Search results for: bet analysis

Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

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Authors: Abigail Amoako Kayser, Brian Kayser

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This study aimed to examine Ghana's 6th-grade Basic School history curriculum to determine how Ghanaian history is taught. We used qualitative methods and document analysis. The document analysis served two primary purposes: (1) To gain insight into what the curriculum materials covered and from whom's perspectives, and (2) To triangulate with teacher interview data. Documents obtained included: (1) Textbooks used by 6th-grade students, (2) Teacher pacing guide provided by the Department of Education in Ghana, and (3) Student work samples. This study was guided through Post-colonial theory and criticisms to explore the remnants of colonial power and hegemony that persist in history curricula used in public schools in Ghana. We also applied African Feminist Thought and Black Feminist Thought to unpack the extent to which issues of patriarchy, race, traditions, underdevelopment, and sexuality impact how we see the experiences of people on the continent. The findings indicated that the remnant of colonial rule persisted in the contents of the history curriculum, and the atrocities of slavery were overlooked or eliminated from the curriculum. The findings also indicated that Ghana's history centered on men's experiences.

Keywords: history, curriculum, decolonialization, culturally relevant pedagogy

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Authors: Nader Nciri, Suil Song, Namho Kim, Namjun Cho

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Properties and compositions of bitumen and bitumen-derived liquids have significant influences on the selection of recovery, upgrading and refining processes. Optimal process conditions can often be directly related to these properties. The end uses of bitumen and bitumen products are thus related to their compositions. Because it is not possible to conduct a complete analysis of the molecular structure of bitumen, characterization must be made in other terms. The present paper focuses on physico-chemical analysis of two different types of bitumens. These bitumen samples were chosen based on: the original crude oil (sand oil and crude petroleum), and mode of process. The aim of this study is to determine both the manufacturing effect on chemical species and the chemical organization as a function of the type of bitumen sample. In order to obtain information on bitumen chemistry, elemental analysis (C, H, N, S, and O), heavy metal (Ni, V) concentrations, IATROSCAN chromatography (thin layer chromatography-flame ionization detection), FTIR spectroscopy, and 1H NMR spectroscopy have all been used. The characterization includes information about the major compound types (saturates, aromatics, resins and asphaltenes) which can be compared with similar data for other bitumens, more importantly, can be correlated with data from petroleum samples for which refining characteristics are known. Examination of Asphalt Ridge froth bitumen showed that it differed significantly from representative petroleum pitches, principally in their nonhydrocarbon content, heavy metal content and aromatic compounds. When possible, properties and composition were related to recovery and refining processes. This information is important because of the effects that composition has on recovery and processing reactions.

Keywords: froth bitumen, oil sand, asphalt ridge, petroleum pitch, thin layer chromatography-flame ionization detection, infrared spectroscopy, 1H nuclear magnetic resonance spectroscopy

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Authors: Zhiqiang Cheng, Qingliang He, Lu Li, Jie Ren

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The safety of pipelines in the condition of frost heave or thaw settlement is necessarily evaluated. A full-scale experiment pipe with the typical structure configuration in station pipeline is constructed, the residual stress is tested with X-ray residual stress device, and the residual stress field of pipe is analyzed. The evolution of pipe strain with pressure in the scope of maximum allowable operation pressure (MAOP) is investigated by both strain gauge and X-ray methods. Load caused by frost heave or thaw settlement is simulated by two ways of lifting jack. The relation of maximum stress of pipe and clearances between supporter and pipe is studied in case of frost heave. The relation of maximum stress of pipe and maximum deformation of pipe on the ground is studied in case of thaw settlement. The study methods and results are valuable for safety assessment of station pipeline according to clearances or deformation in the condition of frost heave or thaw settlement.

Keywords: frost heave, pipeline, stress analysis, thaw settlement

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Teaching practices have been widely studied in relation to students' outcomes, positioning themselves as one of their strongest catalysts and influencing students' emotional experiences. In the higher education context, teachers become even more crucial as many students ground their decisions on which courses to enroll in based on opinions and ratings of teachers from other students. Unfortunately, sometimes universities do not provide the personal, social, and academic stimulation students demand to be actively engaged. To evaluate their teachers, universities often rely on students' evaluations of teaching (SET) collected via Likert scale surveys. Despite its usefulness, such a method has been questioned in terms of validity and reliability. Alternatively, researchers can rely on qualitative answers to open-ended questions. However, the unstructured nature of the answers and a large amount of information obtained requires an overwhelming amount of work. The present work presents an alternative approach to analyse such data: sentiment analysis. To the best of our knowledge, no research before has included results from SA into an explanatory model to test how students' sentiments affect their emotional engagement in class. The sample of the present study included a total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) from the Educational Sciences faculty of a public university in Spain. Data collection took place during the academic year 2021-2022. Students accessed an online questionnaire using a QR code. They were asked to answer the following open-ended question: "If you had to explain to a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?". Sentiment analysis was performed using Microsoft's pre-trained model. The reliability of the measure was estimated between the tool and one of the researchers who coded all answers independently. The Cohen's kappa and the average pairwise percent agreement were estimated with ReCal2. Cohen's kappa was .68, and the agreement reached was 90.8%, both considered satisfactory. To test the hypothesis relations among SA and students' emotional engagement, a structural equation model (SEM) was estimated. Results demonstrated a good fit of the data: RMSEA = .04, SRMR = .03, TLI = .99, CFI = .99. Specifically, the results showed that student’s sentiment regarding their teachers’ teaching positively predicted their emotional engagement (β == .16 [.02, -.30]). In other words, when students' opinion toward their instructors' teaching practices is positive, it is more likely for students to engage emotionally in the subject. Altogether, the results show a promising future for sentiment analysis techniques in the field of education. They suggest the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, students' evaluation of teaching, structural-equation modelling, emotional engagement

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Authors: Masataka Inada, Masanao Kinoshita, Nobuaki Matsumori

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It has been demonstrated that lipid molecules in biological membranes are responsible for the functionalization and structuration of membrane proteins. However, it is still unclear how the interaction of lipid molecules with membrane proteins is correlated with the function of the membrane proteins. Here we first developed an evaluation method for the interaction between membrane proteins and lipid molecules via surface plasmon resonance (SPR) analysis. Bacteriorhodopsin (bR), which was obtained by the culture of halobacteria, was used as a membrane protein. We prepared SPR sensor chips covered with self-assembled monolayer containing mercaptocarboxylic acids, and immobilized bR onto them. Then, we evaluated the interactions with various lipids that have different structures. As a result, the halobacterium-specific glycolipid S-TGA-1 was found to have much higher affinity with bRs than other lipids. This is probably due to not only hydrophobic and electrostatic interactions but also hydrogen bonds with sugar moieties in the glycolipid. Next, we analyzed the roles of the lipid in the structuration and functionalization of bR. CD analysis showed that S-TGA-1 could promote trimerization of bR monomers more efficiently than any other lipids. Flash photolysis further indicated that bR trimers formed by S-TGA-1 reproduced the photocyclic activity of bR in purple membrane, halobacterium-membrane. These results suggest that S-TGA-1 promotes trimerization of bR through strong interactions and consequently fulfills the bR’s function efficiently.

Keywords: membrane protein, lipid, interaction, bacteriorhodopsin, glycolipid

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Authors: Priyadarshini Alok

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The present situation in India envisages that because of the surge in population and the economy, cities are expected to spill over to hinterland areas. The consumption-led factors such as land, labor, etc. will be boosted. Hence, the need for regional connectivity becomes obligatory. But, there is enormous pressure upon the land; proving itself through rising traffic congestion, roads, and railway accidents. Air transport is practical, but due to decreasing availability of land, this will not be a wise solution. What with the introduction of seaplanes in the country which was once the vital asset in the world prior to Second World War. Maldives has proved it. Seaplanes offer natural landing site and are time and cost-efficient. Seaplanes in accordance with UDAN can prove to be the solution in linking various regions with other states. This research paper aims to offer the feasibility analysis along with site justification of the potential areas in the state of Andhra Pradesh, India; for the operation of seaplanes. The standards are taken from the US Department of Transportation, Federal Aviation Administration for the analysis. The conflation of Seaplanes with UDAN will offer an alternate mode of air connectivity, strengthen the transport network by simulation of connectivity to unserved and under-served areas and boost the nation's economy.

Keywords: connectivity, seaplanes, transport, UDAN

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Authors: Rashid Masoud Ali Al-Mazrui, Ramadhani Mashaka Shabani

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Islamic banks and financial institutions are exposed to the same risks as conventional banking. These risks include the rate return risk, credit or market risk, liquidity risk, and operational risk among others. However, being a financial institution that operates Islamic banking and finance operations, there is additional risk associated with its operations different from conventional finance, such as displacing commercial risk. They face Shari'ah compliance risks because of their failure to follow Shari'ah principles. To have proper mitigation and risk management, banks should have proper risk management policies to mitigate risks. This paper aims to study the risk management taken by Islamic banks in comparison with conventional banks. Also, the study evaluates the provisions for risk management taken by selected Islamic banks and conventional banks. The study employs qualitative analysis using secondary data by applying a content analysis approach with a sample size of 4 Islamic banks and four conventional banks ranging from 2010 to 2020. We find that these banks all use the same technique, except for the associated risk. The extra ways are used, but only for additional risks that are available to Islamic banking and finance.

Keywords: emerging risk, risk management, Islamic banking, conventional bank

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Authors: Mohsen Torabi, Kaili Zhang

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This work considers forced convection in a channel partially filled with porous media from local thermal non-equilibrium (LTNE) point of view. The channel is heated with constant heat flux from the lower side and is isolated on the top side. The wall heat flux is considered to be divided between the solid and fluid phases based on their temperature gradients and effective thermal conductivities. The general forms of the velocity and temperature fields are analytically obtained. To obtain the constant parameters for temperature equations, a numerical solution is considered. Using different thermophysical parameters, both velocity and temperature fields are comprehensively illustrated. Discussions regarding bifurcation phenomenon are provided. Since this geometry has not been considered yet, the present analysis is a useful addition to the literature on thermal performance of porous systems from LTNE perspective.

Keywords: local thermal non-equilibrium, forced convection, thermal bifurcation, porous-fluid interface, combined analytical-numerical solution

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Laurie Prange-Martin, Romeo Turcan, Norman Fraser

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The aim of this study is to identify the conditions required and describe the process of emergence for a new economic sector created from new or established businesses. A systematic literature review of English-language studies published from 1983 to 2016 was conducted using the following databases: ABI/INFORM Complete; Business Source Premiere; Google Scholar; Scopus; and Web of Science. The two main terms of business sector and emergence were used in the systematic literature search, along with another seventeen synonyms for each these main terms. From the search results, 65 publications met the requirements of an empirical study discussing and reporting the conditions of new sector emergence. A meta-analysis of the literature examined suggest that there are six favourable conditions and five key individuals or groups required for new sector emergence. In addition, the results from the meta-analysis showed that there are eighteen theories used in the literature to explain the phenomenon of new sector emergence, which can be grouped in three study disciplines. With such diversity in theoretical frameworks used in the 65 empirical studies, the authors of this paper propose the development of a new theory of sector emergence.

Keywords: economic geography, new sector emergence, economic diversification, regional economies

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Authors: V. T. Gerov, D. I. Gerova, I. D. Micheva, N. F. Nazifova-Tasinova, M. N. Nikolova, M. G. Pasheva, B. T. Galunska

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Multiple myeloma (MM) is the most frequent plasma cell (PC) dyscrasia that involves the skeleton. Myeloma bone disease (MBD) is characterized by osteolytic bone lesions as a result of increased osteoclasts activity not followed by reactive bone formation due to osteoblasts suppression. Skeletal complications cause significant adverse effects on quality of life and lead to increased morbidity and mortality. Last decade studies revealed the implication of different proteins in osteoclast activation and osteoblast inhibition. The aim of the present study was to determine serum levels of periostin, sRANKL and osteopontin and to evaluate their role as bone markers in MBD. Materials and methods. Thirty-two newly diagnosed MM patients (mean age: 62.2 ± 10.7 years) and 33 healthy controls (mean age: 58.9 ± 7.5 years) were enrolled in the study. According to IMWG criteria 28 patients were with symptomatic MM and 4 with monoclonal gammopathy of undetermined significance (MGUS). In respect to their bone involvement all symptomatic patients were divided into two groups (G): 9 patients with 0-3 osteolytic lesions (G1) and 19 patients with >3 osteolytic lesions and/or pathologic fractures (G2). Blood samples were drawn for routine laboratory analysis and for measurement of periostin, sRANKL and osteopontin serum levels by ELISA kits (Shanghai Sunred Biological Technology, China). Descriptive analysis, Mann-Whitney test for assessment the differences between groups and non-parametric correlation analysis were performed using GraphPad Prism v8.01. Results. The median serum levels of periostin, sRANKL and osteopontin of ММ patients were significantly higher compared to controls (554.7pg/ml (IQR=424.0-720.6) vs 396.9pg/ml (IQR=308.6-471.9), p=0.0001; 8.9pg/ml (IQR=7.1-10.5) vs 5.6pg/ml (IQR=5.1-6.4, p<0.0001 and 514.0ng/ml (IQR=469.3-754.0) vs 387.0ng/ml (IQR=335.9-441.9), p<0.0001, respectively). for assessment of differences between groups and non-parametric correlation analysis were performed using GraphPad Prism v8.01. Statistical significance was found for all tested bone markers between symptomatic MM patients and controls: G1 vs controls (p<0.03), G2 vs controls (p<0.0001) for periostin; G1 vs controls (p<0.0001), G2 vs controls (p<0.0001) for sRANKL; G1 vs controls (p=0.002), G2 vs controls (p<0.0001) for osteopontin, as well between symptomatic MM patients and MGUS patients: G1 vs MGUS (p<0.003), G2 vs MGUS (p=0.003) for periostin; G1 vs MGUS (p<0.05), G2 vs MGUS (p<0.001) for sRANKL; G1 vs MGUS (p=0.011), G2 vs MGUS (p=0.0001) for osteopontin. No differences were detected between MGUS and controls and between patients in G1 and G2 groups. Spearman correlation analysis revealed moderate positive correlation between periostin and beta-2-microglobulin (r=0.416, p=0.018), percentage bone marrow myeloma PC (r=0.432, p=0.014), and serum total protein (r=0.427, p=0.015). Osteopontin levels were also positively related to beta-2-microglobulin (r=0.540, p=0.0014), percentage bone marrow myeloma PC (r=0.423, p=0.016), and serum total protein (r=0.413, p=0.019). Serum sRANKL was only related to beta-2-microglobulin levels (r=0.398, p=0.024). Conclusion: In the present study, serum levels of periostin, sRANKL and osteopontin in newly diagnosed MM patients were evaluated. They gradually increased from MGUS to more advanced stages of MM reflecting the severity of bone destruction. These results support the idea that some new protein markers could be used in monitoring the MBD as a most severe complication of MM.

Keywords: myeloma bone disease, periostin, sRANKL, osteopontin

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Authors: Asma Alyahya

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This study attempts to elicit the perceptions and attitudes of EFL learners of the Preparatory Year Program at KSU towards dialogue journal writing as an EFL learning strategy. The descriptive research design used incorporated both qualitative and quantitative instruments to accomplish the objectives of the study. A learners’ attitude questionnaire and follow-up interviews with learners from a randomly selected representative sample of the participants were employed. The participants were 55 female Saudi university students in the Preparatory Year Program at King Saud University. The analysis of the results indicated that the PYP learners had highly positive attitudes towards dialogue journal writing in their EFL classes and positive perceptions of the benefits of the use of dialogue journal writing as an EFL learning strategy. The results also revealed that dialogue journals are considered an effective EFL learning strategy since they fulfill various needs for both learners and instructors. Interestingly, the analysis of the results also revealed that Saudi university level students tend to write about personal topics in their dialogue journals more than academic ones.

Keywords: dialogue journals, EFL, learning strategy, writing

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Authors: Rutcher M. Lacaza, Stephen Jun V. Villejo

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This paper investigated the patterns of private transfers in the Philippines using the Family Income Expenditure Survey (FIES) 2009, conducted by the Philippine government’s National Statistics Office (NSO) every three years. The paper performed bivariate analysis on net transfers, using the identified determinants for a household to be either a net receiver or a net giver. The household characteristics considered are the following: age, sex, marital status, employment status and educational attainment of the household head, and also size, location, pre-transfer income and the number of employed members of the household. The variables net receiver and net giver are determined by computing the net transfer, subtracting total gifts from total receipts. The receipts are defined as the sum of cash received from abroad, cash received from domestic sources, total gifts received and inheritance. While gifts are defined as the sum of contributions and donations to church and other religious institutions, contributions and donations to other institutions, gifts and contributions to others, and gifts and assistance to private individuals outside the family. Both in kind and in cash transfers are considered in the analysis. It also performed a multiple regression analysis on transfers received and income including other household characteristics to examine the motives for giving transfers – whether altruism or exchanged. It also used the binary logistic regression to estimate the probability of being a net receiver or net giver given the household characteristics. The study revealed that receiving tends to be universal – both the non-poor and the poor benefit although the poor receive substantially less than the non-poor. Regardless of whether households are net receivers or net givers, households in the upper deciles generally give and receive more than those in the lower deciles. It also appears that private transfers may just flow within economic groups. Big amounts of transfers are, therefore, directed to the non-poor and the small amounts go to the poor. This was also supported by the increasing function of gross transfers received and the income of households – the poor receiving less and the non-poor receiving more. This is contrary to the theory that private transfers can help equalize the distribution of income. This suggested that private transfers in the Philippines are not altruistically motivated but exchanged. However, bilateral data on transfers received or given is needed to test this theory directly. The results showed that transfers are much needed by the poor and it is important to understand the nature of private transfers, to ensure that government transfer programs are properly designed and targeted so as to prevent the duplication of private safety nets already present among the non-poor.

Keywords: private transfers, net receiver, net giver, altruism, exchanged.

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Authors: Oyetunji John Adenuga

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analysed using t-test and regression analysis. The findings of the study revealed that there is significant difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State (t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching-aid facilities, laboratories and libraries. Government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators and government. Headmasters, proprietors and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves form time to time based on subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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Authors: John Gaber

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Planners regularly use citizen input as empirical data to help them better understand community issues they know very little about. This type of community data is based on the lived experiences of local residents and is known as "emic" data. What is becoming more common practice for planners is their use of data from local experts and stakeholders (known as "etic" data or the outsider perspective) to help them fill in the gaps in their analysis of applied planning research projects. Utilizing international Health Impact Assessment (HIA) data, I look at who planners invite to their citizen input investigations. Research presented in this paper shows that planners access a wide range of emic and etic community perspectives in their search for the “community’s view.” The paper concludes with how planners can chart out a new empirical path in their execution of emic/etic citizen participation strategies in their applied planning research projects.

Keywords: citizen participation, emic data, etic data, Health Impact Assessment (HIA)

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Authors: Samuel Abraham Berhane, Lingbing Bu

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This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

Keywords: aerosol-cloud-precipitation, aerosol optical depth, cloud effective radius, cloud optical thickness, HYSPLIT

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Authors: Cho Achidi

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Tomato is a crucial food crop significantly contributes to global food and nutrition security. However, postharvest losses severely limit its role. Therefore, it is necessary to develop sustainable strategies to minimize these losses and improve the shelf-life of tomato fruits. One of the major concerns is bacterial infections, particularly by faecal coliform bacteria, which can cause food poisoning and illnesses like diarrhoea and dysentery. This study seeks to identify the presence of coliform bacteria on tomato fruits in fields and markets in Muea, Buea Municipality. The study also evaluated different management strategies to reduce the bacterial incidence and load on tomato fruits. A total of 200 fruits were sampled for both the coliform survey and shelf-life analysis. Ten farmers and traders provided samples, including asymptomatic and symptomatic tomato fruits. The samples designated for shelf-life analysis were treated with Aquatab, warm water, lemon, and onion. The results indicated that out of the 80 symptomatic samples collected, 12.5% contained faecal and total coliform species. Among the ten farms sampled, 14% were infected with coliform bacteria, with the highest infestation rate of 60% recorded in field 4. Furthermore, 15% of the asymptomatic tomato fruits were found to be infected by coliform bacteria. Regarding the management strategies, Aquatabs exhibited the highest efficacy in reducing the incidence of coliform bacteria on tomato fruits, followed by onion and lemon extracts. Although hot water treatment effectively removed bacteria from the fruits, damaging the cell wall negatively affected their shelf-life. Overall, this study emphasizes the severity of coliform bacterial pathogens in the Muea area, particularly their occurrence on asymptomatic tomatoes, which poses a significant concern for plant quarantine services. It also demonstrates potential options for mitigating this bacterial challenge.

Keywords: tomato, shelf-life analysis, food and nutrition security, coliform bbacteria

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Authors: Jaehyung An, Sungjoo Lee

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Patent documents constitute an up-to-date and reliable source of knowledge for reflecting technological advance, so patent analysis has been widely used for identification of technological trends and formulation of technology strategies. But, identifying technological information from patent data entails some limitations such as, high cost, complexity, and inconsistency because it rely on the expert’ knowledge. To overcome these limitations, researchers have applied to a quantitative analysis based on the keyword technique. By using this method, you can include a technological implication, particularly patent documents, or extract a keyword that indicates the important contents. However, it only uses the simple-counting method by keyword frequency, so it cannot take into account the sematic relationship with the keywords and sematic information such as, how the technologies are used in their technology area and how the technologies affect the other technologies. To automatically analyze unstructured technological information in patents to extract the semantic information, it should be transformed into an abstracted form that includes the technological key concepts. Specific sentence structure ‘SAO’ (subject, action, object) is newly emerged by representing ‘key concepts’ and can be extracted by NLP (Natural language processor). An SAO structure can be organized in a problem-solution format if the action-object (AO) states that the problem and subject (S) form the solution. In this paper, we propose the new methodology that can extract the SAO structure through technical elements extracting rules. Although sentence structures in the patents text have a unique format, prior studies have depended on general NLP (Natural language processor) applied to the common documents such as newspaper, research paper, and twitter mentions, so it cannot take into account the specific sentence structure types of the patent documents. To overcome this limitation, we identified a unique form of the patent sentences and defined the SAO structures in the patents text data. There are four types of technical elements that consist of technology adoption purpose, application area, tool for technology, and technical components. These four types of sentence structures from patents have their own specific word structure by location or sequence of the part of speech at each sentence. Finally, we developed algorithms for extracting SAOs and this result offer insight for the technology innovation process by providing different perspectives of technology.

Keywords: NLP, patent analysis, SAO, semantic-analysis

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Authors: Mohammad Asadpour, Gholamreza Razmi, Gholamreza Mohammadi, Abolghasem Naghibi

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Cryptosporidium Spp., protozoan parasites of the phylum Apicomplexa, have a wide spectrum of hosts including humans, domestic animals and wild mammals, birds, reptiles, amphibians and fish. Dairy cattle have been identified in numerous reports as a major source of environmental contamination with this pathogen. In this study, a Polymerase Chain Reaction (PCR), Restriction Fragment Length Polymorphism (RFLP) analysis of the Small-Subunit (SSU) rRNA gene was used to detect and identify Cryptosporidium Spp. in 300 fecal specimens from 1 to 30 days pre-wean calves in 10 farms in Mashhad, Iran. Eighty five (28.3%) and forty five (15%) of the specimens were positive for Cryptosporidium by microscopic and PCR examination respectively. Restriction digestion of the PCR products by VSPI and Ssp1 restriction enzymes and analysis of sequence data revealed the presence of C. parvum, bovine genotype in all isolates. Our findings suggest that cattle can be a source of Cryptosporidial infections for humans and animals in Mashhad area. This is the first published description of Cryptosporidium sub genotyping in Mashhad.

Keywords: cryptosporidium, genotype, dairy calves, 18S rRNA, Mashhad

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Authors: Shabana Noureen, Zafar Mahmood

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Economies consistently engage in trade across borders and face tariff, non-tariff barriers and other quotas that constitute trade costs. The trade costs imposed by policy barriers on exports are considered an impediment in the export growth rate. This work aims to measure over-year trends in total and bilateral trade costs and their trends in relevance to policy barriers (tariff and non-tariff). The analysis through the micro-founded theoretically based gravity model showed that the total trade costs have a general decreasing trend in the world while in the case of developing countries, the rate by which these trends decline is very low. Bilateral trade cost estimates associated with the policy barriers represent that the non-tariff barriers in a developing country have a major role in sustaining the high trade costs as compared to the tariff barriers. This ultimately leads to a low net declining rate. This work emphasizes that for developing countries the non-tariff barriers are a major factor that renders their exports and to be uncompetitive in the world market.

Keywords: trade costs, policy barriers, tariff barriers, non-tariff barriers, trade policies, export growth

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Camilo A. Guerrero-Martin, Erik Montes Paez, Marcia C. K. Oliveira, Jonathan Campos, Elizabete F. Lucas

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Asphaltenes precipitation is considered as a formation damage problem, which can reduce the oil recovery factor. It fouls piping and surface installations, as well as cause serious flow assurance complications and decline oil well production. Therefore, researchers have shown an interest in chemical treatments to control this phenomenon. The aim of this paper is to assess the asphaltenes precipitation onset of crude oils in the presence of cardanol, by titrating the crude with n-heptane. Moreover, based on this results obtained at atmosphere pressure, the asphaltenes precipitation onset pressure were calculated to predict asphaltenes precipitation in the reservoir, by using differential liberation and refractive index data of the oils. The influence of cardanol concentrations in the asphaltenes stabilization of three Brazilian crude oils samples (with similar API densities) was studied. Therefore, four formulations of cardanol in toluene were prepared: 0, 3, 5, 10 and 15 m/m%. The formulations were added to the crude at 2:98 ratio. The petroleum samples were characterized by API density, elemental analysis and differential liberation test. The asphaltenes precipitation onset (APO) was determined by titrating with n-heptane and monitoring with near-infrared (NIR). UV-Vis spectroscopy experiments were also done to assess the precipitate asphaltenes content. The asphaltenes precipitation envelopes (APE) were also determined by numerical simulation (Multiflash). In addition, the adequate artificial lift systems (ALS) for the oils were selected. It was based on the downhole well profile and a screening methodology. Finally, the oil flowrates were modelling by NODAL analysis production system in the PIPESIM software. The results of this study show that the asphaltenes precipitation onset of the crude oils were 2.2, 2.3 and 6.0 mL of n-heptane/g of oil. The cardanol was an effective inhibitor of asphaltenes precipitation for the crude oils used in this study, since it displaces the precipitation pressure of the oil to lower values. This indicates that cardanol can increase the oil wells productivity.

Keywords: asphaltenes, NODAL analysis production system, precipitation pressure onset, inhibitory molecule

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Students’ emotional experiences have been a widely discussed theme among researchers, proving a central role on students’ outcomes. Yet, up to now, far too little attention has been paid to teaching practices that negatively relate with students’ negative emotions in the higher education. The present work aims to examine the relationship between teachers’ teaching practices (i.e., students’ evaluations of teaching and autonomy support), the students’ feelings of boredom and agentic engagement and motivation in the higher education context. To do so, the present study incorporates one of the most popular tools in natural processing language to address students’ evaluations of teaching: sentiment analysis. Whereas most research has focused on the creation of SA models and assessing students’ satisfaction regarding teachers and courses to the author’s best knowledge, no research before has included results from SA into an explanatory model. A total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) participated in the study. Students were enrolled in degree and masters’ studies at the faculty of Education of a public university of Spain. Data was collected using an online questionnaire students could access through a QR code they completed during a teaching period where the assessed teacher was not present. To assess students’ sentiments towards their teachers’ teaching, we asked them the following open-ended question: “If you had to explain a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?”. Sentiment analysis was performed with Microsoft's pre-trained model. For this study, we relied on the probability of the students answer belonging to the negative category. To assess the reliability of the measure, inter-rater agreement between this NLP tool and one of the researchers, who independently coded all answers, was examined. The average pairwise percent agreement and the Cohen’s kappa were calculated with ReCal2. The agreement reached was of 90.8% and Cohen’s kappa .68, both considered satisfactory. To test the hypothesis relations a structural equation model (SEM) was estimated. Results showed that the model fit indices displayed a good fit to the data; χ² (134) = 351.129, p < .001, RMSEA = .07, SRMR = .09, TLI = .91, CFI = .92. Specifically, results show that boredom was negatively predicted by autonomy support practices (β = -.47[-.61, -.33]), whereas for the negative sentiment extracted from SET, this relation was positive (β = .23[.16, .30]). In other words, when students’ opinion towards their instructors’ teaching practices was negative, it was more likely for them to feel bored. Regarding the relations among boredom and student outcomes, results showed a negative predictive value of boredom on students’ motivation to study (β = -.46[-.63, -.29]) and agentic engagement (β = -.24[-.33, -.15]). Altogether, results show a promising future for sentiment analysis techniques in the field of education as they proved the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, boredom, motivation, agentic engagement

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Kashvi Jain, Adam Burston

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Right-wing social movements are a dominant force in American politics, as evidenced by the January 6th Insurrection, the prevalence of extremist conspiracy theories, and a nationwide surge in hate crime. Despite an abundance of scholarship on contemporary right-wing extremism, there is little scholarship that explains their rise. This paper examines how the white power movement developed through tactical innovation and strategic use of increasingly powerful digital technologies. Using qualitative content analysis of archived digital bulletin boards and websites, we examine right-wing extremists’ digital communication during three consequential time periods of tactical and technological innovation: pre-internet (1980s), web 1.0 (1990s), and web 2.0 (2000s). Our analysis suggests that right-wing activists innovatively exploited the features and affordances of digital technologies and their knowledge of free speech rights to spread supremacist collective identity and ideology. Beyond our empirical contribution, we offer policy advice that school administrators can employ to limit hate.

Keywords: leaderless resistance, technological affordances, anti-defamation league, white power movement, tactical

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Authors: Ahmad Abubakar Sadiq, Nwohu Ndubuka Mark, Jacob Tsado, Ahmad Adam Asharaf, Agbachi E. Okenna, Enesi E. Yahaya, Ambafi James Garba

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Transmission system performance analysis is vital to proper planning and operations of power systems in the presence of deregulation. Key performance indicators (KPIs) are often used as measure of degree of performance. This paper gives a novel method to determine the transmission efficiency by evaluating the ratio of real power losses incurred from a specified transfer direction. Available Transmission Transfer Efficiency (ATTE) expresses the percentage of real power received resulting from inter-area available power transfer. The Tie line (Rated system path) performance is seen to differ from system wide (Network response) performance and ATTE values obtained are transfer direction specific. The required sending end quantities with specified receiving end ATC and the receiving end power circle diagram are obtained for the tie line analysis. The amount of real power loss load relative to the available transfer capability gives a measure of the transmission grid efficiency.

Keywords: performance, transmission system, real power efficiency, available transfer capability

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Authors: Mahsaossadat Pourrahmati Khelejan

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The purpose of this research was to identify and prioritize the sustainable development of sports venues using new and degradable energies with using the AHP Hierarchical Analysis approach. The research method is a descriptive strategy with regard to the direction of implementation and is a hierarchical research with a practical purpose. In this study, 30 experts (physical education faculty members, geography professors, accredited sports venues managers, and renewable energy engineers) were selected using purposeful sampling method as the research population. The research tool was a researcher-made questionnaire on the factors affecting the sustainable development of sports venues by using new technologies and degradable energy. Finally, the research questionnaire was designed with four components and 21 items. All steps were performed by using Expert Choice software. The importance of indicators that influence the sustainable development of sports venues is highlighted by the use of clean and degradable energy, for example: 1. Economic factor, weighing 0.420 2. Environmental index, weighing 0. 320 3. Physical index, weighing 0.148 4. Social index, weighing 0.122.

Keywords: Sports Venues, Sustainable Development, Degradable Energies, Prioritize

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Authors: Francesco Paolone

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This paper investigates the role of Operating Cash Flow (OCF) and accruals in firm valuation analyzing financial statement information from the largest European companies and evaluating their relation to firm market value. Using a dataset of 500 largest European companies in 2018, the study investigates the relative value-relevance of equity, net income and operating cash flow (OCF). Findings show that the cash flow measure has the same explanatory power and intensity as equity and earnings to explain the market value. This study contributes to the debate on the value relevance of OCF incremental to book value and earnings. It also extends the literature, showing that OCF has information content (value relevance) superior to earnings and book value in the main European markets (Bepari et al., 2013). Finally, the study provides a support that accounting method choice may confuse investors, who have reduced confidence in accounting earnings and book value; in other words, nowadays European investors rely more on cash flows instead of accruals numbers.

Keywords: Cash Flow Statement, Value Relevance, Accounting, Financial Statement Analysis

Procedia PDF Downloads 132