Search results for: automatic question answering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2990

Search results for: automatic question answering

2030 Multi-Agent System for Irrigation Using Fuzzy Logic Algorithm and Open Platform Communication Data Access

Authors: T. Wanyama, B. Far

Abstract:

Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

Procedia PDF Downloads 292
2029 A General Approach to Define Adjoint of Linear and Non-linear Operators

Authors: Mehdi Jafari Matehkolaee

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In this paper, we have obtained the adjoint of an arbitrary operator (linear and nonlinear) in Hilbert space by introducing an n-dimensional Riemannian manifold. This general formalism covers every linear operator (non – differential) in Hilbert space. In fact, our approach shows that instead of using the adjoint definition of an operator directly, it can be obtained directly by relying on a suitable generalized space according to the action of the operator in question. For the case of nonlinear operators, we have to change the definition of the linear operator adjoint. But here, we have obtained an adjoint of these operators with respect to the definition of the derivative of the operator. As a matter of fact, we have shown one of the straight applications of the ''Frechet derivative'' in the algebra of the operators.

Keywords: adjoint operator, non-linear operator, differentiable operator, manifold

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2028 Benefits of Tourist Experiences for Families: A Systematic Literature Review Using Nvivo

Authors: Diana Cunha, Catarina Coelho, Ana Paula Relvas, Elisabeth Kastenholz

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Context: Tourist experiences have a recognized impact on the well-being of individuals. However, studies on the specific benefits of tourist experiences for families are scattered across different disciplines. This study aims to systematically review the literature to synthesize the evidence on the benefits of tourist experiences for families. Research Aim: The main objective is to systematize the evidence in the literature regarding the benefits of tourist experiences for families. Methodology: A systematic literature review was conducted using Nvivo, analyzing 33 scientific studies obtained from various databases. The search terms used were "family"/ "couple" and "tourist experience". The studies included quantitative, qualitative, mixed methods, and literature reviews. All works prior to the year 2000 were excluded, and the search was restricted to full text. A language filter was also used, considering articles in Portuguese, English, and Spanish. For NVivo analysis, information was coded based on both deductive and inductive perspectives. To minimize the subjectivity of the selection and coding process, two of the authors discussed the process and agreed on criteria that would make the coding more objective. Once the coding process in NVivo was completed, the data relating to the identification/characterization of the works were exported to the Statistical Package for the Social Sciences (SPPS), to characterize the sample. Findings: The results highlight that tourist experiences have several benefits for family systems, including the strengthening of family and marital bonds, the creation of family memories, and overall well-being and life satisfaction. These benefits contribute to both immediate relationship quality improvement and long-term family identity construction and transgenerational transmission. Theoretical Importance: This study emphasizes the systemic nature of the effects and relationships within family systems. It also shows that no harm was reported within these experiences, with only some challenges related to positive outcomes. Data Collection and Analysis Procedures: The study collected data from 33 scientific studies published predominantly after 2013. The data were analyzed using Nvivo, employing a systematic review approach. Question Addressed: The study addresses the question of the benefits of tourist experiences for families and how these experiences contribute to family functioning and individual well-being. Conclusion: Tourist experiences provide opportunities for families to enhance their interpersonal relationships and create lasting memories. The findings suggest that formal interventions based on evidence could further enhance the potential benefits of these experiences and be a valuable preventive tool in therapeutic interventions.

Keywords: family systems, individual and family well-being, marital satisfaction, tourist experiences

Procedia PDF Downloads 65
2027 Intelligent Control of Agricultural Farms, Gardens, Greenhouses, Livestock

Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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2026 Digital Retinal Images: Background and Damaged Areas Segmentation

Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

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Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

Procedia PDF Downloads 396
2025 Economic Assessment Methodology to Support Decisions for Transport Infrastructure Development

Authors: Dimitrios J. Dimitriou

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The decades after the end of the second War provide evidence that infrastructures investments contibute to economic development, on terms of productivity and income growth. In order to force productivity and increase competitiveness the financing of large transport infrastructure projects are on the top of the agenda in strategic planning process. Such a decision may take form some days to some decades and stakeholders as well as decision makers need tools in order to estimate the economic impact on natioanl economy of such an investment. The key question in such decisions is if the effects caused by the new infrastructure could be able to boost economic development on one hand, and create new jobs and activities on the other. This paper deals with the review of estimation of the mega transport infrastructure projects economic effects in economy.

Keywords: economic impact, transport infrastructure, strategic planning, decision making

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2024 The Impact of Artificial Intelligence on Human Rights Development

Authors: Romany Wagih Farag Zaky

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The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 51
2023 Practice of Social Audit in Hotel Companies: Case Study of Agadir, Morocco

Authors: M. El Mousadik, F. Elkandoussi

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The concern for increased rigor in social management has led more and more Moroccan business leaders to question the value of applying social audit as an essential tool in the management of human resources. Hotel companies are not excluded; in fact, they are expected to implement such an audit to develop sound and credible human resources management (HRM) policies. The main objective of this paper is to establish the relationship between the practice of social audit as a tool, and its impact on the tourism sector, especially on hotels at one of the Morocco’s first and most popular city for tourism, Agadir. This exploratory study of properties in Agadir has revealed that hotel executives are aware of the importance of social auditing to hone their decisions in the field of HRM.

Keywords: social audit, hotel companies, human resources management, social piloting

Procedia PDF Downloads 275
2022 An Accurate Brain Tumor Segmentation for High Graded Glioma Using Deep Learning

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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2021 From Linear to Nonlinear Deterrence: Deterrence for Rising Power

Authors: Farhad Ghasemi

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Along with transforming the international system into a complex and chaotic system, the fundamental question arises: how can deterrence be reconstructed conceptually and theoretically in this system model? The deterrence system is much more complex today than it was seven decades ago. This article suggests that the perception of deterrence as a linear system is a fundamental mistake because it does not consider the new dynamics of the international system, including network power dynamics. The author aims to improve this point by focusing on complexity and chaos theories, especially their nonlinearity and cascading failure principles. This article proposes that the perception of deterrence as a linear system is a fundamental mistake, as the new dynamics of the surrounding international system do not take into account. The author recognizes deterrence as a nonlinear system and introduces it as a concept in strategic studies.

Keywords: complexity, international system, deterrence, linear deterrence, nonlinear deterrence

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2020 Distributed Processing for Content Based Lecture Video Retrieval on Hadoop Framework

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

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There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

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2019 Segmentation of Arabic Handwritten Numeral Strings Based on Watershed Approach

Authors: Nidal F. Shilbayeh, Remah W. Al-Khatib, Sameer A. Nooh

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Arabic offline handwriting recognition systems are considered as one of the most challenging topics. Arabic Handwritten Numeral Strings are used to automate systems that deal with numbers such as postal code, banking account numbers and numbers on car plates. Segmentation of connected numerals is the main bottleneck in the handwritten numeral recognition system.  This is in turn can increase the speed and efficiency of the recognition system. In this paper, we proposed algorithms for automatic segmentation and feature extraction of Arabic handwritten numeral strings based on Watershed approach. The algorithms have been designed and implemented to achieve the main goal of segmenting and extracting the string of numeral digits written by hand especially in a courtesy amount of bank checks. The segmentation algorithm partitions the string into multiple regions that can be associated with the properties of one or more criteria. The numeral extraction algorithm extracts the numeral string digits into separated individual digit. Both algorithms for segmentation and feature extraction have been tested successfully and efficiently for all types of numerals.

Keywords: handwritten numerals, segmentation, courtesy amount, feature extraction, numeral recognition

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2018 Air-Coupled Ultrasonic Testing for Non-Destructive Evaluation of Various Aerospace Composite Materials by Laser Vibrometry

Authors: J. Vyas, R. Kazys, J. Sestoke

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Air-coupled ultrasonic is the contactless ultrasonic measurement approach which has become widespread for material characterization in Aerospace industry. It is always essential for the requirement of lightest weight, without compromising the durability. To archive the requirements, composite materials are widely used. This paper yields analysis of the air-coupled ultrasonics for composite materials such as CFRP (Carbon Fibre Reinforced Polymer) and GLARE (Glass Fiber Metal Laminate) and honeycombs for the design of modern aircrafts. Laser vibrometry could be the key source of characterization for the aerospace components. The air-coupled ultrasonics fundamentals, including principles, working modes and transducer arrangements used for this purpose is also recounted in brief. The emphasis of this paper is to approach the developed NDT techniques based on the ultrasonic guided waves applications and the possibilities of use of laser vibrometry in different materials with non-contact measurement of guided waves. 3D assessment technique which employs the single point laser head using, automatic scanning relocation of the material to assess the mechanical displacement including pros and cons of the composite materials for aerospace applications with defects and delaminations.

Keywords: air-coupled ultrasonics, contactless measurement, laser interferometry, NDT, ultrasonic guided waves

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2017 A Comparison between Five Indices of Overweight and Their Association with Myocardial Infarction and Death, 28-Year Follow-Up of 1000 Middle-Aged Swedish Employed Men

Authors: Lennart Dimberg, Lala Joulha Ian

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Introduction: Overweight (BMI 25-30) and obesity (BMI 30+) have consistently been associated with cardiovascular (CV) risk and death since the Framingham heart study in 1948, and BMI was included in the original Framingham risk score (FRS). Background: Myocardial infarction (MI) poses a serious threat to the patient's life. In addition to BMI, several other indices of overweight have been presented and argued to replace FRS as more relevant measures of CV risk. These indices include waist circumference (WC), waist/hip ratio (WHR), sagittal abdominal diameter (SAD), and sagittal abdominal diameter to height (SADHtR). Specific research question: The research question of this study is to evaluate the interrelationship between the various body measurements, BMI, WC, WHR, SAD, and SADHtR, and which measurement is strongly associated with MI and death. Methods: In 1993, 1,000 middle-aged Caucasian, randomly selected working men of the Swedish Volvo-Renault cohort were surveyed at a nurse-led health examination with a questionnaire, EKG, laboratory tests, blood pressure, height, weight, waist, and sagittal abdominal diameter measurements. Outcome data of myocardial infarction over 28 years come from Swedeheart (the Swedish national myocardial infarction registry) and the Swedish death registry. The Aalen-Johansen and Kaplan–Meier methods were used to estimate the cumulative incidences of MI and death. Multiple logistic regression analyses were conducted to compare BMI with the other four body measurements. The risk for the various measures of obesity was calculated with outcomes of accumulated first-time myocardial infarction and death as odds ratios (OR) in quartiles. The ORs between the 4th and the 1st quartile of each measure were calculated to estimate the association between the body measurement variables and the probability of cumulative incidences of myocardial infarction (MI) over time. Double-sided P values below 0.05 will be considered statistically significant. Unadjusted odds ratios were calculated for obesity indicators, MI, and death. Adjustments for age, diabetes, SBP, and the ratio of total cholesterol/HDL-C and blue/white collar status were performed. Results: Out of 1000 people, 959 subjects had full information about the five different body measurements. Of those, 90 participants had a first MI, and 194 persons died. The study showed that there was a high and significant correlation between the five different body measurements, and they were all associated with CVD risk factors. All body measurements were significantly associated with MI, with the highest (OR=3.6) seen for SADHtR and WC. After adjustment, all but SADHtR remained significant with weaker ORs. As for all-cause mortality, WHR (OR=1.7), SAD (OR=1.9), and SADHtR (OR=1.6) were significantly associated, but not WC and BMI. However, after adjustment, only WHR and SAD were significantly associated with death, but with attenuated ORs.

Keywords: BMI, death, epidemiology, myocardial infarction, risk factor, sagittal abdominal diameter, sagittal abdominal diameter to height, waist circumference, waist-hip ratio

Procedia PDF Downloads 90
2016 Data Modeling and Calibration of In-Line Pultrusion and Laser Ablation Machine Processes

Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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2015 How to Applicate Knowledge Management in Security Environment within the Scope of Optimum Balance Model

Authors: Hakan Erol, Altan Elibol, Ömer Eryılmaz, Mehmet Şimşek

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Organizations aim to manage information in a most possible effective way for sustainment and development. In doing so, they apply various procedures and methods. The very same situation is valid for each service of Armed Forces. During long-lasting endeavors such as shaping and maintaining security environment, supporting and securing peace, knowledge management is a crucial asset. Optimum Balance Model aims to promote the system from a decisive point to a higher decisive point. In this context, this paper analyses the application of optimum balance model to knowledge management in Armed Forces and tries to find answer to the question how Optimum Balance Model is integrated in knowledge management.

Keywords: optimum balance model, knowledge management, security environment, supporting peace

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2014 Design of Target Selection for Pedestrian Autonomous Emergency Braking System

Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

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An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

Procedia PDF Downloads 153
2013 Menopause Hormone Therapy: An Insight into Knowledge and Attitudes of Obstetricians and Gynecologists in Singapore

Authors: Tan Hui Ying Renee, Stella Rizalina Sasha, Farah Safdar Husain

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Introduction: Menopause Hormone Therapy (MHT) is an effective drug indicated for the treatment of menopausal symptoms and as replacement therapy in women who undergo premature menopause. In 2020, less than 8.8% of perimenopausal Singaporean women are on hormonal therapy, as compared to the Western population, where up to 50% may be on MHT. Factors associated with MHT utilization have been studied from patient characteristics, but the impact of locally prescribing physicians resulting in low MHT utilization has yet to be evaluated. The aim of the study is to determine the level of knowledge physicians in the Obstetrics and Gynaecology specialty have and their attitudes toward MHT. We believe that knowledge of MHT is lacking and that negative attitudes towards MHT may influence its use and undermine the benefits MHT may have for women. This paper is a part of a larger study on Singaporean physicians’ knowledge and attitudes towards MHT. Methods: This is a cross-sectional study intended to assess the knowledge and attitudes of physicians toward Menopausal Hormone Therapy. An anonymous questionnaire was disseminated via institutional internal circulations to optimize reach to physicians who may prescribe MHT, particularly in the fields of Gynaecology, Family Medicine and Endocrinology. Responses were completed voluntarily. Physicians had the option for each question to declare that they were ‘unsure’ or that the question was ‘beyond their expertise’. 21 knowledge questions tested factual recall on indications, contraindications, and risks of MHT. The remaining 6 questions were clinical scenarios crafted with the intention of testing specific principles related to the use of MHT. These questions received face validation from experts in the field. 198 responses were collected, 79 of which were from physicians in the Obstetrics and Gynaecology specialty. The data will be statistically analyzed to investigate areas that can be improved to increase the overall benefits of MHT for the Singaporean population. Results: Preliminary results show that the prevailing factors that limit Singaporean gynecologists and obstetricians from prescribing MHT are a lack of knowledge of MHT and a lack of confidence in prescribing MHT. Risks and indications of MHT were not well known by many physicians, with the majority of the questions having more than 25% incorrect and ‘unsure’ as their reply. The clinical scenario questions revealed significant shortcomings in knowledge on how to navigate real-life challenges in MHT use, with 2 of 6 questions with more than 50% incorrect or ‘beyond their expertise’ as their reply. The portion of the questionnaire that investigated the attitudes of physicians showed that though a large majority believed MHT to be an effective drug, only 40.5% were confident in prescribing it. Conclusion: Physicians in the Obstetrics and Gynaecology specialty lack knowledge and confidence in MHT. Therefore, it is imperative to formulate solutions on both the individual and institutional levels to fill these gaps and ensure that MHT is used appropriately and prescribed to the patients who need it.

Keywords: menopause, menopause hormone therapy, physician factors, obstetrics and gynecology, menopausal symptoms, Singapore

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2012 Environmental Impacts on Urban Agriculture in Algiers

Authors: Sara Bouzekri, Said Madani

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In many Mediterranean cities such as Algiers, the human activity, the strong mobility the urban sprawl, the air pollution, the problems of waste management, the wasting of the resources and the degradation of the environment weaken in an unquestionable way the farming. The question of sustainable action vis-a-vis these threats arises then in order to maintain a level of desired local development. The methodology is based on a multi-criteria method based on the AFOM diagnosis, which classifies agricultural strength indicators and those of threat, according to an analytical approach. In a sustainable development perspective, it will be appropriate to link the threat factors of the case study with the factors of climate change to see their impact on the future of agriculture. This will be accompanied by a SWOT analysis, which crosses the most significant criteria to arrive at the necessary recommendations based on future projects for urban agriculture.

Keywords: Algiers, environment, urban agriculture, threat factors

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2011 VIAN-DH: Computational Multimodal Conversation Analysis Software and Infrastructure

Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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2010 The Evloution of LGBTQ Right in the U. S.: The Vaugries of Presidential Leadership and Followership

Authors: Michael A. Genovese

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The struggle for LGBTQ rights in the United States began in Greenwich Village, New York, in 1967, when police tried to break up a gathering of mostly gay men who were partying at the Stonewall Bar in NYC. As unlikely as it may sound, this “riot” proved to be consequential in raising the political consciousness of gay men in America. From that point on, gays engaged in a political battle to achieve the rights to which they were entitled. This essay examines changes in popular opinion regarding LGBTQ rights from the late 1960s through the Trump administration, and examines the role public pressure played on presidential politics. For most of this period, presidents “followed” public opinion. This was true even during the administration of Barack Obama when gay Americans finally achieved some clearly spelled out rights (e.g. same-sex marriage). The findings of this paper call into question certain assumptions about presidential leadership, and underline the power of public opinion in shaping policy.

Keywords: presidential leadership, gay rights, LGBTQ, popular opinion

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2009 An Exploration of Policy-related Documents on District Heating and Cooling in Flanders: a Slow and Bottom-up Process

Authors: Isaura Bonneux

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District heating and cooling (DHC) is increasingly recognized as a viable path towards sustainable heating and cooling. While some countries like Sweden and Denmark have a longstanding tradition of DHC, Belgium is lacking behind. The Northern part of Belgium, Flanders, had only a total of 95 heating networks in July 2023. Nevertheless, it is increasingly exploring its possibilities to enhance the scope of DHC. DHC is a complex energy system, requiring a lot of collaboration between various stakeholders on various levels. Therefore, it is of interest to look closer at policy-related documents at the Flemish (regional) level, as these policies set the scene for DHC development in the Flemish region. This kind of analysis has not been undertaken so far. This paper has the following research question: “Who talks about DHC, and in which way and context is DHC discussed in Flemish policy-related documents?” To answer this question, the Overton policy database was used to search and retrieve relevant policy-related documents. Overton retrieves data from governments, think thanks, NGOs, and IGOs. In total, out of the 244 original results, 117 documents between 2009 and 2023 were analyzed. Every selected document included theme keywords, policymaking department(s), date, and document type. These elements were used for quantitative data description and visualization. Further, qualitative content analysis revealed patterns and main themes regarding DHC in Flanders. Four main conclusions can be drawn: First, it is obvious from the timeframe that DHC is a new topic in Flanders with still limited attention; 2014, 2016 and 2017 were the years with the most documents, yet this number is still only 12 documents. In addition, many documents talked about DHC but not much in depth and painted it as a future scenario with a lot of uncertainty around it. The largest part of the issuing government departments had a link to either energy or climate (e.g. Flemish Environmental Agency) or policy (e.g. Socio-Economic Council of Flanders) Second, DHC is mentioned most within an ‘Environment and Sustainability’ context, followed by ‘General Policy and Regulation’. This is intuitive, as DHC is perceived as a sustainable heating and cooling technique and this analysis compromises policy-related documents. Third, Flanders seems mostly interested in using waste or residual heat as a heating source for DHC. The harbors and waste incineration plants are identified as potential and promising supply sources. This approach tries to conciliate environmental and economic incentives. Last, local councils get assigned a central role and the initiative is mostly taken by them. The policy documents and policy advices demonstrate that Flanders opts for a bottom-up organization. As DHC is very dependent on local conditions, this seems a logic step. Nevertheless, this can impede smaller councils to create DHC networks and slow down systematic and fast implementation of DHC throughout Flanders.

Keywords: district heating and cooling, flanders, overton database, policy analysis

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2008 Autism Spectrum Disorder Classification Algorithm Using Multimodal Data Based on Graph Convolutional Network

Authors: Yuntao Liu, Lei Wang, Haoran Xia

Abstract:

Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

Procedia PDF Downloads 59
2007 How Does Improving the Existing DSL Infrastructure Influences the Expansion of Fiber Technology?

Authors: Peter Winzer, Erik Massarczyk

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Experts, enterprises and operators expect that the bandwidth request will increase up to rates of 100 to 1,000 Mbps within several years. Therefore the most important question is, which technology shall satisfy the future consumer broadband demands. Currently the consensus is, that the fiber technology has the best technical characteristics to achieve such the high bandwidth rates. But fiber technology is so far very cost-intensive and resource consuming. To avoid these investments, operators are concentrating to upgrade the existing copper and hybrid fiber coax infrastructures. This work presents a comparison of the copper and fiber technologies including an overview about the current German broadband market. Both technologies are reviewed in the terms of demand, willingness to pay and economic efficiency in connection with the technical characteristics.

Keywords: broadband customer demand, fiber development, g.fast, vectoring, willingness to pay for broadband services

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2006 A Deep-Learning Based Prediction of Pancreatic Adenocarcinoma with Electronic Health Records from the State of Maine

Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

Abstract:

Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

Procedia PDF Downloads 153
2005 A Study Regarding Nanotechnologies as a Vector of New European Business Model

Authors: Adriana Radan Ungureanu

Abstract:

The industrial landscape is changing due to the financial crises, poor availability of raw materials, new discoveries and interdisciplinary collaborations. New ideas shape the change through technologies and bring responses for a better life. The process of change is leaded by big players like states and companies, but they cannot keep their places on the market without the help of the small ones. The main tool of change is technology and the entire developed world dedicated efforts for decades in this direction. Even the expectations are not yet met, the research for finding adequate solutions is far from to be stopped. A relevant example is nanotechnology where most of discoveries still remain into laboratory and could not succeed to find the right way to the market. In front of this situation the right question could be: ”Is it worth investing in nanotechnology in the name of an uncertain future but with very little impact on present?” This paper tries to find a positive answer from a three-dimensional approach using a descriptive analyse based on available database supplied by the European case studies, reports, and literature.

Keywords: Europe, KET’s, nanotechnology, technology

Procedia PDF Downloads 413
2004 Removing the Veils of Caste from the Face of Islam in the Sub-Continent

Authors: Elaheh Ghasempour

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India has always been an all-encompassing center of attention in the theological and cultural studies since it beholds a very diverse nation within its borders. Among the uncountable faiths and traditions of this massive land, this article shall negotiate Islam in a Hindu dominated society. Practicing Caste and the views on it are the most controversial topics in modern-day India. Some blame it on the teachings of Hinduism; some call it a colonial outcome; and yet many believe that it is, in fact, a social construct. Islam was the souvenir coming from the Arabian Peninsula into the Indian Subcontinent in the hands of Arab, Persian, and Turk religious missionaries and Sufi saints. The aim of bringing the faith to this region was to enlighten the people of East and the Far East with the ideas of peace, justice, brotherhood as well as a proper way of living. Due to many reasons, the concept of the Islamic Nation or ‘Ummah’ has been touched by the native teachings of Hinduism which negates and questions the actual Islamic principles and laws. The Islamic Nation in India has been parted to different classes and each class nowadays beholds one level of a hierarchy. The superiors do not hesitate to keep the inferiors oppressed as much as they can since their own high position in this hierarchy depends on such oppressions. Their rules and laws to keep the lower castes out of the political and economical scene found ways into the religious traditions so much that it has become hard to question it by the masses; the masses who are too uneducated to question their own heretical faith and traditions. But now that the world is rapidly evolving, the access to knowledge has evoked an awareness of many lower caste or ‘Dalit’ Muslims. They no longer wish to be oppressed for their ethnicity or rootless principles of the old generations to guarantee the survival of the higher caste Muslims or ‘Ashrafs’. In recent years, many have stood against the rules of the caste system. As the oppressed no longer wishes to be oppressed, they also show acts of violence against the rulers who destined them the life they currently have. Considering they are usually poor and uneducated, and they might do violent actions, this can threaten not only Indians but the whole world; especially because the ISIS can easily fund a troop of hungry men who are looking forward to revenge their masters and others for all the unjust discriminations. Therefore for the sake of social security and stopping the disrepute for followers of Islam, the entire Islamic nation must consider taking actions against practicing Caste, regardless of where they come from. Since the teachings of the Quran and the Sunnah of the Prophet (PBUH) invite all Muslims to practice equality and brotherhood in the Ummah, this article would find the practical ways to abolish the caste-system through the Islamic liturgical texts and traditions.

Keywords: Dalit Muslims, Islam in India, caste system, justice in Islam, violence

Procedia PDF Downloads 200
2003 Estimating PM2.5 Concentrations Based on Landsat 8 Imagery and Historical Field Data over the Metropolitan Area of Mexico City

Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

Abstract:

High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

Procedia PDF Downloads 189
2002 On a Theoretical Framework for Language Learning Apps Evaluation

Authors: Juan Manuel Real-Espinosa

Abstract:

This paper addresses the first step to evaluate language learning apps: what theoretical framework to adopt when designing the app evaluation framework. The answer is not just one since there are several options that could be proposed. However, the question to be clarified is to what extent the learning design of apps is based on a specific learning approach, or on the contrary, on a fusion of elements from several theoretical proposals and paradigms, such as m-learning, mobile assisted language learning, and a number of theories about language acquisition. The present study suggests that the reality is closer to the second assumption. This implies that the theoretical framework against which the learning design of the apps should be evaluated must also be a hybrid theoretical framework, which integrates evaluation criteria from the different theories involved in language learning through mobile applications.

Keywords: mobile-assisted language learning, action-oriented approach, apps evaluation, post-method pedagogy, second language acquisition

Procedia PDF Downloads 200
2001 Data Augmentation for Automatic Graphical User Interface Generation Based on Generative Adversarial Network

Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

Abstract:

As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

Procedia PDF Downloads 178