Search results for: least square support vector machine

Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

Procedia PDF Downloads 499

Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

Procedia PDF Downloads 142

Authors: Md. Shah Alam

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Mushfiq Ahmad has defined a Mixed Number, which is the sum of a scalar and a Cartesian vector. He has also defined the elementary group operations of Mixed numbers i.e. the norm of Mixed numbers, the product of two Mixed numbers, the identity element and the inverse. It has been observed that Mixed Number is consistent with Pauli matrix algebra and a handy tool to work with Dirac electron theory. Its use as a mathematical method in Physics has been studied. (1) We have applied Mixed number in Quantum Mechanics: Mixed Number version of Displacement operator, Vector differential operator, and Angular momentum operator has been developed. Mixed Number method has also been applied to Klein-Gordon equation. (2) We have applied Mixed number in Electrodynamics: Mixed Number version of Maxwell’s equation, the Electric and Magnetic field quantities and Lorentz Force has been found. (3) An associative transformation of Mixed Number numbers fulfilling Lorentz invariance requirement is developed. (4) We have applied Mixed number algebra as an extension of Complex number. Mixed numbers and the Quaternions have isomorphic correspondence, but they are different in algebraic details. The multiplication of unit Mixed number and the multiplication of unit Quaternions are different. Since Mixed Number has properties similar to those of Pauli matrix algebra, Mixed Number algebra is a more convenient tool to deal with Dirac equation.

Keywords: mixed number, special relativity, quantum mechanics, electrodynamics, pauli matrix

Procedia PDF Downloads 364

Authors: Mehtap Öztürk, Adem Öğüt, Emine Öğüt

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Leader member exchange is considered as relationship-based approach to leadership. The focal point of this theory is that effective leadership processes occur when leaders and followers are able to develop mature leadership relationships and thus gain access to a variety of benefits these relationships bring. In this context, it can be claimed that the quality of leader member exchange appears to have a strong affect on perceived organizational support and reduce turnover intention. The purpose of this study is to determine the relationship between the levels of leader member exchange, perceived organizational support and turnover intention on the employees of a health institution operating in the province of Konya. A field study based on survey method on 134 physicians who are employees of a health institution operating in the mentioned sample. In accordance with this purpose, it has been observed that there is a negative and statistically significant relationship between leader member exchange and turnover intention. Furthermore, it has been also realized that there is a negative and statistically significant relationship between perceived organizational support and turnover intention.

Keywords: leader member exchange, perceived organizational support, social exchange theory, turnover intention

Procedia PDF Downloads 357

Authors: Elif Aykin Dincer, Mustafa Erbas

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The vacuum drying behavior of beef slices (10 x 4 x 0.2 cm3) was experimentally investigated at the temperature of 60, 70, and 80°C under 25 mbar ultimate vacuum pressure and the mathematical models (Lewis, Page, Midilli, Two-term, Wangh and Singh and Modified Henderson and Pabis) were used to fit the vacuum drying of beef slices. The increase in drying air temperature resulted in a decrease in drying time. It took approximately 206, 180 and 157 min to dry beef slices from an initial moisture content to a final moisture content of 0.05 kg water/kg dry matter at 60, 70 and 80 °C of vacuum drying, respectively. It is also observed that the drying rate increased with increasing drying temperature. The coefficients (R2), the reduced chi-square (x²) and root mean square error (RMSE) values were obtained by application of six models to the experimental drying data. The best model with the highest R2 and, the lowest x² and RMSE values was selected to describe the drying characteristics of beef slices. The Page model has shown a better fit to the experimental drying data as compared to other models. In addition, the effective moisture diffusivities of beef slices in the vacuum drying at 60 - 80 °C varied in the range of 1.05 – 1.09 x 10-10 m2/s. Consequently, this results can be used to simulate vacuum drying process of beef slices and improve efficiency of the drying process.

Keywords: beef slice, drying models, effective diffusivity, vacuum

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Authors: Hiroaki Sumi, Kiichiro Hayashi

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Now, the use of renewable energy power generation has been advanced. In this paper, we compared the expansion support policy of photovoltaic power generation which was researched using The internet and the amount of resource for photovoltaic power generation which was estimated using the NEDO formula in the municipality level in Hokkaido and Aichi Prefecture, Japan. This paper will contribute to grasp the current situation especially about the policy. As a result, there were municipalities which seemed to be no consideration of the amount of resources. We think it would need to consider the suitability between the policies and resources.

Keywords: photovoltaic power generation, dissemination and support policy, amount of resources, Japan

Procedia PDF Downloads 565

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

Procedia PDF Downloads 184

Authors: Hojjat Mohammadi, Randall Divito, Gary J. E. Kramer

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Tunnelling and pipe jacking in very soft soils (fat clays), even with an Earth Pressure Balance tunnel boring machine (EPBM), can cause large ground displacements. In this study, the short-term and long-term ground and tunnel response is predicted for twin, pipe-jacked EPBM 3 meter diameter tunnels with a narrow pillar width. Initial modelling indicated complete closure of the annulus gap at the tail shield onto the centrifugally cast, glass-fiber-reinforced, polymer mortar jacking pipe (FRP). Numerical modelling was employed to simulate the excavation and support installation sequence, examine the ground response during excavation, confirm the adequacy of the pillar width and check the structural adequacy of the installed pipe. In the numerical models, Mohr-Coulomb constitutive model with the effect of unloading was adopted for the fat clays, while for the bedrock layer, the generalized Hoek-Brown was employed. The numerical models considered explicit excavation sequences and different levels of ground convergence prior to support installation. The well-studied excavation sequences made the analysis possible for this study on a very soft clay, otherwise, obtaining the convergency in the numerical analysis would be impossible. The predicted results indicate that the ground displacements around the tunnel and its effect on the pipe would be acceptable despite predictions of large zones of plastic behaviour around the tunnels and within the entire pillar between them due to excavation-induced ground movements.

Keywords: finite element modeling (FEM), pipe-jacked tunneling, very soft clay, EPBM

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Authors: Cristina Hotoleanu

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Introduction: The recent Covid-19 pandemic accelerated the development of e-health, including telemedicine, smartphone applications, and medical wearable devices. Providing remote teleconsultations supposes challenges which may require further face-to-face medical interactions. The aim of this study was to assess the correlation between the types of teleconsultations and the need of onsite medical services (investigations and medical visits) for the diagnosis and treatment. Methods: a retrospective study including all the teleconsultations using the platform offered by a telehealth provider in Romania (Telios Care SA) between May 1, 2021- April 30, 2022, was performed. Binary data were analysed using the chi-square test with a significance level of p < 0.05. Results: out of 7163 consultations, 3961 were phone calls, 1981 were online messages, and 1221 were video calls. Onsite medical services were indicated in 3327 (46.44%) cases; the onsite investigations or the onsite visits were recommended for 2908 patients as follows: 2326 in case of phone calls, 582 in case of online messages, none in case of video calls. Both onsite investigations and visits were indicated for 419 patients. The need for onsite additional medical services was significantly higher in the case of phone calls than in the other 2 types of teleconsultations (Chi square= 1207.06, p= 0.00001). The indication for onsite services was done mainly after teleconsultations covering medical specialties (87.34%), significantly higher than the other specialties (Chi square=914.59, p=0.00001). Teleconsultations in surgical specialties and other fields (pharmacy, dentistry, psychology, wellbeing- nutrition, fitness) resulted in 12.13%, respective less than 1%, indication for onsite investigations or visits, explained by using of video calls in most of the cases. Conclusion: a further onsite medical service was necessary in less than a half of the teleconsultations. This indication was done mainly after phone calls and teleconsultations in medical specialties. Video calls were used mostly in psychology, nutrition, and fitness teleconsultations and did not require a further onsite medical service. Other studies are necessary to assess better the types of teleconsultations and the specialties bringing the biggest benefit for the patients.

Keywords: onsite medical services, phone calls, teleconsultations, telemedicine

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Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

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In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

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Authors: Mahvish Anwaar

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Research Question: In this paper, we explore the causal relationship between banking competition, banking stability, and economic growth. Research Findings: The unbalanced panel data starting from 2000 to 2018 is collected to analyze the causality among banking competition, banking stability, and economic growth. The main focus of the study is to check the direction of causality among selected variables. The results of the study support the demand following, supply leading, feedback, and neutrality hypothesis conditional to different measures of banking competition, banking stability, and economic growth. Theoretical Implication: Jayakumar, Pradhan, Dash, Maradana, and Gaurav (2018) proposed a theoretical model of the causal relationship between banking competition, banking stability, and economic growth by using different indicators. So, we empirically test the proposed indicators in our study. This study makes a contribution to the literature by showing the defined relationship between developing and developed countries. Policy Implications: The study covers various policy implications regarding investors to analyze how to properly manage their finances, and government agencies will take help from the present study to find the best and most suitable policies by examining how the economy can grow concerning its finances.

Keywords: competition, stability, economic growth, vector auto-regression, granger causality

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Authors: J. Ikome, M. Ndeley

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When a machine breakdown forces a Modified Flow Shop (MFS) out of the prescribed state, the proposed strategy reschedules part of the initial schedule to match up with the preschedule at some point. The objective is to create a new schedule that is consistent with the other production planning decisions like material flow, tooling and purchasing by utilizing the time critical decision making concept. We propose a new rescheduling strategy and a match-up point determination procedure through a feedback mechanism to increase both the schedule quality and stability. The proposed approach is compared with alternative reactive scheduling methods under different experimental settings.

Keywords: advanced critical task methods modified flow shop (MFS), Manufacturing, experiment, determination

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Authors: Mona Hoyng

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In times of digitalization nowadays, the use of games became a crucial new way for digital game-based learning (DGBL) in higher education. In this regard, the development of a gameful experience (GE) among students is decisive when examining DGBL as the GE is a necessary precondition determining the effectiveness of games. In this regard, the purpose of this study is to provide deeper insights into the GE and to empirically investigate whether and how these meaningful learning experiences within games, i.e., GE, among students are created. Based on the theory of experience and flow theory, a double-mediation model was developed considering instructional support, group engagement, and flow as determinants of students’ GE. Based on data of 337 students taking part in a business simulation game at two different universities in Germany, regression-based statistical mediation analysis revealed that instructional support promoted students’ GE. This relationship was further sequentially double mediated by group engagement and flow. Consequently, in the context of DGBL, meaningful learning experiences within games in terms of GE are created and promoted through appropriate instructional support, as well as high levels of group engagement and flow among students.

Keywords: gameful experience, instructional support, group engagement, flow, education, learning

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Jiying Han

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Teaching is widely known to be an emotional endeavor, and teachers’ ability to regulate their emotions is important for their well-being and the effectiveness of their classroom management. Considering that teachers’ emotion regulation is an underexplored issue in the field of educational research, some studies have attempted to explore the role of emotion regulation in teachers’ work and to explore the links between teachers’ emotion regulation, job characteristics, and well-being, based on the Job Demands-Resources (JD-R) model. However, those studies targeted primary or secondary teachers. So far, very little is known about the relationships between university teachers’ emotion regulation and its antecedents and effects on teacher well-being. Based on the job demands-resources model and emotion regulation theory, this study examined the relationships between job characteristics of university teaching (i.e., emotional job demands and teaching support), emotion regulation strategies (i.e., reappraisal and suppression), and university teachers’ well-being. Data collected from a questionnaire survey of 643 university teachers in China were analysed. The results indicated that (1) both emotional job demands and teaching support had desirable effects on university teachers’ well-being; (2) both emotional job demands and teaching support facilitated university teachers’ use of reappraisal strategies; and (3) reappraisal was beneficial to university teachers’ well-being, whereas suppression was harmful. These findings support the applicability of the job demands-resources model to the contexts of higher education and highlight the mediating role of emotion regulation.

Keywords: emotional job demands, teaching support, emotion regulation strategies, the job demands-resources model

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

Procedia PDF Downloads 179

Authors: Sandra Maria Cerqueira Da Silva

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In Brazil, women are the majority of the country's population. They have advanced in terms of years of education and professional training. However, this has not prevented the differences in the labor market from being sustained, particularly the wage gap and inequalities concerning the access to command positions and promotions, i.e., in the gender relations and treatment. One of the conditions which constitute a barrier to career advancement is the necessary support chain to support women when they are in the labor market. Therefore, the purpose of this research is to demonstrate, describe, and criticize some of the current conformations of support chains and how these compete to promote the phenomenon known as glass ceiling in the country. However, this support may come even from inside a woman's own home, with a fairer division of household activities between men and women. Such behavior can free an entire network of women within the same family. In addition, it can serve as pressure to structure better conditions for women as a whole, improving the living conditions of the poor population. This can occur through programs and projects for qualification and retraining of adult women. In answer to the question that guides this study, it is concluded that a family support system is critical to the success of women in management positions. To meet this demand, one of the ways could be the development of specific gender policies by the public authorities, in accordance with the emerging global economic policies, in order to provide and structure the necessary support. This would respond to feminist manifestations - which should go on pointing needs – although the legislative assembly should also propose ideas to change this picture. This is a qualitative research, with a poststructuralist approach, featuring a cutout corpus of three interviews carried out with women holding leadership positions in the academia. Questions related to this very discussion are many. New studies could address points as the promotion of qualification and expansion of skills of women in subaltern condition. There is also need to investigate possible support systems, considering the inequalities and local economic conditions.

Keywords: gender and labor market, glass ceiling, post-structuralism, support chain

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Authors: Dodi Ikhsanshaleh

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When subjected to dynamic load, foundation oscillates in the way that depends on the soil behaviour, the geometry and inertia of the foundation and the dynamic exctation. The practical guideline to analysis block-type foundation excitated by dynamic load from vibrating machine is presented. The analysis use Lumped Mass Parameter Method to express dynamic properties such as stiffness and damping of soil. The numerical examples are performed on design block-type foundation supporting gas turbine compressor which is important equipment package in gas processing plant

Keywords: block foundation, dynamic load, lumped mass parameter

Procedia PDF Downloads 490

Authors: Mahbub C. Mishu, Venktesh N. Dubey, Tamas Hickish, Jonathan Cole

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Pressure ulcer is a common problem for today's healthcare industry. It occurs due to external load applied to the skin. Also when the subject is immobile for a longer period of time and there is continuous load applied to a particular area of human body,blood flow gets reduced and as a result pressure ulcer develops. Body support surface has a significant role in preventing ulceration so it is important to know the characteristics of support surface under loading conditions. In this paper we have presented mathematical models of different types of viscoelastic materials and also we have shown the validation of our simulation results with experiments.

Keywords: pressure ulcer, viscoelastic material, mathematical model, experimental validation

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Authors: Muluken Z. Getie, Francois Lanzetta, Sylvie Begot, Bimrew T. Admassu

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This study is aimed at the numerical analysis of the effects of phase angle and losses (shuttle heat loss and gas leakage to the crankcase) that could have an impact on the pressure and temperature of working fluid for a β-type Stirling cycle refrigerating machine. First, the developed numerical model incorporates into the ideal adiabatic analysis, the shuttle heat transfer (heat loss from compression space to expansion space), and gas leakage from the working space to the buffer space into the crankcase. The other losses that may not have a direct effect on the temperature and pressure of working fluid are simply incorporated in a simple analysis. The model is then validated by reversing the model to the engine model and compared with other literature results using (GPU-3) engine. After validating the model with other engine model and experiment results, analysis of the effect of phase angle, shuttle heat lose and gas leakage on temperature, pressure, and performance (power requirement, cooling capacity and coefficient of performance) of refrigerating machine considering the FEMTO 60 Stirling engine as a case study have been conducted. Shuttle heat loss has a greater effect on the temperature of working gas; gas leakage to the crankcase has more effect on the pressure of working spaces and hence both have a considerable impact on the performance of the Stirling cycle refrigerating machine. The optimum coefficient of performance exists between phase angles of 900-950, and optimum cooling capacity could be found between phase angles of 950-980.

Keywords: beta configuration, engine model, moderate cooling, stirling refrigerator, and validation

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

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This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

Procedia PDF Downloads 478

Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Lemuel David

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The importance of the Micro, Small, and Medium Enterprises sector is well recognized for its legitimate contribution to the Macroeconomic objectives of the Republic of Liberia, like generation of employment, input t, exports, and enhancing entrepreneurship. Right now, Medium and Small enterprises accounts for about 99 percent of the industrial units in the country, contributing 60 percent of the manufacturing sector output and approximately one-third of the nation’s exports. The role of various financial institutions like ECO bank and Non-financial Institutions like Bearch Limited support promoting the growth of Micro, Small, and Medium Enterprises is unique. A small enterprise or entrepreneur gets many types of assistance from different institutions for varied purposes in the course of his entrepreneurial journey. This paper focuses on the factors related to financial institutional support and non-financial institutional support entrepreneurs to the growth of Medium and Small enterprises in the Republic of Liberia. The significance of this paper is to support Policy and Institutional Support for Medium and Small enterprises to know the views of entrepreneurs about financial and non-financial support systems in the Republic of Liberia. This study was carried out through a survey method, with the use of questionnaires. The population for this study consisted of all registered Medium and Small enterprises which have been registered during the years 2004-2014 in the republic of Liberia. The sampling method employed for this study was a simple random technique and determined a sample size of 400. Data for the study was collected using a standard questionnaire. The questionnaire consisted of two parts: the first part consisted of questions on the profile of the respondents. The second part covers (1) financial, promotional factors and (2) non-financial promotional factors. The results of the study are based on financial and non-financial supporting activities provided by institutions to Medium and Small enterprises. After investigation, it has been found that there is no difference in the support given by Financial Institutions and non-financial Institutions. Entrepreneurs perceived “collateral-free schemes and physical infrastructure support factors are highest contributing to entry and growth of Medium and Small enterprises.

Keywords: micro, small, and medium enterprises financial institutions, entrepreneurship

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

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This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.

Keywords: data mining technique, the decision support system, knowledge and decision rules, education

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Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

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Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

Procedia PDF Downloads 121

Authors: Akriti Kafle Baral, Ruixing Zhang, Dzifa K Lalit, Manthar M Alli

Abstract:

Introduction: Hemodialysis is the most common type of dialysis globally approximately million are reported to receive this type of dialysis. Psychosocial issues in hemodialysis are the psychological and socioeconomic burdens emanating from the initiation and course of treatment and have the potential for gross deterioration in the quality of life and general well-being of patients. Understanding the psychosocial issues and needs of patients undergoing hemodialysis could pave the way for comprehensive support and therapies designed to reduce stress, improve social support, and foster mental resilience. Objectives: The aim of this study was to explore the psychosocial issues and support needs of patients undergoing hemodialysis at a tertiary care center in Nepal. Methods: A qualitative descriptive study was conducted among 20 purposefully selected patients attending hemodialysis treatment at Pokhara Academy of Health Sciences, Nepal. Data was analyzed via thematic analysis. Results: The study resulted in three major themes which included Emotional, psychological, and spiritual struggles, Social and economic impacts, and Support and information needs. Moreover, 16 sub-themes emerged which are Frustration with daily life, Constant fear of death, Thoughts of self-harm, Perceived Burden on Family, Sense of Divine Punishment, Sense of Unfairness, Fear about future uncertainties, Social avoidance, Social stigmatization, Loss of employment, Financial strain, Transportation challenges, Need for early, clear and comprehensive information, Need for support and reassurance from family, Support through peer connections, and Reassurance from healthcare providers. Conclusion: The findings of this study indicate that patients undergoing hemodialysis in Nepal experience numerous hardships and multifaceted struggles that require support from different dimensions. Establishing robust support systems that include family involvement, peer networks, and effective communication from healthcare professionals can significantly mitigate feelings of anxiety and isolation.

Keywords: hemodialysis, psychosocial issues, support needs, chronic kidney disease, end stage renal disease, Nepal

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Authors: Busra Ekinci

Abstract:

Urban heat island term becomes one of the most important problem in urban areas as a reflection of global warming in local scale last years. Many communities and governments are taking action to reduce heat island effects on urban areas where the half of the world's population live today. At this point, urban design turned out to be an important practice and research area for providing an environmentally sensitive urban development. In this study, mitigating strategies of urban heat island effects by urban design are investigated in Aksaray Square and surroundings in Istanbul. Aksaray is an important historical and commercial center of Istanbul, which has an increasing density due to be the node of urban transportation. Also, Istanbul Metropolitan Municipality prepared an urban design project to respond the needs of growing population in the area for 2018. The purpose of the study is emphasizing the importance of urban design objectives and strategies that are developed to reduce the heat island effects on urban areas. Depending on this, the urban heat island effect of the area was examined based on the albedo (reflectivity) parameter which is the most effective parameter in the formation of the heat island effect in urban areas. Albedo values were calculated by Albedo Viewer web application model that was developed by Energy and Environmental Engineering Department of Kyushu University in Japan. Albedo parameter had examined for the present situation and the planned situation with urban design project. The results show that, the current area has urban heat island potential. With the Aksaray Square Project, the heat island effect on the area can be reduced, but would not be completely prevented. Therefore, urban design strategies had been developed to reduce the island effect in addition to the urban design project of the area. This study proves that urban design objectives and strategies are quite effective to reduce the heat island effects, which negatively affect the social environment and quality of life in urban areas.

Keywords: Albedo, urban design, urban heat island, sustainable design

Procedia PDF Downloads 580

Authors: Cao Jiayu, Lan Ximing, Huang Jingjia, Burra Venkata Durga Kumar

Abstract:

The first virus to attack personal computers was born in early 1986, called C-Brain, written by a pair of Pakistani brothers. In those days, people still used dos systems, manipulating computers with the most basic command lines. In the 21st century today, computer performance has grown geometrically. But computer viruses are also evolving and escalating. We never stop fighting against security problems. Stack overflow is one of the most common security vulnerabilities in operating systems. It may result in serious security issues for an operating system if a program in it has a vulnerability with administrator privileges. Certain viruses change the value of specific memory through a stack overflow, allowing computers to run harmful programs. This study developed a mechanism to detect and respond to time whenever a stack overflow occurs. We demonstrate the effectiveness of standard machine learning algorithms and control flow enforcement techniques in predicting computer OS security using generating suspicious vulnerability functions (SVFS) and associated suspect areas (SAS). The method can minimize the possibility of stack overflow attacks occurring.

Keywords: operating system, security, stack overflow, buffer overflow, machine learning, control-flow enforcement technology

Procedia PDF Downloads 115