Search results for: supervised decision tree

Authors: Oliveira M., Gonçalves L., Francisco I., Caramelo F., Vale F., Sanz D., Domingues M., Lopes M., Moreia D., Lopes T., Santos T., Cardoso H.

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The ARTHUR project consists of a platform that allows the virtual performance of maxillofacial surgeries, offering, in a photorealistic concept, the possibility for the patient to have an idea of the surgical changes before they are performed on their face. For this, the system brings together several image formats, dicoms and objs that, after loading, will generate the bone volume, soft tissues and hard tissues. The system also incorporates the patient's stereophotogrammetry, in addition to their data and clinical history. After loading and inserting data, the clinician can virtually perform the surgical operation and present the final result to the patient, generating a new facial surface that contemplates the changes made in the bone and tissues of the maxillary area. This tool acts in different situations that require facial reconstruction, however this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. Being developed a cloud based solution, with mobile support, the tool aims to reduce the decision time window of patient. Because the current simulations are not realistic or, if realistic, need time due to the need of building plaster models, patient rates on decision, rely on a long time window (1,2 months), because they don’t identify themselves with the presented surgical outcome. On the other hand, this planning was performed time based on average estimated values of the position of the maxilla and mandible. The team was based on averages of the facial measurements of the population, without specifying racial variability, so the proposed solution was not adjusted to the real individual physiognomic needs.

Keywords: 3D computing, image processing, image registry, image reconstruction

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

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Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

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Authors: Pilly Joseph Kagosi

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The study aims at assessing challenges observed during implementation of participatory irrigation management (PIM) approach for food security in semi-arid areas of Tanzania. Data were collected through questionnaire, PRA tools, key informants discussion, Focus Group Discussion (FGD), participant observation and literature review. Data collected from questionnaire was analyzed using SPSS while PRA data was analyzed with the help of local communities during PRA exercise. Data from other methods were analyzed using content analysis. The study revealed that PIM approach has contribution in improved food security at household level due to involvement of communities in water management activities and decision making which enhanced availability of water for irrigation and increased crop production. However there were challenges observed during implementation of the approach including; minimum participation of beneficiaries in decision making during planning and designing stages, meaning inadequate devolution of power among scheme owners; Inadequate and lack of transparency on income expenditure in Water Utilization Associations’ (WUAs), water conflict among WUAs members, conflict between farmers and livestock keepers and conflict between WUAs leaders and village government regarding training opportunities and status; WUAs rules and regulation are not legally recognized by the National court and few farmers involved in planting trees around water sources. However it was realized that some of the mentioned challenges were rectified by farmers themselves facilitated by government officials. The study recommends that, the identified challenges need to be rectified for farmers to realize impotence of PIM approach as it was realized by other Asian countries.

Keywords: potentials of implementing participatory approach, challenges of participatory approach, irrigation management, Tanzania

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Authors: Djeffal Asma, Zemmouri Noureddine

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In order for building designer to be able to balance environmental concerns with other performance requirements, they need clear and concise information. For certain decisions during the design process, qualitative guidance, such as design checklists or guidelines information may not be sufficient for evaluating the environmental benefits between different building materials, products and designs. In this case, quantitative information, such as that generated through a life cycle assessment, provides the most value. LCA provides a systematic approach to evaluating the environmental impacts of a product or system over its entire life. In the case of buildings life cycle includes the extraction of raw materials, manufacturing, transporting and installing building components or products, operating and maintaining the building. By integrating LCA into building design process, designers can evaluate the life cycle impacts of building design, materials, components and systems and choose the combinations that reduce the building life cycle environmental impact. This article attempts to give an overview of the integration of LCA methodology in the context of building design, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. A multiple case study was conducted in order to assess the benefits of the LCA as a decision making aid tool during the first stages of the building design under specific climate conditions of the North East region of Algeria. It is clear that the LCA methodology can help to assess and reduce the impact of a building design and components on the environment even if the process implementation is rather long and complicated and lacks of global approach including human factors. It is also demonstrated that using LCA as a multi objective optimization of building process will certainly facilitates the improvement in design and decision making for both new design and retrofit projects.

Keywords: life cycle assessment, buildings, sustainability, elementary schools, environmental impacts

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: J. Magerman, P. Martin

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Nursing students' clinical abilities is highly dependent on the quality of the clinical experience obtained while placed in the clinical environment. The clinical environment has amongst other, key role players which include the clinical supervisor. The primary role of the clinical supervisor is to guide nursing students to become the best practice nursing professionals. However, globally literature alludes to the failure of educating institutions to deliver competent nursing professionals to meet the needs of patients and deliver quality patient care. At the participating university, this may be due to various factors such as large student numbers and social and environmental challenges experienced by clinical supervisors. The aim of this study was to explore and describe the lived experiences of clinical supervisors who supervise nursing students at a higher education institution. The study employed a qualitative research approach utilizing a descriptive phenomenological design. Purposive sampling was used to select participants, who supervised first and second year nursing studnets at the higher education institution under study. TH esample comprised of eight clinical supervisors who supervise first and secon year nursing studnets at teh institution under study. Data was collected by means of in-depht interviews. Data was analysed using Collaizzi's seven steps method of qualitative analysis. Five major themes identified , focussed on the experiences regarding time a sa constraint to job productivity, the impact of teh organisational culture on the fluidity of support, interpersonal relationships a sa dynamic communication process, impact on the self, and limited resources. Trustworthiness of the data was ensured by means of applying Guba's model of truth value, applicability, consistency and neutrality. Reflexivity was also used by the researcher to further enhance trustworthiness.

Keywords: clinical supervision, clinical supervisors, nursing students, clinical placements

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Authors: Hritik Bhattarai, Vivek Dumre, Ananya Neupane, Poonam Koirala, Anjali Singh

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The availability of clean and reliable groundwater is essential for the sustainment of human and environmental health. Groundwater is a crucial resource that contributes significantly to the total annual supply. However, over-exploitation has depleted groundwater availability considerably and led to some land subsidence. Determining the potential zone of groundwater is vital for protecting water quality and managing groundwater systems. Groundwater potential zones are marked with the assistance of Geographic Information System techniques. During the study, a standard methodology was proposed to determine groundwater potential using an integration of GIS and AHP techniques. When choosing the prospective groundwater zone, accurate information was generated to get parameters such as geology, slope, soil, temperature, rainfall, drainage density, and lineament density. However, identifying and mapping potential groundwater zones remains challenging due to aquifer systems' complex and dynamic nature. Then, ArcGIS was incorporated with a weighted overlay, and appropriate ranks were assigned to each parameter group. Through data analysis, MCDA was applied to weigh and prioritize the different parameters based on their relative impact on groundwater potential. There were three probable groundwater zones: low potential, moderate potential, and high potential. Our analysis showed that the central and lower parts of the Bagmati River Basin have the highest potential, i.e., 7.20% of the total area. In contrast, the northern and eastern parts have lower potential. The identified potential zones can be used to guide future groundwater exploration and management strategies in the region.

Keywords: groundwater, geographic information system, analytic hierarchy processes, multi-criteria decision analysis, Bagmati

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Authors: Rishi Agarwal

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Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

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Authors: Amin Padash, Gholam Reza Nabi Bid Hendi, Hassan Hoveidi

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Purpose: The aim of this research is developing a model for green management based on Health, Safety and Environmental Management System. An HSE-MS can be a powerful tool for organizations to both improve their environmental, health and safety performance, and enhance their business efficiency to green management. Model: The model is developed in this study can be used for industries as guidelines for implementing green management issue by considering Health, Safety and Environmental Management System. Case Study: The Pars Special Economic / Energy Zone Organization on behalf of Iran’s Petroleum Ministry and National Iranian Oil Company (NIOC) manages and develops the South and North oil and gas fields in the region. Methodology: This research according to objective is applied and based on implementing is descriptive and also prescription. We used technique MCDM (Multiple Criteria Decision-Making) for determining the priorities of the factors. Based on process approach the model consists of the following steps and components: first factors involved in green issues are determined. Based on them a framework is considered. Then with using MCDM (Multiple Criteria Decision-Making) algorithms (TOPSIS) the priority of basic variables are determined. The authors believe that the proposed model and results of this research can aid industries managers to implement green subjects according to Health, Safety and Environmental Management System in a more efficient and effective manner. Finding and conclusion: Basic factors involved in green issues and their weights can be the main finding. Model and relation between factors are the other finding of this research. The case is considered Petrochemical Company for promoting the system of ecological industry thinking.

Keywords: Fuzzy-AHP method , green management, health, safety and environmental management system, MCDM technique, TOPSIS

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Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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Authors: Saied Farham-Nia, Alireza Ghaffari-Hadigheh

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Game theory is a mathematical tool to study the behaviors of a rational and strategic decision-makers, that analyze existing equilibrium in interest conflict situation and provides an appropriate mechanisms for cooperation between two or more player. Game theory is applicable for any strategic and interest conflict situation in politics, management and economics, sociology and etc. Real worlds’ decisions are usually made in the state of indeterminacy and the players often are lack of the information about the other players’ payoffs or even his own, which leads to the games in uncertain environments. When historical data for decision parameters distribution estimation is unavailable, we may have no choice but to use expertise belief degree, which represents the strength with that we believe the event will happen. To deal with belief degrees, we have use uncertainty theory which is introduced and developed by Liu based on normality, duality, subadditivity and product axioms to modeling personal belief degree. As we know, the personal belief degree heavily depends on the personal knowledge concerning the event and when personal knowledge changes, cause changes in the belief degree too. Uncertainty theory not only theoretically is self-consistent but also is the best among other theories for modeling belief degree on practical problem. In this attempt, we primarily reintroduced Expected Utility Function in uncertainty environment according to uncertainty theory axioms to extract payoffs. Then, we employed Nash Equilibrium to investigate the solutions. For more practical issues, Stackelberg leader-follower Game and Bertrand Game, as a benchmark models are discussed. Compared to existing articles in the similar topics, the game models and solution concepts introduced in this article can be a framework for problems in an uncertain competitive situation based on experienced expert’s belief degree.

Keywords: game theory, uncertainty theory, belief degree, uncertain expected value, Nash equilibrium

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Authors: Nsimbe Allan

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The study examines the impact of Building Information Modeling (BIM) on the cost management of engineering projects, focusing specifically on the Mombasa Port Area Development Project. The objective of this research venture is to determine the mechanisms through which Building Information Modeling (BIM) facilitates stakeholder collaboration, reduces construction-related expenses, and enhances the precision of cost estimation. Furthermore, the study investigates barriers to execution, assesses the impact on the project's transparency, and suggests approaches to maximize resource utilization. The study, selected for its practical significance and intricate nature, conducted a Systematic Literature Review (SLR) using credible databases, including ScienceDirect and IEEE Xplore. To constitute the diverse sample, 69 individuals, including project managers, cost estimators, and BIM administrators, were selected via stratified random sampling. The data were obtained using a mixed-methods approach, which prioritized ethical considerations. SPSS and Microsoft Excel were applied to the analysis. The research emphasizes the crucial role that project managers, architects, and engineers play in the decision-making process (47% of respondents). Furthermore, a significant improvement in cost estimation accuracy was reported by 70% of the participants. It was found that the implementation of BIM resulted in enhanced project visibility, which in turn optimized resource allocation and facilitated the process of budgeting. In brief, the study highlights the positive impacts of Building Information Modeling (BIM) on collaborative decision-making and cost estimation, addresses challenges related to implementation, and provides solutions for the efficient assimilation and understanding of BIM principles.

Keywords: cost management, resource utilization, stakeholder collaboration, project transparency

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Authors: Abiodun O. Ibude

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Several organizations have devised the strategy of engaging the services of staff not directly employed by them in their production and service delivery. Some organizations also engage on contracting another organization to carry out a part of service or production process on their behalf. Outsourcing is becoming an important alternative employment option for most organizations. This paper attempts an exposition on the rights of workers within the more specific context of outsourcing as a human resource management phenomenon. Outsourced employees and their rights are treated conceptually and analytically in a generic sense as a mere subset of the larger whole, that is, labor. Outsourced employees derive their rights, like all workers, from their job context as well as the legal environment (municipal and global) in which they operate. The dynamics of globalization and the implications of this development for labor practices receive considerable attention in this exposition. In this regard, a guarded proposition is made, to examine the practice and effect of engaging outsourcing as an economic decision designed primarily to cut down on operational costs rather than a Human Resources Management decision to improve worker welfare. The population of the study was selected from purposive and simple random sampling techniques. Data obtained were analyzed through a simple percentage, Pearson product-moment correlation, and cross-tabulation. From the research conducted, it was discovered that, although outsourcing possesses opportunities for organizations, there are drawbacks arising from its implementation of job securities. It was also discovered that some employees are being exploited through this strategy. This gives rise to lower motivation and thereby decline in performance. In conclusion, there is need for examination of Human Resource Managers’ strategies that can serve as management policy tools for the protection of the rights of outsourced employees.

Keywords: legal environment, operational cost, outsourcing, protection

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Authors: Silvija Šiljeg, Ivan Marić, Ante Šiljeg

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The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.

Keywords: urban green spaces (UGS), accessibility indicator, subjective and objective measurements, Zadar

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Malani Herath, Sohan Wijesekera, Jagath Munasingha

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The impact of recent floods become significant, and the extraordinary flood events cause considerable damage to lives, properties, environment and negatively affect the whole development of Colombo urban region. Even though the Colombo urban region experiences recurrent flood impacts, several spatial planning interventions have been taken from time to time since early 20th century. All past plans have adopted a traditional approach to flood management, using infrastructural measures to reduce the chance of flooding together with rigid planning regulations. The existing flood risk management practices do not operate to be acceptable by the local community particular the urban poor. Researchers have constantly reported the differences in estimations of flood risk, priorities, concerns of experts and the local community. Risk-based decision making in flood management is not only a matter of technical facts; it has a significant bearing on how flood risk is viewed by local community and individuals. Moreover, sustainable flood management is an integrated approach, which highlights joint actions of experts and community. This indicates the necessity of further societal discussion on the acceptable level of flood risk indicators to prioritize and identify the appropriate flood management measures in Colombo. The understanding and evaluation of flood risk by local people are important to integrate in the decision-making process. This research questioned about the gap between the acceptable level of flood risk to spatial planners and to the local communities in Colombo. A comprehensive literature review was conducted to prepare a framework to analyze the public perception in Colombo. This research work identifies the factors that affect the variation of flood risk and acceptable levels to both local community and planning authorities.

Keywords: Colombo basin, public perception, urban flood risk, multi-criteria analysis

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Authors: Elzbieta Sikorska-Simmons

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Advanced dementia is a progressive terminal brain disease that is accompanied by a syndrome of difficult to manage symptoms and complications that eventually lead to death. The management of advanced dementia poses major challenges to family caregivers who act as patient health care proxies in making medical treatment decisions. Little is known, however, about how they manage advanced dementia and how their treatment choices influence the quality of patient life. This prospective qualitative study examines the key medical treatment decisions that family caregivers make while managing advanced dementia. The term ‘family caregiver’ refers to a relative or a friend who is primarily responsible for managing patient’s medical care needs and legally authorized to give informed consent for medical treatments. Medical decision-making implies a process of choosing between treatment options in response to patient’s medical care needs (e.g., worsening comorbid conditions, pain, infections, acute medical events). Family caregivers engage in this process when they actively seek treatments or follow recommendations by healthcare professionals. Better understanding of medical decision-making from the family caregiver perspective is needed to design interventions that maximize the quality of patient life and limit inappropriate treatments. Data were collected in three waves of semi-structured interviews with 20 family caregivers for patients with advanced dementia. A purposive sample of 20 family caregivers was recruited from a senior care center in Central Florida. The qualitative personal interviews were conducted by the author in 4-5 months intervals. The ethical approval for the study was obtained prior to the data collection. Advanced dementia was operationalized as stage five or higher on the Global Deterioration Scale (GDS) (i.e., starting with the GDS score of five, patients are no longer able survive without assistance due to major cognitive and functional impairments). Information about patients’ GDS scores was obtained from the Center’s Medical Director, who had an in-depth knowledge of each patient’s health and medical treatment history. All interviews were audiotaped and transcribed verbatim. The qualitative data analysis was conducted to answer the following research questions: 1) what treatment decisions do family caregivers make while managing the symptoms of advanced dementia and 2) how do these treatment decisions influence the quality of patient life? To validate the results, the author asked each participating family caregiver if the summarized findings accurately captured his/her experiences. The identified medical decisions ranged from seeking specialist medical care to end-of-life care. The most common decisions were related to arranging medical appointments, medication management, seeking treatments for pain and other symptoms, nursing home placement, and accessing community-based healthcare services. The most challenging and consequential decisions were related to the management of acute complications, hospitalizations, and discontinuation of treatments. Decisions that had the greatest impact on the quality of patient life and survival were triggered by traumatic falls, worsening psychiatric symptoms, and aspiration pneumonia. The study findings have important implications for geriatric nurses in the context of patient/caregiver-centered dementia care. Innovative nursing approaches are needed to support family caregivers to effectively manage medical care needs of patients with advanced dementia.

Keywords: advanced dementia, family caregiver, medical decision-making, symptom management

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Authors: Lorenzo Buti

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This paper investigates the nature of democratic action through a critical reading of Claude Lefort’s notion of the democratic ‘regime’. Lefort provides one of the most innovative accounts of the essential features of a democratic regime. According to him, democracy is a political regime that acknowledges the indeterminacy of a society and stages it as a contestation between competing political actors. As such, democracy provides the symbolic markers of society’s openness towards the future. However, despite their democratic features, the recent decades in late capitalist societies attest to a sense of the future becoming fixed and predetermined. This suggests that Lefort’s conception of democracy harbours a misunderstanding of the character and experience of democratic action. This paper examines this underlying tension in Lefort’s work. It claims that Lefort underestimates how a democratic regime, next to its symbolic function, also takes a materially constituted form with its particular dynamics of power relations. Lefort’s systematic dismissal of this material dimension for democratic action can lead to the contemporary paradoxical situation where democracy’s symbolic markers are upheld (free elections, public debate, dynamic between government and opposition in parliament,…) but the room for political decision-making is constrained due to a myriad of material constraints (e.g., market pressures, institutional inertias). The paper draws out the implications for the notion of democratic action. Contra Lefort, it argues that democratic action necessarily targets the material conditions that impede the capacity for decision-making on the basis of equality and liberty. This analysis shapes our understanding of democratic action in two ways. First, democratic action takes an asymmetrical, insurgent form, as a contestation of material power relations from below. Second, it reveals an ambivalent position vis-à-vis the political regime: democratic action is symbolically made possible by the democratic dispositive, but it contests the constituted form that the democratic regime takes.

Keywords: Claude Lefort, democratic action, material constitution, political regime

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Authors: Daniel J. Glauber

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Knowledge transfer between personnel could benefit an organization’s improved competitive advantage in the marketplace from a strategic approach to knowledge management. The lack of information sharing between personnel could create knowledge transfer gaps while restricting the decision-making processes. Knowledge transfer between personnel can potentially improve information sharing based on an implemented knowledge management strategy. An organization’s capacity to gain more knowledge is aligned with the organization’s prior or existing captured knowledge. This case study attempted to understand the overall influence of a KMS within the corporate environment and knowledge exchange between personnel. The significance of this study was to help understand how organizations can improve the Return on Investment (ROI) of a knowledge management strategy within a knowledge-centric organization. A qualitative descriptive case study was the research design selected for this study. The lack of information sharing between personnel may create knowledge transfer gaps while restricting the decision-making processes. Developing a knowledge management strategy acceptable at all levels of the organization requires cooperation in support of a common organizational goal. Working with management and executive members to develop a protocol where knowledge transfer becomes a standard practice in multiple tiers of the organization. The knowledge transfer process could be measurable when focusing on specific elements of the organizational process, including personnel transition to help reduce time required understanding the job. The organization studied in this research acknowledged the need for improved knowledge management activities within the organization to help organize, retain, and distribute information throughout the workforce. Data produced from the study indicate three main themes including information management, organizational culture, and knowledge sharing within the workforce by the participants. These themes indicate a possible connection between an organizations KMS, the organizations culture, knowledge sharing, and knowledge transfer.

Keywords: knowledge transfer, management, knowledge management strategies, organizational learning, codification

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Authors: Gulnara Galeeva

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The Analytic Hierarchy Process is widely used in the economic and financial studies, including the formation of investment portfolios. In this study, a generalized method of obtaining a vector of priorities for the case with separate pairwise comparisons of the expert opinion being presented as a set of several equal evaluations on a ratio scale is examined. The author claims that this method allows solving an important and up-to-date problem of excluding vagueness and ambiguity of the expert opinion in the decision making theory. The study describes the authentic wide pairwise comparison matrix. Its application in the formation of the efficient investment portfolio of intangible assets of a small business enterprise with limited funding is considered. The proposed method has been successfully approbated on the practical example of a functioning dental clinic. The result of the study confirms that the wide pairwise comparison matrix can be used as a simple and reliable method for forming the enterprise investment policy. Moreover, a comparison between the method based on the wide pairwise comparison matrix and the classical analytic hierarchy process was conducted. The results of the comparative analysis confirm the correctness of the method based on the wide matrix. The application of a wide pairwise comparison matrix also allows to widely use the statistical methods of experimental data processing for obtaining the vector of priorities. A new method is available for simple users. Its application gives about the same accuracy result as that of the classical hierarchy process. Financial directors of small and medium business enterprises get an opportunity to solve the problem of companies’ investments without resorting to services of analytical agencies specializing in such studies.

Keywords: analytic hierarchy process, decision processes, investment portfolio, intangible assets

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Authors: Ozhan Simsek, Dicle Donmez, Burhanettin Imrak, Ahsen Isik Ozguven, Yildiz Aka Kacar

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Pomegranate (Punica granatum L.) is known to be one of the oldest edible fruit tree species, with a wide geographical global distribution. Fruits from the two defined varieties (Hicaznar and 33N26) were taken at intervals after pollination and fertilization at different sizes. Seed samples were used for transcriptome sequencing. Primary sequencing was produced by Illumina Hi-Seq™ 2000. Firstly, we had raw reads, and it was subjected to quality control (QC). Raw reads were filtered into clean reads and aligned to the reference sequences. De novo analysis was performed to detect genes expressed in seeds of pomegranate varieties. We performed downstream analysis to determine differentially expressed genes. We generated about 27.09 gb bases in total after Illumina Hi-Seq sequencing. All samples were assembled together, we got 59,264 Unigenes, the total length, average length, N50, and GC content of Unigenes are 84.547.276 bp, 1.426 bp, 2,137 bp, and 46.20 %, respectively. Unigenes were annotated with 7 functional databases, finally, 42.681(NR: 72.02%), 39.660 (NT: 66.92%), 30.790 (Swissprot: 51.95%), 20.212 (COG: 34.11%), 27.689 (KEGG: 46.72%), 12.328 (GO: 20.80%), and 33,833 (Interpro: 57.09%) Unigenes were annotated. With functional annotation results, we detected 42.376 CDS, and 4.999 SSR distribute on 16.143 Unigenes.

Keywords: next generation sequencing, SSR, RNA-Seq, Illumina

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Lisete Barlach, Guilherme Ary Plonski

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Innovative ideas are not always synonymous with business opportunities. Any idea can be creative and not recognized as a potential project in which money and time will be invested, among other resources. Even in firms that promote and enhance innovation, there are two 'check-points', the first corresponding to the acknowledgment of the idea as creative and the second, its consideration as a business opportunity. Both the recognition of new business opportunities or new ideas involve cognitive and psychological frameworks which provide individuals with a basis for noticing connections between seemingly independent events or trends as if they were 'connecting the dots'. It also involves prototypes-representing the most typical member of a certain category–functioning as 'templates' for this recognition. There is a general assumption that these kinds of evaluation processes develop through experience, explaining why expertise plays a central role in this process: the more experienced a professional, the easier for him (her) to identify new opportunities in business. But, paradoxically, an increase in expertise can lead to the inflexibility of thought due to automation of procedures. And, besides this, other cognitive biases can also be present, because new ideas or business opportunities generally depend on heuristics, rather than on established algorithms. The paper presents a literature review about the Einstellung effect by tracking famous cases of rejected ideas, extracted from historical records. It also presents the results of empirical research, with data upon rejected ideas gathered from two different environments: projects rejected during first semester of 2017 at a large incubator center in Sao Paulo and ideas proposed by employees that were rejected by a well-known business company, at its Brazilian headquarter. There is an implicit assumption that Einstellung effect tends to be more and more present in contemporaneity, due to time pressure upon decision-making and idea generation process. The analysis discusses desirability, viability, and feasibility as elements that affect decision-making.

Keywords: cognitive biases, Einstellung effect, recognition of business opportunities, rejected ideas

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Authors: Chaghoub Soraya, Zhang Xiaoyan

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This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.

Keywords: approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median

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Authors: L. Salomon, P. Sklenar

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The Andes hold the highest plant species diversity in the world. How this occurred is one of the most intriguing questions in studies addressing the origin and patterning of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as triggers to this spectacular diversity. The Andes is the species-richest area for the biggest genus from the Asteraceae family: Senecio. There, the genus presents an incredible diversity of species, striking growth form variation, and large niche span. Even when some studies tried to disentangle the evolutionary story for some Andean species in Senecio, they obtained partially resolved and low supported phylogenies, as expected for recently radiated groups. The high-throughput sequencing (HTS) approaches have proved to be a powerful tool answering phylogenetic questions in those groups whose evolutionary stories are recent and traditional techniques like Sanger sequencing are not informative enough. Although these tools have been used to understand the evolution of an increasing number of Andean groups, nowadays, their scope has not been applied for Senecio. This project aims to contribute to a better knowledge of the mechanisms shaping the hyper diversity of Senecio in the Andean region, using HTS focusing on Senecio ser. Culcitium (Asteraceae), recently recircumscribed. Firstly, reconstructing a highly resolved and supported phylogeny, and after assessing the role of allopatric differentiation, hybridization, and genome duplication in the diversification of the group. Using the Hyb-Seq approach, combining target enrichment using Asteraceae COS loci baits and genome skimming, more than 100 new accessions were generated. HybPhyloMaker and HybPiper pipelines were used for the phylogenetic analyses, and another pipeline in development (Paralogue Wizard) was used to deal with paralogues. RAxML was used to generate gene trees and Astral for species tree reconstruction. Phyparts were used to explore as first step of gene tree discordance along the clades. Fully resolved with moderated supported trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within the group, some species formed well-supported clades with morphologically related species, while some species would not have exclusive ancestry, in concordance with previous studies using amplified fragment length polymorphism (AFLP) showing geographical differentiation. Discordance between gene trees was detected. Paralogues were detected for many loci, indicating possible genome duplications; ploidy level estimation using flow cytometry will be carried out during the next months in order to identify the role of this process in the diversification of the group. Likewise, TreeSetViz package for Mesquite, hierarchical likelihood ratio congruence test using Concaterpillar, and Procrustean Approach to Cophylogeny (PACo), will be used to evaluate the congruence among different inheritance patterns. In order to evaluate the influence of hybridization and Incomplete Lineage Sorting (ILS) in each resultant clade from the phylogeny, Joly et al.'s 2009 method in a coalescent scenario and Paterson’s D-statistic will be performed. Even when the main discordance sources between gene trees were not explored in detail yet, the data show that at least to some degree, processes such as genome duplication, hybridization, and/or ILS could be involved in the evolution of the group.

Keywords: adaptive radiations, Andes, genome duplication, hybridization, Senecio

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.

Keywords: defense/attack strategies, information, networks, reliability, survivability

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Authors: Som Pal Baliyan

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The purpose of this quantitative study was to analyze farm management skills in broiler poultryproducers in Botswana. The study adopted a descriptive and correlation research design. The population of the study was the poultry farm operators who had been in broiler poultry farming at least for two years. Based on the information from literature, a questionnaire was constructed for data collection on seven areas of farm management skills namely; planning skills, accounting and financial management skills, production management skills, product procurement and marketing skills, decision making skills, risk management skills, and specific technical skills. The validity and reliability of the questionnaire were accomplished by a panel of experts and by calculating the Cronbach’s alpha coefficient, respectively. Data were collected through a survey of 60 randomly sampled poultry farm operators in Botswana. Data were analyzed through descriptive statistical tools whereby the level of farm management skills were determined by calculating means and standard deviations of the management skills among the broiler producers. The level of farm management skills in broilers producers was discussed. All the seven farm management skills were ranked based on their calculated means. The specific technical skills and risk management skills were the highest and the lowest ranked farm management skills, respectively.Findings revealed that the broiler producers had skills above the average level only in specific technical skills whereas the skill levels in the remaining six farm management skills under study were found below the average level. This prevailing low level of farm management skills can be justified asthe cause of failure or poor performance of the broiler poultry farms in Botswana. Therefore, in order to improve the efficiency and productivityin broiler production in the country, it was recommended that the broiler poultry producers should be adequately trained in areas of planning skills, financial management skills, production management skills, product procurement and marketing skills, decision making skills and risk management skills.

Keywords: poultry production, broiler production, management skills, levels of skills

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Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

Procedia PDF Downloads 138