Search results for: student-centered learning technologies

Authors: Bhagwant Singh, Sikander Singh Cheema

Abstract:

This paper examines firewall mechanisms routinely implemented for network security in depth. A firewall can't protect you against all the hazards of unauthorized networks. Consequently, many kinds of infrastructure are employed to establish a secure network. Firewall strategies have already been the subject of significant analysis. This study's primary purpose is to avoid unnecessary connections by combining the capability of the firewall with the use of additional firewall mechanisms, which include packet filtering and NAT, VPNs, and backdoor solutions. There are insufficient studies on firewall potential and combined approaches, but there aren't many. The research team's goal is to build a safe network by integrating firewall strength and firewall methods. The study's findings indicate that the recommended concept can form a reliable network. This study examines the characteristics of network security and the primary danger, synthesizes existing domestic and foreign firewall technologies, and discusses the theories, benefits, and disadvantages of different firewalls. Through synthesis and comparison of various techniques, as well as an in-depth examination of the primary factors that affect firewall effectiveness, this study investigated firewall technology's current application in computer network security, then introduced a new technique named "tight coupling firewall." Eventually, the article discusses the current state of firewall technology as well as the direction in which it is developing.

Keywords: firewall strategies, firewall potential, packet filtering, NAT, VPN, proxy services, firewall techniques

Procedia PDF Downloads 91

Authors: Amanda Rithieli Pereira Dos Santos, Rute Quelvia De Faria, Álvaro De Oliveira Cardoso, Anderson Rodrigo Da Silva, Érica Leão Fernandes Araújo

Abstract:

The study of the kinetics of drying has great importance for the mathematical modeling, allowing to know about the processes of transference of heat and mass between the products and to adjust dryers managing new technologies for these processes. The present work had the objective of studying the kinetics of drying of soybean seeds and adjusting different statistical models to the experimental data varying cultivar and temperature. Soybean seeds were pre-dried in a natural environment in order to reduce and homogenize the water content to the level of 14% (b.s.). Then, drying was carried out in a forced air circulation oven at controlled temperatures of 38, 43, 48, 53 and 58 ± 1 ° C, using two soybean cultivars, BRS 8780 and Sambaíba, until reaching a hygroscopic equilibrium. The experimental design was completely randomized in factorial 5 x 2 (temperature x cultivar) with 3 replicates. To the experimental data were adjusted eleven statistical models used to explain the drying process of agricultural products. Regression analysis was performed using the least squares Gauss-Newton algorithm to estimate the parameters. The degree of adjustment was evaluated from the analysis of the coefficient of determination (R²), the adjusted coefficient of determination (R² Aj.) And the standard error (S.E). The models that best represent the drying kinetics of soybean seeds are those of Midilli and Logarítmico.

Keywords: curve of drying seeds, Glycine max L., moisture ratio, statistical models

Procedia PDF Downloads 613

Authors: Yuni Rochmawati, Luluk Il Mukarromah

Abstract:

Android is a mobile operating system (OS) based on the linux kerrnel and currently developed by google. With a user interface based on direct manipulation, Android is designed primarily for touchscreen mobile deviced such as smartphone and tablet computer, with specialized user interface for television (Android TV), cars (Android Auto), and wrist watches (Android Wear). Now, almost all peoples using smartphone. Smartphone seems to be a must-have object, because smartphone has many benefits. In addition, of course smartphone have many benefits for education, like resume of lesson that form of e-book. However, this article is not about resume of lesson. This article is about practical based on android, exactly for physics. Therefore, we will explain our idea about physics’s practical based on android and for output, we wish many students will be like to studying physics and always remember about physics’s phenomenon by physics’s practical based on android.

Keywords: android, smartphone, physics, practical

Procedia PDF Downloads 228

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

Abstract:

Catecholamines are vital neurotransmitters that mediate a variety of central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, optical techniques for the detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid-modified enzymatic sensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence as well as electrochemical sensing strategy for catecholamines detection.

Keywords: biosensors, catecholamines, fluorescence, enzymes

Procedia PDF Downloads 101

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

Abstract:

Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 353

Authors: A. Alssbaiheen, S. Love

Abstract:

Mobile government (m-government) is one of the promising technologies for developing the governance of developing countries. While developing countries often have less advanced internet infrastructure compared to the developed world, mobile phone penetration is very high in the Gulf Cooperation Council (GCC) countries and mobile internet use offers a means to transcend traditional logistical barriers to accessing government services. The study explores the challenges and opportunities of the mobile government in Saudi Arabia. Semi-structured interviews were conducted with a diverse cohort of Saudi mobile users. A total of 77 semi-structured interviews were collected and subsequently analysed using open, axial, and selective coding. The participants’ responses revealed that many opportunities exist for the development of m-government in Saudi Arabia, including high popular awareness of government initiatives in e-government, and willingness to use such services, largely due to the time-saving and convenience aspects it offers compared with traditional bureaucratic services. However, numerous barriers were identified, including the low quality and speed of the internet, service customization, and concerns about privacy data security. It was also felt that in addition to infrastructure challenges, the traditional bureaucratic attitude of government department would itself hinder the effective deployment and utilization of m-government services.

Keywords: awareness, barriers, challenges, government services, mobile government, m-government, opportunities

Procedia PDF Downloads 459

Authors: Philipp Sommer, Amgad Agoub

Abstract:

The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

Procedia PDF Downloads 36

Authors: Hyunki Kang, Hi Won Jeong

Abstract:

The gas turbine operates for a long period of time under harsh, cyclic conditions of high temperature and pressure, where high turbine inlet temperature (TIT) can range from 1273 to 1873K. Therefore, Ni-base superalloys such as IN738, IN939, Rene 45, Rene 71, Rene 80, Mar M 247, CM 247, and CMSX-4 with excellent mechanical properties and resistance to creep, corrosion and oxidation at high temperatures are indeed used. Among the alloying additions for these alloys, aluminum (Al) and titanium (Ti) form gamma prime and enhance the high-temperature properties. However, when crack-damaged high-temperature turbine components such as blade and vane are repaired by fusion welding, they cause cracks. For example, when arc welding is applied to certain superalloys that contain Al and Ti with more than 3 wt.% and T3.5 wt%, respectively, such as IN738, IN939, Rene 80, Mar M 247, and CM 247, aging cracks occur. Therefore, repair technologies using diffusion brazing, which has less heat input into the base material, are being developed. Analysis of microstructural evolution of the brazed joints with a base metal of IN 939 Ni-base superalloy using brazing different filler metals was also carried out using X-ray diffraction, OEM, SEM-EDS, and EPMA. Stress rupture and high-temperature tensile strength properties were also measured to analyze the effects of different brazing heat cycles. The boron amount in the diffusion-affected zone (DAZ) was decreased towards the base metal and the formation of borides at grain boundaries was detected through EPMA.

Keywords: gas turbine, diffusion brazing, superalloy, gas turbine repair

Procedia PDF Downloads 37

Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

Abstract:

In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

Procedia PDF Downloads 112

Authors: Gholam Reza Parvizi, Ali Reza Kargar, Amir Arani

Abstract:

In the present days, learning and teaching researchers have emphasized the role which teachers, tutors, and trainers’ constraint knowledge treat in resizing and trimming what they perform in educational atmosphere. Regarding English language as subject to teaching, although the prominence of instructor’s knowledge about grammar has also been stressed, but the lack of empirical insights into the relationship between teacher’ self-monitoring and self-response of grammar knowledge have been observed. With particular attention to the grammar this article indicates and discusses information obtained self- feedback and conversing teachers of a kind who backwash the issue. The result of the study indicates that enabling teachers to progress and maintain a logical and realistic awareness of their knowledge about grammar have to be prominent goal for teachers’ education and development programs.

Keywords: grammar knowledge, self-monitoring, self-response, teaching grammar, language teaching program

Procedia PDF Downloads 547

Authors: Paola Molteni, Luigi d’Alonzo

Abstract:

Background: Sensory issues are now considered one of the key aspects in defining and diagnosing autism, changing the perspectives on behavioural analysis and intervention in mainstream educational services. However, Italian teachers’ training is yet not specific on the topic of autism and its sensory-related effects and this research investigates the teacher’s capability in understanding the student’s needs and his/her challenging behaviours considering sensory perceptions. Objectives: The research aims to analyse mainstream schools teachers’ awareness on students’ sensory perceptions and how this affects classroom inclusion and learning process. The research questions are: i) Are teachers able to identify student’s sensory issues?; ii) Are trained teachers more able to identify sensory problems then untrained ones?; iii) What is the impact of sensory issues on inclusion in mainstream classrooms?; iv) What should teachers know about autistic sensory dimensions? Methods: This research was designed as a pilot study that involves a multi-methods approach, including action and collaborative research methodology. The designed research allows the researcher to catch the complexity of a province school district (from kindergarten to high school) through a deep detailed analysis of selected aspects. The researcher explored the questions described above through 133 questionnaires and 6 focus groups. The qualitative and quantitative data collected during the research were analysed using the Interpretative Phenomenological Analysis (IPA). Results: Mainstream schools teachers are not able to confidently recognise sensory issues of children included in the classroom. The research underlines: how professionals with no specific training on autism are not able to recognise sensory problems in students on the spectrum; how hearing and sight issues have higher impact on classroom inclusion and student’s learning process; how a lack of understanding is often followed by misinterpretations of the impact of sensory issues and challenging behaviours. Conclusions: As this research has shown, promoting and enhancing the importance of understanding sensory issues related to autism is fundamental to enable mainstream schools teachers to define educational and life-long plans able to properly answer the student’s needs and support his/her real inclusion in the classroom. This study is a good example of how the educational research can meet and help the daily practice in working with people on the autism spectrum and support the training design for mainstream school teachers: the emerging need of designed preparation on sensory issues is fundamental to be considered when planning school district in-service training programmes, specifically declined for inclusive services.

Keywords: autism spectrum condition, scholastic inclusion, sensory overload, teacher's training

Procedia PDF Downloads 311

Authors: Pooja Rawat, Rakhi Tyagi

Abstract:

Globally, almost 3 billion people rely on biomass (wood, charcoal, dung and crop residues) and coal as their primary source of domestic energy. Cooking and heating with solid fuels on open fire give rise to major pollutants. Women are primarily affected by these pollutants as they spend most of their time in the house. The WHO World Health Report 2002 estimates that indoor air pollution (IAP) is responsible for 2.7% of the loss of disability adjusted life years (DALYs) worldwide and 3.7% in high mortality developing countries. Indoor air pollution has the potential to not only impact health, but also impact the general economic well-being of the household. Exposure to high level of household pollution lead to acute and chronic respiratory conditions (e.g.: pneumonia, chronic obstructive pulmonary disease, lung cancer and cataract). There has been many strategies for reducing IAP like subsidize cleaner fuel technologies, for example use of kerosene rather than traditional biomass fuels. Another example is development, promotion of 'improved cooking stoves'. India, likely ranks second- distributing over 12 million improved stoves in the first seven years of a national program to develop. IAP should be reduced by understanding the welfare effects of reducing IAP within households and to understanding the most cost effective way to reduce it.

Keywords: open fire, indoor pollution, lung diseases, indoor air pollution

Procedia PDF Downloads 288

Authors: Olga Kononova, Sergey Lyapin

Abstract:

Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

Procedia PDF Downloads 347

Authors: Nidhi Gadura

Abstract:

Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.

Keywords: partially online course, pedagogy, student engagement, community college

Procedia PDF Downloads 382

Authors: Anis Eloud, Ben Salah Nahla, Sayed Chehaibi

Abstract:

In order to improve and develop the Tunisian agriculture, the government has encouraged the introduction of modern technologies and has also promoted the adoption of innovative practices cultures. Indeed, the extensive use of mechanization can increase crop productivity but its inadequate application also has a negative impact on the ground caused by the phenomenon of compaction. Which will cause the loss of soil fertility and increased production costs. This problem is accentuated with increase the stress on contact wheel / ground. For this reason, the objective of this study is to simulate the footprint of the ground contact / tire two types of tractor after their passage. The method of this work is based on a simulation including passages from two different tractors on soil with similar characteristics. Simulation parameters were based on the choice of two tractors masses of 6500 kg and 4400 kg of soil and sandy loam in nature. The analysis was performed using specific software. The main results showed that the heaviest tractor caused a constraint wheel / rear floor exceeding 100 kPa. For cons, the second tractor has caused stress wheel / rear floor of 50 kPa. The comparison of the two results showed that 6500 kg tractor made a serious and excessive compaction which generated a negative impact on soil quality and crop yields.

Keywords: compaction, soil, resistance to penetration, crop yields

Procedia PDF Downloads 425

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 207

Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

Abstract:

Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

Procedia PDF Downloads 195

Authors: Boulis M. Ibrahim, Iordanis A. Kalaitzoglou

Abstract:

A micro structural pricing model is proposed in which price components account for learning by incorporating changing expectations of the trading intensity and the risk level of incoming trades. An analysis of European carbon futures transactions finds expected trading intensity to increase the information component and decrease the liquidity component of price changes, but at different rates. Among the results, the expected persistence in trading intensity explains the majority of the auto correlations in the level and the conditional volatility of price changes, helps predict hourly patterns in the bid–ask spread and differentiates between the impact of buy versus sell and continuing versus reversing trades.

Keywords: CO2 emission allowances, market microstructure, duration, price discovery

Procedia PDF Downloads 398

Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

Abstract:

Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a negative binomial structure model and Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

Procedia PDF Downloads 18

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

Procedia PDF Downloads 116

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 164

Authors: Aisha Siddiqa

Abstract:

The knowledge of pragmatic practices in a particular language is considered key to effective communication. Unlike one’s native language where this knowledge is acquired spontaneously, more conscious attention is required to learn second language pragmatics. Traditional foreign language (FL) classrooms generally focus on the acquisition of vocabulary and lexico-grammatical structures, neglecting pragmatic functions that are essential for effective communication in the multilingual networks of the modern world. In terms of effective communication, of particular importance is knowledge of what is perceived as polite or impolite in a certain language, an aspect of pragmatics which is not perceived as obligatory but is nonetheless indispensable for successful intercultural communication and integration. While learning a second language, the acquisition of politeness assumes more prominence as the politeness norms and practices vary according to language and culture. Therefore, along with focusing on the ‘use’ of politeness strategies, it is crucial to examine the ‘acquisition’ and the ‘acquisitional development’ of politeness strategies by second language learners, particularly, by lower proficiency leaners as the norms of politeness are usually focused in lower levels. Hence, there is an obvious need for a study that not only investigates the acquisition of pragmatics by young FL learners using innovative multiple methods; but also identifies the potential causes of the gaps in their development. The present research employs a cross sectional design to explore the acquisition of politeness by young English as a foreign language learners (EFL) in France; at three levels of secondary school learning. The methodology involves two phases. In the first phase a cartoon oral production task (COPT) is used to elicit samples of requests from young EFL learners in French schools. These data are then supplemented by a) role plays, b) an analysis of textbooks, and c) video recordings of classroom activities. This mixed method approach allows us to explore the repertoire of politeness strategies the learners possess and delve deeper into the opportunities available to learners in classrooms to learn politeness strategies in requests. The paper will provide the results of the analysis of COPT data for 250 learners at three different stages of English as foreign language development. Data analysis is based on categorization of requests developed in CCSARP project. The preliminary analysis of the COPT data shows that there is substantial evidence of pragmalinguistic development across all levels but the developmental process seems to gain momentum in the second half of the secondary school period as compared to the early period at school. However, there is very little evidence of sociopragmatic development. The study aims to document the current classroom practices in France by looking at the development of young EFL learner’s politeness strategies across three levels of secondary schools.

Keywords: acquisition, English, France, interlanguage pragmatics, politeness

Procedia PDF Downloads 414

Authors: Nivedita Ghosh

Abstract:

In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.

Keywords: documentary filmmaking, India, technology, knowledge, hierarchy

Procedia PDF Downloads 250

Authors: Reda Abdel-Aziz

Abstract:

Agricultural activities in Egypt generate annually around 35 million tons of waste. Composting is one of the most promising technologies to turnover waste in a more economical way, for many centuries. Composting has been used as a mean of recycling organic matter back into the soil to improve soil structure and fertility. Field experiments were conducted in two governorates, Giza and Al-Monofia, to find out the effect of compost with different rates of chemical fertilizers on growth and yield of corn (Zea mays L.) during two constitutive seasons of 2012 and 2013. The experiment, laid out in a randomized complete block design (RCBD), was carried out on five farmers’ fields in each governorate. The treatments were: unfertilized control, full dose of NPK (120, 30, and 50 kg/acre, respectively), compost at rate of 20 ton/acre, compost at rate of 10 ton/acre + 25% of chemical fertilizer, compost at rate of 10 ton/acre + 50% of chemical fertilizer and compost at rate of 10 ton/acre + 75% of chemical fertilizer. Results revealed a superiority of the treatment of compost at rate of 10 ton/acre + 50% of NPK that caused significant improvement in growth, yield and nutrient uptakes of corn in the two governorates during the two constitutive seasons. Results showed that agricultural waste could be composted into value added soil amendment to enhance efficiency of chemical fertilizer. Composting of agricultural waste could also reduce the chemical fertilizers potential hazard to the environment.

Keywords: agricultural waste, compost, chemical fertilizers, corn production, environment

Procedia PDF Downloads 310

Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

Abstract:

A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

Procedia PDF Downloads 264

Authors: Wajiha Fatima

Abstract:

Various approaches and methods for second language classroom teaching have been proposed since the nineteenth century. Task Based Language Teaching has been prevailing approach in a second language classroom context. It is an approach which immerses students in a naturalistic setting. Tasks are the core unit of planning and instruction. This paper aims at expounding the concept of Task Based Language Teaching and how it has been evolved. In this study, researcher will highlight the usefulness of TBLT and the role it played as a powerful tool for learning and teaching in a second language setting. The article will reflect the implementation of various tasks based activities as well as the roles played by learners and teachers and the problems faced by them. In the end, researcher will discuss how TBLT can be implemented in second language classroom pedagogy.

Keywords: implementation, second language classroom, tasks, task based language teaching

Procedia PDF Downloads 341

Authors: Rong-Terng Juang

Abstract:

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

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

Procedia PDF Downloads 151

Authors: Andrew Kurochkin, Kostiantyn Bokhan

Abstract:

In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 122

Authors: Shatha Alkhalaf

Abstract:

This study aimed to investigate the effectiveness of the English Speaking Practice App in improving the speaking skills of English as a Foreign Language (EFL) learners. The participants were 44 diploma students at Qassim University in Saudi Arabia. They used the app for 30 minutes per week over a 12-week period. A survey questionnaire was used to measure their perceptions of the app's effectiveness, usability, and impact on motivation. The questionnaire showed high internal consistency (Cronbach's alpha = 0.89). The findings suggest that the app was perceived positively by the participants in terms of its effectiveness in improving speaking skills, usability, and motivation. This research contributes to the field of language teaching by highlighting the potential of technology-enhanced language learning.

Keywords: second language, English, speaking, technology

Procedia PDF Downloads 71

Authors: Odette Umugiraneza, Etienne Nzaramyimana

Abstract:

Confidence and beliefs are the main contributors to the improvement of teachers’ mathematical knowledge. The objective of this study was to investigate teachers’ confidence and beliefs towards technology use in teaching mathematics subjects in the Musanze District. The data were collected using closed and open questions. These were distributed to 118 secondary school senior 1 to 6 mathematics teachers in Musanze district. The findings revealed that the teachers’ confidence about the use of technology in teaching mathematics needs improvement. Apart from confidence, almost a third of the teachers convoyed negative beliefs that technology plays great importance in promoting the understanding of mathematics. Teachers as knowledge transmitters are required to join various professional courses towards technology integration in the teaching of mathematics, to improve the effectiveness of teaching and learning.

Keywords: knowledge, technology, teachers’ confidence, beliefs, barriers of technology use

Procedia PDF Downloads 114