Search results for: elliptic curve digital signature algorithm

Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

Procedia PDF Downloads 199

Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

Procedia PDF Downloads 336

Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowd-sourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowd-sourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is -to our best knowledge- the first to develop safety performance functions using crowd-sourced data by adopting a negative binomial structure model and the Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

Procedia PDF Downloads 52

Authors: Farzaneh Sarbandi Farahani

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Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

Procedia PDF Downloads 90

Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 353

Authors: Bonchan Koo, Junhee Han, Dohyung Lee

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The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

Procedia PDF Downloads 467

Authors: Noha El-Gohary, Thanaa El-Shater, A. A. Mahfouz, M. M. Sakr

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Searching for high power conversion efficiency and long lifetime are important goals when designing a power supply subsystem for satellite applications. To fulfill these goals, this paper presents a power supply subsystem for small satellites in which flywheel energy storage system is used as a secondary power source instead of chemical battery. In this paper, the model of flywheel energy storage system is introduced; a DC bus regulation control algorithm for charging and discharging of flywheel based on space vector pulse width modulation technique and motor current control is also introduced. Simulation results showed the operation of the flywheel for charging and discharging mode during illumination and shadowed period. The advantages of the proposed system are confirmed by the simulation results of the power supply system.

Keywords: small-satellites, flywheel energy storage system, space vector pulse width modulation, power conversion

Procedia PDF Downloads 400

Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

Procedia PDF Downloads 459

Authors: Shang-Hua Wu, Rong-Chi Chang, Horng–Twu Liaw

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Nowadays, competencies of e-learning project personnel are very important in assisting them in offering courses, serving students in an effective way, leveraging advantages, strengthen their relationships with potential students, etc. among e-learning platforms, MOOCs has recently attracted increasing focuses in distance education since it can be conducted for a large numbers of virtual learners. Nonetheless, since MOOCs is a relatively new e-learning platform, top concerns have been paid to what competencies are important for e-learning personnel to consider. Taking this need, this research aimed to carry out an in-depth exploration of competency requirements of MOOCs (e-learning) project personnel in Taiwan vocational schools. Data were collected through thorough literature reviews and discussions and competency analysis was carried out using Delphi technique questionnaires. The results show that that MOOCs (e-learning) project personnel’ professional competency lie in three main dimensions, among which ‘demand analysis competency’ (i.e., containing 10 major competences and 48 subordinate capabilities) is the most important competency, followed by ‘project management competency’ (i.e., comprising 6 major competences and 31 secondary capabilities), and finally ‘digital content production competency’ (i.e., including 12 major competences and 79 secondary capabilities). As such, in Taiwan context with different organizational scales and market sizes, the e-learning competency items and unique experience/ achievements throughout the promotion process obtained in this research will provide useful references for academic institutions in promoting e-learning.

Keywords: competency analysis, Delphi technique questionnaire, e-learning, massive open online courses

Procedia PDF Downloads 285

Authors: Achmad Muchadam Fahham, Sony Hendra Permana

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Millennial Muslims are a generation of young people between 20-30 years. They will play an important role in various aspects of life for the next 10 to 20 years. In Indonesia, the population of this generation is quite large and in the next ten to twenty years they will occupy strategic position in various fields of social, economic and political life. One of the characteristics of the millenials generation are always connected to the internet and independence to learn anything from the internet. In terms of religion, the majority of millennial are Muslim. In digital era, the generation of millenial Muslim is vulnerable to the influence of radical Islamic thinking because of their easy access to that thought on social media, new media, and the books they read. This study seeks to examine the religious views of millennial Muslim women in four main focuses, namely religious identity, religious leaders, the role of the state on religious issues, and religious radicalism. This study was conducted with a qualitative approach, the data collection was carried out by the interview method. The study was conducted in Jakarta, mainly in religious study groups located in several mosques and shopping center in Jakarta. This study is expected to portray the religious views of millennial Muslim women, especially their commitment to Islamic identity, their views on the authority of religious leaders, the role of the state in various religious problems, and religious radicalism.

Keywords: millenial Muslims, radicalism, muslim mowen, religious identity

Procedia PDF Downloads 152

Authors: Shima Nabinejad, Holger Schüttrumpf

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Farmers who are living in flood-prone areas such as coasts are exposed to storm surges increased due to climate change. Crop cultivation is the most important economic activity of farmers, and in the time of flooding, agricultural lands are subject to inundation. Additionally, overflow saline water causes more severe damage outcomes than riverine flooding. Agricultural crops are more vulnerable to salinity than other land uses for which the economic damages may continue for a number of years even after flooding and affect farmers’ decision-making for the following year. Therefore, it is essential to assess what extent the agricultural areas are flooded and how much the associated flood damage to each individual farmer is. To address these questions, we integrated farmers’ decision-making at farm-scale with flood risk management. The integrated model includes identification of hazard scenarios, failure analysis of structural measures, derivation of hydraulic parameters for the inundated areas and analysis of the economic damages experienced by each farmer. The present study has two aims; firstly, it attempts to investigate the flooded cropland and potential crop damages for the whole area. Secondly, it compares them among farmers’ field for three flood scenarios, which differ in breach locations of the flood protection structure. To achieve its goal, the spatial distribution of fields and cultivated crops of farmers were fed into the flood risk model, and a 100-year storm surge hydrograph was selected as the flood event. The study area was Pellworm Island that is located in the German Wadden Sea National Park and surrounded by North Sea. Due to high salt content in seawater of North Sea, crops cultivated in the agricultural areas of Pellworm Island are 100% destroyed by storm surges which were taken into account in developing of depth-damage curve for analysis of consequences. As a result, inundated croplands and economic damages to crops were estimated in the whole Island which was further compared for six selected farmers under three flood scenarios. The results demonstrate the significance and the flexibility of the proposed model in flood risk assessment of flood-prone areas by integrating flood risk management and decision-making.

Keywords: crop damages, flood risk analysis, individual farmer, inundated cropland, Pellworm Island, storm surges

Procedia PDF Downloads 257

Authors: Masauso Moses Phiri

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Frequent glucose monitoring is essential to the management of diabetes. Plasmonic enzyme-based glucose biosensors have the advantages of greater specificity, simplicity and rapidity. The aim of this study was to develop a rapid plasmonic colorimetric glucose biosensor based on biocatalytic enlargement of AuNS guided by GOx. Gold nanoparticles of 18 nm in diameter were synthesized using the citrate method. Using these as seeds, a modified seeded method for the synthesis of monodispersed gold nanostars was followed. Both the spherical and star-shaped nanoparticles were characterized using ultra-violet visible spectroscopy, agarose gel electrophoresis, dynamic light scattering, high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. The feasibility of a plasmonic colorimetric assay through growth of AuNS by silver coating in the presence of hydrogen peroxide was investigated by several control and optimization experiments. Conditions for excellent sensing such as the concentration of the detection solution in the presence of 20 µL AuNS, 10 mM of 2-(N-morpholino) ethanesulfonic acid (MES), ammonia and hydrogen peroxide were optimized. Using the optimized conditions, the glucose assay was developed by adding 5mM of GOx to the solution and varying concentrations of glucose to it. Kinetic readings, as well as color changes, were observed. The results showed that the absorbance values of the AuNS were blue shifting and increasing as the concentration of glucose was elevated. Control experiments indicated no growth of AuNS in the absence of GOx, glucose or molecular O₂. Increased glucose concentration led to an enhanced growth of AuNS. The detection of glucose was also done by naked-eye. The color development was near complete in ± 10 minutes. The kinetic readings which were monitored at 450 and 560 nm showed that the assay could discriminate between different concentrations of glucose by ± 50 seconds and near complete at ± 120 seconds. A calibration curve for the qualitative measurement of glucose was derived. The magnitude of wavelength shifts and absorbance values increased concomitantly with glucose concentrations until 90 µg/mL. Beyond that, it leveled off. The lowest amount of glucose that could produce a blue shift in the localized surface plasmon resonance (LSPR) absorption maxima was found to be 10 – 90 µg/mL. The limit of detection was 0.12 µg/mL. This enabled the construction of a direct sensitivity plasmonic colorimetric detection of glucose using AuNS that was rapid, sensitive and cost-effective with naked-eye detection. It has great potential for transfer of technology for point-of-care devices.

Keywords: colorimetric, gold nanostars, glucose, glucose oxidase, plasmonic

Procedia PDF Downloads 152

Authors: Nguyen Lan, Le Tan Kien, Nguyen Pham Gia Bao

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The cable-stayed bridge belongs to the combined system, in which the cables is a major strutual element. Cable-stayed bridges with large spans are often arranged with structural health monitoring systems to collect data for bridge health diagnosis. Cables tension monitoring is a structural monitoring content. It is common to measure cable tension by a direct force sensor or cable vibration accelerometer sensor, thereby inferring the indirect cable tension through the cable vibration frequency. To translate cable-stayed vibration acceleration data to real-time tension requires some necessary calculations and programming. This paper introduces the algorithm, labview program that converts cable-stayed vibration acceleration data to real-time tension. The research results are applied to the monitoring system of Tran Thi Ly cable-stayed bridge and Song Hieu cable-stayed bridge in Vietnam.

Keywords: cable-stayed bridge, cable fore, structural heath monitoring (SHM), fast fourie transformed (FFT), real time, vibrations

Procedia PDF Downloads 71

Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

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By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

Procedia PDF Downloads 397

Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

Procedia PDF Downloads 103

Authors: Seolah Lee, Yoohyk Jang, Soyoung Lee, Kon Chu, Sang Kun Lee

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Objective: The International League Against Epilepsy (ILAE) currently suggests a topiramate serum level range of 5-20 mg/L. However, numerous institutions have observed substantial drug response at lower levels. This study aims to investigate the correlation between topiramate serum levels, drug responsiveness, and adverse events to establish a more accurate and tailored therapeutic range. Methods: We retrospectively analyzed topiramate serum samples collected between January 2017 and January 2022 at Seoul National University Hospital. Clinical data, including serum levels, antiseizure regimens, seizure frequency, and adverse events, were collected. Patient responses were categorized as "insufficient" (reduction in seizure frequency <50%) or "sufficient" (reduction ≥ 50%). Within the "sufficient" group, further subdivisions included seizure-free and tolerable seizure subgroups. A population pharmacokinetic model estimated serum levels from spot measurements. ROC curve analysis determined the optimal serum level cut-off. Results: A total of 389 epilepsy patients, with 555 samples, were reviewed, having a mean dose of 178.4±117.9 mg/day and a serum level of 3.9±2.8 mg/L. Out of the samples, only 5.6% (n=31) exhibited insufficient response, with a mean serum level of 3.6±2.5 mg/L. In contrast, 94.4% (n=524) of samples demonstrated sufficient response, with a mean serum level of 4.0±2.8 mg/L. This difference was not statistically significant (p = 0.45). Among the 78 reported adverse events, logistic regression analysis identified a significant association between ataxia and serum concentration (p = 0.04), with an optimal cut-off value of 6.5 mg/L. In the subgroup of patients receiving monotherapy, those in the tolerable seizure group exhibited a significantly higher serum level compared to the seizure-free group (4.8±2.0 mg/L vs 3.4±2.3 mg/L, p < 0.01). Notably, patients in the tolerable seizure group displayed a higher likelihood of progressing into drug-resistant epilepsy during follow-up visits compared to the seizure-free group. Significance: This study proposed an optimal therapeutic concentration for topiramate based on the patient's responsiveness to the drug and the incidence of adverse effects. We employed a population pharmacokinetic model and analyzed topiramate serum levels to recommend a serum level below 6.5 mg/L to mitigate the risk of ataxia-related side effects. Our findings also indicated that topiramate dose elevation is unnecessary for suboptimal responders, as the drug's effectiveness plateaus at minimal doses.

Keywords: topiramate, therapeutic range, low dos, antiseizure effect

Procedia PDF Downloads 55

Authors: Cinna Soltanpur, Mohammad Ghamari, Behzad Momahed Heravi, Fatemeh Zare

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Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.

Keywords: concatenated coding, low–density parity–check codes, array code, error floors

Procedia PDF Downloads 356

Authors: Leonie Laskowitz

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A self-confident appearance is a basic prerequisite for success in the world of work 4.0. Within a few seconds, people convey a first impression that usually lasts. Artificial intelligence is making it increasingly important how our virtual selves appear and communicate (nonverbally) in digital worlds such as the metaverse. In addition to the modified creation of an avatar, the field of photogrammetry is developing fast, creating exact likenesses of ourselves in virtual environments. Given the importance of self-representation in virtual space for future collaborations, it is important to investigate the impact of phenotype in virtual worlds and how an avatar type can profitably be used situationally. We analyzed the effect of self-similar versus desirable self-presentation as an avatar on one's self-awareness, considering various theoretical constructs in the area of self-awareness and stress stimuli. The avatars were arbitrarily created on the one hand and scanned on the other hand with the help of a lidar sensor, the state-of-the-art photogrammetry method. All subjects were exposed to the established Trier Social Stress Test. The results showed that especially insecure people prefer to create rather than be scanned when confronted with a stressful work situation. (1) If they are in a casual work environment and a relaxed situation, they prefer a 3D photorealistic avatar that reflects them in detail. (2) Confident people will give their avatar their true appearance in any situation, while insecure people would only do so for honesty and authenticity. (3) Thus, the choice of avatar type has considerable impact on self-confidence in different situations.

Keywords: avatar, virtual identity, self-presentation, metaverse, virtual reality, self-awareness

Procedia PDF Downloads 148

Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

Procedia PDF Downloads 342

Authors: Karen C. Olufokunbi, Odetunji A. Odejobi

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The discourse of this paper is the examination of the generation, accumulation and growth of e-waste in a developing country. Images and other data about computer e-waste were collected using a digital camera, 290 copies of questionnaire and three structured interviews using Obafemi Awolowo University (OAU), Ile-Ife, Nigeria environment as a case study. The numerical data were analysed using R data analysis and process tool. Automata-based techniques and Petri net modeling tool were used to design and simulate a computational model for the recovery of saleable materials from e-waste. The R analysis showed that at a 95 percent confidence level, the computer equipment that will be disposed by 2020 will be 417 units. Compared to the 800 units in circulation in 2014, 50 percent of personal computer components will become e-waste. This indicates that personal computer components were in high demand due to their low costs and will be disposed more rapidly when replaced by new computer equipment Also, 57 percent of the respondents discarded their computer e-waste by throwing it into the garbage bin or by dumping it. The simulated model using Coloured Petri net modelling tool for the process showed that the e-waste dynamics is a forward sequential process in the form of a pipeline meaning that an e-waste recovery of saleable materials process occurs in identifiable discrete stages indicating that e-waste will continue to accumulate and grow in volume with time.

Keywords: Coloured Petri net, computational modelling, electronic waste, electronic waste process dynamics

Procedia PDF Downloads 166

Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

Procedia PDF Downloads 173

Authors: Lisa Naudine Parrock, Geoffrey Lautenbach

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The changes brought to society by the technological development in the Fourth Industrial Revolution are also reaching the sphere of education and the education system needs to respond. Students need skills such as communication, collaboration, creativity and critical thinking in order to be successful in the 21st Century, which could be developed through the meaningful use of technology. This study is theorized by the 21st Century Framework for Learning and examines the student perceptions of grade 10 and 11 English Home language learners on how the technology used in their English classroom contributes to the development of 21st Century skills. The researcher adopted a constructivist paradigm and presented findings based on a general qualitative method. The study found that students perceived the use of technology in the classroom positively contributed to their development of communication, collaboration, creativity and critical thinking. Students also perceived technology as contributing to their access to information, a positive classroom atmosphere, heightened engagement in learning and developing skills necessary for their future. In addition, this study highlighted certain pedagogical strategies and digital tools that support the development of 21st Century skills. The findings suggest that the meaningful integration of technology fosters the development of 21st Century skills in grade 10 and 11 learners.

Keywords: educational technology, 21st century skills, fourth industrial revolution, affordances of technology

Procedia PDF Downloads 134

Authors: M. Maatar, M. Mekadem, M. Medale, B. Hadjed, B. Imine

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In this paper, numerical simulations have been carried out to study the performances of a flapping wing used as an energy collector. Metamodeling and genetic algorithms are used to detect the optimal configuration, improving power coefficient and/or efficiency. Radial basis functions and genetic algorithms have been applied to solve this problem. Three optimization factors are controlled, namely dimensionless heave amplitude h₀, pitch amplitude θ₀ and flapping frequency f. ANSYS FLUENT software has been used to solve the principal equations at a Reynolds number of 1100, while the heave and pitch motion of a NACA0015 airfoil has been realized using a developed function (UDF). The results reveal an average power coefficient and efficiency of 0.78 and 0.338 with an inexpensive low-fidelity model and a total relative error of 4.1% versus the simulation. The performances of the simulated optimum RBF-NSGA-II have been improved by 1.2% compared with the validated model.

Keywords: numerical simulation, flapping wing, energy extraction, power coefficient, efficiency, RBF, NSGA-II

Procedia PDF Downloads 43

Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

Procedia PDF Downloads 132

Authors: Farid Gaci, Zoubir Nemouchi

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A numerical study of laminar and turbulent fluid flows in 90° bend of square section was carried out. Three-dimensional meshes, based on hexahedral cells, were generated. The QUICK scheme was employed to discretize the convective term in the transport equations. The SIMPLE algorithm was adopted to treat the velocity-pressure coupling. The flow structure obtained showed interesting features such as recirculation zones and counter-rotating pairs of vortices. The performance of three different turbulence models was evaluated: the standard k- ω model, the SST k-ω model and the Reynolds Stress Model (RSM). Overall, it was found that, the multi-equation model performed better than the two equation models. In fact, the existence of four pairs of counter rotating cells, in the straight duct upstream of the bend, were predicted by the RSM closure but not by the standard eddy viscosity model nor the SST k-ω model. The analysis of the results led to a better understanding of the induced three dimensional secondary flows and the behavior of the local pressure coefficient and the friction coefficient.

Keywords: curved duct, counter-rotating cells, secondary flow, laminar, turbulent

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Authors: Sima Shakoorjavan, Mahdieh Eskafi, Dawid Stawski, Somaye Akbari

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In this study, poly (amidoamine) dendritic material (PAMAM) and poly (acrylic acid) (PAA) as polycation and polyanion were deposited on surface charged polylactide (PLA) nonwoven to study the relationship of dye absorption capacity of layered-PLA with the number of deposited layers. To produce negatively charged-PLA, acrylic acid (AA) was grafted on the PLA surface (PLA-g-AA) through a chemical redox reaction with the strong oxidizing agent. Spectroscopy analysis, water contact measurement, and FTIR-ATR analysis confirm the successful grafting of AA on the PLA surface through the chemical redox reaction method. In detail, an increase in dye absorption percentage by 19% and immediate absorption of water droplets ensured hydrophilicity of PLA-g-AA surface; and the presence of new carbonyl bond at 1530 cm-¹ and a wide peak of hydroxyl between 3680-3130 cm-¹ confirm AA grafting. In addition, PLA as linear polyester can undergo aminolysis, which is the cleavage of ester bonds and replacement with amid bonds when exposed to an aminolysis agent. Therefore, to produce positively charged PLA, PAMAM as amine-terminated dendritic material was introduced to PLA molecular chains at different conditions; (1) at 60 C for 0.5, 1, 1.5, 2 hours of aminolysis and (2) at room temperature (RT) for 1, 2, 3, and 4 hours of aminolysis. Weight changes and spectrophotometer measurements showed a maximum in weight gain graph and K/S value curve indicating the highest PAMAM attachment at 60 C for 1 hour and RT for 2 hours which is considered as an optimum condition. Also, the emerging new peak around 1650 cm-1 corresponding to N-H bending vibration and double wide peak at around 3670-3170 cm-1 corresponding to N-H stretching vibration confirm PAMAM attachment in selected optimum condition. In the following, regarding the initial surface charge of grafted-PLA, lbl deposition was performed and started with PAA or PAMAM. FTIR-ATR results confirm chemical changes in samples due to deposition of the first layer (PAA or PAMAM). Generally, spectroscopy analysis indicated that an increase in layer number costed dye absorption capacity. It can be due to the partial deposition of a new layer on the previously deposited layer; therefore, the available PAMAM at the first layer is more than the third layer. In detail, in the case of layer-PLA starting lbl with negatively charged, having PAMAM as the first top layer (PLA-g-AA/PAMAM) showed the highest dye absorption of both cationic and anionic model dye.

Keywords: surface modification, layer-by-layer technique, dendritic materials, PAMAM, dye absorption capacity, PLA nonwoven

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Authors: Lidija Jevrić, Denis Kučević, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Milica Karadžić

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In the present study, the Hierarchical Cluster Analysis (HCA) was applied in order to determine the differences between the milk samples originating from a conventional dairy farm (CF) and an organic dairy farm (OF) in AP Vojvodina, Republic of Serbia. The clustering was based on the basis of the average values of saturated fatty acids (SFA) content and unsaturated fatty acids (UFA) content obtained for every season. Therefore, the HCA included the annual SFA and UFA content values. The clustering procedure was carried out on the basis of Euclidean distances and Single linkage algorithm. The obtained dendrograms indicated that the clustering of UFA in OF was much more uniform compared to clustering of UFA in CF. In OF, spring stands out from the other months of the year. The same case can be noticed for CF, where winter is separated from the other months. The results could be expected because the composition of fatty acids content is greatly influenced by the season and nutrition of dairy cows during the year.

Keywords: chemometrics, clustering, food engineering, milk quality

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

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Authors: Cam-Duc Au, Philippe Krahnhof, Lars Klingenberger

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German banks are experiencing harsh times due to rising costs and declining profits. On the one hand, acquisition costs for new customers are increasing because of the rise of innovative FinTechs, which entered the market with one specific goal: disrupting the whole financial services industry by occupying parts of the value chain. On the other hand, the COVID-19 pandemic, as well as an overall low level of interest rates, cause the traditional source of bank income to still drain. Consequently, traditional banks must rethink their strategies or their identity, so to speak, because they go beyond their traditional offering of products and services. Having said that, banks may create new sources of income to stabilize their economic situation and replenish profits. The given paper aims to research the opportunities of establishing an ecosystem model. In doing so, the paper contributes to the current literature debate and provide reference points for traditional banks to start. Firstly, a systematic literature review introduces a selection of research works the author regards as significant. In the following step, quantitative data from an online survey with bank clients are analysed by means of descriptive statistics to show the perspective of Germans with regards to an ecosystem offering. The final research findings indicate that the surveyed retail banking clients express interest in the new offer, whereas non-financial products and services are of lower interest than their financial pendants.

Keywords: banking, ecosystem, disruptive innovation, digital offering, open-banking-strategy, financial services industry

Procedia PDF Downloads 133