Search results for: surveillance systems

Authors: D. E. Egirani, J. E. Andrews, A. R. Baker

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This study investigates sorption of Cu and Zn contained in natural mine wastewater, using mixed mineral systems in sulfidic-anoxic condition. The mine wastewater was obtained from disused mine workings at Cwmheidol in Wales, United Kingdom. These contaminants flow into water courses. These water courses include River Rheidol. In this River fishing activities exist. In an attempt to reduce Cu-Zn levels of fish intake in the watercourses, single mineral systems and 1:1 mixed mineral systems of clay and goethite were tested with the mine waste water for copper and zinc removal at variable pH. Modelling of hydroxyl complexes was carried out using phreeqc method. Reactions using batch mode technique was conducted at room temperature. There was significant differences in the behaviour of copper and zinc removal using mixed mineral systems when compared  to single mineral systems. All mixed mineral systems sorb more Cu than Zn when tested with mine wastewater.

Keywords: Cu- Zn, hydroxyl complexes, kinetics, mixed mineral systems, reactivity

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Authors: M. N. Tandjaoui, C. Banoudjafar, C. Benachaiba, O. Abdelkhalek, A. Kechich

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Advanced power electronic systems are deemed to be an integral part of renewable, green, and efficient energy systems. Wind energy is one of the renewable means of electricity generation that is now the world’s fastest growing energy source can bring new challenges when it is connected to the power grid due to the fluctuation nature of the wind and the comparatively new types of its generators. The wind energy is part of the worldwide discussion on the future of energy generation and use and consequent effects on the environment. However, this paper will introduce some of the requirements and aspects of the power electronic involved with modern wind generation systems, including modern power electronics and converters, and the issues of integrating wind turbines into power systems.

Keywords: power electronics, renewable energy, smart grid, green energy, power technology

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Authors: Claire Biasco, Thaier Hayajneh

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A smart city is the integration of digital technologies in urban environments to enhance the quality of life. Smart cities capture real-time information from devices, sensors, and network data to analyze and improve city functions such as traffic analysis, public safety, and environmental impacts. Current smart cities face controversy due to their reliance on real-time data tracking and surveillance. Internet of Things (IoT) devices and blockchain technology are converging to reshape smart city infrastructure away from its centralized model. Connecting IoT data to blockchain applications would create a peer-to-peer, decentralized model. Furthermore, blockchain technology powers the ability for IoT device data to shift from the ownership and control of centralized entities to individuals or communities with Decentralized Autonomous Organizations (DAOs). In the context of smart cities, DAOs can govern cyber-physical systems to have a greater influence over how urban services are being provided. This paper will explore how the core components of a smart city now apply to DAOs. We will also analyze different definitions of DAOs to determine their most important aspects in relation to smart cities. Both categorizations will provide a solid foundation to conduct a cybersecurity assessment of DAOs in smart cities. It will identify the benefits and risks of adopting DAOs as they currently operate. The paper will then provide several mitigation methods to combat cybersecurity risks of DAO integrations. Finally, we will give several insights into what challenges will be faced by DAO and blockchain spaces in the coming years before achieving a higher level of maturity.

Keywords: blockchain, IoT, smart city, DAO

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Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: Mahdi Alkaeed, Adeel Ehsan

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Enterprise information systems (EIS) act as the backbone of organizations that belong to different domains. These systems not only play a major role in the efficient usage of resources and time but also throw light on the future roadmap for the enterprise. In today's rapidly expanding world of business and technology, enterprise systems from various heterogenous environments have to exchange information at some point, be it within the same organization or between different organizations. This reality strengthens the importance of interoperability between these systems, which is one of the key enablers of systems collaboration. Both information technology infrastructure and business processes have to be aligned with each other to achieve this effect. This will be difficult to attain if traditional tightly coupled architecture is used. Instead, a more loosely coupled service-oriented architecture has to be used. That would enable an effective interoperability level between different EIS. This paper discusses and presents the current work that has been done in the field of EIS interoperability. Along the way, it also discusses the challenges, solutions to tackle those challenges presented in the studied literature, and limitations, if any.

Keywords: enterprise systems interoperability, collaboration and integration, service-based architecture, open system architecture

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Authors: Chukwuka E. V., Rowling J. K., Rushdie Salman

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The field of electronic engineering encompasses the study and application of electrical systems, circuits, and devices. Engineers in this discipline design, analyze and optimize electronic components to develop innovative solutions for various industries. This abstract provides a brief overview of the diverse areas within electronic engineering, including analog and digital electronics, signal processing, communication systems, and embedded systems. It highlights the importance of staying abreast of advancements in technology and fostering interdisciplinary collaboration to address contemporary challenges in this rapidly evolving field.

Keywords: smart home engineering, energy efficiency, user-centric design, security frameworks

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Authors: Mojtaba Saeedinezhad, Sarah Yousefi

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In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

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Authors: Mengqiu Deng, Xiao Peng, Yang Zhao

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The development of local energy systems requires the collective involvement of different actors from various levels of society. However, the stakeholder analysis of local energy systems still has been under-developed. This paper proposes an multi-agent system (MAS) framework to facilitate the development of stakeholder analysis of local energy systems. The framework takes into account the most influencing stakeholders, including prosumers/consumers, system operators, energy companies and government bodies. Different stakeholders are modeled based on agent architectures for example the belief-desire-intention (BDI) to better reflect their motivations and interests in participating in local energy systems. The agent models of different stakeholders are then integrated in one model of the whole energy system. An illustrative case study is provided to elaborate how to develop a quantitative agent model for different stakeholders, as well as to demonstrate the practicability of the proposed framework. The findings from the case study indicate that the suggested framework and agent model can serve as analytical instruments for enhancing the government’s policy-making process by offering a systematic view of stakeholder interconnections in local energy systems.

Keywords: multi-agent system, BDI agent, local energy systems, stakeholders

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Authors: Seon-Hack Hong, Tae-Il Choi

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Interoperability is defined as systems, components, and devices developed by different entities smoothly exchanging information and functioning organically without mutual consultation, being able to communicate with each other and computer systems of the same type or different types, and exchanging information or the ability of two or more systems to exchange information and use the information exchanged without extra effort. Insufficiencies such as duplication of functions when developing systems and applications due to lack of interoperability in the electric power system and low efficiency due to a lack of mutual information transmission system between the inside of the application program and the design is improved, and the seamless linkage of newly developed systems is improved. Since it is necessary to secure interoperability for this purpose, we designed the smart grid-based interoperability standard model in this paper.

Keywords: interoperability, power system, common information model, SCADA, IEEE2030, Zephyr

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Authors: Bruno Vilić Belina, Jadranko Matuško

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The rapid development of cyber-physical systems significantly influences modern control systems introducing a whole new range of applications of control systems but also putting them under new challenges to ensure their resiliency to possible cyber attacks, either in the form of data integrity attacks or deception attacks. This paper presents a model predictive approach to the control of cyber-physical systems robust to cyber attacks. We assume that a cyber attack can be modelled as an additive disturbance that acts in the measuring channel. For such a system, we designed a tube-based predictive controller based. The performance of the designed controller has been verified in Matlab/Simulink environment.

Keywords: control systems, cyber attacks, resiliency, robustness, tube based model predictive control

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Authors: Vandana N. Purav

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The Dynamical systems concept is a mathematical formalization for any fixed rule that describes the time dependence of a points position in its ambient space. e.g. pendulum of a clock, the number of fish each spring in a lake, the number of rabbits spring in an enclosure, etc. The Dynamical system theory used to describe the complex nature that is dynamical systems with differential equations called continuous dynamical system or dynamical system with difference equations called discrete dynamical system. The concept of dynamical system has its origin in Newtonian mechanics.

Keywords: dynamical systems, Fibonacci numbers, Newtonian mechanics, discrete dynamical system

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Authors: Grienggrai Rajchakit

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This paper is concerned with the exponential stability of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton's formula, a switching rule for the exponential stability of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability of the systems are first established in terms of LMIs. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: exponential stability, hybrid systems, time-varying delays, lyapunov-krasovskii functional, leibniz-newton's formula

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Authors: Farshad Badie

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The central focus of this article is on the fact that knowledge is constructed from an interaction between humans’ experiences and over their conceptions of constructed concepts. Logical characterisation of ‘human inductive learning over human’s constructed concepts’ within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. This research connects with the topics ‘human learning’, ‘epistemology’, ‘cognitive modelling’, ‘knowledge representation’ and ‘ontological reasoning’.

Keywords: human concept learning, concept construction, knowledge construction, terminological systems

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Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

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Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

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Authors: Henry Memczak, Marc Hovestaedt, Bernhard Ay, Sandra Saenger, Thorsten Wolff, Frank F. Bier

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The influenza viruses cause flu epidemics every year and serious pandemics in larger time intervals. The only cost-effective protection against influenza is vaccination. Due to rapid mutation continuously new subtypes appear, what requires annual reimmunization. For a correct vaccination recommendation, the circulating influenza strains had to be detected promptly and exactly and characterized due to their antigenic properties. During the flu season 2016/17, a wrong vaccination recommendation has been given because of the great time interval between identification of the relevant influenza vaccine strains and outbreak of the flu epidemic during the following winter. Due to such recurring incidents of vaccine mismatches, there is a great need to speed up the process chain from identifying the right vaccine strains to their administration. The monitoring of subtypes as part of this process chain is carried out by national reference laboratories within the WHO Global Influenza Surveillance and Response System (GISRS). To this end, thousands of viruses from patient samples (e.g., throat smears) are isolated and analyzed each year. Currently, this analysis involves complex and time-intensive (several weeks) animal experiments to produce specific hyperimmune sera in ferrets, which are necessary for the determination of the antigen profiles of circulating virus strains. These tests also bear difficulties in standardization and reproducibility, which restricts the significance of the results. To replace this test a peptide-based assay for influenza virus subtyping from corresponding virus samples was developed. The differentiation of the viruses takes place by a set of specifically designed peptidic recognition molecules which interact differently with the different influenza virus subtypes. The differentiation of influenza subtypes is performed by pattern recognition guided by machine learning algorithms, without any animal experiments. Synthetic peptides are immobilized in multiplex format on various platforms (e.g., 96-well microtiter plate, microarray). Afterwards, the viruses are incubated and analyzed comparing different signaling mechanisms and a variety of assay conditions. Differentiation of a range of influenza subtypes, including H1N1, H3N2, H5N1, as well as fine differentiation of single strains within these subtypes is possible using the peptide-based subtyping platform. Thereby, the platform could be capable of replacing the current antigenic characterization of influenza strains using ferret hyperimmune sera.

Keywords: antigenic characterization, influenza-binding peptides, influenza subtyping, influenza surveillance

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Authors: Samuel Kaspi, Sitalakshmi Venkatraman

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In-memory database systems are becoming popular due to the availability and affordability of sufficiently large RAM and processors in modern high-end servers with the capacity to manage large in-memory database transactions. While fast and reliable in-memory systems are still being developed to overcome cache misses, CPU/IO bottlenecks and distributed transaction costs, disk-based data stores still serve as the primary persistence. In addition, with the recent growth in multi-tenancy cloud applications and associated security concerns, many organisations consider the trade-offs and continue to require fast and reliable transaction processing of disk-based database systems as an available choice. For these organizations, the only way of increasing throughput is by improving the performance of disk-based concurrency control. This warrants a hybrid database system with the ability to selectively apply an enhanced disk-based data management within the context of in-memory systems that would help improve overall throughput. The general view is that in-memory systems substantially outperform disk-based systems. We question this assumption and examine how a modified variation of access invariance that we call enhanced memory access, (EMA) can be used to allow very high levels of concurrency in the pre-fetching of data in disk-based systems. We demonstrate how this prefetching in disk-based systems can yield close to in-memory performance, which paves the way for improved hybrid database systems. This paper proposes a novel EMA technique and presents a comparative study between disk-based EMA systems and in-memory systems running on hardware configurations of equivalent power in terms of the number of processors and their speeds. The results of the experiments conducted clearly substantiate that when used in conjunction with all concurrency control mechanisms, EMA can increase the throughput of disk-based systems to levels quite close to those achieved by in-memory system. The promising results of this work show that enhanced disk-based systems facilitate in improving hybrid data management within the broader context of in-memory systems.

Keywords: in-memory database, disk-based system, hybrid database, concurrency control

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Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

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This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

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Authors: Rodrigo S. Moreira, Nelson F. F. Ebecken

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This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs.

Keywords: ram memory, WiSARD weightless neural network, object tracking, quantization

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Authors: Sadegh Torfi

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Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

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Authors: Natchaphon Auampradit, Patama Vapattanawong, Sureeporn Punpuing, Malee Sunpuwan, Tawanchai Jirapramukpitak

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Longitudinal studies related to cognitive impairment in elderly are necessary for health promotion and development. The purposes of this study were (1) to examine changes in cognition of elderly over time and (2) to examine the impacts of changes in social determinants of health (SDH) toward changes in cognition of elderly by using the secondary data derived from the Kanchanaburi Demographic Surveillance System (KDSS) by the Institute for Population and Social Research (IPSR) which contained longitudinal data on individuals, households, and villages. Two selected projects included the Health and Social Support for Elderly in KDSS in 2007 and the Population, Economic, Social, Cultural, and Long-term Care Surveillance for Thai Elderly People’s Health Promotion in 2011. The samples were 586 elderly participated in both projects. SDH included living arrangement, social relationships with children, relatives, and friends, household asset-based wealth index, household monthly income, loans for livings, loans for investment, and working status. Cognitive impairment was measured by category fluency and delayed recall. This study employed Generalized Estimating Equation (GEE) model to investigate changes in cognition by taking SDH and other variables such as age, gender, marital status, education, and depression into the model. The unstructured correlation structure was selected to use for analysis. The results revealed that 24 percent of elderly had cognitive impairment at baseline. About 13 percent of elderly still had cognitive impairment during 2007 until 2011. About 21 percent and 11 percent of elderly had cognitive decline and cognitive improvement, respectively. The cross-sectional analysis showed that household asset-based wealth index, social relationship with friends, working status, age, marital status, education, and depression were significantly associated with cognitive impairment. The GEE model revealed longitudinal effects of household asset-based wealth index and working status against cognition during 2007 until 2011. There was no longitudinal effect of social conditions against cognition. Elderly living with richer household asset-based wealth index, still being employed, and being younger were less likely to have cognitive impairment. The results strongly suggested that poorer household asset-based wealth index and being unemployed were served as a risk factor for cognitive impairment over time. Increasing age was still the major risk for cognitive impairment as well.

Keywords: changes in cognition, cognitive impairment, elderly, KDSS, longitudinal study

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Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

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This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: state estimation, control systems, observer systems, nonlinear systems

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Authors: Matthew I. Bellgard

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The field of bioinformatics has made, and continues to make, substantial progress and contributions to life science research and development. However, this paper contends that a systems approach integrates bioinformatics activities for any project in a defined manner. The application of critical control points in this bioinformatics systems approach may be useful to identify and evaluate points in a pathway where specified activity risk can be reduced, monitored and quality enhanced.

Keywords: bioinformatics, food security, personalized medicine, systems approach

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Authors: Kazem Ghanbari, Yousef Gholami

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This paper deals with study about fractional order impulsive Hamiltonian systems and fractional impulsive Sturm-Liouville type problems derived from these systems. The main purpose of this paper devotes to obtain so called Lyapunov type inequalities for mentioned problems. Also, in view point on applicability of obtained inequalities, some qualitative properties such as stability, disconjugacy, nonexistence and oscillatory behaviour of fractional Hamiltonian systems and fractional Sturm-Liouville type problems under impulsive conditions will be derived. At the end, we want to point out that for studying fractional order Hamiltonian systems, we will apply recently introduced fractional Conformable operators.

Keywords: fractional derivatives and integrals, Hamiltonian system, Lyapunov-type inequalities, stability, disconjugacy

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Authors: Lei Zhou, Chao Li, Ruiqi Ren, Dan Li, Yali Wang, Daxin Ni, Zijian Feng, Qun Li

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Background: Since the first human infection with avian influenza A(H7N9) case was reported in China on 31 March 2013, five epidemics have been observed in China through February 2013 and September 2017. Though the overall mortality rate of H7N9 has remained as high as around 40% throughout the five epidemics, the specific mortality rate in Mainland China varied by provinces. We conducted a descriptive analysis of mortality rates of H7N9 cases to explore the various severity features of the disease and then to provide clues of further analyses of potential factors associated with the severity of the disease. Methods: The data for analysis originated from the National Notifiable Infectious Disease Report and Surveillance System (NNIDRSS). The surveillance system and identification procedure for H7N9 infection have not changed in China since 2013. The definition of a confirmed H7N9 case is as same as previous reports. Mortality rates of H7N9 cases are described and compared by time and location of reporting, age and sex, and genetic features of H7N9 virus strains. Results: The overall mortality rate, the male and female specific overall rates of H7N9 is 39.6% (608/1533), 40.3% (432/1072) and 38.2% (176/461), respectively. There was no significant difference between the mortality rates of male and female. The age-specific mortality rates are significantly varied by age groups (χ²=38.16, p < 0.001). The mortality of H7N9 cases in the age group between 20 and 60 (33.17%) and age group of over 60 (51.16%) is much higher than that in the age group of under 20 (5.00%). Considering the time of reporting, the mortality rates of cases which were reported in the first (40.57%) and fourth (42.51%) quarters of each year are significantly higher than the mortality of cases which were reported in the second (36.02%) and third (27.27%) quarters (χ²=75.18, p < 0.001). The geographic specific mortality rates vary too. The mortality rates of H7N9 cases reported from the Northeast China (66.67%) and Westeast China (56.52%) are significantly higher than that of H7N9 cases reported from the remained area of mainland China. The mortality rate of H7N9 cases reported from the Central China is the lowest (34.38%). The mortality rates of H7N9 cases reported from rural (37.76%) and urban (38.96%) areas are similar. The mortality rate of H7N9 cases infected with the highly pathogenic avian influenza A(H7N9) virus (48.15%) is higher than the rate of H7N9 cases infected with the low pathogenic avian influenza A(H7N9) virus (37.57%), but the difference is not statistically significant. Preliminary analyses showed that age and some clinical complications such as respiratory failure, heart failure, and septic shock could be potential risk factors associated with the death of H7N9 cases. Conclusions: The mortality rates of H7N9 cases varied by age, sex, time of reporting and geographical location in mainland China. Further in-depth analyses and field investigations of the factors associated with the severity of H7N9 cases need to be considered.

Keywords: H7N9 virus, Avian Influenza, mortality, China

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Andrei Nosov

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This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: observer systems, unscented Kalman filter, nonlinear systems, Burgers' equation

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Authors: Abdelmanie Suleimat, Nagham Abu Shaqra, Sawsan Majali, Issam Adawi, Heba Abo Shindi, Anas Al Mohtaseb

Abstract:

The Government of Jordan recognizes that maternal mortality constitutes a grave public health problem. Over the past two decades, there has been significant progress in improving the quality of maternal health services, resulting in improved maternal and child health outcomes. Despite these efforts, measurement and analysis of maternal mortality remained a challenge, with significant discrepancies from previous national surveys that inhibited accuracy. In response with support from USAID, the Jordan Maternal Mortality Surveillance Response (JMMSR) System was established to collect, analyze, and equip policymakers with data for decision-making guided by interdisciplinary multi-levelled advisory groups aiming to eliminate preventable maternal deaths, A 2016 Public Health Bylaw required the notification of deaths among women of reproductive age. The JMMSR system was launched in 2018 and continues annually, analyzing data received from health facilities, to guide policy to prevent avoidable deaths. To date, there have been four annual national maternal mortality reports (2018-2021). Data is collected, reviewed by advisory groups, and then consolidated in an annual report to inform and guide the Ministry of Health (MOH); JMMSR collects the necessary information to calculate an accurate maternal mortality ratio and assists in identifying leading causes and contributing factors for each maternal death. Based on this data, national response plans are created. A monitoring and evaluation plan was designed to define, track, and improve implementation through indicators. Over the past four years, one of these indicators, ‘percent of facilities notifying respective health directorates of all deaths of women of reproductive age,’ increased annually from 82.16%, 92.95%, and 92.50% to 97.02%, respectively. The Government of Jordan demonstrated commitment to the JMMSR system by designating the MOH to primarily host the system and lead the development and dissemination of policies and procedures to standardize implementation. The data was translated into practical and evidence-based recommendations. The successful impact of results deepened the understanding of maternal mortality in Jordan, which convinced the MOH to amend the Bylaw now mandating electronic reporting of all births and neonatal deaths from health facilities to empower the JMMSR system, by developing a stillbirths and neonatal mortality surveillance and response system.

Keywords: maternal health, maternal mortality, preventable maternal deaths, maternal morbidity

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