increasingly calling for learning experiences that mirror the work of scientists. Although inquiry-based science education is aligned with these calls, the implementation of this strategy is a complex and daunting task for many teachers. Thus, policymakers and researchers have noted the need for continued teacher Professional Development (PD) in the enactment of inquiry-based science education, coupled with effective ways of reaching the goals of teacher PD. This is a complex problem for which educational design research is suitable. The purpose at this stage of our design research is to develop a generic PD framework that is valid as the blueprint of a PD program for supporting science teachers in relation to inquiry-based curriculum units. The seven components of the framework are the goal, learning theory, strategy, phases, support, motivation, and an instructional model. Based on a systematic review of the literature on effective (science) teacher PD, coupled with developer screening, we have generated a design principle per component of the PD framework. For example, as per the associated design principle, the goal of the framework is to provide science teachers with experiences in authentic inquiry, coupled with enhancing their competencies linked to the adoption, customization and design; then the classroom implementation and the revision of inquiry-based curriculum units. The seven design principles have allowed us to synthesize the PD framework, which, coupled with the design principles, are the preliminary outcomes of the current research. We are in the process of evaluating the content and construct validity of the framework, based on nine one-on-one interviews with experts in inquiry-based classroom and teacher learning. To this end, we have developed an interview protocol with the input of eight such experts in South Africa and Germany. Using the protocol, the expert appraisal of the PD framework will involve three experts from Germany, South Africa, and Cameroon, respectively. These countries, where we originate and/or work, provide a variety of inquiry-based science education contexts, making the countries suitable in the evaluation of the generic PD framework. Based on the evaluation, we will revise the framework and its seven design principles to arrive at the final outcomes of the current research. While the final content and construct a valid version of the framework will serve as an example of the needed ways through which effective inquiry-based science teacher PD may be achieved, the final design principles will be useful to researchers when transforming the framework for use in any specific educational context. For example, in our further research, we will transform the framework to one that is practical and effective in supporting inquiry-based practical work in resource-constrained physical sciences classrooms in South Africa. Researchers in other educational contexts may similarly consider the final framework and design principles in their work. Thus, our final outcomes will inform practice and research around the support of teachers to increase the incorporation of learning experiences that mirror the work of scientists in a worldwide manner.

Keywords: design principles, educational design research, evaluation, inquiry-based science education, professional development framework

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Authors: Nur Sofi Hidayah, Ratih Tri Purwatiningsih

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Learning is a process attempts person to obtain a new behavior changes as a whole, as a result of his own experience in the interaction with the environment. Learning involves our brain to think, while the ability of the brain to each student's performance is different. To obtain optimal learning results then need time to learn the exact hour that the brain's performance is not too heavy. Referring to the learning system in Finland which apply 45 minutes to learn and a 15-minute break is expected to be the brain work better, with the rest of the brain, the brain will be more focused and lessons can be absorbed well. It can be concluded that learning in this way students learn with brain always fresh and the best possible use of the time, but it can make students not saturated in a lesson.

Keywords: learning, working hours brain, time efficient learning, working hours in the brain receive stimulus.

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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Authors: A. Yawootti, P. Intra, P. Sardyoung, P. Phoosomma, R. Puttipattanasak, S. Leeragreephol, N. Tippayawong

Abstract:

The aim of this work is to design, develop and test the low-cost implementation of a particulate air pollution sensor system for continuous monitoring of outdoors and indoors particulate air pollution at a lower cost than existing instruments. In this study, measuring electrostatic charge of particles technique via high efficiency particulate-free air filter was carried out. The developed detector consists of a PM10 impactor, a particle charger, a Faraday cup electrometer, a flow meter and controller, a vacuum pump, a DC high voltage power supply and a data processing and control unit. It was reported that the developed detector was capable of measuring mass concentration of particulate ranging from 0 to 500 µg/m3 corresponding to number concentration of particulate ranging from 106 to 1012 particles/m3 with measurement time less than 1 sec. The measurement data of the sensor connects to the internet through a GSM connection to a public cellular network. In this development, the apparatus was applied the energy by a 12 V, 7 A internal battery for continuous measurement of about 20 hours. Finally, the developed apparatus was found to be close agreement with the import standard instrument, portable and benefit for air pollution and particulate matter measurements.

Keywords: particulate, air pollution, wireless communication, sensor

Procedia PDF Downloads 345

Authors: Gabriela Kloudova, Miloslav Stehlik, Peter Sos

Abstract:

The quality of sleep can affect combat performance where the vigilance, accuracy and reaction time are a decisive factor. In the present study, airborne and special units are measured on duty using actigraphy fingerprint scoring algorithm and QEEG (quantitative EEG). Actigraphic variables of interest will be: mean nightly sleep duration, mean napping duration, mean 24-h sleep duration, mean sleep latency, mean sleep maintenance efficiency, mean sleep fragmentation index, mean sleep onset time, mean sleep offset time and mean midpoint time. In an attempt to determine the individual somnotype of each subject, the data like sleep pattern, chronotype (morning and evening lateness), biological need for sleep (daytime and anytime sleepability) and trototype (daytime and anytime wakeability) will be extracted. Subsequently, a series of recommendations will be included in the training plan based on daily routine, timing of the day and night activities, duration of sleep and the number of sleeping blocks in a defined time. The aim of these modifications in the training plan is to reduce day-time sleepiness, improve vigilance, attention, accuracy, speed of the conducted tasks and to optimize energy supplies. Regular improvement of the training supposed to have long-term neurobiological consequences including neuronal activity changes measured by QEEG. Subsequently, that should enhance cognitive functioning in subjects assessed by the digital cognitive test batteries and improve their overall performance.

Keywords: sleep quality, combat performance, actigraph, somnotype

Procedia PDF Downloads 144

Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

Procedia PDF Downloads 69

Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

Abstract:

With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

Procedia PDF Downloads 102

Authors: Sukhleen Kaur

Abstract:

In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

Procedia PDF Downloads 397