Search results for: empirical data

Authors: Mounir Kehal

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The post-globalization epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behavior has come to provide the competitive and comparative edge. Enterprises have turned to explicit - and even conceptualizing on tacit - knowledge management to elaborate a systematic approach to develop and sustain the intellectual capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualized. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper, we present an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Amina Benabderrahmane, Abdelylah Benazza, Samir Laouedj

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Three dimensional numerical investigation of heat transfer enhancement inside a non-uniformly heated parabolic trough solar collector fitted with baffles under turbulent flow was studied in the current paper. Molten salt is used as heat transfer fluid and simulations are carried out in ANSYS computational fluid dynamics (CFD). The present data was validating by the empirical correlations available in the literatures and good agreement was obtained. The Nusselt number and friction factor values for using baffles are considerably higher than that for smooth pipe. The emplacement and the distance between two consecutive baffles have an effect non-negligible on heat transfer characteristics; the results demonstrate that the temperature gradient reduces with the inclusion of inserts.

Keywords: Baffles, heat transfer enhancement, molten salt, Monte Carlo ray trace technique, numerical investigation

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Authors: Moses Pinto, Ana Paula Monte

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The present research analyses the interactions between various categories of corporate social responsibility (CSR) that mediate the relationship between CSR and financial performance in Multinational Enterprises (MNE) in light of the present socio-political factors prevalent in the countries under observation. In the research it has been hypothesized that the absence of consensus in the empirical literature on the CSR–financial performance relationship may be explained by the existence of synergies (Complementarities) between the different CSR components. Upon investigation about whether such relationships exist, a final unbalanced panel sample of 1000 observations taken from 100 Multinational Enterprises per year functioning in the Schengen countries and one south east Asian country namely: India, over the span of 10 years i.e. from the year 2008 to 2018 has been analyzed. The empirical analysis used in the research methodology employs dynamic Panel Data in time series specifically, the system Generalized Method of Moments (GMM) which had been used to detect the varying degrees of relationships between the CSR and financial performance parameters in the background of the socio-political factors prevailing in the countries at the time and also taking into account the bilateral treaty obligations between the countries under observation. The econometric model has employed the financial ratio namely the Return on Assets (ROA) as an indicator of financial performance in order to gauge the internal performance and valuation of a firm as opposed to the Tobin’s Q that provides for the external evaluation of a firm’s financial performance which may not always be accurate. The various CSR dimensions have demonstrated significant correlations to the ‘ROA’ which include some negatively associated correlations and one positively associated correlation that is highly significant throughout the analysis of the observations, namely the correlation between the ‘ROA’ and the CSR dimension: ‘Environment’. The results provide a deeper insight in the synergistic CSR activities that managers could adapt into their Firm’s CSR strategy in order to enhance the ‘ROA’ and also to understand which interactions between the CSR dimensions can be adapted together due to their positively correlated association with each other and the ROA. The future lines of research would be inclined to investigate the effects of socio-political factors on the ROA of the MNEs through better designed econometric models.

Keywords: CSR, financial performance, complementarity, sociopolitical factors

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Authors: Deonie Botha

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Digital transformation and the digitization of occupational health and safety training have grown exponentially due to a variety of contributing factors. The literature suggests that digitalization has numerous benefits but also has associated challenges. The aim of the paper is to develop an understanding of both the perceived benefits and challenges of digitalization in an occupational health and safety context in an effort to design and develop e-learning interventions that will optimize the benefits of digitalization and address the associated challenges. The paper proposes, deliberate and tests the design principles of an e-learning intervention to ensure alignment with the requirements of a digitally transformed environment. The results of the research are based on a literature review regarding the requirements and effect of the Fourth Industrial Revolution on learning and e-learning in particular. The findings of the literature review are enhanced with empirical research in the form of a case study conducted in an organization that designs and develops e-learning content in the occupational health and safety industry. The primary findings of the research indicated that: (i) The requirements of learners and organizations in respect of e-learning are different than previously (i.e., a pre-Fourth Industrial Revolution related work setting). (ii) The design principles of an e-learning intervention need to be aligned with the entire value chain of the organization. (iii) Digital twins support and enhance the design and development of e-learning. (iv)Learning should incorporate a multitude of sensory experiences and should not only be based on visual stimulation. (v) Data that are generated as a result of e-learning interventions should be incorporated into big data streams to be analyzed and to become actionable. It is therefore concluded that there is general consensus on the requirements that e-learning interventions need to adhere to in a digitally transformed occupational health and safety work environment. The challenge remains for organizations to incorporate data generated as a result of e-learning interventions into the digital ecosystem of the organization.

Keywords: digitalization, training, fourth industrial revolution, big data

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: Saira Tajdar, Sajad Ahmad

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The pharmaceutical market of Pakistan showed a mixed trend since 1947. In these six decades various local and foreign pharmaceutical companies entered the market with their highly researched based formulas and brands for various diseases. It also created a very competitive market between local and foreign companies and brands. But this intense competition does not clear the picture that whether the customers (Doctors) are preferring/prescribing foreign or local brands more frequently. Previous research has been done in various markets for different brands that whether the customers in that industry prefer foreign or local brands. However, the pharmaceutical industry in this regard has been ignored by the researchers. Generally people don't know that for prescription brands of medicines what the preferences of customers (Doctors) are. Therefore, this study is conducted in two departments of Pharmaceutical industry by selecting the top recommended formulas in those departments that for those formulas whether the customers (Doctors) are prescribing either foreign brands or local brands. Secondary data has been collected from previous studies on the country of origin (COO), ethnocentrism and factors influencing brands preferences from authentic sources. Primary data was also collected through 100 self administered questionnaires from top five hospitals of Peshawar. The results of the study were analyzed through SPSS which shows that in some categories of pharmaceutical products the COO is very important but not for all.

Keywords: customer prescription, country of origin, empirical study, foreign versus local brands, pharmaceutical industry, Pakistan

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Authors: Seon Soon Choi

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The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: Nazima Ellahi, Danish Ramzan

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There is a growing trend among development economists regarding the importance of financial sector for economic development and growth activities. The development thus introduced, helps to promote welfare effects and poverty alleviation. This study is an attempt to find the nature of link between Islamic banking financing and development of output growth for Pakistan. Time series data set has been utilized for a time period ranging from 1990 to 2010. Following the Phillip Perron (PP) and Augmented Dicky Fuller (ADF) test of unit root this study applied Ordinary Least Squares (OLS) method of estimation and found encouraging results in favor of promoting the Islamic banking practices in Pakistan.

Keywords: Islamic finance, poverty alleviation, economic growth, finance, commerce

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Authors: Sinchul Back, Sun Ho Kim, Jennifer LaPrade, Ilju Seong

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Due to the advantage of using the Internet, cybercriminals can reach target(s) without border controls. Prior research on criminology and crime science has largely been void of empirical studies on journey-to-cybercrime and crime opportunity. Thus, the purpose of this study is to understand more about cyber offender spatial decision making associated with crime opportunity factors (i.e., co-offending, offender-stranger). Data utilized in this study were derived from 306 U.S. Federal court cases of cybercrime. The findings of this study indicated that there was a positive relationship between co-offending and journey-to-cybercrime, whereas there was no link between offender-stranger and journey-to-cybercrime. Also, the results showed that there was no relationship between cybercriminal sex, age, and journey-to-cybercrime. The policy implications and limitations of this study are discussed.

Keywords: co-offending, crime opportunity, journey-to-cybercrime, offender-stranger

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Muhammad Azeem Qureshi, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study examines empirically the effect of brand satisfaction, brand trust and brand experience on brand loyalty which can be helpful to retain and increase customer base and satisfying customer needs as well. Methodology: Data has been collected on convenient sampling method and cause and effect among variables has been measured by applying regression analysis technique. Findings: Finding of this study have supported the proposed hypotheses and results show that brand loyalty is significantly explained by brand satisfaction, brand trust and brand experience. Practical Implications: The outcome of this study provides a useful framework and importance of brand loyalty culture in Pakistan. Marketers can be benefited trough the findings of this study.

Keywords: brand experience, brand satisfaction, brand trust, brand loyalty, hair-care products

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Authors: Asowata Osamede, Trudy Sutherland

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The purpose of this paper is to assess the available power from a Renewable Energy Source (off-grid photovoltaic (PV) panel) in the Southern Hemisphere using anisotropic model. Direct solar radiation is the driving force in photovoltaics. In a basic PV panels in the Southern Hemisphere, Power conversion is eminent, and this is achieved by the PV cells converting solar energy into electrical energy. In this research, the results was determined for a 6 month period from September 2022 through February 2023. Preliminary results, which include Normal Probability plot, data analysis - R2 value, effective conversion-time per week and work-time per day, indicate a favorably comparison between the empirical results and the simulation results.

Keywords: power-conversion, mathematical model, PV panels, DC-DC converters, direct solar radiation

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Mary Edokpa Fadal, Frances Agweda

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Considering the volatile and evolving nature of the political environment in the developing countries, it is important that the subject of effective leadership practices that focus on transformational and systematic political development and values be reviewed. If the attitude towards partisan politics and the played politics by political parties is relatively deviated from expected adherence to acceptance, safe, efficient and practical standard, the political parties will continue to struggle endlessly in an effort to maintain a system that works. The analysis is situated in the context of political parties and partisan political behavior in contemporary societies and developing nations. Recent research of empirical evidence shows that most of the political parties are more or less, not too active in playing their instrumental role in the political system, such as unifying, simplifying and stabilizing the political process. This is however traced to the problem of ethnic politics that have been dominated by tribalism. The rising clamor for political development needs re-structuring and correcting the abnormalities in the center of the polity to address the flaws in our political system. The paper argues that political parties and political actors are some of the vital instrument of attaining societal goals of democratic principles for peace and durability. Issues of ethnic and partisan politics are also discussed, as it relates to question pertaining to political ideologies. It is in the findings that this paper examines some of the issues that have been seen revolving the true practice of political parties and its activities towards the democratic trend of a society, that help to resolve questions surrounding the issues of politics and governance in developing countries. These issues are seen as an aberration that have characterized politics and political behavior especially in the aspect of transparency and fulfilling its purpose of existence. The paper argues that the transition of the developing nature of states largely depends on the political structures and party politics and the nature of constitutionalism following the democratic awakening. The paper concludes that politics and political behavior are all human factors that play a vital role in the development of contemporary societies. They drive the wheel of nations towards its goal attainment. This paper relies on documentary, primary sources of data collection and empirical analysis.

Keywords: development, ethnicity, partisan politics, political behavior, political parties

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Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: automation, hydroponics, internet of things, monitoring system, urban farming

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Authors: Noawanit Songkram

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This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.

Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: Mohammed Gamil Montasser, Angelo Battaglia

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Entrepreneurship is mostly related to the beginning of organization. In growing business organizations, entrepreneurship expands its conceptualization. It reveals itself through new business creation in the active organization, through renewal, change, innovation, creation and development of current organization, through breaking and changing of established rules inside or outside the organization and becomes more flexible, adaptive and competitive, also improving effectiveness of organization activity. Therefore, the topic of entrepreneurship, relates the creation of firms to personal / individual characteristics of the entrepreneurs and their social context. This paper is an empirical study, which aims to address these two gaps in the literature. For this endeavor, we use the latest available data from the Global Entrepreneurship Monitor (GEM) project. This data set is widely regarded as a unique source of information about entrepreneurial activity, as well as the aspirations and attitudes of individuals across a wide number of countries and territories worldwide. This paper tries to contribute to fill this gap, by exploring the key drivers of innovative entrepreneurship in the tourism sector. Our findings are consistent with the existing literature in terms of the individual characteristics of entrepreneurs, but quite surprisingly we find an inverted U-shape relation between human development and innovative entrepreneurship in tourism sector. It has been revealed that tourism entrepreneurs are less likely to have innovative products, compared with entrepreneurs in medium developed countries.

Keywords: GEM, human development, innovative entrepreneurship, occupational choice, tourism

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Esraa Alhadad

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Recently, there has been considerable debate surrounding the definition, conservation, and management of heritage. Over the past few years, there has been a growing call for the inclusion of local communities in heritage management. However, the perspectives on involvement, especially concerning key stakeholders like community members, often diverge significantly. While the theoretical foundation for community involvement is reasonably established, the application of this approach in heritage management has been sluggish. Achieving a balance to fulfill the diverse goals of stakeholders in any involvement project proves challenging in practice. Consequently, there is a dearth of empirical studies exploring the practical implications of effective tools in heritage management, and limited indication exists to persuade current authorities, such as governmental organizations, to share their influence with local community members. This research project delves into community involvement within heritage management as a potent means of constructing a robust management framework. Its objective is to assess both the extent and caliber of involvement within the management of heritage sites overall, utilizing a cultural mapping-centered methodology. The findings of this study underscore the significance of engaging the local community in both heritage management and planning endeavors. Ultimately, this investigation furnishes crucial empirical evidence and extrapolates valuable theoretical and practical insights that advance understanding of cultural mapping in pivotal areas, including the catalysts for involvement and collaborative decision-making processes.

Keywords: community involvement, heritage management, cultural mapping, stakeholder mangement

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Authors: Elena Bulmer

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The research for this study has found that the formation of alliances for the successful revitalization of the global partnership for sustainable development, as defined by UN Sustainable Development Goal 17, entails considerable difficulty. This study uses for its empirical work marine environmental conservation projects and analyses the potential involvement of nonhuman actors as primordial stakeholders in these types of projects. The idea is to extend the scope of SDG 17 for it to also consider nonhuman subjects in order for it to better achieve its goal. The results of this study may be extrapolated to the business and management fields, which depend on natural resources for the development of their products. In the same way, in these areas, natural resources as nonhuman actors are not present in the stakeholder maps of these projects. Environmental Conservation projects are thus especially interesting to study with regards to their stakeholder context and have been used as the experimental setting for the empirical work of this study. The primordial stakeholders of these projects are not social objects and therefore go beyond the present limits of present stakeholder theory. The study that has been used to analyse this concept is a marine conservation project based in Spain, and to shed light in potential extending the role of the 17th Sustainable Development Goal to include nonhuman beings to be able to better achieve the rest of the SDGs, in this case, SDG 14 whose aim is to promote the conservation and sustainability of the world´s oceans.

Keywords: SDG 17, sustainability, stakeholder management, environmental conservation projects

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Mahmudjon Kuchkarov, Marufjon Kuchkarov, Mukhayyo Sobirjanova

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The origins of human language remain a profound scientific mystery, characterized by speculative theories often lacking empirical support. This study presents findings that may illuminate the genesis of human language, emphasizing its roots in natural, systematic, and repetitive sound patterns. Also, this paper presents the phonosignological and semantic analysis of linguistic elements across various languages and cultures. By utilizing the principles of the "Human Language" theory, we analyze the symbolic, phonetic, and semantic characteristics of elements such as "A", "L", "I", "F", and "四" (pronounced /si/ in Chinese and /shi/ in Japanese). Our findings reveal that natural sounds and their symbolic representations form the foundation of language, with significant implications for understanding religious and secular myths. This paper explores the intricate relationships between these elements and their cultural connotations, particularly focusing on the concept of "descent" in the context of the phonetic sequence "A, L, I, F," and the symbolic associations of the number four with death.

Keywords: empirical research, human language, phonosignology, semantics, sound patterns, symbolism, body shape, body language, coding, Latin alphabet, merging method, natural sound, origin of language, pairing, phonetics, sound and shape production, word origin, word semantic

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Authors: Wasmi Woishi

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Smart card technology is a secure and safe technology that is expanding its capabilities day by day in terms of holding important information without alteration. It is readily available, and its ease of portability makes it more efficient in terms of its usage. The smart card is in use by many industries such as financial, insurance, governmental industries, personal identification, to name a few. Smart card technology is popular for its wide familiarity, adaptability, accessibility, benefits, and portability. This research aims to find out the perception toward the application of a cloud-based healthcare system through a smart card in KSA. The research has compiled the countries using a smart card or smart healthcare card and indicated the potential benefits of implementing smart healthcare cards. 120 participants from Riyadh city were surveyed by the means of a closed-ended questionnaire. Data were analyzed through SPSS. This research extends the research body in the healthcare system. Empirical evidence regarding smart healthcare cards is scarce and hence undertaken in this study. The study provides a useful insight into collecting, storing, analyzing, manipulating, and accessibility of medical information regarding smart healthcare cards. Research findings can help achieve KSA's Vision 2030 goals in terms of the digitalization of healthcare systems in improving its efficiency and effectiveness in storing and accessing healthcare data.

Keywords: smart card technology, healthcare using smart cards, smart healthcare cards, KSA healthcare information system, cloud-based healthcare cards

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Authors: David A. Swanson, Lucky M. Tedrow

Abstract:

Taylor’s Law is a widely observed empirical pattern that relates variances to means in sets of non-negative measurements via an approximate power function, which has found application to human mortality. This study adds to this research by showing that Taylor’s Law leads to a model that reasonably describes the relationship between life expectancy at birth (e0, which also is equal to mean age at death in a life table) and variance at age of death in seven World Bank regional life tables measured at two points in time, 1970 and 2000. Using as a benchmark a non-random sample of four Japanese female life tables covering the period from 1950 to 2004, the study finds that the simple linear model provides reasonably accurate estimates of variance in age at death in a life table from e0, where the latter range from 60.9 to 85.59 years. Employing 2017 life tables from the Human Mortality Database, the simple linear model is used to provide estimates of variance at age in death for six countries, three of which have high e0 values and three of which have lower e0 values. The paper provides a substantive interpretation of Taylor’s Law relative to e0 and concludes by arguing that reasonably accurate estimates of variance in age at death in a period life table can be calculated using this approach, which also can be used where e0 itself is estimated rather than generated through the construction of a life table, a useful feature of the model.

Keywords: empirical pattern, mean age at death in a life table, mean age of a stationary population, stationary population

Procedia PDF Downloads 328

Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

Abstract:

Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

Procedia PDF Downloads 851