Search results for: Yan Wang; Mathis Stock

Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

Procedia PDF Downloads 542

Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

Procedia PDF Downloads 98

Authors: H. C. Chang, J. R. Wang, A. L. Ho, S. W. Chen, J. H. Yang, C. Shih, L. C. Wang

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To confirm the reactor and containment integrity of the Advanced Boiling Water Reactor (ABWR), we perform the analysis of main steamline break (MSLB) transient by using the TRACE, PARCS, and SNAP codes. The process of the research has four steps. First, the ABWR nuclear power plant (NPP) model is developed by using the above codes. Second, the steady state analysis is performed by using this model. Third, the ABWR model is used to run the analysis of MSLB transient. Fourth, the predictions of TRACE and PARCS are compared with the data of FSAR. The results of TRACE/PARCS and FSAR are similar. According to the TRACE/PARCS results, the reactor and containment integrity of ABWR can be maintained in a safe condition for MSLB.

Keywords: advanced boiling water reactor, TRACE, PARCS, SNAP

Procedia PDF Downloads 207

Authors: Maya Safira Dewi

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Indonesia is one in the top ten countries most funds flowing into Tax Haven. Illegal funds flowing out of Indonesia reached USD 10.9 billion per year. While the total to 2010 of the Indonesian financial assets are in tax havens from Indonesia amounted to USD 331 billion (Kar and Freitas, 2012). Singapore, Netherlands, Virgin Island, Mauritius and Cayman Island are the highest countries that became the location of companies affiliated with the company listed in Indonesia Stock Exchange. The 469 companies listed on the stock exchange there are 128 companies (27.29%) with overseas entities, listed total overseas affiliated companies amounted to 417 firms in 2012 and 415 companies in 2011. The most of the branches or the parent company are located in Singapore, Netherlands, Virgin Island, Mauritius and Cayman Island. Judging from the existing tax provisions in these countries, have corporate tax rates that is lower than Indonesia. Tax avoidance to tax haven countries can be made by using some Strategies. They are transfer pricing, shopping treaty, thin capitalization and the controlled foreign company. Singapore, Netherlands, Virgin Island, Mauritius and Cayman Island are tax haven countries which become a tax heaven for Indonesian tax payer. It can be concluded that tax havens are a serious problem for Indonesia, and the need for a more assertive policy establishment and more detail about tax havens.

Keywords: tax avoidance, tax haven, transfer pricing, tax rate, tax payer

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

Procedia PDF Downloads 422

Authors: Meseret Habtamu, Mekuria Argaw

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Urban forests can help to improve the microclimate and air quality. Urban forests in Addis Ababa are important sinks for GHGs as the number of vehicles and the traffic constrain is steadily increasing. The objective of this study was to characterize the vegetation types in selected public parks and to estimate the carbon stock potential of urban forests by assessing carbon in the above, below ground biomass, in the litter and soil. Species which vegetation samples were taken using a systematic transect sampling within value DBH ≥ 5cm were recorded to measure the above, the below ground biomass and the amount of C stored. Allometric models (Y= 34.4703 - 8.0671(DBH) + 0.6589(DBH2) were used to calculate the above ground and Below ground biomass (BGB) = AGB × 0.2 and sampling of soil and litter was based on quadrates. There were 5038 trees recorded from the selected study sites with DBH ≥ 5cm. Most of the Parks had large number of indigenous species, but the numbers of exotic trees are much larger than the indigenous trees. The mean above ground and below ground biomass is 305.7 ± 168.3 and 61.1± 33.7 respectively and the mean carbon in the above ground and below ground biomass is 143.3±74.2 and 28.1 ± 14.4 respectively. The mean CO2 in the above ground and below ground biomass is 525.9 ± 272.2 and 103.1 ± 52.9 respectively. The mean carbon in dead litter and soil carbon were 10.5 ± 2.4 and 69.2t ha-1 respectively. Urban trees reduce atmospheric carbon dioxide (CO2) through sequestration which is important for climate change mitigation, they are also important for recreational, medicinal value and aesthetic and biodiversity conservation.

Keywords: biodiversity, carbon sequestration, climate change, urban forests

Procedia PDF Downloads 229

Authors: Joseph Paul Chunga

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The investment universe is awash with a myriad of financial choices that investors have to opt for, which principally culminates into a duality between aggressive or conservative approaches. Howbeit, it is pertinent to emphasize that the investment vehicles with an aggressive approach tend to take on more risk than the latter group in an effort to generate higher future returns for their respective investors. This study examines the conditionality effect that such partiality in financing has on the High-Tech and Public Utility companies listed on the Shenzhen Stock Exchange (SSE). Specifically, it examines the significance of the relationship between capitalization ratios of Total Debt Ratio (TDR), Degree of Financial Leverage (DFL) and profitability ratios of Earnings per Share (EPS) and Returns on Equity (ROE) on the Financial Risk of the two industries. We employ a modified version of the Panel Regression Model used by Rahman (2017) to estimate the relationship. The study finds that there is a significant positive relationship between the capitalization ratios on the financial risk of Public Utility companies more than High-Tech companies and a substantial negative relationship between the profitability ratios and the financial risk of the former than the latter companies. This then spells an important insight for prospective investors with regards to the volatility of earnings of such companies.

Keywords: financial leverage, debt financing, conservative firms, aggressive firms

Procedia PDF Downloads 186

Authors: Qingqing Zhao, Junhong Bai

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To investigate the effects of salinity on dynamics of soil carbon and nitrogen contents and stocks, soil samples were collected at a depth of 30 cm at four sampling sites (Sites B, T, S and P) along a salinity gradient in a drained coastal wetland, the Yellow River Delta, China. The salinity of these four sites ranked in the order: B (8.68±4.25 ms/cm) > T (5.89±3.17 ms/cm) > S (3.19±1.01 ms/cm) > P (2.26±0.39 ms/cm). Soil total carbon (TC), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil total nitrogen (TC) and soil microbial biomass carbon (MBC) were measured. Based on these data, soil organic carbon density (SOCD), soil microbial biomass carbon density (MBCD), soil nitrogen density (TCD) and soil microbial biomass nitrogen density (MBND) were calculated at four sites. The results showed that the mean concentrations of TC, SOC, MBC, TN and MBN showed a general deceasing tendency with increasing salinities in the top 30 cm of soils. The values of SOCD, MBCD, TND and MBND exhibited similar tendency along the salinity gradient. As for profile distribution pattern, The C/N ratios ranged from 8.28 to 56. 51. Higher C/N ratios were found in samples with high salinity. Correlation analysis showed that the concentrations of TC, SOC and MBC at four sampling sites were significantly negatively correlated with salinity (P < 0.01 or P < 0.05), indicating that salinity could inhibit soil carbon accumulation. However, no significant relationship was observed between TN, MBN and salinity (P > 0.05).

Keywords: carbon content and stock, nitrogen content and stock, salinity, coastal wetland

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Authors: Mekdes Lulu

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This study assessed the soil organic C (SOC) and soil nutrients in smallholding home garden, woodlot, grazing land, and cropland at two soil depths and two sites in Wolaita Zone, southern Ethiopia. The results showed that soil properties were significantly influenced by land use. The home garden had significantly higher (p < 0.05) SOC and soil nutrients when compared to the cropland. When the home garden was compared to the woodlot and grazing land uses, it had significantly higher (p < 0.05) values except in SOC, total N (TN), cation exchange capacity (CEC), and exchangeable Ca. Cropland, in comparison with grazing land and woodlot, had a non-significant difference except TN. The SOC stock (0–40 cm) in the home garden, woodlot, grazing land and cropland was 79.5, 68.0, 65.0, and 58.1 Mg ha–1, respectively. Home garden significantly differed (p <0.05) in SOC only from cropland, and this was attributed not only to the relatively higher organic input in the home garden but also to the little organic matter input and frequently tillage of the cropland. The similar SOC among the home garden, woodlot and grazing lands may imply that the balance between inputs and outputs could be nearly similar for the land uses. Soil TN and CEC had a nearly similar pattern of difference as in SOC among the land uses because of their close relationship with SOC. In general, the land use influence on soil nutrients can be in the order: home garden > wood land » grazing land » cropland, with home garden showing the least difference from the woodlot and the greatest from the cropland. In the agroecosystem, in general, the influence of smallholding home garden on SOC and soil nutrient was marginally different from Eucalyptus woodlot and grazing lands but evidently different from cropland.

Keywords: cropland, grazing land, home garden, soc stock, soil nutrients, woodlot

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Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

Procedia PDF Downloads 111

Authors: Min Wang, Sergey Utev

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The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid.

Keywords: combinatorial construction, graphical representation, matroid, path calculation, share price, Tutte polynomial

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Authors: Yosra Makni Fourati, Sana Masmoudi Mardassi

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This paper investigates the effect of Book-tax conformity on audit quality regarding the proxies of audit fees, auditors’ industry specialization and audit report lag. Using a sample of Canadian firms listed on the Toronto Stock Exchange spanning the years 2006- 2016, we applied an Ordinary Least Squares (OLS) regression to test hypotheses of this research. The authors find that higher Book-tax conformity leads to lower audit fees. They also provide evidence that there is a negative association between Book-tax conformity and auditors’ industry specialization, whereas there is a positive association between Book-tax conformity and audit report lag. Overall, the findings are prominent to better understanding the effect of Book-tax conformity on audit quality and are relevant for academic researchers, practitioners, and regulators. As the paper investigates the relationship of Book-tax conformity and audit quality using a sample of Canadian firms, it brings original insights regarding the importance of audit fees and Book-tax conformity. In addition, it considers the role of auditor’s industry specialization in the relation between audit quality and Book-tax conformity by considering a sample listed on the Toronto Stock Exchange. This paper contributes to the existing literature by highlighting the Canadian setting, to our best knowledge. In addition, our results are prominent to the auditing literature as they introduce a different determinant of auditors’ industry specialization and audit report lag.

Keywords: audit fees, auditors' industry specialization, audit report lag, book-tax conformity

Procedia PDF Downloads 158

Authors: Faustina Masocha

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This study sought to determine if the Covid-19 pandemic played a disruptive role in the signalling effect of dividend increases for the Top 40 companies listed on the Johannesburg Stock Exchange. With the use of Event Study Methodologies, it was found that dividend increases that were announced in the 2018 and 2019 financial years resulted in Cumulative Abnormal Returns (CARs) that were significantly different from zero, as confirmed by a p-value of 0,0300. This resulted in the conclusion that, under normal circumstances, dividend increases follow the precepts outlined in signalling theories which indicate that the announcement of dividend increases sent positive signals about the expected financial performance of a company. To prove the notion that Covid-19 plays a disruptive role on the signalling hypothesis, it was found from both parametric and non-parametric tests of significance that CARs related to dividend increases that were announced during the 2020 and 2021 financial years, when the Covid-19 pandemic was at its peak, were not significantly different from zero. Therefore, although the dividend increases still resulted in some CARs, such CARs were not statistically different from zero to confirm the signalling hypothesis. A p-value of 0.9830 from parametric t-tests and a p-value of 0.8971 from the Wilcoxon signed-rank test were used as a gauge that led to the conclusion that Covid-19 plays a disruptive effect on the signalling process of dividend increases.

Keywords: cumulative abnormal returns, dividend increases, event study methodology, signalling

Procedia PDF Downloads 122

Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

Procedia PDF Downloads 136

Authors: Dewan Ali Ahsan

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Hilsa (Tenualosa ilisha) is one of the most important anadromous fish species of the trans-boundary ecosystem of Bangladesh, India and Myanmar. Hilsa is not only an economically important species specially for Bangladesh and India, but also for the integral part of the culture of the Bangladesh and India. This flag-ship species in Bangladesh contributed alone of 10.82% of the total fish production of the country and about 75% of world’s total catch of hilsa comes from Bangladesh alone. As hilsa is an anadromous fish, it migrates from the Bay of Bengal to rivers for spawning, nursing and growing and for all of these purposes hilsa needs freshwaters. Ripe broods prefer turbid, fast flowing freshwater for spawning but young prefer clear and slow flowing freshwater. Climate change (salinity intrusion, sea level rise, temperature rise, impact of fresh water flow), unplanned developmental activities and other anthropogenic activities all together are severely damaging the hilsa stock and its habitats. So, climate change and human interferences are predicted to have a range of direct and indirect impacts on marine and freshwater hilsa fishery, with implications for fisheries-dependent economies, coastal communities and fisherfolk. The present study identified that salinity intrusion, siltation in river bed, decrease water flow from upstream, fragmentation of river in dry season, over exploitation, use of small mesh nets are the major reasons to affect the upstream migration of hilsa and its sustainable management. It has been also noticed that Bangladesh government has taken some actions for hilsa management. Government is trying to increase hilsa production not only by conserving jatka (juvenile hilsa) but also protecting the brood hilsa during the breeding seasons by imposing seasonal ban on fishing, restricted mesh size etc. Unfortunately, no such management plans are available for Indian and Myanmar territory. As hilsa is a highly migratory trans-boundary fish in the Bay of Bengal (and all of these countries share the same stock), it is essential to adopt a joint management policy (by Bangladesh-India-Myanmar) for the sustainable management for the hilsa stock.

Keywords: hilsa, climate change, south-east Asia, fishery management

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Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

Procedia PDF Downloads 459

Authors: Amin Davoudi

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Aim: New approaches have been introduced to improve soft tissue indices of the dental implants. This systematic review aimed to investigate the effect of computer-aided design and computer-assisted manufacture (CAD/CAM) zirconia (Zr) implant abutments on periodontal aspects. Materials and Methods: Five electronic databases were searched thoroughly based on prior defined MeSH and non-MeSH keywords. Clinical studies were collected via hand searches in English language journals up to September 2020. Interproximal papilla stability, papilla recession, pink and white esthetic score (PES, WES), bone and gingival margin levels, color, and contour of soft tissue were reviewed. Results: The initial literature search yielded 412 articles. After the evaluation of abstracts and full texts, six studies were eligible to be screened. The study design of the included studies was a prospective cohort (n=3) and randomized clinical trial (n=3). The outcome was found to be significantly better for Zr than titanium abutments, however, the studies did not show significant differences between stock and CAD/CAM abutments. Conclusion: Papilla fill, WES, PES, and the distance from the contact point to dental crest bone of adjacent tooth and inter-tooth–implant distance were not significantly different between Zr CAD/CAM and Zr stock abutments. However, soft tissue stability and recession index were better in Zr CAD/CAM abutments.

Keywords: zirconia, CADCAM, periodental, implant

Procedia PDF Downloads 101

Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang

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Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. It is more and more necessary to replace manual polishing with robot polishing. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a new type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model shows that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.

Keywords: robot polishing, force feedback, impedance control, adaptive control

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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Authors: Akash Verma, Sujit Kumar Samanta

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This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Saeidreza Radpour, Md. Alam Mondal, Amit Kumar

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Market penetration of high energy efficiency technologies has key impacts on energy consumption and GHG mitigation. Also, it will be useful to manage the policies formulated by public or private organizations to achieve energy or environmental targets. Energy intensity in residential sector of Alberta was 148.8 GJ per household in 2012 which is 39% more than the average of Canada 106.6 GJ, it was the highest amount among the provinces on per household energy consumption. Energy intensity by appliances of Alberta was 15.3 GJ per household in 2012 which is 14% higher than average value of other provinces and territories in energy demand intensity by appliances in Canada. In this research, a framework has been developed to analyze the market penetration and market share of high energy efficiency technologies in residential sector. The overall methodology was based on development of data-intensive models’ estimation of the market penetration of the appliances in the residential sector over a time period. The developed models were a function of a number of macroeconomic and technical parameters. Developed mathematical equations were developed based on twenty-two years of historical data (1990-2011). The models were analyzed through a series of statistical tests. The market shares of high efficiency appliances were estimated based on the related variables such as capital and operating costs, discount rate, appliance’s life time, annual interest rate, incentives and maximum achievable efficiency in the period of 2015 to 2050. Results show that the market penetration of refrigerators is higher than that of other appliances. The stocks of refrigerators per household are anticipated to increase from 1.28 in 2012 to 1.314 and 1.328 in 2030 and 2050, respectively. Modelling results show that the market penetration rate of stand-alone freezers will decrease between 2012 and 2050. Freezer stock per household will decline from 0.634 in 2012 to 0.556 and 0.515 in 2030 and 2050, respectively. The stock of dishwashers per household is expected to increase from 0.761 in 2012 to 0.865 and 0.960 in 2030 and 2050, respectively. The increase in the market penetration rate of clothes washers and clothes dryers is nearly parallel. The stock of clothes washers and clothes dryers per household is expected to rise from 0.893 and 0.979 in 2012 to 0.960 and 1.0 in 2050, respectively. This proposed presentation will include detailed discussion on the modelling methodology and results.

Keywords: appliances efficiency improvement, energy star, market penetration, residential sector

Procedia PDF Downloads 285

Authors: Ludmila A. Gavriliuc, Jerry McLarty, Heather E. Kleiner, J. Michael Mathis

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Abstract -- Background: The citrus coumarine Auraptene (Aur) is an effective chemopreventive agent, as manifested in many models of diseases and cancer. Nuclear factor erythroid 2-related factor (Nrf2) is an important regulator of genes induced by oxidative stress, such as glutathione S-transferases, heme oxygenase-1, and peroxiredoxin 1, by activating the antioxidant response element (ARE). Genetic and biochemical evidence has demonstrated that glutathione (GSH) and glutathione-dependent enzymes, glutathione reductase (GR), glutathione peroxidases (GPs), glutathione S-transferases (GSTs) are responsible for the control of intracellular reduction-oxidation status and participate in cellular adaptation to oxidative stress. The effect of Aur on the activity of GR, GPs (Se-GP and Se-iGP), and content of GSH in the liver, kidney, and spleen is insufficiently explored. Aim: Our goal was the examination of the Aur influence on the redox-system of GSH in Nrf2 wild type and Nrf2 knockout mice via activation of Nrf2 and ARE. Methods: Twenty female mice, 10 Nrf2 wild-type (WT) and 10 Nrf2 (-/-) knockout (KO), were bred and genotyped for our study. The activity of GR, Se-GP, Se-iGP, GST, G6PD, CytP450 reductase, catalase (Cat), and content of GSH were analyzed in the liver, kidney, and spleen using Spectrophotometry methods. The results of the specific activity of enzymes and the amount of GSH were analyzed with ANOVA and Spearman statistical methods. Results: Aur (200 mg/kg) treatment induced hepatic GST, GR, Se-GP activity and inhibited their activity in the spleen of mice, most likely via activation of the ARE through Nrf2. Activation in kidney Se-GP and G6PD by Aur is also controlled, apparently through Nrf2. Results of the non-parametric Spearman correlation analysis indicated the strong positive correlation between GR and G6PD only in the liver in WT control mice (r=+0.972; p < 0.005) and in the kidney KO control mice (r=+0.958; p < 0.005). The observed low content of GSH in the liver of KO mice indicated an increase in its participation in the neutralization of toxic substances with the absence of induction of GSH-dependent enzymes, such as GST, GR, Se-GP, and Se-iGP. Activation of CytP450 in kidney and spleen and Cat in the liver in KO mice probably revealed another regulatory mechanism for these enzymes. Conclusion: Thereby, obtained results testify that Aur can modulate the activity of genes and antioxidant enzymatic redox-system of GSH, responsible for the control of intracellular reduction-oxidation status.

Keywords: auraptene, glutathione, GST, Nrf2

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Authors: Mengxia Jin, Yongqiang Chen, Wenqian Wang, Yu Wang

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The complexity and specificity of construction projects have made common opportunism phenomenon, and contractual governance for opportunism has been a topic of considerable ongoing research. Based on TCE, the research distinguishes control and coordination as different functions of the contract to investigate their complexity separately. And in a nuanced way, the dimensionality of contractual control is examined. Through the analysis of motivation and capability of strong or weak form opportunism, the framework focuses on the relationship between the complexity of above contractual dimensions and different types of opportunistic behavior and attempts to verify the possible explanatory mechanism. The explanatory power of the research model is evaluated in the light of empirical evidence from questionnaires. We collect data from Chinese companies in the construction industry, and the data collection is still in progress. The findings will speak to the debate surrounding the effects of contract complexity on opportunistic behavior. This nuanced research will derive implications for research on the role of contractual mechanisms in dealing with inter-organizational opportunism and offer suggestions for curbing contract parties’ opportunistic behavior in construction projects.

Keywords: contractual complexity, contractual control, contractual coordinatio, opportunistic behavior

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Authors: Rit M., Girard R., Villot J., Thorel M.

Abstract:

In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Prajwal Eachempati, Laurent Muzellec, Ashish Kumar Jha

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We use Facebook as a case study to investigate the complex relationship between the firm’s public discourse (and actions) surrounding data privacy and the performance of a business model based on monetizing user’s data. We do so by looking at the evolution of public discourse over time (2004–2021) and relate topics to revenue and stock market evolution Drawing from archival sources like Zuckerberg We use LDA topic modelling algorithm to reveal 19 topics regrouped in 6 major themes. We first show how, by using persuasive and convincing language that promises better protection of consumer data usage, but also emphasizes greater user control over their own data, the privacy issue is being reframed as one of greater user control and responsibility. Second, we aim to understand and put a value on the extent to which privacy disclosures have a potential impact on the financial performance of social media firms. There we found significant relationship between the topics pertaining to privacy and social media/technology, sentiment score and stock market prices. Revenue is found to be impacted by topics pertaining to politics and new product and service innovations while number of active users is not impacted by the topics unless moderated by external control variables like Return on Assets and Brand Equity.

Keywords: public discourses, data protection, social media, privacy, topic modeling, business models, financial performance

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Authors: F. Ghandehari, H. Lu, L. El-Jahel, D. Jayasuriya

Abstract:

Disagreement among investors is a fundamental aspect of financial markets, significantly influencing market dynamics. Measuring this disagreement has traditionally posed challenges, often relying on proxies like analyst forecast dispersion, which are limited by biases and infrequent updates. Recent movements in social media indicate that retail investors actively seek financial advice online and can influence the stock market. The evolution of the investing landscape, particularly the rise of social media as a hub for financial advice, provides an alternative avenue for real-time measurement of investor sentiment and disagreement. Platforms like Reddit offer rich, community-driven discussions that reflect genuine investor opinions. This research explores how social media empowers retail investors and the potential of leveraging textual analysis of social media content to capture daily fluctuations in investor disagreement. This study investigates the relationship between daily investor disagreement and trading volume, focusing on the role of social media platforms in shaping market dynamics, specifically using data from WallStreetBets (WSB) on Reddit. This paper uses data from 2020 to 2023 from WSB and analyses 4,896 firms with enough social media activity in WSB to define stock-day level disagreement measures. Consistent with traditional theories that disagreement induces trading volume, the results show significant evidence supporting this claim through different disagreement measures derived from WSB discussions.

Keywords: disagreement, retail investor, social finance, social media

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Authors: Chi-Cheng Cheng, Che-Hsin Lin, Yu-Jen Wang, Chua-Chin Wang

Abstract:

The project-oriented capstone course has become a required element for most engineering educational units. It is not only because the capstone course is an important criterion for international accreditation of engineering degree programs under Washington Accord, but also the capstone course provides an opportunity for students to apply what they have learned in their school years to actual engineering problems. Nevertheless, most project-oriented capstone courses are conducted with one single project for all students or teams. In other words, students work to reach the same or similar goals by coming up with different layouts and approaches. It appears not suitable for a multidisciplinary engineering department. Therefore, a one-year multidisciplinary project-oriented capstone course was designed for the junior year of the undergraduate program. About one-half of faculty members in the department needs to be involved in generating as many projects as possible to meet different students' interests and specialties. Project achievement has to be displayed and demonstrated in the annual exposition and competition at the end of this course. Significant success in attracting attention and hardworking of students on projects was witnessed for the past two pilot years. Analysis of course evaluation demonstrates positive impact on all perspectives despite of slightly negative influence due to poor communication and collaboration between students and their project supervisors.

Keywords: Capstone course, CDIO, engineering education, project-oriented learning

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

Abstract:

This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Rui Du

Abstract:

This paper attempts to assess the impact of a major sporting event —the Super Bowl on the local economies. The identification strategy is to compare the winning and losing cities at the National Football League (NFL) conference finals under the assumption of similar pre-treatment trends. The stock market performances of companies headquartered in these cities are used to capture the sudden changes in local economic activities during a short time span. The exogenous variations in the football game outcome allow a straightforward difference-in-differences approach to identify the effect. This study finds that the post-event trends in winning and losing cities diverge despite the fact that both cities have economically and statistically similar pre-event trends. Empirical analysis provides suggestive evidence of a positive, significant local economic impact of conference final wins, possibly through city image enhancement. Further empirical evidence shows the presence of heterogeneous effects across industrial sectors, suggesting that city image enhancing the effect of the Super Bowl participation is empirically relevant for the changes in the composition of local industries. Also, this study also adopts a similar strategy to examine the local economic impact of Super Bowl successes, however, finds no statistically significant effect.

Keywords: Super Bowl Participation, local economies, city image enhancement, difference-in-differences, industrial sectors

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

Abstract:

Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent preservation has been proposed, but it does not take into account the association between test repairs and assertions, leading to a large number of irrelevant candidates and decreasing the repair capability. This paper proposes an assertion-driven test repair approach. Furthermore, an intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) of broken test cases, which is more effective than the existing intentpreserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: test repair, test intent, software test, test case evolution

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