Search results for: hanging veneer cladding systems

Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: M. Ben Slimene, M.-S. Ouali

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Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

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Authors: Rodrigo Costa, Thomas Mazzuchi, Shahram Sarkani

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This study analyzes the evolution of Bitcoin Improvement Proposals (BIPs), the self-governing mechanism that enables updates to the Bitcoin protocol. By modeling BIP submission frequencies with a Negative Binomial distribution and detecting change points with the Pelt Rupture model, we identify three distinct intervals of proposal activity, suggesting shifts in development priorities over time. Long-term growth patterns, captured by Gompertz and Weibull models, indicate an S-shaped trend in cumulative BIP counts, pointing toward a maturation phase in Bitcoin’s protocol. Our findings suggest that Bitcoin may be entering a stable stage, with fewer fundamental changes and more incremental enhancements. This trend highlights the need for further research into BIP content and more studies into its dynamics to better understand decentralized protocol governance and maturation.

Keywords: bitcoin improvement proposals, innovation management, change point detection, systems modeling, simulation

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Authors: A. Ortuzar, I. Escondrillas, F. Mijangos

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There is a need for new systems that can be attached to drinking water treatment plants and have the required treatment capacity as well as the selectivity regarding components derived from anthropogenic activities. In a context of high volumes of water and low concentration of contaminants, adsorption/interchange processes are appealing since they meet the required features. Iron oxides such as siderite and molysite, which are respectively based on FeCO₃ and FeCl₃, can be found in nature. In this work, their observed performance, raw or roasted at different temperatures, as adsorbents of some inorganic anions is discussed. Roasted 1:1 FeCO₃: FeCl₃ mixture was very selective for arsenic and allowed a 100% removal of As from a 10 mg L^-1 As solution. Besides, the 1:1 FeCO₃ and FeCl₃ mixture roasted at 500 ºC showed good selectivity for, in order of preference, arsenate, bromate, phosphate, fluoride and nitrate anions with distribution coefficients of, respectively, 4200, 2800, 2500 0.4 and 0.03 L g^-1.

Keywords: drinking water, natural adsorbent materials, removal, selectivity

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Authors: Giada Feletti, Daniela Tedesco, Paolo Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning the indicators currently used for the performance measurement of EMS systems. From this literature analysis, it emerged that current studies focus on two distinct perspectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). The perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal focuses on the entire healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid to the dependency of decisions that in current EMS management models tend to be neglected or underestimated. In particular, the integration of the two processes enables the evaluation of the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in the extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating the ones firstly not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draws us to exclude additional indicators due to the unavailability of data required for their computation. The final dashboard, which was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness of EDs accessibility in real-time. By associating each KPI to the EMS phase it refers to, it was also possible to design a well-balanced dashboard covering both efficiency and effective performance of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient’s care are covered by traditional KPIs compared to the subsequent phases taking place in the hospital ED. This could be taken into consideration for the potential future development of the dashboard. Moreover, the research could proceed by building a multi-layer dashboard composed of the first level with a minimal set of KPIs to measure the basic performance of the EMS system at an aggregate level and further levels with KPIs that can bring additional and more detailed information.

Keywords: dashboard, decision support, emergency medical services, key performance indicators

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: P. Ghann, J. Shiguang, C. Zhou

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Access control is one of the most challenging issues facing information security. Access control is defined as, the ability to permit or deny access to a particular computational resource or digital information by an unauthorized user or subject. The concept of usage control (UCON) has been introduced as a unified approach to capture a number of extensions for access control models and systems. In UCON, an access decision is determined by three factors: Authorizations, obligations and conditions. Attribute mutability and decision continuity are two distinct characteristics introduced by UCON for the first time. An observation of UCON components indicates that, the components are predefined and static. In this paper, we propose a new and flexible model of usage control for the creation and elimination of some of these components; for example new objects, subjects, attributes and integrate these with the original UCON model. We also propose a model for concurrent usage scenarios in UCON.

Keywords: access control, concurrency, digital container, usage control

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Authors: Cheng-En Tsai, Chung-Chun Hsiao, Fu-Yuan Chang, Liang-Lun Lan, Jia-Ying Tu

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New design of three dimensional (3D) flywheel system based on gimbal and gyro mechanics is proposed. The 3D flywheel device utilizes the rotational motion of three spherical shells and the conservation of angular momentum to achieve planar locomotion. Actuators mounted to the ring-shape frames are installed within the system to drive the spherical shells to rotate, for the purpose of steering and stabilization. Similar to the design of 2D flywheel system, it is expected that the spherical shells may function like a “flyball” to store and supply mechanical energy; additionally, in comparison with typical single-wheel and spherical robots, the 3D flywheel can be used for developing omnidirectional robotic systems with better mobility. The Lagrangian method is applied to derive the equation of motion of the 3D flywheel system, and simulation studies are presented to verify the proposed design.

Keywords: Gimbal, spherical robot, gyroscope, Lagrangian formulation, flyball

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Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

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UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and non military works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (sound navigation and ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: UAV, Surveillance, RF signals, fishing, sonar, GPS, video stream, school of fish

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Authors: Nadaniela Egidi, Pierluigi Maponi

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The approximate solution of a time-harmonic electromagnetic scattering problem for inhomogeneous media is required in several application contexts, and its two-dimensional formulation is a Fredholm integral equation of the second kind. This integral equation provides a formulation for the direct scattering problem, but it has to be solved several times also in the numerical solution of the corresponding inverse scattering problem. The discretization of this Fredholm equation produces large and dense linear systems that are usually solved by iterative methods. In order to improve the efficiency of these iterative methods, we use the Symmetric SOR preconditioning, and we propose an algorithm for the evaluation of the associated relaxation parameter. We show the efficiency of the proposed algorithm by several numerical experiments, where we use two Krylov subspace methods, i.e., Bi-CGSTAB and GMRES.

Keywords: Fredholm integral equation, iterative method, preconditioning, scattering problem

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Authors: Riku Hayashida, Tomoaki Hashimoto

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This paper provides a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. Underwater robots are expected to be used for various work assignments. The large variety of applications of underwater robots motivates researchers to develop control systems and technologies for underwater robots. Several control methods have been proposed so far for the stabilization of nominal system model of underwater robots with no parameter uncertainty. Parameter uncertainties are considered to be obstacles in implementation of the such nominal control methods for underwater robots. The objective of this study is to establish a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: robust control, stabilization method, underwater robot, parameter uncertainty

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Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Abdul Amir Hazbavi

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The present study is an attempt to provide a relatively comprehensive preview of the Iranian English translators’ perception on Machine Translation. Furthermore, the study tries to shed light on the status of implementation of Machine Translation among the Iranian English Translators. To reach the aforementioned objectives, the Localization Industry Standards Association’s questioner for measuring perceptions with regard to the adoption of a technology innovation was adapted and used to investigate three parameter among the participants of the study, namely familiarity with Machine Translation, general perception on Machine Translation and implementation of Machine Translation systems in translation tasks. The participants of the study were 224 last-year undergraduate Iranian students of English translation at 10 universities across the country. The study revealed a very low level of adoption and a very high level of willingness to get familiar with and learn about Machine Translation, as well as a positive perception of and attitude toward Machine Translation by the Iranian English translators.

Keywords: translation technology, machine translation, perception, implementation

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Hassan Mohammad Alkomy, Hesham Elkaranshawy, Ahmed Ibrahim Ashour, Khaled Tawfik Mohamed

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For a rigid body sliding on a rough surface, a range of uncertainty or non-uniqueness of solution could be found, which is termed: Painlevé paradox. Painlevé paradox is the reason of a wide range of bouncing motion, observed during sliding of robotic manipulators on rough surfaces. In this research work, the existence of the paradox zone during the sliding motion of a two-link (P-R) robotic manipulator with a unilateral constraint is investigated. Parametric study is performed to investigate the effect of friction, link-length ratio, total height and link-mass ratio on the paradox zone.

Keywords: dynamical system, friction, multibody system, painlevé paradox, robotic systems, sliding robots, unilateral constraint

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Authors: Reza Hadjiaghaie Vafaie, Aysan Madanpasandi, Behrooz Zare Desari, Seyedmohammad Mousavi

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High lamination in microchannel is one of the main challenges in on-chip components like micro total analyzer systems and lab-on-a-chips. Electro-osmotic force is highly effective in chip-scale. This research proposes a microfluidic-based micropump for low ionic strength solutions. Narrow microchannels are designed to generate an efficient electroosmotic flow near the walls. Microelectrodes are embedded in the lateral sides and actuated by low electric potential to generate pumping effect inside the channel. Based on the simulation study, the fluid velocity increases by increasing the electric potential amplitude. We achieve a net flow velocity of 100 µm/s, by applying +/- 2 V to the electrode structures. Our proposed low voltage design is of interest in conventional lab-on-a-chip applications.

Keywords: integration, electrokinetic, on-chip, fluid pumping, microfluidic

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Authors: Charawee Butbumrung

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This research aim to study the financial service of the Thailand financial Institution, second is to identify "best practices" offered by four financial institutions, namely, Kasikornthai Bank, Bangkok Bank, Siam Commercial Bank, and Thanachart Bank. In-depth interviews with managers of financial institution and borrowers reveal best practices from each financial institution. Close monitoring of and a close relationship with borrowers appear to be important for early detection of any problem. Another aspect that may be important is building up loyalty and developing reliability among members. A close and informal relationship with borrowers may also help in monitoring and early detection of problems that may arise in non-repayment of loans. Other factors that may be considered important to the success of a financial service scheme are cooperation and coordination among various agencies that provide additional support to borrowers. Indirectly, these support systems contribute to the success of a SME in Thailand.

Keywords: best practices, financial service, financial institution, SME in Thailand

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Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

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In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: automotive gearbox, mathematical morphology, wavelet, bispectrum

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Authors: Sowmiyaa V. S., Tiruvengala Padma, Dhanasekaran B.

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Due to urbanization, traffic congestion, air pollution and fuel consumption underground metros are constructed in urban cities nowadays. These metros reduce the commutation time and makes the daily transportation in urban cities hassle free. To construct the underground metros deep excavations are to be carried out. These excavations should be supported by an appropriate earth retaining structures to provide stability and to prevent deformation failures. The failure of deep excavations is catastrophic and hence appropriate caution need to be carried out during design and construction stages. This paper covers the construction aspects, equipment, quality control, design aspects of one of the earth retaining systems the Diaphragm Walls.

Keywords: underground metros, diaphragm wall, quality control of diaphragm wall, design aspects of diaphragm wall

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Iyad Muslih, Azzah Alkhalailah, Ali Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: solar energy, PV system, soiling, MENA

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

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Authors: Boukhris Lahouari, Bouchetara Mostefa

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The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. This will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: Carlos Roberto Valêncio, Fábio Renato de Almeida, Thatiane Kawabata, Leandro Alves Neves, Julio Cesar Momente, Mario Luiz Tronco, Angelo Cesar Colombini

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By running transactions under the Snapshot isolation we can achieve a good level of concurrency, specially in databases with high-intensive read workloads. However, Snapshot is not immune to all the problems that arise from competing transactions and therefore no serialization warranty exists. We propose in this paper a technique to obtain data consistency with Snapshot by using some special triggers that we named Daemon Triggers. Besides keeping the benefits of the Snapshot isolation, the technique is specially useful for those database systems that do not have an isolation level that ensures serializability, like Firebird and Oracle. We describe all the anomalies that might arise when using the Snapshot isolation and show how to preclude them with Daemon Triggers. Based on the methodology presented here, it is also proposed the creation of a new isolation level: Daemon Snapshot.

Keywords: data consistency, serialization, snapshot, isolation

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Authors: E. Omanya, E. Mueni, G. Makau, M. Kariuki

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HIV infection is the strongest risk factor for a person to develop TB. Isoniazid preventive therapy (IPT) for People Living with HIV (PLWHIV) not only reduces the individual patients’ risk of developing active TB but mitigates cross infection. In Kenya, IPT for six months was recommended through the National TB, Leprosy and Lung Disease Program to treat latent TB. In spite of this recommendation by the national government, uptake of IPT among PLHIV remained low in Kenya by the end of 2015. The USAID/Kenya and East Africa Afya Jijini project, which supports 42 TBHIV health facilities in Nairobi County, began addressing low uptake of IPT through Quality Improvement (QI) teams set up at the facility level. Quality is characterized by WHO as one of the four main connectors between health systems building blocks and health systems outputs. Afya Jijini implements the Kenya Quality Model for Health, which involves QI teams being formed at the county, sub-county and facility levels. The teams review facility performance to identify gaps in service delivery and use QI tools to monitor and improve performance. Afya Jijini supported the formation of these teams in 42 facilities and built the teams’ capacity to review data and use QI principles to identify and address performance gaps. When the QI teams began working on improving IPT uptake among PLHIV, uptake was at 31.8%. The teams first conducted a root cause analysis using cause and effect diagrams, which help the teams to brainstorm on and to identify barriers to IPT uptake among PLHIV at the facility level. This is a participatory process where program staff provides technical support to the QI teams in problem identification and problem-solving. The gaps identified were inadequate knowledge and skills on the use of IPT among health care workers, lack of awareness of IPT by patients, inadequate monitoring and evaluation tools, and poor quantification and forecasting of IPT commodities. In response, Afya Jijini trained over 300 health care workers on the administration of IPT, supported patient education, supported quantification and forecasting of IPT commodities, and provided IPT data collection tools to help facilities monitor their performance. The facility QI teams conducted monthly meetings to monitor progress on implementation of IPT and took corrective action when necessary. IPT uptake improved from 31.8% to 61.2% during the second year of the Afya Jijini project and improved to 80.1% during the third year of the project’s support. Use of QI teams and root cause analysis to identify and address service delivery gaps, in addition to targeted program interventions and continual performance reviews, can be successful in increasing TB related service delivery uptake at health facilities.

Keywords: isoniazid, quality, health care workers, people leaving with HIV

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Authors: Muna Tabuni

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The paper contains an investigation of the notion of Q algebras. A brief introduction to quantum mechanics is given, in that systems the state defined by a vector in a complex vector space H which have Hermitian inner product property. H may be finite or infinite-dimensional. In quantum mechanics, operators must be hermitian. These facts are saved by Lie algebra operators but not by those of quantum algebras. A Hilbert space H consists of a set of vectors and a set of scalars. Lie group is a differentiable topological space with group laws given by differentiable maps. A Lie algebra has been introduced. Q-algebra has been defined. A brief introduction to BCI-algebra is given. A BCI sub algebra is introduced. A brief introduction to BCK=BCH-algebra is given. Every BCI-algebra is a BCH-algebra. Homomorphism maps meanings are introduced. Homomorphism maps between two BCK algebras are defined. The mathematical formulations of quantum mechanics can be expressed using the theory of unitary group representations. A generalization of Q algebras has been introduced, and their properties have been considered. The Q- quantum algebra has been studied, and various examples have been given.

Keywords: Q-algebras, BCI, BCK, BCH-algebra, quantum mechanics

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Authors: Salwa Enneifer

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The research is intended to investigate Tunisian students’ own perception of the difficulties they encounter in the writing task. To achieve this objective, a questionnaire was administered to students enrolled in the ‘Faculty of Letters Arts and Humanities’ in Kairouan, in Tunisia. Students were classified into three groups: first-, second-, and third-year students. The researcher used 120 questionnaires filled in by the students as data for this study; moreover, 30 students participated in a semi-structured interview to complete the data. The questionnaire results revealed that Tunisian EFL students faced spelling and grammar difficulties. ANOVA also revealed that the first-year students did not recognise that Arabic and English greatly differ in their respective punctuation systems. The second-year class, however, was fully aware of this difference. Additionally, the interview shed light on other aspects or different difficulties experienced by students in writing: a cruel ‘lack of vocabulary’, Arabic language interference, the organisation of the essay and especially the academic essay, and difficulty with writing an argumentative essay.

Keywords: difficulties, writing, Tunisian, EFL students

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Eiman Nour

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The rising interest in harvesting power is because of the capabilities application of expanding self-powered systems based on nanostructures. Using renewable and self-powered sources is necessary for the growth of green electronics and could be of the capability to wireless sensor networks. The ambient mechanical power is among the ample sources for various power harvesting device configurations that are published. In this work, we design and fabricate a paper-based nanogenerator (NG) utilizing piezoelectric zinc oxide (ZnO) nanowires (NWs) grown hydrothermally on a paper substrate. The fabricated NG can harvest ambient mechanical energy from various kinds of human motions, such as handwriting. The fabricated NG from a single ZnO NWs/PVDF-TrFE NG has been used firstly as handwriting-driven NG. The mechanical pressure applied on the paper platform while handwriting is harvested by the NG to deliver electrical energy; depending on the mode of handwriting, a maximum harvested voltage of 4.8 V was obtained.

Keywords: nanostructure, zinc oxide, nanogenerator, energy harvesting

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 150