Search results for: Indian auto component industry

Authors: Namhun Lee, Seong Jin Kim

Abstract:

The construction industry represents one of the largest industries in the United States, yet it continues to face several occupational health and safety challenges. Many workers on construction sites are suffering from extended exposure to stressful situations such as poor and hazardous work environments and task complexity. Stress can be commonly defined as a feeling of emotional or physical tension, which can easily impact construction safety and result in a higher rate of job-related injuries in the construction industry. Physiological signals transmitted from wearable biosensors can be used to detect excessive stress. Therefore, workers’ stress should be detected and mitigated to prevent any type of serious incident or accident proactively. By doing this, construction productivity, as well as job satisfaction, would also be improved in the construction industry. To establish a foundation in this field of research, a conceptual framework for using wearable technology for construction safety has been developed for continuous and automatic monitoring of worker’s stress. The conceptual framework will serve as a foothold in future studies on the application of wearable technology for construction safety.

Keywords: construction safety, occupational stress, stress monitoring, wearable biosensors

Procedia PDF Downloads 151

Authors: Dwipa Rizki Utama, Hanief Ibrahim

Abstract:

The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.

Keywords: industry retail, strategy, association rule, supermarket

Procedia PDF Downloads 180

Authors: Juan Pedro Aznar Alarcon, Josep Maria Sayeras Maspera

Abstract:

Airbnb and other similar platforms are offering a near substitute to the traditional accommodation service supplied by the hotel sector. In this context, hotels can try to compete by offering higher quality and additional services, which imply the need for new investments or try to compete by reducing prices. The theoretical model presented in this paper analyzes the best response using a sequential game theory model. The main conclusion is that due to the financial constraints that small and medium hotels have these hotels have reduced prices whereas hotels that belong to international groups or have an easy access to financial resources have increased their investment to increase the quality of the service provided. To check the validity of the theoretical model financial data from Barcelona, London and Paris hotels have been used analyzing profitability, quality of the service provided, the investment propensity and the evolution of the gross profit. The model and the empirical data provide the base for some industrial policy in the hospitality industry. To address the extra cost that small hotels in Europe have to face compared by bigger firms would help to improve the level of quality provided and to some extent have positive externalities in terms of job creation and an increasing added value for the industry.

Keywords: Airbnb, profitability, hospitality industry, game theory

Procedia PDF Downloads 340

Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó

Abstract:

Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper, a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate an FEM model which is accurate and competitive for a future shape optimization task.

Keywords: rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model

Procedia PDF Downloads 501

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 165

Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

Abstract:

The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

Procedia PDF Downloads 77

Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini

Abstract:

Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.

Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling

Procedia PDF Downloads 88

Authors: Zarina Zahari, Maria Justine, Kamaria Kamaruddin

Abstract:

Low back pain (LBP) is a major musculoskeletal problem in global population. This study aimed to examine the relationship between pain, disability and quality of life in patients with non-specific low back pain (LBP). One hundred LBP participants were recruited in this cross-sectional study (mean age = 42.23±11.34 years old). Pain was measured using Numerical Rating Scale (11-point). Disability was assessed using the revised Oswestry low back pain disability questionnaire (ODQ) and quality of life (QoL) was evaluated using the SF-36 v2. Majority of participants (58%) presented with moderate pain and 49% experienced severe disability. Thus, the pain and disability were found significant with negative correlation (r= -0.712, p<0.05). The pain and QoL also showed significant and positive correlation with both Physical Health Component Summary (PHCS) (r= .840, p<0.05) and Mental Health Component Summary (MHCS) (r= 0.446, p<0.05). Regression analysis indicated that pain emerged as an indicator of both disability and QoL (PHCS and MHCS) accounting for 51%, 71% and 21% of the variances respectively. This indicates that pain is an important factor in predicting disability and QoL in LBP sufferers.

Keywords: disability, low back pain, pain, quality of life

Procedia PDF Downloads 527

Authors: Dibyendu Rakshit, Santosh K. Sarkar

Abstract:

The study illustrates a comprehensive account of large-scale changes plankton community structure in relevance to water quality characteristics due to anthropogenic stresses, mainly concerned for Annual Gangasagar Festival (AGF) at the southern tip of Sagar Island of Indian Sundarban wetland for 3-year duration (2012-2014; n=36). This prograding, vulnerable and tide-dominated megadelta has been formed in the estuarine phase of the Hooghly Estuary infested by largest continuous tract of luxurious mangrove forest, enriched with high native flora and fauna. The sampling strategy was designed to characterize the changes in plankton community and water quality considering three diverse phases, namely during festival period (January) and its pre - (December) as well as post (February) events. Surface water samples were collected for estimation of different environmental variables as well as for phytoplankton and microzooplankton biodiversity measurement. The preservation and identification techniques of both biotic and abiotic parameters were carried out by standard chemical and biological methods. The intensive human activities lead to sharp ecological changes in the context of poor water quality index (WQI) due to high turbidity (14.02±2.34 NTU) coupled with low chlorophyll a (1.02±0.21 mg m-3) and dissolved oxygen (3.94±1.1 mg l-1), comparing to pre- and post-festival periods. Sharp reduction in abundance (4140 to 2997 cells l-1) and diversity (H′=2.72 to 1.33) of phytoplankton and microzooplankton tintinnids (450 to 328 ind l-1; H′=4.31 to 2.21) was very much pronounced. The small size tintinnid (average lorica length=29.4 µm; average LOD=10.5 µm) composed of Tintinnopsis minuta, T. lobiancoi, T. nucula, T. gracilis are predominant and reached some of the greatest abundances during the festival period. Results of ANOVA revealed a significant variation in different festival periods with phytoplankton (F= 1.77; p=0.006) and tintinnid abundance (F= 2.41; P=0.022). RELATE analyses revealed a significant correlation between the variations of planktonic communities with the environmental data (R= 0.107; p= 0.005). Three distinct groups were delineated from principal component analysis, in which a set of hydrological parameters acted as the causative factor(s) for maintaining diversity and distribution of the planktonic organisms. The pronounced adverse impact of anthropogenic stresses on plankton community could lead to environmental deterioration, disrupting the productivity of benthic and pelagic ecosystems as well as fishery potentialities which directly related to livelihood services. The festival can be considered as multiple drivers of changes in relevance to beach erosion, shoreline changes, pollution from discarded plastic and electronic wastes and destruction of natural habitats resulting loss of biodiversity. In addition, deterioration in water quality was also evident from immersion of idols, causing detrimental effects on aquatic biota. The authors strongly recommend for adopting integrated scientific and administrative strategies for resilience, sustainability and conservation of this megadelta.

Keywords: Gangasagar festival, phytoplankton, Sundarban megadelta, tintinnid

Procedia PDF Downloads 224

Authors: Thandokazi Nyangiwe, Christopher Amoah, Charles P. Mukumba

Abstract:

The South African construction sector is threatened by emerging black business forums called construction mafias. The emergence of the construction mafia has culminated in the disruptions and abandonment of construction sites resulting in the loss of jobs for construction workers. The paper examines the origin of construction mafias and their impact on the construction sector, including the potential ways to cope with their operations. A qualitative research approach was adopted for this study using open-ended interview questions to gather information from 30 key construction industry stakeholders, including contractors, subcontractors, consultants, and the construction project communities. Content and thematic analysis were used to analyse the data collected. The findings suggest that most participants do not fully understand the existence and operations of construction mafias in the construction industry. Construction mafias claim to be part of the local business forums. They disrupt construction projects and demand a certain amount, usually 30% of the construction value. Construction mafias frequently resort to intimidation and violence if their demands are unmet. Their operations have resulted in delayed completion of construction projects, abandonment of projects, and loss of income for the contractor and jobs for the construction workers. The interviews were limited to construction stakeholders. Because of the nature of the mafias’ operations, they could not be accessed for interviews for fear of being identified because of the connotation attached to their role as construction mafias. Construction project owners face disruptions of projects resulting in loss of equipment, materials, and income. Therefore, there is a need to sensitise the construction stakeholders in the construction industry regarding the existence and operations of the construction mafia and the implications on construction project performance and delivery. The findings will give insight into the operations of the construction mafias in the South African construction industry, which has caused disruptions in construction project sites. Stakeholders must find solutions to address the construction mafias’ disruptive actions on construction projects. The study presents an initial inquiry that will come up with how to manage and cope with the growing operations of construction mafias in the South African construction industry.

Keywords: black business forums, construction mafia, emergence, implication

Procedia PDF Downloads 122

Authors: V. Jamuna, A. K. Chakravarty, C. S. Patil, Vijay Kumar, M. A. Mir, Rakesh Kumar

Abstract:

Intense selection of buffaloes for milk production at organized herds of the country without giving due attention to fertility traits viz. pregnancy rate has lead to deterioration in their performances. Aim of study is to develop an optimum model for predicting pregnancy rate and to assess the level of pregnancy rate with respect to milk production Murrah buffaloes. Data pertaining to 1224 lactation records of Murrah buffaloes spread over a period 21 years were analyzed and it was observed that pregnancy rate depicted negative phenotypic association with lactation milk yield (-0.08 ± 0.04). For developing optimum model for pregnancy rate in Murrah buffaloes seven simple and multiple regression models were developed. Among the seven models, model II having only Service period as an independent reproduction variable, was found to be the best prediction model, based on the four statistical criterions (high coefficient of determination (R 2), low mean sum of squares due to error (MSSe), conceptual predictive (CP) value, and Bayesian information criterion (BIC). For standardizing the level of fertility with milk production, pregnancy rate was classified into seven classes with the increment of 10% in all parities, life time and their corresponding average pregnancy rate in relation to the average lactation milk yield (MY).It was observed that to achieve around 2000 kg MY which can be considered optimum for Indian Murrah buffaloes, level of pregnancy rate should be in between 30-50%.

Keywords: life time, pregnancy rate, production, service period, standardization

Procedia PDF Downloads 627

Authors: Khaled Benyounes

Abstract:

Determination of the rock mechanical properties such as unconfined compressive strength UCS, Young’s modulus E, and tensile strength by the Brazilian test Rtb is considered to be the most important component in drilling and mining engineering project. Research related to establishing correlation between strength and physical parameters of rocks has always been of interest to mining and reservoir engineering. For this, many rock blocks of limestone were collected from the quarry located in Meftah (Algeria), the cores were crafted in the laboratory using a core drill. This work examines the relationships between mechanical properties and some physical properties of limestone. Many empirical equations are established between UCS and physical properties of limestone (such as dry bulk density, velocity of P-waves, dynamic Young’s modulus, alteration index, and total porosity). Other correlations, UCS - tensile strength, dynamic Young’s modulus - static Young’s modulus have been find. Based on the Mohr-Coulomb failure criterion, we were able to establish mathematical relationships that will allow estimating the cohesion and internal friction angle from UCS and indirect tensile strength. Results from this study can be useful for mining industry for resolve range of geomechanical problems such as slope stability.

Keywords: limestone, mechanical strength, Young’s modulus, porosity

Procedia PDF Downloads 632

Authors: Michael Smalenberger

Abstract:

Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

Procedia PDF Downloads 166

Authors: Peter Kress, Alexander Pflaum, Ulrich Loewen

Abstract:

The number of Internet-of-Things (IoT) platforms is steadily increasing across various industries, especially for smart factories, smart homes and smart mobility. Also in the manufacturing industry, the number of Industrial-IoT platforms is growing. Both IT players, start-ups and increasingly also established industry players and small-and-medium-enterprises introduce offerings for the connection of industrial equipment on platforms, enabled by advanced information and communication technology. Beside the offered functionalities, the established ecosystem of partners around a platform is one of the key differentiators to generate a competitive advantage. The key question is how platform operators design the business model around their platform to attract a high number of customers and partners to co-create value for the entire ecosystem. The present research tries to answer this question by determining the key characteristics of business models of successful platforms in the manufacturing industry. To achieve that, the authors selected an explorative qualitative research approach and created an inductive comparative case study. The authors generated valuable descriptive insights of the business model elements (e.g., value proposition, pricing model or partnering model) of various established platforms. Furthermore, patterns across the various cases were identified to derive propositions for the successful design of business models of platforms in the manufacturing industry.

Keywords: industrial-internet-of-things, business models, platforms, ecosystems, case study

Procedia PDF Downloads 236

Authors: A. R. Anwar

Abstract:

The development of discrimination case which is now extended to the issue of female workers dress code in the hotel industry seen as a challenging topic and a solution is needed. Discrimination generally gives a negative impact on the victim and has a direct impact on female workers if it involves the issue of this dress code. Hence it is not appropriate if these genders are subjected to discrimination that prohibits them from wearing a hijab and required to wear a short skirt during working hours. On this basis, this study discusses the major problems pertaining to dress code faced by female workers in the Malaysian hotel industry. An interview with qualified parties from human resource department in each selected hotels has been conducted in which later generated the findings and supported by materials that obtained from libraries, archives and other databases. Through the research findings, several recommendations were introduced to reduce and eliminate the discrimination issue in Malaysian working sector particularly in the hotel industry in order to achieve the equality among men and women in the workplace.

Keywords: discrimination, dress code in the hotel, impact on female workers, equality

Procedia PDF Downloads 192

Authors: Diptimayee Nayak

Abstract:

Ecotourism has been recognised as a popular component of alternative tourism, which claims to guard host local environment and economy. This concept of ecological tourism (eco-tourism) has become more meaningful in evaluating the recreational function and services of any pristine ecosystem in context of ‘The Economics of Ecosystem and Biodiversity (TEEB)’. This ecotourism is said to be a local solution to the global problem of conserving ecosystems and optimising the utilisations of their services. This paper takes a case of recreational services of an Indian protected area ecosystems ‘Bhitarakanika mangrove protected area’ discussing how ecotourism is functioning taking the perspectives of different stakeholders. Specific stakeholders are taken for analysis, viz., tourists and local people, as they are believed to be the major beneficiaries of ecotourism. The stakeholders’ analysis is evaluated on the basis of travel cost techniques (by using truncated Poisson distribution model) for tourists and descriptive and analytical tools for local people. The evaluation of stakeholders’ analysis of ecotourism has gained its impetus after the formulation of Ecotourism guidelines by the Ministry of Environment and Forest (MoEF), Government of India. The paper concludes that ecotourism issues and challenges are site-specific and region-specific; without critically focussing challenges of ecotourism faced at local level the discourses of ecotourism at global level cannot be tackled. Mere integration and replication of policies at global level to be followed at local level will not be successful (top down policies). Rather mainstreaming the decision making process at local level with the global policy stature helps to solve global issues to a bigger extent (bottom up).

Keywords: ecosystem services, ecotourism, TEEB, economic valuation, stakeholders, travel cost techniques

Procedia PDF Downloads 242

Authors: G. Sridevi, Amalendu Jyotishi, Sushanta Mahapatra, G. Jagadeesh, Satyasiba Bedamatta

Abstract:

Climate change is a main challenge for agriculture, food security and rural livelihoods for millions of people in India. Agriculture is the sector most vulnerable to climate change due to its high dependence on climate and weather conditions. Among India’s population of more than one billion people, about 68% are directly or indirectly involved in the agricultural sector. This sector is particularly vulnerable to present-day climate variability. In this contest this paper examines the Socio-economic and climate analytical study of the vulnerability index in Indian states of Andhra Pradesh and Karnataka. Using secondary data; it examines the vulnerability through five different sub-indicator of socio-demographic, agriculture, occupational, common property resource (CPR), and climate in respective states among different districts. Data used in this paper has taken from different sources, like census in India 2011, Directorate of Economics and Statistics of respective states governments. Rainfall data was collected from the India Meteorological Department (IMD). In order to capture the vulnerability from two different states the composite vulnerability index (CVI) was developed and used. This indicates the vulnerability situation of different districts under two states. The study finds that Adilabad district in Andhra Pradesh and Chamarajanagar in Karnataka had highest level of vulnerability while Hyderabad and Bangalore in respective states have least level of vulnerability.

Keywords: vulnerability, agriculture, climate change, global warming

Procedia PDF Downloads 455

Authors: John Akinwumi Makinde

Abstract:

Nigerian manufacturing industry, particularly the fast moving consumer producing firms play vital roles in Nigerian economy. This sector’s product acceptability is given very little attention along with social media advertising that communicate product information to audience across the globe need to be documented. Procter and Gamble Plc operate in Nigeria with appreciable number of fast moving consumer goods that service Nigerian economy. Social media advertising disposition of the company and product acceptability of the company deserve some elucidations. This study therefore examined the impact of social media advertising on product acceptability of FMCG in Nigerian manufacturing industry, using Procter and Gamble Plc as case study. The study employed the case study type of descriptive survey research design. The population consisted of 235 customers of G&P Plc, which were selected through random sampling method. A total of 235 copies of questionnaires titled 'Social Media Advertising and Product Acceptability (SMA-PA) Questionnaire' was administered and retrieved. Data generated were analysed using frequency distribution and regression analysis at 0.05 level. It was found that social media advertising positively and significantly motivated customers to buy product of P&G Plc (r =.147**, N= 235, p(.000) < .01). Findings also showed that social media advertising has significant impact on product acceptability of FCMG in P&G Plc (F(2,61)=22.250; R2=.629; P(.000) < .05). The study concluded that social media advertising is a determinant factor of consumer decision to accept fast moving consumer goods in Nigerian manufacturing industry. It is recommended that with the growing market of FMCG, there is need to educate the market with the product unique features, standard and quality on social media. Finally, Fast Moving Consumer Goods firms should deploy excellent marketing mix on social media.

Keywords: advertising, fast moving consumer goods, manufacturing industry, product acceptability, social media

Procedia PDF Downloads 307

Authors: P. Saee, Baiju Gopal

Abstract:

YouTube has seen a surge in the recent years in the number of creators opening up about their mental illness on the video-sharing platform. In documenting their mental health, YouTubers perform an identity of their mental illness in the online world. Identity performance is a theory under identity research that has been readily applied to illness narratives and internet studies. Furthermore, in India, suffering from mental illnesses is regarded with stigma, making the act of taking mental health from a personal to a public space on YouTube a phenomenon worth exploring. Thus, the aim of this paper is to analyse the mental illness narratives of Indian YouTubers for understanding its performance in the virtual world. For this purpose, thematic narrative analysis on the interviews of four Indian YouTubers was conducted. This data was synthesized with analysis of the videos the YouTubers had uploaded on their channel sharing about their mental illness. The narratives of the participants shed light on two significant presentations that they engage in: (a) the identity of a survivor/fighter and (b) the identity of a silent sufferer. Further, the participants used metaphors to describe their illness, thereby co-constructing a corresponding identity based on their particular metaphors. Lastly, the process of bringing mental illness from back stage to front stage on YouTube involves a shift in the audience, from being rejecting and invalidating in real life to being supportive and encouraging in the virtual space. Limitations and implications for future research were outlined.

Keywords: cyber-psychology, internet, media, mental health, mental illness, technology

Procedia PDF Downloads 169

Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

Abstract:

Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

Procedia PDF Downloads 308

Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

Abstract:

The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

Procedia PDF Downloads 405

Authors: Rafael Zhindon Almeida

Abstract:

Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource.

Keywords: statistical modeling, water quality, multiple linear regression, principal components, statistical models

Procedia PDF Downloads 84

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

Procedia PDF Downloads 75

Authors: Shazia Ali, Yves Mard, Éric Severin

Abstract:

To the best of our knowledge, this is the first study to have analyzed the impact of a) firm-specific product-market power and b) industry competition on earnings management behavior of European firms in distress versus healthy years while controlling for firm-level characteristics. We predicted a significant relationship between firms’ product market power and earnings management tools and their trade-off under the moderation effect of financial distress. We found that the firm-level market power hereinafter referred to as MP (proxied by the industry-adjusted Lerner Index) is positively associated with both real and accrual earnings management. However, MP is associated with a higher level of real earnings management compared to accrual earnings management in distress years compared to healthy years. On the other hand, industry product market power (representing low competition and proxied by the inverse of the total number of firms in an industry hereinafter referred to as NUMB) and firms product market power (proxied by firm market share hereinafter referred to as MS) are associated with lower inflationary accruals and higher deflationary accruals respectively. On the other hand, they are found to be linked with higher real earnings management in distress versus healthy years. When we divided the sample into small and big firms based on their respective industry-year median total assets, we found that all three measures of industry competition (Industry Median Lerner Index (hereinafter referred to as IMLI), NUMB, and Herfindahl–Hirschman Index (hereinafter referred to as HHI) indicate that small firms in low-competitive industries in financial distress are more likely to inflate their earnings through discretionary accruals. While big firms in this situation are more likely to lower the use of both inflationary and deflationary discretionary accruals as indicated by IMLI and HHI and trade-off accruals earnings management for real earnings management as indicated by NUMB. Moreover, IMLI and HHI did not show any interesting results when we divided the sample based on the firm Lerner Index/Market Power. However, the distressed firms with high market power (MP>industry median) are found to engage in income-decreasing discretionary accruals in low-competitive industries (high NUMB). Whereas firms with low market power in the same industry use downward discretionary accruals but inflate income using real activities (abnCFO). Our findings are robust across alternate measures of discretionary accruals and financial distress, such as the Altman Z-Score. The finding of the study is valuable for accounting standard setters, competition authorities, policymakers, and investors alike to help in informed decision-making.

Keywords: financial distress, earnings management, market competition

Procedia PDF Downloads 107

Authors: D. Garg, S. Luthra, A. Haleem

Abstract:

Due to growing concern about environmental and social consequences throughout the world, a need has been felt to incorporate sustainability concepts in conventional manufacturing. This paper is an attempt to identify and evaluate drivers in implementing sustainable manufacturing in Indian context. Nine possible drivers for successful implementation of sustainable manufacturing have been identified from extensive review. Further, Decision Making Trial and Evaluation Laboratory (DEMATEL) approach has been utilized to evaluate and categorize these identified drivers for implementing sustainable manufacturing in to the cause and effect groups. Five drivers (Societal Pressure and Public Concerns; Regulations and Government Policies; Top Management Involvement, Commitment and Support; Effective Strategies and Activities towards Socially Responsible Manufacturing and Market Trends) have been categorized into the cause group and four drivers (Holistic View in Manufacturing Systems; Supplier Participation; Building Sustainable culture in Organization; and Corporate Image and Benefits) have been categorized into the effect group. “Societal Pressure and Public Concerns” has been found the most critical driver and “Corporate Image and Benefits” as least critical or the most easily influenced driver to implementing sustainable manufacturing in Indian context. This paper may surely help practitioners in better understanding of these drivers and their priorities towards effective implementation of sustainable manufacturing.

Keywords: drivers, decision making trial and evaluation laboratory (DEMATEL), India, sustainable manufacturing

Procedia PDF Downloads 383

Authors: Chimey Lhamo, Ngawang Tsering

Abstract:

Traditional Tibetan medicine, known as Sowa Rigpa (Science of healing), originated more than 2500 years ago with an insightful background, and it has been growing significant attention in many Asian countries like China, India, Bhutan, and Nepal. Particularly, the Indian government has targeted Traditional Tibetan medicine as its major Indian medical system, including Ayurveda. Although Traditional Tibetan medicine has been growing interest and has a long history, it is not easily recognized worldwide because it exists only in the Tibetan language and it is neither accessible nor understood by patent examiners at the international patent office, data about Traditional Tibetan medicine is not yet broadly exist in the Internet. There has also been the exploitation of traditional Tibetan medicine increasing. The Traditional Knowledge Digital Library is a database aiming to prevent the patenting and misappropriation of India’s traditional medicine knowledge by using India’s Traditional knowledge Digital Library on Sowa Rigpa in order to prevent its exploitation at international patent with the help of information technology tools and an innovative classification systems-traditional knowledge resource classification (TKRC). As of date, more than 3000 Sowa Rigpa formulations have been transcribed into a Traditional Knowledge Digital Library database. In this paper, we are presenting India's Traditional Knowledge Digital Library for Traditional Tibetan medicine, and this database system helps to preserve and prevent the exploitation of Sowa Rigpa. Gradually it will be approved and accepted globally.

Keywords: traditional Tibetan medicine, India's traditional knowledge digital library, traditional knowledge resources classification, international patent classification

Procedia PDF Downloads 124

Authors: Tatiana L. Avalos-Rendon, Elias A. Pasten Chelala, Carlos J. Mendoza EScobedo, Ignacio A. Figueroa, Victor H. Lara, Luis M. Palacios-Romero

Abstract:

The cement industry is facing cost increments in energy supply, requirements for reduction of CO₂, and insufficient supply of raw materials of good quality. According to all these environmental issues, cement industry must change its consumption patterns and reduce CO₂ emissions to the atmosphere. This can be achieved by generating environmental consciousness, which encourages the use of industrial by-products and/or recycling for the production of cement, as well as alternate, environment-friendly methods of synthesis which reduce CO₂. Calcination is the conventional method for the obtainment of Portland cement clinker. This method consists of grinding and mixing of raw materials (limestone, clay, etc.) in an adequate dosage. Resulting mix has a clinkerization temperature of 1450 °C so that the formation of the main component occur: alite (Ca₃SiO₅, C₃S). Considering that the energy required to produce C₃S is 1810 kJ kg -1, calcination method for the obtainment of clinker represents two major disadvantages: long thermal treatment and elevated temperatures of synthesis, both of which cause high emissions of carbon dioxide (CO₂) to the atmosphere. Belite Portland clinker is characterized by having a low content of calcium oxide (CaO), causing the presence of alite to diminish and favoring the formation of belite (β-Ca₂SiO₄, C₂S), so production of clinker requires a reduced energy consumption (1350 kJ kg-1), releasing less CO₂ to the atmosphere. Conventionally, β-Ca₂SiO₄ is synthetized by the calcination of calcium carbonate (CaCO₃) and silicon dioxide (SiO₂) through the reaction in solid state at temperatures greater than 1300 °C. Resulting belite shows low hydraulic reactivity. Therefore, this study concerns a new simple modified combustion method for the synthesis of two belite cements at low temperatures (1000 °C). Silica fume, as subproduct of metallurgic industry and commercial natural zeolite were utilized as raw materials. These are considered low-cost materials and were utilized with no additional purification process. Belite cements properties were characterized by XRD, SEM, EDS and BET techniques. Hydration capacity of belite cements was calculated while the mechanical strength was determined in ordinary Portland cement specimens (PC) with a 10% partial replacement of the belite cements obtained. Results showed belite cements presented relatively high surface áreas, at early ages mechanical strengths similar to those of alite cement and comparable to strengths of belite cements obtained by different synthesis methods. Cements obtained in this work present good hydraulic reactivity properties.

Keywords: belite, silica fume, zeolite, hydraulic reactivity

Procedia PDF Downloads 342

Authors: Janet Lynn S. Montemayor

Abstract:

Dropping survivability and rising drop-out rate in the graduate school is attributed to the demands that come along with research-related requirements. Graduate students tend to withdraw from their studies when confronted with such requirements. This act of succumbing to the challenge is primarily due to a negative mindset. An understanding of students’ view towards research is essential for teachers in facilitating research activities in the graduate school. This study aimed to develop a tool that accurately measures attitude towards research. Psychometric properties of the Research Attitude Inventory (RAIn) was assessed. A pool of items (k=50) was initially constructed and was administered to a development sample composed of Masters and Doctorate degree students (n=159). Results show that the RAIn is a reliable measure of research attitude (k=41, αmax = 0.894). Principal component analysis using orthogonal rotation with Kaiser normalization identified four underlying factors of research attitude, namely predisposition, purpose, perspective, and preparation. Research attitude among the respondents was analyzed using this measure.

Keywords: graduate education, principal component analysis, research attitude, scale development

Procedia PDF Downloads 189

Authors: Paulina Zavistanaviciute, Vita Krungleviciute, Elena Bartkiene

Abstract:

Lactic acid bacteria (LAB) are microbial supplements that increase the nutritional, therapeutic, and safety value of food and feed. Often LAB strains are incubated in an expensive commercially available de Man-Rogosa-Sharpe (MRS) medium; the cultures are centrifuged, and the cells are washing with sterile water. Potato juice and apple juice industry bio-products are industrial wastes which may constitute a source of digestible nutrients for microorganisms. Due to their low cost and good chemical composition, potato juice and apple juice production bio- products could have a potential application in LAB encapsulation. In this study, pure LAB (P. acidilactici and P. pentosaceus) were multiplied in a crushed potato juice and apple juice industry bio-products medium. Before using, bio-products were sterilized and filtered. No additives were added to mass, except apple juice industry bioproducts were diluted with sterile water (1/5; v/v). The tap of sterilised mass, and LAB cell suspension (5 mL), containing of 8.9 log10 colony-forming units (cfu) per mL of the P. acidilactici and P. pentosaceus was used to multiply the LAB for 72 h. The final colony number in the potato juice and apple juice bio- products substrate was on average 9.60 log10 cfu/g. In order to stabilize the LAB, several methods of dehydration have been tested: lyophilisation (MilrockKieffer Lane, Kingston, USA) and dehydration in spray drying system (SD-06, Keison, Great Britain). Into the spray drying system multiplied LAB in a crushed potato juice and apple juice bio-products medium was injected in peristaltic way (inlet temperature +60 °C, inlet air temperature +150° C, outgoing air temperature +80 °C, air flow 200 m3/h). After lyophilisation (-48 °C) and spray drying (+150 °C) the viable cell concentration in the fermented potato juice powder was 9.18 ± 0.09 log10 cfu/g and 9.04 ± 0.07 log10 cfu/g, respectively, and in apple mass powder 8.03 ± 0.04 log10 cfu/g and 7.03 ± 0.03 log10 cfu/g, respectively. Results indicated that during the storage (after 12 months) at room temperature (22 +/- 2 ºC) LAB count in dehydrated products was 5.18 log10 cfu/g and 7.00 log10 cfu/g (in spray dried and lyophilized potato juice powder, respectively), and 3.05 log10 cfu/g and 4.10 log10 cfu/g (in spray dried and lyophilized apple juice industry bio-products powder, respectively). According to obtained results, potato juice could be used as alternative substrate for P. acidilactici and P. pentosaceus cultivation, and by drying received powders can be used in food/feed industry as the LAB starters. Therefore, apple juice industry by- products before spray drying and lyophilisation should be modified (i. e. by using different starches) in order to improve its encapsulation.

Keywords: bio-products, encapsulation, lactic acid bacteria, sustainability

Procedia PDF Downloads 273

Authors: Pawan Kumar, Dhananjoy Shaw, Manoj Kumar Rathi

Abstract:

Purpose of the study were to compare between (a) frequencies among the four quartiles of percentile norms of autonomic variables from power events and (b) frequencies among the four quartiles percentile norms of autonomic variables from aerobic events of Indian sportspersons withdrawn from competitive games and sports in regard to number of samples falling in each quartile. The study was conducted on 430 males of 30 to 35 years of age. Based on the nature of game/sports the retired sportspersons were classified into power events (throwers, judo players, wrestlers, short distance swimmers, cricket fast bowlers and power lifters) and aerobic events (long distance runners, long distance swimmers, water polo players). Date was collected using ECG polygraphs. Data were processed and extracted using frequency domain analysis and time domain analysis. Collected data were computed with frequency, percentage of each quartile and finally the frequencies were compared with the chi square analysis. The finding pertaining to norm reference comparison of frequencies among the four quartiles of Indian sportspersons withdrawn from competitive games and sports from (a) power events suggests that frequency distribution in four quartile namely Q1, Q2, Q3, and Q4 are significantly different at .05 level in regard to variables namely, SDNN, Total Power (Absolute Power), HF (Absolute Power), LF (Normalized Power), HF (Normalized Power), LF/HF ratio, deep breathing test, expiratory respiratory ratio, valsalva manoeuvre, hand grip test, cold pressor test and lying to standing test, whereas, insignificantly different at .05 level in regard to variables namely, SDSD, RMSSD, SDANN, NN50 Count, pNN50 Count, LF (Absolute Power) and 30: 15 Ratio (b) aerobic events suggests that frequency distribution in four quartile are significantly different at .05 level in regard to variables namely, SDNN, LF (Normalized Power), HF (Normalized Power), LF/HF ratio, deep breathing test, expiratory respiratory ratio, hand grip test, cold pressor test, lying to standing test and 30: 15 ratio, whereas, insignificantly different at .05 level in regard to variables namely, SDSD, RMSSD. SDANN, NN50 count, pNN50 count, Total Power (Absolute Power), LF(Absolute Power) HF(Absolute Power), and valsalva manoeuvre. The study concluded that comparison of frequencies among the four quartiles of Indian retired sportspersons from power events and aerobic events are different in four quartiles in regard to selected autonomic functions, hence the developed percentile norms are not homogenously distributed across the percentile scale; hence strengthen the percentage distribution towards normal distribution.

Keywords: power, aerobic, absolute power, normalized power

Procedia PDF Downloads 349