Search results for: multi layer perceptrons

Authors: Mikko Hänninen

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This paper explores the effect online retail platforms have on customer behavior and retail patronage through an inductive multi-case study. Existing research on retail platforms and ecosystems generally focus on competition between platform members and most papers maintain a managerial perspective with customers seen mainly as merely one stakeholder of the value-exchange relationship. It is proposed that retail platforms change the nature of customer relationships compared to traditional brick-and-mortar or e-commerce retailers. With online retail platforms such as Alibaba, Amazon and Rakuten gaining increasing traction with their platform based business models, the purpose of this paper is to define retail platforms and look at how leading retail platforms are able to create value for their customers, in order to foster meaningful customer’ relationships. An analysis is conducted on the major global retail platforms with a focus specifically on understanding the tools in place for creating customer value in order to show how retail platforms create and maintain customer relationships for fostering customer loyalty. The results describe the opportunities and challenges retailers face when competing against platform based businesses and outline the advantages as well as disadvantages that platforms bring to individual consumers. Based on the inductive case research approach, five theoretical propositions on consumer behavior in online retail platforms are developed that also form the basis of further research with this research making both a practical as well as theoretical contribution to platform research streams.

Keywords: retail, platform, ecosystem, e-commerce, loyalty

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Authors: Juhee Lee, Yongjun Lee

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In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: finite volume method, fluid flow, laminar flow, unstructured grid

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Authors: Kassaye Bewketu Zellelew

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The Main Ethiopian Rift Valley lakes suffer from water level fluctuations due to several natural and anthropocentric factors. Lakes located at terminal positions are highly affected by the fluctuations. These fluctuations are disturbing the stability of ecosystems, putting very serious impacts on the lives of many animals and plants around the lakes. Hence, studying the hydrodynamics of the lakes was found to be very essential. The main purpose of this study is to find the most significant factors that contribute to the water level fluctuations and also to quantify the fluctuations so as to identify lakes that need special attention. The research method included correlations, least squares regressions, multi-temporal satellite image analysis and land use change assessment. The results of the study revealed that much of the fluctuations, specially, in Central Ethiopian Rift are caused by human activities. Lakes Abiyata, Chamo, Ziway and Langano are declining while Abaya and Hawassa are rising. Among the studied lakes, Abiyata is drastically reduced in size (about 28% of its area in 1986) due to both human activities (most dominant ones) and natural factors. The other seriously affected lake is Chamo with about 11% reduction in its area between 1986 and 2010. Lake Abaya was found to be relatively stable during this period (showed only a 0.8% increase in its area). Concerned bodies should pay special attention to and take appropriate measures on lakes Abiyata, Chamo and Hawassa.

Keywords: correlations, hydrodynamics, lake level fluctuation, landsat satellite images

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Promil Mehra, Nanthi Bolan, Jack Desbiolles, Risha Gupta

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Agricultural practices affect the soil physical and chemical properties, which in turn influence the soil microorganisms as a function of the soil biological environment. On the return to conventional tillage (CT) from continuing no-till (NT) cropping system, a very little information is available from the impact caused by the intermittent tillage on the soil biochemical properties from a short-term (2-year) study period. Therefore, the contribution made by different microorganisms (fungal, bacteria) was also investigated in order to find out the effective changes in the soil microbial activity under a South Australian dryland faring system. This study was conducted to understand the impact of microbial dynamics on the soil organic carbon (SOC) under NT and CT systems when treated with different levels of mulching (0, 2.5 and 5 t/ha). Our results demonstrated that from the incubation experiment the cumulative CO2 emitted from CT system was 34.5% higher than NT system. Relatively, the respiration from surface layer (0-10 cm) was significantly (P<0.05) higher by 8.5% and 15.8 from CT; 8% and 18.9% from NT system w.r.t 10-20 and 20-30 cm respectively. Further, the dehydrogenase enzyme activity (DHA) and microbial biomass carbon (MBC) were both significantly lower (P<0.05) under CT, i.e., 7.4%, 7.2%, 6.0% (DHA) and 19.7%, 15.7%, 4% (MBC) across the different mulching levels (0, 2.5, 5 t/ha) respectively. In general, it was found that from both the tillage system the enzyme activity and MBC decreased with the increase in depth (0-10, 10-20 and 20-30 cm) and with the increase in mulching rate (0, 2.5 and 5 t/ha). From the perspective of microbial stress, there was 28.6% higher stress under CT system compared to NT system. Whereas, the microbial activity of different microorganisms like fungal and bacterial activities were determined by substrate-induced inhibition respiration using antibiotics like cycloheximide (16 mg/gm of soil) and streptomycin sulphate (14 mg/gm of soil), by trapping the CO2 using an alkali (0.5 M NaOH) solution. The microbial activities were confirmed through platting technique, where it was that found bacterial activities were 46.2% and 38.9% higher than fungal activity under CT and NT system. In conclusion, it was expected that changes in the relative abundance and activity of different microorganisms (bacteria and fungi) under different tillage systems could significantly affect the C cycling and storage due to its unique structures and differential interactions with the soil physical properties.

Keywords: tillage, soil respiration, MBC, fungal-bacterial activity

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Authors: Nunik Junara, Sugeng Triyadi

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Sustainable Housing in Islamic perspective, can be defined as a multi-dimensional process that seeks to achieve a balance between economic and socio-cultural aspects on the side, and environmental aspect on the other. There are many quotes verses in the Quran and Hadith that leads to the belief that Islam as a Rahmatan lil Alamin, where men are encouraged to act wisely in treating nature and all living things in it. One aspect of the natural environment that closed to human is plants. In the settlement, the availability of plants or also called green open space is highly recommended. The availability of green open space in the neighborhood, both the public and private green open spaces is expected to reduce the effects of global warming that has engulfed various parts of the world. Green open space that can be viewed from the angle of eco-aestetic and eco-medical in sustainable architecture, is expected to increase the temperature and provide aesthetic impression to the surrounding environment. This paper attempts to discuss the principles of Islamic values related to the natural environment as a major resource for sustainability. This paper also aims to raise awareness of the importance of the theme of sustainability in settlements, especially in big cities. Analysis of the availability of green open space in kampung Kauman Malang is one example of the effort to apply the principles of sustainable housing.

Keywords: green open space, sustainable housing, Islamic values, Kampung Kauman Malang

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Authors: M. Nazem Salimi, C. Abrinia, M. Baniassadi, M. Ehsani

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Mechanical properties of epoxy based nanocomposites containing copper coated MWCNTs were investigated and a comparative study between nanocomposites containing functionalized MWCNTs and copper coated MWCNTs which are already functionalized was conducted. The MWCNTs was deposited with copper nanoparticles through electroless deposition process after accomplishment of "two-step" method as sensitization and activation procedures on oxidized MWCNTs. In addition, functionalization of MWCNTs was carried out through combination of two covalent and non-covalent funcionalization methods using HNO3 for acid solution of covalent treatment and Triton X100 as non-ionic surfactant of non-covalent treatment. The presence of functional groups and removal of impurities of MWCNTs were confirmed by FTIR and Raman spectroscopy, respectively. The layer of copper nanoparticles on the MWCNTs wall increasing its diameter was observed by SEM. Utilizing solution blending process, 0.1%, 0.5% and 1.5% wt loading of both copper coated MWCNTs and non-coated MWCNTs were used to prepare epoxy-based nanocomposites. The tensile, flexural and impact properties of nanocomposites were investigated. The results of tensile test demonstrated that nanocomposites containing copper coated MWCNTs exhibited brittle behavior compared to those reinforced with functionalized MWCNTs, whereas former one exhibited higher values of modulus than latter one for concentrations more than 0.4% wt. Presence of copper particles on MWCNTs surface decreased the tensile strength of nanocomposites. In comparison to pure epoxy, nanocomposites with treated-MWCNTs and Cu-MWCNTs loading of 0.1% wt showed an increase of 35% and 51.6% for flexural strength beside 20% and 30% increase in flexural modulus, respectively, whereas flexural properties of both naocomposites decreased with increasing of CNTs concentration. The results of impact strength of nanocomposites with Cu-CNTs demonstrated that impact properties decreased with increasing of filler content with a optimum value at 0.1% wt while in high concentrations impact properties of Cu-nanocomposites exhibited lower values than f-MWCNT nanocomposites.

Keywords: epoxyresin, nanocomposite, functionalization, copper, electroless deposition process, mechanical properties

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Authors: Kelsi Hagerty, Ami Rosen, Aaliyah Heyward, Nadia Ali, Emily Brown, Erin Demo, Yue Guan, Modele Ogunniyi, Brianna McDaniels, Alanna Morris, Kunal Bhatt

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Hereditary transthyretin amyloidosis (hATTR) is a progressive, multi-systemic, and life-threatening disease caused by a disruption in the TTR protein that delivers thyroxine and retinol to the liver. This disruption causes the protein to misfold into amyloid fibrils, leading to the accumulation of the amyloid fibrils in the heart, nerves, and GI tract. Over 130 variants in the TTR gene are known to cause hATTR. The Val122Ile variant is the most common in the United States and is seen almost exclusively in people of African descent. TTR variants are inherited in an autosomal dominant fashion and have incomplete penetrance and variable expressivity. Individuals with hATTR may exhibit symptoms from as early as 30 years to as late as 80 years of age. hATTR is characterized by a wide range of clinical symptoms such as cardiomyopathy, neuropathy, carpal tunnel syndrome, and GI complications. Without treatment, hATTR leads to progressive disease and can ultimately lead to heart failure. hATTR disproportionately affects individuals of African descent; the estimated prevalence of hATTR among Black individuals in the US is 3.4%. Unfortunately, hATTR is often underdiagnosed and misdiagnosed because many symptoms of the disease overlap with other cardiac conditions. Due to the progressive nature of the disease, multi-systemic manifestations that can lead to a shortened lifespan, and the availability of free genetic testing and promising FDA-approved therapies that enhance treatability, early identification of individuals with a pathogenic hATTR variant is important, as this can significantly impact medical management for patients and their relatives. Furthermore, recent literature suggests that TTR genetic testing should be performed in all patients with suspicion of TTR-related cardiomyopathy, regardless of age, and that follow-up with genetic counseling services is recommended. Relatives of patients with hATTR benefit from genetic testing because testing can identify carriers early and allow relatives to receive regular screening and management. Despite the striking prevalence of hATTR among Black individuals, hATTR remains underdiagnosed in this patient population, and germline genetic testing for hATTR in Black individuals seems to be underrepresented, though the reasons for this have not yet been brought to light. Historically, Black patients experience a number of barriers to seeking healthcare that has been hypothesized to perpetuate the underdiagnosis of hATTR, such as lack of access and mistrust of healthcare professionals. Prior research has described a myriad of factors that shape an individual’s decision about whether to pursue presymptomatic genetic testing for a familial pathogenic variant, such as family closeness and communication, family dynamics, and a desire to inform other family members about potential health risks. This study explores these factors through 10 in-depth interviews with patients with hATTR about what factors may be contributing to the underdiagnosis of hATTR in the Black population. Participants were selected from the Emory University Amyloidosis clinic based on having a molecular diagnosis of hATTR. Interviews were recorded and transcribed verbatim, then coded using MAXQDA software. Thematic analysis was completed to draw commonalities between participants. Upon preliminary analysis, several themes have emerged. Barriers identified include i) Misdiagnosis and a prolonged diagnostic odyssey, ii) Family communication and dynamics surrounding health issues, iii) Perceptions of healthcare and one’s own health risks, and iv) The need for more intimate provider-patient relationships and communication. Overall, this study gleaned valuable insight from members of the Black community about possible factors contributing to the underdiagnosis of hATTR, as well as potential solutions to go about resolving this issue.

Keywords: cardiac amyloidosis, heart failure, TTR, genetic testing

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Authors: M. G. Murtaza, E. E. Tzirtzilakis, M. Ferdows

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Biomagnetic fluid dynamics is an interdisciplinary field comprising engineering, medicine, and biology. Bio fluid dynamics is directed towards finding and developing the solutions to some of the human body related diseases and disorders. This article describes the flow and heat transfer of two dimensional, steady, laminar, viscous and incompressible biomagnetic fluid over a non-linear stretching sheet in the presence of magnetic dipole. Our model is consistent with blood fluid namely biomagnetic fluid dynamics (BFD). This model based on the principles of ferrohydrodynamic (FHD). The temperature at the stretching surface is assumed to follow a power law variation, and stretching velocity is assumed to have a nonlinear form with signum function or sign function. The governing boundary layer equations with boundary conditions are simplified to couple higher order equations using usual transformations. Numerical solutions for the governing momentum and energy equations are obtained by efficient numerical techniques based on the common finite difference method with central differencing, on a tridiagonal matrix manipulation and on an iterative procedure. Computations are performed for a wide range of the governing parameters such as magnetic field parameter, power law exponent temperature parameter, and other involved parameters and the effect of these parameters on the velocity and temperature field is presented. It is observed that for different values of the magnetic parameter, the velocity distribution decreases while temperature distribution increases. Besides, the finite difference solutions results for skin-friction coefficient and rate of heat transfer are discussed. This study will have an important bearing on a high targeting efficiency, a high magnetic field is required in the targeted body compartment.

Keywords: biomagnetic fluid, FHD, MHD, nonlinear stretching sheet

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Authors: Siu-Siu Guo, Qingxuan Shi

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In this paper, single-degree-of-freedom (SDOF) systems to white noise and colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis.

Keywords: filtered noise, narrow-banded noise, nonlinear dynamic, random vibration

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Authors: Jiahui Song

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The use of electric fields with high intensity (~ 100kV/cm or higher) and ultra short pulse durations (nanosecond range) has been a recent development. Most of the studies of electroporation have ignored possible thermal effects because of the small duration of the applied voltage pulses. However, it has been predicted membrane temperature gradients ranging from 0.2×109 to 109 K/m. This research focuses on thermal effects that drive for electroporative enhancements, even though the actual temperature values might not have changed appreciably from their equilibrium levels. The dynamics of pore formation with the application of an externally applied electric field is studied on the basis of molecular dynamics (MD) simulations using the GROMACS package. MD simulations of a lipid layer with constant electric field strength of 0.5 V/nm at 25 °C and 47 °C are implemented to simulate the appropriate thermal effects. The GROMACS provides the force fields for the lipid membranes, which is taken to comprise of dipalmitoyl-phosphatidyl-choline (DPPC) molecules. The water model mimicks the aqueous environment surrounding the membrane. Velocities of water and membrane molecules are generated randomly at each simulation run according to a Maxwellian distribution. The high background electric field is typically used in MD simulations to probe electroporation. It serves as an accelerated test of the pore formation process since low electric fields would take inordinately long simulation time. MD simulation shows no pore is formed in a 1-ns snapshot for a DPPC membrane set at a temperature of 25°C after a 0.5 V/nm electric field is applied. A nano-sized pore is clearly seen in a 0.75-ns snapshot on the same geometry, but with the membrane surfaces kept at temperatures of 47°C. And the pore increases at 1 ns. The MD simulation results suggest the possibility that the increase in temperature can result in different degrees of electrically stimulated bio-effects. The results points to the role of thermal effects in facilitating and accelerating the electroporation process.

Keywords: high-intensity, ultra-short, electroporation, thermal effects, molecular dynamics

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Authors: W. T. A. Mohammed, M. Eltaeb, R. Kashani

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The first bending modes of tall asymmetric structures in the two lateral X and Y-directions have two different natural frequencies. To add tuned damping to these bending modes, one needs to either a) use two pendulum-tuned mass dampers (PTMDs) with one tuning frequency, each PTMD targeting one of the bending modes, or b) use one PTMD with two tuning frequencies (one in each lateral directions). Option (a), being more massive, requiring more space, and being more expensive, is less attractive than option (b). Considering that the tuning frequency of a pendulum depends mainly on the pendulum length, one way of realizing option (b) is by constraining the swinging length of the pendulum in one direction but not in the other; such PTMD is dubbed passive Bi-PTMD. Alternatively, option (b) can be realized by actively setting the tuning frequencies of the PTMD in the two directions. In this work, accurate physical models of passive Bi-PTMD and active PTMD are developed and incorporated into the numerical model of a tall asymmetric structure. The model of PTMDs plus structure is used for a)synthesizing such PTMDs for particular applications and b)evaluating their damping effectiveness in mitigating the dynamic lateral responses of their target asymmetric structures, perturbed by wind load in X and Y-directions. Depending on how elaborate the control scheme is, the active PTMD can either be made to yield the same damping effectiveness as the passive Bi-PTMD of the same size or the passive Bi-TMD twice as massive as the active PTMD.

Keywords: active tuned mass damper, high-rise building, multi-frequency tuning, vibration control

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Authors: Bassim Shaheen Bachy, Jörg Franke

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In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multi-functional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: laser structuring, simulation, finite element analysis, thermal modeling

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Authors: Hassen Hamouda, Mohamed Ouwais Kabaou, Med Salim Bouhlel

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The growth of wireless technology made opportunistic scheduling a widespread theme in recent research. Providing high system throughput without reducing fairness allocation is becoming a very challenging task. A suitable policy for resource allocation among users is of crucial importance. This study focuses on scheduling multiple streaming flows on the downlink of a WiMAX system based on orthogonal frequency division multiple access (OFDMA). In this paper, we take the first step in formulating and analyzing this problem scrupulously. As a result, we proposed a new scheduling scheme based on Round Robin (RR) Algorithm. Because of its non-opportunistic process, RR does not take in account radio conditions and consequently it affect both system throughput and multi-users diversity. Our contribution called MORRA (Modified Round Robin Opportunistic Algorithm) consists to propose a solution to this issue. MORRA not only exploits the concept of opportunistic scheduler but also takes into account other parameters in the allocation process. The first parameter is called courtesy coefficient (CC) and the second is called Buffer Occupancy (BO). Performance evaluation shows that this well-balanced scheme outperforms both RR and MaxSNR schedulers and demonstrate that choosing between system throughput and fairness is not required.

Keywords: OFDMA, opportunistic scheduling, fairness hierarchy, courtesy coefficient, buffer occupancy

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Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Mattea Carmen Castrovilli, Antonella Cartoni

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Electrospray ionisation (ESI), a well-established technique widely used to produce ion beams of biomolecules in mass spectrometry (ESI-MS), can be used for ambient soft landing of enzymes on a specific substrate. In this work, we show how the ambient electrospray deposition (ESD) technique can be successfully exploited for manufacturing a promising, green-friendly electrochemical amperometric laccase-based biosensor with unprecedented reuse and storage performance. These biosensors have been manufactured by spraying a laccase solution of 2μg/μL at 20% of methanol on a commercial carbon screen printed electrode (C-SPE) using a custom ESD set-up. The laccase-based ESD biosensor has been tested against catechol compounds in the linear range 2-100 μM, with a limit of detection of 1.7 μM, without interference from cadmium, chrome, arsenic, and zinc and without any memory effects, but showing a matrix effect in lake and well water. The ESD biosensor shows enhanced performances compared to the ones fabricated with other immobilization methods, like drop-casting. Indeed, it retains 100% activity up to two months of storage at ambient conditions without any special care and working stability up to 63 measurements on the same electrode just prepared and 20 on a one-year-old electrode subjected to redeposition together with a 100% resistance to use of the same electrode in subsequent days. The ESD method is a one-step, environmentally friendly method that allows the deposition of the bio-recognition layer without using any additional chemicals. The promising results in terms of storage and working stability also obtained with the more fragile lactate oxidase enzyme suggest these improvements should be attributed to the ESD technique rather than to the bioreceptor, highlighting how the ESD could be useful in reducing pollution from disposable devices. Acknowledgment: The understanding at the molecular level of this promising biosensor by using different spectroscopies, microscopies and analytical techniques is the subject of our PRIN 2022 project ESILARANTE.

Keywords: reuse, storage performance, immobilization, electrospray deposition, biosensor, laccase, catechol detection, green chemistry

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Authors: S. Mohajeri

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Electrocodeposition of Ni-TiO2 nanocomposite single layers and Ni-TiO2/TiO2 multilayers from Watts bath containing TiO2 sol was carried out on copper substrate. Pulse plating and pulse reverse plating techniques were applied to facilitate higher incorporations of TiO2 nanoparticles in Ni-TiO2 nanocomposite single layers, and the results revealed that by prolongation of the current-off durations and the anodic cycles, deposits containing 11.58 wt.% and 13.16 wt.% TiO2 were produced, respectively. Multilayer coatings which consisted of Ni-TiO2 and TiO2-rich layers were deposited by pulse potential deposition through limiting the nickel deposition by diffusion control mechanism. The TiO2-rich layers thickness and accordingly, the content of TiO2 reinforcement reached 104 nm and 18.47 wt.%, respectively in the optimum condition. The phase structure and surface morphology of the nanocomposite coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The cross sectional morphology and line scans of the layers were studied by field emission scanning electron microscopy (FESEM). It was confirmed that the preferred orientations and the crystallite sizes of nickel matrix were influenced by the deposition technique parameters, and higher contents of codeposited TiO2 nanoparticles refined the microstructure. The corrosion behavior of the coatings in 1M NaCl and 0.5M H2SO4 electrolytes were compared by means of potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. Increase of corrosion resistance and the passivation tendency were favored by TiO2 incorporation, while the degree of passivation declined as embedded particles disturbed the continuity of passive layer. The role of TiO2 incorporation on the improvement of mechanical properties including hardness, elasticity, scratch resistance and friction coefficient was investigated by the means of atomic force microscopy (AFM). Hydrophilicity and wettability of the composite coatings were investigated under UV illumination, and the water contact angle of the multilayer was reduced to 7.23° after 1 hour of UV irradiation.

Keywords: electrodeposition, hydrophilicity, multilayer, pulse-plating

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Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

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Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

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Authors: Rueyhung Weng, Chia-En Huang, Jung-Chi-Liao

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The transition zone (TZ) serves as a diffusion barrier to regulate the ins and outs of the proteins recruited to the primary cilia. TCTN2 is one of the TZ proteins and its mutation causes Joubert syndrome, a serious multi-organ disease. Despite its important medical relevance, the functions of TCTN2 remain elusive. Here we created a TCTN2 gene deleted retinal pigment epithelial cells (RPE1) using CRISPR/Cas9-based genome editing technique and used this knockout line to reveal roles of TCTN2. TCTN2 knockout RPE1 cells displayed a significantly reduced ciliogenesis or a shortened primary cilium length in the cilium-remaining population. Intraflagellar transport protein IFT88 aberrantly accumulated at the tip of TCTN2 deficient cells. Guanine nucleotide exchange factor Arl13B was mostly absent from the ciliary compartment, with a small population localizing at the ciliary tip. The deficient TZ was corroborated with the mislocalization of two other TZ proteins TMEM67 and MKS1. In addition, TCTN2 deficiency induced TZ impairment led to the suppression of Sonic hedgehog signaling in response to Smoothened (Smo) agonist. Together, depletion of TCTN2 destabilizes other TZ proteins and considerably alters the localization of key transport and signaling-associated proteins, including IFT88, Arl13B, and Smo.

Keywords: CRISPR/Cas9, primary cilia, Sonic hedgehog signaling, transition zone

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Authors: Gia Sirbiladze

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Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

Procedia PDF Downloads 126

Authors: Sara Mosallanejad, Bogdan Z. Dlugogorski, Jeff Gore, Mohammednoor Altarawneh

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Ammonium nitrate (NH­₄NO₃, AN) is commonly used as the main component of AN emulsion and fuel oil (ANFO) explosives, that use extensively in civilian and mining operations for underground development and tunneling applications. The emulsion formulation and wettability of AN prills, which affect the physical stability and detonation of ANFO, highly depend on the surface tension, density, viscosity of the used liquid. Therefore, for engineering applications of this material, the determination of density and surface tension of concentrated aqueous solutions of AN is essential. The molecular dynamics (MD) simulation method have been used to investigate the density and the surface tension of high concentrated ammonium nitrate solutions; up to its solubility limit in water. Non-polarisable models for water and ions have carried out the simulations, and the electronic continuum correction model (ECC) uses a scaling of the charges of the ions to apply the polarisation implicitly into the non-polarisable model. The results of calculated density and the surface tension of the solutions have been compared to available experimental values. Our MD simulations show that the non-polarisable model with full-charge ions overestimates the experimental results while the reduce-charge model for the ions fits very well with the experimental data. Ions in the solutions show repulsion from the interface using the non-polarisable force fields. However, when charges of the ions in the original model are scaled in line with the scaling factor of the ECC model, the ions create a double ionic layer near the interface by the migration of anions toward the interface while cations stay in the bulk of the solutions. Similar ions orientations near the interface were observed when polarisable models were used in simulations. In conclusion, applying the ECC model to the non-polarisable force field yields the density and surface tension of the AN solutions with high accuracy in comparison to the experimental measurements.

Keywords: ammonium nitrate, electronic continuum correction, non-polarisable force field, surface tension

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

Procedia PDF Downloads 323

Authors: Kasi Jockeil-Ojike

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The study of signage and wayfinding design guidelines is to provide consistent, coherent, and comprehensive guidelines for all type of signage design that may be applied to guide persons from the freeway into campus, and to specific building. As the world becomes more complex and the population increases, people increasingly rely on signage and wayfinding systems to navigate their way in built environment such as university campus. This paper will demonstrate and discuss signage and wayfinding, and the importance of visual literacy in university campuses. It discusses the process of wayfinding and signage, how poor signage and wayfinding systems affect people when navigating, and why wayfinding is more than just signage. Hence, this paper tries to examine the design guideline that primarily addresses the signage and wayfinding system that improves visual literacy within University of Port Harcourt multi-campuses. In doing this, the paper explore the environmental graphic design senori-emotional values and communicative information theories that takes the subjectivity of the observer in account. By making these connections, the paper will also determine what University of Port Harcourt need to focus on to be counted in the global trends, using developed visual communication guidelines based on previous studies or concept from professional. In conclusion, information about why physical structures (buildings and waypaths) on University of Port Harcourt multiple campuses need to be branded in self-communicative manner using signage and wayfinding design as integral part of its physical planning policy is recommended.

Keywords: campus-signage, movement, visual-literacy, wayfinding-guidelines

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Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek

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Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.

Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.

Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors

Procedia PDF Downloads 389

Authors: Sheng Huang, Xin Zhao, Xiaofeng Gao, Tao Zhou, Shijin Dai, Youcai Zhao

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Adsorption of heavy metal pollutants (Zn, Cd, Pb, Cr, Cu) and organic pesticide (phorate, dithiophosphate diethyl, triethyl phosphorothioate), along with their multi-contamination on the surface of industrial construction & demolition waste (C&D waste) was investigated. Brick powder was selected as the appropriate waste while its maximum equilibrium adsorption amount of heavy metal under single controlled contamination matrix reached 5.41, 0.81, 0.45, 1.13 and 0.97 mg/g, respectively. Effects of pH and spiking dose of ICDW was also investigated. Equilibrium adsorption amount of organic pesticide varied from 0.02 to 0.97 mg/g, which was negatively correlated to the size distribution and hydrophilism. Existence of organic pesticide on surface of ICDW caused various effects on the heavy metal adsorption, mainly due to combination of metal ions and the floccule formation along with wrapping behaviors by pesticide pollutants. Adsorption of Zn was sharply decreased from 7.1 to 0.15 mg/g compared with clean ICDW and phorate contaminated ICDW, while that of Pb, Cr and Cd experienced an increase- then decrease procedure. On the other hand, runoff of pesticide contaminants was investigated under 25 mm/h simulated rainfall. Results showed that the cumulative runoff amount fitted well with curve obtained from a power function, of which r2=0.95 and 0.91 for 1DAA (1 day between contamination and runoff) and 7DAA, respectively. This study helps provide evaluation of industrial construction and demolition waste contamination into aquatic systems.

Keywords: adsorption mechanism, industrial construction waste, metals, pesticide, runoff

Procedia PDF Downloads 459

Authors: Azadeh Yaraghchi, Reza Bagherian Sararoodi, Niknaz Salehi Moghadam, Mohammad Hossein Mandegar, Adis Kraskian Mujembari, Omid Rezaei

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Background: Quality of life is one of the most important consequences of disease in psychosomatic disorders. Many psychological factors are considered in predicting quality of life in patients with coronary artery bypass graft (CABG). The present study was aimed to determine the relationship between perceived social support and quality of life in patients with coronary artery bypass graft (CABG). Methods: The population included 82 patients who had undergone CABG from October 2014 to May 2015 in four different hospitals in Tehran. The patients were evaluated with Multi-dimension scale of perceived social support (MSPSS) and after three months follow up were evaluated by Short-Form quality of life questionnaire (SF-36). The obtained data were analyzed through Pearson correlation test and multiple variable regression models. Findings: A relationship between perceived social support and quality of life in patients with CABG was observed (r=0.374, p<0.01). The results showed that 22.4% of variation in quality of life is predicted by perceived social support components (p<0.01, R2 =0.224). Conclusion: Based on the results, perceived social support is one of the predictors of quality of life in patients with coronary artery bypass graft. Accordingly, these results can be useful in conceiving proactive policies, detecting high risk patients and planning for psychological interventions.

Keywords: coronary artery bypass graft, perceived social support, psychological factors, quality of life

Procedia PDF Downloads 363

Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

Procedia PDF Downloads 181