Search results for: computational intelligence

Authors: Radhwane Boudjelthia

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The most recent earthquakes occurred in the world have killed thousands of people and severe damage. For all the actors involved in the building process, the earthquake is the litmus test for construction. The goal we set ourselves is to contribute to the implementation of a thoughtful approach to the seismic protection of structures. For many engineers, the most conventional approach to protection works (buildings and bridges) the effects of earthquakes is to increase rigidity. This approach is not always effective, especially when there is a context that favors the phenomenon of resonance and amplification of seismic forces. Therefore, the field of earthquake engineering has made significant inroads, among others catalyzed by the development of computational techniques in computer form and the use of powerful test facilities. This has led to the emergence of several innovative technologies, such as the introduction of special devices insulation between infrastructure and superstructure. This approach, commonly known as "seismic isolation," to absorb the significant efforts without the structure is damaged and thus ensuring the protection of lives and property. In addition, the restraints to the construction by the ground shaking are located mainly at the supports. With these moves, the natural period of construction is increasing, and seismic loads are reduced. Thus, there is an attenuation of the seismic movement. Likewise, the insulation of the base mechanism may be used in combination with earthquake dampers in order to control the deformation of the insulation system and the absolute displacement of the superstructure located above the isolation interface. On the other hand, only can use these earthquake dampers to reduce the oscillation amplitudes and thus reduce seismic loads. The use of damping devices represents an effective solution for the rehabilitation of existing structures. Given all these acceleration reducing means considered passive, much research has been conducted for several years to develop an active control system of the response of buildings to earthquakes.

Keywords: earthquake, building, seismic forces, displacement, resonance, response.

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Authors: Sherman Ho, Ahmed Cherif Megri

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Headers play a critical role in conveying steam to regulate heating system temperatures. While various materials like steel grades 91 and 92 have been traditionally used for pipes, this research proposes the use of a robust and innovative material, INCONEL Alloy 740H. Boilers in power plant configurations are exposed to cycling conditions due to factors such as daily, seasonal, and yearly variations in weather. These cycling conditions can lead to the deterioration of headers, which are vital components with intricate geometries. Header failures result in substantial financial losses from repair costs and power plant shutdowns, along with significant public inconveniences such as the loss of heating and hot water. To address this issue and seek solutions, a mechanical analysis, as well as a structural analysis, are recommended. Transient analysis to predict heat transfer conditions is of paramount importance, as the direction of heat transfer within the header walls and the passing steam can vary based on the location of interest, load, and operating conditions. The geometry and material of the header are also crucial design factors, and the choice of pipe material depends on its usage. In this context, the heat transfer coefficient plays a vital role in header design and analysis. This research employs ANSYS Fluent, a numerical simulation program, to understand header behavior, predict heat transfer, and analyze mechanical phenomena within the header. Transient simulations are conducted to investigate parameters like heat transfer coefficient, pressure loss coefficients, and heat flux, with the results used to optimize header design.

Keywords: CFD, header, power plant, heat transfer coefficient, simulation using experimental data

Procedia PDF Downloads 48

Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: L. Melzerová, T. Janda, M. Šejnoha, J. Šejnoha

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Two finite element (FEM) models are presented in this paper to address the random nature of the response of glued timber structures made of wood segments with variable elastic moduli evaluated from 3600 indentation measurements. This total database served to create the same number of ensembles as was the number of segments in the tested beam. Statistics of these ensembles were then assigned to given segments of beams and the Latin Hypercube Sampling (LHS) method was called to perform 100 simulations resulting into the ensemble of 100 deflections subjected to statistical evaluation. Here, a detailed geometrical arrangement of individual segments in the laminated beam was considered in the construction of two-dimensional FEM model subjected to in four-point bending to comply with the laboratory tests. Since laboratory measurements of local elastic moduli may in general suffer from a significant experimental error, it appears advantageous to exploit the full scale measurements of timber beams, i.e. deflections, to improve their prior distributions with the help of the Bayesian statistical method. This, however, requires an efficient computational model when simulating the laboratory tests numerically. To this end, a simplified model based on Mindlin’s beam theory was established. The improved posterior distributions show that the most significant change of the Young’s modulus distribution takes place in laminae in the most strained zones, i.e. in the top and bottom layers within the beam center region. Posterior distributions of moduli of elasticity were subsequently utilized in the 2D FEM model and compared with the original simulations.

Keywords: Bayesian inference, FEM, four point bending test, laminated timber, parameter estimation, prior and posterior distribution, Young’s modulus

Procedia PDF Downloads 259

Authors: Evgeny Obraztsov, Ilya Kremnev, Vitaly Sokolov, Maksim Gavrilov, Evgeny Tretyakov, Vladimir Kukhtevich, Vladimir Bezlepkin

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Over the last decade, a specific set of connected software tools and calculation codes has been gradually developed. It allows simulating I&C systems, thermal-hydraulic, neutron-physical and electrical processes in elements and systems at the Unit of NPP (initially with WWER (pressurized water reactor)). In 2012 it was called a complex simulation suite “Virtual Unit of NPP” (or CSS “VEB” for short). Proper application of this complex tool should result in a complex coupled mathematical computational model. And for a specific design of NPP, it is called the Virtual Power Unit (or VPU for short). VPU can be used for comprehensive modelling of a power unit operation, checking operator's functions on a virtual main control room, and modelling complicated scenarios for normal modes and accidents. In addition, CSS “VEB” contains a combination of thermal hydraulic codes: the best-estimate (two-liquid) calculation codes KORSAR and CORTES and a homogenous calculation code TPP. So to analyze a specific technological system one can build thermal-hydraulic simulation models with different detalization levels up to a nodalization scheme with real geometry. And the result at some points is similar to the notion “engineering/testing simulator” described by the European utility requirements (EUR) for LWR nuclear power plants. The paper is dedicated to description of the tools mentioned above and an example of the application of the engineering thermal-hydraulic simulator in analysis of the boron acid concentration in the primary coolant (changed by the make-up and boron control system).

Keywords: best-estimate code, complex simulation suite, engineering simulator, power plant, thermal hydraulic, VEB, virtual power unit

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Iara Rezende, Djalma Silva, Alcino Costa Neto

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Considering the transformations of the contemporary world linked to globalization and climate changes caused by global warming, the environmental and energy issues have been increasingly present in the decisions of the world scenario. Thus, the aim of reducing the impacts caused by human activities there are the energy efficiency measures, which are also applicable in the scope of Civil Engineering. Considering that a large part of the energy demand from buildings is related to the need to adapt the internal environment to the users comfort and productivity, measures capable of reducing this need can minimize the climate changes impacts and also the energy consumption of the building. However, these important measures are currently little used by civil engineers, either because of the interdisciplinarity of the subject, the time required to apply certain methods or the difficult interpretation of the results obtained by computational programs that often have a complex and little applied approach. Thus, it was proposed the development of a Java application with a simpler and applied approach to evaluate the thermal performance of a building in order to obtain results capable of assisting the civil engineers in the decision making related to the users thermal comfort. The program was built in Java programming language and the method used for the evaluation was the Center Scientifique et Technique du Batiment (CSTB) method. The program was used to evaluate the thermal performance of a university classroom. The analysis was carried out from simulations considering the worst climatic situation of the building occupation. Thus, at the end of the process, the favorable result was obtained regarding the classroom comfort zone and the feasibility of using the program, thus achieving the proposed objectives.

Keywords: building occupation, CSTB method, energy efficiency measures, Java application, thermal comfort

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Authors: Mudassir Ghafoor, Irsalan Arif, Shuaib Salamat

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This paper presents modeling and analysis of different intake bump (compression surface) configurations and comparison with an existing supersonic aircraft having bump intake configuration. Many successful aircraft models have shown that Diverter less Supersonic Inlet (DSI) as compared to conventional intake can reduce weight, complexity and also maintenance cost. The research is divided into two parts. In the first part, four different intake bumps are modeled for comparative analysis keeping in view the consistency of outer perimeter dimensions of fighter aircraft and various characteristics such as flow behavior, boundary layer diversion and pressure recovery are analyzed. In the second part, modeled bumps are integrated with intake duct for performance analysis and comparison with existing supersonic aircraft data is carried out. The bumps are named as uniform large (Config 1), uniform small (Config 2), uniform sharp (Config 3), non-uniform (Config 4) based on their geometric features. Analysis is carried out at different Mach Numbers to analyze flow behavior in subsonic and supersonic regime. Flow behavior, boundary layer diversion and Pressure recovery are examined for each bump characteristics, and comparative study is carried out. The analysis reveals that at subsonic speed, Config 1 and Config 2 give similar pressure recoveries as diverterless supersonic intake, but difference in pressure recoveries becomes significant at supersonic speed. It was concluded from research that Config 1 gives better results as compared to Config 3. Also, higher amplitude (Config 1) is preferred over lower (Config 2 and 4). It was observed that maximum height of bump is preferred to be placed near cowl lip of intake duct.

Keywords: bump intake, boundary layer, computational fluid dynamics, diverter-less supersonic inlet

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Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

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Authors: Li-Kai Kuo, Shyh-Hau Wang

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The kinetic trajectory of the median nerve (MN) in the wrist has shown to be capable of being applied to assess the carpal tunnel syndrome (CTS), and was found able to be detected by high-frequency ultrasound image via motion tracking technique. Yet, previous study may not quickly perform the measurement due to the use of a single element transducer for ultrasound image scanning. Therefore, previous system is not appropriate for being applied to clinical application. In the present study, B-mode ultrasound images of the wrist corresponding to movements of fingers from flexion to extension were acquired by clinical applicable real-time scanner. The kinetic trajectories of MN were off-line estimated utilizing two dimensional Baysian speckle tracking (TDBST) technique. The experiments were carried out from ten volunteers by ultrasound scanner at 12 MHz frequency. Results verified from phantom experiments have demonstrated that TDBST technique is able to detect the movement of MN based on signals of the past and present information and then to reduce the computational complications associated with the effect of such image quality as the resolution and contrast variations. Moreover, TDBST technique tended to be more accurate than that of the normalized cross correlation tracking (NCCT) technique used in previous study to detect movements of the MN in the wrist. In response to fingers’ flexion movement, the kinetic trajectory of the MN moved toward the ulnar-palmar direction, and then toward the radial-dorsal direction corresponding to the extensional movement. TDBST technique and the employed ultrasound image scanner have verified to be feasible to sensitively detect the kinetic trajectory and displacement of the MN. It thus could be further applied to diagnose CTS clinically and to improve the measurements to assess 3D trajectory of the MN.

Keywords: baysian speckle tracking, carpal tunnel syndrome, median nerve, motion tracking

Procedia PDF Downloads 474

Authors: George Hanna Abdelmelek Henien

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Quality and safety issues are common in Ethiopia's food processing industry, which can negatively impact consumers' health and livelihoods. The country is known for its various agricultural products that are important to the economy. However, food quality and safety policies and management practices in the food processing industry have led to many health problems, foodborne illnesses and economic losses. This article aims to show the causes and consequences of food safety and quality problems in the food processing industry in Ethiopia and discuss possible solutions to solve them. One of the main reasons for food quality and safety in Ethiopia's food processing industry is the lack of adequate regulation and enforcement mechanisms. Inadequate food safety and quality policies have led to inefficiencies in food production. Additionally, the failure to monitor and enforce existing regulations has created a good opportunity for unscrupulous companies to engage in harmful practices that endanger the lives of citizens. The impact on food quality and safety is significant due to loss of life, high medical costs, and loss of consumer confidence in the food processing industry. Foodborne diseases such as diarrhoea, typhoid and cholera are common in Ethiopia, and food quality and safety play an important role in . Additionally, food recalls due to contamination or contamination often cause significant economic losses in the food processing industry. To solve these problems, the Ethiopian government began taking measures to improve food quality and safety in the food processing industry. One of the most prominent initiatives is the Ethiopian Food and Drug Administration (EFDA), which was established in 2010 to monitor and control the quality and safety of food and beverage products in the country. EFDA has implemented many measures to improve food safety, such as carrying out routine inspections, monitoring the import of food products and implementing labeling requirements. Another solution that can improve food quality and safety in the food processing industry in Ethiopia is the implementation of food safety management system (FSMS). FSMS is a set of procedures and policies designed to identify, assess and control food safety risks during food processing. Implementing a FSMS can help companies in the food processing industry identify and address potential risks before they harm consumers. Additionally, implementing an FSMS can help companies comply with current safety and security regulations. Consequently, improving food safety policy and management system in Ethiopia's food processing industry is important to protect people's health and improve the country's economy. . Addressing the root causes of food quality and safety and implementing practical solutions that can help improve the overall food safety and quality in the country, such as establishing regulatory bodies and implementing food management systems.

Keywords: food quality, food safety, policy, management system, food processing industry food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

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Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: Manar Al-Ateeq

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The building construction industry plays a major role in the economy of the word and the state of Kuwait. This paper evaluates existing new civil site engineers, describes a new system for improvement and insures the importance of prequalifying and developing for new engineers. In order to have a strong base in engineering, educational institutes and workplaces should be responsible to continuously train engineers and update them with new methods and techniques in engineering. As to achieve that, school of engineering should constantly update computational resources to be used in the professions. A survey was prepared for graduated Engineers based on stated objectives to understand the status of graduate engineers in both the public and private sector. Interviews were made with different sectors in Kuwait, and several visits were made to different training centers within different workplaces in Kuwait to evaluate training process and try to improve it. Virtual Reality (VR) technology could be applied as a complement to three-dimensional (3D) modeling, leading to better communication whether in job training, in education or in professional practice. Techniques of 3D modeling and VR can be applied to develop the models related to the construction process. The 3D models can support rehabilitation design as it can be considered as a great tool for monitoring failure and defaults in structures; also it can support decisions based on the visual analyses of alternative solutions. Therefore, teaching computer-aided design (CAD) and VR techniques in school will help engineering students in order to prepare them to site work and also will assist them to consider these technologies as important supports in their later professional practice. This teaching technique will show how the construction works developed, allow the visual simulation of progression of each type of work and help them to know more about the necessary equipment needed for tasks and how it works on site.

Keywords: three dimensional modeling (3DM), civil engineers (CE), professional practice (PP), virtual reality (VR)

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Authors: Jirapan Khruesarn, Wimwipa Boonklin

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Background: Currently, Thailand has an aging population. In 2017, the elderly population was over 11.14 million. There will be an increase in the number of elderly people, 8.39 million, some people grumble to themselves and have conflicts with their offspring or those close to them. It is a source of stress. Mental health promotion should be given to the elderly in order to cope with these changes. Due to the family characteristics of Thai society, these family members will act as caregivers for the elderly. Therefore, a group-counseling program based on Personnel-Centered Theory for Elderly Caregivers in Mental Health Promotion for Older People in Na Kaeo Municipality, Kau Ka District, Lampang Province, has been developed to compare the elderly care behavior before and after the participation. Methods: This research was study for 20 elderly' caregiver: Those aimed to compare the before and after use of group program for caregiver to promoting for the elderly by the following methods: Step 1 Establish a framework for evaluating elderly care behaviors and develop a group counseling program for promote mental health for elderly on: 1) Body 2) Willpower 3) Social and community management and 4) Organizing learning process. Step 2 Assessing an Elderly Care Behaviors by using "The behavior assessment on caring for the elderly" and assessing the mental health power level of the elderly and follow the counseling program 9 times and compare of the elderly care behaviors before and after joined a group program, and compare of mental health level of caregiver attends a group program. Results: This study is developing a group counseling program to promoting for the resilience quotient in elderly people that the results of the study could be summarized as follows: 1) Before the elderly's caregivers join a group counseling program: Mental health promotion behaviors of the elderly were at the high level of (3.32), and after: were at the high level of (3.44). 2) Before the elderly's caregiver attends a group counseling program: the mental health level of the elderly the mean score was (47.85 percent), and the standard deviation was (0.21 percent) and after. The elderly had a higher score of (51.45 percent) In summary, after the elderly caregivers joined the group, the elderly are higher in all aspects promote mental health for elderly and the statistically significance at the 0.05, It shows that programs are fit for personal and community condition in promoting the mental health of the elderly because this theory has the idea that: Humans have the ability to use their intelligence to solve problems or make decisions effectively, And member of group counseling program have ventured and express grievances that the counselor is a facilitator who focuses on personal development by building relationships among people. In other words, the factors contributing to higher levels of elderly care behaviors is group counseling, that isn't a hypothetical process but focus on building relationships that are based on mutual trust and Unconditional acceptance.

Keywords: group counseling base on person-centered theory, elderly person, resilience quotient: RQ, caregiver

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Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

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Authors: Mateusz Frydrych

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The construction of diaphragm walls as excavation shoring as well as part of deep foundations is widely used in geotechnical engineering. Today's design challenges lie in the optimal dimensioning of the cross-section, which is demanded by technological considerations. Also in force is the issue of optimization and sustainable use of construction materials, including reduction of carbon footprint, which is currently a relevant challenge for the construction industry. The author presents the concept of an approach to achieving increased efficiency of diaphragm wall excavation shoring by using structural compression technology. The author proposes to implement prestressed tendons in a non-linear manner in the reinforcement cage. As a result bending moment is reduced, which translates into a reduction in the amount of steel needed in the section, a reduction in displacements, and a reduction in the scratching of the casing, including the achievement of better tightness. This task is rarely seen and has not yet been described in a scientific way in the literature. The author has developed a dynamic numerical model that allows the dimensioning of the cross-section of a prestressed shear wall, as well as the study of casing displacements and cross-sectional forces in any defined computational situation. Numerical software from the Sofistik - open source development environment - was used for the study, and models were validated in Plaxis software . This is an interesting idea that allows for optimizing the execution of construction works and reducing the required resources by using fewer materials and saving time. The author presents the possibilities of a prestressed diaphragm wall, among others, using. The example of a diaphragm wall working as a cantilever at the height of two underground floors without additional strutting or stability protection by using ground anchors. This makes the execution of the work more criminal for the contractor and, as a result, cheaper for the investor.

Keywords: prestressed diaphragm wall, Plaxis, Sofistik, innovation, FEM, optimisation

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Authors: Mihaja Razafimbelo, Guillaume Herve-Secourgeon, Fabrice Gatuingt, Marina Bottoni, Tulio Honorio-De-Faria

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The challenge of the research is to provide engineering with a robust, semi-automatic method for calculating optimal reinforcement for massive structural elements. In the absence of such a digital post-processing tool, design office engineers make intensive use of plate modelling, for which automatic post-processing is available. Plate models in massive areas, on the other hand, produce conservative results. In addition, the theoretical foundations of automatic post-processing tools for reinforcement are those of reinforced concrete beam sections. As long as there is no suitable alternative for automatic post-processing of plates, optimal modelling and a significant improvement of the constructability of massive areas cannot be expected. A method called strut-and-tie is commonly used in civil engineering, but the result itself remains very subjective to the calculation engineer. The tool developed will facilitate the work of supporting the engineers in their choice of structure. The method implemented consists of defining a ground-structure built on the basis of the main constraints resulting from an elastic analysis of the structure and then to start an optimization of this structure according to the fully stressed design method. The first results allow to obtain a coherent return in the first network of connecting struts and ties, compared to the cases encountered in the literature. The evolution of the tool will then make it possible to adapt the obtained latticework in relation to the cracking states resulting from the loads applied during the life of the structure, cyclic or dynamic loads. In addition, with the constructability constraint, a final result of reinforcement with an orthogonal arrangement with a regulated spacing will be implemented in the tool.

Keywords: strut and tie, optimization, reinforcement, massive structure

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

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Authors: Jamil Hijazi, Stirling Howieson

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Reducing energy consumption and CO₂ emissions are probably the greatest challenge now facing mankind. From considerations surrounding global warming and CO₂ production, it has to be recognized that oil is a finite resource and the KSA like many other oil-rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground-cooling pipes in combination with the black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing cooling load and carbon emissions while providing all year-round thermal comfort in a typical Saudi Arabian urban housing block. Soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (DesignBuilder) that utilized the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/stack ventilation and radiant cooling pipes embed in floor). Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.

Keywords: cooling load, energy efficiency, ground pipe cooling, hybrid cooling strategy, hydronic radiant systems, low carbon emission, passive designs, thermal comfort

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Jim Weese

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The Kinesiology, Exercise and Sport Science environment remain excellent venues for leadership research. Prescribed leadership (coaching), emergent leadership (players and organizations), and executive leadership are all popular themes in the research literature. Leadership remains a popular area of inquiry in the sport management domain as well as an interesting area for practitioners who wish to heighten their leadership practices and effectiveness. The need for effective leadership in these areas given competing demands for attention and resources may be at an all-time high. The presenter has extensive research and practical experience in the area and has developed his concept based on the latest leadership literature. He refers to this as the Five ’C’s of Leadership. These components, noted below, have been empirically validated and have served as the foundation for extensive consulting with academic, sport, and business leaders. Credibility (C1) is considered the foundation of leadership. There are two components to this area, namely: (a) leaders being respected for having the relevant knowledge, insights, and experience to be seen as credible sources of information, and (b) followers perceiving the leader as being a person of character, someone who is honest, reliable, consistent, and trustworthy. Compelling Vision (C2) refers to the leader’s ability to focus the attention of followers on a desired end goal. Effective leaders understand trends and developments in their industry. They also listen attentively to the needs and desires of their stakeholders and use their own instincts and experience to shape these ideas into an inspiring vision that is effectively and continuously communicated. Charismatic Communicator (C3) refers to the leader’s ability to formally and informally communicate with members. Leaders must deploy mechanisms and communication techniques to keep their members informed and engaged. Effective leaders sprinkle in ‘proof points’ that reinforce the vision’s relevance and/or the unit’s progress towards its attainment. Contagious Enthusiasm (C4) draws on the emotional intelligence literature as it relates to exciting and inspiring followers. Effective leaders demonstrate a level of care, commitment, and passion for their people and feelings of engagement permeate the group. These leaders genuinely care about the task at hand, and for the people working to make it a reality. Culture Builder (C5) is the capstone component of the model and is critical to long-term success and survival. Organizational culture refers to the dominant beliefs, values and attitudes of members of a group or organization. Some have suggested that developing and/or imbedding a desired culture for an organization is the most important responsibility for a leader. The author outlines his Five ‘C’s’ of Leadership concept and provide direct application to executive leadership in Kinesiology, Exercise and Sport Science.

Keywords: effectiveness, leadership, management, sport

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Authors: Alexander Kospach, Fabian Benezeder, Jürgen Abraham

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E-mobility poses new challenges for inverters (e.g., higher switching frequencies) in terms of thermal behavior and thermal management. Due to even higher switching frequencies, thermal losses become greater, and the cooling of critical components (like insulated gate bipolar transistor and diodes) comes into focus. New manufacturing methods, such as 3D printing, enable completely new pin-fin structures that can handle higher waste heat to meet the new thermal requirements. Based on the geometrical specifications of the industrial partner regarding the manufacturing possibilities for 3D printing, different and completely new pin-fin structures were numerically investigated for their hydraulic and thermal behavior in fundamental studies assuming an indirect liquid cooling. For the 3D computational fluid dynamics (CFD) thermal simulations OpenFOAM was used, which has as numerical method the finite volume method for solving the conjugate heat transfer problem. A steady-state solver for turbulent fluid flow and solid heat conduction with conjugate heat transfer between solid and fluid regions was used for the simulations. In total, up to fifty pinfin structures and arrangements, some of them completely new, were numerically investigated. On the basis of the results of the principal investigations, the best two pin-fin structures and arrangements for the complete module cooling of an automotive inverter were numerically investigated and compared. There are clear differences in the maximum temperatures for the critical components, such as IGTBs and diodes. In summary, it was shown that 3D pin fin structures can significantly contribute to the improvement of heat transfer and cooling of an automotive inverter. This enables in the future smaller cooling designs and a better lifetime of automotive inverter modules. The new pin fin structures and arrangements can also be applied to other cooling applications where 3D printing can be used.

Keywords: pin fin heat sink optimization, 3D printed pin fins, CFD simulation, power electronic cooling, thermal management

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Authors: B. Lefranc, C. Aufauvre-Poupon, C. Martin-Krumm, M. Trousselard

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Isolated and confined environments (ICE) present several challenges which may adversely affect human’s psychology and physiology. Submariners in Sub-Surface Ballistic Nuclear (SSBN) mission exposed to these environmental constraints must be able to perform complex tasks as part of their normal duties, as well as during crisis periods when emergency actions are required or imminent. The operational and environmental constraints they face contribute to challenge human adaptability. The impact of such a constrained environment has yet to be explored. Establishing a knowledge framework is a determining factor, particularly in view of the next long space travels. Ensuring that the crews are maintained in optimal operational conditions is a real challenge because the success of the mission depends on them. This study focused on the evaluation of the impact of stress on mental health and sensory degradation of submariners during a mission on SSBN using cardiac biosignal (heart rate variability, HRV) clustering. This is a pragmatic exploratory study of a prospective cohort included 19 submariner volunteers. HRV was recorded at baseline to classify by clustering the submariners according to their stress level based on parasympathetic (Pa) activity. Impacts of high Pa (HPa) versus low Pa (LPa) level at baseline were assessed on emotional state and sensory perception (interoception and exteroception) as a cardiac biosignal during the patrol and at a recovery time one month after. Whatever the time, no significant difference was found in mental health between groups. There are significant differences in the interoceptive, exteroceptive and physiological functioning during the patrol and at recovery time. To sum up, compared to the LPa group, the HPa maintains a higher level in psychosensory functioning during the patrol and at recovery but exhibits a decrease in Pa level. The HPa group has less adaptable HRV characteristics, less unpredictability and flexibility of cardiac biosignals while the LPa group increases them during the patrol and at recovery time. This dissociation between psychosensory and physiological adaptation suggests two treatment modalities for ICE environments. To our best knowledge, our results are the first to highlight the impact of physiological differences in the HRV profile on the adaptability of submariners. Further studies are needed to evaluate the negative emotional and cognitive effects of ICEs based on the cardiac profile. Artificial intelligence offers a promising future for maintaining high level of operational conditions. These future perspectives will not only allow submariners to be better prepared, but also to design feasible countermeasures that will help support analog environments that bring us closer to a trip to Mars.

Keywords: adaptation, exteroception, HRV, ICE, interoception, SSBN

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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Authors: Amir Sattari, Mac Panah, Naeim Rashidfarokhi

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To enhance the mixing of fluid in a rectangular enclosure with a circular inlet and outlet, an energy-efficient approach is further investigated through computational fluid dynamics (CFD). Particle image velocimetry (PIV) measurements help confirm that the pulsation of the inflow velocity improves the mixing performance inside the enclosure considerably without increasing energy consumption. In this study, multiple CFD simulations with different turbulent models were performed. The results obtained were compared with experimental PIV results. This study investigates small-scale representations of flow patterns in a ventilated rectangular room. The objective is to validate the concept of an energy-efficient ventilation strategy with improved thermal comfort and reduction of stagnant air inside the room. Experimental and simulated results confirm that through pulsation of the inflow velocity, strong secondary vortices are generated downstream of the entrance wall-jet. The pulsatile inflow profile promotes a periodic generation of vortices with stronger eddies despite a relatively low inlet velocity, which leads to a larger boundary layer with increased kinetic energy in the occupied zone. A real-scale study was not conducted; however, it can be concluded that a constant velocity inflow profile can be replaced with a lower pulsated flow rate profile while preserving the mixing efficiency. Among the turbulent CFD models demonstrated in this study, SST-kω is most advantageous, exhibiting a similar global airflow pattern as in the experiments. The detailed near-wall velocity profile is utilized to identify the wall-jet instabilities that consist of mixing and boundary layers. The SAS method was later applied to predict the turbulent parameters in the center of the domain. In both cases, the predictions are in good agreement with the measured results.

Keywords: CFD, PIV, pulsatile inflow, ventilation, wall-jet

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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