Search results for: growth performance

Authors: Jiyaul Haque, Vandana Srivastava, M. A. Quraishi

Abstract:

The amino acids based corrosion inhibitors 2-(3-(carboxymethyl)-1H-imidazol-3-ium-1-yl) acetate (Z-1),2-(3-(1-carboxyethyl)-1H-imidazol-3-ium-1-yl) propanoate (Z-2) and 2-(3-(1-carboxy-2-phenylethyl)-1H-imidazol-3-ium-1-yl)-3- phenylpropanoate (Z-3) were synthesized by the reaction of amino acids, glyoxal and formaldehyde, and characterized by the FTIR and NMR spectroscopy. The corrosion inhibition performance of synthesized inhibitors was studied by electrochemical (EIS and PDP), surface and DFT methods. The results show, the studied Z-1, Z-2 and Z-3 are effective inhibitors, showed the maximum inhibition efficiency of 88.52 %, 89.48 and 96.08% at concentration 200ppm, respectively. The results of potentiodynamic polarization (PDP) study showed that Z-1 act as a cathodic inhibitor, while Z-2 and Z-3 act as mixed type inhibitors. The results of electrochemical impedance spectroscopy (EIS) studies showed that zwitterions inhibit the corrosion through adsorption mechanism. The adsorption of synthesized zwitterions on the mild steel surface was followed the Langmuir adsorption isotherm. The formation of zwitterions film on mild steel surface was confirmed by the scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDX). The quantum chemical parameters were used to study the reactivity of inhibitors and supported the experimental results. An inhibitor adsorption model is proposed.

Keywords: electrochemical impedance spectroscopy, green corrosion inhibitors, mild steel, SEM, quantum chemical calculation, zwitterions

Procedia PDF Downloads 161

Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

Procedia PDF Downloads 140

Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

Abstract:

Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

Procedia PDF Downloads 552

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

Abstract:

Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 107

Authors: Despina Vamvuka, Despina Pentari

Abstract:

Forestry wastes are readily available in large quantities around the world. Based on European Green Deal for the deployment of renewable and decarbonized energy by 2050, as well as global energy crisis, energy recovery from such wastes reducing greenhouse gas emissions is very attractive. Gasification has superior environmental performance to combustion, producing a clean fuel gas utilized in internal combustion engines, gas turbines, solid oxide fuel cells, or for synthesis of liquid bio-fuels and value-added chemicals. In this work, pine needles, which are abundantly found in Mediterranean countries, were gasified by either steam or carbon dioxide via a two-step process to improve reactivity and eliminate tar, employing a fixed bed unit and a thermal analysis system. Solid, liquid and gaseous products from the whole process were characterized and their energy potential was determined. Thermal behaviour, reactivity, conversion and energy recovery were examined. The gasification process took place above 650°C. At 950°C conversion and energy recovery were 77% dry and 2 under a flow of steam and 85% dry and 2.9 under a flow of carbon dioxide, respectively. Organic matter was almost completely converted to syngas, the yield of which varied between 89% and 99%. The higher heating values of biochar, bio-oil and pyrolysis gas were 27.8 MJ/kg, 33.5 MJ/kg and 13.6 MJ/m3. Upon steam or carbon dioxide gasification, the higher heating value of syngas produced was 11.5 MJ/m3 and 12.7 MJ/m3, respectively.

Keywords: gasification, biomass, steam, carbon dioxide

Procedia PDF Downloads 73

Authors: Endalamaw Ewnu Kassa, Ade Kurniawan, Ya-Fen Wu, Sajal Biring

Abstract:

Perovskite-based gas sensors represent a highly promising materials within the realm of gas sensing technology, with a particular focus on detecting ammonia (NH3) due to its potential hazards. Our work conducted thorough comparison of various solvents, including dimethylformamide (DMF), DMF-dimethyl sulfoxide (DMSO), dimethylacetamide (DMAC), and DMAC-DMSO, for the preparation of our perovskite solution (MAPbI3). Significantly, we achieved an exceptional response at 10 ppm of ammonia gas by employing a binary solvent mixture of DMAC-DMSO. In contrast to prior reports that relied on single solvents for MAPbI3 precursor preparation, our approach using mixed solvents demonstrated a marked improvement in gas sensing performance. We attained enhanced surface coverage, a reduction in pinhole occurrences, and precise control over grain size in our perovskite films through the careful selection and mixtures of appropriate solvents. This study shows a promising potential of employing binary and multi-solvent mixture strategies as a means to propel advancements in gas sensor technology, opening up new opportunities for practical applications in environmental monitoring and industrial safety.

Keywords: sensors, binary solvents, ammonia, sensitivity, grain size, pinholes, surface coverage

Procedia PDF Downloads 67

Authors: Franklin Nakpodia, Femi Olan

Abstract:

A blend of internal factors (firm performance, internal stakeholders) and external pressures (globalisation, technology, corporate scandals) have intensified calls for corporate governance reforms. While several countries and their governments have responded to these calls, the effect of such reforms on corporate governance systems across countries remains mixed. In particular, the literature reports that the effectiveness of corporate governance interventions in many developing economies is limited. Relying on the corporate governance system in Africa’s largest economy (Nigeria), this research addresses two issues. First, this study explores why previous corporate governance reforms have failed and second, the article investigates what reforms could improve corporate governance practices in the country. In addressing the above objectives, this study adopts a qualitative approach that permits data collection via semi-structured interviews with 21 corporate executives. The data supports the articulation of two sequential levels of reforms (i.e., the upstream and downstream reforms). The upstream reforms focus on two crucial but often overlooked areas that undermine reform effectiveness, i.e., the extent of government commitment and an enabling environment. The downstream reforms combine awareness and regulatory elements to proffer a path to robust corporate governance in the country. Furthermore, findings from this study stress the need to consider the use of a bottom-up approach to corporate governance practice and policymaking in place of the dominant top-down strategy.

Keywords: bottom-up approach, corporate governance, reforms, regulation

Procedia PDF Downloads 176

Authors: Emmanuel Sachikumba, Micheal Msoni, Westone Mafuleka

Abstract:

Zambia has a good climate with favourable rainfall pattern; this provides sufficient recharge for the surface and groundwater resources. In spite of the sufficient surface and ground water resources, accessibility to water at household levels is problematic both in quality and quantity. The study examined water accessibility as well as water quality at the household level. The research looked at the sources of water for the households and considered the complications of accessibility to water and the available opportunities therein. The investigation involved fifty households and the data was collected by the use of questionnaires (to assess accessibility) and laboratory tests (for ascertaining water quality). In addition to this, government departments such as the health, agriculture, forestry and education as well as the municipal council were interviewed on the topic under study. The study was descriptive in nature where clustered sampling procedures using simple random methods were utilised to select the households which were to participate in the study. The key findings were that; accessibility to water household levels is still a challenge in the settlement as most of the point sources (shallow wells, the stream and the river) were found to be contaminated. In addition to this, it was found that there was no direct relationship between the economic performance of a household and the accessibility to water. The study also observed that there were opportunities for the people in the settlement as they were increasingly getting into the education system, and adult literacy was being encouraged in the settlement. Furthermore, the settlement has groundwater resources which indicate that there can be sufficient water provision for the settlers.

Keywords: accessibility, household, water, settlement

Procedia PDF Downloads 417

Authors: Jamilah Halina Abdul Halim, Norsiah Hassan, Azlina Aziz, Norhayati Mat Wajid, Mohd Saipul Asrafi

Abstract:

There are various types of vertical greenery system (VGS) in Malaysia, but none is installed at government buildings, although the government is looking into energy efficient building design. This is due to lack of technical information that focus on the maintenance and care, issues, and challenges face by vertical greenery system under tropical climate conditions. This research aim to identify issues in implementation of vertical greenery system on existing government building in Malaysia. The methodology used are literature reviews (desktop study), observation on sites, and case studies. Initial findings indicates that design and maintenance issues of vertical greenery system are the main challenges faced mainly by designer, especially those who involved in decision-making process. It can be concluded that orientation, openings, maintenance, performance, longevity, structural load, access, wind resistance, design failure, system failure, and lack of maintenance foresight are the main factors that need to be considered. These factors should be holistically aligned towards the economic cost, effective time, and quality design in implementation of vertical greenery system on existing government building. A comprehensive implementation of vertical greenery system will lead to greater sustainable investment for government buildings and responsive action to climate change.

Keywords: issues, government building, maintenance, vertical greenery system

Procedia PDF Downloads 66

Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

Procedia PDF Downloads 203

Authors: Jerzy Bański

Abstract:

Central and Eastern European agriculture is characterized by large spatial variations in the structure of agricultural land and the structure of crops on arable land. In general, field crops predominate among the land used for agriculture. In the southern part of the study area, permanent crops have a relatively large share, which is due to favorable climatic conditions. Clear differences between the north and south of the region concern the structure of crop cultivation. In the north, the cultivation of cereals, mainly wheat, definitely prevails. In the south of the region, on the other hand, the structure of crops is more diverse, as more industrial crops are grown in addition to cereals. The primary cognitive objective of the study is to diagnose and identify the directions of changes in the structure of agricultural land use in the CEE region. Particular attention was paid to the spatial differentiation of this structure and its importance in its formation of various conditions. The analysis included the basic elements of the structure of agricultural land use and the structure of crops on arable land. The decrease in the area of arable land is characteristic of the entire region and is the result of the territorial growth of cities, the development of communications infrastructure (rail and road), and the increase in the rationality of crop production involving, among other things, the exclusion from the cultivation of land with the lowest agro-ecological values and their afforestation. It can be summarized that the directions of changes in the basic categories of agricultural land are related to agro-ecological conditions, which indicates an increase in the rationality of crop production. In countries with lower-quality of agricultural production space, the share of grassland generally increased, while in countries with favorable conditions -mainly soil- the share of arable land increased. As for the structure of field crops, the direction of its changes seems to be mainly due to economic and social reasons. Ownership changes shaping an unfavorable agrarian structure (fragmentation and fragmentation of arable fields) and the process of aging of the rural population resulted in the abandonment of resource- and labor-intensive crops. As a result, the importance of growing fruits and vegetables, and potatoes has declined. The structure of vegetable crops has been greatly influenced by the accession of Central and Eastern European countries to the European Union. This is primarily the increase in the importance of oil crops (rapeseed and sunflower) related to biofuel production. In the case of cereal crops, the main direction of change was the increase in the share of wheat at the expense of other cereal species.

Keywords: agriculture, land use, Central and Eastern Europe, crops, arable land

Procedia PDF Downloads 54

Authors: Raymond Feng, Shadi Ghiasi

Abstract:

An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

Procedia PDF Downloads 30

Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

Abstract:

This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

Procedia PDF Downloads 49

Authors: Tony Ngoy Mbodi, Christophe Muanda

Abstract:

Textile industry is considered as one of the most polluting sectors in terms of effluent volume of discharge and wastewater composition, such as dye, which represents an environmental hazard when discharged without any proper treatment. A study was conducted to investigate the capability of the use of recycled alum sludge (RAS) as an alternative treatment for the reduction of colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH adjustment from dye based synthetic textile industry wastewater. The coagulation/flocculation process was studied for coagulants of Alum:RAS ratio of, 1:1, 2:1, 1:2 and 0:1. Experiments on treating the synthetic wastewater using membrane filtration and adsorption with corn cobs were also conducted. Results from the coagulation experiment were compared to those from adsorption with corn cobs and membrane filtration experiments conducted on the same synthetic wastewater. The results of the RAS experiments were also evaluated against standard guidelines for industrial effluents treated for discharge purposes in order to establish its level of compliance. Based on current results, it can be concluded that reusing the alum sludge as a low-cost material pretreatment method into the coagulation/flocculation process can offer some advantages such as high removal efficiency for disperse dye and economic savings on overall treatment of the industry wastewater.

Keywords: alum, coagulation/flocculation, dye, recycled alum sludge, textile wastewater

Procedia PDF Downloads 323

Authors: Eric S. Lee, Connie Bygrave, Jordan Mahar, Naina Garg, Suzanne Cottreau

Abstract:

Marking exams is universally detested by lecturers. Final exams in many higher education courses often last 3.0 hrs. Do exams really need to be so long? Can we justifiably reduce the number of questions on them? Surprisingly few have researched these questions, arguably because of the complexity and difficulty of using traditional methods. To answer these questions empirically, we used a new approach based on three key elements: Use of an unusual variation of a true experimental design, equivalence hypothesis testing, and an expanded set of six psychometric criteria to be met by any shortened exam if it is to replace a current 3.0-hr exam (reliability, validity, justifiability, number of exam questions, correspondence, and equivalence). We compared student performance on each official 3.0-hr exam with that on five shortened exams having proportionately fewer questions (2.5, 2.0, 1.5, 1.0, and 0.5 hours) in a series of four experiments conducted in two classes in each of two finance courses (224 students in total). We found strong evidence that, in these courses, shortening of final exams to 2.0 hrs was warranted on all six psychometric criteria. Shortening these exams by one hour should result in a substantial one-third reduction in lecturer time and effort spent marking, lower student stress, and more time for students to prepare for other exams. Our approach provides a relatively simple, easy-to-use methodology that lecturers can use to examine the effect of shortening their own exams.

Keywords: exam length, psychometric criteria, synthetic experimental designs, test length

Procedia PDF Downloads 256

Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

Abstract:

As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

Procedia PDF Downloads 260

Authors: Ali Afaghi, Sehraneh Ghaemi

Abstract:

The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

Procedia PDF Downloads 373

Authors: Hubert Beisch, Janik Marx, Svenja Garlof, Roman Shvets, Ivan Grygorchak, Andriy Kityk, Bodo Fiedler

Abstract:

Three-dimensional carbon materials can be used as electrode materials for energy storage systems such as batteries and supercapacitors. Fast charging and discharging times are realizable without reducing the performance due to aging processes. Furthermore high specific surface area (SSA) of three-dimensional carbon structures leads to high specific capacities. One newly developed carbon foam is Globugraphite. This interconnected globular carbon morphology with statistically distributed hierarchical pores is manufactured by a chemical vapor deposition (CVD) process from ceramic templates resulting from a sintering process. Via scanning electron (SEM) and transmission electron microscopy (TEM), the morphology is characterized. Moreover, the SSA was measured by the Brunauer–Emmett–Teller (BET) theory. Measurements of Globugraphite in an organic and inorganic electrolyte show high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. A comparison of the specific values is summarized in a Ragone diagram. Energy densities up to 48 Wh/kg and power densities to 833 W/kg could be achieved for an SSA from 376 m²/g to 859 m²/g. For organic electrolyte, a specific capacity of 100 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, carbon foam, CVD process, electrochemical cell, Ragone diagram, SEM, TEM

Procedia PDF Downloads 210

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

Procedia PDF Downloads 26

Authors: Robert Cui

Abstract:

COVID-19 has drastically changed the way students interact and engage with their environments. Students, in particular, have been forced to change from in-person to online learning. How can we ensure that students continue to remain motivated even as their mode of education transitions to online learning? In this study conducted on high school students from a small private school (n = 50), we investigate the factors that predict student motivation during online learning. Using the framework of self-determination theory, we examine the three facets of student motivation during online learning: engagement, autonomy, and competence. We find that students' perception of their peers' engagement with the curriculum, feelings of parental academic expectations, perceptions of favoritism by the teacher, and perceived clarity of instruction given by the teacher all predict student engagement in online learning. Student autonomy is predicted by the amount of parental control a student feels, the clarity of instruction given by the teacher, and also the amount to which a student is perceiving their peers to be paying attention. Finally, competence is predicted by favoritism a student perceives from a teacher and also the amount of which a student is perceiving their peers to be paying attention. Based on these findings, we provide insights on how three important stakeholders –parents, teachers, and peers can enhance students' motivation during online learning.

Keywords: academic performance, motivation, online learning, parental influence, teacher, peers

Procedia PDF Downloads 118

Authors: Kanika Gupta, Ashok Kumar

Abstract:

Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

Procedia PDF Downloads 146

Authors: Jagoda Przybysz

Abstract:

The main objective of this paper is to provide a comprehensive description of the immigrants in Poland, especially situation at the labour market. The paper will provide descriptive information on the composition of immigrants in Poland, and how this has changed over time, their socio-economic characteristics, their industry allocation and their labour market outcomes. Then we will investigate various labour market performance indicators (labour force participation, employment, wages and self-employment) for immigrants of different origins based on reached statistics. Individual interviews with immigrants will indicate areas of problems of living in Poland, mostly on labour market. The article shows that immigrants from some ethnic minority groups are more active in selected sectors of labour market. The empirical basis for the work related to the situation on the labor market of foreigners who came to the Poland and live in Lodz. The studies assumed that foreigners work in Poland and operate in different ways being integrated / excluded in varying degrees. Theoretical framework for analysis are: concepts of inclusion and exclusion, the concept of a dual labour market and the concept of social anchors. Completed in the 2014-2016, a pilot study (The forms of individual interviews) with 32 foreigners arrived in the last decade to Lodz. Preliminary studies have enabled the formulation of research issues and have set the future direction of research revealing to the personal experiences of respondents, a group of factors hindering integration and exclusion areas.

Keywords: foreigners, immigrants, labour market, migration, Poland

Procedia PDF Downloads 155

Authors: Hailemeleak Regassa

Abstract:

Traditional medicines use medicinal plants as a source of ingredients, and many modern medications are indirectly derived from plants. Consumers in affluent nations are growing disenchanted with contemporary healthcare and looking for alternatives. Oxidative stress is the primary cause of multiple diseases, and exogenous antioxidant supplementation or strengthening the body's endogenous antioxidant defenses are potential ways to counteract the negative effects of oxidative damage. Plants can biosynthesize non-enzymatic antioxidants that can reduce ROS-induced oxidative damage. Aging often aids the propagation and development of carcinogenesis, and older animals and older people exhibit increased vulnerability to tumor promoters. Cancer is a major public health issue, with several anti-cancer medications in clinical use. Potential drugs such as flavopiridol, roscovitine, combretastatin A-4, betulinic acid, and silvestrol are in the clinical or preclinical stages of research. Methodology: Microbial Growth media, Dimethyl sulfoxide (DMSO), methanol, ethyl acetate, and n-hexane were obtained from Himedia Labs, Mumbai, India. plant were collected from the Herbal Garden of Shoolini University campus, Solan, India (Latitude - 30.8644° N and longitude - 77.1184° E). The identity was confirmed by Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.), India, and documented in Voucher specimens - UHF- Herbarium no. 13784; vide book no. 3818 Receipt No. 086. The plant materials were washed with tap water, and 0.1% mercury chloride for 2 minutes, rinsed with distilled water, air dried, and kept in a hot air oven at 40ºc on blotting paper until all the water evaporated and became well dried for grinding. After drying, the plant materials were grounded using a mixer grinder into fine powder transferred into airtight containers with proper labeling, and stored at 4ºc for future use (Horablaga et al., 2023). The extraction process was done according to Altemimi et al., 2017. The 5g powder was mixed with 15 ml of the respective solvents (n-hexane, ethyl acetate, and methanol), and kept for 4-5 days on the platform shaker. The solvents used are based on their increasing polarity index. Then the extract was centrifuged at 10,000rpm for 5 minutes and filtered using No.1 Whatman filter paper.

Keywords: cancer, phytomedicine, medicinal plants, oncology

Procedia PDF Downloads 46

Authors: M. Ezkurra, J. A. Esnaola, M. Martinez-Agirre, U. Etxeberria, U. Lertxundi, L. Colomo, M. Begiristain, I. Zurutuza

Abstract:

Butterfly valves are widely used industrial piping components as on-off and flow controlling devices. The main challenge in the design process of this type of valves is the correct dimensioning to ensure proper mechanical performance as well as to minimise flow losses that affect the efficiency of the system. Butterfly valves are typically dimensioned in a closed position based on mechanical approaches considering uniform hydrostatic pressure, whereas the flow losses are analysed by means of CFD simulations. The main limitation of these approaches is that they do not consider either the influence of the dynamics of the manoeuvring stage or coupled phenomena. Recent works have included the influence of the flow on the mechanical behaviour for different opening angles by means of one-way FSI approach. However, these works consider steady-state flow for the selected angles, not capturing the effect of the transient flow evolution during the manoeuvring stage. Two-way FSI modelling approach could allow overcoming such limitations providing more accurate results. Nevertheless, the use of this technique is limited due to the increase in the computational cost. In the present work, the applicability of FSI one-way and two-way approaches is evaluated for the analysis of butterfly valves, showing that not considering fluid-structure coupling involves not capturing the most critical situation for the valve disc.

Keywords: butterfly valves, fluid-structure interaction, one-way approach, two-way approach

Procedia PDF Downloads 146

Authors: Mohit Singla, Vishavjeet Singh Hans, Sukhmeet Singh

Abstract:

Heat transfer and friction characteristics of evacuated tube collector solar air heater artificially roughened with periodic circular rib of uniform cross-section were investigated. The present investigation was carried out in ANSYS Fluent 15.0 to study the impact of roughness geometry parameters, i.e. relative roughness pitch (P/e) of 8 and relative roughness height (e/Dh) of 0.064 and flow parameters, i.e. Reynolds number range of 2500-8000 on Nusselt number and friction factor. RNG k-ε with enhanced wall treatment turbulence model was selected for analysis. The results obtained for roughened evacuated tube collector has been compared with smooth evacuated tube collector for the similar flow conditions. With the increment in Reynolds number from 2500 to 8000, Nusselt number augments while friction factor decreases. Maximum enhancement ratio of Nusselt number and friction factor was 1.71 and 2.7 respectively, obtained at Reynolds number value of 8000. The value of thermo-hydraulic performance parameter was varied between 1.18 - 1.23 for the entire range of Reynolds number, indicates the advantage to use the roughened evacuated tube collector over smooth evacuated tube collector in solar air heater.

Keywords: artificial roughness, evacuated tube collector, friction factor, Nusselt number

Procedia PDF Downloads 139

Authors: N. Mahmoudnia, M. Khormali

Abstract:

This experiment was conducted to determine the apparent protein digestibility of poultry byproduct meal (PBPM) from two industrial poultry slaughter-houses on Ross 308 male broiler chickens in independent comparisons. The experiment consisted of seven dietary treatments and three replicates per treatment with three broiler chickens per replicate in a completely randomized design. Dietary treatments consisted of a control corn- soybean diet, and levels 3, 6, and 9% PBPM produced by slaughter-house 1 and levels 3, 6, and 9% PBPM produced by slaughter house 2. Chromic oxide was added to the experimental diets as an indigestible marker. The apparent protein digestibility of each diet were determined with two methods of sample collection of ileum and excreta in 21-28 d of age. The results this experiment showed that use of PBPM had no significant effect on the performance of broiler chicks during period of experiments. The apparent protein digestibility of PBPM groups was significantly higher than control group by excreta sampling procedure (P<0.05). Using of PBPM 2 significantly (P<0.05) decreased the apparent protein digestibility values based on ileum sampling procedure vs control (85.21 vs. 90.14).Based results of this experiment,it is possible to use of PBPM 1 in broiler chicken.

Keywords: poultry by-product meal, apparent protein digestibility, independed comparison, broiler chicken

Procedia PDF Downloads 468

Authors: Rofayda A. Hout

Abstract:

This study aims to investigate the relationship between women on board and corporate social responsibility (CSR) in addition to the role of corporate governance in introducing and implementing CSR practices. Analysis has been conducted on 30 prior studies published between 2007 and 2017 to investigate the common areas and differences across the studies with varying conclusions. The study also handles the differences between developing and developed countries when it comes to gender diverse board and corporate social responsibility. The review conducted reveals that there is a positive relationship between women on board and corporate social responsibility. Comparison between developed and developing countries with respect to CSR implementation highlighted differences due to possible reasons relating to socio-political, cultural, socio-economic, and institutional factors. In addition, developing countries perceive CSR as philanthropy rather than part of their business mission. Given that, CSR needs to be integrated into the corporate strategic planning and be considered as fundamental part of the operations to improve the region’s needs. Developing countries were late in adopting CSR in comparison to developed countries, thus to have a fair comparison between developed and developing countries, corporate governance in developing countries should take serious steps in developing a framework for CSR implementation and integrating it within corporate operations.

Keywords: corporate governance, corporate performance, corporate social responsibility, developed countries, developing countries, gender diverse board, systematic review

Procedia PDF Downloads 183

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

Procedia PDF Downloads 40

Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

Procedia PDF Downloads 140

Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

Abstract:

In 1994, Korea experienced a national tragedy of Seongsu Bridge collapse. The accident was severe enough to alert governmental officers to the problem of existing management policy for national infrastructures. As a result, government legislated the ‘Guidelines for the safety inspection and test of infrastructure’ which have been utilized as the primary tool to make decision for the maintenance and rehabilitation of infrastructure for last twenty years. Although it is clear that the guideline established a basics how to evaluate and manage the condition of infrastructures in systematic manner, it is equally clear that the guideline needs improvements in order to obtain reasonable investment decisions for budget allocation. Because its inspection and evaluation procedures mainly focused on the structural condition of infrastructures, it was hard to make decision when the infrastructures were in same level of structural condition. In addition, it did not properly reflect various aspects of infrastructures such as performance, public demand, capacity, etc., which were more valuable to public. Regardless of the importance, these factors were commonly neglected in governmental decision-making process, because there factors were somewhat subjective and difficult to quantify in rational manner. Thus, this study proposes a framework to properly evaluate the serviceability indicators using AHP and Fuzzy approach. The framework is expected to assist governmental agency in establishing effective investment strategies for budget planning.

Keywords: infrastructure, evaluation, serviceability, fuzzy

Procedia PDF Downloads 266