Search results for: iterative rational Krylov algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4257

Search results for: iterative rational Krylov algorithm

1707 A Generative Pretrained Transformer-Based Question-Answer Chatbot and Phantom-Less Quantitative Computed Tomography Bone Mineral Density Measurement System for Osteoporosis

Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

Abstract:

Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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1706 Tiebout and Crime: How Crime Affect the Income Tax Capacity

Authors: Nik Smits, Stijn Goeminne

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Despite the extensive literature on the relation between crime and migration, not much is known about how crime affects the tax capacity of local communities. This paper empirically investigates whether the Flemish local income tax base yield is sensitive to changes in the local crime level. The underlying assumptions are threefold. In a Tiebout world, rational voters holding the local government accountable for the safety of its citizens, move out when the local level of security gets too much alienated from what they want it to be (first assumption). If migration is due to crime, then the more wealthy citizens are expected to move first (second assumption). Looking for a place elsewhere implies transaction costs, which the more wealthy citizens are more likely to be able to pay. As a consequence, the average income per capita and so the income distribution will be affected, which in turn, will influence the local income tax base yield (third assumption). The decreasing average income per capita, if not compensated by increasing earnings by the citizens that are staying or by the new citizens entering the locality, must result in a decreasing local income tax base yield. In the absence of a higher level governments’ compensation, decreasing local tax revenues could prove to be disastrous for a crime-ridden municipality. When communities do not succeed in forcing back the number of offences, this can be the onset of a cumulative process of urban deterioration. A spatial panel data model containing several proxies for the local level of crime in 306 Flemish municipalities covering the period 2000-2014 is used to test the relation between crime and the local income tax base yield. In addition to this direct relation, the underlying assumptions are investigated as well. Preliminary results show a modest, but positive relation between local violent crime rates and the efflux of citizens, persistent up until a 2 year lag. This positive effect is dampened by possible increasing crime rates in neighboring municipalities. The change in violent crimes -and to a lesser extent- thefts and extortions reduce the influx of citizens with a one year lag. Again this effect is diminished by external effects from neighboring municipalities, meaning that increasing crime rates in neighboring municipalities (especially violent crimes) have a positive effect on the local influx of citizens. Crime also has a depressing effect on the average income per capita within a municipality, whereas increasing crime rates in neighboring municipalities increase it. Notwithstanding the previous results, crime does not seem to significantly affect the local tax base yield. The results suggest that the depressing effect of crime on the income basis has to be compensated by a limited, but a wealthier influx of new citizens.

Keywords: crime, local taxes, migration, Tiebout mobility

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1705 Practical Problems as Tools for the Development of Secondary School Students’ Motivation to Learn Mathematics

Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: mathematics, motivation, secondary school, student, practical problem

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1704 Secured Transmission and Reserving Space in Images Before Encryption to Embed Data

Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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1703 Improved Particle Swarm Optimization with Cellular Automata and Fuzzy Cellular Automata

Authors: Ramin Javadzadeh

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The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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1702 Detect QOS Attacks Using Machine Learning Algorithm

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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1701 Application of Artificial Intelligence to Schedule Operability of Waterfront Facilities in Macro Tide Dominated Wide Estuarine Harbour

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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1700 Energy Usage in Isolated Areas of Honduras

Authors: Bryan Jefry Sabillon, Arlex Molina Cedillo

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Currently, the raise in the demand of electrical energy as a consequence of the development of technology and population growth, as well as some projections made by ‘La Agencia Internacional de la Energía’ (AIE) and research institutes, reveal alarming data about the expected raise of it in the next few decades. Because of this, something should be made to raise the awareness of the rational and efficient usage of this resource. Because of the global concern of providing electrical energy to isolated areas, projects consisting of energy generation using renewable resources are commonly carried out. On a socioeconomically and cultural point of view, it can be foreseen a positive impact that would result for the society to have this resource. This article is focused on the great potential that Honduras shows, as a country that is looking forward to produce renewable energy due to the crisis that it’s living nowadays. Because of this, we present a detailed research that exhibits the main necessities that the rural communities are facing today, to allay the negative aspects due to the scarcity of electrical energy. We also discuss which should be the type of electrical generation method to be used, according to the disposition, geography, climate, and of course the accessibility of each area. Honduras is actually in the process of developing new methods for the generation of energy; therefore, it is of our concern to talk about renewable energy, the exploitation of which is a global trend. Right now the countries’ main energetic generation methods are: hydrological, thermic, wind, biomass and photovoltaic (this is one of the main sources of clean electrical generation). The use of these resources was possible partially due to the studies made by the organizations that focus on electrical energy and its demand, such as ‘La Cooperación Alemana’ (GIZ), ‘La Secretaria de Energía y Recursos Naturales’ (SERNA), and ‘El Banco Centroamericano de Integración Económica’ (BCIE), which eased the complete guide that is to be used in the protocol to be followed to carry out the three stages of this type of projects: 1) Licences and Permitions, 2) Fincancial Aspects and 3) The inscription for the Protocol in Kyoto. This article pretends to take the reader through the necessary information (according to the difficult accessibility that each zone might present), about the best option of electrical generation in zones that are totally isolated from the net, pretending to use renewable resources to generate electrical energy. We finally conclude that the usage of hybrid systems of generation of energy for small remote communities brings about a positive impact, not only because of the fact of providing electrical energy but also because of the improvements in education, health, sustainable agriculture and livestock, and of course the advances in the generation of energy which is the main concern of this whole article.

Keywords: energy, isolated, renewable, accessibility

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1699 Self-Tuning Robot Control Based on Subspace Identification

Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

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1698 Natural Convection of a Nanofluid in a Conical Container

Authors: Brahim Mahfoud, Ali Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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1697 Social Mentoring: Towards Formal and Informal Deployment in the Structures of the Social and Solidarity Economy

Authors: Vanessa Casadella, Mourad Chouki, Agnès Ceccarelli, Sofiane Tahi

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Mentoring is positioned in an interpersonal and intergenerational perspective, serving the transmission of interpersonal skills and organizational culture. It echoes orientation, project, self-actualization, guidance, transmission, and filiation. It is available using a formal or informal approach. The formal dimension refers to a privileged relationship between a senior and a junior. Informal mentoring is unplanned and emerges naturally between two people who choose each other. However, it remains more difficult to understand. To study the link between formal and informal mentoring and to define the notion of “social” mentoring, we conducted a qualitative study of an exploratory nature with around ten SSE organizations located in the southeast region of Tunisia. The wealth of this territory has pushed residents to found SSE organizations with a view to creating jobs but also to preserving traditions and preserving nature. These organizations developed spontaneously to solve various local problems, such as the revitalization of deserted rural areas, environmental degradation, and the reskilling and professional reintegration of people marginalized in the labor market. This research, based on semi-structured interviews in order to obtain exhaustive and sensitive data, involves an interview guide with few questions mobilized to let the respondents, leaders of the different structures, express themselves freely. The guide includes questions on activities, methods of sharing knowledge, and difficulties in understanding between stakeholders. The interviews, lasting 30 to 60 minutes, were recorded using a dictaphone and then transcribed in full. The results are as follows: 1. We see two iterative mentoring loops. A first loop can be considered a type of formal mentoring. It highlights the support organized (in the form of training) by social enterprises with the aim of developing the autonomy, know-how, and interpersonal skills of members. A second loop concerns informal mentoring. This is non-formalized support provided by members or with other members of the entourage. This informal mentoring is mainly based on the observation of good practices and learning by doing. 2. We notice an intersection between the two loops. If the first loop is not done, the second will not take place. The knowledge acquired in the first loop is used to feed the second. 3. We note a form of reluctance on the part of some members to share their knowledge for reasons of competition. Ultimately, we retain the notion of “social” mentoring as a hybridization of formal and informal mentoring while dimensioning the “social” perspective by emphasizing the reciprocal character, solidarity, confidence, and trust between the mentor and the mentee.

Keywords: social innovation, social mentoring, social and solidarity economy, informal mentoring

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1696 Limit State of Heterogeneous Smart Structures under Unknown Cyclic Loading

Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

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1695 Real-Time Implementation of Self-Tuning Fuzzy-PID Controller for First Order Plus Dead Time System Base on Microcontroller STM32

Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

Abstract:

First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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1694 Modeling of in 738 LC Alloy Mechanical Properties Based on Microstructural Evolution Simulations for Different Heat Treatment Conditions

Authors: M. Tarik Boyraz, M. Bilge Imer

Abstract:

Conventionally cast nickel-based super alloys, such as commercial alloy IN 738 LC, are widely used in manufacturing of industrial gas turbine blades. With carefully designed microstructure and the existence of alloying elements, the blades show improved mechanical properties at high operating temperatures and corrosive environment. The aim of this work is to model and estimate these mechanical properties of IN 738 LC alloy solely based on simulations for projected heat treatment conditions or service conditions. The microstructure (size, fraction and frequency of gamma prime- γ′ and carbide phases in gamma- γ matrix, and grain size) of IN 738 LC needs to be optimized to improve the high temperature mechanical properties by heat treatment process. This process can be performed at different soaking temperature, time and cooling rates. In this work, micro-structural evolution studies were performed experimentally at various heat treatment process conditions, and these findings were used as input for further simulation studies. The operation time, soaking temperature and cooling rate provided by experimental heat treatment procedures were used as micro-structural simulation input. The results of this simulation were compared with the size, fraction and frequency of γ′ and carbide phases, and grain size provided by SEM (EDS module and mapping), EPMA (WDS module) and optical microscope for before and after heat treatment. After iterative comparison of experimental findings and simulations, an offset was determined to fit the real time and theoretical findings. Thereby, it was possible to estimate the final micro-structure without any necessity to carry out the heat treatment experiment. The output of this microstructure simulation based on heat treatment was used as input to estimate yield stress and creep properties. Yield stress was calculated mainly as a function of precipitation, solid solution and grain boundary strengthening contributors in microstructure. Creep rate was calculated as a function of stress, temperature and microstructural factors such as dislocation density, precipitate size, inter-particle spacing of precipitates. The estimated yield stress values were compared with the corresponding experimental hardness and tensile test values. The ability to determine best heat treatment conditions that achieve the desired microstructural and mechanical properties were developed for IN 738 LC based completely on simulations.

Keywords: heat treatment, IN738LC, simulations, super-alloys

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1693 GIS-Based Topographical Network for Minimum “Exertion” Routing

Authors: Katherine Carl Payne, Moshe Dror

Abstract:

The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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1692 Finding Viable Pollution Routes in an Urban Network under a Predefined Cost

Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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1691 The Relationship between Environmental Factors and Purchasing Decisions in the Residential Market in Sweden

Authors: Agnieszka Zalejska-Jonsson

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The Swedish Green Building Council (SGBC) was established in 2009. Since then, over 1000 buildings have been certified, of which approximately 600 are newly produced and 340 are residential buildings. During that time, approximately 2000 apartment buildings have been built in Sweden. This means that over a five- year period 17% of residential buildings have been certified according to the environmental building scheme. The certification of the building is not a guarantee of environmental progress but it gives us an indication of the extent of the progress. The overarching aim of this study is to investigate the factors behind the relatively slow evolution of the green residential housing market in Sweden. The intention is to examine stated willingness to pay (WTP) for green and low energy apartments, and to explore which factors have a significant effect on stated WTP among apartment owners. A green building was defined as a building certified according to the environmental scheme and a low energy building as a building designed and constructed with high energy efficiency goals. Data for this study were collected through a survey conducted among occupants of comparable apartment buildings: two green and one conventional. The total number of received responses was 429: green A (N=160), response rate 42%; green B (N=138) response rate 35%, and conventional (N=131) response rate 43%. The study applied a quasi-experimental method. Survey responses regarding factors affecting purchase of apartment, stated WTP and environmental literacy have been analysed using descriptive statistics, the Mann–Whitney (rank sum) test and logistic models. Comments received from respondents have been used for further interpretation of results. Results indicate that environmental education has a significant effect on stated WTP. Occupants who declared higher WTP showed a higher level of environmental literacy and indicated that energy efficiency was one of the important factors that affected their decision to buy an apartment. Generally, the respondents were more likely to pay more for low energy buildings than for green buildings. This is to a great extent a consequence of rational customer behaviour and difficulty in apprehending the meaning of green building certification. The analysis shows that people living in green buildings indicate higher WTP for both green and low energy buildings, the difference being statistically significant. It is concluded that growth in the green housing market in Sweden might be achieved if policymakers and developers engage in active education in the environmental labelling system. The demand for green buildings is more likely to increase when the difference between green and conventional buildings is easily understood and information is not only delivered by the estate agent, but is part of an environmental education programme.

Keywords: consumer, environmental education, housing market, stated WTP, Sweden

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1690 Particle Swarm Optimisation of a Terminal Synergetic Controllers for a DC-DC Converter

Authors: H. Abderrezek, M. N. Harmas

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DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so-called terminal scheme to achieve finite time convergence. Lyapunov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.

Keywords: DC-DC converter, PSO, finite time, terminal, synergetic control

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1689 Efficient Positioning of Data Aggregation Point for Wireless Sensor Network

Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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1688 Applying a Noise Reduction Method to Reveal Chaos in the River Flow Time Series

Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

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1687 A Summary-Based Text Classification Model for Graph Attention Networks

Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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1686 Integration of an Innovative Complementary Approach Inspired by Clinical Hypnosis into Oncology Care: Nurses’ Perception of Comfort Talk

Authors: Danny Hjeij, Karine Bilodeau, Caroline Arbour

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Background: Chemotherapy infusions often lead to a cluster of co-occurring and difficult-to-treat symptoms (nausea, tingling, etc.), which may negatively impact the treatment experience at the outpatient clinic. Although several complementary approaches have shown beneficial effects for chemotherapy-induced symptom management, they are not easily implementable during chemotherapy infusion. In response to this limitation, comfort talk (CT), a simple, fast conversational method inspired by the language principles of clinical hypnosis, is known to optimize the management of symptoms related to antineoplastic treatments. However, the perception of nurses who have had to integrate this practice into their care has never been documented. Study design: A qualitative descriptive study with iterative content analysis was conducted among oncology nurses working in a chemotherapy outpatient clinic who had previous experience with CT. Semi-structured interviews were conducted by phone, using a pre-tested interview guide and a sociodemographic survey to document their perception of CT. The conceptual framework. Results: A total of six nurses (4 women, 2 men) took part in the interviews (N=6). The average age of participants was 49 years (36-61 years). Participants had an average of 24 years of experience (10-38 years) as a nurse, including 14.5 years in oncology (5-32 years). Data saturation (i.e., redundancy of words) was observed around the fifth interview. A sixth interview was conducted as confirmation. Six themes emerged: two addressing contextual and organizational obstacles at the chemotherapy outpatient clinic, and three addressing the added value of CT for oncology nursing care. Specific themes included: 1) the outpatient oncology clinic, a saturated care setting, 2) the keystones that support the integration of CT into care, 3) added value for patients, 4) a positive and rewarding experience for nurses, 5) collateral benefits, and 6) CT an approach to consider during the COVID-19 pandemic. Conclusion: For the first time, this study describes nurses' perception of the integration of CT into the care surrounding the administration of chemotherapy at the outpatient oncology clinic. In summary, contextual and organizational difficulties, as well as the lack of training, are among the main obstacles that could hinder the integration of CT in oncology. Still, the experience was reported mostly as positive. Indeed, nurses saw HC as an added value to patient care and meeting their need for holistic care. HC also appears to be beneficial for patients on several levels (for pain management in particular). Results will be used to inform future knowledge transfer activities related to CT in oncology nursing.

Keywords: cancer, chemotherapy, comfort talk, oncology nursing role

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1685 Radar on Bike: Coarse Classification based on Multi-Level Clustering for Cyclist Safety Enhancement

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

Abstract:

Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 68
1684 Joint Path and Push Planning among Moveable Obstacles

Authors: Victor Emeli, Akansel Cosgun

Abstract:

This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

Procedia PDF Downloads 157
1683 Path Planning for Collision Detection between two Polyhedra

Authors: M. Khouil, N. Saber, M. Mestari

Abstract:

This study aimed to propose, a different architecture of a Path Planning using the NECMOP. where several nonlinear objective functions must be optimized in a conflicting situation. The ability to detect and avoid collision is very important for mobile intelligent machines. However, many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons linear and threshold logic, which simplified the actual implementation of all the networks proposed. This article represents a comprehensive algorithm that determine through the AMAXNET network a measure (a mini-maximum point) in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: path planning, collision detection, convex polyhedron, neural network

Procedia PDF Downloads 429
1682 Proposed Terminal Device for End-to-End Secure SMS in Cellular Networks

Authors: Neetesh Saxena, Narendra S. Chaudhari

Abstract:

Nowadays, SMS is a very popular mobile service and even the poor, illiterate people and those living in rural areas use SMS service very efficiently. Although many mobile operators have already started 3G and 4G services, 2G services are still being used by the people in many countries. In 2G (GSM), only encryption provided is between the MS and the BTS, there is no end-to-end encryption available. Sometimes we all need to send some confidential message to other person containing bank account number, some password, financial details, etc. Normally, a message is sent in plain text only to the recipient and it is not an acceptable standard for transmitting such important and confidential information. Authors propose an end-to-end encryption approach by proposing a terminal for sending/receiving a secure message. An asymmetric key exchange algorithm is used in order to transmit secret shared key securely to the recipient. The proposed approach with terminal device provides authentication, confidentiality, integrity and non-repudiation.

Keywords: AES, DES, Diffie-Hellman, ECDH, A5, SMS

Procedia PDF Downloads 400
1681 An Online Priority-Configuration Algorithm for Obstacle Avoidance of the Unmanned Air Vehicles Swarm

Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

Abstract:

Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

Procedia PDF Downloads 203
1680 Secure Transfer of Medical Images Using Hybrid Encryption Authentication, Confidentiality, Integrity

Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

Abstract:

In this paper, we propose a new encryption system for security issues medical images. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity, and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every new session of encryption, that will be used to encrypt each frame of the medical image basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, medical images, encryption, decryption, key, correlation

Procedia PDF Downloads 531
1679 Stabilization of the Bernoulli-Euler Plate Equation: Numerical Analysis

Authors: Carla E. O. de Moraes, Gladson O. Antunes, Mauro A. Rincon

Abstract:

The aim of this paper is to study the internal stabilization of the Bernoulli-Euler equation numerically. For this, we consider a square plate subjected to a feedback/damping force distributed only in a subdomain. An algorithm for obtaining an approximate solution to this problem was proposed and implemented. The numerical method used was the Finite Difference Method. Numerical simulations were performed and showed the behavior of the solution, confirming the theoretical results that have already been proved in the literature. In addition, we studied the validation of the numerical scheme proposed, followed by an analysis of the numerical error; and we conducted a study on the decay of the energy associated.

Keywords: Bernoulli-Euler plate equation, numerical simulations, stability, energy decay, finite difference method

Procedia PDF Downloads 405
1678 Block Matching Based Stereo Correspondence for Depth Calculation

Authors: G. Balakrishnan

Abstract:

Stereo Correspondence plays a major role in estimation of distance of an object from the stereo camera pair for various applications. In this paper, a stereo correspondence algorithm based on block-matching technique is presented. Initially, an energy matrix is calculated for every disparity obtained using modified Sum of Absolute Difference (SAD). Higher energy matrix errors are removed by using threshold value in order to reduce the mismatch errors. A smoothening filter is applied to eliminate unreliable disparity estimate across the object boundaries. The purpose is to improve the reliability of calculation of disparity map. The experimental results obtained shows that the final depth map produce better results and can be used to all the applications using stereo cameras.

Keywords: stereo matching, filters, energy matrix, disparity

Procedia PDF Downloads 207