Search results for: leverage

Authors: Bander Alzahrani

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Information-centric networking (ICN) using architectures such as Publish-Subscribe Internet Routing Paradigm (PSIRP) is one of the promising candidates for a future Internet, has recently been under the spotlight by the research community to investigate the possibility of redesigning the current Internet architecture to solve many issues such as routing scalability, security, and quality of services issues.. The Bloom filter-based forwarding is a source-routing approach that is used in the PSIRP architecture. This mechanism is vulnerable to brute force attacks which may lead to denial-of-service (DoS) attacks. In this work, we present a new forwarding approach that keeps the advantages of Bloom filter-based forwarding while mitigates attacks on the forwarding mechanism. In practice, we introduce a special type of forwarding nodes called Edge-FW to be placed at the edge of the network. The role of these node is to add an extra security layer by validating and inspecting packets at the edge of the network against brute-force attacks and check whether the packet contains a legitimate forwarding identifier (FId) or not. We leverage Certificateless Aggregate Signature (CLAS) scheme with a small size of 64-bit which is used to sign the FId. Hence, this signature becomes bound to a specific FId. Therefore, malicious nodes that inject packets with random FIds will be easily detected and dropped at the Edge-FW node when the signature verification fails. Our preliminary security analysis suggests that with the proposed approach, the forwarding plane is able to resist attacks such as DoS with very high probability.

Keywords: bloom filter, certificateless aggregate signature, denial-of-service, information centric network

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Authors: Kristopher A. Pruitt, Justin M. Hill

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The purpose of this research is to determine the pacing and nutrition strategies which minimize completion time and carbohydrate intake for athletes competing in ultramarathon races. The model formulation consists of a two-phase optimization. The first-phase mixed-integer nonlinear program (MINLP) determines the minimum completion time subject to the altitude, terrain, and distance of the race, as well as the mass and cardiovascular fitness of the athlete. The second-phase MINLP determines the minimum total carbohydrate intake required for the athlete to achieve the completion time prescribed by the first phase, subject to the flow of carbohydrates through the stomach, liver, and muscles. Consequently, the second phase model provides the optimal pacing and nutrition strategies for a particular athlete for each kilometer of a particular race. Validation of the model results over a wide range of athlete parameters against completion times for real competitive events suggests strong agreement. Additionally, the kilometer-by-kilometer pacing and nutrition strategies, the model prescribes for a particular athlete suggest unconventional approaches could result in lower completion times. Thus, the MINLP provides prescriptive guidance that athletes can leverage when developing pacing and nutrition strategies prior to competing in ultramarathon races. Given the highly-variable topographical characteristics common to many ultramarathon courses and the potential inexperience of many athletes with such courses, the model provides valuable insight to competitors who might otherwise fail to complete the event due to exhaustion or carbohydrate depletion.

Keywords: nutrition, optimization, pacing, ultramarathons

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Authors: Jocelyn Cohen

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This paper identifies a powerful synchronicity of two traditions of life-story writing in the autobiographies of ritual abuse (RA) survivors, the Christian conversion narrative and the memoir of healing from childhood sexual trauma. Using methodologies from literary studies, history, and psychology, a close reading of three RA memoirs sheds light on a taboo and deeply suspect form of violence. Treatment of RA survivors and the unique role of psychotherapists, in particular, deserve far greater attention from multi-disciplinary scholars. Each story reflects salient characteristics of the Christian conversion narrative, a genre which originated in the US in the early 19th century with the serendipitous confluence of the simultaneous emergence of print culture and the basic structures of evangelicalism during the Second Great Awakening. The impulse of writing is thus to give testimony against the sin they witnessed and endured as young children during ritual violence perpetrated within the church. Importantly, RA is seen as an inherent if obscure aspect of Christian discourse itself, not in opposition to it, and not as an aberration. In RA's memoir, healing comes in part from the Christian narrative praxis of personal redemption, framed as prevailing in a war between good and evil. In other words, storytelling itself affects the healing, much as it does by means of each writer’s 'talking cure,' in the relationship with a psychotherapist who guides her through a repair of the life-story through the excavation of traumatic memories and their integration into the writer’s psyche. Integrating literary techniques into the psychotherapeutic relationship, therapists leverage the deep linguistic structures that clients possess as a resource to aid in their healing.

Keywords: memoir, psychotherapy, religion, trauma

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Authors: Jesica López, Deniz Koca, Asaf Tzachor

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In 2016 the historic peace accord between the Colombian government and the Revolutionary Armed Forces of Colombia (FARC) had no strong mechanism for managing changes to land use and the environment. Since the end of a 60-year conflict in Colombia, large areas of forest in the Amazon region have been rapidly converted to agricultural uses, most recently by cattle ranching. This suggests that the peace agreement presents a threat to the conservation of the country's rainforest. We analyze the effects of cattle ranching as a driver and accelerator of deforestation from a systemic perspective, focusing on two key leverage points the legal and illegal activities involved in the cattle ranching practices. We map and understand the inherent dynamic complexity of deforestation, including factors such as land policy instruments, national strategy to tackle deforestation, land use nexus with Amazonian food systems, and loss of biodiversity. Our results show that deforestation inside Colombian Protected Areas (PAs) in the Amazon region and the surrounding buffer areas has accelerated with the onset of peace. By using a systems analysis approach, we contextualized the competition of land between cattle ranching and the need to protect tropical forests and their biodiversity loss. We elaborate on future recommendations for land use management decisions making suggest the inclusion of an Amazonian food system, interconnecting and visualizing the synergies between sustainable development goals, climate action (SDG 13) and life on land (SDG 15).

Keywords: tropical rainforest, deforestation, sustainable land use, food security, Colombian Amazon

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Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Derejaw Lake Melie, Alemu Kumlachew Tegegne

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The increasing prevalence of social media in Ethiopia has exacerbated societal challenges by fostering the proliferation of negative emotional posts and comments. Illicit use of social media has further exacerbated divisions among the population. Addressing these issues through manual identification and aggregation of emotions from millions of users for swift decision-making poses significant challenges, particularly given the rapid growth of Amharic language usage on social platforms. Consequently, there is a critical need to develop an intelligent system capable of automatically detecting and categorizing negative emotional content into social, religious, and political categories while also filtering out toxic online content. This paper aims to leverage sentiment analysis techniques to achieve automatic detection and filtering of negative emotional content from Amharic social media texts, employing a comparative study of deep learning algorithms. The study utilized a dataset comprising 29,962 comments collected from social media platforms using comment exporter software. Data pre-processing techniques were applied to enhance data quality, followed by the implementation of deep learning methods for training, testing, and evaluation. The results showed that CNN, GRU, LSTM, and Bi-LSTM classification models achieved accuracies of 83%, 50%, 84%, and 86%, respectively. Among these models, Bi-LSTM demonstrated the highest accuracy of 86% in the experiment.

Keywords: negative emotion, emotion detection, social media filtering sentiment analysis, deep learning.

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Authors: Hussaini Bala

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There are different opinions in the literature on the relationship between Audit Committee characteristics and earnings management. The mix of opinions makes the direction of their relationship ambiguous. This study investigated the relationship between Audit Committee characteristics and earnings management of listed food and beverages Firms in Nigeria. The study covered the period of six years from 2007 to 2012. Data for the study were extracted from the Firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences. The dependent variable was generated using two steps regression in order to determine the discretionary accrual of the sample Firms. Multiple regression was employed to run the data of the study using Random Model. The results from the analysis revealed a significant association between audit committee characteristics and earnings management of the Firms. While audit committee size and committees’ financial expertise showed an inverse relationship with earnings management, committee’s independence, and frequency of meetings are positively and significantly related to earnings management. In line with the findings, the study recommended among others that listed food and beverages Firms in Nigeria should strictly comply with the provision of Companies and Allied Matters Act (CAMA) and SEC Code of Corporate Governance on the issues regarding Audit Committees. Regulators such as SEC should increase the minimum number of Audit Committee members with financial expertise and also have a statutory position on the maximum number of Audit Committees meetings, which should not be greater than four meetings in a year as SEC code of corporate governance is silent on this.

Keywords: audit committee, earnings management, listed Food and beverages size, leverage, Nigeria

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Authors: Olurankinse Felix, Fatukasi Bayo

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Over the years, the medium through which government financial statements are prepared has been on cash basis of accounting. This basis was characterised with some shortcomings ranging from non- disclosure of quality and detail information relating to government financial transactions, ill informed assessment of government resource allocation, weak internal control system that inhibits accountability and transparency and non- standardisation of reporting ethics for the purpose of comparability. The emergence of international public sector accounting standards (IPSAS) is therefore seen as leverage as it aims at improving the quality of general purpose financial reporting by public sector entities thereby increasing transparency and accountability. IPSAS is a new concept that all institutions must fully adopts. The crux of this paper is to find out to what extent is the awareness and adoption of IPSAS to both students and lecturers interms of teaching, learning and inclusion in the curriculum of accounting education. The methodology involved the use of well designed questionnaires to obtain information from some selected institutions and the analysis was done with the use of maximum likelihood ordered probit regression. The result of the analysis shows that despite a high level of sensitisation/awareness of IPSAS, the degree of adoption is still low due to low level of desirability by students and lecturers. The paper recommend the need for the government to enact an enabling law to back up the adoption and more importantly to institute appropriate sanctions to ensure full compliance.

Keywords: assessment, awareness, adoption, IPSAS, cash basis

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Authors: Taurai T. Chikotie, Bruce W. Watson

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The manifestation of ‘new’ infectious diseases and the re-emergence of ‘old’ infectious diseases now present global problems and Southern Africa has not been spared from such calamity. Although having an organized public health system, countries in this region have failed to leverage on the proliferation in use of Information and Communication Technologies to promote effective disease surveillance. Objective: The objective of this study was to critically review and analyse the crucial variables to consider in the development and implementation of electronic disease surveillance systems in public health within the context of Southern Africa. Methodology: A critical review of literature published in English using, Google Scholar, EBSCOHOST, Science Direct, databases from the Centre for Disease Control (CDC and articles from the World Health Organisation (WHO) was undertaken. Manual reference and grey literature searches were also conducted. Results: Little has been done towards harnessing the potential of information technologies towards disease surveillance and this has been due to several challenges that include, lack of funding, lack of health informatics experts, poor supporting infrastructure, an unstable socio-political and socio-economic ecosystem in the region and archaic policies towards integration of information technologies in public health governance. Conclusion: The Southern African region stands to achieve better health outcomes if they adopt the use of e-disease surveillance systems in public health. However, the dynamics and complexities of the socio-economic, socio-political and technical variables would need addressing to ensure the successful development and implementation of e-disease surveillance systems in the region.

Keywords: critical review, disease surveillance, public health informatics, Southern Africa

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Authors: Mahdi Bastan, Ali Mohammad Ahmadvand, Fatemeh Soltani Khamsehpour

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Health organizations’ sustainable development has nowadays become highly affected by customers’ satisfaction due to significant changes made in the business environment of the healthcare system and emerging of Competitiveness paradigm. In case we look at the hospitals and other health organizations as service providers concerning profit issues, the satisfaction of employees as interior customers, and patients as exterior customers would be of significant importance in health business success. Furthermore, satisfaction rate could be considered in performance assessment of healthcare organizations as a perceived quality measure. Several researches have been carried out in identification of effective factors on patients’ satisfaction in health organizations. However, considering a systemic view, the complex causal relations among many components of healthcare system would be an issue that its acquisition and sustainability requires an understanding of the dynamic complexity, an appropriate cognition of different components, and effective relationships among them resulting ultimately in identifying the generative structure of patients’ satisfaction. Hence, the presenting paper applies system dynamics approaches coherently and methodologically to represent the systemic structure of customers’ satisfaction of a health system involving the constituent components and interactions among them. Then, the results of different policies taken on the system are simulated via developing mathematical models, identifying leverage points, and using scenario making technique and then, the best solutions are presented to improve customers’ satisfaction of the services. The presenting approach supports taking advantage of decision support systems. Additionally, relying on understanding of system behavior Dynamics, the effective policies for improving the health system would be recognized.

Keywords: customer satisfaction, healthcare, scenario, simulation, system dynamics

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Authors: Ghadeer A.Al-Jabaree, Husam Aldeen Al-Khadash, M. Nassar

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This study aimed at investigating the effect of well-designed corporate governance system on the financial stability of insurance companies listed in ASE. Further, this study provides a comprehensive model for evaluating and analyzing insurance companies' financial position and prospective for comparing the degree of corporate governance application provisions among Jordanian insurance companies. In order to achieve the goals of the study, a whole population that consist of (27) listed insurance companies was introduced through the variables of (board of director, audit committee, internal and external auditor, board and management ownership and block holder's identities). Statistical methods were used with alternative techniques by (SPSS); where descriptive statistical techniques such as means, standard deviations were used to describe the variables, while (F) test and ANOVA analysis of variance were used to test the hypotheses of the study. The study revealed the existence of significant effect of corporate governance variables except local companies that are not listed in ASE on financial stability within control variables especially debt ratio (leverage),where it's also showed that concentration in motor third party doesn't have significant effect on insurance companies' financial stability during study period. Moreover, the study concludes that Global financial crisis affect the investment side of insurance companies with insignificant effect on the technical side. Finally, some recommendations were presented such as enhancing the laws and regulation that help the appropriate application of corporate governance, and work on activating the transparency in the disclosures of the financial statements and focusing on supporting the technical provisions for the companies, rather than focusing only on profit side.

Keywords: corporate governance, financial stability and solvency margin, insurance companies, Jordan

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Authors: S. O. Okoro

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Some words become the catch phrase of a particular decade. Globalization, Openness, and Privatization are certainly among the most frequently encapsulation of 1990’s; the market is ‘in’, ‘the state is out’. In the 1970’s, there were many political economists who spoke of autarky as one possible response to global economic forces. Be self-contained, go it alone, put up barriers to trans-nationalities, put in place import-substitution industrialization policy and grow domestic industries. In 1990’s, the emasculation of the state is by no means complete, but there is an acceptance that the state’s power is circumscribed by forces beyond its control and potential leverage. Autarky is no longer as a policy option. Nigeria, since its emergence as an independent nation, has evolved two macroeconomic management regimes of the interventionist and market friendly styles. This paper investigates Nigeria’s growth performance over the periods incorporating these two regimes and finds that there is no structural break in Total Factor Productivity, (TFP) growth and besides, the TFP growth over the entire period of study 1970-2012 is very negligible and hence growth can only be achieved by the unsustainable factor accumulation. Another important finding of this work is that the openness-human capital interaction term has a significant impact on the TFP growth, but the sign of the estimated coefficient does not meet it a theoretical expectation. This is because the negative coefficient on the human capital outweighs the positive openness effect. The poor quality of human capital is considered to have given rise to this. Given these results a massive investment in the education sector is required. The investment should be targeted at reforms that go beyond mere structural reforms to a reform agenda that will improve the quality of human capital in Nigeria.

Keywords: globalization, emasculation, openness and privatization, total factor productivity

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Authors: Iacopo Carnacina, Mohammad Keshtpoor, Richard Yablonsky

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Non-structural protection measures against flooding are becoming increasingly popular flood risk mitigation strategies. In particular, coastal flood insurance impacts not only private citizens but also insurance and reinsurance companies, who may require it to retain solvency and better understand the risks they face from a catastrophic coastal flood event. In this context, a framework is presented here to assess the risk for coastal flooding across the UK. The area has a long history of catastrophic flood events, including the Great Flood of 1953 and the 2013 Cyclone Xaver storm, both of which led to significant loss of life and property. The current framework will leverage a technology based on a hydrodynamic model (Delft3D Flexible Mesh). This flexible mesh technology, coupled with a calibration technique, allows for better utilisation of computational resources, leading to higher resolution and more detailed results. The generation of a stochastic set of extra tropical cyclone (ETC) events supports the evaluation of the financial losses for the whole area, also accounting for correlations between different locations in different scenarios. Finally, the solution shows a detailed analysis for the Thames River, leveraging the information available on flood barriers and levees. Two realistic disaster scenarios for the Greater London area are simulated: In the first scenario, the storm surge intensity is not high enough to fail London’s flood defences, but in the second scenario, London’s flood defences fail, highlighting the potential losses from a catastrophic coastal flood event.

Keywords: storm surge, stochastic model, levee failure, Thames River

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Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: propaganda analysis, emotive triggers environmental security, frames

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Authors: Nisar Ahmad, Xuyi, Ali Akbar

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As healthcare systems worldwide strive for improvement, the integration of advanced health information systems (HIS) has emerged as a pivotal strategy. This study aims to investigate the critical role of leadership in the implementation and enhancement of HIS in Chinese hospitals and how such leadership can drive improvements in patient outcomes and overall healthcare satisfaction. We propose a comprehensive study to be conducted across various hospitals in China, targeting healthcare professionals as the primary population. The research will leverage established theories of transformational leadership and technology acceptance to underpin the analysis. In our approach, data will be meticulously gathered through surveys and interviews, focusing on the experiences and perceptions of healthcare professionals regarding HIS implementation and its impact on patient care. The study will utilize SPSS and SmartPLS software for robust data analysis, ensuring precise and comprehensive insights into the correlation between leadership effectiveness and HIS success. We hypothesize that strong, visionary leadership is essential for the successful adoption and optimization of HIS, leading to enhanced patient outcomes and increased satisfaction with healthcare services. By applying advanced statistical methods, we aim to identify key leadership traits and practices that significantly contribute to these improvements. Our research will provide actionable insights for policymakers and healthcare administrators in China, offering evidence-based recommendations to foster leadership that champions HIS and drives continuous improvement in healthcare delivery. This study will contribute to the global discourse on health information systems, emphasizing the future role of leadership in transforming healthcare environments and outcomes.

Keywords: health information systems, leadership, patient outcomes, healthcare satisfaction

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Authors: Omar Alsetoohy, Mohamed Ezzat, Mahmoud Abou Kamar

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The success of a restaurant or hotel depends very much on the quality and quantity of its human resources. Thus, establishing a competitive edge through human assets requires careful attention to the practices that best leverage these assets. Usually, hotel or restaurant employees recognize customer defection as an unfavorable or unpleasant occurrence associated with failure. These failures could be in handling, communication, learning, or encouragement. Besides, employees could be afraid of blame from their colleagues and managers, which prevents them from freely discussing these mistakes with them. Such behaviors, in turn, would push employees to withdraw from the workplace. However, we have a good knowledge of the leadership outcomes, but less is known about how and why these effects occur. Accordingly, mindful leaders usually analyze the causes and underlying mechanisms of failures for work improvement. However, despite the excessive literature in the field of leadership and employee behaviors, to date, no research studies had investigated the impact of a failure-tolerant restaurant culture on the employees’ withdrawal behaviors considering the moderating role of psychological empowerment and mindful leadership. Thus, this study seeks to investigate the impact of a failure-tolerant culture on the employees’ withdrawal behaviors in fast-food restaurants in Egypt considering the moderating effects of employee empowerment and mindful leaders. This study may contribute to the existing literature by filling the gap between failure-tolerant cultures and employee withdrawal behaviors in the hospitality literature. The study may also identify the best practices for restaurant operators and managers to deal with employees' failures as an improvement tool for their performance.

Keywords: failure-tolerant culture, employees’ withdrawal behaviors psychological empowerment, mindful leadership, restaurants

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Authors: Junyu Chen, Peng Xu

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In the context of global efforts to enhance building energy efficiency, accurate thermal load forecasting is crucial for both device sizing and predictive control. Variable Refrigerant Flow (VRF) systems are widely used in buildings around the world, yet VRF zonal load prediction has received limited attention. Due to differences between VRF zones in building-level prediction methods, zone-level load forecasting could significantly enhance accuracy. Given that modern VRF systems generate high-quality data, this paper introduces transfer learning to leverage this data and further improve prediction performance. This framework also addresses the challenge of predicting load for building zones with no historical data, offering greater accuracy and usability compared to pure white-box models. The study first establishes an initial variable set of VRF zonal building loads and generates a foundational white-box database using EnergyPlus. Key variables for VRF zonal loads are identified using methods including SRRC, PRCC, and Random Forest. XGBoost and LSTM are employed to generate pre-trained black-box models based on the white-box database. Finally, real-world data is incorporated into the pre-trained model using transfer learning to enhance its performance in operational buildings. In this paper, zone-level load prediction was integrated with transfer learning, and a framework was proposed to improve the accuracy and applicability of VRF zonal load prediction.

Keywords: zonal load prediction, variable refrigerant flow (VRF) system, transfer learning, energyplus

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Namirimu Beatrice Doreen

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In recent years, there has been growing recognition of the importance of diversity, equity, and inclusion (DEI) in advertising, driven in part by the increasing diversity of society and the expanding reach of new media platforms. As marketers grapple with the challenge of creating campaigns that resonate with a wide range of audiences, the role of new media adoption emerges as a critical, independent variable shaping the landscape of DEI in advertising. This paper delves into the evolving dynamics of DEI in advertising, examining the multifaceted challenges and opportunities encountered by brands in their pursuit of more inclusive marketing strategies. Drawing on theoretical frameworks from marketing, sociology, and communication studies, this paper explores the intricate interplay between DEI initiatives and their impact on consumer perceptions, brand reputation, and market performance. The analysis considers how new media adoption influences the effectiveness and reach of DEI initiatives as brands leverage digital platforms to engage with diverse audiences in innovative ways. Through insightful case studies, this paper illustrates best practices and identifies areas for improvement in the realm of inclusive advertising, shedding light on the practical implications of DEI principles for marketers. By synthesizing insights from academia and industry, this paper offers actionable recommendations for marketers seeking to navigate the complexities of DEI in their advertising strategies. By embracing DEI principles and harnessing the power of new media platforms, brands can foster a more equitable and inclusive advertising landscape, ultimately enhancing their connections with diverse audiences and driving positive social change.

Keywords: diversity, equity, inclusion, new media, contemporary marketing communication

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Authors: Atia Alam

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Growing liberalisation and intense market competition increase firm’s risk exposure and induce corporations to use derivatives extensively as a risk management instrument, which results in decrease in firm’s risk, and increase in value. Present study contributes towards existing literature by providing an in-depth analysis regarding the effect of extent of derivative usage on firm’s risk and value by using panel data models and seemingly unrelated regression technique. New evidence is established in current literature by dividing the sample data based on firm’s Exchange Rate (ER) and Interest Rate (IR) exposure. Analysis is performed for the effect of extent of derivative usage on firm’s risk and value and its variation with respect to the ER and IR exposure. Sample data consists of 166 Pakistani firms listed on Pakistan stock exchange for the period of 2004-2010. Results show that extensive usage of derivative instruments significantly increases firm value and reduces firm’s risk. Furthermore, comprehensive analysis depicts that Pakistani corporations having higher exchange rate exposure, with respect to foreign sales, and higher interest rate exposure, on the basis of industry adjusted leverage, have higher firm value and lower risk. Findings from seemingly unrelated regression also provide robustness to results obtained through panel data analysis. Study also highlights the role of derivative usage as a risk management instrument in high and low ER and IR risk and helps practitioners in understanding how value increasing effect of extent of derivative usage varies with the intensity of firm’s risk exposure.

Keywords: extent of derivative usage, firm value, risk, Pakistan, non-financial firms

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Authors: Loide Sambo

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Achieving energy security has, in the past few decades, become one of the main goals in the security agenda of every country around the world. For Southern African Countries (SAC) the aim is not different, yet these countries face a particular challenge in the pursuit of their energy security. More than just secure enough energy sources to fuel their industrial and societal needs, SAC have as well to ensure that they trade their rich energy resources to the global market in a way that promotes and safeguards their economic development objectives. Considering the relevance of this issue to the SAC, the present paper explores the possibility of these countries to achieve energy security through regional cooperation, under the Southern Africa Development Community (SADC) platform. It discusses the challenges and opportunities for advancing energy security in this region through cooperation. After analyzing the data through the documentary analysis method, it was found that regional cooperation among SAC to improve energy security is not effective since cooperation in the region is still very susceptible to a plethora of challenges, such as political instability, lack of development of infrastructure and expertise, lack of good governance, lack of sense of cohesiveness, and most important lack of political commitment. It was also found that significant commitment on regional cooperation had been centered on the electricity sub-sector due to the region’s huge electricity deficit. Thus less commitment is dedicated to the development and policy harmonization of the other sub-sectors such as the one of natural gas and oil, for instance. Hence, it is recommended that the leadership of the SAC is fully committed to cooperate and harmonize the policies, the strategic plans, as well as the infrastructure concerning to all the natural energy resources and its respective sub-sectors. This would provide the SAC significant leverage to negotiate for the energy market access, ensuring that the region’s energy commodities are traded, while the countries themselves retain enough energy to sustain their economic growth and development, improving, therefore, their energy security.

Keywords: regional cooperation, energy security, economic development, political commitment

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Authors: Maria Granados

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Information technology (IT) facilitates the management of knowledge in organisations through the effective leverage of collective experience and knowledge of employees. This supports information processing needs, as well as enables and facilitates sense-making activities of knowledge workers. The study of IT support for knowledge management (KM) has been carried out mainly in larger organisations where resources and competitive conditions can trigger the use of KM. However, there is still a lack of understanding on how IT can support the management of knowledge under different organisational settings influenced by: constant tensions between social and economic objectives, more focus on sustainability than competiveness, limited resources, and high levels of democratic participation and intrinsic motivations among employees. All these conditions are presented in Social Enterprises (SEs), which are normally micro and small businesses that trade to tackle social problems, improve communities, people’s life chances, and the environment. Thus, their importance to society and economies is increasing. However, there is still a need for more understanding of how these organisations operate, perform, innovate and scale-up. This knowledge is crucial to design and provide accurate strategies to enhance the sector and increase its impact and coverage. To obtain a conceptual and empirical understanding of how IT can facilitate KM in the particular organisational conditions of SEs, a quantitative study was conducted with 432 owners and senior members of SEs in UK, underpinned by 21 interviews. The findings demonstrated how IT was supporting more the recovery and storage of necessary information in SEs, and less the collaborative work and communication among enterprise members. However, it was established that SEs were using cloud solutions, web 2.0 tools, Skype and centralised shared servers to manage informally their knowledge. The possible impediments for SEs to support themselves more on IT solutions can be linked mainly to economic and human constraints. These findings elucidate new perspectives that can contribute not only to SEs and SE supporters, but also to other businesses.

Keywords: social enterprises, knowledge management, information technology, collaboration, small firms

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Authors: Sade Ogundipe

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The private healthcare sector in the United Kingdom has experienced unprecedented challenges during times of crisis, necessitating effective leadership adaptability. This qualitative study delves into the dynamic landscape of leadership within the sector, particularly during crises, employing the lenses of complexity theory and institutional theory to unravel the intricate mechanisms at play. Through in-depth interviews with 25 various levels of leaders in the UK private healthcare sector, this research explores how leaders in UK private healthcare organizations navigate complex and often chaotic environments, shedding light on their adaptive strategies and decision-making processes during crises. Complexity theory is used to analyze the complicated, volatile nature of healthcare crises, emphasizing the need for adaptive leadership in such contexts. Institutional theory, on the other hand, provides insights into how external and internal institutional pressures influence leadership behavior. Findings from this study highlight the multifaceted nature of leadership adaptability, emphasizing the significance of leaders' abilities to embrace uncertainty, engage in sensemaking, and leverage the institutional environment to enact meaningful changes. Furthermore, this research sheds light on the challenges and opportunities that leaders face when adapting to crises within the UK private healthcare sector. The study's insights contribute to the growing body of literature on leadership in healthcare, offering practical implications for leaders, policymakers, and stakeholders within the UK private healthcare sector. By employing the dual perspectives of complexity theory and institutional theory, this research provides a holistic understanding of leadership adaptability in the face of crises, offering valuable guidance for enhancing the resilience and effectiveness of healthcare leadership within this vital sector.

Keywords: leadership, adaptability, decision-making, complexity, complexity theory, institutional theory, organizational complexity, complex adaptive system (CAS), crises, healthcare

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Authors: Sami M. Alshareef

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In the rapidly evolving energy landscape, the integration of renewable energy sources and the electrification of transportation are essential steps toward achieving sustainability goals. However, these advancements introduce new challenges, particularly in maintaining frequency stability due to variable photovoltaic (PV) generation and the growing demand for fast charging stations. The variability of photovoltaic (PV) generation due to weather conditions can disrupt the balance between generation and load, resulting in frequency deviations. To ensure the stability of power systems, it is imperative to develop effective under frequency load-shedding schemes. This research proposal presents an adaptive under-frequency load shedding scheme based on the power swing equation, designed explicitly for the IEEE-9 Bus Test System, that includes PV generation and fast charging stations. This research aims to address these challenges by developing an advanced scheme that dynamically disconnects fast charging stations based on power imbalances. The scheme prioritizes the disconnection of stations near affected areas to expedite system frequency stabilization. To achieve these goals, the research project will leverage the power swing equation, a widely recognized model for analyzing system dynamics during under-frequency events. By utilizing this equation, the proposed scheme will adaptively adjust the load-shedding process in real-time to maintain frequency stability and prevent power blackouts. The research findings will support the transition towards sustainable energy systems by ensuring a reliable and uninterrupted electricity supply while enhancing the resilience and stability of power systems during under-frequency events.

Keywords: load shedding, fast charging stations, pv generation, power system resilience

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Authors: Antonia Hoffmann, Andrea Stübner

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Resource scarcity and rising material prices are forcing companies to rethink their business models. The conventional linear system of economic growth and rising social needs further exacerbates the problem of resource scarcity. Therefore, it is necessary to separate economic growth from resource consumption. This can be achieved through the circular economy (CE), which focuses on sustainable product life cycles. However, companies face challenges in implementing CE into their businesses. Small and medium-sized enterprises are particularly affected by these problems, as they have a limited resource base. Collaboration and social interaction between different actors can help to overcome these obstacles. Based on a self-generated sample of 1,023 German small and medium-sized enterprises, we use a questionnaire to investigate the influence of social capital and its three dimensions - structural, relational, and cognitive capital - on the implementation of CE and the mediating effect of dynamic capabilities in explaining these relationships. Using regression analyses and structural equation modeling, we find that social capital is positively associated with CE implementation and dynamic capabilities partially mediate this relationship. Interestingly, our findings suggest that not all social capital dimensions are equally important for CE implementation. We theoretically and empirically explore the network forms of social capital and extend the CE literature by suggesting that dynamic capabilities help organizations leverage social capital to drive the implementation of CE practices. The findings of this study allow us to suggest several implications for managers and institutions. From a practical perspective, our study contributes to building circular production and service capabilities in small and medium-sized enterprises. Various CE activities can transform products and services to contribute to a better and more responsible world.

Keywords: circular economy, dynamic capabilities, SMEs, social capital

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Authors: Getiye Dejenu Kibret, Daniel Demant, Andrew Hayen

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Introduction: In Ethiopia, more than half of newborn babies do not have access to Emergency Obstetric and Neonatal Care (EmONC) services. Understanding the effect of distance to health facilities on service use and neonatal survival is crucial to recommend policymakers and improve resource distribution. We aimed to investigate the effect of distance to health services on maternal service use and neonatal mortality. Methods: We implemented a data linkage method based on geographic coordinates and calculated straight-line (Euclidean) distances from the Ethiopian 2016 demographic and health survey clusters to the closest health facility. We computed the distance in ESRI ArcGIS Version 10.3 using the geographic coordinates of DHS clusters and health facilities. Generalised Structural Equation Modelling (GSEM) was used to estimate the effect of distance on neonatal mortality. Results: Poor geographic accessibility to health facilities affects maternal service usage and increases the risk of newborn mortality. For every ten kilometres (km) increase in distance to a health facility, the odds of neonatal mortality increased by 1.33% (95% CI: 1.06% to 1.67%). Distance also negatively affected antenatal care, facility delivery and postnatal counselling service use. Conclusions: A lack of geographical access to health facilities decreases the likelihood of newborns surviving their first month of life and affects health services use during pregnancy and immediately after birth. The study also showed that antenatal care use was positively associated with facility delivery service use and that both positively influenced postnatal care use, demonstrating the interconnectedness of the continuum of care for maternal and neonatal care services. Policymakers can leverage the findings from this study to improve accessibility barriers to health services.

Keywords: acessibility, distance, maternal health service, neonatal mortality

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Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 78