Search results for: traditional models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10912

Search results for: traditional models

9442 Vibrations of Springboards: Mode Shape and Time Domain Analysis

Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

Abstract:

Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

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9441 Predicting the Effect of Silicon Electrode Design Parameters on Thermal Performance of a Lithium-Ion Battery

Authors: Harika Dasari, Eric Eisenbraun

Abstract:

The present study models the role of electrode structural characteristics on the thermal behavior of lithium-ion batteries. Preliminary modeling runs have employed a 1D lithium-ion battery coupled to a two-dimensional axisymmetric model using silicon as the battery anode material. The two models are coupled by the heat generated and the average temperature. Our study is focused on the silicon anode particle sizes and it is observed that silicon anodes with nano-sized particles reduced the temperature of the battery in comparison to anodes with larger particles. These results are discussed in the context of the relationship between particle size and thermal transport properties in the electrode.

Keywords: particle size, NMC, silicon, heat generation, separator

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9440 Identification of Tangible and Intangible Heritage and Preparation of Conservation Proposal for the Historic City of Karanja Laad

Authors: Prachi Buche Marathe

Abstract:

Karanja Laad is a city located in the Vidarbha region in the state of Maharashtra, India. It has a huge amount of tangible and intangible heritage in the form of monuments, precincts, a group of structures, festivals and procession route, which is neglected and lost with time. Three different religions Hinduism, Islam and Jainism along with associations of being a birthplace of Swami Nrusinha Saraswati, an exponent of Datta Sampradaya sect and the British colonial layer have shaped the culture and society of the place over the period. The architecture of the town Karanja Laad has enhanced its unique historic and cultural value with a combination of all these historic layers. Karanja Laad is also a traditional trading historic town with unique hybrid architectural style and has a good potential for developing as a tourist place along with the present image of a pilgrim destination of Datta Sampradaya. The aim of the research is to prepare a conservation proposal for the historic town along with the management framework. Objectives of the research are to study the evolution of Karanja town, to identify the cultural resources along with issues of the historic core of the city, to understand Datta sampradaya, and contribution of Saint Nrusinha Saraswati in the religious sect and his association as an important personality with Karanja. The methodology of the research is site visits to the Karanja city, making field surveys for documentation and discussions and questionnaires with the residents to establish heritage and identify potential and issues within the historic core thereby establishing a case for conservation. Field surveys are conducted for town level study of land use, open spaces, occupancy, ownership, traditional commodity and community, infrastructure, streetscapes, and precinct activities during the festival and non-festival period. Building level study includes establishing various typologies like residential, institutional commercial, religious, and traditional infrastructure from the mythological references like waterbodies (kund), lake and wells. One of the main issues is that the loss of the traditional footprint as well as the traditional open spaces which are getting lost due to the new illegal encroachments and lack of guidelines for the new additions to conserve the original fabric of the structures. Traditional commodities are getting lost since there is no promotion of these skills like pottery and painting. Lavish bungalows like Kannava mansion, main temple Wada (birthplace of the saint) have a huge potential to be developed as a museum by adaptive re-use which will, in turn, attract many visitors during festivals which will boost the economy. Festival procession routes can be identified and a heritage walk can be developed so as to highlight the traditional features of the town. Overall study has resulted in establishing a heritage map with 137 heritage structures identified as potential. Conservation proposal is worked out on the town level, precinct level and building level with interventions such as developing construction guidelines for further development and establishing a heritage cell consisting architects and engineers for the upliftment of the existing rich heritage of the Karanja city.

Keywords: built heritage, conservation, Datta Sampradaya, Karanja Laad, Swami Nrusinha Saraswati, procession route

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9439 Stability Analysis of Two-delay Differential Equation for Parkinson's Disease Models with Positive Feedback

Authors: M. A. Sohaly, M. A. Elfouly

Abstract:

Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation

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9438 Selection of Variogram Model for Environmental Variables

Authors: Sheikh Samsuzzhan Alam

Abstract:

The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

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9437 Evolution of Pop Art Pattern on Modern Ao Dai

Authors: Mai Anh Pham Ho

Abstract:

Ao Dai is the traditional dress of Vietnamese women that consists of a long tunic with slits on either side and wide trousers. This is the Vietnamese national costume which most common worn by women in daily life. The Vietnamese men may wear Ao Dai on special occasions like New Year Eve or Wedding Ceremony. Ao Dai is one of the few Vietnamese words that appear in English language dictionaries. Nowadays, there are variations in modern Ao Dai that consist of a short tunic on knee and slim trousers with the other materials like kaki or jeans. This paper aims to apply Pop art pattern on modern Ao Dai through the image of Vietnamese women by modifying the creation process of fashion design. It reflects on how modern culture is involved in Ao Dai and how it affects on fashion design. The research method of this paper is done through surveying the various examples of technological applications to fashion design, then the pop art pattern with the image of Vietnamese women is applied on modern Ao Dai. The results of this paper have shown through the collection of modern Ao Dai with three artworks applied the pop art pattern. In conclusion, the role of fashion technology supports and evolves the traditional value in order to establish the Vietnamese national personality as well as distinguish to other cultural values in the world.

Keywords: pop art pattern, Vietnamese national costume, modern ao dai, fashion design

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9436 Chemometric Analysis of Raw Milk Quality Originating from Conventional and Organic Dairy Farming in AP Vojvodina, Serbia

Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

Abstract:

The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

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9435 Probabilistic Analysis of Bearing Capacity of Isolated Footing using Monte Carlo Simulation

Authors: Sameer Jung Karki, Gokhan Saygili

Abstract:

The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

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9434 Faster, Lighter, More Accurate: A Deep Learning Ensemble for Content Moderation

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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9433 Future Design and Innovative Economic Models for Futuristic Markets in Developing Countries

Authors: Nessreen Y. Ibrahim

Abstract:

Designing the future according to realistic analytical study for the futuristic market needs can be a milestone strategy to make a huge improvement in developing countries economics. In developing countries, access to high technology and latest science approaches is very limited. The financial problems in low and medium income countries have negative effects on the kind and quality of imported new technologies and application for their markets. Thus, there is a strong need for shifting paradigm thinking in the design process to improve and evolve their development strategy. This paper discusses future possibilities in developing countries, and how they can design their own future according to specific future models FDM (Future Design Models), which established to solve certain economical problems, as well as political and cultural conflicts. FDM is strategic thinking framework provides an improvement in both content and process. The content includes; beliefs, values, mission, purpose, conceptual frameworks, research, and practice, while the process includes; design methodology, design systems, and design managements tools. In this paper the main objective was building an innovative economic model to design a chosen possible futuristic scenario; by understanding the market future needs, analyze real world setting, solve the model questions by future driven design, and finally interpret the results, to discuss to what extent the results can be transferred to the real world. The paper discusses Egypt as a potential case study. Since, Egypt has highly complex economical problems, extra-dynamic political factors, and very rich cultural aspects; we considered Egypt is a very challenging example for applying FDM. The paper results recommended using FDM numerical modeling as a starting point to design the future.

Keywords: developing countries, economic models, future design, possible futures

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9432 Forecasting Solid Waste Generation in Turkey

Authors: Yeliz Ekinci, Melis Koyuncu

Abstract:

Successful planning of solid waste management systems requires successful prediction of the amount of solid waste generated in an area. Waste management planning can protect the environment and human health, hence it is tremendously important for countries. The lack of information in waste generation can cause many environmental and health problems. Turkey is a country that plans to join European Union, hence, solid waste management is one of the most significant criteria that should be handled in order to be a part of this community. Solid waste management system requires a good forecast of solid waste generation. Thus, this study aims to forecast solid waste generation in Turkey. Artificial Neural Network and Linear Regression models will be used for this aim. Many models will be run and the best one will be selected based on some predetermined performance measures.

Keywords: forecast, solid waste generation, solid waste management, Turkey

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9431 CAD Tool for Parametric Design modification of Yacht Hull Surface Models

Authors: Shahroz Khan, Erkan Gunpinar, Kemal Mart

Abstract:

Recently parametric design techniques became a vital concept in the field of Computer Aided Design (CAD), which helps to provide sophisticated platform to the designer in order to automate the design process in efficient time. In these techniques, design process starts by parameterizing the important features of design models (typically the key dimensions), with the implementation of design constraints. The design constraints help to retain the overall shape of the model while modifying its parameters. However, the process of initializing an appropriate number of design parameters and constraints is the crucial part of parametric design techniques, especially for complex surface models such as yacht hull. This paper introduces a method to create complex surface models in favor of parametric design techniques, a method to define the right number of parameters and respective design constraints, and a system to implement design parameters in contract to design constraints schema. For this, in our proposed approach the design process starts by dividing the yacht hull into three sections. Each section consists of different shape lines, which form the overall shape of yacht hull. The shape lines are created using Cubic Bezier Curves, which allow larger design flexibility. Design parameters and constraints are defined on the shape lines in 3D design space to facilitate the designers for better and individual handling of parameters. Afterwards, shape modifiers are developed, which allow the modification of each parameter while satisfying the respective set of criteria and design constraints. Such as, geometric continuities should be maintained between the shape lines of the three sections, fairness of the hull surfaces should be preserved after modification and while design modification, effect of a single parameter should be negligible on other parameters. The constraints are defined individually on shape lines of each section and mutually between the shape lines of two connecting sections. In order to validate and visualize design results of our shape modifiers, a real time graphic interface is created.

Keywords: design parameter, design constraints, shape modifies, yacht hull

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9430 Modelling of Damage as Hinges in Segmented Tunnels

Authors: Gelacio JuáRez-Luna, Daniel Enrique GonzáLez-RamíRez, Enrique Tenorio-Montero

Abstract:

Frame elements coupled with springs elements are used for modelling the development of hinges in segmented tunnels, the spring elements modelled the rotational, transversal and axial failure. These spring elements are equipped with constitutive models to include independently the moment, shear force and axial force, respectively. These constitutive models are formulated based on damage mechanics and experimental test reported in the literature review. The mesh of the segmented tunnels was discretized in the software GID, and the nonlinear analyses were carried out in the finite element software ANSYS. These analyses provide the capacity curve of the primary and secondary lining of a segmented tunnel. Two numerical examples of segmented tunnels show the capability of the spring elements to release energy by the development of hinges. The first example is a segmental concrete lining discretized with frame elements loaded until hinges occurred in the lining. The second example is a tunnel with primary and secondary lining, discretized with a double ring frame model. The outer ring simulates the segmental concrete lining and the inner ring simulates the secondary cast-in-place concrete lining. Spring elements also modelled the joints between the segments in the circumferential direction and the ring joints, which connect parallel adjacent rings. The computed load vs displacement curves are congruent with numerical and experimental results reported in the literature review. It is shown that the modelling of a tunnel with primary and secondary lining with frame elements and springs provides reasonable results and save computational cost, comparing with 2D or 3D models equipped with smeared crack models.

Keywords: damage, hinges, lining, tunnel

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9429 Secure E-Voting Using Blockchain Technology

Authors: Barkha Ramteke, Sonali Ridhorkar

Abstract:

An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

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9428 The Creation of a Yeast Model for 5-oxoproline Accumulation

Authors: Pratiksha Dubey, Praveen Singh, Shantanu Sen Gupta, Anand K. Bachhawat

Abstract:

5-oxoproline (pyroglutamic acid) is a cyclic lactam of glutamic acid. In the cell, it can be produced by several different pathways and is metabolized into glutamate with the help of the 5-oxoprolinase enzyme (OPLAH or OXP1). The inhibition of 5-oxoprolinase enzyme in mammals was found to result in heart failure and is thought to be a consequence of oxidative stress [1]. To analyze the consequences of 5-oxoproline accumulation more clearly, we are generating models for 5-oxoproline accumulation in yeast. The 5-oxoproline accumulation model in yeast is being developed by two different strategies. The first one is by overexpression of the mouse  -glutamylcyclotransferase enzyme. It degrades -glu-met dipeptide into 5-oxoproline and methionine taken by the cell from the medium. The second strategy is by providing high concentration of 5-oxoproline externally to the yeast cells. The intracellular 5-oxoproline levels in both models are being evaluated. In addition, the metabolic and cellular consequences are being investigated.

Keywords: 5-oxoproline, pyroglutamic acid, yeast, genetics

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9427 Green Architecture from the Thawing Arctic: Reconstructing Traditions for Future Resilience

Authors: Nancy Mackin

Abstract:

Historically, architects from Aalto to Gaudi to Wright have looked to the architectural knowledge of long-resident peoples for forms and structural principles specifically adapted to the regional climate, geology, materials availability, and culture. In this research, structures traditionally built by Inuit peoples in a remote region of the Canadian high Arctic provides a folio of architectural ideas that are increasingly relevant during these times of escalating carbon emissions and climate change. ‘Green architecture from the Thawing Arctic’ researches, draws, models, and reconstructs traditional buildings of Inuit (Eskimo) peoples in three remote, often inaccessible Arctic communities. Structures verified in pre-contact oral history and early written history are first recorded in architectural drawings, then modeled and, with the participation of Inuit young people, local scientists, and Elders, reconstructed as emergency shelters. Three full-sized building types are constructed: a driftwood and turf-clad A-frame (spring/summer); a stone/bone/turf house with inwardly spiraling walls and a fan-shaped floor plan (autumn); and a parabolic/catenary arch-shaped dome from willow, turf, and skins (autumn/winter). Each reconstruction is filmed and featured in a short video. Communities found that the reconstructed buildings and the method of involving young people and Elders in the reconstructions have on-going usefulness, as follows: 1) The reconstructions provide emergency shelters, particularly needed as climate change worsens storms, floods, and freeze-thaw cycles and scientists and food harvesters who must work out of the land become stranded more frequently; 2) People from the communities re-learned from their Elders how to use materials from close at hand to construct impromptu shelters; 3) Forms from tradition, such as windbreaks at entrances and using levels to trap warmth within winter buildings, can be adapted and used in modern community buildings and housing; and 4) The project initiates much-needed educational and employment opportunities in the applied sciences (engineering and architecture), construction, and climate change monitoring, all offered in a culturally-responsive way. Elders, architects, scientists, and young people added innovations to the traditions as they worked, thereby suggesting new sustainable, culturally-meaningful building forms and materials combinations that can be used for modern buildings. Adding to the growing interest in bio-mimicry, participants looked at properties of Arctic and subarctic materials such as moss (insulation), shrub bark (waterproofing), and willow withes (parabolic and catenary arched forms). ‘Green Architecture from the Thawing Arctic’ demonstrates the effective, useful architectural oeuvre of a resilient northern people. The research parallels efforts elsewhere in the world to revitalize long-resident peoples’ architectural knowledge, in the interests of designing sustainable buildings that reflect culture, heritage, and identity.

Keywords: architectural culture and identity, climate change, forms from nature, Inuit architecture, locally sourced biodegradable materials, traditional architectural knowledge, traditional Inuit knowledge

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9426 Ethnic Andean Concepts of Health and Illness in the Post-Colombian World and Its Relevance Today

Authors: Elizabeth J. Currie, Fernando Ortega Perez

Abstract:

—‘MEDICINE’ is a new project funded under the EC Horizon 2020 Marie-Sklodowska Curie Actions, to determine concepts of health and healing from a culturally specific indigenous context, using a framework of interdisciplinary methods which integrates archaeological-historical, ethnographic and modern health sciences approaches. The study will generate new theoretical and methodological approaches to model how peoples survive and adapt their traditional belief systems in a context of alien cultural impacts. In the immediate wake of the conquest of Peru by invading Spanish armies and ideology, native Andeans responded by forming the Taki Onkoy millenarian movement, which rejected European philosophical and ontological teachings, claiming “you make us sick”. The study explores how people’s experience of their world and their health beliefs within it, is fundamentally shaped by their inherent beliefs about the nature of being and identity in relation to the wider cosmos. Cultural and health belief systems and related rituals or behaviors sustain a people’s sense of identity, wellbeing and integrity. In the event of dislocation and persecution these may change into devolved forms, which eventually inter-relate with ‘modern’ biomedical systems of health in as yet unidentified ways. The development of new conceptual frameworks that model this process will greatly expand our understanding of how people survive and adapt in response to cultural trauma. It will also demonstrate the continuing role, relevance and use of TM in present-day indigenous communities. Studies will first be made of relevant pre-Colombian material culture, and then of early colonial period ethnohistorical texts which document the health beliefs and ritual practices still employed by indigenous Andean societies at the advent of the 17th century Jesuit campaigns of persecution - ‘Extirpación de las Idolatrías’. Core beliefs drawn from these baseline studies will then be used to construct a questionnaire about current health beliefs and practices to be taken into the study population of indigenous Quechua peoples in the northern Andean region of Ecuador. Their current systems of knowledge and medicine have evolved within complex historical contexts of both the conquest by invading Inca armies in the late 15th century, followed a generation later by Spain, into new forms. A new model will be developed of contemporary  Andean concepts of health, illness and healing demonstrating  the way these have changed through time. With this, a ‘policy tool’ will be constructed as a bridhging facility into contemporary global scenarios relevant to other Indigenous, First Nations, and migrant peoples to provide a means through which their traditional health beliefs and current needs may be more appropriately understood and met. This paper presents findings from the first analytical phases of the work based upon the study of the literature and the archaeological records. The study offers a novel perspective and methods in the development policies sensitive to indigenous and minority people’s health needs.

Keywords: Andean ethnomedicine, Andean health beliefs, health beliefs models, traditional medicine

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9425 Detecting Earnings Management via Statistical and Neural Networks Techniques

Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

Abstract:

Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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9424 Establishing the Microbial Diversity of Traditionally Prepared Rice Beer of Northeast India to Impact in Increasing Its Shelf Life

Authors: Shreya Borthakur, Adhar Sharma

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The North-east states of India are well known for their age-old practice of preparing alcoholic beer from rice and millet. They do so in a traditional way by sprinkling starter cake (inoculum) on cooked rice or millet after which the fermentation starts and eventually, forms the beer. This starter cake has a rich composition of different microbes and medicinal herbs along with the powdered rice dough or maize dough with rice bran. The starter cake microbial composition has an important role in determining the microbial succession and metabolic secretions as the fermentation proceeds from the early to its late stage, thus, giving the beer a unique aroma, taste, and other sensory properties of traditionally prepared beer. Here, We have worked on identifying and characterizing the microbial community in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. A total of 18 microbial strains have been isolated from the starter cake of Monpa tribe, while 10 microbial isolates in that of Galo tribe. A metagenomic approach was applied to enumerate the cultural and non-cultural microbes present in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. The findings of the mini-project lays foundation to understand the role of microbes present in the starter cake in the beer’s fermentation process and will aide in future research on re-formulating the starter cakes to prevent the early spoilage of the ready to consume beer as the traditional rice beer has a short shelf-life. The paper concludes with the way forward being controlled CRISPR-Cas9.

Keywords: fermentation, traditional beer, microbial succession, preservation, CRISPR-Cas, food microbiology

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9423 Hand Motion Trajectory Analysis for Dynamic Hand Gestures Used in Indian Sign Language

Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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9422 Multi-Period Portfolio Optimization Using Predictive Machine Learning Models

Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

Abstract:

This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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9421 Smart Defect Detection in XLPE Cables Using Convolutional Neural Networks

Authors: Tesfaye Mengistu

Abstract:

Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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9420 Prediction on Housing Price Based on Deep Learning

Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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9419 Predictive Modeling of Student Behavior in Virtual Reality: A Machine Learning Approach

Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

Abstract:

In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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9418 The Incubation of University Spin-Offs: An Exploratory Study of a Deep Tech Venture

Authors: Jerome D. Donovan

Abstract:

The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

Procedia PDF Downloads 74
9417 Behavior Consistency Analysis for Workflow Nets Based on Branching Processes

Authors: Wang Mimi, Jiang Changjun, Liu Guanjun, Fang Xianwen

Abstract:

Loop structure often appears in the business process modeling, analyzing the consistency of corresponding workflow net models containing loop structure is a problem, the existing behavior consistency methods cannot analyze effectively the process models with the loop structure. In the paper, by analyzing five kinds of behavior relations of transitions, a three-dimensional figure and two-dimensional behavior relation matrix are proposed. Based on this, analysis method of behavior consistency of business process based on Petri net branching processes is proposed. Finally, an example is given out, which shows the method is effective.

Keywords: workflow net, behavior consistency measures, loop, branching process

Procedia PDF Downloads 377
9416 Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks

Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

Abstract:

The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

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9415 Knowledge Co-Production on Future Climate-Change-Induced Mass-Movement Risks in Alpine Regions

Authors: Elisabeth Maidl

Abstract:

The interdependence of climate change and natural hazard goes along with large uncertainties regarding future risks. Regional stakeholders, experts in natural hazards management and scientists have specific knowledge, resp. mental models on such risks. This diversity of views makes it difficult to find common and broadly accepted prevention measures. If the specific knowledge of these types of actors is shared in an interactive knowledge production process, this enables a broader and common understanding of complex risks and allows to agree on long-term solution strategies. Previous studies on mental models confirm that actors with specific vulnerabilities perceive different aspects of a topic and accordingly prefer different measures. In bringing these perspectives together, there is the potential to reduce uncertainty and to close blind spots in solution finding. However, studies that examine the mental models of regional actors on future concrete mass movement risks are lacking so far. The project tests and evaluates the feasibility of knowledge co-creation for the anticipatory prevention of climate change-induced mass movement risks in the Alps. As a key element, mental models of the three included groups of actors are compared. Being integrated into the research program Climate Change Impacts on Alpine Mass Movements (CCAMM2), this project is carried out in two Swiss mountain regions. The project is structured in four phases: 1) the preparatory phase, in which the participants are identified, 2) the baseline phase, in which qualitative interviews and a quantitative pre-survey are conducted with actors 3) the knowledge-co-creation phase, in which actors have a moderated exchange meeting, and a participatory modelling workshop on specific risks in the region, and 4) finally a public information event. Results show that participants' mental models are based on the place of origin, profession, believes, values, which results in narratives on climate change and hazard risks. Further, the more intensively participants interact with each other, the more likely is that they change their views. This provides empirical evidence on how changes in opinions and mindsets can be induced and fostered.

Keywords: climate change, knowledge-co-creation, participatory process, natural hazard risks

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9414 The Impact of Model Specification Decisions on the Teacher ValuE-added Effectiveness: Choosing the Correct Predictors

Authors: Ismail Aslantas

Abstract:

Value-Added Models (VAMs), the statistical methods for evaluating the effectiveness of teachers and schools based on student achievement growth, has attracted decision-makers’ and researchers’ attention over the last decades. As a result of this attention, many studies have conducted in recent years to discuss these statistical models from different aspects. This research focused on the importance of conceptual variables in VAM estimations; therefor, this research was undertaken to examine the extent to which value-added effectiveness estimates for teachers can be affected by using context predictions. Using longitudinal data over three years from the international school context, value-added teacher effectiveness was estimated by ordinary least-square value-added models, and the effectiveness of the teachers was examined. The longitudinal dataset in this study consisted of three major sources: students’ attainment scores up to three years and their characteristics, teacher background information, and school characteristics. A total of 1,027 teachers and their 35,355 students who were in eighth grade were examined for understanding the impact of model specifications on the value-added teacher effectiveness evaluation. Models were created using selection methods that adding a predictor on each step, then removing it and adding another one on a subsequent step and evaluating changes in model fit was checked by reviewing changes in R² values. Cohen’s effect size statistics were also employed in order to find out the degree of the relationship between teacher characteristics and their effectiveness. Overall, the results indicated that prior attainment score is the most powerful predictor of the current attainment score. 47.1 percent of the variation in grade 8 math score can be explained by the prior attainment score in grade 7. The research findings raise issues to be considered in VAM implementations for teacher evaluations and make suggestions to researchers and practitioners.

Keywords: model specification, teacher effectiveness, teacher performance evaluation, value-added model

Procedia PDF Downloads 121
9413 Developing a South African Model of Neuropsychological Rehabilitation for Adults After Acquired Brain Injury

Authors: Noorjehan Joosub-Vawda

Abstract:

Objectives: The aim of this poster presentation is to examine cultural contextual understandings of ABI that could aid conceptualisation and the development of a model for neuropsychological rehabilitation in this context. Characteristics of the South African context that make the implementation of international NR practices difficult include socioeconomic disparities, sociocultural influences, lack of accessibility to healthcare services, and poverty and unemployment levels. NR services in the developed world have characteristics such as low staff-to-patient ratios and interdisciplinary teams that make them unsuitable for the resource-constrained South African context. Methods: An exploratory, descriptive research design based on programme theory is being followed in the development of a South African model of neuropsychological rehabilitation. Results: The incorporation of African traditional understandings and practices, such as beliefs about ancestral spirits in the etiology of Acquired Brain Injury are relevant to the planning of rehabilitation interventions. Community-Based Rehabilitation workers, psychoeducation, and cooperation among the different systemic levels especially in rural settings is also needed to improve services offered to patients living with ABI. Conclusions. The preliminary model demonstrated in this poster will attempt to build on the strengths of South African communities, incorporating valuable evidence from international models to serve those affected with brain injury in this context.

Keywords: neuropsychological rehabilitation, South Africa, acquired brain injury, developing context

Procedia PDF Downloads 312