Search results for: Seismic attributes

Authors: Yaru Meng

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The study contributes to the small but growing literature around computerized approaches to dynamic assessment (C-DA), wherein individual items are accompanied by mediating prompts. Mediation in the current computerized dynamic listening assessment (CDLA) was informed by an attribute-based mediation model (AMM) that identified the underlying L2 listening cognitive abilities and associated descriptors. The AMM served to focus mediation during C-DA on particular cognitive abilities with a goal of specifying areas of learner difficulty. 86 low-intermediate L2 English learners from a university in China completed three listening assessments, with an experimental group receiving the CLDA system and a control group a non-dynamic assessment. As an assessment, the use of the AMM in C-DA generated detailed diagnoses for each learner. In addition, both within- and between-group repeated ANOVA found greater gains at the level of specific attributes among C-DA learners over the course of a 5-week study. Directions for future research are discussed.

Keywords: computerized dynamic assessment, effectiveness, English as foreign language listening, attribute-based mediation model

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Authors: Reza Karami, Ali Akbar Ebrahimi

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This paper discusses concurrent engineering of robot manipulators, based on the Holistic Concurrent Design (HCD) methodology and by using a hardware-in-the-loop simulation platform. The methodology allows for considering numerous design variables with different natures concurrently. It redefines the ultimate goal of design based on the notion of satisfaction, resulting in the simplification of the multi-objective constrained optimization process. It also formalizes the effect of designer’s subjective attitude in the process. To enhance modeling efficiency for both computation and accuracy, a hardware-in-the-loop simulation platform is used, which involves physical joint modules and the control unit in addition to the software modules. This platform is implemented in the HCD design architecture to reliably evaluate the design attributes and performance super criterion during the design process. The resulting overall architecture is applied to redesigning kinematic, dynamic and control parameters of an industrial robot manipulator.

Keywords: concurrent engineering, hardware-in-the-loop simulation, robot manipulator, multidisciplinary systems, mechatronics

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Authors: Alexandre M. Brighenti

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One of the most damaging species in sunflower crops in Brazil is the hairy beggarticks (Bidens pilosa L.). The large number of seeds, the various vegetative cycles during the year, the staggered germination and the scarcity of selective and effective herbicides to control this weed in sunflower are some of attributes that hinder the effectiveness in controlling hairy beggarticks populations. The experiment was carried out with the objectives of evaluating the control of hairy beggarticks plants in sunflower crops, and to assess sunflower tolerance to residual herbicides. The treatments were as follows: S-metolachlor (1,200 and 2,400 g ai ha^-1), flumioxazin (60 and 120 g ai ha^-1), sulfentrazone (150 and 300 g ai ha^-1) and two controls (weedy and weed-free check). Phytotoxicity on sunflower plants, percentage of control and density of hairy beggarticks plants, sunflower stand and plant height, head diameter, oil content and sunflower yield were evaluated. The herbicides flumioxazin and sulfentrazone were the most efficient in hairy beggarticks control. S-metolachlor provided acceptable control levels. S-metolachlor (1,200 g ha^-1), flumioxazin (60 g ha^-1) and sulfentrazone (150 g ha^-1) were the most selective doses for sunflower crop.

Keywords: flumioxazin, Helianthus annuus, S-metolachlor, sulfentrazone, weeds

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Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

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A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Najla Althuniyan

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Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

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Authors: Maria Luskova, Maria Hudakova, Katarina Buganova

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Established objective and subjective preconditions for entrepreneurship, forming the business organically related whole, are the necessary condition of successful entrepreneurial activities. Objective preconditions for entrepreneurship are developed by the market economy that should stimulate entrepreneurship by allowing the use of economic opportunities for all those who want to do business in respective field while providing guarantees to all owners and creating a stable business environment for entrepreneurs. Subjective preconditions of entrepreneurship are formed primarily by personal characteristics of the entrepreneur. These are his properties, abilities, skills, physiological, and psychological preconditions which may be inherited, inborn or sequentially developed and obtained during his life on the basis of education and influences of surrounding environment. The paper is dealing with issues of objective and subjective preconditions for entrepreneurship and provides their analysis in view of the current situation in Slovakia. It presents risks of the business environment in Slovakia that the Slovak managers considered the most significant in 2014 and defines the dominant attributes of the entrepreneur in the current business environment in Slovakia.

Keywords: entrepreneurship, innovations, opportunity, risk, uncertainty

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Authors: Mehmet Karahan, Nevin Karahan

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Water and air permeability and thermal resistance of fabrics are the important attributes which strongly influence the thermo-physiological comfort properties of sportswear fabrics in different environmental conditions. In this work, terry and fleece fabrics were developed by varying the fiber content and areal density of fabrics. Further, the thermo-physical properties, including air permeability, water vapor permeability, and thermal resistance, of the developed fabrics were analyzed before and after washing. The multi-response optimization of thermo-physiological comfort properties was done by using principal component analysis (PCA) and Taguchi signal to noise ratio (PCA-S/N ratio) for optimal properties. It was found that the selected parameters resulted in a significant effect on thermo-physiological comfort properties of knitted fabrics. The PCA analysis showed that before wash, 100% cotton fabric with an aerial weight of 220 g.m⁻² gave optimum values of thermo-physiological comfort.

Keywords: thermo-physiological comfort, fleece knitted fabric, air permeability, water vapor transmission, cotton/polyester

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Li Yong

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Using the data of 135 financial institutions in China from 2018 to 2022, this paper deeply analyzes the underlying theoretical mechanism of artificial intelligence (AI) technology promoting financial development and examines the impact of AI technology on the digital transformation performance of financial enterprises. It is found that the level of AI technology has a significant positive impact on the development of finance. Compared with the impact on the expansion of financial scale, AI technology plays a greater role in improving the performance of financial institutions, reflecting the trend characteristics of the current AI technology to promote the evolution of financial structure. By investigating the intermediary transmission effects, we found that AI technology plays a positive role in promoting the performance of financial institutions by reducing operating costs and improving customer satisfaction, but its function in innovating financial products and mitigating financial risks is relatively limited. In addition, the promotion of AI technology in financial development has significant heterogeneity in terms of the type, scale, and attributes of financial institutions.

Keywords: artificial intelligence technology, financial development, China, heterogeneity

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Rapid urban development leads to the construction of urban tunnels for transport. Passage of tunnels under the surface structures and utilities prompted the changes in the site conditions and hence alteration of the dynamic response of surface structures. Therefore, in this study, the effect of the interaction of tunnel-superstructure on the site response is investigated numerically. For this purpose, Fast Lagrangian Analysis of Continua (FLAC 2D) is used, and stratification and properties of soil layers are selected based on the line No 7 of Tehran subway. The superstructure is modeled both as an equivalent surcharge and the actual structure, and the results are compared. A comparison of the results shows that consideration of structure geometry is necessary for dynamic analysis and it leads to the changes in displacements and accelerations. Consequently, the geometry of the superstructure should be modeled completely instead of the application of an equivalent load. The effect of tunnel diameter and depth on the settlement of superstructures is also studied. Results show that when the tunnel depth and diameter grow, the settlements increase considerably.

Keywords: tunnel, FLAC2D, settlement, dynamic analysis

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Funmilayo Florence Adegoke

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The study looks into the issue of gender equity among the staff and students of tertiary institutions in Osun State, Nigeria, specifically the study examined the opinion of the staff and students concerning equity of gender and also examined access to tertiary Education and related courses vis-à-vis gender. A total of 800 subjects consisting of six hundred and forty students, eighty lecturers and eighty non-teaching staff were drawn from four tertiary institutions namely a University, a Polytechnic and two Colleges of Education in the State. The main research instruments used for the study are two sets of questionnaires (one for the students and one for the staff) and records of students’ analyzed for the purpose of testing the research questions that were raised. The result showed among others that the staff and the students opined that there are generally inequalities in the attributes of the two genders. It was also found that significantly more boys enrolled in science and related courses than girls. Based on the findings, useful recommendations that would enhance the contribution of both male and female to science education and the nation as a whole were made.

Keywords: gender, access, tertiary, education, Nigeria

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Authors: Lemu Abebe Geleta

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In this study, it compare the performance of banks and financial services (operational, financial, and market) across four major regions including Asia, Europe, Africa, and North with the extent of sustainability reporting. We examine how the Environment, Social, and Governance score (ESG) and the three pillars such as Return on Assets, Return on Equity, and Tobin's (Q) affect the performance of banks using data collected from 3450 observations across 40 different nations over ten years of (2011-2020). it also consider implications for governance, macroeconomics, and specific bank attributes. The results indicate a negative correlation between ESG and operational performance (ROA), financial performance (ROE), and market performance (TQ). The inclusion of diverse political and economic contexts lends distinctiveness to this paper. the findings hold significant theoretical implications for global scholars and policymakers. The limited correlation between ESG, its pillars, and the performance of banks and financial services underscores managerial shortcomings within these sectors.

Keywords: bank specialization, financial crisis, credit risk, difference-in-differences, herfindahl hirschman index

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Authors: K. Kusakana

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A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems.

Keywords: renewable energies, hybrid systems, optimization, operation control

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Authors: Siziwe Monica Zuma

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The Expanded Public Works Program (EPWP) is an instrument that the South African Government uses to reduce unemployment and poverty and also stimulate economic growth. However, due to the limited budget and programs in the EPWP, the program has had challenges in reducing unemployment, poverty and stimulating economic growth. The EPWP Vuk’uphile program had positive outcomes in developing Black emerging contractors, in order for them to participate in the main stream economy far better than when the EPWP program was not introduced. The Skills component of the program particularly the EPWP Infrastructure, which is the most funded program under EPWP has had limited success in transferring appropriate skills to ensure labour participants can penetrate the labour market after participating in the EPWP. Education and skills are important attributes that can contribute to labour absorption, however, the EPWP particularly the infrastructure program needs to strengthen skills development over a longer period of time suggested a year with multi skills relevant to the labour market. Longer and more sustained employment provides a safety net and reduces poverty better that short term employment. The EPWP program can be expanded in the infrastructure sector, focusing on rural infrastructure, agricultural infrastructure, infrastructure related components like property, ownership, management, and other services. These can stimulate the Economic sector Infrastructure of EPWP, offer longer term and more sustained employment and rural enterprise development and further employment. The Expanded Public Works Program (EPWP) is an instrument that the South African Government uses to reduce unemployment and poverty and also stimulate economic growth. However, due to the limited budget and programs in the EPWP, the program has had challenges in reducing unemployment, poverty and stimulating economic growth. The EPWP Vuk’uphile program has had positive outcomes in developing Black emerging contractors, in order for them to participate in the main stream economy far better than when the EPWP program was not introduced. The Skills component of the program particularly the EPWP Infrastructure, which is the most funded program under EPWP has had limited success in transferring appropriate skills to ensure labour participants are able to penetrate the labour market after participating in the EPWP. Education and skills are important attributes that can contribute to labour absorption, however, the EPWP particularly the infrastructure program needs to strengthen skills development over a longer period of time suggested a year with multi skills relevant to the labour market. Longer and more sustained employment provides a safety net and reduces poverty better that short term employment. The EPWP program can be expanded in the infrastructure sector, focusing on rural infrastructure, agricultural infrastructure, infrastructure related components like property, ownership, management, and other services. These can stimulate the Economic sector Infrastructure of EPWP, offer longer term and more sustained employment and rural enterprise development and further employment.

Keywords: Expanded Public Works Program (EPWP), VUKÚPHILE, youth, Public Works Programs (PWP), Infrastructure Sector of EPWP (EPWP Infrastructure)

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Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

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Authors: Giovanni Forte, Melania De Falco, Antonio Santo

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On 24th August 2016, central Italy was affected by a Mw 6.0 earthquake, representing the main shock of a long seismic sequence, which had a second shock Mw 6.6 on 26th October and lasts still nowadays. After the event, several field survey were carried out in the affected areas, which is made of historical masonry buildings. The post event reconnaissance missions were aimed at collecting information on the damage states of the buildings, the triggering of the landslides and the relationships with site effects. In this paper, the data collected after the event are analyzed considering the role of the geological and geomorphological setting and the ground motion scenario. The buildings displayed an uneven damage distribution, which was affected by both topographic and stratigraphic amplification. As pertains the landslides, which were the most recurrent among the ground failures, consisted mainly of rock falls and subordinately of translational slides. Finally, the collected knowledge showed a strong contribution of the local geological and geomorphological site condition on the resulting damage.

Keywords: Amatrice earthquake, damage states, landslides, site effects

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Authors: Qiuwen Ma, Sai On Cheung

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Incentive contracting has been developed to push the agent team for extra effort. Generally, there are three types of incentive arrangement, namely incentive/penalty for super performance/underperformance, risk/reward sharing and future business opportunities. It is found that there are significant differences in the use of incentive arrangement in private and public projects. In Hong Kong, very few public projects have used future business as incentivizer whereas private developers often signal repeated business coupled with heavy penalty. This study was conducted to identify various attributes affecting the use of I/D in both private and public engineering sectors of Hong Kong. The diverging preferences were unveiled with reference to a literature review and semi-structured interviews with industry experts. The findings reveal the public/private sectors would consider the implementation issues regarding the various performance targets. The most deterministic factor for the public sector is about accountability. The private sector is in general skeptical about the need to provide extra for the contractors for what they have already contracted to perform.

Keywords: construction incentive, public/private projects, semi-structured interview, hong kong

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Authors: Susmita Sharma, Pankaj Pathak

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Biosolids are by-products of municipal and industrial wastewater treatment process. The generation of the biosolids is increasing at an alarming rate due to the implementation of strict environmental legislation to improve the quality of discharges from wastewater treatment plant. As such, proper management and safe disposal of sewage sludge have become a worldwide topic of research. Biosolids, rich in organic matter and essential micro and macronutrients; can be used as a soil conditioner, to cut fertilizer costs and create favorable conditions for vegetation. However, it also contains pathogens and heavy metals which are undesirable as they are harmful to both humans and the environment. Therefore, for safe utilization of biosolids for land application purposes, categorization of the contaminant and pathogen is mandatory. In this context, biosolids collected from a wastewater treatment plant in Maharashtra are utilized to determine its physical, chemical and microbiological attributes. This study would ascertain, if the use of these materials from the specific site, are suitable for agriculture. Further, efforts have also been made to present the internationally acceptable legal standards and guidelines for biosolids management or application.

Keywords: biosolids, sewage, heavy metal, sustainable agriculture

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Authors: Assefa Mitike Janko, Gosa Alemu

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The review of supply and marketing of floriculture in Ethiopia was conducted to analyses the production potential and to know the marketing share of the country. The data was collected from secondary and primary. Ethiopia has been operating in the floriculture industry for over 20 years. As is the case in many developing countries, the major export items of Ethiopia are dominated by few agricultural products that earn very small amounts in the international market. Moreover, most of the exports are destined to only few countries. Given the highly capital intensive nature of production and processing, rose farming is not a smallholder activity. It is also important to note the extremely tightly controlled time dimension of the logistics process, given the product attributes desired and the fragility and perishability of the roses. Another characteristic of the Ethiopian floriculture sector is the lack of domestically produced inputs that flower producers can access. The export volume and value of cut-flowers accounts for a small proportion of the total exports of Ethiopia. In recent years the sector is showing improvements in terms of the quality and quantity of exports to the international market.

Keywords: roses, production, value chain, floriculture, supply

Procedia PDF Downloads 380

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

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

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

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Authors: Shekhar Chatterjee

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Architectural marvels of the Patan stepwell in Gujarat state in India were studied, to look into the cultural and design attributes in them. Direct observation, photography and interviewing the local people (especially senior citizens) were the methodology adopted. The aim was to look for clues into how culture and design affected architectural marvels of a building and convey that to the tourists. These interpretations from this building can offer many ideas to the contemporary design world in the form of design of modern day garments for various occasions, ornaments or accessory products for daily usage like bags, shoes and similar products. These monuments currently lack proper information system for guiding a tourist. Absence of any qualified tourist guides at the site compounds the problem further. This project investigates the feasibility of making the space more interactive for the tourist through proper digital information design and installations at places. Along with this, illumination and sound are also being used to narrate the history of these ancient monuments so that tourists get a flavor of the medieval past. Most importantly, all these digital interventions are low cost and done with easily available throw-away materials and can be replicated for other monuments as well.

Keywords: interaction, well, building, context

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Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

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Authors: Bita Mashayekhi, Marjan Fayyazi, Parisa Sefati

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Audit quality is a popular topic in accounting and auditing research because recent decades’ financial crises reduce the reliability of financial reports to public investors and cause significant doubt about the audit profession. Therefore, doing research to identify effective factors in improving audit quality is necessary for bringing back public investors’ trust to financial statements as well as audit reports. In this study, we explore the relationship between audit rotation and audit quality. For this purpose, we employ the Duff (2009) model of audit quality to measure audit quality and use a questionnaire survey of 27 audit service quality attributes. Our results show that there is a negative relationship between auditor’s rotation and audit quality as we consider the auditor’s reputation, capability, assurance, experience, and responsiveness as surrogates for audit quality. There is no evidence for verifying a same relationship when we use the auditor’s independence and expertise for measuring audit quality.

Keywords: audit quality, auditor’s rotation, reputation, capability, assurance, experience, responsiveness, independence, expertise

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Authors: Lim Lie Pin, Lin Hui Wen

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Rural tourism has become popular in Taiwan, the villages based on agriculture including fishery have to follow the trend to develop the local economy and achieve the sustainable development of the rural areas. Through cultural festivals, the tourist could experience the benefit while promoting and stimulating the local development of rural tourism. Cigu is famous for salt history and abundant natural resources, such as lagoon, black-faced spoonbills and other fishery products. Digging clam has become the most special parent-child activities in Tainan and increasing awareness since it was initiated. Therefore, festival organizers and regional destination marketers need to identify visitors’ experiences attributes which lead to opportunities for industry professionals, community involvement to plan and organize regional festivals and their programmes for effective destination branding finding out more potential rural resources encouraging the local industry growth and sustainable development.

Keywords: rural tourism, cultural festival, destination branding, tourist experience, sustainable development

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Authors: Kalinga Jagoda

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With changing population demographics and consumer preferences, specialty crops present significant opportunities for Ontario agri-businesses to develop niche markets. However, the greater rewards offered by such opportunities come with comparable challenges that are driven by specific productmarket attributes, as well as supply and demand-side factors, including certain risks. Thus, initiatives to promote and support such sectors need to be informed by an understanding of the impact of these product-market and industry specific factors on supply chain development. To this end, this project proposes to map selected specialty crops supply chains, using a suite of tested methodological approaches to evaluate their market potential, considering total supply chain costs, lead times and responsiveness. The project will deliver comprehensive supply chain maps identifying the points of value addition and value capture that are of benefit to key stakeholders for the purposes of developing policy interventions, conducting market appraisals and identifying industry best practices.

Keywords: supply chain management, hazelnut industry, supply chain maps, market opportunity

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Authors: Amine Ganibardi, Cherif Arab Ali

Abstract:

This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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Authors: Viriyavudh Sim, Jung Kyu Choi, Yong Ju Kwak, Oh Hyeon Jeon, Woo Young Jung

Abstract:

In this study, we investigated the buckling performance of basalt fiber reinforced polymer (BFRP) sandwich infill panels. Fiber Reinforced Polymer (FRP) is a major evolution for energy dissipation when used as infill material of frame structure, a basic Polymer Matrix Composite (PMC) infill wall system consists of two FRP laminates surrounding an infill of foam core. Furthermore, this type of component is for retrofitting and strengthening frame structure to withstand the seismic disaster. In-plane compression was considered in the numerical analysis with ABAQUS platform to determine the buckling failure load of BFRP infill panel system. The present result shows that the sandwich BFRP infill panel system has higher resistance to buckling failure than those of glass fiber reinforced polymer (GFRP) infill panel system, i.e. 16% increase in buckling resistance capacity.

Keywords: Basalt Fiber Reinforced Polymer (BFRP), buckling performance, FEM analysis, sandwich infill panel

Procedia PDF Downloads 441