Search results for: traditional market revitalization

Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

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Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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Authors: Xiaoling Dai

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Many Chinese artists have used digital photography to create works with features of Chinese landscape paintings since the 20th century. The ‘New Mountains and Water’ works created by digital techniques reflect the fusion of photographic techniques and traditional Chinese aesthetic thoughts. Borrowing from Chinese landscape paintings in the Song Dynasty, the Chinese photographer Yao Lu uses digital photography to reflect contemporary environmental construction in his series New Landscapes. By portraying a variety of natural environments brought by urbanization in the contemporary period, Lu deconstructs traditional Chinese paintings and reconstructs contemporary photographic practices. The primary object of this study is to investigate how Chinese photographer Yao Lu redefines and re-interprets the relationship between tradition and contemporaneity. In this study, Yao Lu’s series work New Landscapes is used for photo elicitation, which seeks to broaden understanding of the development of Chinese landscape photography. Furthermore, discourse analysis will be used to evaluate how Chinese social developments influence the creation of photographic practices. Through visual and discourse analysis, this study aims to excavate the relationship between tradition and contemporaneity in Lu’s works. According to New Landscapes, the study argues that in Lu’s interpretations of landscapes, tradition and contemporaneity are seen to establish a new relationship. Traditional approaches to creation do not become obsolete over time. On the contrary, traditional notions and styles of creation can shed new light on contemporary issues or techniques.

Keywords: Chinese aesthetics, Yao Lu, new landscapes, tradition, contemporaneity

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Authors: Muhammad Faheem Khakhi, Jian Yu Wang, Salman Muhammad, Muhammad Faisal Shabir

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Population growth and Chinese two-child policy will boost pharmaceutical market, and it will continue to maintain the growth for a period of time in the future, the traditional pharmacy dispensary has been unable to meet the growing medical needs of the peoples. Under the strong support of the national policy, the automatic transformation of traditional pharmacies is the inclination of the Times, the new type of intelligent pharmacy system will continue to promote the development of the pharmaceutical industry. Under this background, based on PLC control, the paper proposed an intelligent storage and automatic drug delivery system; complete design of the lower computer's control system and the host computer's software system has been present. The system can be applied to dispensing work for Chinese herbal medicinal and Western medicines. Firstly, the essential of intelligent control system for pharmacy is discussed. After the analysis of the requirements, the overall scheme of the system design is presented. Secondly, introduces the software and hardware design of the lower computer's control system, including the selection of PLC and the selection of motion control system, the problem of the human-computer interaction module and the communication between PC and PLC solves, the program design and development of the PLC control system is completed. The design of the upper computer software management system is described in detail. By analyzing of E-R diagram, built the establish data, the communication protocol between systems is customize, C++ Builder is adopted to realize interface module, supply module, main control module, etc. The paper also gives the implementations of the multi-threaded system and communication method. Lastly, each module of the lower computer control system is tested. Then, after building a test environment, the function test of the upper computer software management system is completed. On this basis, the entire control system accepts the overall test.

Keywords: automatic pharmacy, PLC, control system, management system, communication

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Authors: Gevher Sayar, Dicle Aydın

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The need for shelter which is one of the essential requirement of humanity has emerged for different type of dwelling needs depend on upon different culture and location. Almost all dwellings as an element of the public improvements effect the physical appearance of the city. Dwelling zones create part of whole in terms of urban area use. Whereas in traditional texture merger of parcels create city blocks, in new settlement area city blocks become a part, so the property of each part differs. The perspective of this study is part-to-whole relationship of residential areas and diversified residential areas are illustrated. The purpose of this study is that dwelling applications which have constructed quickly as gated community in the last 20 years in new settlement area of Konya (Turkey) have compared traditional texture in terms of part-to-whole relationship. According to the perception of traditional neighborhood in Konya, the relationship of houses between street pattern and each other are suited for city culture and location. In contrast, new settlement areas cannot become integrated another part of city, they have become restricted areas, so new settlement areas have not integrated, they have separated. The perception of part forms whole has changed, roads provide the relationship of growing parts with one another and walls of gated communities has disjunctive feature. In this study, by using visual analysis photographs and technical drawings are used. Traditional texture and current dwelling have compared.

Keywords: dwelling, residential area, urban part, urban whole

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

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Authors: Fatma Ismailia, Malek Saihi

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This research provides an explanation of exchange incentives on the Tunis stock market from a behavioural point of view. The elucidation of the anomalies of excessive volume of transactions and that of excessive volatility cannot be done without the recourse to the psychological aspects of investors. The excessive confidence has been given the predominant role for the explanation of these phenomena. Indeed, when investors store increments, they become more confident about the precision of their private information and their exchange activities then become more aggressive on the subsequent periods. These overconfident investors carry out the intensive exchanges leading to an increase of securities volatility. The objective of this research is to identify whether the trading volume and the excessive volatility of securities observed on the Tunisian stock market come from the excessive exchange of overconfident investors. We use a sample of daily observations over the period January 1999 - October 2007 and we relied on various econometric tests including the VAR model. Our results provide evidence on the importance to consider the bias of overconfidence in the analysis of Tunis stock exchange specificities. The results reveal that the excess of confidence has a major impact on the trading volume while using daily temporal intervals.

Keywords: overconfidence, trading volume, efficiency, rationality, anomalies, behavioural finance, cognitive biases

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Authors: Sy, Melecio Jr

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The decision to adopt vertical integration (VI) is firm-specific, but there is a common practice among businesses in an industry to maximize the massive potential benefits of VI. This study aims to determine VI adoption in the restaurant industry in Davao City. Using a two-step sampling process, the study used a validated survey questionnaire among 264 restaurant owners and managers randomly selected and geographically classified. It is a quantitative study where the data were subjected to a structural equation model (SEM). The results revealed that VI is present but limited to procurement, production, restaurant services, and online marketing. Raw materials were outsourced while delivery to customers through third-party delivery services. VI slowly increased over ten years except for online marketing, which has grown significantly in a few years. The endogenous and exogenous variables were correlated and established the linear regression model. The SEM's best fit model revealed that strategic motives (SMOT) and market factors (MFAC) influenced VI adoption while MFAC is the best predictor. Favorable market factors may lead restaurants to adopt VI. It is, thus, recommended for restaurants to institutionalize strategic management, quantify the impact of double marginalization in future studies as a reason for VI and conduct this study during the new normal to see the influence of business efficiencies and firm economies on VI adoption.

Keywords: business efficiencies, business management, davao city, firm economies, market factors, philippines, strategic motives, structural equation model, supply chain, vertical integration adoption

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Authors: Chia-Yu Lin, Yu-Hsiang Shen, Cing-Ciao Ke, Chia-Hao Chang, Fan-Pin Tseng, Yu-Ching Ni, Sheng-Pin Tseng

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Tomosynthesis is an imaging system that generates a 3D image by scanning in a limited angular range. It could provide more depth information than traditional 2D X-ray single projection. Radiation dose in tomosynthesis is less than computed tomography (CT). Because of limited angular range scanning, there are many properties depending on scanning direction. Therefore, non-coplanar imaging technique was developed to improve image quality in traditional tomosynthesis. The purpose of this study was to establish the non-coplanar imaging technique of tomosynthesis system and evaluate this technique by the reconstructed image. INER prototype tomosynthesis system contains an X-ray tube, a flat panel detector, and a motion machine. This system could move X-ray tube in multiple directions during the acquisition. In this study, we investigated three different imaging techniques that were 2D X-ray single projection, traditional tomosynthesis, and non-coplanar tomosynthesis. An anthropopathic chest phantom was used to evaluate the image quality. It contained three different size lesions (3 mm, 5 mm and, 8 mm diameter). The traditional tomosynthesis acquired 61 projections over a 30 degrees angular range in one scanning direction. The non-coplanar tomosynthesis acquired 62 projections over 30 degrees angular range in two scanning directions. A 3D image was reconstructed by iterative image reconstruction algorithm (ML-EM). Our qualitative method was to evaluate artifacts in tomosynthesis reconstructed image. The quantitative method was used to calculate a peak-to-valley ratio (PVR) that means the intensity ratio of the lesion to the background. We used PVRs to evaluate the contrast of lesions. The qualitative results showed that in the reconstructed image of non-coplanar scanning, anatomic structures of chest and lesions could be identified clearly and no significant artifacts of scanning direction dependent could be discovered. In 2D X-ray single projection, anatomic structures overlapped and lesions could not be discovered. In traditional tomosynthesis image, anatomic structures and lesions could be identified clearly, but there were many artifacts of scanning direction dependent. The quantitative results of PVRs show that there were no significant differences between non-coplanar tomosynthesis and traditional tomosynthesis. The PVRs of the non-coplanar technique were slightly higher than traditional technique in 5 mm and 8 mm lesions. In non-coplanar tomosynthesis, artifacts of scanning direction dependent could be reduced and PVRs of lesions were not decreased. The reconstructed image was more isotropic uniformity in non-coplanar tomosynthesis than in traditional tomosynthesis. In the future, scan strategy and scan time will be the challenges of non-coplanar imaging technique.

Keywords: image reconstruction, non-coplanar imaging technique, tomosynthesis, X-ray imaging

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Authors: Huynh Viet Khai, Mitsuyasu Yabe

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The study investigated the economic value of biodiversity attributes that could provide policy-makers reliable information to estimate welfare losses due to biodiversity reductions and analyse the trade-off between biodiversity and economics. In order to obtain the non-market benefits of biodiversity conservation, an indirect utility function and willingness to pay for biodiversity attributes were applied using the approach of choice modelling with the analysis of conditional logit model. The study found that Mekong Delta residents accepted their willingness to pay for VND 913 monthly for a one percent increase in healthy vegetation, VND 360 for an additional mammal species and VND 2,440 to avoid the welfare losses of 100 local farmers.

Keywords: choice modelling, genetic resources, wetland conservation, marginal willingness to pay

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Authors: Farhad Reyazat, Richard Werner

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This paper contributes to the existent literature by developing a framework that explains how to monitor potential threats to banking sector stability. The study explores structural vulnerabilities at the country level, but also look at bilateral exposures within a network context. The study contributes in analysing of the European banking systemic risk at aggregated level, which integrates the characteristics of bank size, and interconnectedness relative to the size of the economy which ultimate risk belong to, taking to account the concentration ratio of the banking industry within the whole economy. The nature of the systemic risk depends on the interplay of the network topology with the nature of financial transactions over the network, assets and buffer stemming from bank size, correlations, and the nature of the shocks to the financial system. The study’s results illustrate the contribution of banks’ size, size of economy and concentration of counterparty exposures to a given country’s banks in explaining its systemic importance, how much the banking network depends on a few traditional hubs activities and the changes of this dependencies over the last 9 years. The role of few of traditional hubs such as Swiss banks and British Banks and also Irish banks- where the financial sector is fairly new and grew strongly between 1990s till 2008- take the fourth position on 2014 reducing the relative size since 2006 where they had the first position. In-degree concentration index analysis in the study shows concentration index of banking network was not changed since financial crisis 2007-8. In-degree concentration index on first quarter of 2014 indicates that US, UK and Germany together, getting over 70% of the network exposures. The result of comparing the in-degree concentration index with 2007-4Q, shows the same group having over 70% of the network exposure, however the UK getting more important role in the hub and the market share of US and Germany are slightly diminished.

Keywords: systemic risk, counterparty risk, financial stability, interconnectedness, banking concentration, european banks risk, network effect on systemic risk, concentration risk

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Authors: Hoang Thi Quynh, Shima Kazuto

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Organic farming is gaining interest in Vietnam. However, organic fertilizer production is not sufficiently regulated, resulting in unknown quality. This study investigated characteristics of so-called organic fertilizers in the Vietnam’s market and their mineralization in soil-plant system. We collected 15 commercial products (11 domestic and 4 imported) which labelled 'organic fertilizer' in the market to analyze nutrients composition. A 20 day-incubation experiment was carried on with 80 g sandy-textured soil, amended with the fertilizer at a rate of 109.4 mgN.kg⁻¹soil in 150 mL glass bottle at 25℃. We categorized them according to nutrients content and mineralization rate, and then selected 8 samples for cultivation experiment. The experiment was conducted by growing Komatsuna (Brassica campestris) in sandy-textured soil using an automatic watering apparatus in a greenhouse. The fertilizers were applied to the top one-third of the soil stratum at a rate of 200 mgN.kg⁻¹ soil. Our study also analyzed material flow of coffee husk compost in Central Highland of Vietnam. Total N, P, K, Ca, Mg and C: N ratio varied greatly cross the domestic products, whereas they were quite similar among the imported materials. The proportion of inorganic-N to T-N of domestic products was higher than 25% in 8 of 11 samples. These indicate that N concentration increased dramatically in most domestic products compared with their raw materials. Additionally, most domestic products contained less P, and their proportions of Truog-P to T-P were greatly different. These imply that some manufactures were interested in adjusting P concentration, but some ones were not. Furthermore, the compost was made by mixing with chemical substances to increase nutrients content (N, P), and also added construction surplus soil to gain weight before packing product to sell in the market as 'organic fertilizer'. There was a negative correlation between C:N ratio and mineralization rate of the fertilizers. There was a significant difference in N efficiency among the fertilizer treatments. N efficiency of most domestic products was higher than chemical fertilizer and imported organic fertilizers. These results suggest regulations on organic fertilizers production needed to support organic farming that is based on internationally accepted standards in Vietnam.

Keywords: inorganic N, mineralization, N efficiency, so-called organic fertilizers, Vietnam’s market

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Authors: Jessica Ding

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The field of global health is currently advocating for a resurgence in the use of traditional medicines to improve people-centered care. Healthcare policies are rapidly changing in response; in China, the increasing presence of TCM in the same spaces as biomedicine has led to a new term: integrative medicine. However, the existence of TCM as a part of integrative medicine creates a pressing paradoxical tension where TCM is both seen as a marginalized system within ‘modern’ hospitals and as a modality worth integrating. Additionally, the impact of such shifts has not been fully explored: the World Health Organization for one focuses only on three angles —practices, products, and practitioners— with regards to traditional medicines. Through ten weeks of fieldwork conducted at an urban hospital in Shanghai, China, this research expands the perspective of existing strategies by looking at integrative care through a fourth lens: patients and families. The understanding of self-care, health-seeking behavior, and non-professional caregiving structures are critical to grasping the significance of traditional medicine for people-centered care. Indeed, those individual and informal health care expectations align with the very spaces and needs that traditional medicine has filled before such ideas of integration. It specifically looks at this issue via three processes that operationalize experiences of care: (1) how aspects of TCM are valued within integrative medicine, (2) how negotiations of care occur between patients and doctors, and (3) how 'good quality' caregiving presents in integrative clinical spaces. This research hopes to lend insight into how culturally embedded traditions, bureaucratic and institutional rationalities, and social patterns of health-seeking behavior influence care to shape illness experiences at the intersection of two medical modalities. This analysis of patients’ clinical and illness experiences serves to enrich the narratives of integrative medical care’s ability to provide patient-centered care to determine how international policies are realized at the individual level. This anthropological study of the integration of Traditional Chinese medicine in local contexts can reveal the extent to which global strategies, as promoted by the WHO and the Chinese government actually align with the expectations and perspectives of patients receiving care. Ultimately, this ethnographic analysis of a local Chinese context hopes to inform global policies regarding the future use and integration of traditional medicines.

Keywords: emergent systems, global health, integrative medicine, traditional Chinese medicine, TCM

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Authors: Dina H. Gabr, Mona A. El Bannan

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With growing worldwide concern for global warming, green finance has become the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the United Nations Sustainable Development Goals, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits. This paper provides a comprehensive review of the concepts and definitions of green finance and the importance of 'green' impact investments today. The core challenge in combating climate change is reducing and controlling Greenhouse gas emissions; therefore, this study explores the solutions green finance provides putting emphasis on the use of renewable energy, which is necessary for enhancing the transition to the green economy. With increasing attention to the concept of green finance, multiple forms of green investments and financial tools have come to fruition; the most prominent are green bonds. The rise of green bonds, a debt market to finance climate solutions, provide a promising mechanism for sustainable finance. Following the review, this paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

Keywords: climate change, GHG emissions, green bonds, green finance, sustainable finance

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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: Raphaël Weuts, Mykyta Petik, Anton Vedder

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Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.

Keywords: AI Act, healthcare, confounders, risks

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Authors: Mohamed Zaher Bouaziz

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Our study examines the Ohlson Model, which links a company's market value to its equity and net earnings, in the context of the evolution of the Canadian accounting model, characterized by more extensive use of fair value and a broader measure of performance after IFRS adoption. Our hypothesis is that if equity is reported at its fair value, this valuation is closely linked to market capitalization, so the weight of earnings weakens or even disappears in the Ohlson Model. Drawing on Canada's adoption of the International Financial Reporting Standards (IFRS), our results support our hypothesis that equity appears to include most of the relevant information for investors, while earnings have become less important. However, the predictive power of earnings does not disappear.

Keywords: fair value accounting, Ohlson model, IFRS adoption, value-relevance of equity and earnings

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Authors: Kwasi Sarfo, Bernard Okoampah Otu

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The 1992 constitution of the Republic of Ghana recognises the authority and roles of traditional leaders and considers them as being entrusted with fiduciary responsibility over land in their respective territories. The new land act, Act 1036 of 2020, in buttressing the fiduciary role of traditional leaders in land matters, inserted the traditional leaders’ accountability clause. Many traditional leaders have expressed their misgivings about the insertion of this clause. Therefore, there appears to be a misunderstanding of the concept of fiduciary in land management in Ghana. The objective of this study is to examine the concept of fiduciary in respect of allodial rights holders in land management and administration and how this concept is perceived and applied by traditional leaders. The study seeks to provide insights into the discrepancy between fiduciary theory and its practical implementation in Ghana. The study is based on a qualitative empirical research approach and adopts in-depth interviews as a primary method of data collection. The study also adopts the theory of New Institutionalism of social anthropology in analysing and interpreting the findings. The data for this study was collected over a period of one year, from July 2022 to July 2023, as part of one of the author's PhD dissertation. The collected data were carefully analysed using the principles of thematic analysis, identifying key themes and patterns. This study does not seek to pursue the discussions from a legal standpoint but from a social anthropological perspective and argues that the concept of fiduciary in theory is far different from what pertains in practice and that traditional leaders’ assumptions and application of this concept contribute to the alienation of customary and communal land at the expense of their subjects. This study deepens our understanding of the continuous expropriation of communal landholders in many rural communities in Africa in the era of global land grabbing, which worsens their poverty levels. It also explains further the theory of new institutionalism of social anthropology by highlighting how the theory manifests in practice in the case of Ghana.

Keywords: fiduciary, customary land tenure, allodial rights, land alienation, communal land, Ghana

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Authors: Faroogh Khakzad, Marzieh Dehghani, Elahe Hejazi

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The present study investigates the effect of teaching a Thinking and Research lesson by cooperative and traditional methods on the creativity of sixth-grade students in Piranshahr province. The statistical society includes all the sixth-grade students of Piranshahr province. The sample of this studytable was selected by available sampling from among male elementary schools of Piranshahr. They were randomly assigned into two groups of cooperative teaching method and traditional teaching method. The design of the study is quasi-experimental with a control group. In this study, to assess students’ creativity, Abedi’s creativity questionnaire was used. Based on Cronbach’s alpha coefficient, the reliability of the factor flow was 0.74, innovation was 0.61, flexibility was 0.63, and expansion was 0.68. To analyze the data, t-test, univariate and multivariate covariance analysis were used for evaluation of the difference of means and the pretest and posttest scores. The findings of the research showed that cooperative teaching method does not significantly increase creativity (p > 0.05). Moreover, cooperative teaching method was found to have significant effect on flow factor (p < 0.05), but in innovation and expansion factors no significant effect was observed (p < 0.05).

Keywords: cooperative teaching method, traditional teaching method, creativity, flow, innovation, flexibility, expansion, thinking and research lesson

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Authors: Y. Boulaksil, J. C. Fransoo, E.E. Blanco, S. Koubida

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In this paper, we study the small traditional retailers that are located in the neighborhoods of big cities in emerging markets. Although modern retailing has grown in the last two decades in these markets, the number of small retailers is still increasing and serving a substantial part of the daily demand for many basic products, such as bread, milk, and cooking oil. We conduct an empirical study to understand the business environment of these small traditional retailers in emerging markets by collecting data from 333 small retailers, spread over 8 large cities in Morocco. We analyze the data and describe their business environment with a focus on the informal credits they offer to their customers. We find that smaller small retailers that are funded from personal savings and managed by the owner himself offer relatively the most credits. Our study also provides interesting insights about these small retailers that will help FMCG manufacturers that are (planning to be) active in Morocco and other emerging markets. We also discuss a number opportunities to improve the efficiency of the supply chains that serve them.

Keywords: small retailers, big cities, emerging markets, empirical study, supply chain management, Morocco

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Authors: Priyanka Sinnarkar

Abstract:

The appropriation of traditional knowledge has already deprived vast indigenous communities of material benefits. One such industry in India responsible for the extensive exploitation of the indigenous communities is Bollywood or the film industry. Indigenous communities are usually marginalized and exploited, whilst the beneficiary is always the third part. Transgender culture in India dates back to 400 AD with a precise description in the Kama Sutra. Since then, with escalating evolution in governance, the community lost its glory and was criminalized until late 2014. However, the traditional knowledge and cultural practices never diminished. The formation of cults (gharanas) and peculiar folklore has remained in place. This study is intended to highlight the culture of the hijra gharanas and their contribution to intangible cultural heritage. Whilst adhering to the norms of the United Nations pertaining to traditional knowledge and indigenous communities, these papers focuses on the fact that one of the most marginalized and ostracized communities in India treasures a huge amount of rituals and practices that are appropriated by the film industry, leaving the transgender community to indulge into odd jobs and commercial sex work leading to poverty and illiteracy. A comparison between caste reservations and no reservation for this community will bring to light the lacuna in the democratic system. Also, through empirical findings, it can be inferred that a creative sector of the society is not properly exploited to its complete potential, thereby restricting a good contribution to intellectual property. It is important to state that the roots of this problem are not in modern practices. Thus an etymological analysis from mythology to the present will help understand that appropriate application of human rights in this segment will be useful to render justice to this community and thereby recognize the IP that has been succumbed since ages.

Keywords: indigenous, intellectual property, traditional knowedge, transgender

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Authors: Ved Kulkarni, Karthik Kini

Abstract:

This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.

Keywords: data mining, language processing, artificial neural networks, sentiment analysis

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Authors: Tchapo Tchaga Sophia, Cai Chun

Abstract:

This study measures the efficiency level of corporate governance to improve the quality level of value relevance in the resolution of market value efficiency increase issues, transparency problems, risk frauds, agency problems, investors' confidence, and decision-making issues using IFRS and Corporate Governance Acts (CGA). The final sample of this study contains 3660 firms from ten countries' stock markets from 2010 to 2020. Based on the efficiency market theory and the positive accounting theory, this paper uses multiple econometrical methods (DID method, multivariate and univariate regression methods) and models (Ohlson model and compliance index model) regression to see the incidence results of corporate governance mechanisms on the value relevance level under the influence of IFRS and corporate governance regulations act framework in Africa's stock exchanges for non-financial firms. The results on value relevance show that the corporate governance system, strengthened by the adoption of IFRS and enforcement of new corporate governance regulations, produces better financial statement information when its compliance level is high. And that is both value-relevant and comparable to results in more developed markets. Similar positive and significant results were obtained when predicting future book value per share and earnings per share through the determination of stock price and stock return. The findings of this study have important implications for regulators, academics, investors, and other users regarding the effects of IFRS and the Corporate Governance Act (CGA) on the relationship between corporate governance and accounting information relevance in the African stock market. The contributions of this paper are also based on the uniqueness of the data used in this study. The unique data is from Africa, and not all existing findings provide evidence for Africa and of the DID method used to examine the relationship between corporate governance and value relevance on African stock exchanges.

Keywords: corporate governance value, market efficiency value, value relevance, African stock market, stock return-stock price

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Authors: Darrol Stanley, Levan Efremidze, Jannie Rossouw

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We investigate the predictability of the USD/ZAR (South African Rand) exchange rate with sample entropy analytics for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. These results are preliminary and do not yet account for reasonable transactions costs, although these are very small in currency markets.

Keywords: currency trading, entropy, market timing, risk factor model

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Chiara De Amicis, Sonia Falconieri, Mesut Tastan

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In this study, we analyze the language employed by Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) during earnings conference calls from a gender perspective. We find evidences that conference calls held by female CEOs and/or CFOs exhibit a higher level of optimism compared to conference calls held by male CEOs and/or CFOs. Moreover, female managers tend to present and discuss firm performances with less vagueness as compared to their male colleagues. We then observe the market reaction around each earnings conference call: while manager optimism is perceived as a good signal by investors, manager vagueness significantly dampens the market reaction around the call. Whether the gender of the CEO and/or the CFO delivering the conference call affects investors’ perceptions about the firm performance is still an open question. Some evidences show that the language employed by female managers conveys more valuable information for market participants as compared to the language employed by their male counterparts. This study contributes to a growing literature in finance and accounting that uses textual analysis to assess the informativeness of corporate disclosure. To our knowledge, this is the first paper that aims at answering the question whether the gender of firm’s top managers does matter when it comes to assess the informativeness of corporate spoken communication. We believe that our results will be of relevance for future research in the field. Moreover, our evidence may be used in support of the debate if a larger participation by women in the management of companies should be encouraged or not.

Keywords: conference calls, even study, gender, market reaction, textual analysis

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Authors: Aparna Sengupta

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The paper seeks to find answers to the question as to why India’s disaster management policies have been unable to deliver the desired results. Are the shortcomings in policy formulation, effective policy implementation or timely prevention mechanisms? Or is there a fundamental issue of policy formulation which sparsely takes into account the cultural specificities and uniqueness, technological know-how, educational, religious and attitudinal capacities of the target population into consideration? India was slow in legislating disaster policies but more than that the reason for lesser success of disaster polices seems to be the gap between policy and the people. We not only keep hearing about the failure of governmental efforts but also how the local communities deal far more efficaciously with disasters utilizing their traditional knowledge. The 2004 Indian Ocean tsunami which killed 250,000 people (approx.) could not kill the tribal communities who saved themselves due to their age-old traditional knowledge. This large scale disaster, considered as a landmark event in history of disasters in the twenty-first century, can be attributed in bringing and confirming the importance of Traditional Environmental Knowledge in managing disasters. This brings forth the importance of cultural and traditional know-how in dealing with natural disasters and one is forced to question as to why shouldn’t traditional environmental knowledge (TEK) be taken into consideration while formulating India’s disaster resilience policies? Though at the international level, many scholars have explored the connectedness of disaster to cultural dimensions and several research examined how culture acts as a stimuli in perceiving disasters and their management (Clifford, 1956; Mcluckie, 1970; Koentjaraningrat, 1985; Peacock, 1997; Elliot et.al, 2006; Aruntoi, 2008; Kulatunga, 2010). But in the Indian context, this field of inquiry i.e. linking disaster policies with tradition and generational understanding has seldom received attention of the government, decision- making authorities, disaster managers and even in the academia. The present study attempts to fill this gap in research and scholarship by presenting an historical analysis of disaster and its cognition by cultural communities in India. The paper seeks to interlink the cultural comprehension of Indian tribal communities with scientific-technology towards more constructive disaster policies in India.

Keywords: culture, disasters, local communities, traditional knowledge

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Authors: Bedilu Tafesse

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Conservation of crop genetic resources presents a challenge of identifying specific determinants driving maintenance of diversity at farm and agroecosystems. The objectives of this study were to identify socioeconomic, market and agroecological determinants of farmers’ maintenance of wheat diversity at the household level and derive implications for policies in designing on-farm conservation programs. We assess wheat diversity at farm level using household survey data. A household decision making model is conceptualized using microeconomic theory to assess and identify factors influencing on-farm rice diversity. The model is then tested econometrically by using various factors affecting farmers’ variety choice and diversity decisions. The findings show that household-specific socioeconomic, agroecological and market factors are important in determining on-farm wheat diversity. The significant variables in explaining richness and evenness of wheat diversity include distance to the nearest market, subsistence ratio, modern variety sold, land types and adult labour working in agriculture. The statistical signs of the factors determining wheat diversity are consistent in explaining the richness, dominance and evenness among rice varieties. Finally, the study implies that the cost-effective means of promoting and sustaining on-farm conservation programmes is to target them in market isolated geographic locations of high crop diversity where farm households have more heterogeneity of agroecological conditions and more active family adult labour working on-farm.

Keywords: diversity indices, dominance, evenness, on-farm conservation, wheat diversity, richness

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Authors: Vladimir M. Tomović, Branislav V. Šojić, Predrag M. Ikonić, Ljiljana S. Petrović, Anamarija I. Mandić, Natalija R. Džinić, Snežana B. Škaljac, Tatjana A. Tasić, Marija R. Jokanović

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In this paper influence of packaging method (vacuum and modified atmosphere packaging) on lipid oxidative stability and sensory properties of odor and taste of the traditional sausage Petrovská klobása were examined. These parameters were examined during storage period (7 months). In the end of storage period, vacuum packed sausage showed better oxidative stability. Propanal content was significantly lower (P<0.05) in vacuum packed sausage compared to these values in unpacked and modified atmosphere packaging sausage. Hexanal content in vacuum packed sausage was 1.85 µg/g, in MAP sausage 2.98 µg/g and in unpacked sausage 4.94 µg/g. After 2 and 7 months of storage, sausages packed in vacuum had the highest grades for sensory properties of odor and taste.

Keywords: lipid oxidation, MAP, sensory properties, traditional sausage, vacuum

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