Search results for: learning and teaching

Authors: Jacob Wahl, Jane Zhang

Abstract:

This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 138

Authors: David Ross Cameron

Abstract:

In an attempt to alleviate the educational planning problem, double-shift schools have been created throughout various regions in Jordan, namely communities closer to the Syrian border, where a large portion of the refugee population settled, allowing Jordanians to attend the morning-shift and Syrians to attend the afternoon-shift. Subsequently, overcrowded classrooms have added a significant amount of stress on school facilities and teacher capacities. Established national policies and the implementation of inclusive educational practices have been jeopardized. In particular, teachers’ and student’s attitudes of the importance of inclusive education provisions in the classroom have deteriorated. To have a more comprehensive understanding of the current situation and possible plan for intervention, a focus study was carried out at a double-shift Jordanian/Syrian girls’ public school in Irbid, Jordan. Interviews and surveys of 29 students with physical, learning, emotional and behavioral disabilities, 33 students without any special needs and nine teachers were included with a mixed-method social research approach to highlight the current attitudes that students and teachers held and factors that contributed to shaping their inclinations and beliefs of inclusive education.

Keywords: capacity building, development, double-shift, Irbid, inclusive education, Jordan, pedagogy, planning, policy, refugee, special education, special needs, vulnerable population

Procedia PDF Downloads 255

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

Abstract:

Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

Procedia PDF Downloads 123

Authors: Robson da Cunha Santos, Caio Cezar R. Bonifacio, Diego Mureb Quesada, Gerson Gomes Cunha

Abstract:

The paper is related to the safety of oil wells and environmental preservation on the planet, because they require great attention and commitment from oil companies and people who work with these equipments. This must occur from drilling the well until it is abandoned in order to safeguard the environment and prevent possible damage. The project had as main objective the constitution resulting from comparatives made among books, articles and publications with information gathered in technical visits to operational bases of Petrobras. After the visits, the information from methods of utilization and present managements, which were not available before, became available to the general audience. As a result, it is observed a huge flux of incorrect and out-of-date information that comprehends not only bibliographic archives, but also academic resources and materials. During the gathering of more in-depth information on the manufacturing, assembling, and use aspects of DHSVs, several issues that were previously known as correct, customary issues were discovered to be uncertain and outdated. Information of great importance resulted in affirmations about subjects as the depth of the valve installation that was before installed to 30 meters from the seabed (mud line). Despite this, the installation should vary in conformity to the ideal depth to escape from area with the biggest tendency to hydrates formation according to the temperature and pressure. Regarding to valves with nitrogen chamber, in accordance with books, they have their utilization linked to water line ≥ 700 meters, but in Brazilian exploratory fields, their use occurs from 600 meters of water line. The valves used in Brazilian fields are able to be inserted to the production column and self-equalizing, but the use of screwed valve in the column of production and equalizing is predominant. Although these valves are more expensive to acquire, they are more reliable, efficient, with a bigger shelf life and they do not cause restriction to the fluid flux. It follows that based on researches and theoretical information confronted to usual forms used in fields, the present project is important and relevant. This project will be used as source of actualization and information equalization that connects academic environment and real situations in exploratory situations and also taking into consideration the enrichment of precise and easy to understand information to future researches and academic upgrading.

Keywords: down hole safety valve, security devices, installation, oil-wells

Procedia PDF Downloads 270

Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

Procedia PDF Downloads 140

Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

Abstract:

Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

Procedia PDF Downloads 313

Authors: Kathryn Norgang, Sarah Howrath, Auni Idi Muhire, Pacifique Umubyeyi

Abstract:

Description : A group of nurses address the shortage of trained staff to respond to critical patients at Rwanda Military Hospital (RMH) by developing a training program and a resuscitation response team. Members of the group who received the training when it first launched are now trainer of trainers; all components of the training program are organized and delivered by RMH staff-the clinical mentor only provides adjunct support. This two day training is held quarterly at RMH; basic life support and exposure to interventions for advanced care are included in the test and skills sign off. Seventy staff members have received the training this year alone. An increased number of admission/transfer to ICU due to successful resuscitation attempts is noted. Lessons learned: -Number of staff trained 2012-2014 (to be verified). -Staff who train together practice with greater collaboration during actual resuscitation events. -Staff more likely to initiate BLS if peer support is present-more staff trained equals more support. -More access to Advanced Cardiac Life Support training is necessary now that the cadre of BLS trained staff is growing. Conclusions: Increased access to training, peer support, and collaborative practice are effective strategies to strengthening resuscitation capacity within a hospital.

Keywords: resuscitation, basic life support, capacity building, resuscitation response teams, nurse trainer of trainers

Procedia PDF Downloads 304

Authors: Peniah Mabaso-Shamano

Abstract:

The paper evaluates Shona terms that were created to teach Phonetics and Phonology courses at Great Zimbabwe University (GZU). The phonetics and phonology terms to be discussed in this paper were created using different processes and strategies such as translation, borrowing, neologising, compounding, transliteration, circumlocution among many others. Most phonetics and phonology terms are alien to Shona and as a result, there are no suitable Shona equivalents. The lecturers and students for these courses have a mammoth task of creating terminology for the different modules offered in Shona and other Zimbabwean indigenous languages. Most linguistic reference books are written in English. As such, lecturers and students translate information from English to Shona, a measure which is proving to be too difficult for them. A term creation workshop was held at GZU to try to address the problem of lack of terminology in indigenous languages. Different indigenous language practitioners from different tertiary institutions convened for a two-day workshop at GZU. Due to the 'specialized' nature of phonetics and phonology, it was too difficult to come up with 'proper' indigenous terms. The researcher will consult tertiary institutions lecturers who teach linguistics courses and linguistics students to get their views on the created terms. The people consulted will not be the ones who took part in the term creation workshop held at GZU. The selected participants will be asked to evaluate and back-translate some of the terms. In instances where they feel the terms created are not suitable or user-friendly, they will be asked to suggest other terms. Since the researcher is also a linguistics lecturer, her observation and views will be important. From her experience in using some of the terms in teaching phonetics and phonology courses to undergraduate students, the researcher noted that most of the terms created have shortcomings since they are not user-friendly. These shortcomings include terms longer than the English terms as some terms are translated to Shona through a whole statement. Most of these terms are neologisms, compound neologisms, transliterations, circumlocutions, and blends. The paper will show that there is overuse of transliterated terms due to the lack of Shona equivalents for English terms. Most single English words were translated into compound neologisms or phrases after attempts to reduce them to one word terms failed. In other instances, circumlocution led to the problem of creating longer terms than the original and as a result, the terms are not user-friendly. The paper will discuss and evaluate the different phonetics and phonology terms created and the different strategies and processes used in creating them.

Keywords: blending, circumlocution, term creation, translation

Procedia PDF Downloads 147

Authors: Hanae Ait Hattani, Nohaila Ait Hattani

Abstract:

Globalization, with the rapid technological progress, is affecting every life aspect. The 21st century higher education faces a major challenge in preparing well-rounded and competent graduates to compete in the global marketplace. Worldwide, educational policies work to develop the quality of instruction at all educational levels by focusing on promoting students’ qualifications and skills, considering both academic activities and non-academic attributes. In fact, extracurricular activities (ECAs) complement the academic curriculum and enhance the student experience by improving their interpersonal skills and attitudes. This study comes to examine the potential of extracurricular activities as a vital tool for soft skills’ development. Using empirical research, the study aims to measure and evaluate the extent to which university students’ engagement in extracurricular activities contribute in positively changing their learning experience, fostering their soft skills and fostering their behaviors and attitudes. Findings emanating from a questionnaire and semi-structured interviews add a number of contributions to the literature. They support the assumption suggesting that ECAs can be considered a valuable way to acquire, develop, and demonstrate softs skills that students today need to evidence in a variety of contexts, such as communication skills, team work, leadership, problem-solving, to name but a few.

Keywords: extracurricular activities (ECAs), soft skills, education, university, attitude

Procedia PDF Downloads 72

Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

Abstract:

This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

Procedia PDF Downloads 178

Authors: Masoomeh Estaji, Ahdie Tahamtani

Abstract:

Considering the necessity of conducting research and publishing academic papers during Master’s and Ph.D. programs, graduate students are in dire need of improving their writing skills through either writing courses or self-study planning. One key feature that could aid academic papers to look more sophisticated is the application of grammatical metaphors (GMs). These types of metaphors represent the ‘non-congruent’ and ‘implicit’ ways of decoding meaning through which one grammatical category is replaced by another, more implied counterpart, which can alter the readers’ understanding of the text as well. Although a number of studies have been conducted on the application of GMs across various disciplines, almost none has been devoted to the field of environmental management, and the scope of the previous studies has been relatively limited compared to the present work. In the current study, attempts were made to analyze different types of GMs used in academic papers published in top-tiered journals in the field of environmental management, and make a list of the most frequently used GMs based on their functions in this particular discipline to make the teaching of academic writing courses more explicit and the composition of academic texts more well-structured. To fulfill these purposes, a corpus-based analysis based on the two theoretical models of Martin et al. (1997) and Liardet (2014) was run. Through two stages of manual analysis and concordancers, ten recent academic articles entailing 132490 words published in two prestigious journals were precisely scrutinized. The results yielded that through the whole IMRaD sections of the articles, among all types of ideational GMs, material processes were the most frequent types. The second and the third ranks would apply to the relational and mental categories, respectively. Regarding the use of interpersonal GMs, objective expanding metaphors were the highest in number. In contrast, subjective interpersonal metaphors, either expanding or contracting, were the least significant. This would suggest that scholars in the field of Environmental Management tended to shift the focus on the main procedures and explain technical phenomenon in detail, rather than to compare and contrast other statements and subjective beliefs. Moreover, since no instances of verbal ideational metaphors were detected, it could be deduced that the act of ‘saying or articulating’ something might be against the standards of the academic genre. One other assumption would be that the application of ideational GMs is context-embedded and that the more technical they are, the least frequent they become. For further studies, it is suggested that the employment of GMs to be studied in a wider scope and other disciplines, and the third type of GMs known as ‘textual’ metaphors to be included as well.

Keywords: English for specific purposes, grammatical metaphor, academic texts, corpus-based analysis

Procedia PDF Downloads 167

Authors: E. Isaac, I. Jalo, Y. Alkali, A. Ajani, A. Rasaki, Y. Jibrin, K. Mustapha, S. Charanchi, A. Kudi, H. Danlami

Abstract:

Introduction: Hepatitis B infection is endemic in sub-Saharan Africa, where transmission predominantly occurs in infants and children by perinatal and horizontal routes. The risk of chronic infection peaks when infection is acquired early. Materials and Methods: Records of Hepatitis B surface and envelope antigen results in Federal Teaching Hospital, Gombe between May 2000 and May 2015 were retrieved and analyzed. Results: Paediatric outpatient visits and in-patient admissions were 64,193 accounting for 13% of total. Individuals tested for Hepatitis B surface antigenaemia were 23,866. Children aged 0-18 years constituted 11% (2,626). Among children tested, males accounted for 52.8% (1386/2626) and females 47.2% (1240/2626). Infants contributed 65 (2.3%); 1-4 year old children 309 (11.7%); 5-9 year old children 564 (21.4%) and adolescents 1717 (65.1%). HbSAg sero-positivity was 18% (496/2626) among children tested. The highest number of children tested per year was in 2009 (518) and 2014 (569) and the lowest, in the first study year (62). The highest sero-positivity rate was in 2010; 21.7% (54/255). Children aged 0-18years accounted for 10.5% (496/4720) of individuals with Hepatitis B surface antigenaemia. Sero-positivity was 3.1% (2/65); 12.9% (40/309); 18.1% (102/564); and 20.5% (352/1717) in infants, children ages 1-4years, 5-9years and adolescents respectively. 2.5% (1/40) and 4% (1/25) of male and female infants respectively had HbSAg. Among children aged 1-4years, 15.1% (30/198) of males and 9.0% (10/111) of females were seropositive; 14.8% (52/350) and 22% (50/224) of male and female 5-9year old children respectively has HbSAg. 14.3% (138/943) of adolescent females had Hepatitis B surface antigenaemia. Adolescent males demonstrated the highest sero-positivity rate 27.6% (214/774). 97.3% (483/496) of children who demonstrated Hepatitis B surface antigenaemia were tested for dual carriage with the e antigen. Males accounted for 296/483 (63.1%) and females 187/483 (36.9%). Infants constituted 0.97% (4/482); children aged 1-4years, 5-9years and adolescents were 6.8% (33/483); 20.9% (100/483) and 71.3% (342/483) respectively. 17.6% (85/483) of children tested had HBe antigenaemia. Of these, males accounted for 69.4% (59/85). 1.2% (1/85) were infants; 9.4% (8/85%) 1-4years; 22.3% (19/85) 5-9years and 68.2% (58/85) adolescents. 25% (1/4) infants; 24% (8/33) children aged 1-4 years; 19% (19/100) 5-9 year old children and 16.9% (58/342) adolescents had dual carriage. Infants and young children demonstrated the highest rate of dual carriage but were less likely to be tested for dual carriage 37/42 (88%) than their 5-9 year old 98% (100/102) and adolescent 342/352 (97%) counterparts. HB e antigen positivity rate was 45.4% (59/130) males and 36.0% (27/75) in females. Conclusion: Hepatitis B surface antigenaemia is high among adolescent males. Infants and young children who had HBSAg had the highest rate of envelope antigen carriage. Testing in pregnancy, vaccination programmes and prophylaxis need to be strengthened.

Keywords: children, dual carriage, Gombe, hepatitis B

Procedia PDF Downloads 310

Authors: Syahruddin Sumardi Samindjaya, Indra Fajar Alamsyah, Junaidah Hashim

Abstract:

Purpose: This study attempts to explore and presents a proposed recruitment model in Islamic university which aligned with holistic role. Design/methodology/approach: It is a conceptual paper in nature. In turn, this study is designed to utilize exploratory approach. Literature and document review that related to this topic are used as the methods to analyse the content found. Findings: Recruitment for any organization is fundamental to achieve its goal effectively. Staffing in universities is vital due to the important role of lecturers. Currently, Islamic universities still adopt the common process of recruitment for their academic staffs. Whereas, they have own characteristics which are embedded in their institutions. Furthermore, the FCWC (Foundation, Capability, Worldview and Commitment) model of recruitment proposes to suit the holistic character of Islamic university. Research limitation/implications: Further studies are required to empirically validate the concept through systematic investigations. Additionally, measuring this model by a designed means is appreciated. Practical implications: The model provides the map and alternative tool of recruitment for Islamic universities to determine the process of recruitment which can appropriate their institutions. In addition, it also allows stakeholders and policy makers to consider regarding Islamic values that should inculcate in the Islamic higher learning institutions. Originality/value: This study initiates a foundational contribution for an early sequence of research.

Keywords: academic staff, Islamic values, recruitment model, university

Procedia PDF Downloads 185

Authors: Belete Abebaw, Mulugeta Atinafu, Awoke Shishigu

Abstract:

The study aimed to examine students’ problem-solving skills through mixed instruction (variation theory based Geogerba assisted problem-solving instructional approaches). A total of 125 students divided into 4 intact groups participated in the study. The study employed a quasi-experimental research design. Three intact groups were randomly assigned as a treatment group, while one group was taken as a comparison group. Each of the groups took a specific instructional approach, while the comparison group proceeded as usual without any changes to the instructional process for all sessions. Both pre and post problem-solving tests were administered to all groups. To analyze the data and examine the differences (if any) in each group, ANCOVA and Paired samples t-tests were employed. There was a significant mean difference between students pre-test and post-test in their conceptual understanding of each treatment group. Furthermore, the mixed treatment had a large mean difference. It was recommended that teachers give attention to using variation theory-based geometry problem-solving approaches for students’ better understanding. Administrators should emphasize launching Geogebra software through IT labs in schools, and government officials should appreciate the implementation of technology in schools.

Keywords: conceptual understanding, Geogebra, learning geometry, problem solving approaches, variation theory

Procedia PDF Downloads 25

Authors: Momen Yaseen M. Amin

Abstract:

Despite widespread coverage of language policy in the literature, there has been scant research probing into English language education policy at tertiary levels in general and in the case of higher education context of Iraqi Kurdistan in particular. The present qualitative study investigated the results of a questionnaire on attitudes toward English language education policy in terms of attitudes toward the English language in general, the current English education policy, and the purposes for learning English among Kurdish EFL university students. Moreover, this study aimed to investigate this topic in light of the participants’ gender and major. To this end, an adapted version of Yang’s (2012) questionnaire was administered to university EFL students majoring in soft and hard sciences (N=300, male 34%, female 67%, four and two disciplines, respectively) at two-state and private universities in Iraqi Kurdistan. The findings revealed positive attitudes toward English as an international language in both soft and hard sciences. While strongly subscribing to the idea that all Iraqi Kurdish students should learn the English language and the courses to be offered in English as well as Kurdish, the majority of the participants expressed their readiness and enthusiasm to excel in English and considered such competency a significant academic accomplishment. However, a good number felt dissatisfied with the status quo of English education at their institutions. This paper provides some implications and recommendations for English education policies makers, administrators, and English language instructors at tertiary levels.

Keywords: attitudes, language policy, English language education, Iraqi Kurdistan

Procedia PDF Downloads 179

Authors: O. P. Oladipo, O. A. Falode

Abstract:

The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

Procedia PDF Downloads 441

Authors: Oluwatosin M. A. Jesuyon

Abstract:

In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

Procedia PDF Downloads 203

Authors: Andre Wittenborn, Jarek Krajewski

Abstract:

Trauma-related sadness in speech can alter the voice in several ways. The generation of non-linear aerodynamic phenomena within the vocal tract is crucial when analyzing trauma-influenced speech production. They include non-laminar flow and formation of jets rather than well-behaved laminar flow aspects. Especially state-space reconstruction methods based on chaotic dynamics and fractal theory have been suggested to describe these aerodynamic turbulence-related phenomena of the speech production system. To extract the non-linear properties of the speech signal, we used the time delay embedding method to reconstruct from a scalar time series (reconstructed phase space, RPS). This approach results in the extraction of 7238 Features per .wav file (N= 47, 32 m, 15 f). The speech material was prompted by telling about autobiographical related sadness-inducing experiences (sampling rate 16 kHz, 8-bit resolution). After combining these features in a support vector machine based machine learning approach (leave-one-sample out validation), we achieved a correlation of r = .41 with the well-established, self-report ground truth measure (RATS) of post-traumatic stress disorder (PTSD).

Keywords: non-linear dynamics features, post traumatic stress disorder, reconstructed phase space, support vector machine

Procedia PDF Downloads 102

Authors: Guizella Rocabado, Cassidy Wilkes

Abstract:

It is well known that chemistry is one of the most feared courses in college. Although many students enjoy learning about science, most of them perceive that chemistry is “too difficult”. These perceptions of chemistry result in many students not considering Science, Technology, Engineering, and Mathematics (STEM) majors because they require chemistry courses. Ultimately, these perceptions are also thought to be related to high attrition rates of students who begin STEM majors but do not persist. Students perceived costs of a chemistry class can be many, such as task effort, loss of valued alternatives, emotional, and others. These costs might be overcome by students’ interests and goals, yet the level of perceived costs might have a lasting impact on the students’ overall perception of chemistry and their desire to pursue chemistry and other STEM careers in the future. In this mixed methods study, we investigated task effort and emotional cost, as well as a mastery or performance goal orientation, and the impact these constructs may have on achievement in general chemistry classrooms. Utilizing cluster analysis as well as student interviews, we investigated students’ profiles of perceived cost and goal orientation as it relates to their final grades. Our results show that students who are well prepared for general chemistry, such as those who have taken chemistry in high school, display less negative perceived costs and thus believe they can master the material more fully. Other interesting results have also emerged from this research, which has the potential to have an impact on future instruction of these courses.

Keywords: chemistry education, motivation, affect, perceived costs, goal orientations

Procedia PDF Downloads 90

Authors: K. Julia Rose Mary, Victor Arokia Doss

Abstract:

Electrical and chemical stimulations up-regulate phosphorylaion of CREB, a transcriptional factor that induces its target gene production for memory consolidation and Late Long-Term Potentiation (L-LTP) in CA1 region of the hippocampus. L-LTP requires complex interactions among second-messenger signaling cascade molecules such as cAMP, CAMKII, CAMKIV, MAPK, RSK, PKA, all of which converge to phosphorylate CREB which along with CBP induces the transcription of target genes involved in memory consolidation. A differential equation based model for L-LTP representing stimulus-mediated activation of downstream mediators which confirms the steep, supralinear stimulus-response effects of activation and inhibition was used. The same was extended to accommodate the inhibitory effect of the Inducible cAMP Early Repressor (ICER). ICER is the natural inducible CREB antagonist represses CRE-Mediated gene transcription involved in long-term plasticity for learning and memory. After verifying the sensitivity and robustness of the model, we had simulated it with various empirical levels of repressor concentration to analyse their effect on the gene induction. The model appears to predict the regulatory dynamics of repression on the L-LTP and agrees with the experimental values. The flux data obtained in the simulations demonstrate various aspects of equilibrium between the gene induction and repression.

Keywords: CREB, L-LTP, mathematical modeling, simulation

Procedia PDF Downloads 294

Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

Abstract:

Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

Procedia PDF Downloads 138

Authors: Mohd Fairus Humar, Ibrahim Sulaiman, Pedro Cruz, Hasry Harun

Abstract:

This paper presents the propose knowledge transfer program on railway signaling and communication by Original Equipment Manufacturer (OEM) Thales Portugal. The fundamental issue is that there is no rail related course offered by local universities and colleges in Malaysia which could be an option to pursue student career path. Currently, dedicated trainings related to the rail technology are provided by in-house training academies established by the respective rail operators such as Malaysia Railway Academy (MyRA) and Rapid Rail Training Centre. In this matter, the content of training and facilities need to be strengthened to keep up-to-date with the dynamic evolvement of the rail technology. This is because rail products have evolved to be more sophisticated and embedded with high technology components which no longer exist in the mechanical form alone but combined with electronics, information technology and others. These demand for a workforce imbued with knowledge, multi-skills and competency to deal with specialized technical areas. Talent is needed to support sustainability in Southeast Asia. Keeping the above factors in mind, an Industrial Collaboration Program (ICP) was carried out to transfer knowledge on curricula of railway signaling and communication to a selected railway operators and tertiary educational institution in Malaysia. In order to achieve the aim, a partnership was formed between Technical Depository Agency (TDA), Thales Portugal and MyRA for two years with three main stages of program implementation comprising of: i) training on basic railway signaling and communication for 1 month with Thales in Malaysia; ii) training on advance railway signaling and communication for 4 months with Thales in Portugal and; iii) a series of workshop. Two workshops were convened to develop and harmonize curricula of railway signaling and communication course and were followed by one training for installation equipment of railway signaling and Controlled Train Centre (CTC) system from Thales Portugal. With active involvement from Technical Depository Agency (TDA), railway operators, universities, and colleges, in planning, executing, monitoring, control and closure, the program module of railway signaling and communication course with a lab railway signaling field equipment and CTC simulator were developed. Through this program, contributions from various parties help to build committed societies to engage important issues in relation to railway signaling and communication towards creating a sustainable future.

Keywords: knowledge transfer program, railway signaling and communication, curricula, module and teaching aid simulator

Procedia PDF Downloads 192

Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaar

Abstract:

Objectives: To assess the effect of using audio-visual aids and computer-assisted/ aided language instruction (CALI) in the performance of students of special needs studying vocabulary course. Methods: The performance of forty students of special needs (males and females) who used audiovisual aids and CALI in their vocabulary course at al-Malādh school for students of special needs was compared to that of another group (control group) of the same number and age (8-18). Again, subjects in the experimental group were given lessons using audio-visual aids and CALI, while those in the control group were given lessons using ordinary educational aids only, although both groups almost shared the same features (class environment, speech language therapist (SLT), etc.). Pre-andposttest was given at the beginning and end of the semester and a qualitative and quantitative analysis followed. Results & conclusions: Results of the present experimental study's pre-and-posttests indicated that the performance of the students in the first group was higher than that of those of the second group (34.27%, 73.82% vs. 33.57%, 34.92%, respectively). Compared with females, males’ performance was higher (1515 scores vs. 1438 scores). Such findings suggest that the presence of these audiovisual aids and CALI in the classes of students of special needs, especially if they are studying vocabulary building course is very important due to their usefulness in the improvement of performance of the students of special needs.

Keywords: language components, vocabulary, audio-visual aids, CALI, special needs, students, SLTs

Procedia PDF Downloads 50

Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

Abstract:

Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

Procedia PDF Downloads 83

Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

Abstract:

Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

Procedia PDF Downloads 79

Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

Abstract:

The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

Procedia PDF Downloads 432

Authors: Cara DiGirolamo

Abstract:

In his 2017 Ph.D. thesis, script doctor David Baboulene presented a theory of fiction in which differences in the knowledge states between participants in a literary experience, including reader, author, and characters, create many story elements, among them suspense, expectations, subtext, theme, metaphor, and allegory. This theory can be adjusted and modeled by incorporating a formal pragmatic approach that understands narrative as a speech act with a conversational function. This approach requires both the Speaker and the Listener to be understood as participants in the discourse. It also uses theories of cooperativity and the QUD to identify the existence of implicit questions. This approach predicts that what an effective literary narrative must do: provide a conversational context early in the story so the reader can engage with the text as a conversational participant. In addition, this model incorporates schema theory. Schema theory is a cognitive model for learning and processing information about the world and transforming it into functional knowledge. Using this approach can extend the QUD model. Instead of describing conversation as a form of information gathering restricted to question-answer sets, the QUD can include knowledge modeling and understanding as a possible outcome of a conversation. With this model, Baboulene’s “Knowledge Gaps” can provide real insight into storytelling as a conversational move, and extend the QUD to be able to simply and effectively apply to a more diverse set of conversational interactions and also to narrative texts.

Keywords: literature, speech acts, QUD, literary theory

Procedia PDF Downloads 6

Authors: Olusola Joseph Adesina, Abiodun Ezekiel Adesina

Abstract:

Efforts at improving the falling standard of education in the country call for the need-based assessment of the primary tier of education in Nigeria. Teachers’ cluster meeting intervention is a step towards enhancing the teachers’ professional competency, efficient and effective pupils’ academic achievement and attitudinal development. The study thus determined the impact of the intervention on pupils’ achievement in Oyo State, Nigeria. Three research questions and four hypotheses guided the study. Pre-test, post-test control group, quasi-experimental design was adopted for the study. Eight intact classes from eight different schools were randomly selected into treatment and control groups. Two response instruments, pupils academic achievement test (PAAT; r = 0.87) and pupils attitude to lesson scale (PALS; r = 0.80) were used for data collection. Mean, standard deviation and analysis of covariance (ANCOVA) were used to analyse the collected data. The results showed that the teachers’ cluster meeting have significant impact on pupils academic achievement (F (1,327) =41.79; p<0.05) and attitudinal development (F (1,327) =26.01; p<0.05) in the core subjects of primary schools in Oyo State, Nigeria. The study therefore recommended among others that teachers’ cluster meeting should be sustained for teachers’ professional development and pupils’ upgradement in the State.

Keywords: teachers’ cluster meeting, pupils’ academic achievement, pupils’ attitudinal development, academic achievement

Procedia PDF Downloads 471

Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Abstract:

Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

Procedia PDF Downloads 225

Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

Procedia PDF Downloads 413