Search results for: ERA-5 analysis data

Authors: Nadya Inda Syartanti

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This research aims to identify, classify, and analyze descriptively the aspects of grammatical and lexical cohesion in the speech text of Japan’s Prime Minister Shinzo Abe entitled Nihon wa Modotte kimashita delivered in Washington DC, the United States on February 23, 2013, as a research data source. The method used is qualitative research, which uses descriptions through words that are applied by analyzing aspects of grammatical and lexical cohesion proposed by Halliday and Hasan (1976). The aspects of grammatical cohesion consist of references (personal, demonstrative, interrogative pronouns), substitution, ellipsis, and conjunction. In contrast, lexical cohesion consists of reiteration (repetition, synonym, antonym, hyponym, meronym) and collocation. Data classification is based on the 6 aspects of the cohesion. Through some aspects of cohesion, this research tries to find out the frequency of using grammatical and lexical cohesion in Shinzo Abe's speech text entitled Nihon wa Modotte kimashita. The results of this research are expected to help overcome the difficulty of understanding speech texts in Japanese. Therefore, this research can be a reference for learners, researchers, and anyone who is interested in the field of discourse analysis.

Keywords: cohesion, grammatical cohesion, lexical cohesion, speech text, Shinzo Abe

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Authors: Ali Maksum

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In a number of countries, including Indonesia, the tendency for non-communicable diseases is increasing. As a result, health costs must be paid by the state continues to increase as well. People's lifestyles, including due to lack of physical activity, are thought to have contributed significantly to the problem. This study aims to examine the impact of participation in sports on quality of life, which is reflected in three main indicators, namely health, psychological, and social aspects. The study was conducted in the city of Surabaya and its surroundings, with a total of 490 participants, consisting of 245 men and 245 women with an average age of 45.4 years. Data on physical activity and quality of life were collected by questionnaire and analyzed using structural equation modeling. The test results of the model prove that the value of chi-square = 8,259 with p = .409, RMSEA = .008, NFI = .992, and CFI = 1. This means that the model is compatible with the data. The model explains that physical activity has a significant effect on quality of life. People who exercise regularly are better able to cope with stress, have a lower risk of illness, and have higher pro-social behavior. Therefore, it needs serious efforts from stakeholders, especially the government, to create an ecosystem that allows the growth of movement culture in the community.

Keywords: participation, physical activity, quality of life, structural equation modelling

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Authors: Muneeb Banday, Anukriti Dixit

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Change in organizations is viewed as a conversion process of the organizational functioning. One of the crucial elements of this conversion process is the employee resistance to organizational change. The existing literature on change resistance has generally treated resistance as a barrier or an opportunity for successful implementation of change. However, there is little empirical research exploring how resistance to change is managed. This may be partially due to difficulty in getting information on resistance to change. The top management does not divulge such information to avoid negative evaluation whereas employees face huge risk in sharing information related to resistance. The focus of the study is to understand how the organization under study dealt with the employee resistance to change. The conversion process is a story of how the organization went from one stage to another. We used narrative approach to change. Data was collected data through company visits and interviews. The interviews were transcribed, coded, and themes were identified. We focused on the strands that left huge scope for alternative interpretations than the dominant narrative of change prevalent in the organization. The study reveals that the top management strategically uses the legitimacy of leadership, roles of key employees, and rationality of change to manage resistance.

Keywords: employee resistance, legitimacy of leadership, narrative analysis, organisational change

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Alexander Rych

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Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

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Authors: Mohammed Bala Banki

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This paper examines the relationship between employee satisfaction, customer satisfaction and loyalty in fast food restaurants in Nigeria and ascertains if prior job experience of employees before their present job moderate the relationship between customer satisfaction and loyalty. Data for this study were collected from matched pairs of employees and customers of fast restaurants in four Nigerian cities. A Structural Equation Modelling (SEM) was used for the analysis to test the proposed relationships and hierarchical multiple regression was performed in SPSS 22 to test moderating effect. Findings suggest that there is a direct positive and significant relationship between employee satisfaction and customer satisfaction and customer satisfaction and loyalty while the path between employee satisfaction and customer loyalty is insignificant. Results also reveal that employee’s prior job experience significantly moderate the relationship between customer satisfaction and loyalty. Further analysis indicates that employees with more years of experience provide more fulfilling services to restaurants customers. This paper provides some theoretical and managerial implications for academia and practitioners.

Keywords: employee’s satisfaction, customer’s satisfaction, loyalty, employee’s prior job experience, fast food industry

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Authors: Arka Roy, Chandra Prakash Dubey

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Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

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Authors: Ibrahim Khan, Waqas Khalid

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The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.

Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning

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Authors: Hyun-Woo Jun, Tae-Chul Jeong, Huai-Cong Liu, Ju Lee

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The paper presents the electromagnetic-thermal flow coupled analysis of permanent magnet synchronous motor (PMSM) which has cooling channel in stator core for forced air cooling. Unlike the general PMSM design, to achieve ohmic loss reduction for high efficiency, cooling channel actively used in the stator core. Equivalent thermal network model was made to analyze the effect of the formation of the additional flow path in the core. According to the shape and position changing of the channel design, electromagnetic-thermal coupled analysis results were reviewed.

Keywords: coupled problems, electric motors, equivalent circuits, fluid flow, thermal analysis

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Authors: Dmitry V. Fomichev, Vladimir I. Solonin

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In this paper, experimental and numerical study of hydrodynamic characteristics of the air coolant flow in the test wire-wrapped assembly is presented. The test assembly has 37 rods, which are similar to the real fuel pins of the BREST-OD-300 fuel assemblies geometrically. Air open loop test facility installed at the “Nuclear Power Plants and Installations” department of BMSTU was used to obtain the experimental data. The obtaining altitudinal distribution of static pressure in the near-wall test assembly as well as velocity and temperature distribution of coolant flow in the test sections can give us some new knowledge about the mechanism of formation of the turbulence flow structure in the wire wrapped fuel assemblies. Numerical simulations of the turbulence flow has been accomplished using ANSYS Fluent 14.5. Different non-local turbulence models have been considered, such as standard and RNG k-e models and k-w SST model. Results of numerical simulations of the flow based on the considered turbulence models give the best agreement with the experimental data and help us to carry out strong analysis of flow characteristics.

Keywords: wire-spaces fuel assembly, turbulent flow structure, computation fluid dynamics

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Authors: Wudneh Asegedech Ayele

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Background: Dietary diversity is strongly related with non-communicable disease (NCDs). Diet plays a key role as a risk factor for hypertension. Diets rich in fruits, vegetables, and low-fat dairy products that include whole grains, poultry, fish, and nuts, that contain only small amounts of red meat, sweets, and sugar-containing beverages, and that contain decreased amounts of total and saturated fat and cholesterol have been found to have a protective effect against hypertension. Methods: hospital based Cross-sectional study design was employed from June 1-June 25, 2021. Sampling technique was Systematic random sampling and data were collected using an interview method. Data were entered into Epi Data version 3.1 and exported to SPSS version 25 for processed and analysis respectively. Descriptive statistics were used to summarize data. Bivariate and multivariate logistic regression will employed to determine dietary diversity among hypertension patients. Results: Adequate dietary diversity score were 96 (24.68%). Most of them cereal, white roots and tubers, dark green leafy vegetables, Vitamin A rich fruits ,meat, egg and coffee or tea more intakes. Hypertensive patients who didn’t consume cereals four times less likely adequate dietary diversity than who consumed cereals [AOR= 4.083, 95%: CI (2.096 -7.352)]. Hypertensive patients who didn’t consume white roots and tubers 14 times less likely adequate dietary diversity than who consumed white roots and tubers [AOR= 13.733, 95% CI: (5.388-34.946)]. Conclusion and recommendation the study showed one of fourth part reported adequate dietary diversity score. Cereals, fruits, vegetables and milk and milk products were statistically associated with dietary diversity practice. Health education about dietary modifications and behavioral change to dietary diversity

Keywords: dietary diversity practice and associated facrors among hypertension patients at tirunesh beijing hospital, hypertension, dietary, diversity and tirunesh beijing hospital, associated facrors among hypertension patient, at tirunesh beijing hospita

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Ahmed Shaboub, Yusuf Jasim Althawadi, Shadi Alaa Abdelaal, Mohamed Hussein Abdalla, Hatem Amr Elzahaby, Mohamed Mohamed, Hazem S. Ghaith, Ahmed Negida

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Objectives: We aimed to compare the safety and outcomes of the minimally invasive approaches versus conventional sternotomy procedures for aortic valve replacement. Methods: We conducted a PRISMA-compliant systematic review and meta-analysis. We ran an electronic search of PubMed, Cochrane CENTRAL, Scopus, and Web of Science to identify the relevant published studies. Data were extracted and pooled as standardized mean difference (SMD) or risk ratio (RR) using StataMP version 17 for macOS. Results: Forty-one studies with a total of 15,065 patients were included in this meta-analysis (minimally invasive approaches n=7231 vs. conventional sternotomy n=7834). The pooled effect size showed that minimally invasive approaches had lower mortality rate (RR 0.76, 95%CI [0.59 to 0.99]), intensive care unit and hospital stays (SMD -0.16 and -0.31, respectively), ventilation time (SMD -0.26, 95%CI [-0.38 to -0.15]), 24-h chest tube drainage (SMD -1.03, 95%CI [-1.53 to -0.53]), RBCs transfusion (RR 0.81, 95%CI [0.70 to 0.93]), wound infection (RR 0.66, 95%CI [0.47 to 0.92]) and acute renal failure (RR 0.65, 95%CI [0.46 to 0.93]). However, minimally invasive approaches had longer operative time, cross-clamp, and bypass times (SMD 0.47, 95%CI [0.22 to 0.72], SMD 0.27, 95%CI [0.07 to 0.48], and SMD 0.37, 95%CI [0.20 to 0.45], respectively). There were no differences between the two groups in blood loss, endocarditis, cardiac tamponade, stroke, arrhythmias, pneumonia, pneumothorax, bleeding reoperation, tracheostomy, hemodialysis, or myocardial infarction (all P>0.05). Conclusion: Current evidence showed higher safety and better operative outcomes with minimally invasive aortic valve replacement compared to the conventional approach. Future RCTs with long-term follow-ups are recommended.

Keywords: aortic replacement, minimally invasive, sternotomy, mini-sternotomy, aortic valve, meta analysis

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Authors: Simona Perga, Chiara Beltramo, Floriana Fruscione, Isabella Martini, Federica Cavallo, Federica Riccardo, Paolo Buracco, Selina Iussich, Elisabetta Razzuoli, Katia Varello, Lorella Maniscalco, Elena Bozzetta, Angelo Ferrari, Paola Modesto

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Introduction: Human and canine melanoma have common clinical, histologic characteristics making dogs a good model for comparative oncology. The identification of specific genes and a better understanding of the genetic landscape, signaling pathways, and tumor–microenvironmental interactions involved in the cancer onset and progression is essential for the development of therapeutic strategies against this tumor in both species. In the present study, the differential expression of genes in spontaneously occurring canine melanoma and in paired normal tissue was investigated by targeted RNAseq. Material and Methods: Total RNA was extracted from 17 canine malignant melanoma (CMM) samples and from five paired normal tissues stored in RNA-later. In order to capture the greater genetic variability, gene expression analysis was carried out using two panels (Qiagen): Human Immuno-Oncology (HIO) and Mouse-Immuno-Oncology (MIO) and the miSeq platform (Illumina). These kits allow the detection of the expression profile of 990 genes involved in the immune response against tumors in humans and mice. The data were analyzed through the CLCbio Genomics Workbench (Qiagen) software using the Canis lupus familiaris genome as a reference. Data analysis were carried out both comparing the biologic group (tumoral vs. healthy tissues) and comparing neoplastic tissue vs. paired healthy tissue; a Fold Change greater than two and a p-value less than 0.05 were set as the threshold to select interesting genes. Results and Discussion: Using HIO 63, down-regulated genes were detected; 13 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Eighteen genes were up-regulated, 14 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Using the MIO, 35 down regulated-genes were detected; only four of these were down-regulated, also comparing neoplastic sample vs. paired healthy tissue. Twelve genes were up-regulated in both types of analysis. Considering the two kits, the greatest variation in Fold Change was in up-regulated genes. Dogs displayed a greater genetic homology with humans than mice; moreover, the results have shown that the two kits are able to detect different genes. Most of these genes have specific cellular functions or belong to some enzymatic categories; some have already been described to be correlated to human melanoma and confirm the validity of the dog as a model for the study of molecular aspects of human melanoma.

Keywords: animal model, canine melanoma, gene expression, spontaneous tumors, targeted RNAseq

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Authors: Peter Boyes, Sarah Sharples, Paul Tennent, Gary Priestnall, Jeremy Morley

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Significant long-term investment projects can involve complex decisions. These are often described as capital projects, and the factors that contribute to their complexity include budgets, motivating reasons for investment, stakeholder involvement, interdependent projects, and the delivery phases required. The complexity of these projects often requires management groups to be established involving stakeholder representatives; these teams are inherently multidisciplinary. This study uses two university campus capital projects as case studies for this type of management group. Due to the interaction of projects with wider campus infrastructure and users, decisions are made at varying spatial granularity throughout the project lifespan. This spatial-related context brings complexity to the group decisions. Sensemaking is the process used to achieve group situational awareness of a complex situation, enabling the team to arrive at a consensus and make a decision. The purpose of this study is to understand the role of people and data in the complex spatial related long-term decision and sensemaking processes. The paper aims to identify and present issues experienced in practical settings of these types of decision. A series of exploratory semi-structured interviews with members of the two projects elicit an understanding of their operation. From two stages of thematic analysis, inductive and deductive, emergent themes are identified around the group structure, the data usage, and the decision making within these groups. When data were made available to the group, there were commonly issues with the perception of veracity and validity of the data presented; this impacted the ability of group to reach consensus and, therefore, for decisions to be made. Similarly, there were different responses to forecasted or modelled data, shaped by the experience and occupation of the individuals within the multidisciplinary management group. This paper provides an understanding of further support required for team sensemaking and decision making in complex capital projects. The paper also discusses the barriers found to effective decision making in this setting and suggests opportunities to develop decision support systems in this team strategic decision-making process. Recommendations are made for further research into the sensemaking and decision-making process of this complex spatial-related setting.

Keywords: decision making, decisions under uncertainty, real decisions, sensemaking, spatial, team decision making

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

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Authors: Barnabás Körmöndi

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The recent crises have affected societies worldwide, resulting in the irresponsible exploitation of natural resources and the unattainability of sustainability. Regions that are economically underdeveloped, such as the Bodrogköz in Eastern Hungary and Slovakia, experience these issues more severely. The aim of this study is to analyze the natural and social resources of the Bodrogköz area for the planning of complex development based on ecotourism. The objective is to develop ecotourism opportunities in this least developed area of the borderland of Hungary and Slovakia. The study utilizes desk research, deep interviews, focus group meetings, and remote sensing methods. Desk research is aimed at providing a comprehensive understanding of the area, while deep interviews and focus group meetings were conducted to understand the stakeholders' perspectives on the potential for ecotourism. Remote sensing methods were used to better understand changes in the natural environment. The study identified the potential for ecotourism development in the Bodrogköz area due to its near-natural habitats along its bordering rivers and rich cultural heritage. The analysis revealed that ecotourism could promote the region's sustainable development, which is essential for its economic growth. Additionally, the study identified the possible threats to the natural environment during ecotourism development and suggested strategies to mitigate these threats. This study highlights the significance of ecotourism in promoting sustainable development in underdeveloped areas such as the Bodrogköz. It provides a basis for future research on ecotourism development and sustainable planning in similar regions. The analysis is based on the data collected through desk research, deep interviews, focus group meetings, and remote sensing. The assessment was conducted through content analysis, which allowed for the identification of themes and patterns in the data. The study addressed the question of how to develop ecotourism in the least developed area of the borderland of Hungary and Slovakia and promote sustainable development in the region. In conclusion, the study highlights the potential for ecotourism development in Bodrogköz and identifies the natural and social resources that contribute to its development. The study emphasizes the need for sustainable development to promote economic growth and mitigate any environmental threats. The findings can inform the development of future strategic plans for ecotourism, promoting sustainable development in underdeveloped regions.

Keywords: ecotourism, natural resources, remote sensing, social development

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Authors: Nasir Mehmood, Muhammad Yar Khan, Anam Javeed

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This study aims to scrutinize the dynamics which tend to impact customer’s purchasing intention of Islamic credit card and nexus of product’s knowledge and religiosity with the attitude of potential Islamic credit card’s customer. The theory of reasoned action strengthened the idea that intentions due to its proven predictive power are most likely to instigate intended consumer behavior. Particularly, the study examines the relationships of perceived financial cost (PFC), subjective norms (SN), and attitude (ATT) with the intention to purchase Islamic credit cards. Using a convenience sampling approach, data have been collected from 450 customers of banks located in Rawalpindi and Islamabad. A five-point Likert scale self-administered questionnaire was used to collect the data. The data were analyzed using the Statistical Package of Social Sciences (SPSS) through the procedures of principal component and multiple regression analysis. The results suggested that customer’s religiosity and product knowledge are strong indicators of attitude towards buying Islamic credit cards. Likewise, subjective norms, attitude, and perceived financial cost have a significant positive impact on customers’ purchase intent of Islamic bank’s credit cards. This study models a useful path for future researchers to further investigate the underlined phenomenon along with a variety of psychodynamic factors which are still in its infancy, at least in the Pakistani banking sector. The study also provides an insight to the practitioners and Islamic bank managers for directing their efforts toward educating customers regarding the use of Islamic credit cards and other financial products.

Keywords: attitude, Islamic credit card, religiosity, subjective norms

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Authors: Hui Wang, Huan Zhang

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This study uses systematic review and qualitative comparative analysis methods to comprehensively inquire about the recent street-level policy entrepreneurship research, to identify the characteristics and lessons we can learn from 20 years of street-level policy entrepreneurship literature, and the relations between political contexts and street-level policy entrepreneurs’ strategies. Using data from a systematic review of street-level policy entrepreneurship literature, we identify the sub-components of different political contexts and core strategies of street-level policy entrepreneurs and estimate the configurational relations between different political settings and street-level policy entrepreneurs’ strategies. Our results show that street-level policy entrepreneurs display social acuity, define the problem, and build team strategies when policy or political streams dominate. Street-level policy entrepreneurs will use lead-by-example strategies when both policy and political streams dominate. Furthermore, street-level policy entrepreneurs will use bureaucratic strategies, even if no stream dominates in the political context.

Keywords: policy entrepreneurs, qualitative comparative analysis, street-level bureaucracy, systematic review

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Authors: G. A. Asciak, C. Camilleri, A. Rizzo

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The waste management in Malta is a national challenge. Coupled with Malta’s recent economic boom, which has seen massive growth in several sectors, especially the construction industry, drastic actions need to be taken. Wood waste, currently being dumped in landfills, is one type of waste which has increased astronomically. This research study aims to carry out a thorough examination on the possibility of using this waste as a biomass resource and adopting a waste-to-energy technology in order to generate electrical energy. This study is composed of three distinct yet interdependent phases, namely, data collection from the local SMEs, thermal analysis using the bomb calorimeter, and generation of energy from wood waste using a micro biomass plant. Data collection from SMEs specializing in wood works was carried out to obtain information regarding the available types of wood waste, the annual weight of imported wood, and to analyse the manner in which wood shavings are used after wood is manufactured. From this analysis, it resulted that five most common types of wood available in Malta which would suitable for generating energy are Oak (hardwood), Beech (hardwood), Red Beech (softwood), African Walnut (softwood) and Iroko (hardwood). Subsequently, based on the information collected, a thermal analysis using a 6200 Isoperibol calorimeter on the five most common types of wood was performed. This analysis was done so as to give a clear indication with regards to the burning potential, which will be valuable when testing the wood in the biomass plant. The experiments carried out in this phase provided a clear indication that the African Walnut generated the highest gross calorific value. This means that this type of wood released the highest amount of heat during the combustion in the calorimeter. This is due to the high presence of extractives and lignin, which accounts for a slightly higher gross calorific value. This is followed by Red Beech and Oak. Moreover, based on the findings of the first phase, both the African Walnut and Red Beech are highly imported in the Maltese Islands for use in various purposes. Oak, which has the third highest gross calorific value is the most imported and common wood used. From the five types of wood, three were chosen for use in the power plant on the basis of their popularity and their heating values. The PP20 biomass plant was used to burn the three types of shavings in order to compare results related to the estimated feedstock consumed by the plant, the high temperatures generated, the time taken by the plant to produce gasification temperatures, and the projected electrical power attributed to each wood type. From the experiments, it emerged that whilst all three types reached the required gasification temperature and thus, are feasible for electrical energy generation. African Walnut was deemed to be the most suitable fast-burning fuel. This is followed by Red-beech and Oak, which required a longer period of time to reach the required gasification temperatures. The results obtained provide a clear indication that wood waste can not only be treated instead of being dumped in dumped in landfill but coupled.

Keywords: biomass, isoperibol calorimeter, waste-to-energy technology, wood

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Mohammed Al-Shalabi, Alaa Obeidat

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In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

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Authors: Athena Daniilidou, Maria Platsidou

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Resilience is considered to greatly affect the personal and occupational wellbeing and efficacy of individuals; therefore, it has been widely studied in the social and behavioral sciences. Given its significance, several scales have been created to assess resilience of children and adults. However, most of these scales focus on examining only the internal protective or risk factors that affect the levels of resilience. The aim of the present study is to create a reliable scale that assesses both the internal and the external protective factors that affect Greek teachers’ levels of resilience. Participants were 136 secondary school teachers (89 females, 47 males) from urban areas of Greece. Connor-Davidson Resilience Scale (CD-Risc) and Resilience Scale for Adults (RSA) were used to collect the data. First, exploratory factor analysis was employed to investigate the inner structure of each scale. For both scales, the analyses revealed a differentiated factor solution compared to the ones proposed by the creators. That prompt us to create a scale that would combine the best fitting subscales of the CD-Risc and the RSA. To this end, the items of the four factors with the best fit and highest reliability were used to create the ‘Teachers' resilience scale’. Exploratory factor analysis revealed that the scale assesses the following protective/risk factors: Personal Competence and Strength (9 items, α=.83), Family Cohesion Spiritual Influences (7 items, α=.80), Social Competence and Peers Support (7 items, α=.78) and Spiritual Influence (3 items, α=.58). This four-factor model explained 49,50% of the total variance. In the next step, a confirmatory factor analysis was performed on the 26 items of the derived scale to test the above factor solution. The fit of the model to the data was good (χ2/292 = 1.245, CFI = .921, GFI = .829, SRMR = .074, CI90% = .026-,056, RMSEA = 0.43), indicating that the proposed scale can validly measure the aforementioned four aspects of teachers' resilience and thus confirmed its factorial validity. Finally, analyses of variance were performed to check for individual differences in the levels of teachers' resilience in relation to their gender, age, marital status, level of studies, and teaching specialty. Results were consistent to previous findings, thus providing an indication of discriminant validity for the instrument. This scale has the advantage of assessing both the internal and the external protective factors of resilience in a brief yet comprehensive way, since it consists 26 items instead of the total of 58 of the CD-Risc and RSA scales. Its factorial inner structure is supported by the relevant literature on resilience, as it captures the major protective factors of resilience identified in previous studies.

Keywords: protective factors, resilience, scale development, teachers

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Authors: Briony Gray, Glenn Simpson, Hajira Dambha-Miller, Andrew Farmer

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Multimorbidity may be strongly affected by a variety of conditions, factors, and variables requiring higher demands on health and social care services, infrastructure, and expenses. Holding one or more conditions increases one’s risk for development of future conditions; with patients over 65 years old at highest risk. Psychosocial factors such as anxiety and depression are rising exponentially globally, which has been amplified by the COVID19 pandemic. These are highly correlated and predict poorer outcomes when held in coexistence and increase the likelihood of comorbid physical health conditions. While possible future reform of social and healthcare systems may help to alleviate some of these mounting pressures, there remains an urgent need to better understand the potential role health behaviours and psychosocial conditions - such as anxiety and depression – may have on aging populations. Using the UK healthcare scene as a lens for analysis, this study uses big data collected in the UK Longitudinal Study of Aging (ELSA) to examine the role of anxiety and depression in ageing populations (65yrs+). Using logistic regression modelling, results identify the 10 most significant variables correlated with both anxiety and depression from data categorised into the areas of health behaviour, psychosocial, socioeconomic, and life satisfaction (each demonstrated through literature review to be of significance). These are compared with wider global research findings with the aim of better understanding the areas in which social and healthcare reform can support multimorbidity interventions, making suggestions for improved patient-centred care. Scope of future research is outlined, which includes analysis of 59 total multimorbidity variables from the ELSA dataset, going beyond anxiety and depression.

Keywords: multimorbidity, health behaviours, patient centred care, psychosocial factors

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Authors: Ogunlesi Olufunso, John Ogunsola, Omolade Oladele, Benjamin Emikpe

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Context: Coccidiosis is a parasitic disease that affects poultry production, leading to economic losses. Garlic is known for medicinal properties and has been used as a natural remedy for various diseases. This study aims to investigate the prophylactic effect of garlic inclusion in the feed of commercial broilers with coccidiosis. Research Aim: The aim of this study is to determine the possible effect of garlic meal inclusion in poultry feed on the body weight gain of commercial broilers and to investigate it's therapeutic effect on broilers with coccidiosis. Methodology: The study conducted a case-control study for eight weeks with One hundred Arbor acre commercial broilers separated into five (5) groups from day-old, where 6,000 Eimeria oocysts were orally inoculated into each broiler in the different groups. Feed intake, body weight gain, feed conversion ratio, oocyt shedding rate, histopathology and erythrocyte indices were assessed. Findings: The inclusion of garlic meal in the broilers' diet resulted in an improved feed conversion ratio, decreased oocyst counts, reduced diarrhoeic fecal spots, decreased susceptibility to coccidial infection, and increased packed cell volume (PCV). Theoretical Importance: This study contributes to the understanding of the prophylactic effect of garlic supplementation, including its antiparasitic properties on commercial broilers with coccidiosis. It highlights the potential use of non-conventional feed additives or ayurvedic herb and spices in the treatment of poultry diseases. Data Collection and Analysis Procedures: The study collected data on feed intake, body weight gain, oocyst shedding rate, histopathological observations, and erythrocyte indices. Data were analyzed using Analysis of Variance and Duncan's Multiple range Test. Questions Addressed: The study addressed the possible effect of garlic meal inclusion in poultry feed on the body weight gain of broilers and its therapeutic effect on broilers with coccidiosis. Conclusion: The study concludes that garlic inclusion in the feed of broilers has a prophylactic effect, including antiparasitic properties, resulting in improved feed conversion ratio, reduced oocyst counts and increased PCV.

Keywords: broilers, eimeria spp, garlic, Ibadan

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Authors: Elham A. Alsadoon, Hamadah B. Alsadoon

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Educators try to design learning environments that are preferred by their students. With the wide-spread adoption of cell phones surpassing any other technology, educators should not fail to invest in the power of such technology. This study aimed to explore the current use of cell phones in education among Saudi students in Saudi universities and how students perceive such use. Data was collected from 237 students at King Saud University. Descriptive analysis was used to analyze the data. A T-test for independent groups was used to examine whether there was a significant difference between males and females in their perception of using cell phones in education. Findings suggested that students have a positive attitude toward the use of cell phones in education. The most accepted use was for sending notification to students, which has already been experienced through the Twasel system provided by King Saud University. This electronic system allows instructors to easily send any SMS or email to their students. The use of cell phone applications came in the second rank of using cell phones in education. Students have already experienced the benefits of having these applications handy wherever they go. On the other hand, they did not perceive using cell phones for assessment as practical educational usage. No gender difference was detected in terms of students’ perceptions toward using cell phones in education.

Keywords: cell phone, mobile learning, educational sciences, education

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Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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Authors: Weldeabrha Kiros Kidanemaryam

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The investigation is to examine intra-organizational supply chain relationships of firms, which will help to look at and give an emphasis on internal processes and operations strength and achievements to make an influence even for external relationship management and outstanding performances of organizations. The purpose of the study is to scrutinize the internal supply chain relationships within manufacturing companies located in Tigray. The qualitative and quantitative data analysis methods were employed during the study by applying the primary data sources (questionnaires & interviews) and secondary data sources (organizational reports and documents) with the purposive sampling method. Thus, a descriptive research design was also applied in the research project in line with the cross-sectional research design which portrays simply the magnitude of the issues and problems by collecting the required and necessary data once from the sample respondents. This is because the study variables don’t have any cause-and-effect relationship in the research project that requires other types of research design than a descriptive research design; it already needs to be assessed and analyzed with a detailed description of the results after quantifying the outcomes and degree of the issues and problems based on the data gathered from respondents. The collected data was also analyzed by using the statistical package for social sciences (SPSS Version 20). The intra-organizational relationships of the companies are moderately accomplished, which requires an improvement for enhancing the performances of each unit or department within the firms so as to upgrade and ensure the progress of the companies’ effectiveness and efficiency. Moreover, the manufacturing companies have low industrial discipline and working culture, weak supervision of manpower, delayed delivery in the process within the companies, unsatisfactory quality of products, underutilization of capacity, and low productivity and profitability, which in turn results in minimizing the performance of intra-organizational supply chain relationships and to reduce the companies’ organizational efficiency, effectiveness and sustainability. Hence, the companies should have to give emphasize building and managing the intra-organizational supply chain relationships effectively because nothing can be done without creating successful and progressive relationships with internal units or functional areas and individuals for the production and provision of the required and qualified products that permits to meet the intended customers’ desires. The study contributes to improving the practical applications and gives an emphasis on the policy measurements and implications of the manufacturing companies with regard to intra-organizational supply chain relationships.

Keywords: supply chain, supply chain relationships, intra-organizational relationships, manufacturing companies

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Aleksandra Szurlej-Kielanska, Lucyna Pilacka, Dariusz Górecki

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The dynamic development of wind energy requires the simultaneous implementation of effective systems minimizing the risk of collisions between birds and wind turbines. Wind turbines are installed in more and more challenging locations, often close to the natural environment of birds. More and more countries and organizations are defining guidelines for the necessary functionality of such systems. The minimum bird detection distance, trajectory tracking, and shutdown time are key factors in eliminating collisions. Since 2020, we have continued the survey on the validation of the subsequent version of the BPS detection and reaction system. Bird protection system (BPS) is a fully automatic camera system which allows one to estimate the distance of the bird to the turbine, classify its size and autonomously undertake various actions depending on the bird's distance and flight path. The BPS was installed and tested in a real environment at a wind turbine in northern Poland and Central Spain. The performed validation showed that at a distance of up to 300 m, the BPS performs at least as well as a skilled ornithologist, and large bird species are successfully detected from over 600 m. In addition, data collected by BPS systems installed in Spain showed that 60% of the detections of all birds of prey were from individuals approaching the turbine, and these detections meet the turbine shutdown criteria. Less than 40% of the detections of birds of prey took place at wind speeds below 2 m/s while the turbines were not working. As shown by the analysis of the data collected by the system over 12 months, the system classified the improved size of birds with a wingspan of more than 1.1 m in 90% and the size of birds with a wingspan of 0.7 - 1 m in 80% of cases. The collected data also allow the conclusion that some species keep a certain distance from the turbines at a wind speed of over 8 m/s (Aquila sp., Buteo sp., Gyps sp.), but Gyps sp. and Milvus sp. remained active at this wind speed on the tested area. The data collected so far indicate that BPS is effective in detecting and stopping wind turbines in response to the presence of birds of prey with a wingspan of more than 1 m.

Keywords: protecting birds, birds monitoring, wind farms, green energy, sustainable development

Procedia PDF Downloads 79