Search results for: training programs

Authors: V. Mantey, N. Findlay, I. Maddox

Abstract:

The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

Procedia PDF Downloads 169

Authors: Mohamed Mokhtar, Mostafa F. Shaaban

Abstract:

Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

Procedia PDF Downloads 144

Authors: Oladimeji Adetona Adeyeye, Emmanuel Rotimi Sadiku, Oluwaseun Olayinka Adeyeye

Abstract:

In order to resuscitate soybean production and post-harvest processing especially, in term of threshing, there is need to develop an affordable threshing machine which will reduce drudgery associated with manual soybean threshing. Soybean thresher was fabricated and evaluated at Institute of Agricultural Research and Training IAR&T Apata Ibadan. The machine component includes; hopper, threshing unit, shaker, cleaning unit and the seed outlet, all working together to achieve the main objective of threshing and cleaning. TGX1835 - 10E variety was used for evaluation because of its high resistance to pests, rust and pustules. The final moisture content of the used sample was about 15%. The sample was weighed and introduced into the machine. The parameters evaluated includes moisture content, threshing efficiency, cleaning efficiency, machine capacity and speed. The threshing efficiency and capacity are 74% and 65.9kg/hr respectively. All materials used were sourced locally which makes the cost of production of the machine extremely cheaper than the imported soybean thresher.

Keywords: efficiency, machine capacity, speed, soybean, threshing

Procedia PDF Downloads 485

Authors: Ana Maghfiroh

Abstract:

Learning a foreign language needs a big effort from the learner itself to make their language ability grows better day by day. Among those, they also need a support from all around them including teacher, friends, as well as activities which support them to speak the language. When those activities developed well as a habit which are done regularly, it will help improving the students’ language competence. It was a qualitative research which aimed to find out and describe some activities implemented in Pesantren Al Mawaddah, Ponorogo, in order to teach the students a foreign language. In collecting the data, the researcher used interview, questionnaire, and documentation. From the study, it was found that Pesantren Al Mawaddah had successfully built the language habit on the students to speak the target language. More than 15 hours a day students were compelled to speak foreign language, Arabic or English, in turn. It aimed to habituate the students to keep in touch with the target language. The habit was developed through daily language activities, such as dawn vocabs giving, dictionary handling, daily language use, speech training and language intensive course, daily language input, and night vocabs memorizing. That habit then developed the students awareness towards the language learned as well as promoted their language mastery.

Keywords: habit, communicative competence, daily language activities, Pesantren

Procedia PDF Downloads 539

Authors: Lenka Mynaříková, Hedvika Boukalová

Abstract:

The study looks at the ability to detect nonverbal deception among police officers and management students in the Czech Republic. Respondents from police departments (n=197) and university students of human resources (n=161) completed a deception detection task and evaluated veracity of the statements of suspects in 21 video clips from real crime investigations. Their evaluations were based on nonverbal behavior. Voices in the video clips were modified so that words were not recognizable, yet paraverbal voice characteristics were preserved. Results suggest that respondents have a tendency to lie bias based on their profession. In the evaluation of video clips, stereotypes also played a significant role. The statements of suspects of a different ethnicity, younger age or specific visual features were considered deceitful more often. Research might be beneficial for training in professions that are in need of deception detection techniques.

Keywords: deception detection, police officers, human resources, forensic psychology, forensic studies, organizational psychology

Procedia PDF Downloads 431

Authors: Anas H. Aljemely, Jianping Xuan

Abstract:

Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

Procedia PDF Downloads 210

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

Procedia PDF Downloads 253

Authors: Gaurav Sancheti

Abstract:

This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

Procedia PDF Downloads 221

Authors: Stephen O. Amaraihu

Abstract:

This research investigated the effect of Computer Based Instruction on Students’ interest, achievement, and retention in Algebra in Abia State College of Education (Technical), Arochukwu. Three research questions and two hypotheses guided the study. Two instruments, Maths Achievement Test (MAT) and Maths Interest Inventory were employed, to test a population of three hundred and sixteen (316) NCE 1 students in algebra. It is expected that this research will lead to the improvement of students’ performance and enhance their interest and retention of basic algebraic concept. It was found that the majority of students in the college are not proficient in the use of ICT as a result of a lack of trained personnel. It was concluded that the state government was not ready to implement the usage of mathematics in Abia State College of Education. The paper recommends, amongst others, the employment of mathematics Lectures with competent skills in ICT and the training of lecturers of mathematics.

Keywords: achievement, computer based instruction, interest, retention

Procedia PDF Downloads 209

Authors: Kerem Rızvanoglu, Serhat Güney, Betül Aydoğan, Emre Kızılkaya, Ayşegül Boyalı, Onurcan Güden

Abstract:

This study investigates the urban experience of international students coming to Istanbul with exchange programs and reveals how locative media applications accompany their urban experiences. The sample of the research consists of international students who lived, perceived, and conceived the city on a daily basis during the academic year of 2022. Focusing on this particular sample would demonstrate the opportunities and authentic experiences offered by the city as well as the prevalent urban problems for the foreigners. In this regard, international students' urban experience in Istanbul, the blockages they encounter as resident tourists, the hotspots that the city offers, and the role of locative media in enriching the urban experience are the main axes to be evaluated. In the first step of the multi-staged research, we conduct an online qualitative survey with a sample; then, we evaluate the data obtained from the survey using cluster analysis to identify the urban experience, consumption habits, and tastes. In the final stage, digital ethnographic fieldwork will be carried out with representative personas identified by the cluster analysis. With this field research on the urban experience accompanied by locative media applications, suggestions will be developed by evaluating the opportunities these applications offer to enrich the urban practice of foreigners.

Keywords: digital ethnography, international students, locative media applications, urban experience

Procedia PDF Downloads 140

Authors: Aparajita Mukherjee, D. P. Mukherjee

Abstract:

This paper critically assessed pollution problems in small and medium enterprises with unique references to foundries and sponge iron industries to survey the adverse impact on human societies and the environment. The objective of this paper was to show how cleaner production concept was implemented in one foundry through improvisation of existing technology in India. Incremental advancement of existing technology minimized environmental issues and resource utilization. This study depicted that poor fiscal help, poor enforcement of government regulations, owners’ attitude and lacking specialized technical workers were the significant hindrances towards cleaner production. The paper explored the possible ways to overcome these hindrances for cleaner production. On a more general level, findings raise important questions regarding the need for a new paradigm for the implementation of cleaner production. Improvisation of existing technology in these enterprises would be cost effective towards sustainable development.

Keywords: SME pollution, ecological crisis, sustainable development, cleaner production, training

Procedia PDF Downloads 373

Authors: M. A. Fernández-Vilar, M. D. Galián, E. Ato

Abstract:

The aim of this work was to analyze the relation between children´s effortful control and Maths achievement in a sample of 447 Spanish children aged between 6 and 8 years. Traditionally, the literature confirms that higher level of effortful control has been associated with higher academic achievement, but there are few studies that include the effect that children´s social competence exert to this relation. To measure children’s effortful control parents were given the TMCQ (Temperament in Middle Childhood Questionnaire), and Maths achievement was taken from teacher´s rates. To measure social competence, we used the nominations method in the classroom context. Results confirmed that higher effortful control predicted a better maths achievement, whereas lower effortful control scores predicted lower Maths scores. Using a statistical modeling approach, we tested a mediation model that revealed the mediating role of social competence (popularity and rejection) in the relation between effortful control and Maths achievement. Concretely, higher social competence (higher popularity and lower rejection) seems to mediate the better Maths achievement showed by better self´regulated children. Therefore, an adequate social competence mediates the positive effect that self-regulatory capacity exerts to academic achievement. The clinical implications of the present findings should be considered. Specifically, rejected children must be detected and evaluated in community settings, such as school or community programs, due the relevant role of social competence in the relation between temperament and academic achievement.

Keywords: effortful control, maths achievement, social competence, mediation

Procedia PDF Downloads 389

Authors: Yusra A. Ibrahim

Abstract:

Educational efforts to address the school-to-prison pipeline (STPP) and retain students in school require equipping teachers with evidence-based approaches to handle social-emotional behavior (SEB) needs. One aspect of these efforts involves training teachers to utilize effective and current technologies, thereby reducing SEB challenges faced by students with disabilities in their classrooms. This literature review examines eight studies conducted within the past 10 years (from 2013 to 2023) that focus on enhancing SEB needs of students with disabilities using technology. The review reveals that autism spectrum disorder (ASD), emotional behavioral disorder (EBD), and attention deficit and hyperactivity disorder (ADHD) are the predominant disabilities studied through technology interventions. Additionally, it highlights that these studies focused on examining the effectiveness of technologies in reducing disruptive behaviors, increasing on-task behaviors, reducing anxiety, and promoting social skills.

Keywords: school-to-prison pipeline, technology, evidence-based practices, EBD

Procedia PDF Downloads 68

Authors: Gabriel Jinga, Madalina Dumitru

Abstract:

The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalization of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modeled by the contingencies specific to this company (e.g. environment, industry, strategy).

Keywords: management accounting, change, Romania, contingency, institutional theory

Procedia PDF Downloads 516

Authors: Mera Ababneh, Sayer Al-Azzam, Karem Alzoubi, Abeer Rababa'h

Abstract:

Background: Medication errors are among the most common medical errors. Their occurrences result in patient’s mortality, morbidity, and additional healthcare costs. Continuous monitoring and detection is required. Objectives: The aim of this study was to compare medication errors in outpatient’s prescriptions in two different hospitals (paper system vs. electronic system). Methods: This was a cross sectional observational study conducted in two major hospitals; King Abdullah University Hospital (KAUH) and Princess Bassma Teaching Hospital (PBTH) over three months period. Data collection was conducted by two trained pharmacists at each site. During the study period, medication prescriptions and dispensing procedures were screened for medication errors in both participating centers by two trained pharmacist. Results: In the electronic prescription hospital, 2500 prescriptions were screened in which 631 medication errors were detected. Prescription errors were 231 (36.6%), and dispensing errors were 400 (63.4%) of all errors. On the other side, analysis of 2500 prescriptions in paper-based hospital revealed 3714 medication errors, of which 288 (7.8%) were prescription errors, and 3426 (92.2%) were dispensing errors. A significant number of 2496 (67.2%) were inadequately and/or inappropriately labeled. Conclusion: This study provides insight for healthcare policy makers, professionals, and administrators to invest in advanced technology systems, education, and epidemiological surveillance programs to minimize medication errors.

Keywords: medication errors, prescription errors, dispensing errors, electronic prescription, handwritten prescription

Procedia PDF Downloads 282

Authors: Noel Busch-Armendariz, Caitlin Sulley

Abstract:

Introduction: This study investigated the development of college experiences, COVID-19 pandemic experiences, alcohol use, and sexual violence. The longitudinal study includes 656 college students living in the same dormitory. Students' alcohol use and social network structure were investigated to better understand the relationship with sexual violence risk. Basic Methodologies: Over two years, students repeated five web-based surveys, including a pre-college survey and surveys during four consecutive semesters. Questions were added in the fourth wave to assess students’ experiences of the COVID-19 pandemic, administered from November-January 2021, including mental and behavioral health. Analyses include the impact of COVID on living arrangements, drinking behaviors, and daily life; experiences of COVID symptoms, testing, and diagnosis, responses to COVID such as social distancing, quarantining, not working, increased health care needs; experience of fear, worry, stigma, emotional well-being, loneliness, and mental health; experiences of financial loss, lack of basic supplies, receiving emotional and financial support, and comparison with academic disengagement. Concluding Statement: Findings and discussion will include strategies to strengthen mental and behavioral health programs and policies.

Keywords: COVID, mental health, substance abuse, college students, sexual misconducts

Procedia PDF Downloads 79

Authors: Arowosafe Folusade Catherine, Arowosafe Olubunmi, Aina Samson

Abstract:

In many countries, tourism has been portrayed as a contributor to small-scale enterprises, contributing to improved standards of living, a catalyst for community development, and poverty alleviation. This study assessed the willingness of the host communities to provide homestay accommodation and also identified the homestay facilities available to host visitors to the community. A random sampling method was used to administer 150 copies of the questionnaire to the residents in Idanre. Data collected were subjected to descriptive and inferential statistical analysis, and results were presented using frequency and percentage tables. Results: Findings revealed that the majority of the residents were above 60 years (47.3%), with 33% of them aware of the concept of homestay accommodation, and 32% had primary education. The majority were self-employed (43.3%), earning less than ₦30,000 per month; it also revealed that 80.7% of the residents owned at least one house and had adequate water supply facility (100%) and electricity (99.3%). Some constraints observed revealed that safety for the host family (mean 4.81) was ranked high as a possible deterrent to providing homestay accommodation to strangers. Results revealed a correlation between the resident’s awareness and willingness to provide homestay accommodation services (r.0.05, p<0.05). This study recommends that sensitization programs to create awareness of the potential benefits of homestay accommodation in the host communities of Idanre Hills should be carried out by the relevant stakeholders.

Keywords: accommodation, benefits, homestay, Idanre Hills

Procedia PDF Downloads 69

Authors: Asmaa Shehata

Abstract:

Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.

Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning

Procedia PDF Downloads 256

Authors: Ashish James, Anusha James

Abstract:

The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

Procedia PDF Downloads 135

Authors: E. Montesinos-Pedro, L. G. Toscano-Flores, N. Domínguez-Ramírez

Abstract:

Water scarcity is a worldwide issue, coupled with climate change is a relevant problem, that affect not only large cities, but also rural areas. The Municipality of Santiago Tilantongo belongs to the district of Nochixtlán Oaxaca, it’s built up from 14 communities, one of them San Martin de las Palmas. This community was founded in 1900, at that time the inhabitants were supplied with water through rivers of the region which were abundant (they used containers filled in the river for that purpose); However, over the years the level of the rivers began to drop and in 1994 specific wells were located to store water and at the same time make it drinkable, this whit support of the state of Oaxaca and the program Procampo. By the year 2000 the shortage of water in the supply sources was notorious, the community requested support from the Oaxaca State government to solve the problem. The government’s response consisted in the implementation of ferro-cement tanks (2005) and water wells (2010), both for rainwater collection, Hower, it was not enough. Now days the community has a population of 60 inhabitants who have resisted and adapted to water scarcity, not only with the programs implemented by the government, but they also have implemented important structural analysis strategies. The objective of this research is to know the adaptation strategies used by the community to analyze them and propose improvements for water conservation and mitigation of this scarcity.

Keywords: adaptation, climate change, mitigation, resiliencia

Procedia PDF Downloads 97

Authors: L. Arumuru

Abstract:

The paper investigates computer anxiety and the use of computerized library system by university librarians in Delta State University library, Abraka, Nigeria. Some of the root causes of computer anxiety among university librarians such as lack of exposure to computers at early age, inadequate computer skills, inadequate computer training, fear at the sight of a computer, lack of understanding of how computers work, etc. were pin-pointed in the study. Also, the different services rendered in the university libraries with the aid of computers such as reference services, circulation services, acquisition services, cataloguing and classification services, etc. were identified. The study employed the descriptive survey research design through the expo-facto method, with a population of 56 librarians, while the simple percentage and frequency counts were used to analyze the data generated from the administered copies of the questionnaire. Based on the aforementioned root causes of computer anxiety and the resultant effect on computerized library system, recommendations were proffered in the study.

Keywords: computer anxiety, computerized library system, library services, university librarians

Procedia PDF Downloads 387

Authors: Anat Yaron Antar, Tomer Einat

Abstract:

This study explores the effects of the imprisonment of women together with females with mental disorders on the well-being of the former both during imprisonment and after their release from prison. Based on in-depth interviews with 22 women ex-prisoners who had been imprisoned for a period of at least two years in the single Israeli female correctional facility, Neve Tirza Prison, and released one to three months before the initiation of the study to a community-based agency managed by the Israeli Prisoner Rehabilitation Authority, and based on a qualitative, constructive strategy. We found that: (i) mentally ill prisoners’ conduct creates severe feelings of stress and discomfort among many of the prisoners without a mental disorder prisoners; (ii) The intimate and often long-term encounters with prisoners with a mental illness lead to increased feelings of distress, helplessness, fear, and frustration among many of the women prisoners; (iii) the damaging encounters between women prisoners and mentally-ill prisoners harmed the reintegration of the formers into society after release, and (iv) The women ex-prisoners lacked the basic mental, cognitive, and social tools necessary for dealing with female inmates with a mental illness and had received no psychological or emotional support from the prison personnel. Consequently, they suffered – and still suffer – from traumatic and upsetting memories Our findings led us to conclude that women prisoners should be imprisoned separately from female prisoners with mental disorders or be offered a wide range of psychological and emotional coping tools as well as various rehabilitative treatment programs.

Keywords: women, prisoners, mentally ill, health

Procedia PDF Downloads 127

Authors: Eltaib Elzarrouk E. E. Abdalmajeed

Abstract:

This research aims at shedding the light on environmental accounting, which is considered to be one of the most important areas in accounting discipline. It also studies the reality of the application of environmental accounting in the iron and steel sector in Libya. The questionnaire of this study was used for data collection from respondents who are employed in the Libyan Iron and Steel Company, Misurata – Libya (LISC). The Statistical Package for Social Sciences (SPSS) was also used for the analysis. Several important results were revealed include that the (LISC) relatively applies environmental accounting, and it faces some obstacles in conducting its application. Furthermore, the researched company realizes the importance of applying environmental accounting as a need for quality procedures. It was suggested that training courses should be held periodically to spread the awareness of environmental accounting environment. In addition, social responsibility and sustainability should be taken into consideration in the company's strategic plan.

Keywords: environment, environmental accounting, environmental accounting disclosure, The Libyan Iron and Steel Company, Misurata- Libya (LISC)

Procedia PDF Downloads 152

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

Abstract:

Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

Procedia PDF Downloads 92

Authors: Carrollyne Aasen, Laverne Seales

Abstract:

With increased Latinx communities within the United States, specifically in California, and more universities receiving designations of Hispanic-Serving institutions, Spanish programs have evolved to include more targeted and applicable practical skills. The Spanish program in the Languages and Cultures Department at California Lutheran University incorporated an interdisciplinary project with the Communication Department to create student-generated Spanish-language news inserts, which serve as a sister publication to the English-language student newspaper, The Echo. California Lutheran University is a Hispanic-Serving Institution, meaning it is an accredited undergraduate institution with full-time Hispanic/Latinx students equivalent to at least 25 percent of the total students enrolled. As a Hispanic Serving Institution with growing numbers of bilingual students, faculty, staff, and community members, the need for more information aimed at Hispanic/Latinx communities increased, resulting in the opportunity to reflect topics of interest by community members. This project was developed to fulfill the Spanish program's goals for proficiency by using the American Council on the Teaching of Foreign Languages guidelines and the university's need to support students and the community's voices. This article describes the stages from inception to production and the incorporation of journalism principles into the Spanish curriculum.

Keywords: interdisciplinary, media, foreign languages, HSI

Procedia PDF Downloads 69

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

Abstract:

With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

Procedia PDF Downloads 447

Authors: Shilpa Vasavada

Abstract:

One of the 17 SustainableDevelopmentGoals focuses on gender equality. The paper is based on the learning derived from working with two Corporate Social Responsibility cases in India: one, CSR of an International Corporate and the other, CSR of a multi state national level corporate -on their efforts to integrate gender perspective in their agriculture and livestock based rural livelihood programs. The author tries to dissect how ‘gender equality’ is seen by these two CSRs, where the goals are different. The implications of a CSR’sunderstandingon ‘gender equality’ as a goal; versus CSR’s understanding of working 'with women for enhancing quantity or quality of production’ gets reflected in their orientation to staff, resource allocation, strategic level and in processes followed at the rural grassroots level. The paper comes up with examples of changes made at programmatic front when CSR understands and works with the focus on gender equality as a goal. On the other hand, the paper also explores the differential, at times, the negative impact on women and the programmes;- when the goals differ. The paper concludes with recommendations for CSRs to take up at their resource allocation and strategic level if gender equality is the goal- which has direct implication at their grassroots programmatic work. The author argues that if gender equality has to be implemented actually in spirit by a CSR, it requires change in mindset and thus an openness to changes in strategies and resource allocation pattern of the CSR and not simply adding on women in the way intervention has been going on.

Keywords: gender equality, approaches, differential impact, resource allocation

Procedia PDF Downloads 196

Authors: Charles Rutikanga

Abstract:

As part of the effort to reconstruct Rwanda and foster a shared national identity after the 1994 genocide against Tutsi, the government of Rwanda has drawn on aspects of indigenous culture and traditional practices. One of these traditional practices and cultural values is Ubudehe, which has been re-introduced after it has been gradually lost since colonial times. It is a form of collective action at the village level, which is inclusive, covering men, women, and the most marginalized community members. The philosophy behind Ubudehe is to increase the level of participation and institutional problem-solving capacity at the local level by citizens and local government. Since the early 2000s, the government re-introduced Ubudehe as a neo-traditional cultural institution in order to support the implementation of the country’s poverty reduction and development programs. An empirical study on indigenous and innovative models of social work practice was conducted under the framework of the ‘Professional Social Work in East Africa’ (PROSOWO II) project. Field data were collected on traditional/indigenous approaches, including Ubudehe, from different categories of informants through focus group discussions (FGDs) and personal interviews. The research showed that professional social workers play a significant role in the whole Ubudehe process. While there have been some challenges in the administration and implementation, overall it has contributed to poverty reduction in a post-genocide Rwanda.

Keywords: development, indigenous approach, social work, Ubudehe

Procedia PDF Downloads 117

Authors: Ardalan Tofighi Soleimandarabi

Abstract:

Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

Procedia PDF Downloads 15

Authors: Ugbor Raphael Oluchukwu

Abstract:

The survey research design was adopted to examine whether liquidity and cash management practices of owner-managed firms in South East Nigeria influence their profitability, growth and survival. Four independent variables (accounting systems, working capital management, budgetary control, and managerial planning) were used in the evaluation which was restricted to eight small firms. Results indicate that one variable, working capital management alone dominate the liquidity perception of owner managers. As a result, owner managers find it difficult to meet maturing business obligations as growth sets in. The study also reveals that the four independent variables have significant impact on the profitability, growth and survival of owner managed firms. Owner managers are therefore advised to undertake regular entrepreneurship training in order to upgrade their liquidity and cash management knowledge and practices to enhance their overall performance.

Keywords: liquidity management, owner-managed firm, profitability, survival

Procedia PDF Downloads 430