Search results for: impact noise
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12126

Search results for: impact noise

11406 The Impact of Corporate Governance Attributes on Dividends Payouts Policy: Evidence from the Emerging Capital Market of Jordan

Authors: Amneh Alkurdi, Yasean Tahat, Hamzeh Almuali

Abstract:

Purpose: The primary objective of the present paper is to examine the impact of CG attributes, including the board size, independency, separation and managerial ownership) on firm dividend payouts policy; using a sample of 72 Jordanian listed companies for the period of 2007-2013. Methodology: The study does manually review the sample firm’s annual reports for data collection and use OLS regression to carry out this investigation. Findings: The findings indicate that CG attributes have a strong impact on dividend payouts policy. In particular, board size, independency and separation have had significant associations with dividends payouts indicating that such variables matter when determining on dividends which may mitigate the conflicts between stakeholders’ and managers’ interests. The results also indicate that managerial ownership has had no significant impact on the dividends policy suggesting that managers do not use the strength of their position to influence the dividends policy. Finally, the results show that firm size and profitability have had statistically positive associations with dividend payouts, while this was not the case for firm leverage and growth where significant and positive relationships were documented. Originality/implication: The current paper extends the extant literature in this field by investigating the impact of the board composition on dividends and provides some insights for policy makers in emerging markets.

Keywords: corporate governance, dividends payouts policy, jordan, accounting

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11405 Empowerment at the Grassroots: Impact of Participatory (in) Equalities in Policy Formulation and Recognition and Redistribution of Women at the Grassroots in India

Authors: Samanwita Paul

Abstract:

Borrowing from Kabeer’s framework of empowerment, participation of women at Panchayat level politics (grassroots level of politics in India) has been conceptualized as a resource in the study and the impact of the same in influencing the policies at the grassroots as an agency. The study attempts to examine such intricacies in the dynamics of participation and policy formulation at the Panchayat level and to assess its overall impact in altering the recognition and redistribution of women. A conscious attempt has been made to go beyond formal politics and consider participants of the informal political processes as subjects of the study. Primary surveys were conducted for data collection in 4 Panchayat villages (from Jalpaiguri district in West Bengal) of which 2 wards from each were selected based on the nature of reservation of the panchayat seats. In-depth interviews with the Panchayat members and an approximate of 80 voters from each of the villages were conducted. This has been further analyzed with the aid of appropriate statistical tools and narratives. Preliminary findings show that women from vulnerable sections tend to participate more in the political process since it offers them a means of negotiating with their vulnerabilities however in case of its impact on policy formulation, the effect of women’s participation does to appear to be as profound.

Keywords: recognition, redistribution, political participation, women

Procedia PDF Downloads 136
11404 Urban Design for Autonomous Vehicles

Authors: Narjis Zehra

Abstract:

After automobile revolution 1.0, we have automobile revolution 2.0 standing at the horizon, Autonomous Vehicles (AVs). While the technology is developing into more adaptable form, the conversations around its impact on our cities have already started on multiple scales, from academic institutions and community town halls, to the offices of mayors. In order to explore more the AVs impact on Urban transformation, we first inquire if cities can be redesigned or rebuilt. Secondly, we discuss expectation management for the public and policy in terms of what people think/believe AV technology will deliver, and what the current technological evidence suggests the technology and its adoption will look like. Thirdly, based on these discussions, we take Pittsburgh, PA, as a case study to extrapolate what other cities might need to do in order to prepare themselves for the upcoming technological revolution, that may impact more than just the research institutes. Finally, we conclude by suggesting a political way forward to embed urban design with AV technology for equitable cities of tomorrow.

Keywords: urban design, autonomous vehicles, transformation, policy

Procedia PDF Downloads 106
11403 Clustering and Modelling Electricity Conductors from 3D Point Clouds in Complex Real-World Environments

Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

Abstract:

Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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11402 Cultural Heritage Impact Assessments and the Negotiation of Identity in South Africa

Authors: Rosabelle Boswell

Abstract:

South Africa, a country with experience of both colonial rule and apartheid is now more than 25 years past its first democratic elections. However, and as noted in this article, South Africa is still experiencing the legacies of racial segregation and is concerned to address inequality by attracting investment for socioeconomic development. The paper offered considers five cultural heritage impact assessments conducted in South Africa for offshore oil and gas exploration and development. The results of the research, from more than 20 towns and cities in southern Africa, indicate a rich intangible cultural heritage in South Africa and Namibia, and the potential impacts on investor engagements for more inclusive and sustainable coastal development practices. The discussion advances critical heritage studies, taking into account socioeconomic realities and aboriginal concepts of nature and nature management.

Keywords: cultural heritage impact assessments, intangible cultural heritage, South Africa, ocean philosophies

Procedia PDF Downloads 157
11401 The Use of Social Media and Its Impact on the Learning Behavior of ESL University Students for Sustainable Education in Pakistan

Authors: Abdullah Mukhtar, Shehroz Mukhtar, Amina Mukhtar, Choudhry Shahid, Hafiz Raza Razzaq, Saif Ur Rahman

Abstract:

The aim of this study is to find out the negative and positive impacts of social media platforms on the attitude of learning and educational environment of student’s community. Social Media platforms have become a source of collaboration with one another throughout the globe making it a small world. This study performs focalized investigation of the adverse and constructive factors that have a strong impact not only on the psychological adjustments but also on the academic performance of peers. This study is a quantitative research adopting random sampling method in which the participants were the students of university. Researcher distributed 1000 questionnaires among the university students from different departments and asked them to fill the data on Lickert Scale. The participants are from the age group of 18-24 years. Study applies user and gratification theory in order to examine behavior of students practicing social media in their academic and personal life. Findings of the study reveal that the use of social media platforms in Pakistani context has less positive impact as compared to negative impacts on the behavior of students towards learning. The research suggests that usage of online social media platforms should be taught to students; awareness must the created among the users of social media by the means of seminars, workshops and by media itself to overcome the negative impacts of social media leading towards sustainable education in Pakistan.

Keywords: social media, positive impact, negative impact, learning behaviour

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11400 The Impact of the European Single Market on the Austrian Economy

Authors: Reinhard Neck, Guido Schäfer

Abstract:

In this paper, we explore the macroeconomic effects of the European Single Market on Austria by simulating the McKibbin-Sachs Global Model. Global interdependence and the impact of long-run effects on short-run adjustments are taken into account. We study the sensitivity of the results with respect to different assumptions concerning monetary and fiscal policies for the countries and regions of the world economy. The consequences of different assumptions about budgetary policies in Austria are also investigated. The simulation results are contrasted with ex-post evaluations of the actual impact of Austria’s membership in the Single Market. As a result, it can be concluded that the Austrian participation in the European Single Market entails considerable long-run gains for the Austrian economy with nearly no adverse side-effects on any macroeconomic target variable.

Keywords: macroeconomics, European Union, simulation, sensitivity analysis

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11399 The Energy Consumption by the Sector of Transport and His Impact on the Atmospheric Pollution

Authors: Mme Hamani Née Guessas Ghaniya

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The transport is the base of the development of the exchanges and the business, being both a recognized determiner of the economic and social development. The development of the transport is in the center of the big challenges of development of countries, but it is also at the heart of big contradictions, since we integrate the environmental issues which are bound to him, in particular through the questions of energy. Indeed, the energy consumption by the sector of transport is one of bigger concerns, because it is increasing and it has a big impact on our environment. The main consequences are, the atmospheric pollution causing an increase of the greenhouse effect which causes a global warming. These global warming risks to engender a partial cast iron of polar caps so raising the level of seas, flooding the low coastal zones, certain islands and the deltas. Thus, the purpose of this communication is to present the impact of the energy consumption by the sector of transport on the air quality, showing its effect on the health and on the global warming.

Keywords: energy consumption, sector of transport, air quality, atmospheric pollution

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11398 Facade Design Impact on the Urban Landscape

Authors: Seyyed Hossein Alavi, Soudabe Mehri Talarposhti

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Passages urban landscape is made up of various components that the component parts of the whole and vice versa has relationships. In today’s cities, we have not seen a dual relationship and only one side of the equation which is the relationships of the component parts are considered. However, the effect of the component to whole is stronger and also longer. This means that every time the outer shell of the building was constructed instant impact on the viewers while it takes a long time to understand the impact of the building in its environment and basically, it seems city portrait has the sensory and untouchable effect on observer. Today, building facades are designated individually and in isolation from the context. Designers are familiar with the details of the facade, but they are not informed with the science of combination and its impact on portrait. The importance of city and also more important than that, the city portrait haven’t confirmed for those involved in the building and authorities and the construction been changed to a market for more glaring taste of designers and attracting more business and the city and its landscape has been forgotten. This essay is an attempt to collect a part of the principles and definitions needed on perspective issues and portrait, and it is hoped that it will open arena for more research and studies in this field and other related fields.

Keywords: facade, urban housing, urban design, sustainable architecture

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11397 Impact of Normative Institutional Factors on Sustainability Reporting

Authors: Lina Dagilienė

Abstract:

The article explores the impact of normative institutional factors on the development of sustainability reporting. The vast majority of research in the scientific literature focuses on mandatory institutional factors, i.e. how public institutions and market regulators affect sustainability reporting. Meanwhile, there is lack of empirical data for the impact of normative institutional factors. The effect of normative factors in this paper is based on the role of non-governmental organizations (NGO) and institutional theory. The case of Global Compact Local Network in the developing country was examined. The research results revealed that in the absence of regulated factors, companies were not active with regard to social disclosures; they presented non-systemized social information of a descriptive nature. Only 10% of sustainability reports were prepared using the GRI methodology. None of the reports were assured by third parties.

Keywords: institutional theory, normative, sustainability reporting, Global Compact Local Network

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11396 Impact of Economic Crisis on Secondary Education in Anambra State

Authors: Stella Nkechi Ezeaku, Ifunanya Nkechi Ohamobi

Abstract:

This study investigated the impact of economic crisis on education in Anambra state. The population of the study comprised of all principals and teachers in Anambra state numbering 5,887 (253 principles and 5,634 teachers). To guide the study, three research questions and one hypothesis were formulated correlational design was adopted. Stratified random sampling technique was used to select 200 principals and 300 teachers as respondents for the study. A researcher-developed instrument tagged Impact of Economic Crisis on Education questionnaire (IECEQ) was used to collect data needed for the study. The instrument was validated by experts in measurement and evaluation. The reliability of the instrument was established using randomly selected members of the population who did not take part in the study. The data obtained was analyzed using Cronbach alpha technique and reliability co-efficient of .801 and .803 was obtained. The data were analyzed using simple and Multiple Regression Analysis. The formulated hypothesis was tested at .05 level of significance. Findings revealed that: there is a significant relationship between economic crisis and realization of goals of secondary education. The result also shows that economic crisis affect students' academic performance, teachers' morale and productivity and principals' administrative capability. This study therefore concludes that certain strategies must be devised to minimize the impact of economic crisis on secondary education. It is recommended that all stakeholders to education should be more resourceful and self-sufficient in order to cushion the effects of economic crisis currently gripping most world economies Nigeria inclusive.

Keywords: impact, economic, crisis, education

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11395 Methods and Techniques for Lower Danube Sturgeon Monitoring Used for the Assessment of Anthropic Activities Pressures and the Quantification of Risks on These Species

Authors: Gyorgy Deak, Marius C. Raischi, Lucian P. Georgescu, Tiberius M. Danalache, Elena Holban, Madalina G. Boboc, Monica Matei, Catalina Iticescu, Marius V. Olteanu, Stefan Zamfir, Gabriel Cornateanu

Abstract:

At present, on the Lower Danube, different types of pressures have been identified that affect the anadromous sturgeons stocks with an impact that leads to their decline. This paper presents techniques and procedures used by Romanian experts in the tagging and monitoring of anadromous sturgeons, as well as unique results at international level obtained on the basis of an informational volume collected in over 7 years of monitoring on these species behavior (both for adults as well as for ultrasonically tagged juveniles) on the Lower Danube. The local impact of hydrotechnical constructions (bottom sill, maritime navigation channel), the global impact of the poaching phenomenon and the impact of the restocking programs with sturgeon juveniles were assessed. Thus, the bottom sill impact on the Bala branch, the Bastroe Channel (cross-border impact) and the poaching phenomenon at the level of the Lower Danube was analyzed on the basis of a unique informational volume obtained through the use of patented monitoring systems by the Romanian experts (DKTB respectively, DKMR-01T). At the same time, the results from the monitoring of ultrasonically tagged sturgeon juveniles from the 2015 repopulation program are presented. Conclusions resulting from research can ensure favorable premises for finding some conservation solutions for CITES-protected sturgeon species that have survived for millions of years, currently being 1 species on the brink of extinction - Russian sturgeon, 2 species in danger of extinction - Beluga sturgeon and Stellate sturgeon and 2 species already extinct from the Lower Danube, namely common sturgeon and ship sturgeon.

Keywords: Lower Danube, sturgeons monitoring (adults and juveniles), tagging, impact on conservation

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11394 Nonlinear Free Surface Flow Simulations Using Smoothed Particle Hydrodynamics

Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

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The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

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11393 Impact of Storytelling for Effective Marketing and Reputation Management of Heritage Tourism Destination with Special Reference to Haflong (Assam, India)

Authors: Rohit Sarin

Abstract:

This paper is an attempt to prove the impact of storytelling for effective marketing and maintaining the reputation of the destination for long run. This notable aspect of heritage tourism is cultural exchange among the various communities who visit our country India. Every destination has a life cycle like the product known as destination life cycle. India is considered to be the hub of cultural heritage tourism; its cultural heritage tourism can be traced back to several centuries. Heritage tourism has gained the popularity of global cuisine activity. The statistics of 2014 reveals 903 million International Tourist in heritage tourism destination is done to know the impact of storytelling for their visit to particulars heritage tourism destination. SWOT analysis of the destination is undertaken for the research purpose. A collection of data from the travel agency was taken who visited the heritage tourism destination and were asked to fill questionnaire for the research purpose to know the impact of storytelling for their visit to destination. A total of 100 respondents filled the questionnaire. Likert scale was used in the paper also highlighted the scope, advantage and disadvantage of storytelling for effective marketing and reputation management.

Keywords: destination life cycle, heritage tourism, random sampling, reputation management, storytelling

Procedia PDF Downloads 572
11392 Early Impact Prediction and Key Factors Study of Artificial Intelligence Patents: A Method Based on LightGBM and Interpretable Machine Learning

Authors: Xingyu Gao, Qiang Wu

Abstract:

Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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11391 Robustness of the Deep Chroma Extractor and Locally-Normalized Quarter Tone Filters in Automatic Chord Estimation under Reverberant Conditions

Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

Abstract:

In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

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11390 Prediction of Disability-Adjustment Mental Illness Using Machine Learning

Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

Abstract:

Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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11389 Power Series Solution to Sliding Velocity in Three-Dimensional Multibody Systems with Impact and Friction

Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

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The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge-Kutta solution using 38 time steps.

Keywords: impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision

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11388 Improving Cell Type Identification of Single Cell Data by Iterative Graph-Based Noise Filtering

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

Abstract:

Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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11387 An Efficient Approach for Shear Behavior Definition of Plant Stalk

Authors: M. R. Kamandar, J. Massah

Abstract:

The information of the impact cutting behavior of plants stalk plays an important role in the design and fabrication of plants cutting equipment. It is difficult to investigate a theoretical method for defining cutting properties of plants stalks because the cutting process is complex. Thus, it is necessary to set up an experimental approach to determine cutting parameters for a single stalk. To measure the shear force, shear energy and shear strength of plant stalk, a special impact cutting tester was fabricated. It was similar to an Izod impact cutting tester for metals but a cutting blade and data acquisition system were attached to the end of pendulum's arm. The apparatus was included four strain gages and a digital indicator to show the real-time cutting force of plant stalk. To measure the shear force and also testing the apparatus, two plants’ stalks, like buxus and privet, were selected. The samples (buxus and privet stalks) were cut under impact cutting process at four loading rates 1, 2, 3 and 4 m.s-1 and three internodes fifth, tenth and fifteenth by the apparatus. At buxus cutting analysis: the minimum value of cutting energy was obtained at fifth internode and loading rate 4 m.s-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate 1 m.s-1. At privet cutting analysis: the minimum value of shear consumption energy was obtained at fifth internode and loading rate: 4 m.s-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate: 1 m.s-1. The statistical analysis at both plants showed that the increase of impact cutting speed would decrease the shear consumption energy and shear strength. In two scenarios, the results showed that with increase the cutting speed, shear force would decrease.

Keywords: Buxus, Privet, impact cutting, shear energy

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11386 Supply Chain Network Design for Perishable Products in Developing Countries

Authors: Abhishek Jain, Kavish Kejriwal, V. Balaji Rao, Abhigna Chavda

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Increasing environmental and social concerns are forcing companies to take a fresh view of the impact of supply chain operations on environment and society when designing a supply chain. A challenging task in today’s food industry is the distribution of high-quality food items throughout the food supply chain. Improper storage and unwanted transportation are the major hurdles in food supply chain and can be tackled by making dynamic storage facility location decisions with the distribution network. Since food supply chain in India is one of the biggest supply chains in the world, the companies should also consider environmental impact caused by the supply chain. This project proposes a multi-objective optimization model by integrating sustainability in decision-making, on distribution in a food supply chain network (SCN). A Multi-Objective Mixed-Integer Linear Programming (MOMILP) model between overall cost and environmental impact caused by the SCN is formulated for the problem. The goal of MOMILP is to determine the pareto solutions for overall cost and environmental impact caused by the supply chain. This is solved by using GAMS with CPLEX as third party solver. The outcomes of the project are pareto solutions for overall cost and environmental impact, facilities to be operated and the amount to be transferred to each warehouse during the time horizon.

Keywords: multi-objective mixed linear programming, food supply chain network, GAMS, multi-product, multi-period, environment

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11385 Brexit: Implications on Banking Regulations and Conditions; An Analysis

Authors: Astha Sinha, Anjali Kanagali

Abstract:

The United Kingdom’s withdrawal from the European Union, also termed as “Brexit,” took place on June 23, 2016 and immediately had global repercussions on the stock markets of the world. It is however expected to have a greater impact on the Banking sector in the UK. There is a two-fold effect on the earnings of banks which is being expected. First is of the trading activity and investment banking businesses being hit due to global weakness in financial markets. Second is that the banks having a large presence in the European Union will have to restructure their operations in order to cover other European countries as well increase their operating costs. As per the analysis, banks are expected to face rate cuts, bad loans, and tight liquidity. The directives in the Brexit negotiations on the Markets in Financial Instruments Directive (MiFID) will be a major decision to be taken for the Banking sector. New regulations will be required since most of the regulations governing the financial services industry allowing for the cross-border transactions were at the EU level. This paper aims to analyze the effect of Brexit on the UK Banking sector and changes in regulations that are expected due to the same. It shall also lay down the lessons learnt from the 2008 financial crisis and draw a parallel in terms of potential areas to be focused on for revival of the financial sector of Britain.

Keywords: Brexit, Brexit impact on UK, impact of Brexit on banking, impact of Brexit on financial services

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11384 Image-Based UAV Vertical Distance and Velocity Estimation Algorithm during the Vertical Landing Phase Using Low-Resolution Images

Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

Abstract:

The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

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11383 Evaluation of Natural Frequency of Single and Grouped Helical Piles

Authors: Maryam Shahbazi, Amy B. Cerato

Abstract:

The importance of a systems’ natural frequency (fn) emerges when the vibration force frequency is equivalent to foundation's fn which causes response amplitude (resonance) that may cause irreversible damage to the structure. Several factors such as pile geometry (e.g., length and diameter), soil density, load magnitude, pile condition, and physical structure affect the fn of a soil-pile system; some of these parameters are evaluated in this study. Although experimental and analytical studies have assessed the fn of a soil-pile system, few have included individual and grouped helical piles. Thus, the current study aims to provide quantitative data on dynamic characteristics of helical pile-soil systems from full-scale shake table tests that will allow engineers to predict more realistic dynamic response under motions with variable frequency ranges. To evaluate the fn of single and grouped helical piles in dry dense sand, full-scale shake table tests were conducted in a laminar box (6.7 m x 3.0 m with 4.6 m high). Two different diameters (8.8 cm and 14 cm) helical piles were embedded in the soil box with corresponding lengths of 3.66m (excluding one pile with length of 3.96) and 4.27m. Different configurations were implemented to evaluate conditions such as fixed and pinned connections. In the group configuration, all four piles with similar geometry were tied together. Simulated real earthquake motions, in addition to white noise, were applied to evaluate the wide range of soil-pile system behavior. The Fast Fourier Transform (FFT) of measured time history responses using installed strain gages and accelerometers were used to evaluate fn. Both time-history records using accelerometer or strain gages were found to be acceptable for calculating fn. In this study, the existence of a pile reduced the fn of the soil slightly. Greater fn occurred on single piles with larger l/d ratios (higher slenderness ratio). Also, regardless of the connection type, the more slender pile group which is obviously surrounded by more soil, yielded higher natural frequencies under white noise, which may be due to exhibiting more passive soil resistance around it. Relatively speaking, within both pile groups, a pinned connection led to a lower fn than a fixed connection (e.g., for the same pile group the fn’s are 5.23Hz and 4.65Hz for fixed and pinned connections, respectively). Generally speaking, a stronger motion causes nonlinear behavior and degrades stiffness which reduces a pile’s fn; even more, reduction occurs in soil with a lower density. Moreover, fn of dense sand under white noise signal was obtained 5.03 which is reduced by 44% when an earthquake with the acceleration of 0.5g was applied. By knowing the factors affecting fn, the designer can effectively match the properties of the soil to a type of pile and structure to attempt to avoid resonance. The quantitative results in this study assist engineers in predicting a probable range of fn for helical pile foundations under potential future earthquake, and machine loading applied forces.

Keywords: helical pile, natural frequency, pile group, shake table, stiffness

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11382 Early Childhood Education: Working with Children, Families, and Communities for Collective Impact

Authors: Sunico Armie Flores

Abstract:

Early childhood education (ECE) is pivotal in shaping the future of individuals and society. This paper explores the collaborative efforts required among educators, families, and communities to create a collective impact on young children’s development. It delves into the importance of these partnerships, effective strategies for engagement, and the challenges and opportunities inherent in fostering such collaboration. By examining current research and practices, the paper aims to highlight the essential role of an integrated approach in achieving significant and sustainable improvements in early childhood outcomes.

Keywords: early childhood education, lifelong learning, cognitive development, socio-emotional development, educators, families, communities, collaborative efforts, collective impact, early learning environments, holistic development, high-quality ECE programs, investment in education

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11381 Performance Comparison of Non-Binary RA and QC-LDPC Codes

Authors: Ni Wenli, He Jing

Abstract:

Repeat–Accumulate (RA) codes are subclass of LDPC codes with fast encoder structures. In this paper, we consider a nonbinary extension of binary LDPC codes over GF(q) and construct a non-binary RA code and a non-binary QC-LDPC code over GF(2^4), we construct non-binary RA codes with linear encoding method and non-binary QC-LDPC codes with algebraic constructions method. And the BER performance of RA and QC-LDPC codes over GF(q) are compared with BP decoding and by simulation over the Additive White Gaussian Noise (AWGN) channels.

Keywords: non-binary RA codes, QC-LDPC codes, performance comparison, BP algorithm

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11380 Assessing the Impact of Covid-19 Pandemic on Waste Management Workers in Ghana

Authors: Mensah-Akoto Julius, Kenichi Matsui

Abstract:

This paper examines the impact of COVID-19 on waste management workers in Ghana. A questionnaire survey was conducted among 60 waste management workers in Accra metropolis, the capital region of Ghana, to understand the impact of the COVID-19 pandemic on waste generation, workers’ safety in collecting solid waste, and service delivery. To find out correlations between the pandemic and safety of waste management workers, a regression analysis was used. Regarding waste generation, the results show the pandemic led to the highest annual per capita solid waste generation, or 3,390 tons, in 2020. Regarding the safety of workers, the regression analysis shows a significant and inverse association between COVID-19 and waste management services. This means that contaminated wastes may infect field workers with COVID-19 due to their direct exposure. A rise in new infection cases would have a negative impact on the safety and service delivery of the workers. The result also shows that an increase in economic activities negatively impacts waste management workers. The analysis, however, finds no statistical relationship between workers’ service deliveries and employees’ salaries. The study then discusses how municipal waste management authorities can ensure safe and effective waste collection during the pandemic.

Keywords: Covid-19, waste management worker, waste collection, Ghana

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11379 PhD Students’ Challenges with Impact-Factor in Kazakhstan

Authors: Duishon Shamatov

Abstract:

This presentation is about Kazakhstan’s PhD students’ experiences with impact-factor publication requirement. Since the break-up of the USSR, Kazakhstan has been attempting to improve its higher education system at undergraduate and graduate levels. From March, 2010 Kazakhstan joined Bologna process and entered European space of higher education. To align with the European system of higher education, three level of preparation of specialists (undergraduate, master and PhD) was adopted to replace the Soviet system. The changes were aimed at promoting high quality higher education that meets the demands of labor market and growing needs of the industrial-innovative development of the country, and meeting the international standards. The shift to the European system has brought many benefits, but there are also some serious challenges. One of those challenges is related to the requirements for the PhD candidates to publish in national and international journals. Thus, a PhD candidate should have 7 publications in total, out of which one has to be in an international impact factor journal. A qualitative research was conducted to explore the PhD students’ views of their experiences with impact-factor publications. With the help of purposeful sampling, 30 PhD students from seven universities across Kazakhstan were selected for individual and focus group interviews. The key findings of the study are as follows. While the Kazakh PhD students have no difficulties in publishing in local journals, they face great challenges in attempting to publish in impact-factor journals for a range of reasons. They include but not limited to lack of research and publication skills, poorer knowledge of academic English, not familiarity with the peer review publication processes and expectations, and very short time to get published due to their PhD programme requirements. This situation is pushing some these young scholars explore alternative ways to get published in impact factor journals and they seek to publish by any means and often by any costs (which means even paying large sum of money for a publication). This in turn, creates a myth in the scholars’ circles in Kazakhstan, that to get published in impact factor journals, one should necessarily pay much money. This paper offers some policy recommendations on how to improve preparation of future PhD candidates in Kazakhstan.

Keywords: Bologna process, impact-factor publications, post-graduate education, Kazakhstan

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11378 The Impact of Internal and External CSR on Organizational Citizenship Behavior and Performance: Mediation of Organizational Identification and Moderation of Ethical Leadership. A Cross-Cultural Study

Authors: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

Abstract:

The hospitality sector contributes significantly to the global economy but it is also responsible for imposing adverse influences both environmentally and socially. The objective of this research is two-fold: (1) examining the direct impact of internal CSR and external CSR and indirect impact via organizational identification on creative performance and organizational citizenship behavior (OCB), and (2) determining the moderating role of ethical leadership in the relationships of internal- and external- CSR with organizational identification in a cross-cultural context. The data was were collected using multi-respondents and time-lagged data from 260 Pakistani and 239 UK respondents working in upscale hotels of the United Kingdom and Pakistan. The results demonstrate significant differences in both cultures as external CSR has a more substantial impact on organizational identification in the UK, whereas organizational identification has a relatively stronger influence on OCB and creative performance in collectivistic culture (i.e., Pakistan). The findings also confirmed that ethical leadership significantly moderates the relationship of internal- and external - CSR on organizational identification.

Keywords: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

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11377 Nonlinear Impact Responses for a Damped Frame Supported by Nonlinear Springs with Hysteresis Using Fast FEA

Authors: T. Yamaguchi, M. Watanabe, M. Sasajima, C. Yuan, S. Maruyama, T. B. Ibrahim, H. Tomita

Abstract:

This paper deals with nonlinear vibration analysis using finite element method for frame structures consisting of elastic and viscoelastic damping layers supported by multiple nonlinear concentrated springs with hysteresis damping. The frame is supported by four nonlinear concentrated springs near the four corners. The restoring forces of the springs have cubic non-linearity and linear component of the nonlinear springs has complex quantity to represent linear hysteresis damping. The damping layer of the frame structures has complex modulus of elasticity. Further, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled differential equations using normal coordinate corresponding to linear natural modes. Comparing shares of strain energy of the elastic frame, the damping layer and the springs, we evaluate the influences of the damping couplings on the linear and nonlinear impact responses. We also investigate influences of damping changed by stiffness of the elastic frame on the nonlinear coupling in the damped impact responses.

Keywords: dynamic response, nonlinear impact response, finite element analysis, numerical analysis

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