Search results for: effect of collaborative learning

Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

Abstract:

Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

Procedia PDF Downloads 53

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 554

Authors: Tathiana Yesenia Coy Mondragón, Jossitt William Vargas Cruz, Cristian Leonardo Gutiérrez Gómez

Abstract:

The study of cosmic rays is based on two fundamental pillars: the detection of secondary cosmic rays on the Earth's surface and the detection of the source and origin of the cascade. In addition, the constant flow of RC generates a lot of interest for study due to the incidence of various natural phenomena, which makes it relevant to characterize their incidence parameters to determine their effect not only at subsoil or terrestrial surface levels but also throughout the atmosphere. To determine the physical parameters of the primary cosmic ray, the implementation of robust algorithms capable of reconstructing the cascade from the measured values is required, with a high level of reliability. Therefore, it is proposed to build a machine learning system that will be fed from the cosmic ray simulations in CORSIKA at different energies that lie in a range [10⁹-10¹²] eV. in order to generate a trained particle and pattern recognition system to obtain greater efficiency when inferring the nature of the origin of the cascade for EAS in the atmosphere considering atmospheric models.

Keywords: CORSIKA, cosmic rays, eas, Colombia

Procedia PDF Downloads 75

Authors: Gae Hee Song

Abstract:

This paper aims to address the evolution of public-private partnerships for mainstreaming an evaluation approach in the community-based education project. It examines the distinctive features of Save the Children’s School Me project in terms of empowerment evaluation principles introduced by David M. Fetterman, especially community ownership, capacity building, and organizational learning. School Me is a Save the Children Korea funded-project, having been implemented in Cote d’Ivoire and Sierra Leone since 2016. The objective of this project is to reduce gender-based disparities in school completion and learning outcomes by creating an empowering learning environment for girls and boys. Both quasi-experimental and experimental methods for impact evaluation have been used to explore changes in learning outcomes, gender attitudes, and learning environments. To locate School Me in the public-private partnership framework for community empowerment and sustainability, the data have been collected from School Me progress/final reports, baseline, and endline reports, fieldwork observations, inter-rater reliability of baseline and endline data collected from a total of 75 schools in Cote d’Ivoire and Sierra Leone. The findings of this study show that School Me project has a significant evaluation component, including qualitative exploratory research, participatory monitoring, and impact evaluation. It strongly encourages key actors, girls, boys, parents, teachers, community leaders, and local education authorities, to participate in the collection and interpretation of data. For example, 45 community volunteers collected baseline data in Cote d’Ivoire; on the other hand, three local government officers and fourteen enumerators participated in the follow-up data collection of Sierra Leone. Not only does this public-private partnership improve local government and community members’ knowledge and skills of monitoring and evaluation, but the evaluative findings also help them find their own problems and solutions with a strong sense of community ownership. Such community empowerment enables Save the Children country offices and member offices to gain invaluable experiences and lessons learned. As a result, empowerment evaluation leads to community-oriented governance and the sustainability of the School Me project.

Keywords: community empowerment, Cote d’Ivoire, empowerment evaluation, public-private partnership, save the children, school me, Sierra Leone, sustainability

Procedia PDF Downloads 122

Authors: Fasanmi Samuel Sunday, Awosusi Omojola

Abstract:

The aim of the present study was to investigate the effect of abusive supervision, interactional justice and supportive workplace supervision burnout among health workers in Makurdi, Benue State, Nigeria. Three hundred and twenty (320) health workers were sampled within Makurdi metropolis, Benue State, Nigeria. Standardized questionnaire on abusive supervision scale, interactional justice scale, supportive workplace supervision scale and employee burnout scale were used in the study. The research was a 2x2x2 factorial design. Four hypotheses were generated and were tested using Analysis of Variance (ANOVA). Scheffe’s post-hoc analysis was used to know the direction of the findings. Results revealed that there was a significant main effect of perceived abusive supervision on employee burnout among health workers. Also, there was a significant main effect of interactional justice on employee burnout among health workers. It was also found out that there was a significant interaction effect of supportive workplace supervision, interactional justice, and abusive supervision on employee burnout among health workers. Results were discussed in line with hypotheses; and recommendations on how to reduce employee burnout were suggested.

Keywords: employee burnout, abusive supervision, interactional justice, supportive workplace supervision

Procedia PDF Downloads 433

Authors: Cheyne Kirkpatrick

Abstract:

In an attempt to make the university intensive English program more worthwhile for students, many English language programs are redesigning curriculum to offer for-credit English for Academic Purposes classes, sometimes marketed as “bridge” courses. These programs are designed to be accredited to national language standards, provide communicative language learning, and give students the opportunity to simultaneously earn university language credit while becoming proficient in academic English. This presentation will discuss the curriculum design of one such program in the United States at a large private university that created its own for-credit “bridge” program. The planning, development, piloting, teaching, and challenges of designing this type of curriculum will be presented along with the aspects of accreditation, communicative language learning, and integration within various university programs. Attendees will learn about how such programs are created and what types of objectives and outcomes are included in American EAP classes.

Keywords: IEP, AEP, Curriculum, CEFR, University Credit, Bridge

Procedia PDF Downloads 478

Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

Abstract:

This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

Procedia PDF Downloads 467

Authors: Emilee M. Cruz

Abstract:

Teachers take part in short-term teaching fellowships abroad, and their preparation before, during, and after the experience is critical to affecting teachers’ feelings of success in the international classroom. A program evaluation of the teacher preparation within TALMA: The Israel Program for Excellence in English (TALMA) full-year teaching fellowship was conducted. A questionnaire was developed that examined professional development, deliberate reflection, and cultural and language immersion offered before, during, and after the short-term experience. The evaluation also surveyed teachers’ feelings of preparedness for the Israeli classroom and any recommendations they had for future teacher preparation within the fellowship program. The review suggests the TALMA program includes integrated professional learning communities between fellows and Israeli co-teachers, more opportunities for immersive Hebrew language learning, a broader professional network with Israelis, and opportunities for guided discussion with the TALMA community continued participation in TALMA events and learning following the full-year fellowship. Similar short-term international programs should consider the findings in the design of their participation preparation programs. The review also offers direction for future program evaluation of short-term participant preparation, including the need for frequent response item updates to match current offerings and evaluation of participant feelings of preparedness before, during, and after the full-year fellowship.

Keywords: educational program evaluation, international teaching, short-term teaching, teacher beliefs, teaching fellowship, teacher preparation

Procedia PDF Downloads 177

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

Abstract:

Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 174

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 638

Authors: Ksheeraj Sai Vepuri, Nada Attar

Abstract:

We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

Procedia PDF Downloads 138

Authors: Saba Latif

Abstract:

The use of social media among university students is a topic of ongoing debate, with conflicting views on its impact on academic achievement. This study aimed to explore the relationship between social media use and academic achievement among university students and to identify factors that may contribute to positive or negative effects. The study used a mixed-methods design, including a survey of 500 university students and qualitative interviews with a subset of participants. The survey results showed that social media use was prevalent among students, with Facebook and Instagram are the most commonly used platforms. The findings also indicated a positive relationship between social media use and academic achievement, with students who reported higher levels of social media use also reporting higher GPAs. However, the qualitative interviews revealed that excessive use of social media could be a distraction that hinders academic performance, especially when students use it to procrastinate or to stay up late at night. Overall, the findings suggest that social media use can have both positive and negative effects on academic achievement among university students. Responsible and balanced use of social media, such as setting limits on usage and avoiding procrastination, may help students maximize the benefits while minimizing the risks.

Keywords: social media, university, achievement, effective, learning

Procedia PDF Downloads 77

Authors: Yasaman Azarmjoo

Abstract:

Since ancient times, it has been said that mathematics is the mother of all sciences and the foundation of basic concepts in every field and profession. It would be great if, after learning this subject, we could enable students to create games and activities based on the same mathematical concepts. This article explores the design of various mathematical activities in the form of games, utilizing different mathematical topics such as algebra, equations, binary systems, and one-to-one correspondence. The theoretical significance of this article lies in uncovering alternative approaches to teaching and learning mathematics. By employing creative and interactive methods such as game design, it challenges the traditional perception of mathematics as a difficult and laborious subject. The theoretical significance of this article lies in demonstrating that mathematics can be made more accessible and enjoyable, which can result in heightened interest and engagement in the subject. In general, this article reveals another aspect of mathematics.

Keywords: playing with mathematics, algebra and equations, binary systems, one-to-one correspondence

Procedia PDF Downloads 87

Authors: Adeep Hande, Shubham Agarwal

Abstract:

This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

Procedia PDF Downloads 66

Authors: Alibi Kilybay, Emad Alhseinat, Ibrahim Mustafa, Abdulfahim Arangadi, Pei Shui, Faisal Almarzooqi

Abstract:

In this work, the electromagnetic field has been used for improving the performance of the capacitive deionization process. The effect of electromagnetic fields on the efficiency of the capacitive deionization (CDI) process was investigated experimentally. The results showed that treating the feed stream of the CDI process using an electromagnetic field can enhance the electrosorption capacity from 20% up to 70%. The effect of the degree of time of exposure, concentration, and type of ions have been examined. The electromagnetic field enhanced the salt adsorption capacity (SAC) of the Ca²⁺ ions by 70%, while the SAC enhanced 20% to the Na⁺ ions. It is hypnotized that the electrometric field affects the hydration shell around the ions and thus reduces their effective size and enhances the mass transfer. This reduction in ion effective size and increase in mass transfer enhanced the electrosorption capacity and kinetics of the CDI process.

Keywords: capacitive deionization, desalination, electromagnetic treatment, water treatment

Procedia PDF Downloads 258

Authors: Mo'ath F. Bataineh

Abstract:

Exercise is highly effective against obesity. Milk contains several components that support exercising and physical performance. However, there is a lack of published studies on the relationship between camel milk and ability to exercise. A pilot study was conducted with the purpose of comparing the impact of milk type (Cow vs Camel) compared with water on physical performance. Seven male obese participants (age: 20.3 ± 1.5 years; BMI: 35.7 ± 2.7 kg/m2; resting heart rate: 92.7 ± 4.7 beats per minute; training frequency: 4.4 ± 0.8 days/week) were recruited for this pilot study. In a randomized counterbalanced crossover design, participants took part in 3 trials that included ingesting 3 different pre workout drinks in a random order. The pre workout drinks were water (W), whole cow milk (CW), and whole camel milk (CM). On each trial day, participants were asked to report to the laboratory after an overnight fasting. Following a 15-minute short recovery period after their arrival to the laboratory, each participant was presented with a 500 ml of the assigned experimental drink and were asked to ingest it in one minute and at least 120 minutes prior to performing the 6-minute walk test. All drinks were presented at room temperature. Trials with different experimental drinks were performed on separate days. Participants were given at least 4 days of washout period between trials. The trial order was randomized to avoid bias due to learning effect. The 6-minute walk test was performed by all participants and immediately at the conclusion of the test, the covered distance in meters and the rating of perceived exertion (RPE) were recorded. All data were analysed using SPSS software (Version 29.0). The repeated measures ANOVA testing of collected data showed a significant main effect for treatment on covered distance in meters, F (2, 8) = 5.794, p=0.028 with a large effect size (partial eta squared (ηp2) =0.592). Also, LSD post hoc pairwise comparison analysis revealed that Camel milk and Cow milk were significantly (p = 0.044 and p = 0.020 respectively) superior to water in improving the covered distance during the test and that Camel milk tended to be better than Cow’s milk. The RPE values were not significantly different between experimental drinks (p>0.05). In conclusion, milk is superior to water as a pre workout drink, and camel milk is comparable to cow’s milk in enhancing ability to support a higher level of performance compared with water, therefore, camel milk could be used to replace cow’s milk as a suitable pre-exercise drink without expecting any negative consequences on physical performance. The fact that these positive results were obtained with obese individuals should encourage using camel milk without the fear of disturbing physical performance in other weight categories.

Keywords: camel milk, cow milk, obesity, physical performance, pre-workout drink

Procedia PDF Downloads 40

Authors: Amira Khelil, Habib Affes

Abstract:

Organization resource planning implementation success is important. Today`s competitors in business, in enterprise resource planning and in managing are becoming one of the main tools of achieving competitiveness in business. Resource technologies are considered as an infrastructure to create and maintain business to improve front and back-office efficiency and effectiveness. This study is significant to bring new ideas in determining the key antecedents which are technological resource planning implementation based on knowledge capacity perspectives and help to understand the key success factor in the Tunisian banks. Based on a survey of 150 front office Tunisian agents working in Tunisian banks with mixed capital, using Groupware system, only 51 respondents had given feedback to this survey. By using Warp PLS 3.0, through several tests the relationship between knowledge capability and Groupware implementation success having beta coefficient 0.37 and P-Value <0.01. This result highlights that knowledge capability of bank agent can influence the success of the Groupware implementation.

Keywords: groupware implementation, knowledge capacity, partial least squares method, Tunisian banks

Procedia PDF Downloads 486

Authors: E. Al-Essa, R. Bello-Mendoza, D. G. Wareham

Abstract:

Anaerobic batch experiments were conducted to investigate the effect of magnetite-supplementation (7 mM) on methane production from digested sludge undergoing two different microbial growth phases, namely fresh sludge (exponential growth phase) and degassed sludge (endogenous decay phase). Three different particle sizes were assessed: small (50 - 150 nm), medium (168 – 490 nm) and large (800 nm - 4.5 µm) particles. Results show that, in the case of the fresh sludge, magnetite significantly enhanced the methane production rate (up to 32%) and reduced the lag phase (by 15% - 41%) as compared to the control, regardless of the particle size used. However, the cumulative methane produced at the end of the incubation was comparable in all treatment and control bottles. In the case of the degassed sludge, only the medium-sized magnetite particles increased significantly the methane production rate (12% higher) as compared to the control. Small and large particles had little effect on the methane production rate but did result in an extended lag phase which led to significantly lower cumulative methane production at the end of the incubation period. These results suggest that magnetite produces a clear and positive effect on methane production only when an active and balanced microbial community is present in the anaerobic digester. It is concluded that, (i) the effect of magnetite particle size on increasing the methane production rate and reducing lag phase duration is strongly influenced by the initial metabolic state of the microbial consortium, and (ii) the particle size would positively affect the methane production if it is provided within the nanometer size range.

Keywords: anaerobic digestion, iron oxide, methanogenesis, nanoparticle

Procedia PDF Downloads 139

Authors: Ruby A. L. Espineli

Abstract:

The study assessed the Philippine National Police strategies in the implementation of ‘Peace and Order Agenda for Transformation and Upholding of the Rule-of-Law’ P.A.T.R.O.L Plan 2030. Its operational roadmap presents four perspectives which include resource management, learning and growth, process excellence; and community. Focused group discussion, observation, and distribution of survey questionnaire to selected PNP officers and community members were done to identify and describe the implementation, problems encountered and measures to address the problems of the PNP P.A.T.R.O.L Plan 2030. In resource management, PNP allocates most sufficient funds in providing service firearms, patrol vehicle, and internet connections. In terms of learning and growth, the attitude of PNP officers is relatively higher than their knowledge and skills. Moreover, in terms of process excellence, the PNP use several crime preventions and crime solution strategies to deliver an immediate response to calls of the community. As regards, community perspective, PNP takes effort in establishing partnership with community. It is also interesting to note that PNP officers and community were both undecided on the existence of problems encountered in the implementation of P.A.T.R.O.L Plan 2030. But, they had proactive behavior as they agreed on all the specified measures to address the problems encountered in implementation of PNP P.A.T.R.O.L. Plan 2030. A strategic framework, based on the findings was formulated in this study that could improve and entrench the harmonious working relationship between the PNP and stakeholders in the enhancement of the implementation of PNP P.A.T.R.O.L. Plan 2030.

Keywords: community perspectives, learning and growth, process excellence, resource management

Procedia PDF Downloads 227

Authors: Collen T. Masilo, Brane Semolic, Pieter Steyn

Abstract:

The Internet Protocol Television (IPTV) and Hybrid Fibre-Coaxial (HFC) Broadband industrial sector landscape are rapidly changing and organisations within the industry need to stay competitive by exploring new business models so that they can be able to offer new services and products to customers. The business challenge in this industrial sector is meeting or exceeding high customer expectations across multiple content delivery modes. The increasing challenges in the IPTV and HFC broadband industrial sector encourage service providers to form strategic partnerships with key suppliers, marketing partners, advertisers, and technology partners. The need to form enterprise collaborative networks poses a challenge for any organisation in this sector, in selecting the right strategic partners who will ensure that the organisation’s services and products are marketed in new markets. Partners who will ensure that customers are efficiently supported by meeting and exceeding their expectations. Lastly, selecting cooperation partners who will represent the organisation in a positive manner, and contribute to improving the performance of the organisation. Companies in the IPTV and HFC broadband industrial sector tend to form informal partnerships with suppliers, vendors, system integrators and technology partners. Generally, partnerships are formed without thorough analysis of the real reason a company is forming collaborations, without proper evaluations of prospective partners using specific selection criteria, and with ineffective performance monitoring of partners to ensure that a firm gains real long term benefits from its partners and gains competitive advantage. Similar tendencies are illustrated in the research case study and are based on Skyline Communications, a global leader in end-to-end, multi-vendor network management and operational support systems (OSS) solutions. The organisation’s flagship product is the DataMiner network management platform used by many operators across multiple industries and can be referred to as a smart system that intelligently manages complex technology ecosystems for its customers in the IPTV and HFC broadband industry. The approach of the research is to develop the most efficient business model that can be deployed to improve a strategic partnership programme in order to significantly improve the performance and growth of organisations participating in a collaborative network in the IPTV and HFC broadband industrial sector. This involves proposing and implementing a new strategic partnership model and its main features within the industry which should bring about significant benefits for all involved companies to achieve value add and an optimal growth strategy. The proposed business model has been developed based on the research of existing relationships, value chains and business requirements in this industrial sector and validated in 'Skyline Communications'. The outputs of the business model have been demonstrated and evaluated in the research business case study the IPTV and HFC broadband service provider 'Skyline Communications'.

Keywords: growth, partnership, selection criteria, value chain

Procedia PDF Downloads 129

Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

Abstract:

Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

Procedia PDF Downloads 184

Authors: Kerri Alderson

Abstract:

There is pervasive awareness by post secondary faculty that written feedback on course assignments is inconsistently reviewed by students. In order to support student success and growth, a novel method of providing feedback was sought, and screen casting - short, narrated “movies” of audio visual instructor feedback on students’ scholarly papers - was provided as an alternative to traditional means. An overview of the teaching and learning experience as well as the user-friendly software utilized will be presented. This study covers an overview of this more direct, student-centered medium for providing feedback using technology familiar to post secondary students. Reminiscent of direct personal contact, the personalized video feedback is positively evaluated by students as a formative medium for student growth in scholarly writing.

Keywords: education, pedagogy, screen casting, student feedback, teaching and learning

Procedia PDF Downloads 115

Authors: Mairo Musa Galadima, Phoebe Mshelia

Abstract:

In Nigeria, the national policy of education stipulates that the kindergarten-primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo, and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5 (five) selected secondary school in Bauchi. It was discovered that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequately qualified teachers and relevant materials including textbooks. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: stress and intonation, phonetic and challenges, teaching and learning English, secondary schools

Procedia PDF Downloads 349

Authors: Ali Mohammed Ali Lmbash

Abstract:

The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

Procedia PDF Downloads 45

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 77

Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

Abstract:

Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social Networking Sites (SNSs), education, college students, motivations

Procedia PDF Downloads 258

Authors: Zach Banzon, Marina Caculitan, Gianne Laisac, Stephanie Lopez, Marguerite Villegas

Abstract:

The role of incidental positive emotions and gender on people’s trust decisions have been established by existing research. The aim of this experiment is to address the gap in the literature by examining whether these factors will have a similar effect on trust behavior even after the experience of betrayal. A total of 144 undergraduate students participated in a trust game involving the anonymous interaction of a participant and a transgressor. Of these participants, only 125 (63 males and 62 females) were included in the data analyses. A story was used to prime incidental positive emotions or emotions originally unrelated to the trustee. Recovered trust was measured by relating the proportion of the money passed before and after betrayal. Data was analyzed using two-way analysis of variance having two levels for gender (male, female) and two for priming (with, without), with trust propensity scores entered as a covariate. It was predicted that trust recovery will be more apparent in females than in males but the data obtained was not significantly different between the genders. Induced positive emotions, however, had a statistically significant effect on trust behavior even after betrayal. No significant interaction effect was found between induced positive emotion and gender. The experiment provides evidence that the manipulation of situational variables, to a certain extent, can facilitate the reparation of trust.

Keywords: gender effect, positive emotions, trust game, trust recovery

Procedia PDF Downloads 268

Authors: Krisstalova Dana, Mazal Jan

Abstract:

This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths

Procedia PDF Downloads 417

Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

Abstract:

A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

Procedia PDF Downloads 197

Authors: Stephanie Ducrot, Marie Vernet, Eve Meiss, Yves Chaix

Abstract:

Learning to read is a key topic of debate today, both in terms of its implications on school failure and illiteracy and regarding what are the best teaching methods to develop. It is estimated today that four to six percent of school-age children suffer from specific developmental disorders that impair learning. The findings from people with dyslexia and typically developing readers suggest that the problems children experience in learning to read are related to the preliteracy skills that they bring with them from kindergarten. Most tools available to professionals are designed for the evaluation of child language problems. In comparison, there are very few tools for assessing the relations between visual skills and the process of learning to read. Recent literature reports that visual-motor skills and visual-spatial attention in preschoolers are important predictors of reading development — the main goal of this study aimed at improving screening for future reading difficulties in preschool children. We used a prospective, longitudinal approach where oculomotor processes (assessed with the DiagLECT test) were measured in pre-readers, and the impact of these skills on future reading development was explored. The dialect test specifically measures the online time taken to name numbers arranged irregularly in horizontal rows (horizontal time, HT), and the time taken to name numbers arranged in vertical columns (vertical time, VT). A total of 131 preschoolers took part in this study. At Time 0 (kindergarten), the mean VT, HT, errors were recorded. One year later, at Time 1, the reading level of the same children was evaluated. Firstly, this study allowed us to provide normative data for a standardized evaluation of the oculomotor skills in 5- and 6-year-old children. The data also revealed that 25% of our sample of preschoolers showed oculomotor impairments (without any clinical complaints). Finally, the results of this study assessed the validity of the DiagLECT test for predicting reading outcomes; the better a child's oculomotor skills are, the better his/her reading abilities will be.

Keywords: vision, attention, oculomotor processes, reading, preschoolers

Procedia PDF Downloads 144