Search results for: affordance categories

Authors: Antarjeeta Nayak, Jalandhar Pradhan, Ramakrishna Biswal

Abstract:

Poverty is a complex phenomenon influenced by a large number of factors and which can be studied from many different perspectives. Most of the poverty assessments can be divided into three broad categories- construction of poverty profile (who the poor are), causes of poverty (why people are poor) and poverty alleviation strategies (what to do about poverty). In this regard, we need to know more about poverty, the factors that drive it and those that maintain it. Specifically, how people perceive and experience poverty will generate a body of knowledge that would enable government and poverty alleviation agencies to better target their interventions and understand the stigma associated with poverty. In the Indian context, the perceptions of the causes of poverty are particularly relevant because of the persistent higher percent of people below poverty line and wider economic-social inequalities despite the continuing decline of poverty in the present times. In this study we investigated the perceived attributions for poverty among youths (University students) in India. A questionnaire having 35 questions was administered to a sample of 200 University students (n=200). Findings showed that Indian youth were more inclined to attribute poverty to Structural factors; supporting system-blame hypothesis.

Keywords: poverty, perception of the causes of poverty, Indian youth, social sciences and humanities

Procedia PDF Downloads 397

Authors: Isa Muhammad Zumo

Abstract:

Malaria is one of the worst illnesses that may affect humans. It is typically transmitted by the bite of a female Anopheles mosquito and is caused by parasitic protozoans from the Plasmodium parasite. Government and non-governmental organizations made numerous initiatives to combat the threat of malaria in communities. Nevertheless, the necessary attention was not paid to accurate and current information regarding the size and location of these favourable locations for mosquito development. Because mosquitoes can only reproduce in specific habitats with surface water, this study will locate and map those favourable sites that act as mosquito breeding grounds. Spatial and attribute data relating to favourable mosquito breeding places will be collected and analysed using Geographic Information Systems (GIS). The major findings will be in five classes, showing the vulnerable and risky areas for malaria cases. These risk categories are very high, high, moderate, low, and extremely low vulnerable areas. The maps produced by this study will be of great use to the health department in combating the malaria pandemic.

Keywords: Malaria, vulnerability, mapping, space, Damaturu

Procedia PDF Downloads 27

Authors: Tazvin Ijaz, Aisha Shahid Sheikh

Abstract:

The current study was conducted to explore the relationship between body dissatisfaction and the perceived parenting styles of women. For the purpose of study a sample of adult women (N=308) was drawn through the process of stratified random sampling. The sample consisted of women belonging to different categories which were based on their occupation. Two instruments, the Body Dissatisfaction Scale (BDSS) and Perceived Parenting Styles (PPSS) were used in the study to find the relationship between the two variables. The results showed that the controlling parenting style in father led to higher body dissatisfaction while the nurturing parenting style lead to lesser symptoms of body dissatisfaction. The results also proved that the controlling parenting style in mother also lead to high symptoms of body dissatisfaction as well. It was revealed that the women with high education showed more body dissatisfaction than women with lower education. It was also seen that there was a significant difference in the body dissatisfaction of working and the non-working women.

Keywords: body dissatisfaction, perceived parenting styles, Pakistani women, gender

Procedia PDF Downloads 298

Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

Abstract:

From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

Procedia PDF Downloads 365

Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

Abstract:

Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

Procedia PDF Downloads 127

Authors: S. P. Singh

Abstract:

This paper measures technical and scale efficiencies of 40 Indian sugar companies for the period from 2004-05 to 2013-14. The efficiencies are estimated through input-oriented DEA models using one output variable—value of output (VOP) and five input variables—capital cost (CA), employee cost (EMP), raw material (RW), energy & fuel (E&F) and other manufacturing expenses (OME). The sugar companies are classified into integrated and non-integrated categories to know which one achieves higher level of efficiency. Sources of inefficiency in the industry are identified through decomposing the overall technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE). The paper also estimates input-reduction targets for relatively inefficient companies and suggests measures to improve their efficiency level. The findings reveal that the TE does not evince any trend rather it shows fluctuations across years, largely due to erratic and cyclical pattern of sugar production. Further, technical inefficiency in the industry seems to be driven more by the managerial inefficiency than the scale inefficiency, which implies that TE can be improved through better conversion of inputs into output.

Keywords: DEA, slacks, sugar industry, technical efficiency

Procedia PDF Downloads 292

Authors: Rana I. Abdulghani, Amera I. Melhum

Abstract:

With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

Procedia PDF Downloads 360

Authors: Ahmed Tarek, Ahmed Alveed

Abstract:

In the theory of computing, there are a wide variety of direct and indirect proof techniques. However, mathematical induction (MI) stands out to be one of the most powerful proof techniques for proving hypotheses, theorems, and new results. There are variations of mathematical induction-based proof techniques, which are broadly classified into three categories, such as structural induction (SI), weak induction (WI), and strong induction (SI). In this expository paper, several different variants of the mathematical induction techniques are explored, and the specific scenarios are discussed where a specific induction technique stands out to be more advantageous as compared to other induction strategies. Also, the essential difference among the variants of mathematical induction are explored. The points of separation among mathematical induction, recursion, and logical deduction are precisely analyzed, and the relationship among variations of recurrence relations, and mathematical induction are being explored. In this context, the application of recurrence relations, and mathematical inductions are considered together in a single framework for codewords over a given alphabet.

Keywords: alphabet, codeword, deduction, mathematical, induction, recurrence relation, strong induction, structural induction, weak induction

Procedia PDF Downloads 140

Authors: Valentina Dolmova

Abstract:

What consumers choose to buy and who voters select on election days are two questions that have captivated the interest of both academics and practitioners for many decades. The importance of understanding what influences the behavior of those groups and whether or not we can predict or control it fuels a steady stream of research in a range of fields. By looking only at the past 40 years, more than 70 thousand scientific papers have been published in each field – consumer behavior and political psychology, respectively. From marketing, economics, and the science of persuasion to political and cognitive psychology - we have all remained heavily engaged. The ever-evolving technology, inevitable socio-cultural shifts, global economic conditions, and much more play an important role in choice-equations regardless of context. On one hand, this makes the research efforts always relevant and needed. On the other, the relatively low number of cross-field collaborations, which seem to be picking up only in more in recent years, makes the existing findings isolated into framed bubbles. By performing systematic research across both areas of psychology and building a parallel between theories and factors of influence, however, we find that there is not only a definitive common ground between the behaviors of consumers and voters but that we are moving towards a global model of choice. This means that the lines between contexts are fading which has a direct implication on what we should focus on when predicting or navigating buyers and voters’ behavior. Internal and external factors in four main categories determine the choices we make as consumers and as voters. Together, personal, psychological, social, and cultural create a holistic framework through which all stimuli in relation to a particular product or a political party get filtered. The analogy “consumer-voter” solidifies further. Leading academics suggest that this fundamental parallel is the key to managing successfully political and consumer brands alike. However, we distinguish additional four key stimuli that relate to those factor categories (1/ opportunity costs; 2/the memory of the past; 3/recognisable figures/faces and 4/conflict) arguing that the level of expertise a person has determines the prevalence of factors or specific stimuli. Our efforts take into account global trends such as the establishment of “celebrity politics” and the image of “ethically concerned consumer brands” which bridge the gap between contexts to an even greater extent. Scientists and practitioners are pushed to accept the transformative nature of both fields in social psychology. Existing blind spots as well as the limited number of research conducted outside the American and European societies open up space for more collaborative efforts in this highly demanding and lucrative field. A mixed method of research tests three main hypotheses, the first two of which are focused on the level of irrelevance of context when comparing voting or consumer behavior – both from the factors and stimuli lenses, the third on determining whether or not the level of expertise in any field skews the weight of what prism we are more likely to choose when evaluating options.

Keywords: buyers’ behaviour, decision-making, voters’ behaviour, social psychology

Procedia PDF Downloads 131

Authors: Burçe Boyraz

Abstract:

This study examines appearances of brand placement as an alternative communication strategy in television series by focusing on Yalan Dünya which is one of the most popular television series in Turkey. Consequently, this study has a descriptive research design and quantitative content analysis method is used in order to analyze frequency and time data of brand placement appearances in first 3 seasons of Yalan Dünya with 16 episodes. Analysis of brand placement practices in Yalan Dünya is dealt in three categories: episode-based analysis, season-based analysis and comparative analysis. At the end, brand placement practices in Yalan Dünya are evaluated in terms of type, form, duration and legal arrangements. As a result of this study, it is seen that brand placement plays a determinant role in Yalan Dünya content. Also, current legal arrangements make brand placement closer to other traditional communication strategies instead of differing brand placement from them distinctly.

Keywords: advertising, alternative communication strategy, brand placement, Yalan Dünya

Procedia PDF Downloads 222

Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

Procedia PDF Downloads 314

Authors: Leidy M. Aldana, Jorge E. Camargo

Abstract:

Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

Procedia PDF Downloads 29

Authors: Sagir Abubakar

Abstract:

Organization must move along with the employees, because organization should adapt itself to the changing environment. The paper examines the effect of training and development on employee performance. Training and development has an important role in improve the performance, skills and attitude of employee in an organization. Training and development will also help an employee to do his present job or to prepare him for a higher position with increased responsibilities. The paper analyses the employee performance towards training and development conducted in some selected banks within Bauchi metropolis. Review of related literature was done on, training, training objectives, methods and development and its method. A census survey was carried out using staff of GTB and Skye Banks Bauchi branch where a total of 40 questionnaires were administered personally by the researcher and there were 100% responses. Correlation analysis was adopted for the analysis of data collected. The study concludes that 95% of respondents agreed that training and development are vital for both employee and organizations performance. They also suggest that training and development should be made compulsory for all categories of employee in an organization. Training and Development programmes are necessary in any organization for improving the quality of work of the employee.

Keywords: training, development, employee, performance, banks

Procedia PDF Downloads 435

Authors: Aadityaa Singla

Abstract:

The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

Procedia PDF Downloads 114

Authors: Shahbaz G. Hassan

Abstract:

Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.

Keywords: empirical models, mathematical, statistical, water quality

Procedia PDF Downloads 236

Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

Abstract:

Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

Procedia PDF Downloads 177

Authors: Ghada S. Moussa

Abstract:

Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

Procedia PDF Downloads 329

Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

Abstract:

Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

Procedia PDF Downloads 105

Authors: Veena Nair, Srikanth Prakash, Mayuri Wijayasundara

Abstract:

Globally, the textile industry is a key contributor to the generation of solid waste which gets landfilled. Textile waste generation generally occurs in three stages, namely: producer waste, pre-consumer waste, and post-consumer waste. However, the different processes adopted in textile material extraction, manufacturing, and use have their respective impact in terms of the quantity of waste being diverted to landfills. The study is focused on assessing the value chains of the two most common textile fibres: cotton and polyester, catering to a broad categories of apparel products. This study attempts to identify and evaluate the key processes adopted by the textile industry at each of the stages in their value chain in terms of waste generation. The different processes identified in each of the stages in the textile value chains are mapped to their respective contribution in generating fibre waste which eventually gets diverted to landfill. The results of the study are beneficial for the overall industry in terms of improving the traceability of waste in the value chains and the selection of processes and behaviours facilitating the reduction of environmental impacts associated with landfills.

Keywords: textile waste, textile value chains, landfill waste, waste mapping

Procedia PDF Downloads 173

Authors: Evelyn Fabian

Abstract:

The focus of this discussion centres on the emerging issues in Early Childhood Care and development in Nigeria. Early childhood care is the bedrock of Nigeria’s educational system. However, there are critical issues that had not been addressed and it is frustrating the entire educational process. Thus, this paper will show the inter-connectedness between these issues such as poor funding, trained skillful teachers that would supervise the learning process of the kids, unconducive learning environment and lack of relevant facilities. For a clear grasp of these issues, the researcher visited 36 early childhood centres distributed across the 36 spates of Nigeria. The findings which were expressed in simple percentages revealed a near total absence or government neglect of these critical areas. The findings equally showed a misplaced priority in the government allocation of funds to early child care education and development. The study concludes that this mismatch in the training of these categories of pupils, government should expedite action in addressing these emerging issues in early childhood care and development in Nigeria.

Keywords: early childhood, ECCE, education, emerging issues

Procedia PDF Downloads 500

Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

Abstract:

In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: association rules, rule-based classification, classification quality, validation

Procedia PDF Downloads 408

Authors: Laura Cochrane

Abstract:

The United States Centers for Disease Control and Prevention has established three categories of biological agents based on their ease of spread and the severity of the disease they cause. Category A biological agents are the highest priority because of their high degree of morbidity and mortality, ease of dissemination, the potential to cause social disruption and panic, special requirements for public health preparedness, and past use as a biological weapon. Despite the threat of Category A biological agents, opportunities for medical intervention exist. This work summarizes public information, consolidated and reviewed across the situational usefulness and disease awareness to offer discussion to three specific Category A agents: anthrax (Bacillus anthracis), botulism (Clostridium botulinum toxin), and smallpox (variola major), and provides an overview on the management of medical countermeasures available to treat these three (3) different types of pathogens. The medical countermeasures are discussed in the setting of pre-exposure prophylaxis, post-exposure prophylaxis, and therapeutic treatments to provide a framework for requirements in public health preparedness.

Keywords: anthrax, botulism, smallpox, medical countermeasures

Procedia PDF Downloads 50

Authors: Mahdi Aghaei, Saeid Jamshidi, Mastaneh Hajipour

Abstract:

Effective factors on the mechanical wellbore stability are divided in to two categories: 1) Controllable factors, 2) Uncontrollable factors. The purpose of geo-mechanical modeling of wells is to determine the limit of controlled parameters change based on the stress regime at each point and by solving the governing equations the pore-elastic environment around the well. In this research, the mechanical analysis of wellbore stability was carried out for Soroush oilfield. For this purpose, the geo-mechanical model of the field is made using available data. This model provides the necessary parameters for obtaining the distribution of stress around the wellbore. Initially, a basic model was designed to perform various analysis, based on obtained data, using Abaqus software. All of the subsequent sensitivity analysis such as sensitivity analysis on porosity, permeability, etc. was done on the same basic model. The results obtained from these analysis gives various result such as: with the constant geomechanical parameters, and sensitivity analysis on porosity permeability is ineffective. After the most important parameters affecting the wellbore stability and instability are geo-mechanical parameters.

Keywords: wellbore stability, movement, stress, instability

Procedia PDF Downloads 180

Authors: Hamid Fallah

Abstract:

Asphalt is generally a mixture of stone materials with continuous granulation and a binder, which is usually bitumen. Asphalt is made in different shapes according to its use. The most familiar type of asphalt is hot asphalt or hot asphalt concrete. Stone materials usually make up more than 90% of the asphalt mixture. Therefore, stone materials have a significant impact on the quality of the resulting asphalt. According to the method of application and mixing, asphalt is divided into three categories: hot asphalt, protective asphalt, and cold asphalt. Cold mix asphalt is a mixture of stone materials and mixed bitumen or bitumen emulsion whose raw materials are mixed at ambient temperature. In some types of cold asphalt, the bitumen may be heated as necessary, but other materials are mixed with the bitumen without heating. Protective asphalts are used to make the roadbed impermeable, increase its abrasion and sliding resistance, and also temporarily improve the existing asphalt and concrete surfaces. This type of paving is very economical compared to hot asphalt due to the speed and ease of implementation and the limited need for asphalt machines and equipment. The present article, which is prepared in descriptive library form, introduces asphalt, its types, characteristics, and its application.

Keywords: asphalt, type of asphalt, asphalt concrete, sulfur concrete, bitumen in asphalt, sulfur, stone materials

Procedia PDF Downloads 35

Authors: H. Alheeh, M. Alameri, A. Al Tarabsheh

Abstract:

There has been a growing interest in CMOS-based sensors technology in cameras as they afford low-power, small-size, and cost-effective imaging systems. This article describes the CMOS image sensor pixel categories and presents the design and the simulation of the 3-Transistor (3T) Active Pixel Sensor (APS) in MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single pixel sensing circuit, which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for the pixel operation; reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including in dark case, is calculated and showed its inverse proportionality with the light intensity.

Keywords: APS, CMOS image sensor, light intensities photodiode, simulation

Procedia PDF Downloads 140

Authors: Neil Morgan

Abstract:

The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing key knowledge thresholds, it is claimed, can neophytes gain access to the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).

Keywords: TESOL, threshold concepts, TESOL principles, TESOL ITE/INSET, community of practice

Procedia PDF Downloads 114

Authors: Hsiaoping Wu

Abstract:

With the wide use of Internet, learners are exposed to the wider world. This exposure permits learners to discover new information and combine a variety of media in order to reach in-depth and broader understanding of their literacy and the world. Many paper-based teaching, learning and assessment modalities can be transferred to a digital platform. This study examines the use of e-portfolios for ESL (English as a second language) pre-service teacher. The data were collected by reviewing 100 E-portfolio from 2013 to 2015 in order to synthesize meaningful information about e-portfolios for ESL pre-service teachers. Participants were generalists, bilingual and ESL pre-service teachers. The studies were coded into two main categories: learning gains, including assessment, and technical skills. The findings showed that using e-portfolios enhanced and developed ESL pre-service teachers’ teaching and assessment skills. Also, the E-portfolio also developed the pre-service teachers’ technical stills to prepare a comprehensible portfolio to present who they are. Finally, the study and presentation suggested e-portfolios for ecological issues and educational purposes.

Keywords: assessment, e-portfolio, pre-service teacher, reflection

Procedia PDF Downloads 294

Authors: Misrak Assefa

Abstract:

The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

Procedia PDF Downloads 163

Authors: Jean C. A. Sousa, Julio Cesar Maciel Santos, Andressa J. Rubio, Edneia A. S. Paccola, Natália U. Yamaguchi

Abstract:

A bibliometric analysis in the Web of Science database was used to identify overall scientific results of graphene inks to date (2008 to 2018). The objective of this study was to evaluate the evolutionary tendency of graphene inks research and to identify its aspects, aiming to provide data that can guide future work. The contributions of different researches, languages, thematic categories, periodicals, place of publication, institutes, funding agencies, articles cited and applications were analyzed. The results revealed a growing number of annual publications, of 258 papers found, 107 were included because they met the inclusion criteria. Three main applications were identified: synthesis and characterization, electronics and surfaces. The most relevant research on graphene inks has been summarized in this article, and graphene inks for electronic devices presented the most incident theme according to the research trends during the studied period. It is estimated that this theme will remain in evidence and will contribute to the direction of future research in this area.

Keywords: bibliometric, coating, nanomaterials, scientometrics

Procedia PDF Downloads 141

Authors: A. Anis, W. Bekheet, A. El Hakim

Abstract:

Implementing a Road Safety Management System (SMS) in a crowded developing country such as Egypt is a necessity. Beginning a sustainable SMS requires a comprehensive reliable data system for all information pertinent to road crashes. In this paper, a survey for the available data in Egypt and validating it for using in an SMS in Egypt. The research provides some missing data, and refer to the unavailable data in Egypt, looking forward to the contribution of the scientific society, the authorities, and the public in solving the problem of missing or unreliable crash data. The required data for implementing an SMS in Egypt are divided into three categories; the first is available data such as fatality and injury rates and it is proven in this research that it may be inconsistent and unreliable, the second category of data is not available, but it may be estimated, an example of estimating vehicle cost is available in this research, the third is not available and can be measured case by case such as the functional and geometric properties of a facility. Some inquiries are provided in this research for the scientific society, such as how to improve the links among stakeholders of road safety in order to obtain a consistent, non-biased, and reliable data system.

Keywords: road safety management system, road crash, road fatality, road injury

Procedia PDF Downloads 89