Search results for: driven pendulum
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1540

Search results for: driven pendulum

1240 Active Control Effects on Dynamic Response of Elevated Water Storage Tanks

Authors: Ali Etemadi, Claudia Fernanda Yasar

Abstract:

Elevated water storage tank structures (EWSTs) are high elevated-ponderous structural systems and very vulnerable to seismic vibrations. In past earthquake events, many of these structures exhibit poor performance and experienced severe damage. The dynamic analysis of the EWSTs under earthquake loads is, therefore, of significant importance for the design of the structure and a key issue for the development of modern methods, such as active control design. In this study, a reduced model of the EWSTs is explained, which is based on a tuned mass damper model (TMD). Vibration analysis of a structure under seismic excitation is presented and then used to propose an active vibration controller. MATLAB/Simulink is employed for dynamic analysis of the system and control of the seismic response. A single degree of freedom (SDOF) and two degree of freedom (2DOF) models of ELSTs are going to be used to study the concept of active vibration control. Lab-scale experimental models similar to pendulum are applied to suppress vibrations in ELST under seismic excitation. One of the most important phenomena in liquid storage tanks is the oscillation of fluid due to the movements of the tank body because of its base motions during an earthquake. Simulation results illustrate that the EWSTs vibration can be reduced by means of an input shaping technique that takes into account the dominant mode shape of the structure. Simulations with which to guide many of our designs are presented in detail. A simple and effective real-time control for seismic vibration damping can be, therefore, design and built-in practice.

Keywords: elevated water storage tank, tuned mass damper model, real time control, shaping control, seismic vibration control, the laplace transform

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1239 Development of Pre-Mitigation Measures and Its Impact on Life-Cycle Cost of Facilities: Indian Scenario

Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

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1238 Application of Data Driven Based Models as Early Warning Tools of High Stream Flow Events and Floods

Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

Abstract:

The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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1237 A Corpus Study of English Verbs in Chinese EFL Learners’ Academic Writing Abstracts

Authors: Shuaili Ji

Abstract:

The correct use of verbs is an important element of high-quality research articles, and thus for Chinese EFL learners, it is significant to master characteristics of verbs and to precisely use verbs. However, some researches have shown that there are differences in using verbs between learners and native speakers and learners have difficulty in using English verbs. This corpus-based quantitative research can enhance learners’ knowledge of English verbs and promote the quality of research article abstracts even of the whole academic writing. The aim of this study is to find the differences between learners’ and native speakers’ use of verbs and to study the factors that contribute to those differences. To this end, the research question is as follows: What are the differences between most frequently used verbs by learners and those by native speakers? The research question is answered through a study that uses corpus-based data-driven approach to analyze the verbs used by learners in their abstract writings in terms of collocation, colligation and semantic prosody. The results show that: (1) EFL learners obviously overused ‘be, can, find, make’ and underused ‘investigate, examine, may’. As to modal verbs, learners obviously overused ‘can’ while underused ‘may’. (2) Learners obviously overused ‘we find + object clauses’ while underused ‘nouns (results, findings, data) + suggest/indicate/reveal + object clauses’ when expressing research results. (3) Learners tended to transfer the collocation, colligation and semantic prosody of shǐ and zuò to make. (4) Learners obviously overused ‘BE+V-ed’ and used BE as the main verb. They also obviously overused the basic forms of BE such as be, is, are, while obviously underused its inflections (was, were). These results manifested learners’ lack of accuracy and idiomatic property in verb usage. Due to the influence of the concept transfer of Chinese, the verbs in learners’ abstracts showed obvious transfer of mother language. In addition, learners have not fully mastered the use of verbs, avoiding using complex colligations to prevent errors. Based on these findings, the present study has implications for English teaching, seeking to have implications for English academic abstract writing in China. Further research could be undertaken to study the use of verbs in the whole dissertation to find out whether the characteristic of the verbs in abstracts can apply in the whole dissertation or not.

Keywords: academic writing abstracts, Chinese EFL learners, corpus-based, data-driven, verbs

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1236 The Noun-Phrase Elements on the Usage of the Zero Article

Authors: Wen Zhen

Abstract:

Compared to content words, function words have been relatively overlooked by English learners especially articles. The article system, to a certain extent, becomes a resistance to know English better, driven by different elements. Three principal factors can be summarized in term of the nature of the articles when referring to the difficulty of the English article system. However, making the article system more complex are difficulties in the second acquisition process, for [-ART] learners have to create another category, causing even most non-native speakers at proficiency level to make errors. According to the sequences of acquisition of the English article, it is showed that the zero article is first acquired and in high inaccuracy. The zero article is often overused in the early stages of L2 acquisition. Although learners at the intermediate level move to underuse the zero article for they realize that the zero article does not cover any case, overproduction of the zero article even occurs among advanced L2 learners. The aim of the study is to investigate noun-phrase factors which give rise to incorrect usage or overuse of the zero article, thus providing suggestions for L2 English acquisition. Moreover, it enables teachers to carry out effective instruction that activate conscious learning of students. The research question will be answered through a corpus-based, data- driven approach to analyze the noun-phrase elements from the semantic context and countability of noun-phrases. Based on the analysis of the International Thurber Thesis corpus, the results show that: (1) Although context of [-definite,-specific] favored the zero article, both[-definite,+specific] and [+definite,-specific] showed less influence. When we reflect on the frequency order of the zero article , prototypicality plays a vital role in it .(2)EFL learners in this study have trouble classifying abstract nouns as countable. We can find that it will bring about overuse of the zero article when learners can not make clear judgements on countability altered from (+definite ) to (-definite).Once a noun is perceived as uncountable by learners, the choice would fall back on the zero article. These findings suggest that learners should be engaged in recognition of the countability of new vocabulary by explaining nouns in lexical phrases and explore more complex aspects such as analysis dependent on discourse.

Keywords: noun phrase, zero article, corpus, second language acquisition

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1235 The Prospects of Leveraging (Big) Data for Accelerating a Just Sustainable Transition around Different Contexts

Authors: Sombol Mokhles

Abstract:

This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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1234 Balancing Electricity Demand and Supply to Protect a Company from Load Shedding: A Review

Authors: G. W. Greubel, A. Kalam

Abstract:

South Africa finds itself at a confluence of forces where the national electricity supply system is constrained with under-supply primarily from old and failing coal-fired power stations and congested and inadequate transmission and distribution systems. Simultaneously the country attempts to meet carbon reduction targets driven by both an alignment with international goals and a consumer-driven requirement. The constrained electricity system is an aspect of an economy characterized by very low economic growth, high unemployment, and frequent and significant load shedding. The fiscus does not have the funding to build new generation capacity or strengthen the grid. The under-supply is increasingly alleviated by the penetration of wind and solar generation capacity and embedded roof-top solar. However, this increased penetration results in less inertia, less synchronous generation, and less capability for fast frequency response, with resultant instability. The renewable energy facilities assist in solving the under-supply issues, but merely ‘kick the can down the road’ by not contributing to grid stability or by substituting the lost inertia, thus creating an expanding issue for the grid to manage. By technically balancing its electricity demand and supply a company with facilities located across the country can be spared the effects of load shedding, and thus ensure financial and production performance, protect jobs, and contribute meaningfully to the economy. By treating the company’s load (across the country) and its various distributed generation facilities as a ‘virtual grid’ which by design will provide ancillary services to the grid one is able to create a win-win situation for both the company and the grid. This paper provides a review of the technical problems facing the South African electricity system and discusses a hypothetical ‘virtual grid’ concept that may assist in solving the problems. The proposed solution has potential application across emerging markets with constrained power infrastructure or for companies who wish to be entirely powered by renewable energy.

Keywords: load shedding, renewable energy integration, smart grid, virtual grid

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1233 Ownership and Shareholder Schemes Effects on Airport Corporate Strategy in Europe

Authors: Dimitrios Dimitriou, Maria Sartzetaki

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In the early days of the of civil aviation, airports are totally state-owned companies under the control of national authorities or regional governmental bodies. From that time the picture has totally changed and airports privatisation and airport business commercialisation are key success factors to stimulate air transport demand, generate revenues and attract investors, linked to reliable and resilience of air transport system. Nowadays, airport's corporate strategy deals with policies and actions, affecting essential the business plans, the financial targets and the economic footprint in a regional economy they serving. Therefore, exploring airport corporate strategy is essential to support the decision in business planning, management efficiency, sustainable development and investment attractiveness on one hand; and define policies towards traffic development, revenues generation, capacity expansion, cost efficiency and corporate social responsibility. This paper explores key outputs in airport corporate strategy for different ownership schemes. The airport corporations are grouped in three major schemes: (a) Public, in which the public airport operator acts as part of the government administration or as a corporised public operator; (b) Mixed scheme, in which the majority of the shares and the corporate strategy is driven by the private or the public sector; and (c) Private, in which the airport strategy is driven by the key aspects of globalisation and liberalisation of the aviation sector. By a systemic approach, the key drivers in corporate strategy for modern airport business structures are defined. Key objectives are to define the key strategic opportunities and challenges and assess the corporate goals and risks towards sustainable business development for each scheme. The analysis based on an extensive cross-sectional dataset for a sample of busy European airports providing results on corporate strategy key priorities, risks and business models. The conventional wisdom is to highlight key messages to authorities, institutes and professionals on airport corporate strategy trends and directions.

Keywords: airport corporate strategy, airport ownership, airports business models, corporate risks

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1232 Unravelling the Knot: Towards a Definition of ‘Digital Labor’

Authors: Marta D'Onofrio

Abstract:

The debate on the digitalization of the economy has raised questions about how both labor and the regulation of work processes are changing due to the introduction of digital technologies in the productive system. Within the literature, the term ‘digital labor’ is commonly used to identify the impact of digitalization on labor. Despite the wide use of this term, it is still not available an unambiguous definition of it, and this could create confusion in the use of terminology and in the attempts of classification. As a consequence, the purpose of this paper is to provide for a definition and to propose a classification of ‘digital labor’, resorting to the theoretical approach of organizational studies.

Keywords: digital labor, digitalization, data-driven algorithms, big data, organizational studies

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1231 Revolutionizing Legal Drafting: Leveraging Artificial Intelligence for Efficient Legal Work

Authors: Shreya Poddar

Abstract:

Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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1230 The Importance of Intellectual Property for Universities of Technology in South Africa: Challenges Faced and Proposed Way Forward

Authors: Martha E. Ikome, John M. Ikome

Abstract:

Intellectual property should be a day-to-day business decision due to its value, but increasingly, a number of institution are still not aware of the importance. Intellectual Property (IP) and its value are often not adequately appreciated. In the increasingly knowledge-driven economy, IP is a key consideration in day-to-day business decisions because new ideas and products appear almost daily in the market, which results in continuous innovation and research. Therefore, this paper will focus on the importance of IP for universities of technology and also further demonstrates how IP can become an economic tool and the challenges faced by these universities in implementing an IP system.

Keywords: intellectual property, institutions, challenges, protection

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1229 The Nexus between Social Entrepreneurship and Youth Empowerment

Authors: Aaron G. Laylo

Abstract:

This paper mainly assumes that social entrepreneurship contributes significantly to youth empowerment i.e., work and community engagement. Two questions are thus raised in order to establish this hypothesis: 1) First, how does social entrepreneurship contribute to youth empowerment?; and 2) secondly, why is social entrpreneurship significantly incremental to youth empowerment? This research aims a) to investigate on the social aspect of entrepreneurship; b) to explore challenges in youth empowerment particularly in respect to work and community engagement; and c) to inquire into whether social enterprises have truly served as a catalyst for, thus an effective response to, youth empowerment. It must be emphasized that young people, which comprise 1.8 billion in a world of seven billion are an asset; Apparently, how to maximize that potential is crucial. By utilizing exploratory research design, the paper endeavors to generate new ideas in regards to both components, develop tentative theories on social entrepreneurship, and refine certain issues that are under observation and seek scholarly attention— a rather emerging phenomenon vis a vis the challenge to empower a significant cluster of the society. Case studies will be utilized as an approach in order to comparatively analyze youth-driven social enterprises in the Philippines that have been widely recognized as successful insofar as social impact is concerned. As most scholars attested, social entrepreneurship is still at its infancy stage. Youth empowerment, meanwhile, is yet a vast area to explore insofar as academic research is concerned. Programs and projects that advocate the pursuit of these components abound. However, academic research is yet to be undertaken to see and understand their social and economic relevance. This research is also an opportunity for scholars to explore, understand, and make sense of the promise that lies in social entrepreneurship research and how it can serve as a catalyst for youth empowerment. Youth-driven social enterprises can be an influential tool in sustaining development across the globe as they intend to provide opportunities for optimal economic productivity that recognizes social inclusion. Ultimately, this study should be able to contribute to both research and development-in-practice communities for the greater good of the society. By establishing the nexus between these two components, the research may contribute to fostering greater exploration of the benefits that both may yield to human progress as well as the gaps that have to be filled in by various policy stakeholders relevant to these units.

Keywords: social entpreneurship, youth, empowerment, social inclusion

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1228 Machine Learning Framework: Competitive Intelligence and Key Drivers Identification of Market Share Trends among Healthcare Facilities

Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

Abstract:

The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

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1227 Exploring the History of Chinese Music Acoustic Technology through Data Fluctuations

Authors: Yang Yang, Lu Xin

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The study of extant musical sites can provide a side-by-side picture of historical ethnomusicological information. In their data collection on Chinese opera houses, researchers found that one Ming Dynasty opera house reached a width of nearly 18 meters, while all opera houses of the same period and after it was far from such a width, being significantly smaller than 18 meters. The historical transient fluctuations in the data dimension of width that caused Chinese theatres to fluctuate in the absence of construction scale constraints have piqued the interest of researchers as to why there is data variation in width. What factors have contributed to the lack of further expansion in the width of theatres? To address this question, this study used a comparative approach to conduct a venue experiment between this theater stage and another theater stage for non-heritage opera performances, collecting the subjective perceptions of performers and audiences at different theater stages, as well as combining BK Connect platform software to measure data such as echo and delay. From the subjective and objective results, it is inferred that the Chinese ancients discovered and understood the acoustical phenomenon of the Haas effect by exploring the effect of stage width on musical performance and appreciation of listening states during the Ming Dynasty and utilized this discovery to serve music in subsequent stage construction. This discovery marked a node of evolution in Chinese architectural acoustics technology driven by musical demands. It is also instructive to note that, in contrast to many of the world's "unsuccessful civilizations," China can use a combination of heritage and intangible cultural research to chart a clear, demand-driven course for the evolution of human music technology, and that the findings of such research will complete the course of human exploration of music acoustics. The findings of such research will complete the journey of human exploration of music acoustics, and this practical experience can be applied to the exploration and understanding of other musical heritage base data.

Keywords: Haas effect, musical acoustics, history of acoustical technology, Chinese opera stage, structure

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1226 Diversifying Nigeria's Economy Using Tourism as a Richer Alternative to Oil

Authors: Aly Audu Fada

Abstract:

The mono-economic structure of Nigerian economy has made it depend on oil for so many years. Apart from the negative effect of its exploitation, relying solely on oil as the major source of revenue for peddling the ship of development is myopic. The crumbling oil price in the world market is one proof of the dangers of this over-dependence. This paper highlights the consequences of the oil-driven economy and explores the various opportunities that are accessible in tourism through a contextual analysis. It is recommended that those at the helm of affairs should initiate collaboration between the public and private sectors to explore and harness the rich tourism resources naturally dispersed across the country to achieve the objectives of economic transformation agenda of the Federal Government.

Keywords: diversifying, economic, tourism, oil

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1225 The Thinking of Dynamic Formulation of Rock Aging Agent Driven by Data

Authors: Longlong Zhang, Xiaohua Zhu, Ping Zhao, Yu Wang

Abstract:

The construction of mines, railways, highways, water conservancy projects, etc., have formed a large number of high steep slope wounds in China. Under the premise of slope stability and safety, the minimum cost, green and close to natural wound space repair, has become a new problem. Nowadays, in situ element testing and analysis, monitoring, field quantitative factor classification, and assignment evaluation will produce vast amounts of data. Data processing and analysis will inevitably differentiate the morphology, mineral composition, physicochemical properties between rock wounds, by which to dynamically match the appropriate techniques and materials for restoration. In the present research, based on the grid partition of the slope surface, tested the content of the combined oxide of rock mineral (SiO₂, CaO, MgO, Al₂O₃, Fe₃O₄, etc.), and classified and assigned values to the hardness and breakage of rock texture. The data of essential factors are interpolated and normalized in GIS, which formed the differential zoning map of slope space. According to the physical and chemical properties and spatial morphology of rocks in different zones, organic acids (plant waste fruit, fruit residue, etc.), natural mineral powder (zeolite, apatite, kaolin, etc.), water-retaining agent, and plant gum (melon powder) were mixed in different proportions to form rock aging agents. To spray the aging agent with different formulas on the slopes in different sections can affectively age the fresh rock wound, providing convenience for seed implantation, and reducing the transformation of heavy metals in the rocks. Through many practical engineering practices, a dynamic data platform of rock aging agent formula system is formed, which provides materials for the restoration of different slopes. It will also provide a guideline for the mixed-use of various natural materials to solve the complex, non-uniformity ecological restoration problem.

Keywords: data-driven, dynamic state, high steep slope, rock aging agent, wounds

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1224 Rapid and Sensitive Detection: Biosensors as an Innovative Analytical Tools

Authors: Sylwia Baluta, Joanna Cabaj, Karol Malecha

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The evolution of biosensors was driven by the need for faster and more versatile analytical methods for application in important areas including clinical, diagnostics, food analysis or environmental monitoring, with minimum sample pretreatment. Rapid and sensitive neurotransmitters detection is extremely important in modern medicine. These compounds mainly occur in the brain and central nervous system of mammals. Any changes in the neurotransmitters concentration may lead to many diseases, such as Parkinson’s or schizophrenia. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements.

Keywords: adrenaline, biosensor, dopamine, laccase, tyrosinase

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1223 Plethora of Drivers Transforming Colonial Cities: The Case of Allahabad

Authors: Akanksha Gupta, Vishal Dubey

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In the Neoliberal era, there has been a much-talked discourse about urban issues that arise from a narrow approach of the single rationality of market-driven planning in Indian cities. More to this, India's urban planning is already jeopardized by the captious shortage of infrastructure, a cluster of incoherent governing bodies and implementation mechanism, leading cities to lie in the plethora of urban challenges. In this context, Allahabad (now known as Prayagraj) a city in North India is not an exception. Once known as the most planned splendid Colonial city of the British regime in India collapsed phenomenally because of the incompetent approach of planning machinery, straightforward market-driven accession and lack of attention on urban equity and sustainability. Particularly Civil Lines a Colonial neighbourhood, reached to the zenith of the glorified legacy of the Colonial era, transformed into filthy and congested urban form. Contextually this study contemplates and assesses the chronological episodes of major changes in land management reforms and policies under the ad hoc approach of political economy and land use planning which radically degraded the living environment in the present context. This study would empirically showcase the selected sample area detailing some of the major consequences in terms of gradual change in urban morphology, land use, and function. Here the method of study is primarily a qualitative study implying oral history and other historical methods to exhibit the idiom of planning conundrum. This subsequently reflects the repercussions translated into major issues like unclear land titles, encroachment, and unauthorized development and mushrooming of informal and squatter settlements. In nutshell, the study seeks to distinct out the limitations of the land reform and land management policies, which impacted the general degradation to the beautiful setting of Colonial neighbourhood. The Colonial legacy of Civil Lines now exists in the traces of history- memories of people, who once took pride in its serenity have now witnessed the transformation bit by bit till neo-liberal market forces completely swallow it.

Keywords: civil lines, land reforms, policies, urban challenges

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1222 Efficient Utilization of Negative Half Wave of Regulator Rectifier Output to Drive Class D LED Headlamp

Authors: Lalit Ahuja, Nancy Das, Yashas Shetty

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LED lighting has been increasingly adopted for vehicles in both domestic and foreign automotive markets. Although this miniaturized technology gives the best light output, low energy consumption, and cost-efficient solutions for driving, the same is the need of the hour. In this paper, we present a methodology for driving the highest class two-wheeler headlamp with regulator and rectifier (RR) output. Unlike usual LED headlamps, which are driven by a battery, regulator, and rectifier (RR) driven, a low-cost and highly efficient LED Driver Module (LDM) is proposed. The positive half of magneto output is regulated and used to charge batteries used for various peripherals. While conventionally, the negative half was used for operating bulb-based exterior lamps. But with advancements in LED-based headlamps, which are driven by a battery, this negative half pulse remained unused in most of the vehicles. Our system uses negative half-wave rectified DC output from RR to provide constant light output at all RPMs of the vehicle. With the negative rectified DC output of RR, we have the advantage of pulsating DC input which periodically goes to zero, thus helping us to generate a constant DC output equivalent to the required LED load, and with a change in RPM, additional active thermal bypass circuit help us to maintain the efficiency and thermal rise. The methodology uses the negative half wave output of the RR along with a linear constant current driver with significantly higher efficiency. Although RR output has varied frequency and duty cycles at different engine RPMs, the driver is designed such that it provides constant current to LEDs with minimal ripple. In LED Headlamps, a DC-DC switching regulator is usually used, which is usually bulky. But with linear regulators, we’re eliminating bulky components and improving the form factor. Hence, this is both cost-efficient and compact. Presently, output ripple-free amplitude drivers with fewer components and less complexity are limited to lower-power LED Lamps. The focus of current high-efficiency research is often on high LED power applications. This paper presents a method of driving LED load at both High Beam and Low Beam using the negative half wave rectified pulsating DC from RR with minimum components, maintaining high efficiency within the thermal limitations. Linear regulators are significantly inefficient, with efficiencies typically about 40% and reaching as low as 14%. This leads to poor thermal performance. Although they don’t require complex and bulky circuitry, powering high-power devices is difficult to realise with the same. But with the input being negative half wave rectified pulsating DC, this efficiency can be improved as this helps us to generate constant DC output equivalent to LED load minimising the voltage drop on the linear regulator. Hence, losses are significantly reduced, and efficiency as high as 75% is achieved. With a change in RPM, DC voltage increases, which can be managed by active thermal bypass circuitry, thus resulting in better thermal performance. Hence, the use of bulky and expensive heat sinks can be avoided. Hence, the methodology to utilize the unused negative pulsating DC output of RR to optimize the utilization of RR output power and provide a cost-efficient solution as compared to costly DC-DC drivers.

Keywords: class D LED headlamp, regulator and rectifier, pulsating DC, low cost and highly efficient, LED driver module

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1221 A Goal-Oriented Social Business Process Management Framework

Authors: Mohammad Ehson Rangiha, Bill Karakostas

Abstract:

Social Business Process Management (SBPM) promises to overcome limitations of traditional BPM by allowing flexible process design and enactment through the involvement of users from a social community. This paper proposes a meta-model and architecture for socially driven business process management systems. It discusses the main facets of the architecture such as goal-based role assignment that combines social recommendations with user profile, and process recommendation, through a real example of a charity organization.

Keywords: business process management, goal-based modelling, process recommendation social collaboration, social BPM

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1220 Active Features Determination: A Unified Framework

Authors: Meenal Badki

Abstract:

We address the issue of active feature determination, where the objective is to determine the set of examples on which additional data (such as lab tests) needs to be gathered, given a large number of examples with some features (such as demographics) and some examples with all the features (such as the complete Electronic Health Record). We note that certain features may be more costly, unique, or laborious to gather. Our proposal is a general active learning approach that is independent of classifiers and similarity metrics. It allows us to identify examples that differ from the full data set and obtain all the features for the examples that match. Our comprehensive evaluation shows the efficacy of this approach, which is driven by four authentic clinical tasks.

Keywords: feature determination, classification, active learning, sample-efficiency

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1219 Macroeconomic Implications of Artificial Intelligence on Unemployment in Europe

Authors: Ahmad Haidar

Abstract:

Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

Procedia PDF Downloads 48
1218 Development of a Model for the Redesign of Plant Structures

Authors: L. Richter, J. Lübkemann, P. Nyhuis

Abstract:

In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: change driven factory redesign, factory planning, plant structure, flexibility

Procedia PDF Downloads 248
1217 Adsorption Cooling Using Hybrid Energy Resources

Authors: R. Benelmir, M. El Kadri, A. Donnot, D. Descieux

Abstract:

HVAC represents a significant part of energy needs in buildings. Integrating renewable energy in cooling processes contributes to reducing primary energy consumption. Sorption refrigeration allows cold production through the use of solar/biomass/geothermal energy or even valuation of waste heat. This work presents an analysis of an experimental bench incorporating an adsorption chiller driven by hybrid energy resources associating solar thermal collectors with a cogeneration gas engine and a geothermal heat pump.

Keywords: solar cooling, cogeneration, geothermal heat pump, hybrid energy resources

Procedia PDF Downloads 327
1216 A Deep Learning Approach for the Predictive Quality of Directional Valves in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 200
1215 An Analysis and Design of Mobile Payment System Based on NFC Technology

Authors: Shafiq ur Rehman, Zubair Ahmed Shaikh

Abstract:

This research provides the comparative study of different mobile payment system and proposes an efficient solution of mobile payment system. The research involves discovering how the mobile payment methods can be used and implemented keeping user and system interaction under consideration. The implementation of Nielsen’s heuristic and universal design principles enhanced the user’s interaction design and made the system more appropriate, understandable and visible to the end user. The design of application is greatly affected by the user driven factors. These factors help in the efficiency of the application usage.

Keywords: mobile payment system, m-commerce, usability, near field communication

Procedia PDF Downloads 416
1214 CMMI Key Process Areas and FDD Practices

Authors: Rituraj Deka, Nomi Baruah

Abstract:

The development of information technology during the past few years resulted in designing of more and more complex software. The outsourcing of software development makes a higher requirement for the management of software development project. Various software enterprises follow various paths in their pursuit of excellence, applying various principles, methods and techniques along the way. The new research is proving that CMMI and Agile methodologies can benefit from using both methods within organizations with the potential to dramatically improve business performance. The paper describes a mapping between CMMI key process areas (KPAs) and Feature-Driven Development (FDD) communication perspective, so as to increase the understanding of how improvements can be made in the software development process.

Keywords: Agile, CMMI, FDD, KPAs

Procedia PDF Downloads 430
1213 Sales Patterns Clustering Analysis on Seasonal Product Sales Data

Authors: Soojin Kim, Jiwon Yang, Sungzoon Cho

Abstract:

As a seasonal product is only in demand for a short time, inventory management is critical to profits. Both markdowns and stockouts decrease the return on perishable products; therefore, researchers have been interested in the distribution of seasonal products with the aim of maximizing profits. In this study, we propose a data-driven seasonal product sales pattern analysis method for individual retail outlets based on observed sales data clustering; the proposed method helps in determining distribution strategies.

Keywords: clustering, distribution, sales pattern, seasonal product

Procedia PDF Downloads 568
1212 The Return of the Rejected Kings: A Comparative Study of Governance and Procedures of Standards Development Organizations under the Theory of Private Ordering

Authors: Olia Kanevskaia

Abstract:

Standardization has been in the limelight of numerous academic studies. Typically described as ‘any set of technical specifications that either provides or is intended to provide a common design for a product or process’, standards do not only set quality benchmarks for products and services, but also spur competition and innovation, resulting in advantages for manufacturers and consumers. Their contribution to globalization and technology advancement is especially crucial in the Information and Communication Technology (ICT) and telecommunications sector, which is also characterized by a weaker state-regulation and expert-based rule-making. Most of the standards developed in that area are interoperability standards, which allow technological devices to establish ‘invisible communications’ and to ensure their compatibility and proper functioning. This type of standard supports a large share of our daily activities, ranging from traffic coordination by traffic lights to the connection to Wi-Fi networks, transmission of data via Bluetooth or USB and building the network architecture for the Internet of Things (IoT). A large share of ICT standards is developed in the specialized voluntary platforms, commonly referred to as Standards Development Organizations (SDOs), which gather experts from various industry sectors, private enterprises, governmental agencies and academia. The institutional architecture of these bodies can vary from semi-public bodies, such as European Telecommunications Standards Institute (ETSI), to industry-driven consortia, such as the Internet Engineering Task Force (IETF). The past decades witnessed a significant shift of standard setting to those institutions: while operating independently from the states regulation, they offer a rather informal setting, which enables fast-paced standardization and places technical supremacy and flexibility of standards above other considerations. Although technical norms and specifications developed by such nongovernmental platforms are not binding, they appear to create significant regulatory impact. In the United States (US), private voluntary standards can be used by regulators to achieve their policy objectives; in the European Union (EU), compliance with harmonized standards developed by voluntary European Standards Organizations (ESOs) can grant a product a free-movement pass. Moreover, standards can de facto manage the functioning of the market when other regulative alternatives are not available. Hence, by establishing (potentially) mandatory norms, SDOs assume regulatory functions commonly exercised by States and shape their own legal order. The purpose of this paper is threefold: First, it attempts to shed some light on SDOs’ institutional architecture, focusing on private, industry-driven platforms and comparing their regulatory frameworks with those of formal organizations. Drawing upon the relevant scholarship, the paper then discusses the extent to which the formulation of technological standards within SDOs constitutes a private legal order, operating in the shadow of governmental regulation. Ultimately, this contribution seeks to advise whether a state-intervention in industry-driven standard setting is desirable, and whether the increasing regulatory importance of SDOs should be addressed in legislation on standardization.

Keywords: private order, standardization, standard-setting organizations, transnational law

Procedia PDF Downloads 125
1211 Cross-Country Differences in Homeownership: A Cultural Phenomenon?

Authors: Stefanie J. Huber, Tobias Schmidt

Abstract:

Cross-country differences in homeownership rates are large and very persistent over time, ranging between 35% in Switzerland to 80% in Spain. In this project, we test the hypothesis that these cross-country differences are driven by cultural tastes. To isolate the effect of culture from the effects of institutions and economic factors, we investigate the homeownership attitudes of second-generation immigrants in the United States. We find robust evidence that cross-country differences in cultural preferences are an important explanatory factor for the observed persistent differences in homeownership rates across countries.

Keywords: housing markets, homeownership rates, country heterogeneity, preferences, cultural transmission, migration

Procedia PDF Downloads 245