Search results for: data analyses

Authors: Reza Beheshti

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This paper examines remedies for defective manufactured goods in commercial circular economic transactions. The linear ‘take-make-dispose’ model fits well with the conventional remedial framework in which damages are considered the primary remedy. Damages under English Sales Law encourages buyers to look for a substitute seller with broadly similar goods to the ones agreed on in the original contract, enter into contract with this new seller and hence terminate the original contract. By doing so, the buyer ends the contractual relationship. This seems contrary to the core principles of the circular economy: keeping products, components, and materials in longer use, which can partly be achieved by product refurbishment. This process involves returning a product to good working condition by replacing or repairing major components that are faulty or close to failure and making ‘cosmetic’ changes to update the appearance of a product. This remedy has not been widely accepted or applied in commercial cases, which in turn flags up the secondary nature of performance-related remedies. This paper critically analyses the laws concerning the seller’s duty to cure in English law and the extent to which they correspond with core principles of the circular economy. In addition, this paper takes into account the potential of circular economic transactions being characterised as something other than sales. In such situations, the likely outcome will be a license to use products, which may limit the choice of remedy further. Consequently, this paper suggests an outline remedial framework specifically for commercial circular economic transactions in manufactured goods.

Keywords: circular economy, contract law, remedies, English Sales Law

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Authors: Ammar Aljabri, Alhussain Halawani, Alaa Ashqar, Omar Alageely

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Objective: mild Traumatic Brain Injury (mTBI) or concussion is a common yet undermanaged and underreported condition. This systematic review and meta-analysis aim to determine the efficacy of VRT as a treatment option for mTBI. Method: This review and meta-analysis was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and included RCTs and pre-VRT/post-VRT retrospective chart reviews. Records meeting the inclusion criteria were extracted from the following databases: Medline, Embase, and Cochrane Register of Controlled Trials (CENTRAL). Results: Eight articles met the inclusion criteria, and six RCTs were included in the meta-analysis. VRT demonstrated significant improvement in decreasing perceived dizziness at the end of the intervention program, as shown by DHI scores (SMD= -0.33, 95% CI -0.62 to -0.03, p=0.03, I2= 0%). However, no significant reduction in DHI was evident after two months of follow-up (SMD= 0.15, 95% CI -0.23 to 0.52, p=0.44, I2=0%). Quantitative analysis also depicts significant reduction in both VOMS (SMD=-0.40, 95% CI -0.60 to -0.20, p<0.0001, I2=0%) and PCSS (SMD= -0.39, 95% CI -0.71 to -0.07, p=0.02, I2=0%) following the intervention. Lastly, there was no significant difference between intervention groups on BESS scores (SMD= -31, 95% CI -0.71 to 0.10, p=0.14, I2=0%) and return to sport/function (95% CI 0.32 to 30.80, p=0.32, I2=82%). Conclusions: Current evidence on the efficacy of VRT for mTBI is limited. This review and analysis provide evidence that supports the role of VRT in improving perceived symptoms following concussion. There is still a need for high-quality trials evaluating the benefit of VRT using a standardized approach.

Keywords: concussion, traumatic brain injury, vestibular rehabilitation, neurorehabilitation

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Authors: S. C. Lin, W. W. Cheng, M. S. Wu

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This study attempted to investigate the connection between teacher professional development program and students’ Learning. This study took Readers’ Theater Teaching Program (RTTP) for professional development as an example to inquiry how participants apply their new knowledge and skills learned from RTTP to their teaching practice and how the impact influence students learning. The goals of the RTTP included: 1) to enhance teachers RT content knowledge; 2) to implement RT instruction in teachers’ classrooms in response to their professional development. 2) to improve students’ ability of reading fluency in professional development teachers’ classrooms. This study was a two-year project. The researchers applied mixed methods to conduct this study including qualitative inquiry and one-group pretest-posttest experimental design. In the first year, this study focused on designing and implementing RTTP and evaluating participants’ satisfaction of RTTP, what they learned and how they applied it to design their English reading curriculum. In the second year, the study adopted quasi-experimental design approach and evaluated how participants RT instruction influenced their students’ learning, including English knowledge, skill, and attitudes. The participants in this study composed two junior high school English teachers and their students. Data were collected from a number of different sources including teaching observation, semi-structured interviews, teaching diary, teachers’ professional development portfolio, Pre/post RT content knowledge tests, teacher survey, and students’ reading fluency tests. To analyze the data, both qualitative and quantitative data analysis were used. Qualitative data analysis included three stages: organizing data, coding data, and analyzing and interpreting data. Quantitative data analysis included descriptive analysis. The results indicated that average percentage of correct on pre-tests in RT content knowledge assessment was 40.75% with two teachers ranging in prior knowledge from 35% to 46% in specific RT content. Post-test RT content scores ranged from 70% to 82% correct with an average score of 76.50%. That gives teachers an average gain of 35.75% in overall content knowledge as measured by these pre/post exams. Teachers’ pre-test scores were lowest in script writing and highest in performing. Script writing was also the content area that showed the highest gains in content knowledge. Moreover, participants hold a positive attitude toward RTTP. They recommended that the approach of professional learning community, which was applied in RTTP was benefit to their professional development. Participants also applied the new skills and knowledge which they learned from RTTP to their practices. The evidences from this study indicated that RT English instruction significantly influenced students’ reading fluency and classroom climate. The result indicated that all of the experimental group students had a big progress in reading fluency after RT instruction. The study also found out several obstacles. Suggestions were also made.

Keywords: teacher’s professional development, program evaluation, readers’ theater, english reading instruction, english reading fluency

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Authors: Antonela Matana, Dubravka Brdar, Vesela Torlak, Marijana Popovic, Ivana Gunjaca, Ozren Polasek, Vesna Boraska Perica, Maja Barbalic, Ante Punda, Caroline Hayward, Tatijana Zemunik

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Parathyroid hormone (PTH) plays a critical role in the regulation of bone mineral metabolism and calcium homeostasis. Higher PTH levels are associated with heart failure, hypertension, coronary artery disease, cardiovascular mortality and poorer bone health. A twin study estimated that 60% of the variation in PTH concentrations is genetically determined. Only one GWAS of PTH concentration has been reported to date. Identified loci explained 4.5% of the variance in circulating PTH, suggesting that additional genetic variants remain undiscovered. Therefore, the aim of this study was to identify novel genetic variants associated with PTH levels in a general population. We have performed a GWAS meta-analysis on 2596 individuals originating from three Croatian cohorts: City of Split and the Islands of Korčula and Vis, within a large-scale project of “10,001 Dalmatians”. A total of 7 411 206 variants, imputed using the 1000 Genomes reference panel, with minor allele frequency ≥ 1% and Rsq ≥ 0.5 were analyzed for the association. GWAS within each data set was performed under an additive model, controlling for age, gender and relatedness. Meta-analysis was conducted using the inverse-variance fixed-effects method. Furthermore, to identify sex-specific effects, we have conducted GWAS meta-analyses analyzing males and females separately. In addition, we have performed biological pathway analysis. Four SNPs, representing one locus, reached genome-wide significance. The most significant SNP was rs11099476 on chromosome 4 (P=1.15x10-8), which explained 1.14 % of the variance in PTH. The SNP is located near the protein-coding gene RASGEF1B. Additionally, we detected suggestive association with SNPs, rs77178854 located on chromosome 2 in the DPP10 gene (P=2.46x10-7) and rs481121 located on chromosome 1 (P=3.58x10-7) near the GRIK1 gene. One of the top hits detected in the main meta-analysis, intron variant rs77178854 located within DPP10 gene, reached genome-wide significance in females (P=2.21x10-9). No single locus was identified in the meta-analysis in males. Fifteen biological pathways were functionally enriched at a P<0.01, including muscle contraction, ion homeostasis and cardiac conduction as the most significant pathways. RASGEF1B is the guanine nucleotide exchange factor, known to be associated with height, bone density, and hip. DPP10 encodes a membrane protein that is a member of the serine proteases family, which binds specific voltage-gated potassium channels and alters their expression and biophysical properties. In conclusion, we identified 2 novel loci associated with PTH levels in a general population, providing us with further insights into the genetics of this complex trait.

Keywords: general population, genome-wide association analysis, parathyroid hormone, single nucleotide polymorphisms.

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Authors: Justyna Żywiołek, Marek Matulewski

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Data, is information processed by enterprises for primary and secondary purposes as processes. Thanks to processing, the sales process takes place; in the case of the surveyed companies, sales take place online. However, this indirect form of contact with the customer causes many problems for both customers and furniture manufacturers. The article presents solutions that would solve problems related to the analysis of data and information in the order fulfillment process sent to post-warranty service. The article also presents an analysis of threats to the security of this information, both for customers and the enterprise.

Keywords: ordering furniture online, information security, furniture industry, enterprise security, risk analysis

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Authors: Christian H. Girsang, M. Razi B. Mansoor, Noorizal N. Huang

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An offshore platform was installed in 1977 at about 260km offshore West Malaysia at the water depth of 73.6m. Twelve (12) piles were installed with four (4) are skirt piles. The piles have 1.219m outside diameter and wall thickness of 31mm and were driven to 109m below seabed. Deterministic analyses of the pile capacity under axial loading were conducted using the current API (American Petroleum Institute) method and the four (4) CPT-based methods: the ICP (Imperial College Pile)-method, the NGI (Norwegian Geotechnical Institute)-Method, the UWA (University of Western Australia)-method and the Fugro-method. A statistical analysis of the model uncertainty associated with each pile capacity method was performed. There were two (2) piles analysed: Pile 1 and piles other than Pile 1, where Pile 1 is the pile that was most affected by shallow gas problems. Using the mean estimate of soil properties, the five (5) methods used for deterministic estimation of axial pile capacity in compression predict an axial capacity from 28 to 42MN for Pile 1 and 32 to 49MN for piles other than Pile 1. These values refer to the static capacity shortly after pile installation. They do not include the effects of cyclic loading during the design storm or time after installation on the axial pile capacity. On average, the axial pile capacity is expected to have increased by about 40% because of ageing since the installation of the platform in 1977. On the other hand, the cyclic loading effects during the design storm may reduce the axial capacity of the piles by around 25%. The study concluded that all piles have sufficient safety factor when the pile aging and cyclic loading effect are considered, as all safety factors are above 2.0 for maximum operating and storm loads.

Keywords: axial capacity, cyclic loading, pile ageing, shallow gas

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Authors: Judith Sue Hwa Joo

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Guanyin (Avalokiteśvara in Sanskrit), the Bodhisattva of Mercy and Compassion, is the most widely worshipped Buddhist Divinity in Chinese societies and is also believed by more than half of Asian populations across various countries. The most overwhelming reason for the popularity of Guanyin in Chinese societies is, according to the Lotus Sutra, that Guanyin would apperceive voices of those suffering from immense afflictions and troubles, and liberate them upon crying for his/her holy name with wholeheartedness. Its pervasive social influence has spanned more than two thousand years and is still deeply affecting the lives of most Chinese people. This study aimed to investigate whether Guanyin Worship has evolved and changed in modern Chinese societies across the Taiwan Strait. Taiwan and China, albeit having the same language and culture, have been territorially divided and governed by two different political regimes for over 70 years. It would be scientifically intriguing to unveil any substantial changes in religious behaviors in the context of Guanyin Worship. A comprehensive anonymous questionnaire survey in Chinese communities was conducted from October 2017 to May 2019 across various countries, mostly in China, Taiwan, and Hong Kong areas. Since the religious survey is officially prohibited in China, the study was difficult and could only be exercised by means of snowball sampling. Demographic data (age, sex, education, religious belief) were registered and Guanyin’s salvation functions under various confronting situations were investigated. Psychological dimensions of religious belief in Guanyin were probed in terms of the worship experience, the willingness of veneration, and egoistic or altruistic ideations. A literature review on documented functional attributes was carried out in parallel for comparison analyses with traditional roles. Effective 1123 out of 1139 samples were obtained. Statistical analysis revealed that Guanyin Worship is still commonly practiced and deeply rooted in the hearts of all Chinese people regardless of gender, age, education, and residential area, even though they may not enshrine Guanyin at home nowadays. The conventional roles of Guanyin Bodhisattva are still valid and best satisfy the real interests of lifestyles in modern times. When comparing the traditional Buddhist Sutra and the documented literature, the divine power of modern Guanyin has notably empowered to recover, protect and transform fetal and infant spirits due to the sexual liberation, increased abortion rate, gender awakening and enhanced female autonomy in the reproductive decision. However, the One-Child policy may have critically impacted the trajectory of Guanyin Worship so that people in China prevail over those in Taiwan praying for aborted lives or premature deaths. Furthermore, particularly in Hong Kong and Macao, Guanyin not only serves as the sea guardian for the fishermen but also additional services a new function as the God of Wealth. The divine powers and salvation functions of Guanyin are indeed evolving and expanding to comply with the modern psychosocial, cultural and societal needs. This study sheds light on the modernization process of the two-thousand-year-old Guanyin Worship of contemporary Chinese societies.

Keywords: Buddhism, Guanyin, religious behavior, salvation function

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Authors: M. Demir, A. Demir

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The aim of this study is to examine the family sense of coherence of early childhood education students. The Family Sense of Coherence Inventory has applied to 233 (108 girls and 125 boys) early childhood education students in Turkey. At the stage of data collection, with the aim of determining the family sense of coherence of early childhood education students, Family Sense of Coherence Inventory which was developed by Çeçen (2007) was used. In the process of the analysis of data, independent samples t-test, and one-way ANOVA were used. According to the results of the study, there were significant differences between some demographic variables in terms of the family sense of coherence.

Keywords: family sense of coherence, early childhood education students

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Authors: Emil Ghiocel Ioanid, Viorica Frunză, Dorina Rusu, Ana Maria Vlad, Catalin Tanase, Simona Dunca

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The application of cold radio-frequency (RF) plasma in the conservation of cultural heritage became important in the last decades due to the positive results obtained in decontamination treatments. This paper presents an equipment especially designed for RF cold plasma application on paper documents, developed within a research project. The equipment allows the application of decontamination and cleaning treatments on any type of paper support, as well as the coating with a protective polymer. The equipment consists in a Pyrex vessel, inside which are placed two plane-parallel electrodes, capacitively coupled to a radio-frequency generator. The operating parameters of the equipment are: 1.2 MHz frequency, 50V/cm electric field intensity, current intensity in the discharge 100 mA, 40 W power in the discharge, the pressure varying from 5∙10-1 mbar to 5.5∙10-1 mbar, depending on the fragility of the material, operating in gaseous nitrogen. In order to optimize the equipment treatments in nitrogen plasma have been performed on samples infested with microorganisms, then the decontamination and the changes in surface properties (color, pH) were assessed. The analyses results presented in the table revealed only minor modifications of surface pH the colorimetric analysis showing a slight change to yellow. The equipment offers the possibility of performing decontamination, cleaning and protective coating of paper-based documents in successive stages, thus avoiding the recontamination with harmful biological agents.

Keywords: nitrogen plasma, cultural heritage, paper support, radio-frequency

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Authors: Hema Vanita Kesevan

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The global spread of Covid-19 virus in early 2020 has led to major changes in many walks of life, including the education system. Traditional face to face lessons that were carried out for years has been replaced by online learning. Although online learning has been used before the pandemic, it has not been the only source of teaching and learning. This drastic change has brought significant impact to the process of teaching and learning in many classrooms around the world. Likewise, in country like Malaysia that that has been promoting online learning but has not utilize it fully due to many restrictions in terms of technology, accessibility, and online literacy, the sudden change to full online platform learning in all educational sector has definitely caused Issues in terms of its adaptation and usage. Although many studies have been conducted to explore the efficiency and impact of online learning during the pandemic, studies focusing on the same are limited in Malaysian classroom context, especially in English language classrooms. Thus, this study seeks to explore on the efficacy and effectiveness of online learning tools in ESL classroom contexts during the pandemic. The aim of this study is to understand the educator's and student's perceptions on the implementation of online learning tools in the teaching and learning process and the types of online learning tools that were used to assist the teaching and learning process during the pandemic. Particularly, this study focused to explore the types of online learning tools used in Malaysian schools and university during the online teaching and learning process and further explores how the various types of tools used impacted the students' participation in the lessons conducted. The participants of this study are secondary school students, teachers, and university students. Data will be collected in terms of survey questionnaire and interviews. The survey data intends to obtain information on the types of online learning used in ESL teaching and learning practices during the pandemic, how the various types of online tools influence students' participation during lessons. The interview data from the teachers serves to provide information about the selection of online learning tools, challenges of using it to conduct online lessons, and other arising issues. A mixed method design will be used to analysed the data obtained. The questionnaire will be analysed quantitatively using descriptive analysis meanwhile, the interview data will be analysed qualitatively.

Keywords: Covid 19, online learning tools, ESL classroom, effectiveness, efficacy

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Authors: Nyoman Wijana, Chandra Arha

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Disclosures of Intellectual Capital (IC) is a presentation of corporate information assets that are not recorded in the financial statements. This disclosures is very helpful because it provides inform corporate assets are intangible. In the new economic era, the company's intangible assets will determine company's competitive advantage. This study aimed to examine the effect of IC disclosures on market capitalization growth. Observational studies conducted over ten years in 2002-2011. The purpose of this study was to determine the effect for last ten years. One hundred samples of the company's largest market capitalization in 2011 traced back to last ten years. Data that used, are in 2011, 2008, 2005, and 2002 Method that’s used for acquiring the data is content analysis. The analytical method used is Ordinanary Least Square (OLS) and analysis tools are e views 7 This software using Pooled Least Square estimation parameters are specifically designed for panel data. The results of testing analysis showed inconsistent expression levels affect the growth of the market capitalization in each year of observation. The results of this study are expected to motivate the public company in Indonesia to do more voluntary IC disclosures and encourage regulators to make regulations in a comprehensive manner so that all categories of the IC must be disclosed by the company.

Keywords: IC disclosures, market capitalization growth, analytical method, OLS

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Authors: T. Pedersen, A. Lindfeldt

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The minimum dwell time is an important part of railway timetable planning. Due to its stochastic behaviour, the minimum dwell time should be considered to create resilient timetables. While there has been significant focus on how to determine and estimate dwell times, to our knowledge, little research has been carried out regarding temporal and running direction variations of these. In this paper, we examine how the minimum dwell time varies depending on temporal factors such as the time of day, day of the week and time of the year. We also examine how it is affected by running direction and station type. The minimum dwell time is estimated by means of track occupation data. A method is proposed to ensure that only minimum dwell times and not planned dwell times are acquired from the track occupation data. The results show that on an aggregated level, the average minimum dwell times in both running directions at a station are similar. However, when temporal factors are considered, there are significant variations. The minimum dwell time varies throughout the day with peak hours having the longest dwell times. It is also found that the minimum dwell times are influenced by weekday, and in particular, weekends are found to have lower minimum dwell times than most other days. The findings show that there is a potential to significantly improve timetable planning by taking minimum dwell time variations into account.

Keywords: minimum dwell time, operations quality, timetable planning, track occupation data

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Alex Sidarta Guglielmoni

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Since the 1970s, sustainable development has become increasingly present on the international agenda. The present work has as general objective to analyze, discuss and bring answers to the following question, what is the importance of the generation of electric energy through the wind power plants in the Brazilian electricity matrix between 2013 and 2019? To answer this question, we analyzed the generation of renewable energy from wind farms and the consumption of electricity in Brazil during the period of January 2013 until December 2020. The specific objectives of this research are: to analyze the public data, to identify the total wind generation, to identify the total wind capacity generation, to identify the percentage participation of the generation and generation capacity of wind energy in the Brazilian electricity matrix. In order to develop this research, it was necessary a bibliographic search, collection of secondary data, tabulation of generation data, and electricity capacity by a comparative analysis between wind power and the Brazilian electricity matrix. As a result, it was possible to observe how important Brazil is for global sustainable development and how much this country can grow with this, in view of its capacity and potential for generating wind power since this percentage has grown in past few years.

Keywords: wind power, Brazilian market, electricity matrix, generation capacity

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Authors: Hounyèmè Romuald, Maxime Logez, Mama Daouda, Argillier Christine

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In view of the very strong degradation of aquatic ecosystems, it is urgent to set up monitoring systems that are best able to report on the effects of the stresses they undergo. This is particularly true in developing countries, where specific and relevant quality standards and funding for monitoring programs are lacking. The objective of this study was to make a relevant and objective choice of physicochemical parameters informative of the main stressors occurring on African lakes and to identify their alteration thresholds. Based on statistical analyses of the relationship between several driving forces and the physicochemical parameters of the Nokoué lagoon, relevant Physico-chemical parameters were selected for its monitoring. An innovative method based on Bayesian statistical modeling was used. Eleven Physico-chemical parameters were selected for their response to at least one stressor and their threshold quality standards were also established: Total Phosphorus (<4.5mg/L), Orthophosphates (<0.2mg/L), Nitrates (<0.5 mg/L), TKN (<1.85 mg/L), Dry Organic Matter (<5 mg/L), Dissolved Oxygen (>4 mg/L), BOD (<11.6 mg/L), Salinity (7.6 .), Water Temperature (<28.7 °C), pH (>6.2), and Transparency (>0.9 m). According to the System for the Evaluation of Coastal Water Quality, these thresholds correspond to” good to medium” suitability classes, except for total phosphorus. One of the original features of this study is the use of the bounds of the credibility interval of the fixed-effect coefficients as local weathering standards for the characterization of the Physico-chemical status of this anthropized African ecosystem.

Keywords: driving forces, alteration thresholds, acadjas, monitoring, modeling, human activities

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Authors: Feda Negesse

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One of the most important indicators of research quality is a good data - collection instrument that can yield reliable and valid data. The Swadesh wordlist has been used for more than half a century for collecting data in comparative and historical linguistics though arbitrariness is observed in its application and size. This research compare s the classification results of the 100 Swadesh wordlist with those of its subsets to determine if reducing the size of the wordlist impact s its effectiveness. In the comparison, the 100, 50 and 40 wordlists were used to compute lexical distances of 29 Cushitic and Semitic languages spoken in Ethiopia and neighbouring countries. Gabmap, a based application, was employed to compute the lexical distances and to divide the languages into related clusters. The study shows that the subsets are not as effective as the 100 wordlist in clustering languages into smaller subgroups but they are equally effective in di viding languages into bigger groups such as subfamilies. It is noted that the subsets may lead to an erroneous classification whereby unrelated languages by chance form a cluster which is not attested by a comparative study. The chance to get a wrong result is higher when the subsets are used to classify languages which are not closely related. Though a further study is still needed to settle the issues around the size of the Swadesh wordlist, this study indicates that the 50 and 40 wordlists cannot be recommended as reliable substitute s for the 100 wordlist under all circumstances. The choice seems to be determined by the objective of a researcher and the degree of affiliation among the languages to be classified.

Keywords: classification, Cushitic, Swadesh, wordlist

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Nafisa Banu

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The present study is an attempt to analyze the regional disparities in the level of education in West Bengal. The data based on secondary sources obtained from a census of India. The study is divided into four sections. The first section presents introductions, objectives and brief descriptions of the study area, second part discuss the methodology and data base, while third and fourth comprise the empirical results, interpretation, and conclusion respectively. For showing the level of educational development, 8 indicators have been selected and Z- score and composite score techniques have been applied. The present study finds out there are large variations of educational level due to various historical, economical, socio-cultural factors of the study area.

Keywords: education, regional disparity, literacy rate, Z-score, composite score

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Authors: Paraskevi Liosatou

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Climate change is considered to be of global concern being amplified by the fact that by its nature, cannot be spatially limited. This fact makes necessary the intergovernmental decision-making procedures. In the intergovernmental level, the institutions such as the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change develop efforts, methods, and practices in order to plan and suggest climate mitigation and adaptation measures. These measures are based on specific scientific findings and methods making clear the strong connection between science and policy. In particular, these scientific recommendations offer a series of practices, methods, and choices mitigating the problem by aiming at the indirect mitigation of the causes and the factors amplifying climate change. Moreover, modern production and economic context do not take into consideration the social, political, environmental and spatial dimensions of the problem. This work studies the decision-making process working in international and European level. In this context, this work considers the policy tools that have been implemented by various intergovernmental organizations. The methodology followed is based mainly on the critical study of standards and process concerning the connections and cooperation between science and policy as well as considering the skeptic debates developed. The finding of this work focuses on the links between science and policy developed by the institutional and scientific mechanisms concerning climate change mitigation. It also analyses the dimensions and the factors of the science-policy framework; in this way, it points out the causes that maintain skepticism in current scientific circles.

Keywords: climate change, climate change mitigation, climate change skepticism, IPCC, skepticism

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Authors: Bhawesh Kumar, A. P. Krishna

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There are continuous changes upon earth’s surface by a variety of natural and anthropogenic agents cut, carry away and depositing of minerals from land. Running water has higher capacity of erosion than other geomorphologic agents. This research work has been carried out on Ganga River, whose channel is continuously changing under the influence of geomorphic agents and human activities in the surrounding regions. The main focus is to study morphological characteristics and sand dynamics of Ganga River with particular emphasis on bank lines and width changes using remote sensing and GIS techniques. The advance remote sensing data and topographical data were interpreted for obtaining 52 years of changes. For this, remote sensing data of different years (LANDSAT TM 1975, 1988, 1993, ETM 2005 and ETM 2012) and toposheet of SOI for the year 1960 were used as base maps for this study. Sinuosity ratio, braiding index and migratory activity index were also established. It was found to be 1.16 in 1975 and in 1988, 1993, 2005 and 2005 it was 1.09, 1.11, 1.1, 1.09 respectively. The analysis also shows that the minimum value found in 1960 was in reach 1 and maximum value is 4.8806 in 2012 found in reach 4 which suggests creation of number of islands in reach 4 for the year 2012. Migratory activity index (MAI), which is a standardized function of both length and time, was computed for the 8 representative reaches. MAI shows that maximum migration was in 1975-1988 in reach 6 and 7 and minimum migration was in 1993-2005. From the channel change analysis, it was found that the shifting of bank line was cyclic and the river Ganges showed a trend of southward maximum values. The advanced remote sensing data and topographical data helped in obtaining 52 years changes in the river due to various natural and manmade activities like flood, water velocity and excavation, removal of vegetation cover and fertile soil excavation for the various purposes of surrounding regions.

Keywords: braided index, migratory activity index (MAI), Ganga river, river morphology

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Authors: Imren Kutlu, Nurdilek Gulmezoglu

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Triticale (Triticosecale Wittmack) is a man-made crop developed by crossing wheat (Triticum L.) and rye (Secale cereale L.). Triticale has until now been used mostly for animal feed; however, it can be consumed by humans in the form of biscuits, cookies, and unleavened bread. Moreover, one of the reasons for the development of triticale is that it is more efficient in nutrient deficient soil than wheat cultivars. After nitrogen fertilizer, phosphorus (P) is the most used fertilizer for crop production because P fixation occurs highly when it is applied the soil. The aim of the present study was to evaluate P uptake of winter triticale genotypes under different P fertilizer rates in different growth stages. The experiment was conducted in Eskisehir, Central Anatolia, Turkey. Treatments consisted of five triticale lines and one triticale cultivars (Samursortu) with four rates of P fertilization (0, 30, 60 and 120 kg P2O5 ha⁻¹). Phosphorus uptake of triticale genotypes in tillering, heading, as well as grain and straw at harvest stage and yield of grain and straw were determined. The results showed that a P rate of 60 kg/ha and the TCL-25 genotype produced the highest yields of straw and grain at harvest. Phosphorus uptake was the highest in tillering stage, and it decreased towards to harvest time. Phosphorus uptake of all growth stage increased as P rates raised and the application of 120 kg/ha P₂O₅ had the highest P uptake. Phosphorus uptake of genotypes was found differently. The regression analyses indicated that P uptake at tillering stage was the most effective on grain yield. These results will provide useful information to triticale growers about suitable phosphorus fertilization for both forage and food usage.

Keywords: grain yield, growth stage, phosphorus fertilization, phosphorus uptake, triticale

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Authors: Bel G Raggad

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An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

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Authors: Flavia Smarrazzo

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Initial-boundary value problems for nonlinear parabolic equations having a Radon measure as initial data have been widely investigated, looking for solutions which for positive times take values in some function space. On the other hand, if the diffusivity degenerates too fast at infinity, it is well known that function-valued solutions may not exist, singularities may persist, and it looks very natural to consider solutions which, roughly speaking, for positive times describe an orbit in the space of the finite Radon measures. In this general framework, our purpose is to introduce a concept of measure-valued solution which is consistent with respect to regularizing and smoothing approximations, in order to develop an existence theory which does not depend neither on the level of degeneracy of diffusivity at infinity nor on the choice of the initial measures. In more detail, we prove existence of suitably defined measure-valued solutions to the homogeneous Dirichlet initial-boundary value problem for a class of nonlinear parabolic equations without strong coerciveness. Moreover, we also discuss some qualitative properties of the constructed solutions concerning the evolution of their singular part, including conditions (depending both on the initial data and on the strength of degeneracy) under which the constructed solutions are in fact unction-valued or not.

Keywords: degenerate parabolic equations, measure-valued solutions, Radon measures, young measures

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Authors: S. Damapong, C. Kingkeow, W. Kongnoo, P. Pattapokin, S. Pruenglamphu

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As the presence of Thai children double burden malnutrition, we conducted a project to promote holistic age-appropriate nutrition for Thai children. Researchers developed P1-P7 computer software for managing and analyzing diverse types of collected data. The study objectives were: i) to use software to manage and analyze the collected data, ii) to evaluate the children nutritional status and their caretakers’ nutrition practice to create regulations for improving nutrition. Data were collected by means of questionnaires, called P1-P7. P1, P2 and P5 were for children and caretakers, and others were for institutions. The children nutritional status, height-for-age, weight-for-age, and weight-for-height standards were calculated using Thai child z-score references. Institution evaluations consisted of various standard regulations including the use of our software. The results showed that the software was used in 44 out of 118 communities (37.3%), 57 out of 240 child development centers and nurseries (23.8%), and 105 out of 152 schools (69.1%). No major problems have been reported with the software, although user efficiency can be increased further through additional training. As the result, the P1-P7 software was used to manage and analyze nutritional status, nutrition behavior, and environmental conditions, in order to conduct Thai Child Evaluation (TCE). The software was most widely used in schools. Some aspects of P1-P7’s questionnaires could be modified to increase ease of use and efficiency.

Keywords: P1-P7 software, Thai child evaluation, nutritional status, malnutrition

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Authors: Sibel Yoleri

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In this research it is aimed to determine the adjustment of students who attend the first class at elementary school to school in terms of several variables. The study group of the research consists of 286 students (131 female, 155 male) who continue attending the first class of elementary school in 2013-2014 academic year, in the city center of Uşak. In the research, ‘Personal Information Form’ and ‘Walker-Mcconnell Scale of Social Competence and School Adjustment’ have been used as data collection tools. In the analysis of data, the t-test has been applied in the independent groups to determine whether the sampling group students’ scores of school adjustment differ according to the sex variable or not. For the evaluation of data identified as not showing normal distribution, Mann Whitney U test has been applied for paired comparison, Kruskal Wallis H test has been used for multiple comparisons. In the research, all the statistical processes have been evaluated bidirectional and the level of significance has been accepted as .05. According to the results gathered from the research, a meaningful difference could not been identified in the level of students’ adjustment to school in terms of sex variable. At the end of the research, it is identified that the adjustment level of the students who have started school at the age of seven is higher than the ones who have started school at the age of five and the adjustment level of the students who have preschool education before the elementary school is higher than the ones who have not taken.

Keywords: starting school, preschool education, school adjustment, Walker-Mcconnell Scale

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Authors: Nur A. Azmi, Suseela D. Chandran, Fadilah Puteh, Azizan Zainuddin

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Medical tourism has been associated as a global phenomenon in developed and developing countries in the 21st century. Medical tourism is defined as an activity in which individuals who travel from one country to another country to seek or receive medical healthcare. Based on the global trend, the number of medical tourists is increasing annually, especially in the Southeast Asia (SEA) region. Since the establishment of Association of Southeast Asian Nations (ASEAN) in 1967, the SEA nations have worked towards regional integration in medical tourism. The medical tourism in the SEA has become the third-largest sector that contributes towards economic development. Previous research has demonstrated several factors that affect the development of medical tourism. However, despite the already published literature on SEA's medical tourism in the last ten years there continues to be a scarcity of research on niche areas each of the SEA countries. Hence, this paper is significant in enriching the literature in the field of medical tourism particularly in showcasing the niche market of medical tourism among the SEA best players namely Singapore, Thailand, Malaysia and Indonesia. This paper also contributes in offering a comparative analysis between the said nations whether they are complementing or competing with each other in the medical tourism sector. This then, will increase the availability of information in SEA region on medical tourism. The data was collected through an in-depth interview with various stakeholders and private hospitals. The data was then analyzed using two approaches namely thematic analysis (interview data) and document analysis (secondary data). The paper concludes by arguing that the ASEAN countries have specific niche market to promote their medical tourism industry. This paper also concludes that these key nations complement each other in the industry. In addition, the medical tourism sector in SEA region offers greater prospects for market development and expansion that witnessed the emerging of new key players from other nations.

Keywords: healthcare services, medical tourism, medical tourists, SEA region, comparative analysis

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Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan

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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.

Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks

Procedia PDF Downloads 500