Search results for: probabilistic decision making

Authors: B. Chemali, B. Tiliouine

Abstract:

This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: Correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1804

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

Abstract:

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

Keywords: Automation, hydroponics, internet of things, monitoring system, urban farming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1806

Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

Abstract:

PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2678

Authors: A. Zanaz, S. Yotte, F. Fouchal, A. Chateauneuf

Abstract:

This paper presents a methodology for probabilistic assessment of bearing capacity and prediction of failure mechanism of masonry vaults at the ultimate state with consideration of the natural variability of Young’s modulus of stones. First, the computation model is explained. The failure mode corresponds to the four-hinge mechanism. Based on this consideration, the study of a vault composed of 16 segments is presented. The Young’s modulus of the segments is considered as random variable defined by a mean value and a coefficient of variation. A relationship linking the vault bearing capacity to the voussoirs modulus variation is proposed. The most probable failure mechanisms, in addition to that observed in the deterministic case, are identified for each variability level as well as their probability of occurrence. The results show that the mechanism observed in the deterministic case has decreasing probability of occurrence in terms of variability, while the number of other mechanisms and their probability of occurrence increases with the coefficient of variation of Young’s modulus. This means that if a significant change in the Young’s modulus of the segments is proven, taking it into account in computations becomes mandatory, both for determining the vault bearing capacity and for predicting its failure mechanism.

Keywords: Masonry, mechanism, probability, variability, vault.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1982

Authors: Miguel A. Gómez , Enrique Hilario , Francisco J. Alvarez , Elena Gastiasoro , Antonia Alvarez, Juan L. Larrabe

Abstract:

Total liquid ventilation can support gas exchange in animal models of lung injury. Clinical application awaits further technical improvements and performance verification. Our aim was to develop a liquid ventilator, able to deliver accurate tidal volumes, and a computerized system for measuring lung mechanics. The computer-assisted, piston-driven respirator controlled ventilatory parameters that were displayed and modified on a real-time basis. Pressure and temperature transducers along with a lineal displacement controller provided the necessary signals to calculate lung mechanics. Ten newborn lambs (<6 days old) with respiratory failure induced by lung lavage, were monitored using the system. Electromechanical, hydraulic and data acquisition/analysis components of the ventilator were developed and tested in animals with respiratory failure. All pulmonary signals were collected synchronized in time, displayed in real-time, and archived on digital media. The total mean error (due to transducers, A/D conversion, amplifiers, etc.) was less than 5% compared to calibrated signals. Improvements in gas exchange and lung mechanics were observed during liquid ventilation, without impairment of cardiovascular profiles. The total liquid ventilator maintained accurate control of tidal volumes and the sequencing of inspiration/expiration. The computerized system demonstrated its ability to monitor in vivo lung mechanics, providing valuable data for early decision-making.

Keywords: immature lamb, perfluorocarbon, pressure-limited, total liquid ventilation, ventilator; volume-controlled

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509

Authors: S. Halofaki, D. R. Seenivasagam, P. Bijay, K. Singh, R. Ananthanarayanan

Abstract:

This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.

Keywords: Literature review, productivity, small and medium-sized enterprises, SMEs, work system design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46

Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

Abstract:

Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1591

Authors: G. Martino, F. Silva, E. Marchal

Abstract:

The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: Clusterization and classification algorithms, integrated planning, optimization, mathematical modeling, penalty minimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 614

Authors: Dennys Robson Girardi, Hugo Bulegon, Claudia Maria Moro Barra

Abstract:

Leprosy is an infectious disease caused by Mycobacterium Leprae, this disease, generally, compromises the neural fibers, leading to the development of disability. Disabilities are changes that limit daily activities or social life of a normal individual. When comes to leprosy, the study of disability considered the functional limitation (physical disabilities), the limitation of activity and social participation, which are measured respectively by the scales: EHF, SALSA and PARTICIPATION SCALE. The objective of this work is to propose an on-line monitoring of leprosy patients, which is based on information scales EHF, SALSA and PARTICIPATION SCALE. It is expected that the proposed system is applied in monitoring the patient during treatment and after healing therapy of the disease. The correlations that the system is between the scales create a variety of information, presented the state of the patient and full of changes or reductions in disability. The system provides reports with information from each of the scales and the relationships that exist between them. This way, health professionals, with access to patient information, can intervene with techniques for the Prevention of Disability. Through the automated scale, the system shows the level of the patient and allows the patient, or the responsible, to take a preventive measure. With an online system, it is possible take the assessments and monitor patients from anywhere.

Keywords: Leprosy, Medical Informatics, Decision SupportSystem, Disability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2024

Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Abstract:

Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, KL divergence, quickest change detection, time series data.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 968

Authors: D. Kliaugaitė, J. K, Staniškis

Abstract:

In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE).

All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging.

Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH.

The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: Polymer packaging, life cycle assessment, resource efficiency.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4452

Authors: F. Fabeil Noor, Roslinah Mahmud, Janice L. H. Nga, Rasid Mail

Abstract:

In Malaysia, particularly in Sabah, the government has been promoting entrepreneurship among rural people to encourage them to earn their living by making good use of the diverse natural resources and local cultures of Sabah. Nevertheless, despite the government’s aim to encourage more local community in rural area to involve in entrepreneurship, the involvement of community in entrepreneurial activity is still low. It is crucial to identify the factors stimulate (or prevent) the involvement of rural community in Sabah in entrepreneurial activity. Therefore, this study tries to investigate the personal and contextual factors that may have impact on decision to start a business among the local community in Mantanani Island. In addition, this study also aims to identify the perceived benefits they receive from entrepreneurial activity. A structured face-to-face interview was conducted with 61 local communities in Mantanani Island. Data analysis revealed that passion, personal skills and self-confidence are the significant internal factors to entrepreneurial activity, whereas access to finance, labour and infrastructure are the significant external factors that are found to influence entrepreneurship. In terms of perceived rewards they received from taking up small business, it was found that respondents are predominantly agreed that entrepreneurship offers financial benefit than non-financial. In addition, this study also offers several suggestions for entrepreneurship development in Mantanani Island and it is hoped that this study may help the related agency to develop effective support policies in order to encourage more people in rural area to involve in entrepreneurship.

Keywords: Entrepreneurship, motivation, perceived rewards, rural community.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1242

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

Abstract:

Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 213

Authors: Parikshit Dutta, Mathieu Saujot, Elise Arnaud, Benoit Lefevre, Emmanuel Prados

Abstract:

In this work, propagation of uncertainty during calibration process of TRANUS, an integrated land use and transport model (ILUTM), has been investigated. It has also been examined, through a sensitivity analysis, which input parameters affect the variation of the outputs the most. Moreover, a probabilistic verification methodology of calibration process, which equates the observed and calculated production, has been proposed. The model chosen as an application is the model of the city of Grenoble, France. For sensitivity analysis and uncertainty propagation, Monte Carlo method was employed, and a statistical hypothesis test was used for verification. The parameters of the induced demand function in TRANUS, were assumed as uncertain in the present case. It was found that, if during calibration, TRANUS converges, then with a high probability the calibration process is verified. Moreover, a weak correlation was found between the inputs and the outputs of the calibration process. The total effect of the inputs on outputs was investigated, and the output variation was found to be dictated by only a few input parameters.

Keywords: Uncertainty propagation, sensitivity analysis, calibration under uncertainty, hypothesis testing, integrated land use and transport models, TRANUS, Grenoble.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1502

Authors: D. Tedesco, G. Feletti, P. Trucco

Abstract:

The present study aims to develop a Decision Support System (DSS) to support operational decisions in Emergency Medical Service (EMS) systems regarding the assignment of medical emergency requests to Emergency Departments (ED). This problem is called “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of a first phase of review of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a mission. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the travelling time and to free-up the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs also considering the expected time performance in the subsequent phases of the process, such as the case mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to compare different hospital selection policies. The model was implemented with the AnyLogic software and finally validated on a realistic case. The hospital selection policy that returned the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, based on a retrospective estimation of the TTP, and a dynamic approach, focused on a predictive estimation of the TTP which is determined with a constantly updated Winters forecasting model. Findings reveal that considering the minimization of TTP is the best hospital selection policy. It allows to significantly reducing service throughput times in the ED with a negligible increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms on TTP estimation, than a retrospective approach. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: Emergency medical services, hospital selection, discrete event simulation, forecast model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 188

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

Abstract:

In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary design optimisation, rule based architecture, aircraft design, decision support system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1034

Authors: Parvinder S. Sandhu, Hardeep Singh

Abstract:

The requirement to improve software productivity has promoted the research on software metric technology. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. CK metric suit is most widely used metrics for the objectoriented (OO) software; we critically analyzed the CK metrics, tried to remove the inconsistencies and devised the framework of metrics to obtain the structural analysis of OO-based software components. Neural network can learn new relationships with new input data and can be used to refine fuzzy rules to create fuzzy adaptive system. Hence, Neuro-fuzzy inference engine can be used to evaluate the reusability of OO-based component using its structural attributes as inputs. In this paper, an algorithm has been proposed in which the inputs can be given to Neuro-fuzzy system in form of tuned WMC, DIT, NOC, CBO , LCOM values of the OO software component and output can be obtained in terms of reusability. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: CK-Metric, ID3, Neuro-fuzzy, Reusability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1799

Authors: Kevin Fong-Rey Liu, Ken Yeh, Cheng-Wu Chen, Han-Hsi Liang

Abstract:

The sanitary sewerage connection rate becomes an important indicator of advanced cities. Following the construction of sanitary sewerages, the maintenance and management systems are required for keeping pipelines and facilities functioning well. These maintenance tasks often require sewer workers to enter the manholes and the pipelines, which are confined spaces short of natural ventilation and full of hazardous substances. Working in sewers could be easily exposed to a risk of adverse health effects. This paper proposes the use of Bayesian belief networks (BBN) as a higher level of noncarcinogenic health risk assessment of sewer workers. On the basis of the epidemiological studies, the actual hospital attendance records and expert experiences, the BBN is capable of capturing the probabilistic relationships between the hazardous substances in sewers and their adverse health effects, and accordingly inferring the morbidity and mortality of the adverse health effects. The provision of the morbidity and mortality rates of the related diseases is more informative and can alleviate the drawbacks of conventional methods.

Keywords: Bayesian belief networks, sanitary sewerage, healthrisk assessment, hazard quotient, target organ-specific hazard index.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1683

Authors: Inaki Maulida Hakim, Alesandro Romero

Abstract:

This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck has efficiency with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost and increase the average of the truck efficiency per day.

Keywords: Logistic cost, milkrun, simulation, efficiency.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1725

Authors: Mehmet Altınöz

Abstract:

Organizational communication is an administrative function crucial especially for executives in the implementation of organizational and administrative functions. Executives spend a significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or fulfilling the control functions within the organization, an executive typically engages in communication processes. Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For this purpose, management needs to specify the kind of communication system to be set up and the kind of communication devices to be used. Communication is vital for any organization. In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as face-to-face or telephone interaction. Communication in virtual as well as conventional offices is essential for obtaining the right information in administrative activities and decision-making. Virtual communication technologies increase the efficiency of communication especially in virtual teams. Group communication is strengthened through an inter-group central channel. Further, ease of information transmission makes it possible to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different environments. At present, virtual work has become a reality with its pros and cons, and will probably spread very rapidly in coming years, in line with the growth in information technologies.

Keywords: Organization, conventional office, virtual office, communication, communication model, communication functions, communication methods, vertical communication, linear communication, diagonal communication

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3129

Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1223

Authors: Siphiwe P. Mandina, Tinashe Shamuyashe

Abstract:

Tourism has become a topical issue amongst academics and practitioners due to its potential to contribute significantly towards an economy’s GDP. The problem underpinning this research is the fact that the major attraction, Victoria Falls, is being marketed in neighboring countries like South Africa, Botswana and Zambia with tour operators providing just day trips to the Victoria Falls. This has deprived Zimbabwe of income from tourism with tourists making day trips and actually not spending nights in Zimbabwe. This therefore calls for cutting edge marketing strategies that are superior to or inimitable by competing nations such as South Africa and Zambia. This study proposes a shift towards an experience management paradigm in the tourism sector. A qualitative research was adopted for this study, and findings of this study were generalized across different tourism contexts, therefore making the survey based research design more appropriate. The target population for this study is tourists visiting Zimbabwe over the period 2016 and ZTA visitor database acquired from the Department of Immigration will form the sampling frame for the purposes of this study.

Keywords: Competitiveness, tourist arrivals, tourist experience, Zimbabwe.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1077

Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

Abstract:

Events discrimination and decision maker in sport field are the subject of many interesting studies in computer vision and artificial intelligence. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. Indeed the results of these researches have a very significant contribution, as well to television broadcasts as to the football teams, since the result of sporting event can be reflected on the economic field. In this paper, we propose a novel fuzzy sequential technique which lead to discriminate events and specify the technico-tactics on going the game, nor the fuzzy system or the sequential one, may be able to respond to the asked question, in fact fuzzy process is not sufficient, it does not respect the chronological order according the time of various events, similarly the sequential process needs flexibility about the parameters used in this study, it may affect a membership degree of each parameter on the one hand and respect the sequencing of events for each frame on the other hand. Indeed this technique describes special events such as dribbling, headings, short sprints, rapid acceleration or deceleration, turning, jumping, kicking, ball occupation, and tackling according velocity vectors of the two players and the ball direction.

Keywords: Sequential process, Event detection, Soccer videos analysis, Fuzzy process, Spatio-temporal parameters.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1860

Authors: Ion Baş, Claudiu Zoicaş, Angela Ioniţâ

Abstract:

In most of the cases, natural disasters lead to the necessity of evacuating people. The quality of evacuation management is dramatically improved by the use of information provided by decision support systems, which become indispensable in case of large scale evacuation operations. This paper presents a best practice case study. In November 2007, officers from the Emergency Situations Inspectorate “Crisana" of Bihor County from Romania participated to a cross-border evacuation exercise, when 700 people have been evacuated from Netherlands to Belgium. One of the main objectives of the exercise was the test of four different decision support systems. Afterwards, based on that experience, software system called TEVAC (Trans Border Evacuation) has been developed “in house" by the experts of this institution. This original software system was successfully tested in September 2008, during the deployment of the international exercise EU-HUROMEX 2008, the scenario involving real evacuation of 200 persons from Hungary to Romania. Based on the lessons learned and results, starting from April 2009, the TEVAC software is used by all Emergency Situations Inspectorates all over Romania.

Keywords: Emergency evacuation, Searching Features, TEVAC(Trans Border Evacuation) software system, User Interface Design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1562

Authors: Marilena Ianculescu, Adriana Alexandru

Abstract:

Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: Health management, Internet of Health Things, remote monitoring, senior patient.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 612

Authors: Omolola A. Tajelawi, Hari L. Garbharran

Abstract:

Revenue leakages are one of the major challenges manufacturers face in production processes, as most of the input materials that should emanate as products from the lines are lost as waste. Rather than generating income from material input which is meant to end-up as products, losses are further incurred as costs in order to manage waste generated. In addition, due to the lack of a clear view of the flow of resources on the lines from input to output stage, acquiring information on the true cost of waste generated have become a challenge. This has therefore given birth to the conceptualization and implementation of waste minimization strategies by several manufacturing industries. This paper reviews the principles and applications of three environmental management accounting tools namely Activity-based Costing (ABC), Life-Cycle Assessment (LCA) and Material Flow Cost Accounting (MFCA) in the manufacturing industry and their effectiveness in curbing revenue leakages. The paper unveils the strengths and limitations of each of the tools; beaming a searchlight on the tool that could allow for optimal resource utilization, transparency in production process as well as improved cost efficiency. Findings from this review reveal that MFCA may offer superior advantages with regards to the provision of more detailed information (both in physical and monetary terms) on the flow of material inputs throughout the production process compared to the other environmental accounting tools. This paper therefore makes a case for the adoption of MFCA as a viable technique for the identification and reduction of waste in production processes, and also for effective decision making by production managers, financial advisors and other relevant stakeholders.

Keywords: MFCA, environmental management accounting, resource efficiency, waste reduction, revenue losses.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4341

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2142

Authors: Amirali Shirazibeheshti, Tarik Radwan, Alireza Ettefaghian, Farbod Khanizadeh, George Wilson, Cristina Luca

Abstract:

Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.

Keywords: Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1031

Authors: Roy R. Gu, Mahesh Sahu, Xianggui Zhao

Abstract:

Contour filter strips planted with perennial vegetation can be used to improve surface and ground water quality by reducing pollutant, such as NO3-N, and sediment outflow from cropland to a river or lake. Meanwhile, the filter strips of perennial grass with biofuel potentials also have economic benefits of producing ethanol. In this study, The Soil and Water Assessment Tool (SWAT) model was applied to the Walnut Creek Watershed to examine the effectiveness of contour strips in reducing NO3-N outflows from crop fields to the river or lake. Required input data include watershed topography, slope, soil type, land-use, management practices in the watershed and climate parameters (precipitation, maximum/minimum air temperature, solar radiation, wind speed and relative humidity). Numerical experiments were conducted to identify potential subbasins in the watershed that have high water quality impact, and to examine the effects of strip size and location on NO3-N reduction in the subbasins under various meteorological conditions (dry, average and wet). Variable sizes of contour strips (10%, 20%, 30% and 50%, respectively, of a subbasin area) planted with perennial switchgrass were selected for simulating the effects of strip size and location on stream water quality. Simulation results showed that a filter strip having 10%-50% of the subbasin area could lead to 55%- 90% NO3-N reduction in the subbasin during an average rainfall year. Strips occupying 10-20% of the subbasin area were found to be more efficient in reducing NO3-N when placed along the contour than that when placed along the river. The results of this study can assist in cost-benefit analysis and decision-making in best water resources management practices for environmental protection.

Keywords: modeling, SWAT, water quality, NO3-N, watershed.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1713

Authors: Miguel A. Gómez, Enrique Hilario, Francisco J. Alvarez, Elena Gastiasoro, Antonia Alvarez, Jose A. Casla, Jorge Arguinchona, Juan L. Larrabe

Abstract:

Total liquid ventilation can support gas exchange in animal models of lung injury. Clinical application awaits further technical improvements and performance verification. Our aim was to develop a liquid ventilator, able to deliver accurate tidal volumes, and a computerized system for measuring lung mechanics. The computer-assisted, piston-driven respirator controlled ventilatory parameters that were displayed and modified on a real-time basis. Pressure and temperature transducers along with a lineal displacement controller provided the necessary signals to calculate lung mechanics. Ten newborn lambs (<6 days old) with respiratory failure induced by lung lavage, were monitored using the system. Electromechanical, hydraulic and data acquisition/analysis components of the ventilator were developed and tested in animals with respiratory failure. All pulmonary signals were collected synchronized in time, displayed in real-time, and archived on digital media. The total mean error (due to transducers, A/D conversion, amplifiers, etc.) was less than 5% compared to calibrated signals. Improvements in gas exchange and lung mechanics were observed during liquid ventilation, without impairment of cardiovascular profiles. The total liquid ventilator maintained accurate control of tidal volumes and the sequencing of inspiration/expiration. The computerized system demonstrated its ability to monitor in vivo lung mechanics, providing valuable data for early decision-making.

Keywords: Immature lamb, perfluorocarbon, pressure-limited, total liquid ventilation, ventilator, volume-controlled.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1777