Search results for: PU decision

Authors: Sree Sanyal

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Research in ageing often highlights the age-related health dimension more than the psycho-social characteristics of the elderly, which also influences and challenges the health outcomes. Multimorbidity is defined as the person having more than one chronic non-communicable diseases and their prevalence increases with ageing. The study aims to evaluate the influence of social ties on self-reported prevalence of multimorbidity (selected chronic non-communicable diseases) among the selected states of elderly population in India. The data is accessed from Building Knowledge Base on Population Ageing in India (BKPAI), collected in 2011 covering the self-reported chronic non-communicable diseases like arthritis, heart disease, diabetes, lung disease with asthma, hypertension, cataract, depression, dementia, Alzheimer’s disease, and cancer. The data of the above diseases were taken together and categorized as: ‘no disease’, ‘one disease’ and ‘multimorbidity’. The predicted variables were demographic, socio-economic, residential types, and the variable of social ties includes social support, social engagement, perceived support, connectedness, and importance of the elderly. Predicted probability for multiple logistic regression was used to determine the background characteristics of the old in association with chronic morbidities showing multimorbidity. The finding suggests that 24.35% of the elderly are suffering from multimorbidity. Research shows that with reference to ‘no disease’, according to the socio-economic characteristics of the old, the female oldest old (80+) from others in caste and religion, widowed, never had any formal education, ever worked in their life, coming from the second wealth quintile standard, from rural Maharashtra are more prone with ‘one disease’. From the social ties background, the elderly who perceives they are important to the family, after getting older their decision-making status has been changed, prefer to stay with son and spouse only, satisfied with the communication from their children are more likely to have less single morbidity and the results are significant. Again, with respect to ‘no disease’, the female oldest old (80+), who are others in caste, Christian in religion, widowed, having less than 5 years of education completed, ever worked, from highest wealth quintile, residing in urban Kerala are more associated with multimorbidity. The elderly population who are more socially connected through family visits, public gatherings, gets support in decision making, who prefers to spend their later years with son and spouse only but stays alone shows lesser prevalence of multimorbidity. In conclusion, received and perceived social integration and support from associated neighborhood in the older days, knowing about their own needs in life facilitates better health and wellbeing of the elderly population in selected states of India.

Keywords: morbidity, multi-morbidity, prevalence, social ties

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Authors: Camila Lima, Murilo Andrade Valle, Patrícia Teixeira Leite Asano

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The growth in demand for electricity, caused by human development, depletion and environmental impacts caused by traditional sources of electricity generation have made new energy sources are increasingly encouraged and necessary for companies in the electricity sector. Based on this scenario, this paper assesses the negative environmental impacts associated with thermoelectric power plants in Brazil, pointing out the importance of using renewable energy sources, reducing environmental aggression. This article points out the existence of an energy alternative, wind energy, of the municipalities of São Paulo, represented by georeferenced maps with the help of GIS, using as a premise the indicators of sustainability and multicriteria analysis in the decision-making process.

Keywords: GIS (geographic information systems), multicriteria analysis, sustainability, wind energy

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Authors: M. Moradi Dalini, M. R. Talebi

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This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.

Keywords: econometrics, multiobjective optimization, management problem, optimization

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Authors: Wisam Ismail, Chole Wright, Elizabeth Baker, Cathy Tait, Mohamed Salhab, Richard Linforth

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Background: Post-mastectomy breast reconstruction is an important treatment option for women with breast cancer with psychosocial, emotional and quality of life benefits. Despite this, Asian patients are one-fifth as likely as Caucasian patients to undergo reconstruction after mastectomy. Aim: This study aimed to assess the difference in breast reconstruction rates between Asian and Caucasian patients treated at Bradford Teaching Hospitals between May 2011 – December 2015.The long-term goal is to equip healthcare professionals to improve breast cancer treatment outcome by increasing breast reconstruction rates in this sub-population. Methods: All patients undergoing mastectomy were identified using a prospectively collected departmental database. Further data was obtained via retrospective electronic case note review. Bradford city population is about 530.000 by the end of 2015, with 67.44% of the city's population was White ethnic groups and 26.83% Asian Ethnic Groups (UK population consensus). The majority of Asian population speaks Urdu, hence an Urdu speaking breast care nurse was appointed to facilitate communications and deliver a better understanding of the reconstruction options and pathways. Statistical analysis was undertaken using the SAS program. Patients were stratified by age, self-reported ethnicity, axillary surgery and reconstruction. Relative odds were calculated using univariate and multivariate logistic regression analyses with adjustment for known confounders. An Urdu speaking breast care nurse was employed throughout this period to facilitate communication and patient decision making. Results: 506 patients underwent Mastectomy over 5 years. 72 (14%) Asian v. 434 (85%) Caucasian. Overall median age is 64 years (SD1.1). Asian median age is 62 (SD0.9), versus Caucasian 65 (SD1.2). Total axillary clearance rate was 30% (42% Asian v.30% Caucasian). Overall reconstruction rate was 126 patients (28.9%).Only 6 of 72 Asian patients (<1%) underwent breast reconstruction versus 121of 434 Caucasian (28%) (p < 0.04), Odds ratio 0.68, (95% confidence interval 0.57-0.79). Conclusions: There is a significant difference in post-mastectomy reconstruction rates between Asian and Caucasian patients. This difference is likely to be multi-factorial. Higher rates of axillary clearance in Asian patients might suggest later disease presentation and/or higher rates of subsequent adjuvant therapy, both of which, can impact on the suitability of breast reconstruction. Strategies aimed at reducing racial disparities in breast reconstruction should include symptom awareness to enable earlier presentation and facilitated communication to ensure informed decision-making.

Keywords: aesthetic, Asian, breast, reconstruction

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Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

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Authors: Alba Ballester Ciuró, Marc Pares Franzi

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While coming decades are likely to see a higher flood risk in Europe and greater socio-economic damages, traditional flood risk management has become inefficient. In response to that, new approaches such as capacity building and public participation have recently been incorporated in natural hazards mitigation policy (i.e. Sendai Framework for Action, Intergovernmental Panel on Climate Change reports and EU Floods Directive). By integrating capacity building and public participation, we present a research concerning the promotion of participatory social capacity building actions for flood risk mitigation at the local level. Social capacities have been defined as the resources and abilities available at individual and collective level that can be used to anticipate, respond to, cope with, recover from and adapt to external stressors. Social capacity building is understood as a process of identifying communities’ social capacities and of applying collaborative strategies to improve them. This paper presents a proposal of systematization of participatory social capacity building process for flood risk mitigation, and its implementation in a high risk of flooding area in the Ebro river basin: Ribera Alta del Ebro. To develop this process, we designed and tested a tool that allows measuring and building five types of social capacities: knowledge, motivation, networks, participation and finance. The tool implementation has allowed us to assess social capacities in the area. Upon the results of the assessment we have developed a co-decision process with stakeholders and flood risk management authorities on which participatory activities could be employed to improve social capacities for flood risk mitigation. Based on the results of this process, and focused on the weaker social capacities, we developed a set of participatory actions in the area oriented to general public and stakeholders: informative sessions on flood risk management plan and flood insurances, interpretative river descents on flood risk management (with journalists, teachers, and general public), interpretative visit to the floodplain, workshop on agricultural insurance, deliberative workshop on project funding, deliberative workshops in schools on flood risk management (playing with a flood risk model). The combination of obtaining data through a mixed-methods approach of qualitative inquiry and quantitative surveys, as well as action research through co-decision processes and pilot participatory activities, show us the significant impact of public participation on social capacity building for flood risk mitigation and contributes to the understanding of which main factors intervene in this process.

Keywords: flood risk management, public participation, risk reduction, social capacities, vulnerability assessment

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Authors: Nithi Sermsiriviboon, Somchai Supattarakul

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Dividend initiations are an economically significant event that has important implications for a firm’s future financial capacity. Given that the market’s expectation of a consistent payout, managers of IPO firms must approach the initial dividend decision cautiously. We compare the long run performance of IPO firms that initiated dividends with those of similarly matched non-payers. We found that firms which initiated dividends perform significantly better up to three years after the initiation date. Moreover, we measure investor reactions by 2-day around dividend announcement date cumulative abnormal return. We evidence no statistically significant differences between cumulative abnormal returns (CAR) of IPO firms and cumulative abnormal returns of Non-IPO firms, indicating that investors do not respond to dividend announcement of IPO firms more than they do to the dividend announcement of Non-IPO firms.

Keywords: dividend, initial public offerings, long-run performance, finance

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

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Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

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Authors: Hugh Byrd, Steve Matthewnan

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The devastation of the city centre of Christchurch, New Zealand, after the 2010 and 2011 earthquakes presented an opportunity to rebuild infrastructure in a coordinated and efficient manner to allow for a city that was energy efficient, low carbon, resilient and provided both energy security and justice. The research described in this paper records the processes taken to attempt to rebuild the energy infrastructure. The story is one of political decisions overriding appropriate technology and ultimately is a lesson in how not to handle the implementation of post-disaster energy infrastructure. Lack of clarity in decision making by central government and then not pursuing consultant’s recommendations led to a scheme that was effectively abandoned in 2016 and described as ‘a total failure’. The paper records the critical events that occurred and explains why the proposed energy infrastructure was both politically and technologically inappropriate.

Keywords: energy infrastructure, policy and governance, post-disaster rebuilding

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Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

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This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

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Authors: Onder Yakut, Serdar Solak, Emine Dogru Bolat

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Measuring the Electrocardiogram (ECG) signal is an essential process for the diagnosis of the heart diseases. The ECG signal has the information of the degree of how much the heart performs its functions. In medical diagnosis and treatment systems, Decision Support Systems processing the ECG signal are being developed for the use of clinicians while medical examination. In this study, a modular wireless ECG (WECG) measuring and recording system using a single board computer and e-Health sensor platform is developed. In this designed modular system, after the ECG signal is taken from the body surface by the electrodes first, it is filtered and converted to digital form. Then, it is recorded to the health database using Wi-Fi communication technology. The real time access of the ECG data is provided through the internet utilizing the developed web interface.

Keywords: ECG, e-health sensor shield, Raspberry Pi, wiFi technology

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Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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Authors: Majid Mokhtarnia, Alireza Amini

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Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one.

Keywords: bundling, canvas business model, telecommunication, WiFi data offloading

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Authors: Marcio Emilio Dos Santos, Kelly C. F. Dos Santos

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Caregivers of patients diagnosed with ASD are subjected to high stress situations due to the complexity and multiple levels of daily activities that require the organization of events, behaviors and socioemotional situations, such as immediate decision making and in public spaces. The cognitive and emotional requirement needed to fulfill this caregiving role exceeds the regular cultural process that adults receive in their process of preparation for conjugal and parental life. Therefore, in many cases, caregivers present a high level of overload, poor capacity to organize and mediate the development process of the child or patient about their care. Aims: Improvement in the cognitive and emotional capacities related to the caregiver function, allowing the reduction of the overload, the feeling of incompetence and the characteristic level of stress, developing a more organized conduct and decision making more oriented towards the objectives and procedural gains necessary for the integral development of the patient with diagnosis of ASD. Method: The study was performed with 20 relatives, randomly selected from a total of 140 patients attended. The family members were submitted to the Wechsler Adult Intelligence Scale III intelligence test and the Family assessment Management Measure (FaMM) questionnaire as a previous evaluation. Therapeutic activity in a small group of family members or caregivers, with weekly frequency, with a minimum workload of two hours, using the Feuerstein Instrumental Enrichment Cognitive Development Program - Feuerstein Instrumental Enrichment for ten months. Reapplication of the previous tests to verify the gains obtained. Results and Discussion: There is a change in the level of caregiver overload, improvement in the results of the Family assessment Management Measure and highlight to the increase of performance in the cognitive aspects related to problem solving, planned behavior and management of behavioral crises. These results lead to the discussion of the need to invest in the integrated care of patients and their caregivers, mainly by enabling cognitively to deal with the complexity of Autism. This goes beyond the simple therapeutic orientation about adjustments in family and school routines. The study showed that when the caregiver improves his/her capacity of management, the results of the treatment are potentiated and there is a reduction of the level of the caregiver's overload. Importantly, the study was performed for only ten months and the number of family members attended in the study (n = 20) needs to be expanded to have statistical strength.

Keywords: caregiver overload, cognitive development program ASD caregivers, feuerstein instrumental enrichment, family assessment management measure

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Authors: Ivana Yuniarti, Iwan Ridwansyah

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This paper delivers a review of various methodologies for habitat assessment and a proposed methodology to assess an endemic fish species habitat in Lake Maninjau, Indonesia as a part of a Ph.D. project. This application is mainly aimed to assess the trade-off between the economic value of aquaculture and the fisheries. The proposed methodology is a generalized linear model (GLM) combined with GIS to assess presence-absence data or habitat suitability index (HSI) combined with the analytical hierarchy process (AHP). Further, a cost of habitat replacement approach is planned to be used to calculate the habitat value as well as its trade-off with the economic value of aquaculture. The result of the study is expected to be a scientific consideration in local decision making and to provide a reference for other areas in the country.

Keywords: AHP, habitat, GLM, HSI, Maninjau

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Authors: Daniela Pellin, Wilson Engelmann

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Brazil has sought to accelerate your development through technology and innovation as a response to the global influences, which has received in internal management practices. For this, it had edited the Brazilian Law of Innovation 13.243/2016. However observing the Law overestimated economic aspects the respective application will not consider the stakeholders and the technological risks because there is no legal treatment. The economic exploitation and the technological risks must be controlled by limits of democratic system to find better social development to contribute with the economics agents for making decision to conform with global directions. The research understands this is a problem to face given the social particularities of the country because there has been the literal import of the North American Triple Helix Theory consolidated in developed countries and the negative consequences when applied in developing countries. Because of this symptomatic scenario, it is necessary to create adjustment to conduct the management of the law besides social democratic interests to increase the country development. For this, therefore, the Government will have to adopt some conducts promoting side by side with universities, civil society and companies, informational transparency, catch of partnerships, create a Confort Letter document for preparation to ensure the operation, joint elaboration of a Manual of Good Practices, make accountability and data dissemination. Also the Universities must promote informational transparency, drawing up partnership contracts and generating revenue, development of information. In addition, the civil society must do data analysis about proposals received for discussing to give opinion related. At the end, companies have to give public and transparent information about investments and economic benefits, risks and innovation manufactured. The research intends as a general objective to demonstrate that the efficiency of the propeller deployment will be possible if the innovative decision-making process goes through the institutional logic. As specific objectives, the American influence must undergo some modifications to better suit the economic-legal incentives to potentiate the development of the social system. The hypothesis points to institutional model for application to the legal system can be elaborated based on emerging characteristics of the country, in such a way that technological risks can be foreseen and there will be global conformity with attention to the full development of society as proposed by the researchers.The method of approach will be the systemic-constructivist with bibliographical review, data collection and analysis with the construction of the institutional and democratic model for the management of the Law.

Keywords: development, governance of law, institutionalization, triple helix

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Authors: Ananda Perera

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Diet therapy has a positive impact on many diseases in General Practice. If a meal plan can be generated as easily as writing a drug prescription for dyspepsia, then the evidence and practice gap in nutrition therapy can be narrowed. Meal plans of 50 diet prescriptions were compared with the criteria for a healthy diet given by Australian authorities. The energy value of each meal plan was compared with the recommended daily energy requirements of the authorities for Diet Prescription Generator (DPG) accuracy. Meal plans generated were within the criteria laid down by the Australian authorities for a healthy diet.

Keywords: dieting, obesity, diabetes, weight loss, computerized decision support systems, dieting software, CDSS, meal plans

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Authors: Preeda Sansakorn, Min An

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In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: safety risk assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects

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Authors: Nabila Daly, Hamdi Ellouzi, Hela Ltifi

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In last year’s, several recent researches’ that focus on e-learning approaches having as goal to improve pedagogy and student’s academy level assessment. E-learning-related works have become an important research file nowadays due to several problems that make it impossible for students join classrooms, especially in last year’s. Among those problems, we note the current epidemic problems in the word case of Covid-19. For those reasons, several e-learning-related works based on Artificial Intelligence techniques are proposed to improve distant education targets. In the current paper, we will present a short survey of the most relevant e-learning based on Artificial Intelligence techniques giving birth to newly developed e-learning tools that rely on new technologies.

Keywords: artificial intelligence techniques, decision, e-learning, support system, survey

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Authors: Lien T. H. Tran, David A. Holloway

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Corporate governance practices have changed significantly across the world in the past three decades. Spectacular corporate failures during this period have acted as a catalyst for the development of codes and guidelines that have resulted in the global acceptance of a ‘best practice’ model. This study assesses the relevance of such a ‘one size fits all model’ for the developing nation state of Vietnam. The findings of this analytical paper is that there are three key elements (government, international institutions and the nature of business) that are pertinent and central to corporate governance developments in the country. We also find that the quality of corporate governance in Vietnam is at a medium level when compared to international practices. Vietnam still has a long way to go to construct and embed effective corporate governance policies and practices and promote ethical business behaviours and sound decision making at board level.

Keywords: corporate governance, government, international institutions, public companies, Vietnam

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Authors: Maryam Sheikhzadeh Noshabadi

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There is no doubt that the Internet has connected the entire world. As a result of this flexible environment, virtual businesses have grown in importance and become one of the most important types of businesses. Although many governments use the internet and have free access to it, some are not happy with the free space and wide accessibility. As a result of recent events and civil protests in Iran, the country's government leaders have decided to once again cut off and filter its free and global Internet. Several issues were impacted by this decision; this includes the lives of businesses that were formed in virtual spaces platform. In this study, we explored the definitive impact of the Internet in Iran in September 1401, using semi-structured interviews with 20 digital marketing activists. This group was discussed in detail in terms of their financial and psychological damages. As a result of these conditions, this group has experienced a crisis of livelihood.

Keywords: internet, Iran, filtering, digital marketing.

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Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

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The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

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Authors: Paul B Stone, Subhashini Ganapathy, Mary E. Fendley, Layla Akilan

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As notifications become more common through mobile devices, it is important to understand the impact of wearable devices on the improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer-simulated petrochemical system. The key research question was to determine how using the information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch, and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.

Keywords: computer applications, haptic feedback, petrochemical systems, situational awareness, wearable technology

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Authors: Siphethile Phiri

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Although a company is a legal entity with separate legal personality, the courts are empowered to review and set aside the personality of a company on the ground of ‘an unconscionable abuse’. The process is called piercing of the corporate veil. Of interesting note however, it is controversial as to what the concept of ‘unconscionable abuse’ entails. The purpose of this study is to explore this concept in an attempt to understand its proper meaning and how it bears on the powers of the company director to take decision on behalf of the company as a juristic entity. Given the confounding provision, an attempt is made to identify the circumstances in which the courts may pierce the corporate veil and also to investigate the extent to which the courts can do so. The results of this study show that the term unconscionable abuse is a legislative innovation to justify the court’s interference with the separate legal personality functions of a company.

Keywords: company law, unconscionable abuse, director, companies act

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

Procedia PDF Downloads 205

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

Abstract:

Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

Procedia PDF Downloads 36

Authors: Rajoo Balaji, Omar Yaakob

Abstract:

The Ballast Water Convention requires less than 5% of the world tonnage for ratification. Consequently, ships will have to comply with the requirements. Compliance evaluation and enforcement will become mandatory. Ship owners have to invest in treatment systems and shipboard personnel have to operate them and ensure compliance. The monitoring and enforcement will be the responsibilities of the Administrations. Herein, a review of the current status of the Ballast Water Management and the issues faced by these are projected. Issues range from efficacy and economics of the treatment systems to sampling and testing. Health issues of chemical systems, paucity of data for decision support etc., are other issues. It is emphasized that management of ballast water must be extended to ashore and sustainable solutions must be researched upon. An exemplar treatment system based on ship’s waste heat is also suggested.

Keywords: Ballast Water Management, compliance evaluation, compliance enforcement, sustainability

Procedia PDF Downloads 426

Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 170