Search results for: solar energy system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 23365

Search results for: solar energy system

9895 Application of Deep Neural Networks to Assess Corporate Credit Rating

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

Abstract:

In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

Procedia PDF Downloads 222
9894 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration

Authors: C. Iraklis, G. Evmiridis, A. Iraklis

Abstract:

Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

Procedia PDF Downloads 432
9893 Acoustic Characteristics of Ultrasonic Vocalizations in Rat Pups Prenatally Exposed to Ethanol

Authors: Mohd. Ashik Shahrier, Hiromi Wada

Abstract:

Prenatal ethanol exposure has potential to induce difficulties in the social behavior of rats and can alter pup-dam communication suggesting that deficits in pups could result in altered dam behavior, which in turn could result in more aberrant behavior in the pup. Ultrasonic vocalization (USV) is a sensitive tool for investigating social behavior between rat pups and their dam. Rat pups produce USVs on separation from their dam. This signals the dam to locate her pups and retrieve them back to the nest. In this study, it was predicted that prenatal ethanol exposure cause alterations on the acoustic characteristics of USVs in rat pups. Thirteen pregnant rats were purchased and randomly assigned into three groups: high-ethanol (n = 4), low-ethanol (n = 5), and control (n = 4) groups. Laboratory ethanol (purity = 99.5%) was dissolved in tap water and administered to the high- and low-ethanol groups as drinking water from gestational days (GD) 8-20. Ethanol-containing water was administered to the animals in three stages by gradually increasing the concentration between GDs 8–20. From GDs 8–10, 10% and 5%, from GDs 11–13, 20% and 10%, and from GDs 14–20, 30% and 15% ethanol-containing water (v/v) was administered to the high- and low-ethanol groups, respectively. Tap water without ethanol was given to the control group throughout the experiment. The day of birth of the pups was designated as postnatal day (PND) 0. On PND 4, each litter was culled to four male and four female pups. For the present study, two male and two female pups were randomly sampled from each litter as subjects. Thus, eight male and eight female pups from the high-ethanol and control groups and another 10 male and 10 female pups from the low-ethanol group, were sampled. An ultrasonic microphone and the Sonotrack system version 2.4.0 (Metris, Hoofddorp, The Netherlands) were used to record and analyze USVs of the pups. On postnatal days 4, 8, 12 and 16, the resultant pups were individually isolated from their dams and littermates, and USVs were recorded for 5 min in a sound-proof box. Pups in the high-ethanol group produced greater number of USVs compared with that in both low-ethanol and control groups on PND 12. Rat pups in the high-ethanol group also produced higher mean, minimum, and maximum fundamental frequencies of USVs compared with that in both low-ethanol and control groups. Male pups in the high-ethanol group had higher USV amplitudes than in those in low-ethanol and control groups on PND 12. These results suggest that pups in the high-ethanol group relatively experienced more negative emotionality due to the ethanol-induced neuronal activation in the core limbic system and tegmental structures and accordingly, produced altered USVs as distress calls.

Keywords: emotionality, ethanol, maternal separation, ultrasonic vocalization

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9892 Multi Tier Data Collection and Estimation, Utilizing Queue Model in Wireless Sensor Networks

Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

Abstract:

In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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9891 Girls, Justice, and Advocacy: Using Arts-Based Public Health Strategies to Challenge Gender Inequities in Juvenile Justice

Authors: Tasha L. Golden

Abstract:

Girls in the U.S. juvenile justice system are most often arrested for truancy, drug use, or running from home, all of which are symptoms of abuse. In fact, some have called this 'The Sexual Abuse to Prison Pipeline.' Such abuse has consequences for girls' health, education, employment, and parenting, often resulting in significant health disparities. Yet when arrested, girls rarely encounter services designed to meet their unique needs. Instead, they are expected to cope with a system that was historically designed for males. In fact, even literature advocating for increased gender equity frequently fails to include girls’ voices and firsthand accounts. In response to these combined injustices, public health researchers launched a trauma-informed creative writing intervention in a southern juvenile detention facility. The program was designed to improve the health of detained girls, while also establishing innovative methods of both data collection and social justice advocacy. Girls’ poems and letters were collected and coded, adding rich qualitative data to traditional survey responses. In addition, as part of the intervention, these poems are regularly published by international literary publisher Sarabande Books—and distributed to judges, city leaders, attorneys, state representatives, and more. By utilizing a creative medium, girls generated substantial civic engagement with their concerns—thus expanding their influence and improving policy advocacy efforts. Researchers hypothesized that having access to their communities and policy makers would provide its own health benefits for incarcerated girls: cultivating self-esteem, locus of control, and a sense of leadership. This paper discusses the establishment of this intervention, examines findings from its evaluation, and includes several girls’ poems as exemplars. Grounded in social science regarding expressive writing, stigma, muted group theory, and health promotion, the paper theorizes about the application of arts-based advocacy efforts to other social justice endeavors.

Keywords: advocacy, public health, social justice, women’s health

Procedia PDF Downloads 150
9890 Estimating Algae Concentration Based on Deep Learning from Satellite Observation in Korea

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

Abstract:

Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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9889 Nietzsche and Shakti: An Intercultural Analysis of Nietzsche's Experiment with the Eternal Feminine

Authors: Shruti Jain

Abstract:

During its independence struggle in the early 20th century, India witnessed trends of politicisation of various spiritual paths, one of them being that of Shaktism. Interestingly, Nietzsche’s teachings were being interpreted as being essentially the worship of Shakti. The present paper aims at investigating this claim and hence undertakes an intercultural archaeological excavation in the realm of the Goddess archetypes that Nietzsche’s work invokes. Ariadne is placed next to Radha, Baubo to Lajja Gauri, Medusa to Chhinnamasta, Hecate to Kali and Dhumavati and Athena to Sarawati. Indeed, the Eternal Feminine plays a vital role in Nietzsche’s writings. One might recall that Nietzsche even declared himself to be the first Psychologist of the Eternal Feminine. The present paper aims to illustrate how, the matter of the Eternal Feminine, like all other matters, is subjected to Nietzsche’s basic creative principle of transvaluation of values and new meaning making. In order to achieve this, Nietzsche applies what Heidegger calls a 'cross-wise striking-through' technique in his analysis of what can be termed as his engagement with Shaktism. Hence, not only is the mystical ascent and descent of the creative energy (Kundalini Shakti) dealt with under erasure in Thus Spake Zarathustra, but coincidentally also the Three Metamorphoses emerge as an instance of such an erasure, making the Devi invisible and yet not so invisible for an Indian reader.

Keywords: eternal feminine, Nietzsche and India, Shaktism, transvaluation of values

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9888 Design and Implementation of Wireless Syncronized AI System for Security

Authors: Saradha Priya

Abstract:

Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

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9887 Seismic Hazard Prediction Using Seismic Bumps: Artificial Neural Network Technique

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

Abstract:

Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

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9886 A CMOS D-Band Power Amplifier in 22FDSOI Technology for 6G Applications

Authors: Karandeep Kaur

Abstract:

This paper presents the design of power amplifier (PA) for mmWave communication systems. The designed amplifier uses GlobalFoundries 22 FDX technology and works at an operational frequency of 140 GHz in the D-Band. With a supply voltage of 0.8V for the super low threshold voltage transistors, the amplifier is biased in class AB and has a total current consumption of 50 mA. The measured saturated output power from the power amplifier is 5.6 dBm with an output-referred 1dB-compression point of 1.6dBm. The measured gain of PA is 19 dB with 3 dB-bandwidth ranging from 120 GHz to 140 GHz. The chip occupies an area of 795µm × 410µm.

Keywords: mmWave communication system, power amplifiers, 22FDX, D-Band, cross-coupled capacitive neutralization

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9885 Duo Lingo: Learning Languages through Play

Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

Abstract:

This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

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9884 Visible Light Communication and Challenges

Authors: Hamid Sharif, Nazish Saleem Abbas, Muhammad Haris Jamil

Abstract:

Visible light communication is an emerging technology for almost a decade now; there is a growing need for VLC systems to overcome the challenges faced by radio frequency RF communication systems. With the advancement in the development of solid-state sources, in the future would replace incandescent and fluorescent light sources. These solid-state devices are not only to be used for illumination but can also be employed for communication and navigational purposes. The replacement of conventional illumination sources with highly efficient light-emitting diodes (LED's) (generally white light) will reduce energy consumption as well as environmental pollution. White LEDs dissipate very less power as compared to conventional light sources. The use of LED's is not only beneficial in terms of power consumption, but it also has an intrinsic capability for indoor wireless communication as compared to indoor RF communication. It is considerably low in cost to operate than the RF systems such as Wi-Fi routers, allows convenient means of reusing the bandwidth, and there is a huge potential for high data rate transmissions with enhanced data security. This paper provides an overview of some of the current challenges with VLC and proposes a possible solution to deal with these challenges; it also examines some joint protocols to optimize the joint illumination and communication functionality.

Keywords: visible light communication, line of sight, root mean square delay spread, light emitting diodes

Procedia PDF Downloads 58
9883 Guadua Bamboo as Eco-Friendly Element in Interior Design and Architecture

Authors: Sarah Noaman

Abstract:

Utilizing renewable resources has become extensive solution for most problems in Egypt nowadays. It plays role in environmental issues such as energy crisis, lake of natural resources and climate change. This paper focuses on the importance of working with the key concepts of creating eco-friendly spaces in Egypt by using traditional perennial plants, such as Guadua bamboo as renewable resources in structures manufacture. Egypt is in critical need to search for alternative raw materials. Thus, this paper focuses on studying the usage of neglected yet affordable materials, such as Guadua bamboo in light weight structures and digital fabrication. Guadua bamboo has been cultivated throughout in tropical and subtropical areas. In Egypt, they exist in many rural areas where people try to control their growth by using pesticides as it serves no economic purpose. This paper aims to discuss the usage of Guadua bamboo either in its original state or after fabrication in the context of interior design and architecture. The results will show the applicability of using perennial plants as complementary materials in the manufacturing processes; also the conclusion will focus the lights on the importance of re-forming shallow water plants in interior design and architecture.

Keywords: digital fabrication, Guadua bamboo, zero-waste material, sustainable material, interior architecture

Procedia PDF Downloads 141
9882 Fold and Thrust Belts Seismic Imaging and Interpretation

Authors: Sunjay

Abstract:

Plate tectonics is of very great significance as it represents the spatial relationships of volcanic rock suites at plate margins, the distribution in space and time of the conditions of different metamorphic facies, the scheme of deformation in mountain belts, or orogens, and the association of different types of economic deposit. Orogenic belts are characterized by extensive thrust faulting, movements along large strike-slip fault zones, and extensional deformation that occur deep within continental interiors. Within oceanic areas there also are regions of crustal extension and accretion in the backarc basins that are located on the landward sides of many destructive plate margins.Collisional orogens develop where a continent or island arc collides with a continental margin as a result of subduction. collisional and noncollisional orogens can be explained by differences in the strength and rheology of the continental lithosphere and by processes that influence these properties during orogenesis.Seismic Imaging Difficulties-In triangle zones, several factors reduce the effectiveness of seismic methods. The topography in the central part of the triangle zone is usually rugged and is associated with near-surface velocity inversions which degrade the quality of the seismic image. These characteristics lead to low signal-to-noise ratio, inadequate penetration of energy through overburden, poor geophone coupling with the surface and wave scattering. Depth Seismic Imaging Techniques-Seismic processing relates to the process of altering the seismic data to suppress noise, enhancing the desired signal (higher signal-to-noise ratio) and migrating seismic events to their appropriate location in space and depth. Processing steps generally include analysis of velocities, static corrections, moveout corrections, stacking and migration. Exploration seismology Bow-tie effect -Shadow Zones-areas with no reflections (dead areas). These are called shadow zones and are common in the vicinity of faults and other discontinuous areas in the subsurface. Shadow zones result when energy from a reflector is focused on receivers that produce other traces. As a result, reflectors are not shown in their true positions. Subsurface Discontinuities-Diffractions occur at discontinuities in the subsurface such as faults and velocity discontinuities (as at “bright spot” terminations). Bow-tie effect caused by the two deep-seated synclines. Seismic imaging of thrust faults and structural damage-deepwater thrust belts, Imaging deformation in submarine thrust belts using seismic attributes,Imaging thrust and fault zones using 3D seismic image processing techniques, Balanced structural cross sections seismic interpretation pitfalls checking, The seismic pitfalls can originate due to any or all of the limitations of data acquisition, processing, interpretation of the subsurface geology,Pitfalls and limitations in seismic attribute interpretation of tectonic features, Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Carbon capture and geological storage leakage surveillance because fault behave as a seal or a conduit for hydrocarbon transportation to a trap,etc.

Keywords: tectonics, seismic imaging, fold and thrust belts, seismic interpretation

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9881 A South African Perspective on Artificial Intelligence and Legal Personality

Authors: M. Naidoo

Abstract:

The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.

Keywords: artificial intelligence, bioethics, law, legal personality

Procedia PDF Downloads 68
9880 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

Procedia PDF Downloads 365
9879 Improving the Growth Performance of Beetal Goat Kids Weaned at Various Stages with Various Levels of Dietary Protein in Starter Ration under High Input Feeding System

Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

Abstract:

Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

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9878 Reliability-Based Life-Cycle Cost Model for Engineering Systems

Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

Abstract:

The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

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9877 Using Implicit Data to Improve E-Learning Systems

Authors: Slah Alsaleh

Abstract:

In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

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9876 Cryptocurrency-Based Mobile Payments with Near-Field Communication-Enabled Devices

Authors: Marko Niinimaki

Abstract:

Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.

Keywords: cryptocurrency, e-commerce, NFC, mobile devices

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9875 Studies on the Effect of Dehydration Techniques, Treatments, Packaging Material and Methods on the Quality of Buffalo Meat during Ambient Temperature Storage

Authors: Tariq Ahmad Safapuri, Saghir Ahmad, Farhana Allai

Abstract:

The present study was conducted to evaluate the effect dehydration techniques (polyhouse and tray drying), different treatment (SHMP, SHMP+ salt, salt + turmeric), different packaging material (HDPE, combination film), and different packaging methods (air, vacuum, CO2 Flush) on quality of dehydrated buffalo meat during ambient temperature storage. The quality measuring parameters included physico-chemical characteristics i.e. pH, rehydration ratio, moisture content and microbiological characteristics viz total plate content. It was found that the treatment of (SHMP, SHMP + salt, salt + turmeric increased the pH. Moisture Content of dehydrated meat samples were found in between 7.20% and 5.54%.the rehydration ratio of salt+ turmeric treated sample was found to be highest and lowest for controlled meat sample. the bacterial count log TPC/g of salt + turmeric and tray dried was lowest i.e. 1.80.During ambient temperature storage ,there was no considerable change in pH of dehydrated sample till 150 days. however the moisture content of samples increased in different packaging system in different manner. The highest moisture rise was found in case of controlled meat sample HDPE/air packed while the lowest increase was reported for SHMP+ Salt treated Packed by vacuum in combination film packed sample. Rehydration ratio was found considerably affected in case of HDPE and air packed sample dehydrated in polyhouse after 150 days of ambient storage. While there was a very little change in the rehydration ratio of meat samples packed in combination film CO2 flush system. The TPC was found under safe limit even after 150 days of storage. The microbial count was found to be lowest for salt+ turmeric treated samples after 150 days of storage.

Keywords: ambient temperature, dehydration technique, rehydration ratio, SHMP (sodium hexa meta phosphate), HDPE (high density polyethelene)

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9874 Determination of the Walkability Comfort for Urban Green Space Using Geographical Information System

Authors: Muge Unal, Cengiz Uslu, Mehmet Faruk Altunkasa

Abstract:

Walkability relates to the ability of the places to connect people with varied destinations within a reasonable amount of time and effort, and to offer visual interest in journeys throughout the network. So, the good quality of the physical environment and arrangement of walkway and sidewalk appear to be more crucial in influencing the pedestrian route choice. Also, proximity, connectivity, and accessibility are significant factor for walkability in terms of an equal opportunity for using public spaces. As a result, there are two important points for walkability. Firstly, the place should have a well-planned street network for accessible and secondly facilitate the pedestrian need for comfort. In this respect, this study aims to examine the both physical and bioclimatic comfort levels of the current condition of pedestrian route with reference to design criteria of a street to access the urban green spaces. These aspects have been identified as the main indicators for walkable streets such as continuity, materials, slope, bioclimatic condition, walkway width, greenery, and surface. Additionally, the aim was to identify the factors that need to be considered in future guidelines and policies for planning and design in urban spaces especially streets. Adana city was chosen as a study area. Adana is a province of Turkey located in south-central Anatolia. This study workflow can be summarized in four stages: (1) environmental and physical data were collected by referred to literature and used in a weighted criteria method to determine the importance level of these data , (2) environmental characteristics of pedestrian routes gained from survey studies are evaluated to hierarchies these criteria of the collected information, (3) and then each pedestrian routes will have a score that provides comfortable access to the park, (4) finally, the comfortable routes to park will be mapped using GIS. It is hoped that this study will provide an insight into future development planning and design to create a friendly and more comfort street environment for the users.

Keywords: comfort level, geographical information system (GIS), walkability, weighted criteria method

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9873 Challenge Based Learning Approach for a Craft Mezcal Kiln Energetic Redesign

Authors: Jonathan A. Sánchez Muñoz, Gustavo Flores Eraña, Juan M. Silva

Abstract:

Mexican Mezcal industry has reached attention during the last decade due to it has been a popular beverage demanded by North American and European markets, reaching popularity due to its crafty character. Despite its wide demand, productive processes are still made with rudimentary equipment, and there is a lack of evidence to improve kiln energy efficiency. Tec21 is a challenge-based learning curricular model implemented by Tecnológico de Monterrey since 2019, where each formation unit requires an industrial partner. “Problem processes solution” is a formation unity designed for mechatronics engineers, where students apply the acquired knowledge in thermofluids and apply electronic. During five weeks, students are immersed in an industrial problem to obtain a proper level of competencies according to formation unit designers. This work evaluates the competencies acquired by the student through qualitative research methodology. Several evaluation instruments (report, essay, and poster) were selected to evaluate etic argumentation, principles of sustainability, implemented actions, process modelling, and redesign feasibility.

Keywords: applied electronic, challenge based learning, competencies, mezcal industry, thermofluids

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9872 The Effect of Supplementary Cementitious Materials on Fresh and Hardened Properties of Self-Compacting Concretes

Authors: Akram Salah Eddine Belaidi, Said Kenai, El-Hadj Kadri, Benchaâ Benabed, Hamza Soualhi

Abstract:

Self-compacting concrete (SCC) was developed in the middle of the 1980’s in Japan. SCC flows alone under its dead weight and consolidates itself without any entry of additional compaction energy and without segregation. As an integral part of a SCC, self-compacting mortars (SCM) may serve as a basis for the mix design of concrete since the measurement of the rheological properties of SCCs. This paper discusses the effect of using natural pozzolana (PZ) and marble powder (MP) in two alternative systems ratios PZ/MP = 1 and 1/3 of the performance of the SCC. A total of 11 SCC’s were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 475 kg/m3. Then, the fresh properties of the mortars were tested for mini-slump flow diameter and mini-V-funnel flow time for SCMs and Slumps flow test, L-Box height ratio, V-Funnel flow time and sieve stability for SCC. Moreover, the development in the compressive strength was determined at 3, 7, 28, 56, and 90 days. Test results have shown that using of ternary blends improved the fresh properties of the mixtures. The compressive strength of SCC at 90 days with 30% of PZ and MP was similar to those of ordinary concrete use in situ.

Keywords: self-compacting mortar, self-compacting concrete, natural pozzolana, marble powder, rheology, compressive strength

Procedia PDF Downloads 357
9871 DEEPMOTILE: Motility Analysis of Human Spermatozoa Using Deep Learning in Sri Lankan Population

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

Abstract:

Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

Procedia PDF Downloads 92
9870 Modeling Anisotropic Damage Algorithms of Metallic Structures

Authors: Bahar Ayhan

Abstract:

The present paper is concerned with the numerical modeling of the inelastic behavior of the anisotropically damaged ductile materials, which are based on a generalized macroscopic theory within the framework of continuum damage mechanics. Kinematic decomposition of the strain rates into elastic, plastic and damage parts is basis for accomplishing the structure of continuum theory. The evolution of the damage strain rate tensor is detailed with the consideration of anisotropic effects. Helmholtz free energy functions are constructed separately for the elastic and inelastic behaviors in order to be able to address the plastic and damage process. Additionally, the constitutive structure, which is based on the standard dissipative material approach, is elaborated with stress tensor, a yield criterion for plasticity and a fracture criterion for damage besides the potential functions of each inelastic phenomenon. The finite element method is used to approximate the linearized variational problem. Stress and strain outcomes are solved by using the numerical integration algorithm based on operator split methodology with a plastic and damage (multiplicator) variable separately. Numerical simulations are proposed in order to demonstrate the efficiency of the formulation by comparing the examples in the literature.

Keywords: anisotropic damage, finite element method, plasticity, coupling

Procedia PDF Downloads 188
9869 Incorporation of Safety into Design by Safety Cube

Authors: Mohammad Rajabalinejad

Abstract:

Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: safety, safety cube, product, system, machinery, design

Procedia PDF Downloads 228
9868 High Efficient Biohydrogen Production from Cassava Starch Processing Wastewater by Two Stage Thermophilic Fermentation and Electrohydrogenesis

Authors: Peerawat Khongkliang, Prawit Kongjan, Tsuyoshi Imai, Poonsuk Prasertsan, Sompong O-Thong

Abstract:

A two-stage thermophilic fermentation and electrohydrogenesis process was used to convert cassava starch processing wastewater into hydrogen gas. Maximum hydrogen yield from fermentation stage by Thermoanaerobacterium thermosaccharolyticum PSU-2 was 248 mL H2/g-COD at optimal pH of 6.5. Optimum hydrogen production rate of 820 mL/L/d and yield of 200 mL/g COD was obtained at HRT of 2 days in fermentation stage. Cassava starch processing wastewater fermentation effluent consisted of acetic acid, butyric acid and propionic acid. The effluent from fermentation stage was used as feedstock to generate hydrogen production by microbial electrolysis cell (MECs) at an applied voltage of 0.6 V in second stage with additional 657 mL H2/g-COD was produced. Energy efficiencies based on electricity needed for the MEC were 330 % with COD removals of 95 %. The overall hydrogen yield was 800-900 mL H2/g-COD. Microbial community analysis of electrohydrogenesis by DGGE shows that exoelectrogens belong to Acidiphilium sp., Geobacter sulfurreducens and Thermincola sp. were dominated at anode. These results show two-stage thermophilic fermentation, and electrohydrogenesis process improved hydrogen production performance with high hydrogen yields, high gas production rates and high COD removal efficiency.

Keywords: cassava starch processing wastewater, biohydrogen, thermophilic fermentation, microbial electrolysis cell

Procedia PDF Downloads 328
9867 Observations of Magnetospheric Ulf Waves in Connection to the Kelvin-Helmholtz Instability at Mercury

Authors: Elisabet Liljeblad, Tomas Karlsson, Torbjorn Sundberg, Anita Kullen

Abstract:

The magnetospheric magnetic field data from the MESSENGER spacecraft is investigated to establish the presence of ultra-low frequency (ULF) waves in connection to 131 previously observed nonlinear Kelvin-Helmholtz waves (KHWs) at Mercury. Distinct ULF signatures are detected in 44 out of the 131 magnetospheric traversals prior to or after observing a KHW. In particular, 39 of these 44 ULF events are highly coherent at the frequency of maximum power spectral density. The waves observed at the dayside, which appears mainly at the duskside and naturally following the KHW occurrence asymmetry, are significantly different to the events behind the dawn-dusk terminator and have the following distinct wave characteristics: they oscillate clearly in the perpendicular (azimuthal) direction to the mean magnetic field with a wave normal angle more in the parallel than the perpendicular direction, increase in absolute ellipticity with distance from noon, are almost exclusively right-hand polarized, and are observed mainly for frequencies in the range 0.02-0.04 Hz. These results indicate that the dayside ULF waves are likely to shear Alfvén waves driven by KHWs at the magnetopause, which in turn manifests the importance of the Kelvin-Helmholtz instability in terms of mass transport throughout the Mercury magnetosphere.

Keywords: ultra-low frequency waves, kelvin-Helmholtz instability, magnetospheric processes, mercury, messenger, energy and momentum transfer in planetary environments

Procedia PDF Downloads 226
9866 Revolutionary Solutions for Modeling and Visualization of Complex Software Systems

Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

Procedia PDF Downloads 384