Search results for: modeling technique
1778 Safety Culture, Mindfulness and Safe Behaviours of Students Residing in the Halls of Residence of Obafemi Awolowo University, Ile Ife, Nigeria
Authors: Olajumoke Adetoun Ojeleye
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The study assessed the safety culture, mindfulness and safe behaviors of students residing in the halls of residence of Obafemi Awolowo University (OAU), Ile Ife, Nigeria. The objectives of the study were to assess the level of safety mindfulness of students residing in the halls of residence of OAU, examine their safety culture and establish whether these students are involved in unsafe practices. The study employed a cross-sectional research design and instrument used for data collection was a self-structured, self-administered questionnaire. The questionnaire was tested for validity and reliability with its reliability coefficient at 0.71 before being used for data collection. Respondents were selected by multi-stage sampling technique and the sample size was 530. Data collection took 2 weeks and analysed using descriptive statistical techniques. Results showed that about half of the respondents’ population (49.8%) was between the ages of 20-24 years. There were more males (56.2%) than females (43.8%). Although data demonstrated that majority (91.7%) of the respondents are highly safety minded and the safety culture of an equally high proportion (83.4%) was adjudged fair, a lot of improvement is needed in the area of alerting or informing management of impending dangers and studying the hall handbook to internalize its contents. The study further showed that only 43.6% of respondents had good safety practices and behaviors and majority (56.4%) had fair safety practices and behaviors. One accidental discovery of the study is the finding that not a few of the students squat their counterparts. The study recommended the establishment of clearly written out complaint procedure that is accessible and available to all hall residents, building more hostels with adequate facilities to address the issue of overcrowding and also putting systems in place in order to encourage residents to report incidences/accidents.Keywords: safe behaviours, safety culture, safety mindfulness, student
Procedia PDF Downloads 2651777 Evaluating Habitat Manipulation as a Strategy for Rodent Control in Agricultural Ecosystems of Pothwar Region, Pakistan
Authors: Nadeem Munawar, Tariq Mahmood
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Habitat manipulation is an important technique that can be used for controlling rodent damage in agricultural ecosystems. It involves intentionally manipulation of vegetation cover in adjacent habitats around the active burrows of rodents to reduce shelter, food availability and to increase predation pressure. The current study was conducted in the Pothwar Plateau during the respective non-crop period of wheat-groundnut (post-harvested and un-ploughed/non-crop fallow lands) with the aim to assess the impact of the reduction in vegetation height of adjacent habitats (field borders) on rodent’s richness and abundance. The study area was divided into two sites viz. treated and non-treated. At the treated sites, habitat manipulation was carried out by removing crop cache, and non-crop vegetation’s over 10 cm in height to a distance of approximately 20 m from the fields. The trapping sessions carried out at both treated and non-treated sites adjacent to wheat-groundnut fields were significantly different (F 2, 6 = 13.2, P = 0.001) from each other, which revealed that a maximum number of rodents were captured from non-treated sites. There was a significant difference in the overall abundance of rodents (P < 0.05) between crop stages and between treatments in both crops. The manipulation effect was significantly observed on damage to crops, and yield production resulted in the reduction of damage within the associated croplands (P < 0.05). The outcomes of this study indicated a significant reduction of rodent population at treated sites due to changes in vegetation height and cover which affect important components, i.e., food, shelter, movements and increased risk sensitivity in their feeding behavior; therefore, they were unable to reach levels where they cause significant crop damage. This method is recommended for being a cost-effective and easy application.Keywords: agricultural ecosystems, crop damage, habitat manipulation, rodents, trapping
Procedia PDF Downloads 1661776 A Technique for Planning the Application of Buttress Plate in the Medial Tibial Plateau Using the Preoperative CT Scan
Authors: P. Panwalkar, K. Veravalli, R. Gwynn, M. Tofighi, R. Clement, A. Mofidi
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When operating on tibial plateau fracture especially medial tibial plateau, it has regularly been said “where do I put my thumb to reduce the fracture”. This refers to the ideal placement of the buttress device to hold the fracture till union. The aim of this study was to see if one can identify this sweet spot using a CT scan. Methods: Forty-five tibial plateau fractures with medial plateau involvement were identified and included in the study. The preoperative CT scans were analysed and the medial plateau involvement pattern was classified based on modified radiological classification by Yukata et-al of stress fracture of medial tibial plateau. The involvement of part of plateau was compared with position of buttress plate position which was classified as medial posteromedial or both. Presence and position of the buttress was compared with ability to achieve and hold the reduction of the fracture till union. Results: Thirteen fractures were type-1 fracture, 19 fractures were type-2 fracture and 13 fractures were type-3 fracture. Sixteen fractures were buttressed correctly according to the potential deformity and twenty-six fractures were not buttressed and three fractures were partly buttressed correctly. No fracture was over butressed! When the fracture was buttressed correctly the rate of the malunion was 0%. When fracture was partly buttressed 33% were anatomically united and 66% were united in the plane of buttress. When buttress was not used, 14 were malunited, one malunited in one of the two planes of deformity and eleven anatomically healed (of which 9 were non displaced!). Buttressing resulted in statistically significant lower mal-union rate (x2=7.8, p=0.0052). Conclusion: The classification based on involvement of medial condyle can identify the placement of buttress plate in the tibial plateau. The correct placement of the buttress plate results in predictably satisfactory union. There may be a correlation between injury shape of the tibial plateau and the fracture type.Keywords: knee, tibial plateau, trauma, CT scan, surgery
Procedia PDF Downloads 1481775 Adapting Tools for Text Monitoring and for Scenario Analysis Related to the Field of Social Disasters
Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev
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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters
Procedia PDF Downloads 1971774 Drippers Scaling Inhibition of the Localized Irrigation System by Green Inhibitors Based on Plant Extracts
Authors: Driouiche Ali, Karmal Ilham
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The Agadir region is characterized by a dry climate, ranging from arid attenuated by oceanic influences to hyper-arid. The water mobilized in the agricultural sector of greater Agadir is 95% of underground origin and comes from the water table of Chtouka. The rest represents the surface waters of the Youssef Ben Tachfine dam. These waters are intended for the irrigation of 26880 hectares of modern agriculture. More than 120 boreholes and wells are currently exploited. Their depth varies between 10 m and 200 m and the unit flow rates of the boreholes are 5 to 50 l/s. A drop in the level of the water table of about 1.5 m/year, on average, has been observed during the last five years. Farmers are thus called upon to improve irrigation methods. Thus, localized or drip irrigation is adopted to allow rational use of water. The importance of this irrigation system is due to the fact that water is applied directly to the root zone and its compatibility with fertilization. However, this irrigation system faces a thorny problem which is the clogging of pipes and drippers. This leads to a lack of uniformity of irrigation over time. This so-called scaling phenomenon, the consequences of which are harmful (cleaning or replacement of pipes), leads to considerable unproductive expenditure. The objective set by this work is the search for green inhibitors likely to prevent this phenomenon of scaling. This study requires a better knowledge of these waters, their physico-chemical characteristics and their scaling power. Thus, using the "LCGE" controlled degassing technique, we initially evaluated, on pure calco-carbonic water at 30°F, the scaling-inhibiting power of some available plant extracts in our region of Souss-Massa. We then carried out a comparative study of the efficacy of these green inhibitors. The action of the most effective green inhibitor on real agricultural waters was then studied.Keywords: green inhibitors, localized irrigation, plant extracts, scaling inhibition
Procedia PDF Downloads 831773 Liquid-Liquid Plug Flow Characteristics in Microchannel with T-Junction
Authors: Anna Yagodnitsyna, Alexander Kovalev, Artur Bilsky
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The efficiency of certain technological processes in two-phase microfluidics such as emulsion production, nanomaterial synthesis, nitration, extraction processes etc. depends on two-phase flow regimes in microchannels. For practical application in chemistry and biochemistry it is very important to predict the expected flow pattern for a large variety of fluids and channel geometries. In the case of immiscible liquids, the plug flow is a typical and optimal regime for chemical reactions and needs to be predicted by empirical data or correlations. In this work flow patterns of immiscible liquid-liquid flow in a rectangular microchannel with T-junction are investigated. Three liquid-liquid flow systems are considered, viz. kerosene – water, paraffin oil – water and castor oil – paraffin oil. Different flow patterns such as parallel flow, slug flow, plug flow, dispersed (droplet) flow, and rivulet flow are observed for different velocity ratios. New flow pattern of the parallel flow with steady wavy interface (serpentine flow) has been found. It is shown that flow pattern maps based on Weber numbers for different liquid-liquid systems do not match well. Weber number multiplied by Ohnesorge number is proposed as a parameter to generalize flow maps. Flow maps based on this parameter are superposed well for all liquid-liquid systems of this work and other experiments. Plug length and velocity are measured for the plug flow regime. When dispersed liquid wets channel walls plug length cannot be predicted by known empirical correlations. By means of particle tracking velocimetry technique instantaneous velocity fields in a plug flow regime were measured. Flow circulation inside plug was calculated using velocity data that can be useful for mass flux prediction in chemical reactions.Keywords: flow patterns, hydrodynamics, liquid-liquid flow, microchannel
Procedia PDF Downloads 3961772 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: cost prediction, machine learning, project management, random forest, neural networks
Procedia PDF Downloads 601771 Local Directional Encoded Derivative Binary Pattern Based Coral Image Classification Using Weighted Distance Gray Wolf Optimization Algorithm
Authors: Annalakshmi G., Sakthivel Murugan S.
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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization
Procedia PDF Downloads 1641770 Gnss Aided Photogrammetry for Digital Mapping
Authors: Muhammad Usman Akram
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This research work based on GNSS-Aided Photogrammetry for Digital Mapping. It focuses on topographic survey of an area or site which is to be used in future Planning & development (P&D) or can be used for further, examination, exploration, research and inspection. Survey and Mapping in hard-to-access and hazardous areas are very difficult by using traditional techniques and methodologies; as well it is time consuming, labor intensive and has less precision with limited data. In comparison with the advance techniques it is saving with less manpower and provides more precise output with a wide variety of multiple data sets. In this experimentation, Aerial Photogrammetry technique is used where an UAV flies over an area and captures geocoded images and makes a Three-Dimensional Model (3-D Model), UAV operates on a user specified path or area with various parameters; Flight altitude, Ground sampling distance (GSD), Image overlapping, Camera angle etc. For ground controlling, a network of points on the ground would be observed as a Ground Control point (GCP) using Differential Global Positioning System (DGPS) in PPK or RTK mode. Furthermore, that raw data collected by UAV and DGPS will be processed in various Digital image processing programs and Computer Aided Design software. From which as an output we obtain Points Dense Cloud, Digital Elevation Model (DEM) and Ortho-photo. The imagery is converted into geospatial data by digitizing over Ortho-photo, DEM is further converted into Digital Terrain Model (DTM) for contour generation or digital surface. As a result, we get Digital Map of area to be surveyed. In conclusion, we compared processed data with exact measurements taken on site. The error will be accepted if the amount of error is not breached from survey accuracy limits set by concerned institutions.Keywords: photogrammetry, post processing kinematics, real time kinematics, manual data inquiry
Procedia PDF Downloads 331769 Design and Implementation of Generative Models for Odor Classification Using Electronic Nose
Authors: Kumar Shashvat, Amol P. Bhondekar
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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.Keywords: odor classification, generative models, naive bayes, linear discriminant analysis
Procedia PDF Downloads 3901768 Control of a Quadcopter Using Genetic Algorithm Methods
Authors: Mostafa Mjahed
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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system
Procedia PDF Downloads 4351767 Methicillin Resistant Staphylococcus aureus Specific Bacteriophage Isolation from Sewage Treatment Plant and in vivo Analysis of Phage Efficiency in Swiss Albino Mice
Authors: Pratibha Goyal, Nupur Mathur, Anuradha Singh
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Antibiotic resistance is the worldwide threat to human health in this century. Excessive use of antibiotic after their discovery in 1940 makes certain bacteria to become resistant against antibiotics. Most common antibiotic-resistant bacteria include Staphylococcus aureus, Salmonella typhi, E.coli, Klebsiella pneumonia, and Streptococcus pneumonia. Among all Staphylococcus resistant strain called Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for several lives threatening infection in human commonly found in the hospital environment. Our study aimed to isolate bacteriophage against MRSA from the hospital sewage treatment plant and to analyze its efficiency In Vivo in Swiss albino mice model. Sewage sample for the isolation of bacteriophages was collected from SDMH hospital sewage treatment plant in Jaipur. Bacteriophages isolated by the use of enrichment technique and after characterization, isolated phages used to determine phage treatment efficiency in mice. Mice model used to check the safety and suitability of phage application in human need which in turn directly support the use of natural bacteriophage rather than synthetic chemical to kill pathogens. Results show the plaque formation in-vitro and recovery of MRSA infected mice during the experiment. Favorable lytic efficiency determination of MRSA and Salmonella presents a natural way to treat lethal infections caused by Multidrug-resistant bacteria by using their natural host-pathogen relationship.Keywords: antibiotic resistance, bacteriophages, methicillin resistance Staphylococcus aureus, pathogens, phage therapy, Salmonella typhi
Procedia PDF Downloads 1451766 The Usage of Bridge Estimator for Hegy Seasonal Unit Root Tests
Authors: Huseyin Guler, Cigdem Kosar
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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.Keywords: bridge estimators, HEGY test, model selection, seasonal unit root
Procedia PDF Downloads 3421765 Toxic Masculinity as Dictatorship: Gender and Power Struggles in Tomás Eloy Martínez´s Novels
Authors: Mariya Dzhyoyeva
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In the present paper, I examine manifestations of toxic masculinity in the novels by Tomás Eloy Martínez, a post-Boom author, journalist, literary critic, and one of the representatives of the Argentine writing diaspora. I focus on the analysis of Martínez´s characters that display hypermasculine traits to define the relationship between toxic masculinity and power, including the power of authorship and violence as they are represented in his novels. The analysis reveals a complex network in which gender, power, and violence are intertwined and influence and modify each other. As the author exposes toxic masculine behaviors that generate violence, he looks to undermine them. Departing from M. Kimmel´s idea of masculinity as homophobia, I examine how Martínez “outs” his characters by incorporating into the narrative some secret, privileged sources that provide alternative accounts of their otherwise hypermasculine lives. These background stories expose their “weaknesses,” both physical and mental, and thereby feminize them in their own eyes. In a similar way, the toxic masculinity of the fictional male author that wields his power by abusing the written word as he abuses the female character in the story is exposed as a complex of insecurities accumulated by the character due to his childhood trauma. The artistic technique that Martínez uses to condemn the authoritarian male behavior is accessing his subjectivity and subverting it through a multiplicity of identities. Martínez takes over the character’s “I” and turns it into a host of pronouns with a constantly shifting point of reference that distorts not only the notions of gender but also the very notion of identity. In doing so, he takes the character´s affirmation of masculinity to the limit where the very idea of it becomes unsustainable. Viewed in the context of Martínez´s own exilic story, the condemnation of toxic masculine power turns into the condemnation of dictatorship and authoritarianism.Keywords: gender, masculinity., toxic masculinity, authoritarian, Argentine literature, Martínez
Procedia PDF Downloads 721764 Synthesis of Highly Stable Pseudocapacitors From Secondary Resources
Authors: Samane Maroufi, Rasoul Khayyam Nekouei, Sajjad Mofarah
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Fabrication of the state-of-the-art portable pseudocapacitors with the desired transparency, mechanical flexibility, capacitance, and durability is challenging. In most cases, the fabrication of such devices requires critical elements which are either under the crisis of depletion or their extraction from virgin mineral ores have sever environmental impacts. This urges the use of secondary resources instead of virgin resources in fabrication of advanced devices. In this research, ultrathin films of defect-rich Mn1−x−y(CexLay)O2−δ with controllable thicknesses in the range between 5 nm to 627 nm and transmittance (≈29–100%) have been fabricated via an electrochemical chronoamperometric deposition technique using an aqueous precursor derived during the selective purification of rare earth oxide (REOs) isolated from end-of-life nickel-metal hydride (Ni-MH) batteries. Intercalation/de-intercalation of anionic O2− through the atomic tunnels of the stratified Mn1−x−y(CexLay)O2−δ crystallites was found to be responsible for outstanding areal capacitance of 3.4 mF cm−2 of films with 86% transmittance. The intervalence charge transfer among interstitial Ce/La cations and Mn oxidation states within the Mn1−x−y(CexLay)O2−δ structure resulted in excellent capacitance retention of ≈90% after 16 000 cycles. The synthesised transparent flexible Mn1−x−y(CexLay)O2−δ full-cell pseudocapacitor device possessed the energy and power densities of 0.088 μWh cm⁻² and 843 µW cm⁻², respectively. These values show insignificant changes under vigorous twisting and bending to 45–180° confirming these value-added materials are intriguing alternatives for size-sensitive energy storage devices. This research confirms the feasibility of utilisation of secondary waste resources for the fabrication of high-quality pseudocapacitors with engineered defects with the desired flexibility, transparency, and cycling stability suitable for size-sensitive portable electronic devices.Keywords: pseudocapacitors, energy storage devices, flexible and transparent, sustainability
Procedia PDF Downloads 891763 Anaphora and Cataphora on the Selected State of the City Addresses of the Mayor of Dapitan
Authors: Mark Herman Sumagang Potoy
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State of the City Address (SOCA) is a speech, modelled after the State of the Nation Address, given not as mandated by law but usually a matter of practice or tradition delivered before the chief executive’s constituents. Through this, the general public is made to know the performance of the local government unit and its agenda for the coming year. Therefore, it is imperative for SOCAs to clearly convey its message and carry out the myriad function of enlightening its readers which could be achieved through the proper use of reference. Anaphora and cataphora are the two major types of reference; the former refer back to something that has already been mentioned while the latter points forward to something which is yet to be said. This paper seeks to identify the types of reference employed on the SOCAs from 2014 to 2016 of Hon. Rosalina Garcia Jalosjos, Mayor of Dapitan City and look into how the references contribute to the clarity of the message of the text. The qualitative method of research is used in this study through an in-depth analysis of the corpus. As soon as the copies of the SOCAs are secured from the Office of the City Mayor, they are then analyzed using documentary technique categorizing the types of reference as to anaphora and cataphora, counting each of these types and describing the implications of the dominant types used in the addresses. After a thorough analysis, it is found out that the two reference types namely, anaphora and cataphora are both employed on the three SOCAs, the former being used more frequently than the latter accounting to 80% and 20% of actual usage, respectively. Moreover, the use of anaphors and cataphora on the three addresses helps in conveying the message clearly because they primarily become aids to avoid the repetition of the same element in the text especially when there wasn’t a need to emphasize a point. Finally, it is recommended that writers of State of the City Addresses should have a vast knowledge on how reference should be used and the functions they take in the text since this is a vital tool to clearly transmit a message. Moreover, English teachers should explicitly teach the proper usage of anaphora and cataphora, as instruments to develop cohesion in written discourse, to enable students to write not only with sense but also with fluidity in tying utterances together.Keywords: anaphora, cataphora, reference, State of the City Address
Procedia PDF Downloads 1931762 A Machine Learning Approach for Efficient Resource Management in Construction Projects
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management
Procedia PDF Downloads 401761 Facile Synthesis of Sulfur Doped TiO2 Nanoparticles with Enhanced Photocatalytic Activity
Authors: Vishnu V. Pillai, Sunil P. Lonkar, Akhil M. Abraham, Saeed M. Alhassan
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An effectual technology for wastewater treatment is a great demand now in order to encounter the water pollution caused by organic pollutants. Photocatalytic oxidation technology is widely used in removal of such unsafe contaminants. Among the semi-conducting metal oxides, robust and thermally stable TiO2 has emerged as a fascinating material for photocatalysis. Enhanced catalytic activity was observed for nanostructured TiO2 due to its higher surface, chemical stability and higher oxidation ability. However, higher charge carrier recombination and wide band gap of TiO2 limits its use as a photocatalyst in the UV region. It is desirable to develop a photocatalyst that can efficiently absorb the visible light, which occupies the main part of the solar spectrum. Hence, in order to extend its photocatalytic efficiency under visible light, TiO2 nanoparticles are often doped with metallic or non-metallic elements. Non-metallic doping of TiO2 has attracted much attention due to the low thermal stability and enhanced recombination of charge carriers endowed by metallic doping of TiO2. Amongst, sulfur doped TiO2 is most widely used photocatalyst in environmental purification. However, the most of S-TiO2 synthesis technique uses toxic chemicals and complex procedures. Hence, a facile, scalable and environmentally benign preparation process for S-TiO2 is highly desirable. In present work, we have demonstrated new and facile solid-state reaction method for S-TiO2 synthesis that uses abundant elemental sulfur as S source and moderate temperatures. The resulting nano-sized S-TiO2 has been successfully employed as visible light photocatalyst in methylene blue dye removal from aqueous media.Keywords: ecofriendly, nanomaterials, methylene blue, photocatalysts
Procedia PDF Downloads 3501760 Effects of Foam Rolling with Different Application Volumes on the Isometric Force of the Calf Muscle with Consideration of Muscle Activity
Authors: T. Poppendieker, H. Maurer, C. Segieth
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Over the past ten years, foam rolling has become a new trend in the fitness and health market. It is also a frequently used technique for self-massage. However, the scope of effects from foam rolling has only recently started to be researched and understood. The focus of this study is to examine the effects of prolonged foam rolling on muscle performance. Isometric muscle force was used as a parameter to determine an improving impact of the myofascial roller in two different application volumes. Besides the maximal muscle force, data were also collected on muscle activation during all tests. Twenty-four (17 females, 7 males) healthy students with an average age of 23.4 ± 2.8 years were recruited. The study followed a cross-over pre-/post design in which the order of conditions was counterbalanced. The subjects performed a one-minute and three-minute foam rolling application set on two separate days. Isometric maximal muscle force of the dominant calf was tested before and after the self-myofascial release application. The statistic software program SPSS 22 was used to analyze the data of the maximal isometric force of the calf muscle by a 2 x 2 (time of measurement x intervention) analysis of variance with repeated measures. The statistic significance level was set at p ≤ 0.05. Neither for the main effect of time of measurement (F(1,23) = .93, p = .36, f = .20) nor for the interaction of time of measurement x intervention (F(1,23) = 1.99, p = .17, f = 0.29) significant p-values were found. However, the effect size indicates a mean interaction effect with a tendency of greater pre-post improvements under the three-minute foam rolling condition. Changes in maximal force did not correlate with changes in EMG-activity (r = .02, p = .95 in the short and r = -.11, p = .65 in the long rolling condition). Results support findings of previous studies and suggest a positive potential for use of the foam roll as a means for keeping muscle force at least at the same performance level while leading to an increase in flexibility.Keywords: application volume differences, foam rolling, isometric maximal force, self-myofascial release
Procedia PDF Downloads 2871759 Comparison of Different Artificial Intelligence-Based Protein Secondary Structure Prediction Methods
Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo
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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines
Procedia PDF Downloads 6221758 Modified Weibull Approach for Bridge Deterioration Modelling
Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight
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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models
Procedia PDF Downloads 7291757 A Multi-Scale Study of Potential-Dependent Ammonia Synthesis on IrO₂ (110): DFT, 3D-RISM, and Microkinetic Modeling
Authors: Shih-Huang Pan, Tsuyoshi Miyazaki, Minoru Otani, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang
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Ammonia (NH₃) is crucial in renewable energy and agriculture, yet its traditional production via the Haber-Bosch process faces challenges due to the inherent inertness of nitrogen (N₂) and the need for high temperatures and pressures. The electrocatalytic nitrogen reduction (ENRR) presents a more sustainable option, functioning at ambient conditions. However, its advancement is limited by selectivity and efficiency challenges due to the competing hydrogen evolution reaction (HER). The critical roles of protonation of N-species and HER highlight the necessity of selecting optimal catalysts and solvents to enhance ENRR performance. Notably, transition metal oxides, with their adjustable electronic states and excellent chemical and thermal stability, have shown promising ENRR characteristics. In this study, we use density functional theory (DFT) methods to investigate the ENRR mechanisms on IrO₂ (110), a material known for its tunable electronic properties and exceptional chemical and thermal stability. Employing the constant electrode potential (CEP) model, where the electrode - electrolyte interface is treated as a polarizable continuum with implicit solvation, and adjusting electron counts to equalize work functions in the grand canonical ensemble, we further incorporate the advanced 3D Reference Interaction Site Model (3D-RISM) to accurately determine the ENRR limiting potential across various solvents and pH conditions. Our findings reveal that the limiting potential for ENRR on IrO₂ (110) is significantly more favorable than for HER, highlighting the efficiency of the IrO₂ catalyst for converting N₂ to NH₃. This is supported by the optimal *NH₃ desorption energy on IrO₂, which enhances the overall reaction efficiency. Microkinetic simulations further predict a promising NH₃ production rate, even at the solution's boiling point¸ reinforcing the catalytic viability of IrO₂ (110). This comprehensive approach provides an atomic-level understanding of the electrode-electrolyte interface in ENRR, demonstrating the practical application of IrO₂ in electrochemical catalysis. The findings provide a foundation for developing more efficient and selective catalytic strategies, potentially revolutionizing industrial NH₃ production.Keywords: density functional theory, electrocatalyst, nitrogen reduction reaction, electrochemistry
Procedia PDF Downloads 251756 Development of Immuno-Modulators: Application of Molecular Dynamics Simulation
Authors: Ruqaiya Khalil, Saman Usmani, Zaheer Ul-Haq
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The accurate characterization of ligand binding affinity is indispensable for designing molecules with optimized binding affinity. Computational tools help in many directions to predict quantitative correlations between protein-ligand structure and their binding affinities. Molecular dynamics (MD) simulation is a modern state-of-the-art technique to evaluate the underlying basis of ligand-protein interactions by characterizing dynamic and energetic properties during the event. Autoimmune diseases arise from an abnormal immune response of the body against own tissues. The current regimen for the described condition is limited to immune-modulators having compromised pharmacodynamics and pharmacokinetics profiles. One of the key player mediating immunity and tolerance, thus invoking autoimmunity is Interleukin-2; a cytokine influencing the growth of T cells. Molecular dynamics simulation techniques are applied to seek insight into the inhibitory mechanisms of newly synthesized compounds that manifested immunosuppressant potentials during in silico pipeline. In addition to estimation of free energies associated with ligand binding, MD simulation yielded us a great deal of information about ligand-macromolecule interactions to evaluate the pattern of interactions and the molecular basis of inhibition. The present study is a continuum of our efforts to identify interleukin-2 inhibitors of both natural and synthetic origin. Herein, we report molecular dynamics simulation studies of Interluekin-2 complexed with different antagonists previously reported by our group. The study of protein-ligand dynamics enabled us to gain a better understanding of the contribution of different active site residues in ligand binding. The results of the study will be used as the guide to rationalize the fragment based synthesis of drug-like interleukin-2 inhibitors as immune-modulators.Keywords: immuno-modulators, MD simulation, protein-ligand interaction, structure-based drug design
Procedia PDF Downloads 2621755 Incorporation of Growth Factors onto Hydrogels via Peptide Mediated Binding for Development of Vascular Networks
Authors: Katie Kilgour, Brendan Turner, Carly Catella, Michael Daniele, Stefano Menegatti
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In vivo, the extracellular matrix (ECM) provides biochemical and mechanical properties that are instructional to resident cells to form complex tissues with characteristics to develop and support vascular networks. In vitro, the development of vascular networks can be guided by biochemical patterning of substrates via spatial distribution and display of peptides and growth factors to prompt cell adhesion, differentiation, and proliferation. We have developed a technique utilizing peptide ligands that specifically bind vascular endothelial growth factor (VEGF), erythropoietin (EPO), or angiopoietin-1 (ANG1) to spatiotemporally distribute growth factors to cells. This allows for the controlled release of each growth factor, ultimately enhancing the formation of a vascular network. Our engineered tissue constructs (ETCs) are fabricated out of gelatin methacryloyl (GelMA), which is an ideal substrate for tailored stiffness and bio-functionality, and covalently patterned with growth factor specific peptides. These peptides mimic growth factor receptors, facilitating the non-covalent binding of the growth factors to the ETC, allowing for facile uptake by the cells. We have demonstrated in the absence of cells the binding affinity of VEGF, EPO, and ANG1 to their respective peptides and the ability for each to be patterned onto a GelMA substrate. The ability to organize growth factors on an ETC provides different functionality to develop organized vascular networks. Our results demonstrated a method to incorporate biochemical cues into ETCs that enable spatial and temporal control of growth factors. Future efforts will investigate the cellular response by evaluating gene expression, quantifying angiogenic activity, and measuring the speed of growth factor consumption.Keywords: growth factor, hydrogel, peptide, angiogenesis, vascular, patterning
Procedia PDF Downloads 1651754 Bibliometric Analysis of Risk Assessment of Inland Maritime Accidents in Bangladesh
Authors: Armana Huq, Wahidur Rahman, Sanwar Kader
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Inland waterways in Bangladesh play an important role in providing comfortable and low-cost transportation. However, a maritime accident takes away many lives and creates unwanted hazards every year. This article deals with a comprehensive review of inland waterway accidents in Bangladesh. Additionally, it includes a comparative study between international and local inland research studies based on maritime accidents. Articles from inland waterway areas are analyzed in-depth to make a comprehensive overview of the nature of the academic work, accident and risk management process and different statistical analyses. It is found that empirical analysis based on the available statistical data dominates the research domain. For this study, major maritime accident-related works in the last four decades in Bangladesh (1981-2020) are being analyzed for preparing a bibliometric analysis. A study of maritime accidents of passenger's vessels during (1995-2005) indicates that the predominant causes of accidents in the inland waterways of Bangladesh are collision and adverse weather (77%), out of which collision due to human error alone stands (56%) of all accidents. Another study refers that the major causes of waterway accidents are the collision (60.3%) during 2005-2015. About 92% of this collision occurs due to direct contact with another vessel during this period. Rest 8% of the collision occurs by contact with permanent obstruction on waterway roots. The overall analysis of another study from the last 25 years (1995-2019) shows that one of the main types of accidents is collisions, with about 50.3% of accidents being caused by collisions. The other accident types are cyclone or storm (17%), overload (11.3%), physical failure (10.3%), excessive waves (5.1%), and others (6%). Very few notable works are available in testing or comparing the methods, proposing new methods for risk management, modeling, uncertainty treatment. The purpose of this paper is to provide an overview of the evolution of marine accident-related research domain regarding inland waterway of Bangladesh and attempts to introduce new ideas and methods to abridge the gap between international and national inland maritime-related work domain which can be a catalyst for a safer and sustainable water transportation system in Bangladesh. Another fundamental objective of this paper is to navigate various national maritime authorities and international organizations to implement risk management processes for shipping accident prevention in waterway areas.Keywords: inland waterways, safety, bibliometric analysis, risk management, accidents
Procedia PDF Downloads 1841753 Impact of Leadership Styles on Work Motivation and Organizational Commitment among Faculty Members of Public Sector Universities in Punjab
Authors: Wajeeha Shahid
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The study was designed to assess the impact of transformational and transactional leadership styles on work motivation and organizational commitment among faculty members of universities of Punjab. 713 faculty members were selected as sample through convenient random sampling technique. Three self-constructed questionnaires namely Leadership Styles Questionnaire (LSQ), Work Motivation Questionnaire (WMQ) and Organizational Commitment Questionnaire (OCMQ) were used as research instruments. Major objectives of the study included assessing the effect and impact of transformational and transactional leadership styles on work motivation and organizational commitment. Theoretical frame work of the study included Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Contingent Rewards and Management by Exception as independent variables and Extrinsic motivation, Intrinsic motivation, Affective commitment, Continuance commitment and Normative commitment as dependent variables. SPSS Version 21 was used to analyze and tabulate data. Cronbach's Alpha reliability, Pearson Correlation and Multiple regression analysis were applied as statistical treatments for the analysis. Results revealed that Idealized Influence correlated significantly with intrinsic motivation and Affective commitment whereas Contingent rewards had a strong positive correlation with extrinsic motivation and affective commitment. Multiple regression models revealed a variance of 85% for transformational leadership style over work motivation and organizational commitment. Whereas transactional style as a predictor manifested a variance of 79% for work motivation and 76% for organizational commitment. It was suggested that changing organizational cultures are demanding more from their leadership. All organizations need to consider transformational leadership style as an important part of their equipment in leveraging both soft and hard organizational targets.Keywords: leadership styles, work motivation, organizational commitment, faculty member
Procedia PDF Downloads 3111752 Co-Creational Model for Blended Learning in a Flipped Classroom Environment Focusing on the Combination of Coding and Drone-Building
Authors: A. Schuchter, M. Promegger
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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning
Procedia PDF Downloads 1221751 Effect of Concentration Level and Moisture Content on the Detection and Quantification of Nickel in Clay Agricultural Soil in Lebanon
Authors: Layan Moussa, Darine Salam, Samir Mustapha
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Heavy metal contamination in agricultural soils in Lebanon poses serious environmental and health problems. Intensive efforts are employed to improve existing quantification methods of heavy metals in contaminated environments since conventional detection techniques have shown to be time-consuming, tedious, and costly. The implication of hyperspectral remote sensing in this field is possible and promising. However, factors impacting the efficiency of hyperspectral imaging in detecting and quantifying heavy metals in agricultural soils were not thoroughly studied. This study proposes to assess the use of hyperspectral imaging for the detection of Ni in agricultural clay soil collected from the Bekaa Valley, a major agricultural area in Lebanon, under different contamination levels and soil moisture content. Soil samples were contaminated with Ni, with concentrations ranging from 150 mg/kg to 4000 mg/kg. On the other hand, soil with background contamination was subjected to increased moisture levels varying from 5 to 75%. Hyperspectral imaging was used to detect and quantify Ni contamination in the soil at different contamination levels and moisture content. IBM SPSS statistical software was used to develop models that predict the concentration of Ni and moisture content in agricultural soil. The models were constructed using linear regression algorithms. The spectral curves obtained reflected an inverse correlation between both Ni concentration and moisture content with respect to reflectance. On the other hand, the models developed resulted in high values of predicted R2 of 0.763 for Ni concentration and 0.854 for moisture content. Those predictions stated that Ni presence was well expressed near 2200 nm and that of moisture was at 1900 nm. The results from this study would allow us to define the potential of using the hyperspectral imaging (HSI) technique as a reliable and cost-effective alternative for heavy metal pollution detection in contaminated soils and soil moisture prediction.Keywords: heavy metals, hyperspectral imaging, moisture content, soil contamination
Procedia PDF Downloads 1011750 Efficacy of Phonological Awareness Intervention for People with Language Impairment
Authors: I. Wardana Ketut, I. Suparwa Nyoman
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This study investigated the form and characteristic of speech sound produced by three Balinese subjects who have recovered from aphasia as well as intervened their language impairment on side of linguistic and neuronal aspects of views. The failure of judging the speech sound was caused by impairment of motor cortex that indicated there were lesions in left hemispheric language zone. Sound articulation phenomena were in the forms of phonemes deletion, replacement or assimilation in individual words and meaning building for anomic aphasia. Therefore, the Balinese sound patterns were stimulated by showing pictures to the subjects and recorded to recognize what individual consonants or vowels they unclearly produced and to find out how the sound disorder occurred. The physiology of sound production by subject’s speech organs could not only show the accuracy of articulation but also any level of severity the lesion they suffered from. The subjects’ speech sounds were investigated, classified and analyzed to know how poor the lingual units were and observed to clarify weaknesses of sound characters occurred either for place or manner of articulation. Many fricative and stopped consonants were replaced by glottal or palatal sounds because the cranial nerve, such as facial, trigeminal, and hypoglossal underwent impairment after the stroke. The phonological intervention was applied through a technique called phonemic articulation drill and the examination was conducted to know any change has been obtained. The finding informed that some weak articulation turned into clearer sound and simple meaning of language has been conveyed. The hierarchy of functional parts of brain played important role of language formulation and processing. From this finding, it can be clearly emphasized that this study supports the role of right hemisphere in recovery from aphasia is associated with functional brain reorganization.Keywords: aphasia, intervention, phonology, stroke
Procedia PDF Downloads 1961749 Disparities in Language Competence and Conflict: The Moderating Role of Cultural Intelligence in Intercultural Interactions
Authors: Catherine Peyrols Wu
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Intercultural interactions are becoming increasingly common in organizations and life. These interactions are often the stage of miscommunication and conflict. In management research, these problems are commonly attributed to cultural differences in values and interactional norms. As a result, the notion that intercultural competence can minimize these challenges is widely accepted. Cultural differences, however, are not the only source of a challenge during intercultural interactions. The need to rely on a lingua franca – or common language between people who have different mother tongues – is another important one. In theory, a lingua franca can improve communication and ease coordination. In practice however, disparities in people’s ability and confidence to communicate in the language can exacerbate tensions and generate inefficiencies. In this study, we draw on power theory to develop a model of disparities in language competence and conflict in a multicultural work context. Specifically, we hypothesized that differences in language competence between interaction partners would be positively related to conflict such that people would report greater conflict with partners who have more dissimilar levels of language competence and lesser conflict with partners with more similar levels of language competence. Furthermore, we proposed that cultural intelligence (CQ) an intercultural competence that denotes an individual’s capability to be effective in intercultural situations, would weaken the relationship between disparities in language competence and conflict such that people would report less conflict with partners who have more dissimilar levels of language competence when the interaction partner has high CQ and more conflict when the partner has low CQ. We tested this model with a sample of 135 undergraduate students working in multicultural teams for 13 weeks. We used a round-robin design to examine conflict in 646 dyads nested within 21 teams. Results of analyses using social relations modeling provided support for our hypotheses. Specifically, we found that in intercultural dyads with large disparities in language competence, partners with the lowest level of language competence would report higher levels of interpersonal conflict. However, this relationship disappeared when the partner with higher language competence was also high in CQ. These findings suggest that communication in a lingua franca can be a source of conflict in intercultural collaboration when partners differ in their level of language competence and that CQ can alleviate these effects during collaboration with partners who have relatively lower levels of language competence. Theoretically, this study underscores the benefits of CQ as a complement to language competence for intercultural effectiveness. Practically, these results further attest to the benefits of investing resources to develop language competence and CQ in employees engaged in multicultural work.Keywords: cultural intelligence, intercultural interactions, language competence, multicultural teamwork
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