Search results for: artificial agency
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2868

Search results for: artificial agency

1248 Estimate Robert Gordon University's Scope Three Emissions by Nearest Neighbor Analysis

Authors: Nayak Amar, Turner Naomi, Gobina Edward

Abstract:

The Scottish Higher Education Institutes must report their scope 1 & 2 emissions, whereas reporting scope 3 is optional. Scope 3 is indirect emissions which embodies a significant component of total carbon footprint and therefore it is important to record, measure and report it accurately. Robert Gordon University (RGU) reported only business travel, grid transmission and distribution, water supply and transport, and recycling scope 3 emissions. This study estimates the RGUs total scope 3 emissions by comparing it with a similar HEI in scale. The scope 3 emission reporting of sixteen Scottish HEI was studied. Glasgow Caledonian University was identified as the nearest neighbour by comparing its students' full time equivalent, staff full time equivalent, research-teaching split, budget, and foundation year. Apart from the peer, data was also collected from the Higher Education Statistics Agency database. RGU reported emissions from business travel, grid transmission and distribution, water supply, and transport and recycling. This study estimated RGUs scope 3 emissions from procurement, student-staff commute, and international student trip. The result showed that RGU covered only 11% of the scope 3 emissions. The major contributor to scope 3 emissions were procurement (48%), student commute (21%), international student trip (16%), and staff commute (4%). The estimated scope 3 emission was more than 14 times the reported emissions. This study has shown the relative importance of each scope 3 emissions source, which gives a guideline for the HEIs, on where to focus their attention to capture maximum scope 3 emissions. Moreover, it has demonstrated that it is possible to estimate the scope 3 emissions with limited data.

Keywords: HEI, university, emission calculations, scope 3 emissions, emissions reporting

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1247 The Effect of Artificial Intelligence on Media Production

Authors: Mona Mikhail Shakhloul Gadalla

Abstract:

The brand-new media revolution, which features a huge range of new media technologies like blogs, social networking, visual worlds, and wikis, has had a tremendous impact on communications, traditional media and across different disciplines. This paper gives an evaluation of the impact of recent media technology on the news, social interactions and conventional media in developing and advanced nations. The look points to the reality that there is a widespread impact of recent media technologies on the news, social interactions and the conventional media in developing and developed nations, albeit undoubtedly and negatively. Social interactions have been considerably affected, in addition to news manufacturing and reporting. It's miles reiterated that regardless of the pervasiveness of recent media technologies, it might now not carry a complete decline of conventional media. This paper contributes to the theoretical framework of the new media and will assist in assessing the extent of the effect of the new media in special places.

Keywords: court reporting, offenders in media, quantitative content analysis, victims in mediamedia literacy, ICT, internet, education communication, media, news, new media technologies, social interactions, traditional media

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1246 Argentine Immigrant Policy: A Qualitative Analysis of Changes and Trends from 2016 on

Authors: Romeu Bonk Mesquita

Abstract:

Argentina is the South American number 1 country of destiny to intraregional migration flows. This research aims to shed light on the main trends of the Argentine immigrant policy from 2016 on, when Mauricio Marci was elected President, taking the approval of the current and fairly protective of human rights Ley de Migraciones (2003) as an analytical starting point. Foreign Policy Analysis (FPA) serves as the theoretical background, highlighting decision-making processes and institutional designs that encourage or constraint political and social actors. The analysis goes through domestic and international levels, observing how immigration policy is formulated as a public policy and is simultaneously connected to Mercosur and other international organizations, such as the International Organization for Migration (IOM) and the United Nations High Commissioner for Refugees (UNHCR). Thus, the study revolves around the Direccion Nacional de Migraciones, which is the state agency in charge of executing the country’s immigrant policy, as to comprehend how its internal processes and the connections it has with both domestic and international institutions shape Argentina’s immigrant policy formulation and execution. Also, it aims to locate the migration agenda within the country’s contemporary social and political context. The methodology is qualitative, case-based and oriented by process-tracing techniques. Empirical evidence gathered includes official documents and data, media coverage and interviews to key-informants. Recent events, such as the Decreto de Necesidad y Urgencia 70/2017 issued by President Macri, and the return of discursive association between migration and criminality, indicate a trend of nationalization and securitization of the immigration policy in contemporary Argentina.

Keywords: Argentine foreign policy, human rights, immigrant policy, Mercosur

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1245 Predictive Models of Ruin Probability in Retirement Withdrawal Strategies

Authors: Yuanjin Liu

Abstract:

Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

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1244 The Role of Social Media for the Movement of Modest Fashion in Indonesia

Authors: Siti Dewi Aisyah

Abstract:

Islamic Modest Fashion has become one of the emerging industries. It is said that social media has making a role in its development. From designers, hijabi bloggers and then instagrammers, they are often seen posting their everyday outfits. They want to combine their faith with cutting-edge fashion trend. Muslim consumers has become a potential targeted market due to the increasing of people wearing hijab. Muslim consumers are projected to spend $327 bilion on clothing by 2020. Indonesia, as the biggest Muslim majority country, has targeted to be The World’s Center for Muslim Fashion in the world as its national branding by 2020. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it also brings consumer culture to hijabi and as the result it triggers Indonesia to brand itself and how all the elements in Indonesia including the designers, bloggers or instagrammers and also Indonesian Agency for Creative Economy together work to make its dream come true. This research will be conducted through interviews with several elements mentioned, and internet, blog, Instagram and Youtube analysis through visual analysis that also examine the semiotic meaning behind the picture that are posted by the people on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, fashion culture and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The possible benefit of this research is to be a reference literature of Islamic Modest Fashion and social media’s role especially in an Indonesian context.

Keywords: blog, instagram, consumer culture, modest fashion, social media, visual analysis

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1243 Charter versus District Schools and Student Achievement: Implications for School Leaders

Authors: Kara Rosenblatt, Kevin Badgett, James Eldridge

Abstract:

There is a preponderance of information regarding the overall effectiveness of charter schools and their ability to increase academic achievement compared to traditional district schools. Most research on the topic is focused on comparing long and short-term outcomes, academic achievement in mathematics and reading, and locale (i.e., urban, v. Rural). While the lingering unanswered questions regarding effectiveness continue to loom for school leaders, data on charter schools suggests that enrollment increases by 10% annually and that charter schools educate more than 2 million U.S. students across 40 states each year. Given the increasing share of U.S. students educated in charter schools, it is important to better understand possible differences in student achievement defined in multiple ways for students in charter schools and for those in Independent School District (ISD) settings in the state of Texas. Data were retrieved from the Texas Education Agency’s (TEA) repository that includes data organized annually and available on the TEA website. Specific data points and definitions of achievement were based on characterizations of achievement found in the relevant literature. Specific data points include but were not limited to graduation rate, student performance on standardized testing, and teacher-related factors such as experience and longevity in the district. Initial findings indicate some similarities with the current literature on long-term student achievement in English/Language Arts; however, the findings differ substantially from other recent research related to long-term student achievement in social studies. There are a number of interesting findings also related to differences between achievement for students in charters and ISDs and within different types of charter schools in Texas. In addition to findings, implications for leadership in different settings will be explored.

Keywords: charter schools, ISDs, student achievement, implications for PK-12 school leadership

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1242 Foggy Image Restoration Using Neural Network

Authors: Khader S. Al-Aidmat, Venus W. Samawi

Abstract:

Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

Procedia PDF Downloads 382
1241 An Investigation into Root Causes of Sabotage and Vandalism of Pipes: A Major Environmental Effluence in Niger Delta, Nigeria

Authors: Oshienemen Albert

Abstract:

Human’s activities could be pointed as the root cause of almost all environmental damages/ disasters as we contribute to the activities that are currently damaging the ozone layers (global warming), unusual environmental changes and extreme weather conditions (climate change) in recent times. Nigeria just as every other disaster-prone nation is faced with different types of disasters and environmental calamities, starting from terrorist displacement disasters, flood, drought and oil spill hazards. Oil spillage as an environmental disaster has great consequences not just on the environment but on human health, economy and the entire populace that might be involved, which deem necessary to look into the root causes of the incidents and how it can be curtailed. The different incidents of oil spillages and other oil production consequent on the environment is alarming in the Nigerian context and cannot be overemphasized without a critical investigation and synthesis. This paper investigates the root causes of environmental pollution induced by oil spill hazards from petroleum activities within Niger Delta communities of effects and detailed the potential solutions to reduce the causal factors and reoccurrence of the incidents. This study adopts a desk-based approach, interviews with key members of communities which consist of chiefs, youth leaders, and key women within the high environmental damaged communities. Also, Interviews were conducted with environmental expertise representatives from the oil and gas sectors and representatives from oil spill-related agency. Data were analyzed using thematic techniques. The study shows different influencing factors of sabotage and vandalism of oil facilities as such; marginalization, deprivation of resources utility and resource derivation principles were identified as major contributors to vandalism and sabotage act. The study proposed potential strategies to curtail the root causes of sabotage and vandalism as the major causes of environmental devastations in Nigeria.

Keywords: environment, oil spill hazards, Niger delta, Nigeria

Procedia PDF Downloads 191
1240 Intrusion Detection Using Dual Artificial Techniques

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

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1239 Machine Learning Automatic Detection on Twitter Cyberbullying

Authors: Raghad A. Altowairgi

Abstract:

With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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1238 Recent Climate Variability and Crop Production in the Central Highlands of Ethiopia

Authors: Arragaw Alemayehu, Woldeamlak Bewket

Abstract:

The aim of this study was to understand the influence of current climate variability on crop production in the central highlands of Ethiopia. We used monthly rainfall and temperature data from 132 points each representing a pixel of 10×10 km. The data are reconstructions based on station records and meteorological satellite observations. Production data of the five major crops in the area were collected from the Central Statistical Agency for the period 2004-2013 and for the main cropping season, locally known as Meher. The production data are at the Enumeration Area (EA ) level and hence the best available dataset on crop production. The results show statistically significant decreasing trends in March–May (Belg) rainfall in the area. However, June – September (Kiremt) rainfall showed increasing trends in Efratana Gidim and Menz Gera Meder which the latter is statistically significant. Annual rainfall also showed positive trends in the area except Basona Werana where significant negative trends were observed. On the other hand, maximum and minimum temperatures showed warming trends in the study area. Correlation results have shown that crop production and area of cultivation have positive correlation with rainfall, and negative with temperature. When the trends in crop production are investigated, most crops showed negative trends and below average production was observed. Regression results have shown that rainfall was the most important determinant of crop production in the area. It is concluded that current climate variability has a significant influence on crop production in the area and any unfavorable change in the local climate in the future will have serious implications for household level food security. Efforts to adapt to the ongoing climate change should begin from tackling the current climate variability and take a climate risk management approach.

Keywords: central highlands, climate variability, crop production, Ethiopia, regression, trend

Procedia PDF Downloads 438
1237 Estimating Poverty Levels from Satellite Imagery: A Comparison of Human Readers and an Artificial Intelligence Model

Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

Abstract:

The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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1236 A Review of Attractor Neural Networks and Their Use in Cognitive Science

Authors: Makenzy Lee Gilbert

Abstract:

This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, reinforcement, retrieval, and forgetting. Key mathematical foundations, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus's role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future exploration areas.

Keywords: attractor neural networks, connectionism, computational modeling, cognitive neuroscience

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1235 Key Performance Indicators and the Model for Achieving Digital Inclusion for Smart Cities

Authors: Khalid Obaed Mahmod, Mesut Cevik

Abstract:

The term smart city has appeared recently and was accompanied by many definitions and concepts, but as a simplified and clear definition, it can be said that the smart city is a geographical location that has gained efficiency and flexibility in providing public services to citizens through its use of technological and communication technologies, and this is what distinguishes it from other cities. Smart cities connect the various components of the city through the main and sub-networks in addition to a set of applications and thus be able to collect data that is the basis for providing technological solutions to manage resources and provide services. The basis of the work of the smart city is the use of artificial intelligence and the technology of the Internet of Things. The work presents the concept of smart cities, the pillars, standards, and evaluation indicators on which smart cities depend, and the reasons that prompted the world to move towards its establishment. It also provides a simplified hypothetical way to measure the ideal smart city model by defining some indicators and key pillars, simulating them with logic circuits, and testing them to determine if the city can be considered an ideal smart city or not.

Keywords: factors, indicators, logic gates, pillars, smart city

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1234 The Development of an Agent-Based Model to Support a Science-Based Evacuation and Shelter-in-Place Planning Process within the United States

Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

Abstract:

The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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1233 Utilizing Waste Heat from Thermal Power Plants to Generate Power by Modelling an Atmospheric Vortex Engine

Authors: Mohammed Nabeel Khan, C. Perisamy

Abstract:

Convective vortices are normal highlights of air that ingest lower-entropy-energy at higher temperatures than they dismiss higher-entropy-energy to space. By means of the thermodynamic proficiency, it has been anticipated that the force of convective vortices relies upon the profundity of the convective layer. The atmospheric vortex engine is proposed as a gadget for delivering mechanical energy by methods for artificially produced vortex. The task of the engine is in view of the certainties that the environment is warmed from the base and cooled from the top. By generation of the artificial vortex, it is planned to take out the physical solar updraft tower and decrease the capital of the solar chimney power plants. The study shows the essentials of the atmospheric vortex engine, furthermore, audits the cutting edge in subject. Moreover, the study talks about a thought on using the solar energy as heat source to work the framework. All in all, the framework is attainable and promising for electrical power production.

Keywords: AVE, atmospheric vortex engine, atmosphere, updraft, vortex

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1232 Synthesis and Properties of Oxidized Corn Starch Based Wood Adhesive

Authors: Salise Oktay, Nilgun Kizilcan, Basak Bengu

Abstract:

At present, formaldehyde-based adhesives such as urea-formaldehyde (UF), melamine-formaldehyde (MF), melamine – urea-formaldehyde (MUF), etc. are mostly used in wood-based panel industry because of their high reactivity, chemical versatility, and economic competitiveness. However, formaldehyde-based wood adhesives are produced from non- renewable resources and also formaldehyde is classified as a probable human carcinogen (Group B1) by the U.S. Environmental Protection Agency (EPA). Therefore, there has been a growing interest in the development of environment-friendly, economically competitive, bio-based wood adhesives to meet wood-based panel industry requirements. In this study, like a formaldehyde-free adhesive, oxidized starch – urea wood adhesives was synthesized. In this scope, firstly, acid hydrolysis of corn starch was conducted and then acid thinned corn starch was oxidized by using hydrogen peroxide and CuSO₄ as an oxidizer and catalyst, respectively. Secondly, the polycondensation reaction between oxidized starch and urea conducted. Finally, nano – TiO₂ was added to the reaction system to strengthen the adhesive network. Solid content, viscosity, and gel time analyses of the prepared adhesive were performed to evaluate the adhesive processability. FTIR, DSC, TGA, SEM characterization techniques were used to investigate chemical structures, thermal, and morphological properties of the adhesive, respectively. Rheological analysis of the adhesive was also performed. In order to evaluate the quality of oxidized corn starch – urea adhesives, particleboards were produced in laboratory scale and mechanical and physical properties of the boards were investigated such as an internal bond, modulus of rupture, modulus of elasticity, formaldehyde emission, etc. The obtained results revealed that oxidized starch – urea adhesives were synthesized successfully and it can be a good potential candidate to use the wood-based panel industry with some developments.

Keywords: nano-TiO₂, corn starch, formaldehyde emission, wood adhesives

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1231 Design and Implementation of Neural Network Based Controller for Self-Driven Vehicle

Authors: Hassam Muazzam

Abstract:

This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

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1230 Harnessing Community Benefits; Case Study of REDD+ in Ghana

Authors: Abdul-Razak Saeed

Abstract:

Addressing the climate change crisis that this generation faces has evolved to include the consideration of a policy mechanism referred to as reduced emissions from deforestation and forest degradation with plus components of conservation, sustainable forest management and enhancement of forest carbon stocks (REDD+). REDD+ emerged from the International level of UNFCCC but its implementation is by developing countries. It challenges the development paradigm of nations that depend on the unsustainable clearing of forests and land use change for economic development whilst posing as an opportunity or risk for forest community livelihoods, institutions and their interaction with the forest resources. As a novel policy mechanism, it is imperative to gain global insight into local contexts of its implementation and to understand local level mobilization of their agency for institutional sustainability as reconfigured by new carbon economy initiatives like REDD+. Using a systematic review process, as the initial stages of this study, secondary data of REDD+ projects across the globe were evaluated to pick up gaps in research and that of on ground REDD+ implementation. Primary data was gathered from 30 actors in the government, NGO, private sector and traditional authorities using face-to-face semi structured interviews in Ghana; participation in meetings and workshops and policy and strategy document reviews. Preliminary findings of the study include REDD+ knowledge being a key determinant of power distribution and affects who shapes the process; in Ghana, informal relationships are playing key roles in advancing REDD+ unlike in traditional forestry and a subjectivity shift of local communities from an 'emotive-link' of environmental care to one of 'economic self-seeking and enriching' domain of thought.

Keywords: climate change, communities, forests, REDD+

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1229 Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering

Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

Abstract:

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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1228 A Review on Water Models of Surface Water Environment

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

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1227 Efficient Rehearsal Free Zero Forgetting Continual Learning Using Adaptive Weight Modulation

Authors: Yonatan Sverdlov, Shimon Ullman

Abstract:

Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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1226 Uncanny Orania: White Complicity as the Abject of the Discursive Construction of Racism

Authors: Daphne Fietz

Abstract:

This paper builds on a reflection on an autobiographical experience of uncanniness during fieldwork in the white Afrikaner settlement Orania in South Africa. Drawing on Kristeva’s theory of abjection to establish a theory of Whiteness which is based on boundary threats, it is argued that the uncanny experience as the emergence of the abject points to a moment of crisis of the author’s Whiteness. The emanating abject directs the author to her closeness or convergence with Orania's inhabitants, that is a reciprocity based on mutual Whiteness. The experienced confluence appeals to the author’s White complicity to racism. With recourse to Butler’s theory of subjectivation, the abject, White complicity, inhabits both the outside of a discourse on racism, and of the 'self', as 'I' establish myself in relation to discourse. In this view, the qualities of the experienced abject are linked to the abject of discourse on racism, or, in other words, its frames of intelligibility. It then becomes clear, that discourse on (overt) racism functions as a necessary counter-image through which White morality is established instead of questioned, because here, by White reasoning, the abject of complicity to racism is successfully repressed, curbed, as completely impossible in the binary construction. Hence, such discourse endangers a preservation of racism in its pre-discursive and structural forms as long as its critique does not encompass its own location and performance in discourse. Discourse on overt racism is indispensable to White ignorance as it covers underlying racism and pre-empts further critique. This understanding directs us towards a form of critique which does necessitate self-reflection, uncertainty, and vigilance, which will be referred to as a discourse of relationality. Such a discourse diverges from the presumption of a detached author as a point of reference, and instead departs from attachment, dependence, mutuality and embraces the visceral as a resource of knowledge of relationality. A discourse of relationality points to another possibility of White engagement with Whiteness and racism and further promotes a conception of responsibility, which allows for and highlights dispossession and relationality in contrast to single agency and guilt.

Keywords: abjection, discourse, relationality, the visceral, whiteness

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1225 From Pink to Ink: Understanding the Decision-Making Process of Post-mastectomy Women Who Have Covered Their Scars with Decorative Tattoos

Authors: Fernanda Rodriguez

Abstract:

Breast cancer is pervasive among women, and an increasing number of women are opting for a mastectomy: a medical operation in which one or both breasts are removed with the intention of treating or averting breast cancer. However, there is an emerging population of cancer survivors in European nations that, rather than attempting to reconstruct their breasts to resemble as much as possible ‘normal’ breasts, have turned to dress their scars with decorative tattoos. At a practical level, this study hopes to improve the support systems of these women by possibly providing professionals in the medical field, tattoo artists, and family members of cancer survivors with a deeper understanding of their motivations and decision-making processes for choosing an alternative restorative route - such as decorative tattoos - after their mastectomy. At an intellectual level, however, this study aims to narrow a gap in the academic field concerning the relationship between mastectomies and alternative methods of healing, such as decorative tattoos, as well as to broaden the understanding regarding meaning-making and the ‘normal’ feminine body. Thus, by means of semi-structured interviews and a phenomenological standpoint, this research set itself the goal to understand why do women who have undergone a mastectomy choose to dress their scars with decorative tattoos instead of attempting to regain ‘normalcy’ through breast reconstruction or 3D areola tattoos? The results obtained from the interviews with fifteen women showed that the disillusionment with one part of the other of breast restoration techniques had led these women to find an alternative form of healing that allows them not only to close a painful chapter of their life but also to regain control over their bodies after a period of time in which agency was taking away from them. Decorative post-mastectomy tattoos allow these women to grant their bodies with new meanings and produce their own interpretation of their feminine body and identity.

Keywords: alternative femininity, decorative mastectomy tattoos, gender embodiment, social stigmatization

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1224 Health and the Politics of Trust: Multi-Drug-Resistant Tuberculosis in Kathmandu

Authors: Mattia Testuzza

Abstract:

Public health is a social endeavour, which involves many different actors: from extremely stratified, structured health systems to unofficial networks of people and knowledge. Health and diseases are an intertwined individual and social experiences. Both patients and health workers navigate this public space through relations of trust. Trust in healthcare goes from the personal trust between a patient and her/his doctor to the trust of both the patient and the health worker in the medical knowledge and the healthcare system. Trust it is not a given, but it is continuously negotiated, given and gained. The key to understand these essential relations of trust in health is to recognise them as a social practice, which therefore implies agency and power. In these terms, health is constantly public and made public, as trust emerges as a meaningfully political phenomenon. Trust as a power relation can be observed at play in the implementation of public health policies such as the WHO’s Directly-Observed Theraphy Short-course (DOTS), and with the increasing concern for drug-resistance that tuberculosis pose, looking at the role of trust in the healthcare delivery system and implementation of public health policies becomes significantly relevant. The ethnographic fieldwork was carried out in four months through observation of the daily practices at the National Tuberculosis Center of Nepal, and semi-structured interviews with MultiDrug-Resistant Tuberculosis (MDR-TB) patients at different stages of the treatment, their relatives, MDR-TB specialised nurses, and doctors. Throughout the research, the role which trust plays in tuberculosis treatment emerged as one fundamental ax that cuts through all the different factors intertwined with drug-resistance development, unfolding a tension between the DOTS policy, which undermines trust, and the day-to-day healthcare relations and practices which cannot function without trust. Trust also stands out as a key component of the solutions to unforeseen issues which develop from the overall uncertainty of the context - for example, political instability and extreme poverty - in which tuberculosis treatment is carried out in Nepal.

Keywords: trust, tuberculosis, drug-resistance, politics of health

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1223 Modelling of Powered Roof Supports Work

Authors: Marcin Michalak

Abstract:

Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.

Keywords: machine modelling, underground mining, coal mining, structure

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1222 The Impact of Artificial Intelligence on Construction Engineering

Authors: Mina Fawzy Ishak Gad Elsaid

Abstract:

There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

Procedia PDF Downloads 45
1221 The Impact of Artificial Intelligence on Construction Engineering

Authors: Haneen Joseph Habib Yeldoka

Abstract:

There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

Procedia PDF Downloads 40
1220 Findings from an Access Improvement Project for Antiretroviral Therapy Uptake through Traditional Birth Attendants at Mother Theresa Hospital, Lagos, Nigeria

Authors: Daniel Afolayan, Christina Olawepo, Francis Olowookanga, Nguhemen Tingir, Olawale Fadare, John Oko

Abstract:

In Nigeria, traditional birth attendants (TBAs) can play an important role in the prevention of mother-to-child transmission of HIV. However, their role in improving access to antiretroviral therapy (ART) is unclear. Catholic Caritas Foundation of Nigeria (Caritas Nigeria) is an implementing agency supporting increased access to HIV testing and treatment services in Lagos state through health facilities including Mother Theresa Hospital. Despite intra-facility testing and community outreaches, ART uptake at Mother Theresa Hospital, Lagos was low with 6 individuals on antiretroviral drugs 3 months post-activation. This study explored improving access to ART through linkages with TBAs for ART uptake at the facility. Plan-Do-Study-Act model was used. The goal was to improve uptake of ART from 6 to 80 in 5 months (end of project year). Scanning revealed a network of 15 TBAs with potential as satellites for HIV testing. Caritas Nigeria linked the facility with 15 TBAs who were provided with HIV test kits and trained on HIV testing services for provider-initiated testing and outreaches. Weekly reports and referrals of positives were received, tracked and feedback given on testing yield. These TBAs serve individuals of various age and gender at their trado-medical centres. At the end of 5 months, HIV testing increased by 10,575 (78% from TBAs) and HIV positives obtained improved by 77 (44.2% from TBAs). 55 new individuals were enrolled and commenced on ART (61.8% from TBAs). There was a successful linkage of all clients with escort services due to incentives. Total uptake of ART was 61 (76.3% of target). Structured partnerships between TBAs and HIV care and treatment centers should be strengthened to improve access to ART.

Keywords: access improvement, antiretroviral therapy, traditional birth attendants, uptake

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1219 Prosodic Characteristics of Post Traumatic Stress Disorder Induced Speech Changes

Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

Abstract:

This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

Procedia PDF Downloads 90