Search results for: global-local problem
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7185

Search results for: global-local problem

5145 Congestion Control in Mobile Network by Prioritizing Handoff Calls

Authors: O. A. Lawal, O. A Ojesanmi

Abstract:

The demand for wireless cellular services continues to increase while the radio resources remain limited. Thus, network operators have to continuously manage the scarce radio resources in order to have an improved quality of service for mobile users. This paper proposes how to handle the problem of congestion in the mobile network by prioritizing handoff call, using the guard channel allocation scheme. The research uses specific threshold value for the time of allocation of the channel in the algorithm. The scheme would be simulated by generating various data for different traffics in the network as it would be in the real life. The result would be used to determine the probability of handoff call dropping and the probability of the new call blocking as a way of measuring the network performance.

Keywords: call block, channel, handoff, mobile cellular network

Procedia PDF Downloads 396
5144 Ending the Multibillionaire: A Solution to Poverty and Violations of the Right to Health

Authors: Andreanna Kalasountas

Abstract:

A rampant health crisis is facing America. That health crisis is poverty. Millions of Americans live without knowing when they will eat or where they will sleep. Meanwhile, there are over 600 multi-billionaires in the United States. “In April 2021, U.S. billionaires had nearly twice as much combined wealth than the bottom half of Americans -- $4.56 trillion vs. $2.62 trillion.” It's disturbingly ironic that we live in a country where there are people with more money than they know what to do with (or could spend in a lifetime) while simultaneously, people are losing their life because they do not have enough money to survive. Accordingly, this paper argues for the end of the multi-billionaire; that wealth be capped, captured, and redistributed to the poorest among us. To accomplish this goal, this paper begins by identifying the problem, advocating for a new measurement of poverty; and concludes with a both legal and tax policy solutions and what implementation of those solutions would look like.

Keywords: health and human rights, law and policy, poverty, wealth gap

Procedia PDF Downloads 103
5143 The Consequences of Complaint Offenses against Copyright Protection

Authors: Chryssantus Kastowo, Theresia Anita Christiani, Anny Retnowati

Abstract:

Copyright infringement as a form of infringement does not always mean causing harm to the creator. This can be proven with so many copyright violations in society and there is no significant law enforcement effort when compared with the violations that occurred. Copyright law as a form of appreciation from the state to the creator becomes counter productive if there is omission of violations. The problem raised in this article is how is the model of copyright regulation in accordance with the purpose of the law of copyright protection. This article is based on normative legal research focusing on secondary data. The analysis used is a conceptual approach. The analysis shows that the regulation of copyright emphasizes as a subjective right that is wholly within the author's power. This perspective will affect the claim of rights by the creator or allow violations. The creator is obliged to maintain the overall performance of copyright protection, especially in the event of a violation.

Keywords: copyright, enforcement, law, violation

Procedia PDF Downloads 136
5142 Deepfake Detection for Compressed Media

Authors: Sushil Kumar Gupta, Atharva Joshi, Ayush Sonawale, Sachin Naik, Rajshree Khande

Abstract:

The usage of artificially created videos and audio by deep learning is a major problem of the current media landscape, as it pursues the goal of misinformation and distrust. In conclusion, the objective of this work targets generating a reliable deepfake detection model using deep learning that will help detect forged videos accurately. In this work, CelebDF v1, one of the largest deepfake benchmark datasets in the literature, is adopted to train and test the proposed models. The data includes authentic and synthetic videos of high quality, therefore allowing an assessment of the model’s performance against realistic distortions.

Keywords: deepfake detection, CelebDF v1, convolutional neural network (CNN), xception model, data augmentation, media manipulation

Procedia PDF Downloads 13
5141 Research on the Optimization of Satellite Mission Scheduling

Authors: Pin-Ling Yin, Dung-Ying Lin

Abstract:

Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

Procedia PDF Downloads 31
5140 Synthesis and Characterizations of Lead-free BaO-Doped TeZnCaB Glass Systems for Radiation Shielding Applications

Authors: Rezaul K. Sk., Mohammad Ashiq, Avinash K. Srivastava

Abstract:

The use of radiation shielding technology ranging from EMI to high energy gamma rays in various areas such as devices, medical science, defense, nuclear power plants, medical diagnostics etc. is increasing all over the world. However, exposure to different radiations such as X-ray, gamma ray, neutrons and EMI above the permissible limits is harmful to living beings, the environment and sensitive laboratory equipment. In order to solve this problem, there is a need to develop effective radiation shielding materials. Conventionally, lead and lead-based materials are used in making shielding materials, as lead is cheap, dense and provides very effective shielding to radiation. However, the problem associated with the use of lead is its toxic nature and carcinogenic. So, to overcome these drawbacks, there is a great need for lead-free radiation shielding materials and that should also be economically sustainable. Therefore, it is necessary to look for the synthesis of radiation-shielding glass by using other heavy metal oxides (HMO) instead of lead. The lead-free BaO-doped TeZnCaB glass systems have been synthesized by the traditional melt-quenching method. X-ray diffraction analysis confirmed the glassy nature of the synthesized samples. The densities of the developed glass samples were increased by doping the BaO concentration, ranging from 4.292 to 4.725 g/cm3. The vibrational and bending modes of the BaO-doped glass samples were analyzed by Raman spectroscopy, and FTIR (Fourier-transform infrared spectroscopy) was performed to study the functional group present in the samples. UV-visible characterization revealed the significance of optical parameters such as Urbach’s energy, refractive index and optical energy band gap. The indirect and direct energy band gaps were decreased with the BaO concentration whereas the refractive index was increased. X-ray attenuation measurements were performed to determine the radiation shielding parameters such as linear attenuation coefficient (LAC), mass attenuation coefficient (MAC), half value layer (HVL), tenth value layer (TVL), mean free path (MFP), attenuation factor (Att%) and lead equivalent thickness of the lead-free BaO-doped TeZnCaB glass system. It was observed that the radiation shielding characteristics were enhanced with the addition of BaO content in the TeZnCaB glass samples. The glass samples with higher contents of BaO have the best attenuation performance. So, it could be concluded that the addition of BaO into TeZnCaB glass samples is a significant technique to improve the radiation shielding performance of the glass samples. The best lead equivalent thickness was 2.626 mm, and these glasses could be good materials for medical diagnostics applications.

Keywords: heavy metal oxides, lead-free, melt-quenching method, x-ray attenuation

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5139 Cosmic Dust as Dark Matter

Authors: Thomas Prevenslik

Abstract:

Weakly Interacting Massive Particle (WIMP) experiments suggesting dark matter does not exist are consistent with the argument that the long-standing galaxy rotation problem may be resolved without the need for dark matter if the redshift measurements giving the higher than expected galaxy velocities are corrected for the redshift in cosmic dust. Because of the ubiquity of cosmic dust, all velocity measurements in astronomy based on redshift are most likely overstated, e.g., an accelerating Universe expansion need not exist if data showing supernovae brighter than expected based on the redshift/distance relation is corrected for the redshift in dust. Extensions of redshift corrections for cosmic dust to other historical astronomical observations are briefly discussed.

Keywords: alternative theories, cosmic dust redshift, doppler effect, quantum mechanics, quantum electrodynamics

Procedia PDF Downloads 297
5138 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

Abstract:

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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5137 Exponential Spline Solution for Singularly Perturbed Boundary Value Problems with an Uncertain-But-Bounded Parameter

Authors: Waheed Zahra, Mohamed El-Beltagy, Ashraf El Mhlawy, Reda Elkhadrawy

Abstract:

In this paper, we consider singular perturbation reaction-diffusion boundary value problems, which contain a small uncertain perturbation parameter. To solve these problems, we propose a numerical method which is based on an exponential spline and Shishkin mesh discretization. While interval analysis principle is used to deal with the uncertain parameter, sensitivity analysis has been conducted using different methods. Numerical results are provided to show the applicability and efficiency of our method, which is ε-uniform convergence of almost second order.

Keywords: singular perturbation problem, shishkin mesh, two small parameters, exponential spline, interval analysis, sensitivity analysis

Procedia PDF Downloads 277
5136 Some Basic Problems for the Elastic Material with Voids in the Case of Approximation N=1 of Vekua's Theory

Authors: Bakur Gulua

Abstract:

In this work, we consider some boundary value problems for the plate. The plate is the elastic material with voids. The state of plate equilibrium is described by the system of differential equations that is derived from three-dimensional equations of equilibrium of an elastic material with voids (Cowin-Nunziato model) by Vekua's reduction method. Its general solution is represented by means of analytic functions of a complex variable and solutions of Helmholtz equations. The problem is solved analytically by the method of the theory of functions of a complex variable.

Keywords: the elastic material with voids, boundary value problems, Vekua's reduction method, a complex variable

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5135 Biodegradability and Thermal Properties of Polycaprolactone/Starch Nanocomposite as a Biopolymer

Authors: Emad A. Jaffar Al-Mulla

Abstract:

In this study, a biopolymer-based nanocomposite was successfully prepared through melt blending technique. Two biodegradable polymers, polycaprolactone and starch, environmental friendly and obtained from renewable, easily available raw materials, have been chosen. Fatty hydrazide, synthesized from palm oil, has been used as a surfactant to modify montmorillonite (natural clay) for preparation of polycaprolactone/starch nanocomposite. X-ray diffraction and transmission electron microscopy were used to characterize nanocomposite formation. Compatibility of the blend was improved by adding 3% weight modified clay. Higher biodegradability and thermal stability of nanocomopeite were also observed compared to those of the polycaprolactone/starch blend. This product will solve the problem of plastic waste, especially disposable packaging, and reduce the dependence on petroleum-based polymers and surfactants.

Keywords: polycaprolactone, starch, biodegradable, nanocomposite

Procedia PDF Downloads 359
5134 Passive Solar Distiller with Low Cost of Implementation, Operation and Maintenance

Authors: Valentina Alessandra Carvalho do Vale, Elmo Thiago Lins Cöuras Ford, Rudson de Sousa Lima

Abstract:

Around the planet Earth, access to clean water is a problem whose importance has increased due to population growth and its misuse. Thus, projects that seek to transform water sources improper (salty and brackish) in drinking water sources are current issues. However, this transformation generally requires a high cost of implementation, operation and maintenance. In this context, the aim of this work is the development of a passive solar distiller for brackish water, made from recycled and durable materials such as aluminum, cement, glass and PVC basins. The results reveal factors that influence the performance and viability of the expansion project.

Keywords: solar distiller, passive distiller, distiller with pyramidal roof, ecologically correct

Procedia PDF Downloads 417
5133 Towards a Common Architecture for Cloud Computing Interoperability

Authors: Sana Kouchi, Hassina Nacer, Kadda Beghdad-bey

Abstract:

Cloud computing is growing very fast in the market and has become one of the most controversial discussed developments in recent years. Cloud computing providers become very numerous in these areas and each of them prefers its own cloud computing infrastructure, due to the incompatibility of standards and cloud access formats, which prevents them from accepting to support cloud computing applications in a standardized manner, this heterogeneity creates the problem of interoperability between clouds, and considering that cloud customers are probably in search of an interoperable cloud computing, where they will have total control over their applications and simply migrate their services as needed, without additional development investment. A cloud federation strategy should be considered. In this article, we propose a common architecture for the cloud that is based on existing architectures and also the use of best practices from ICT frameworks, such as IBM, ITIL, NIST, etc., to address the interoperability of architectures issues in a multi-cloud system.

Keywords: cloud computing, reference architecture, interoperability, standard

Procedia PDF Downloads 174
5132 Estimation of Population Mean under Random Non-Response in Two-Phase Successive Sampling

Authors: M. Khalid, G. N. Singh

Abstract:

In this paper, we have considered the problem of estimation for population mean, on current (second) occasion in the presence of random non response in two-occasion successive sampling under two phase set-up. Modified exponential type estimators have been proposed, and their properties are studied under the assumptions that numbers of sampling units follow a distribution due to random non response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.

Keywords: successive sampling, random non-response, auxiliary variable, bias, mean square error

Procedia PDF Downloads 522
5131 An Evolutionary Approach for QAOA for Max-Cut

Authors: Francesca Schiavello

Abstract:

This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

Procedia PDF Downloads 60
5130 The Review of Coiled Tubing Intelligent Sidetracking Steering Technology

Authors: Zhao Xueran, Yang Dong

Abstract:

In order to improve the problem that old wells in oilfields are shut down due to low oil recovery, sidetracking has become one of the main technical means to restore the vitality of old wells. A variety of sidetracking technologies have been researched and formed internationally. Among them, coiled tubing sidetracking horizontal wells have significant advantages over conventional sidetracking methods: underbalanced pressure operations; reducing the number of trips of tubing, while drilling and production, saving construction costs, less ground equipment and less floor space, orienter guidance to reduce drilling friction, etc. This paper mainly introduces the steering technology in coiled tubing intelligent sidetracking at home and abroad, including the orienter and the rotary steerable system.

Keywords: sidetracking, coiled tubing, orienter, rotary steering system

Procedia PDF Downloads 170
5129 Intelligent System for Diagnosis Heart Attack Using Neural Network

Authors: Oluwaponmile David Alao

Abstract:

Misdiagnosis has been the major problem in health sector. Heart attack has been one of diseases that have high level of misdiagnosis recorded on the part of physicians. In this paper, an intelligent system has been developed for diagnosis of heart attack in the health sector. Dataset of heart attack obtained from UCI repository has been used. This dataset is made up of thirteen attributes which are very vital in diagnosis of heart disease. The system is developed on the multilayer perceptron trained with back propagation neural network then simulated with feed forward neural network and a recognition rate of 87% was obtained which is a good result for diagnosis of heart attack in medical field.

Keywords: heart attack, artificial neural network, diagnosis, intelligent system

Procedia PDF Downloads 656
5128 Application of the Discrete Rationalized Haar Transform to Distributed Parameter System

Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

Procedia PDF Downloads 509
5127 Protection of Television Programme Formats in Comparative Law

Authors: Mustafa Arikan, Ibrahim Ercan

Abstract:

In this paper, protection of program formats was investigated in terms of program formats. Protection of program formats was studied in the French Law in the sense of competition law and CPI. Since the English Judicial system exhibits differences from the legal system of Continental Europe, its investigation bears a special significance. The subject was also handled in German Law at length. Indeed, German Law was investigated in detail within the overall framework of the study. Here, the court decisions in the German Law and the views in the doctrine were expressed in general. There are many court decisions in the American legal system concerning the subject. These decisions also present alternatives in terms of a solution to the problem.

Keywords: comparative law, protection of television programme formats, intellectual property, american legal system

Procedia PDF Downloads 331
5126 Schrödinger Equation with Position-Dependent Mass: Staggered Mass Distributions

Authors: J. J. Peña, J. Morales, J. García-Ravelo, L. Arcos-Díaz

Abstract:

The Point canonical transformation method is applied for solving the Schrödinger equation with position-dependent mass. This class of problem has been solved for continuous mass distributions. In this work, a staggered mass distribution for the case of a free particle in an infinite square well potential has been proposed. The continuity conditions as well as normalization for the wave function are also considered. The proposal can be used for dealing with other kind of staggered mass distributions in the Schrödinger equation with different quantum potentials.

Keywords: free particle, point canonical transformation method, position-dependent mass, staggered mass distribution

Procedia PDF Downloads 404
5125 Basket Option Pricing under Jump Diffusion Models

Authors: Ali Safdari-Vaighani

Abstract:

Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.

Keywords: basket option, jump diffusion, ‎radial basis function, RBF-PUM

Procedia PDF Downloads 354
5124 A Contribution to Blockchain Privacy

Authors: Malika Yaici, Feriel Lalaoui, Lydia Belhoul

Abstract:

As a new distributed point-to-point (P2P) technology, blockchain has become a very broad field of research, addressing various challenges, including privacy preserving, as is the case in all other technologies. In this work, a study of the existing solutions to the problems related to private life in general and in blockchains in particular is performed. User anonymity and transaction confidentiality are the two main challenges to the protection of privacy in blockchains. Mixing mechanisms and cryptographic solutions respond to this problem but remain subject to attacks and suffer from shortcomings. Taking into account these imperfections and the synthesis of our study, we present a mixing model without trusted third parties, based on group signatures, allowing reinforcing the anonymity of the users, the confidentiality of the transactions, with minimal turnaround time and without mixing costs.

Keywords: anonymity, blockchain, mixing coins, privacy

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5123 Nonstationarity Modeling of Economic and Financial Time Series

Authors: C. Slim

Abstract:

Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

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5122 Sustainable Tourism from a Multicriteria Analysis Perspective

Authors: Olga Blasco-Blasco, Vicente Liern

Abstract:

The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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5121 Cooperative Communication of Energy Harvesting Synchronized-OOK IR-UWB Based Tags

Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

Abstract:

Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

Procedia PDF Downloads 493
5120 Evidence of Social Media Addiction and Problematic Internet Use Among High School and University Students in Cyprus

Authors: Costas Christodoulides

Abstract:

Excessive use of social networking sites (SNS) and the Internet by high school pupils and university students, can cause consequences similar to those observed in substance or gambling related addictions, negatively influence individual well-being notwithstanding self-assessments that people make about their life and experiences. The present study examined, for the first time in Cyprus, the levels of problematic use of the Social Media and the Internet among Cypriot pupils and students aiming at contributing to the discussion about the need for a more conclusive policy framework in the island. The Bergen Social Media Addiction Scale (BSMAS) and the Generalized Problematic Internet Use Scale 2 (GPIUS-2) were adapted to a Cypriot version and along with a sociodemographic questionnaire were introduced to a sample of 1059 young persons in order to respectively assess the addiction risk for Social Media Use and the risk of Problematic Internet Use. The sample consisted of 59% females, aged 15 to 35 (M=18.9 years, SD=3.20), 465 of them were high school students and 594 university students. Of 1059 respondents from 4 high-schools and 5 Universities (HEI) in Cyprus, 8.3% of the sample had BSMAS scores suggestive of addiction. Approximately a quarter of the sample (24%), demonstrated GPIUS-2 scores suggestive of high risk for problematic internet use. It is notable that differences seem to exist across gender with the score of the female population (11.1%) reaching levels of addiction to social media more than twice the level of addiction of the male population (4.3%). Also, the female population of high school students seems to be at the most vulnerable position for problematic internet use (28%). The 26% of the sample often or very often used some SNSs to forget of personal problems. The results of this study show that half of those surveyed used the Internet to feel better when they were upset or to escape the isolation they felt. Among the sample population, the study reports that 60% of the pupils and female university students are in agreement with the relevant statements. Conclusively, this study suggests that SNSs addiction levels among pupils and students in Cyprus ought to be an important public health concern. The same if not more alarming is the identified by the study prevalence of problematic Internet use among the same population. These results confirm international trends reported by scholarly research while also suggest that particular categories such as high school pupils and young females may be more exposed to problem SNSs and Internet use. Preventive strategies need first to acknowledge the problem in order to then formulate an effective strategy for prevention and intervention. For relevant authorities it is of primary importance to “exploit” the fact that high schools and universities can be seen as small communities and units potentially available for forging alliances for healthy Social Media and Internet use.

Keywords: problematic internet use, social media addiction, social networking sites, well-being

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5119 Autism and Mental Health - How Different Individuals Are Impacted

Authors: Kerryn Burgoyne

Abstract:

Statement of the Problem: Women who suffer mental health issues, because of Autism Spectrum Disorder has a significant impact on their lives, especially if they’ve been bullied or discriminated against for the majority of their lives. Autism can impact one's mental health in many ways (child like behaviour), social anxieties or overload. The impact of mental health can also be experienced when the person does not have a good quality of life for themselves (eg employment, independent living skills), or have support from family/friends/society). Mental health issues were also suffered during COVID 19 Lockdown here in Melbourne Australia. It was stated by the Government at the time that people weren’t allowed to travel more than 5 km outside of their residential areas to prevent the spread of COVID to others. Medical appointments were an exception. Kerryn/KTalk will be doing a paper on this topic for the conference if accepted by the committee.

Keywords: Autism, mental health, living & learning, KTalk

Procedia PDF Downloads 47
5118 Correlation Matrix for Automatic Identification of Meal-Taking Activity

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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5117 Graphene/ZnO/Polymer Nanocomposite Thin Film for Separation of Oil-Water Mixture

Authors: Suboohi Shervani, Jingjing Ling, Jiabin Liu, Tahir Husain

Abstract:

Offshore oil-spill has become the most emerging problem in the world. In the current paper, a graphene/ZnO/polymer nanocomposite thin film is coated on stainless steel mesh via layer by layer deposition method. The structural characterization of materials is determined by Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). The total petroleum hydrocarbons (TPHs) and separation efficiency have been measured via gas chromatography – flame ionization detector (GC-FID). TPHs are reduced to 2 ppm and separation efficiency of the nanocomposite coated mesh is reached ≥ 99% for the final sample. The nanocomposite coated mesh acts as a promising candidate for the separation of oil- water mixture.

Keywords: oil spill, graphene, oil-water separation, nanocomposite

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5116 Tumor Detection Using Convolutional Neural Networks (CNN) Based Neural Network

Authors: Vinai K. Singh

Abstract:

In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

Procedia PDF Downloads 137