Search results for: vaporous complex systems

Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: N. Brahmia

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria. As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS)… so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: geomatics, GIS, ODT, transport systems

Procedia PDF Downloads 584

Authors: Samuel Reisman

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Background: Comparative rankings are increasingly used to evaluate health care systems. These rankings combine discrete attribute rankings into a composite overall ranking. Health care equity is a component of overall rankings, but excelling in other categories can counterbalance low inequity grades. Highly ranked inequitable health care would commend systems that disregard human rights. We simulated the ranking of a maximally inequitable health care system using a published, influential ranking methodology. Methods: We used The Commonwealth Fund’s ranking of eleven health care systems to simulate the rank of a maximally inequitable system. Eighty performance indicators were simulated, assuming maximal ineptitude in equity benchmarks. Maximal rankings in all non-equity subcategories were assumed. Subsequent stepwise simulations lowered all non-equity rank positions by one. Results: The maximally non-equitable health care system ranked first overall. Three subsequent stepwise simulations, lowering non-equity rankings by one, each resulted in an overall ranking within the top three. Discussion: Our results demonstrate that grossly inequitable health care systems can rank highly in comparative health care system rankings. These findings challenge the validity of ranking methodologies that subsume equity under broader benchmarks. We advocate limiting maximum overall rankings of health care systems to their individual equity rankings. Such limits are logical given the insignificance of health care system improvements to those lacking adequate health care.

Keywords: global health, health equity, healthcare systems, international health

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Authors: N. Nivedita, S. Durbha

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Critical Infrastructure (CI) consists of services and technological networks such as healthcare, transport, water supply, electricity supply, information technology etc. These systems are necessary for the well-being and to maintain effective functioning of society. Critical Infrastructures can be represented as nodes in a network where they are connected through a set of links depicting the logical relationship among them; these nodes are interdependent on each other and interact with each at other at various levels, such that the state of each infrastructure influences or is correlated to the state of another. Disruption in the service of one infrastructure nodes of the network during a disaster would lead to cascading and escalating disruptions across other infrastructures nodes in the network. The operation of Healthcare Infrastructure is one such Critical Infrastructure that depends upon a complex interdependent network of other Critical Infrastructure, and during disasters it is very vital for the Healthcare Infrastructure to be protected, accessible and prepared for a mass casualty. To reduce the consequences of a disaster on the Critical Infrastructure and to ensure a resilient Critical Health Infrastructure network, knowledge, understanding, modeling, and analyzing the inter-dependencies between the infrastructures is required. The paper would present inter-dependencies related to Healthcare Critical Infrastructure based on Hierarchical Coloured Petri Nets modeling approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The model properties are being analyzed for the various state changes which occur when there is a disruption or damage to any of the Critical Infrastructure. The failure probabilities for the failure risk of interconnected systems are calculated by deriving a reachability graph, which is later mapped to a Markov chain. By analytically solving and analyzing the Markov chain, the overall vulnerability of the Healthcare CI HCPN model is demonstrated. The entire model would be integrated with Geographic information-based decision support system to visualize the dynamic behavior of the interdependency of the Healthcare and related CI network in a geographically based environment.

Keywords: critical infrastructure interdependency, hierarchical coloured petrinet, healthcare critical infrastructure, Petri Nets, Markov chain

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Authors: M. A. Abd-Allah, Mahmoud N. Ali, A. Said

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Lightning Protection Systems (LPS) for wind power generation is becoming an important public issue. A serious damage of blades, accidents where low-voltage and control circuit breakdowns frequently occur in many wind farms. A grounding system is one of the most important components required for appropriate LPSs in wind turbines WTs. Proper design of a wind turbine grounding system is demanding and several factors for the proper and effective implementation must be taken into account. This paper proposed procedure of proper design of grounding systems for a wind turbine was introduced. This procedure depends on measuring of ground current of simulated wind farm under lightning taking into consideration the soil ionization. The procedure also includes the Ground Potential Rise (GPR) and the voltage distributions at ground surface level and Touch potential. In particular, the contribution of mitigating techniques, such as rings, rods and the proposed design were investigated.

Keywords: WTs, Lightning Protection Systems (LPS), GPR, grounding system, mitigating techniques

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Authors: Bogdan Walek, Vladimir Bradac, Radim Farana

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Distance learning systems offer useful methods of learning and usually contain final course test or another form of test. The paper proposes web application for evaluating tests using expert system in distance learning systems. Proposed web application is appropriate for didactic tests or tests with results for subsequent studying follow-up courses. Web application works with test questions and uses expert system and LFLC tool for test evaluation. After test evaluation the results are visualized and shown to student.

Keywords: distance learning, test, uncertainty, fuzzy, expert system, student

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Authors: Moustapha Bande, Hakima Ould-Slimane, Hanifa Boucheneb

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Software development for complex systems requires efficient and automatic tools that can be used to verify the satisfiability of some critical properties such as security ones. With the emergence of Aspect-Oriented Programming (AOP), considerable work has been done in order to better modularize the separation of concerns in the software design and implementation. The goal is to prevent the cross-cutting concerns to be scattered across the multiple modules of the program and tangled with other modules. One of the key challenges in the aspect-oriented programs is to be sure that all the pieces put together at the weaving time ensure the satisfiability of the overall system requirements. Our paper focuses on this problem and proposes a formal property verification approach for a given property from the woven program. The approach is based on the control flow graph (CFG) of the woven program, and the use of a satisfiability modulo theories (SMT) solver to check whether each property (represented par one aspect) is satisfied or not once the weaving is done.

Keywords: aspect-oriented programming, control flow graph, property verification, satisfiability modulo theories

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Authors: Sergey N. Ermoliev, Margarita A. Belousova, Aida D. Goncharenko

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Application of the diagnostic complex of highly informative functional methods (electromyography, reodentography, laser Doppler flowmetry, reoperiodontography, vital computer capillaroscopy, optical tissue oximetry, laser fluorescence diagnosis) allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment. Introduction. It is necessary to create a complex of innovative highly informative and safe functional diagnostic methods for improvement of the quality of patient treatment by the early detection of stomatologic diseases. The purpose of the present study was to investigate the etiology and pathogenesis of functional disorders identified in the pathology of hard tissue, dental pulp, periodontal, oral mucosa and chewing function, and the creation of new approaches to the diagnosis of dental diseases. Material and methods. 172 patients were examined. Density of hard tissues of the teeth and jaw bone was studied by intraoral ultrasonic densitometry (USD). Electromyographic activity of masticatory muscles was assessed by electromyography (EMG). Functional state of dental pulp vessels assessed by reodentography (RDG) and laser Doppler flowmetry (LDF). Reoperiodontography method (RPG) studied regional blood flow in the periodontal tissues. Microcirculatory vascular periodontal studied by vital computer capillaroscopy (VCC) and laser Doppler flowmetry (LDF). The metabolic level of the mucous membrane was determined by optical tissue oximetry (OTO) and laser fluorescence diagnosis (LFD). Results and discussion. The results obtained revealed changes in mineral density of hard tissues of the teeth and jaw bone, the bioelectric activity of masticatory muscles, regional blood flow and microcirculation in the dental pulp and periodontal tissues. LDF and OTO methods estimated fluctuations of saturation level and oxygen transport in microvasculature of periodontal tissues. With LFD identified changes in the concentration of enzymes (nicotinamide, flavins, lipofuscin, porphyrins) involved in metabolic processes Conclusion. Our preliminary results confirmed feasibility and safety the of intraoral ultrasound densitometry technique in the density of bone tissue of periodontium. Conclusion. Application of the diagnostic complex of above mentioned highly informative functional methods allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment.

Keywords: electromyography (EMG), reodentography (RDG), laser Doppler flowmetry (LDF), reoperiodontography method (RPG), vital computer capillaroscopy (VCC), optical tissue oximetry (OTO), laser fluorescence diagnosis (LFD)

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Authors: Fatemeh Yousefi, Narges Fallah, Mohsen Kian, Mehrzad Pakzadeh

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The petrochemical complex releases wastewater, which is rich in organic pollutants and could not be treated easily. Treatment of the wastewater from a petrochemical industry has been investigated using a submerged membrane bioreactor (MBR). For this purpose, a pilot-scale submerged MBR with a flat-sheet ultrafiltration membrane was used for treatment of petrochemical wastewater according to Bandar Imam Petrochemical complex (BIPC) Aromatic plant. The testing system ran continuously (24-h) over 6 months. Trials on different membrane fluxes and hydraulic retention time (HRT) were conducted and the performance evaluation of the system was done. During the 167 days operation of the MBR at hydraulic retention time (HRT) of 18, 12, 6, and 3 and at an infinite sludge retention time (SRT), the MBR effluent quality consistently met the requirement for discharge to the environment. A fluxes of 6.51 and 13.02 L m-2 h-1 (LMH) was sustainable and HRT of 6 and 12 h corresponding to these fluxes were applicable. Membrane permeability could be fully recovered after cleaning. In addition, there was no foaming issue in the process. It was concluded that it was feasible to treat the wastewater using submersed MBR technology.

Keywords: membrane bioreactor (MBR), petrochemical wastewater, COD removal, biological treatment

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Authors: Sudhakar Kadiyala, Sripad R. Naik

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Large cavern in Bhutan Himalayas is being monitored since the construction period. The behavior of the cavern is being monitored for last 16 years. Instrumentation includes measurement of convergence of high walls by geodetic monitoring, load on the support systems with load cells and instrumented bolts. Analysis of the results of instrumentation showed that during the construction period of the cavern, the convergence of the cavern varied from 181 - 233 mm in the unit bay area with maximum convergence rate of 2.80mm/day. Whereas during the operational period the total convergence observed was in the range of 21 to 45 mm during a period of 11.30 years with convergence rate of 0.005 to 0.011 mm/day. During the last five years, there were no instances of high tensile stress recorded by the instrumented bolts. Load on the rock bolts have shown stabilization trend at most of the locations. This paper discusses in detail the results of long-term monitoring using the geotechnical instruments and how the data is being used in 3D numerical model to confirm the stability of the cavern.

Keywords: convergence, displacements, geodetic monitoring, long-term stability

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Johannes Atug, Stefan Braunreuther, Gunther Reinhart

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Volatile markets, as well as increasing global competition in manufacturing, lead to a high demand of flexible and agile production systems. These advanced production systems in turn conduct to high capital expenditure along with high investment risks. Developments in production regarding digitalization and cyber-physical systems result to a merger of informational- and operational technology. The approach of this paper is to benefit from this merger and present a framework of a production network with scalable production capacity and low capital expenditure by adaptation of the IT concept 'everything as a service' into the production environment.

Keywords: digital manufacturing system, everything as a service, reconfigurable production, value network

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Authors: Ceylan Sozer, Ece Ceylan Baba

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The reforms and changes that began with industrialization in cities and continued with globalization in 1980’s, created many changes in urban environments. City centers which are desolated due to industrialization, began to get crowded with globalization and became the heart of technology, commerce and social activities. While the immediate and intense alterations are planned around rigorous visions in developed countries, several urban areas where the processes were underestimated and not taken precaution faced with irrevocable situations. When the effects of the globalization in the cities are examined, it is seen that there are some anticipatory system plans in the cities about the future problems. Several cities such as New York, London and Tokyo have planned to resolve probable future problems in a systematic scheme to decrease possible side effects during globalization. The decisions in urban planning and their applications are the main points in terms of sustainability and livability in such mega-cities. This article examines the effects of globalization on urban planning through 3 mega cities and the applications. When the applications of urban plannings of the three mega-cities are investigated, it is seen that the city plans are generated under light of past experiences and predictions of a certain future. In urban planning, past and present experiences of a city should have been examined and then future projections could be predicted together with current world dynamics by a systematic way. In this study, methods used in urban planning will be discussed and ‘Anticipatory System’ model will be explained and relations with global-urban planning will be discussed. The concept of ‘anticipation’ is a phenomenon that means creating foresights and predictions about the future by combining past, present and future within an action plan. The main distinctive feature that separates anticipatory systems from other systems is the combination of past, present and future and concluding with an act. Urban plans that consist of various parameters and interactions together are identified as ‘live’ and they have systematic integrities. Urban planning with an anticipatory system might be alive and can foresight some ‘side effects’ in design processes. After globalization, cities became more complex and should be designed within an anticipatory system model. These cities can be more livable and can have sustainable urban conditions for today and future.In this study, urban planning of Istanbul city is going to be analyzed with comparisons of New York, Tokyo and London city plans in terms of anticipatory system models. The lack of a system in İstanbul and its side effects will be discussed. When past and present actions in urban planning are approached through an anticipatory system, it can give more accurate and sustainable results in the future.

Keywords: globalization, urban planning, anticipatory system, New York, London, Tokyo, Istanbul

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Authors: Feng-jie Xie, Jian-hong Yan

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Based on the complex network theory, we construct the air cargo network of the Belt and Road area, analyze its regional distribution and structural characteristics, measure the robustness of the network. The regional distribution results show that Southeast Asia and China have the most prominent development in the air cargo network of the Belt and Road area, Central Asia is the least developed. The structure characteristics found that the air cargo network has obvious small-world characteristics; the degree distribution has single-scale property; it shows a significant rich-club phenomenon simultaneously. The network robustness is measured by two attack strategies of degree and betweenness, but the betweenness of network nodes has a greater impact on network connectivity. And identified 24 key cities that have a large impact on the robustness of the network under the two attack strategies. Based on these results, recommendations are given to maintain the air cargo network connectivity in the Belt and Road area.

Keywords: air cargo, complex network, robustness, structure properties, The Belt and Road

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

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Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: Moawia Abulgader Gdara

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En -Naga sub - basin considered to be the most southern of the concessions in the Sirte Basin operated by HOO. En Naga Sub – basin have likely been point-sourced of CO2 accumulations during the last 7 million years from local satellite intrusives associated with the Haruj Al Aswad igneous complex. CO2 occurs in the En Naga Sub-basin as a result of the igneous activity of the Al Harouge Al Aswad complex. Igneous extrusive have been pierced in the subsurface are exposed at the surface. The lower cretaceous Bahi Sandstone facies are recognized in the En Naga Sub-basin. They result from the influence of paleotopography on the processes associated with continental deposition over the Sirt Unconformity and the Cenomanian marine transgression In the Lower Cretaceous Bahi Sandstones, the presence of trapped carbon dioxide is proven within the En Naga Sub-basin. This makes it unique in providing an abundance of CO2 gas reservoirs with almost pure magmatic CO2, which can be easily sampled. Huge amounts of CO2 exist in the Lower Cretaceous Bahi Sandstones in the En-Naga sub-basin, where the economic value of CO2 is related to its use for enhanced oil recovery (EOR) Based on the production tests for the drilled wells that makes Lower Cretaceous Bahi sandstones the principle reservoir rocks for CO2 where large volumes of CO2 gas have been discovered in the Bahi Formation on and near EPSA 120/136(En -Naga sub basin). The Bahi sandstones are generally described as a good reservoir rock. Intergranular porosities and permeabilities are highly variable and can exceed 25% and 100 MD.In the (En Naga sub – basin), The very high pressures assumed associated with local igneous intrusives may account for the abnormally high Bahi (and Lidam Formation) reservoir pressures. The best gas tests from this facies are at F1-72 on the (Barrut I structure) from part of a 458 feet+ section having an estimated high value of CO2 as 98% overpressured. Bahi CO2 prospectivity is thought to be excellent in the central to western areas where At U1-72 (En Naga O structure) a significant CO2 gas kick occurred at 11,971 feet and quickly led to blowout conditions due to uncontrollable leaks in the surface equipment. Which reflects a better reservoir quality sandstones associated with Paleostructural highs. Condensate and gas prospectivity increases to the east as the CO2 prospectivity decreases with distance away from the Al Haruj Al Aswad igneous complex. To date, it has not been possible to accurately determine the volume of these strategically valuable reserves although there are positive indications that they are very large.

Keywords: 1)en naga sub basin, 2)alharouge al aswad igneous complex, 3)co2 generation and migration, 4)lower cretaceous bahi sandstone

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Authors: F. U. Rahman, R. Q. Zhang

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This work aims to develop a systematic numerical technique which can be easily extended to many-body problem. The Lippmann Schwinger equation (integral form of the Schrodinger wave equation) is solved for the nonrelativistic radial wave of hydrogen atom using iterative integration scheme. As the unknown wave function appears on both sides of the Lippmann Schwinger equation, therefore an approximate wave function is used in order to solve the equation. The Green’s function is obtained by the method of Laplace transform for the radial wave equation with excluded potential term. Using the Lippmann Schwinger equation, the product of approximate wave function, the Green’s function and the potential term is integrated iteratively. Finally, the wave function is normalized and plotted against the standard radial wave for comparison. The outcome wave function converges to the standard wave function with the increasing number of iteration. Results are verified for the first fifteen states of hydrogen atom. The method is efficient and consistent and can be applied to complex systems in future.

Keywords: Green’s function, hydrogen atom, Lippmann Schwinger equation, radial wave

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Mohamed M. El-Awad

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This paper describes an educational platform for design analyses of pump-pipe systems by using Microsoft Excel, its Solver add-in, and the associated VBA programming language. The paper demonstrates the capabilities of the Excel-based platform that suits the iterative nature of the design process better than the use of design charts and data tables. While VBA is used for the development of a user-defined function for determining the standard pipe diameter, Solver is used for optimising the pipe diameter of the pipeline and for determining the operating point of the selected pump.

Keywords: design analyses, pump-pipe systems, Excel, solver, VBA

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Authors: Kyunghun Kang, Sangwoo Oh, Yongha Hwang

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PDMS (Polydimethylsiloxane)-based microfluidic device has been recently applied to area of biomedical research, tissue engineering, and diagnostics because PDMS is low cost, nontoxic, optically transparent, gas-permeable, and especially biocompatible. Generally, PDMS microfluidic devices are fabricated by conventional soft lithography. Microfabrication requires expensive cleanroom facilities and a lot of time; however, only two-dimensional or simple three-dimensional structures can be fabricated. In this study, we introduce fabricating method for complex three-dimensional microfluidic channels using soluble wax mold. Using the 3D printing technique, we firstly fabricated three-dimensional mold which consists of soluble wax material. The PDMS pre-polymer is cast around, followed by PDMS casting and curing. The three-dimensional casting mold was removed from PDMS by chemically dissolved with methanol and acetone. In this work, two preliminary experiments were carried out. Firstly, the solubility of several waxes was tested using various solvents, such as acetone, methanol, hexane, and IPA. We found the combination between wax and solvent which dissolves the wax. Next, side effects of the solvent were investigated during the curing process of PDMS pre-polymer. While some solvents let PDMS drastically swell, methanol and acetone let PDMS swell only 2% and 6%, respectively. Thus, methanol and acetone can be used to dissolve wax in PDMS without any serious impact. Based on the preliminary tests, three-dimensional PDMS microfluidic channels was fabricated using the mold which was printed out using 3D printer. With the proposed fabricating technique, PDMS-based microfluidic devices have advantages of fast prototyping, low cost, optically transparence, as well as having complex three-dimensional geometry. Acknowledgements: This research was supported by Supported by a Korea University Grant and Basic Science Research Program through the National Research Foundation of Korea(NRF).

Keywords: microfluidic channel, polydimethylsiloxane, 3D printing, casting

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Authors: Kolesnikova Julia, Fakhrutdinova Elena, Zagidullina Venera, Kamasheva Anastasia

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The article deals with the structure of intangible capital. A significant share of intangible capital is associated with a person as such and can be considered as human capital, which in turn also has a complex structure, including intellectual, social, organizational, client, reputational capital. We have allocated a separate category of intangible capital - unidentifiable capital, including a variety of synergistic interaction effects, etc. the structure of intangible capital. A significant share of intangible capital is associated with a person as such and can be considered as human capital, which in turn also has a complex structure, including intellectual, social, organizational, client, reputational capital. We have allocated unidentifiable capital as a separate category of intangible capital, including a variety of synergistic interaction effects and other.

Keywords: intangible capital, intangible property, object of intangible property, reputation capital

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Authors: Melissa Beck Wells

Abstract:

This study examines the complex factors affecting teacher retention across states, focusing on the roles of salaries, educational policies, and professional development. Despite efforts to reduce teacher turnover, it remains a significant challenge, impacting the quality of education and student outcomes. Analysis of data from the National Education Association, the ‘Raise the Bar’ initiative, and the Education Commission of the States reveals a minimal negative correlation between teacher salaries and retention, indicating that salary alone does not determine retention. Additionally, thematic analysis of educational policies and development programs highlights effective strategies for addressing retention challenges. The research emphasizes the need for holistic support systems, including mentorship and professional growth opportunities, to improve retention. These findings urge policymakers and educational leaders to develop comprehensive strategies to maintain a qualified teaching workforce and enhance educational quality and equity nationwide.

Keywords: teacher retention, salary levels, educational policies, professional development, teacher turnover

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: M. Abderrahmane Mograne, Didier Laux, Jean-Yves Ferrandis

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Rheological characterizations of complex liquids like polymer solutions present an important scientific interest for a lot of researchers in many fields as biology, food industry, chemistry. In order to establish master curves (elastic moduli vs frequency) which can give information about microstructure, classical rheometers or viscometers (such as Couette systems) are used. For broadband characterization of the sample, temperature is modified in a very large range leading to equivalent frequency modifications applying the Time Temperature Superposition principle. For many liquids undergoing phase transitions, this approach is not applicable. That is the reason, why the development of broadband spectroscopic methods around room temperature becomes a major concern. In literature many solutions have been proposed but, to our knowledge, there is no experimental bench giving the whole rheological characterization for frequencies about a few Hz (Hertz) to many MHz (Mega Hertz). Consequently, our goal is to investigate in a nondestructive way in very broadband frequency (A few Hz – Hundreds of MHz) rheological properties using longitudinal ultrasonic waves (L waves), a unique experimental bench and a specific container for the liquid: a test tube. More specifically, we aim to estimate the three viscosities (longitudinal, shear and bulk) and the complex elastic moduli (M*, G* and K*) respectively longitudinal, shear and bulk moduli. We have decided to use only L waves conditioned in two ways: bulk L wave in the liquid or guided L waves in the tube test walls. In this paper, we will present first results for very low frequencies using the ultrasonic tracking of a falling ball in the test tube. This will lead to the estimation of shear viscosity from a few mPa.s to a few Pa.s (Pascal second). Corrections due to the small dimensions of the tube will be applied and discussed regarding the size of the falling ball. Then the use of bulk L wave’s propagation in the liquid and the development of a specific signal processing in order to assess longitudinal velocity and attenuation will conduct to the longitudinal viscosity evaluation in the MHz frequency range. At last, the first results concerning the propagation, the generation and the processing of guided compressional waves in the test tube walls will be discussed. All these approaches and results will be compared to standard methods available and already validated in our lab.

Keywords: nondestructive measurement for liquid, piezoelectric transducer, ultrasonic longitudinal waves, viscosities

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Luca Garbarino, Urbano Tancredi, Domenico Accardo, Michele Grassi, Giancarmine Fasano, Anna Elena Tirri

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The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.

Keywords: ADS-B, avionics, NAVAIDs, real-time simulation, TCAS, UAS ground control station

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Authors: Amanda Cristina de Oliveira, Elias de Souza Monteiro Filho, Roberta Ceriani

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Liquid-liquid extraction in aqueous two-phase systems (ATPSs) constitutes a powerful tool for purifying bio-materials, such as cells, organelles, proteins, among others. In this work, the extraction of the bovine serum albumin (BSA) has been studied in systems formed by polyethylene glycol (PEG) (1500, 4000, and 6000 g.mol⁻¹) + potassium sodium tartrate + water at 303.15°K. Phase diagrams were obtained by turbidimetry and Merchuk’s method (1998). The experimental tie-lines were described using the Othmer-Tobias and Bancroft correlations. ATPSs were correlated with the nonrandom two-liquid (NRTL) model. The results were considered excellent according to global root-mean-square deviations found which were between 0,72 and 1,13%. The concentrations of the proteins in each phase were determined by spectrophotometry at 280 nm, finding partition efficiencies greater than 71%.

Keywords: aqueous two phases systems, bovine serum albumin , liquid-liquid extraction, polyethylene glycol

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Authors: Naci Kalkan, Ihsan Dagtekin

Abstract:

Passive design responds to improve indoor thermal comfort and minimize the energy consumption. The present research analyzed the how efficiently passive solar technologies generate heating and cooling and provide the system integration for domestic applications. In addition to this, the aim of this study is to increase the efficiency of solar systems system with integration some innovation and optimization. As a result, outputs of the project might start a new sector to provide environmentally friendly and cheap cooling for domestic use.

Keywords: passive solar systems, heating, cooling, thermal comfort, ventilation systems

Procedia PDF Downloads 281