Search results for: value stream management (VSM) 4.0

Authors: T. Botelho de Sousa, F. Raphael Cabral Furtado, O. Eduardo da Silva Ferri, A. Batista, W. Augusto Varella, C. Eduardo Pinto, J. Mimar Santa Cruz Yabarrena, S. Gibran Ruwer, F. Müller Guerrini, L. Adalberto Philippsen Júnior

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Lean Supply Chain Management (LSCM) is an emerging research field in Operations Management (OM). As a strategic model that focuses on reduced cost and waste with fulfilling the needs of customers, LSCM attracts great interest among researchers and practitioners. The purpose of this paper is to present an overview of Lean Supply Chains literature, based on bibliometric analysis through 57 papers published in indexed journals by SCOPUS and/or Web of Science databases. The results indicate that the last three years (2015, 2016, and 2017) were the most productive on LSCM discussion, especially in Supply Chain Management and International Journal of Lean Six Sigma journals. India, USA, and UK are the most productive countries; nevertheless, cross-country studies by collaboration among researchers were detected, by social network analysis, as a research practice, appearing to play a more important role on LSCM studies. Despite existing limitation, such as limited indexed journal database, bibliometric analysis helps to enlighten ongoing efforts on LSCM researches, including most used technical procedures and collaboration network, showing important research gaps, especially, for development countries researchers.

Keywords: Lean Supply Chains, Bibliometric Study, SCOPUS, Web of Science

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Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

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Authors: Maariyah Irfan

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Intro: Current cardiovascular (CV) care faces challenges such as low budgets and high hospital admission rates. This review aims to evaluate Big Data in CV healthcare management through the use of wearable devices in atrial fibrillation (AF) detection. AF may present intermittently, thus it is difficult for a healthcare professional to capture and diagnose a symptomatic rhythm. Methods: The iRhythm ZioPatch, AliveCor portable electrocardiogram (ECG), and Apple Watch were chosen for review due to their involvement in controlled clinical trials, and their integration with smartphones. The cost-effectiveness and AF detection of these devices were compared against the 12-lead ambulatory ECG (Holter monitor) that the NHS currently employs for the detection of AF. Results: The Zio patch was found to detect more arrhythmic events than the Holter monitor over a 2-week period. When patients presented to the emergency department with palpitations, AliveCor portable ECGs detected 6-fold more symptomatic events compared to the standard care group over 3-months. Based off preliminary results from the Apple Heart Study, only 0.5% of participants received irregular pulse notifications from the Apple Watch. Discussion: The Zio Patch and AliveCor devices have promising potential to be implemented into the standard duty of care offered by the NHS as they compare well to current routine measures. Nonetheless, companies must address the discrepancy between their target population and current consumers as those that could benefit the most from the innovation may be left out due to cost and access.

Keywords: atrial fibrillation, big data, cardiovascular healthcare management, wearable devices

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Authors: T. Spiegel, J. Siegmann, C. F. Durach

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Challenges resulting from an international and dynamic business environment are increasingly being passed on from manufacturing companies to external service providers. Especially providers of complex, customer-specific industry services have to cope with continuously changing requirements. This is particularly true for contract logistics service providers. They are forced to develop efficient and highly flexible structures and strategies to meet their customer’s needs. One core element they have to focus on is the reorganization of their service development and sales process. Based on an action research approach, this study develops and tests a concept to streamline tender management for contract logistics service providers. The concept of modularized service architecture is deployed in order to derive a practice-oriented approach for the modularization of complex service portfolios and the design of customized quotes. These findings are evaluated regarding their applicability in other service sectors and practical recommendations are given.

Keywords: contract logistics, modularization, service development, tender management

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Gursimran Jandu, Melissa Nelson, Mia Ingram, Hana Jalal

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There is a significant overlap between autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD), with up to 90% of young people diagnosed with ASD having this co-morbidity. Distinguishing between the symptoms of the two leads to issues with accurate treatment, yet this is paramount in benefiting the young person. There are two distinct methods of treatment, psychological or pharmacological, with clinicians tending to choose one or the other, potentially due to the lack of research available. This report reviews the efficacy of psychological and pharmacological treatments for young people diagnosed with ASD and co-morbid OCD. A literature review was performed on papers from the last fifteen years including ‘ASD’, ‘OCD’ and individuals under the age of 18. Eleven papers were selected as relevant. The report looks at the comparison between more traditional methods, such as selective-serotonin-reuptake-inhibitors (SSRI) and Cognitive behaviour therapy (CBT), and newer therapies, such as modified or intensive ASD focused psychotherapies, and the use of other medication classes. On reviewing the data, it was identified that there was a distinct lack of information on this important topic. The most widely used treatment was medication such as Fluoxetine, an SSRI, which rarely showed improvement in symptoms or outcomes. This is in contrast to modified forms of CBT which often reduces symptoms or even results in OCD remission. With increased research into non-traditional management of these co-morbid conditions, it is clear there is scope that modified CBT may become the future treatment of choice for OCD in young people with ASD.

Keywords: autism spectrum disorder, intensive or adapted cognitive behavioural therapy, obsessive compulsive disorder, pharmacological management

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Authors: Hind Bouami, Patrick Millot

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Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, Hospitals, Human-centered automated system, Risk management

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Bernabeo R. Alberto

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Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Oluwagbenga O. Isaac Orimoogunje, Omolola Helen Oshosanya

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The study examined land management in a typical watershed in southwestern Nigeria with a view to ascertaining its impact on land suitability analysis for rice cultivation and production. The study applied the analytical hierarchy process (AHP), weighted overlay analysis (WOA), multi-criteria decision-making techniques, and suitability map calculations within a Geographic Information System environment. Five main criteria were used, and these include climate, topography, soil fertility, macronutrients, and micronutrients. A consistency ratio (CR) of 0.067 was obtained for rice cultivation. The results showed that 95% of the land area is suitable for rice cultivation, with pH units ranging between 4.6 and 6.0, organic matter of 1.4–2.5 g kg-1 and base saturation of more than 80%. The study concluded that the Ofiki watershed is a potential site for large-scale rice cultivation in a sustainable capacity.

Keywords: land management, land characteristics, land suitability, rice production, watershed

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Authors: Han Gul Lee

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When water treatments utilities are designed, an initial construction site risk assessment is conducted. This helps us to understand general safety risks that each utility needs to be complemented in the designing stage. Once it’s built, an additional risk reassessment process secures and supplements its disaster management and response plan. Because of its constantly changing surroundings with city renovation and developments, the degree of various risks that each facility has to face changes. Therefore, to improve the preparedness for spill incidents or disasters, emergency managers should run spill simulations with the available scientific technologies. This research used a two-dimensional flow routing model to simulate its spill disaster scenario based on its digital elevation model (DEM) collected with drone technologies. The results of the simulations can help emergency managers to supplement their response plan with concrete situational awareness in advance. Planning based on this simulation model minimizes its potential loss and damage when an incident like earthquakes man-made disaster happens, which could eventually be a threat in a public health context. This pilot research provides an additional paradigm to increase the preparedness to spill disasters. Acknowledgment: This work was supported by Korea Environmental Industry & Technology Institute (KEITI) through Environmental R&D Project on the Disaster Prevention of Environmental Facilities Program funded by Korea Ministry of Environment (MOE) (No.202002860001).

Keywords: risk assessment, disaster management, water treatment utilities, situational awareness, drone technologies

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Authors: Baobao Li

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Operational risk covers all operations of commercial banks and has a close relationship with the bank’s internal control. But in the commercial banks' management practice, internal control is always separated from the operational risk measurement. With the increasing of operational risk events in recent years, operational risk is paid more and more attention by regulators and banks’ managements. The paper first discussed the relationship between internal control and operational risk management and used CVaR-POT model to measure operational risk, and then put forward a modified measurement method (to use operational risk assessment results to modify the measurement results of the CVaR-POT model). The paper also analyzed the necessity and rationality of this method. The method takes into consideration the influence of internal control, improves the accuracy and effectiveness of operational risk measurement and save the economic capital for commercial banks, avoiding the drawbacks of using some mainstream models one-sidedly.

Keywords: commercial banks, internal control, operational risk, risk measurement

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: Donald Kushon, Jyoti Pillai

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Psychogenic Non-epileptic Seizure Disorder (PNES) is a challenging clinical problem for the neurologist. This study explores the benefits of on-site collaboration between psychiatry and neurology in the management of PNES. A 3 month period at a university hospital seizure clinic is described detailing specific management approaches taken as a result of this collaboration. This study describes four areas of interest: (1. After the video EEG results confirm the diagnosis of PNES, the presentation of the diagnosis of PNES to the patient. (2. The identification of co-morbid psychiatric illness (3. Treatment with specific psychotherapeutic interventions (including Cognitive Behavioral Therapy) and psychopharmacologic interventions (primarily SSRIs) and (4. Preliminary treatment outcomes.

Keywords: cognitive behavioral therapy (CBT), psychogenic non-epileptic seizure disorder (PNES), selective serotonin reuptake inhibitors (SSRIs), video electroencephalogram (VEEG)

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Authors: Krishnan Manickavasagam, Manikandan Shanmugam

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Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Shubham Kumar, Chaitanya Goswami, Sudipto Sarkar

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Pseudoplastic (n < 1, n being the power index) fluid flow can be found in food, pharmaceutical and process industries and has very complex flow nature. To our knowledge, inadequate research work has been done in this kind of flow even at very low Reynolds numbers. Here, in the present computation, we have considered unsteady laminar flow over a square cylinder in pseudoplastic flow environment. For Newtonian fluid flow, this laminar vortex shedding range lies between Re = 47-180. In this problem, we consider Re = 100 (Re = U∞ a/ ν, U∞ is the free stream velocity of the flow, a is the side of the cylinder and ν is the kinematic viscosity of the fluid). The pseudoplastic fluid range has been chosen from close to the Newtonian fluid (n = 0.8) to very high pseudoplasticity (n = 0.1). The flow domain is constituted using Gambit 2.2.30 and this software is also used to generate mesh and to impose the boundary conditions. For all places, the domain size is considered as 36a × 16a with 280 ×192 grid point in the streamwise and flow normal directions respectively. The domain and the grid points are selected after a thorough grid independent study at n = 1.0. Fine and equal grid spacing is used close to the square cylinder to capture the upper and lower shear layers shed from the cylinder. Away from the cylinder the grid is unequal in size and stretched out in all direction. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition du/dy = 0, v = 0) at upper and lower domain boundary conditions are used for this simulation. Wall boundary (u = v = 0) is considered on the square cylinder surface. Fully conservative 2-D unsteady Navier-Stokes equations are discretized and then solved by Ansys Fluent 14.5 to understand the flow nature. SIMPLE algorithm written in finite volume method is selected for this purpose which is the default solver in scripted in Fluent. The result obtained for Newtonian fluid flow agrees well with previous work supporting Fluent’s usefulness in academic research. A minute analysis of instantaneous and time averaged flow field is obtained both for Newtonian and pseudoplastic fluid flow. It has been observed that drag coefficient increases continuously with the reduced value of n. Also, the vortex shedding phenomenon changes at n = 0.4 due to flow instability. These are some of the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: Ansys Fluent, CFD, periodic vortex shedding, pseudoplastic fluid flow

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Authors: Inyoung Park, Youngjoo Woo, Euiseong Seo

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With the advent of WebGL, Web apps are now able to provide high quality graphics by utilizing the underlying graphic processing units (GPUs). Despite that the Web apps are becoming common and popular, the current power management schemes, which were devised for the conventional native applications, are suboptimal for Web apps because of the additional layer, the Web browser, between OS and application. The Web browser running on a CPU issues GL commands, which are for rendering images to be displayed by the Web app currently running, to the GPU and the GPU processes them. The size and number of issued GL commands determine the processing load of the GPU. While the GPU is processing the GL commands, CPU simultaneously executes the other compute intensive threads. The actual user experience will be determined by either CPU processing or GPU processing depending on which of the two is the more demanded resource. For example, when the GPU work queue is saturated by the outstanding commands, lowering the performance level of the CPU does not affect the user experience because it is already deteriorated by the retarded execution of GPU commands. Consequently, it would be desirable to lower CPU or GPU performance level to save energy when the other resource is saturated and becomes a bottleneck in the execution flow. Based on this observation, we propose a power management scheme that is specialized for the Web app runtime environment. This approach incurs two technical challenges; identification of the bottleneck resource and determination of the appropriate performance level for unsaturated resource. The proposed power management scheme uses the CPU utilization level of the Window Manager to tell which one is the bottleneck if exists. The Window Manager draws the final screen using the processed results delivered from the GPU. Thus, the Window Manager is on the critical path that determines the quality of user experience and purely executed by the CPU. The proposed scheme uses the weighted average of the Window Manager utilization to prevent excessive sensitivity and fluctuation. We classified Web apps into three categories using the analysis results that measure frame-per-second (FPS) changes under diverse CPU/GPU clock combinations. The results showed that the capability of the CPU decides user experience when the Window Manager utilization is above 90% and consequently, the proposed scheme decreases the performance level of CPU by one step. On the contrary, when its utilization is less than 60%, the bottleneck usually lies in the GPU and it is desirable to decrease the performance of GPU. Even the processing unit that is not on critical path, excessive performance drop can occur and that may adversely affect the user experience. Therefore, our scheme lowers the frequency gradually, until it finds an appropriate level by periodically checking the CPU utilization. The proposed scheme reduced the energy consumption by 10.34% on average in comparison to the conventional Linux kernel, and it worsened their FPS by 1.07% only on average.

Keywords: interactive applications, power management, QoS, Web apps, WebGL

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Authors: Ali Mohaghar, Iman Ghasemian Sahebi, Alireza Arab

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In the last decades, increasing in human and natural disaster occurrence had very irreparable effects on human life. Hence, one of the important issues in humanitarian supply chain management is identifying and prioritizing the different risks and finding suitable solutions for encountering them at the time of disaster occurrence. This study is an attempt to provide a comprehensive review of humanitarian supply chain risks in a case study of Tehran Red Crescent Societies. For this purpose, Best-Worst method (BWM) has been used for analyzing the risks of the humanitarian supply chain. 22 risks of the humanitarian supply chain were identified based on the literature and interviews with four experts. According to BWM method, the importance of each risk was calculated. The findings showed that culture contexts, little awareness of people, and poor education system are the most important humanitarian supply chain risks. This research provides a useful guideline for managers so that they can benefit from the results to prioritize their solutions.

Keywords: Best-Worst Method, humanitarian logistics, humanitarian supply chain, risk management

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Authors: Innocent Pangapanga, Eric Mungatana

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Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

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Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: Mohammad Amin Hamedirad, Seyed Javad Vaziri Kang Olyaei

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Project planning and control are one of the most critical issues in the management of construction projects. Traditional methods of project planning and control, such as the critical path method or Gantt chart, are not widely used for planning projects with discrete and repetitive activities, and one of the problems of project managers is planning the implementation process and optimal allocation of its resources. Massive concreting projects is also a project with discrete and repetitive activities. This study uses the concept of simulating discrete events to manage resources, which includes finding the optimal number of resources considering various limitations such as limitations of machinery, equipment, human resources and even technical, time and implementation limitations using analysis of resource consumption rate, project completion time and critical points analysis of the implementation process. For this purpose, the concept of discrete-event simulation has been used to model different stages of implementation. After reviewing the various scenarios, the optimal number of allocations for each resource is finally determined to reach the maximum utilization rate and also to reduce the project completion time or reduce its cost according to the existing constraints. The results showed that with the optimal allocation of resources, the project completion time could be reduced by 90%, and the resulting costs can be reduced by up to 49%. Thus, allocating the optimal number of project resources using this method will reduce its time and cost.

Keywords: simulation, massive concreting, discrete event simulation, resource management

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Authors: Heng Ma

Abstract:

Third-party warehousing logistics has an important role in the development of external logistics. At present, the third-party logistics in our country is still a new industry, the accounting system has not yet been established, the current financial accounting system of third-party warehousing logistics is mainly in the traditional way of thinking, and only able to provide the total cost information of the entire enterprise during the accounting period, unable to reflect operating indirect cost information. In order to solve the problem of third-party logistics industry cost information distortion, improve the level of logistics cost management, the paper combines theoretical research and case analysis method to reflect cost allocation by building third-party logistics costing model using Time-Driven Activity-Based Costing(TDABC), and takes S company as an example to account and control the warehousing logistics cost. Based on the idea of “Products consume activities and activities consume resources”, TDABC put time into the main cost driver and use time-consuming equation resources assigned to cost objects. In S company, the objects focuses on three warehouse, engaged with warehousing and transportation (the second warehouse, transport point) service. These three warehouse respectively including five departments, Business Unit, Production Unit, Settlement Center, Security Department and Equipment Division, the activities in these departments are classified by in-out of storage forecast, in-out of storage or transit and safekeeping work. By computing capacity cost rate, building the time-consuming equation, the paper calculates the final operation cost so as to reveal the real cost. The numerical analysis results show that the TDABC can accurately reflect the cost allocation of service customers and reveal the spare capacity cost of resource center, verifies the feasibility and validity of TDABC in third-party logistics industry cost accounting. It inspires enterprises focus on customer relationship management and reduces idle cost to strengthen the cost management of third-party logistics enterprises.

Keywords: third-party logistics enterprises, TDABC, cost management, S company

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Authors: Ngoc Dang Khoa Nguyen, Imran Ali

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The cloud customer relationship management (CRM) has emerged as an innovative tool to augment the customer satisfaction and performance of banking systems. Cloud CRM allows to collect, analyze and utilize customer-associated information and update the systems, thereby offer superior customer service. Cloud technologies have invaluable potential to ensure innovative customer experiences, successful collaboration, enhanced speed to marketplace and IT effectiveness. As such, many leading banks have been attracted towards adoption of such innovative and customer-driver solutions to revolutionize their existing business models. Chief Information Officers (CIOs) are already implemented or in the process of implementation of cloud CRM. However, many organizations are still reluctant to take such initiative due to the lack of information on the factors influencing its implementation. This paper, therefore, aims to delve into the strategies, benefits and challenges intertwined in the implementation of Cloud CRM in banking sector and provide reliable solutions.

Keywords: banking sector, cloud computing, cloud CRM, strategy

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Authors: Udeh Nneka Evelyn

Abstract:

The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

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Authors: Amy Lebar, Kim L. Trenbath, Bennett Doherty, William Livingood

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Plug and process loads (PPLs) account for 47% of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering and data storage. A laboratory proof of concept (PoC) demonstrated all but the data storage capabilities and these capabilities were validated using an office building scenario. The PoC can identify when a device is plugged into an outlet and the location of the device in the building. When a device is moved, the PoC’s dashboard and database are automatically updated with the new location. The PoC implements controls to devices from the system dashboard so that devices maintain correct schedules regardless of where they are plugged in within a building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. A system like ATLIS could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings (GEB), miscellaneous electric loads (MELs), plug loads, plug load management (PLM)

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Authors: Jovian Cheung, Thomas Kwok, Victor Wong

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Buildings are entwined with smart city developments. Building performance relies heavily on electrical and mechanical (E&M) systems and services accounting for about 40 percent of global energy use. By cohering the advancement of technology as well as energy and operation-efficient initiatives into the buildings, people are enabled to raise building performance and enhance the sustainability of the built environment in their daily lives. Digital transformation in the buildings is the profound development of the city to leverage the changes and opportunities of digital technologies To optimize the building performance, intelligent power quality and energy management system is developed for transforming data into actions. The system is formed by interfacing and integrating legacy metering and internet of things technologies in the building and applying big data techniques. It provides operation and energy profile and actionable insights of a building, which enables to optimize the building performance through raising people awareness on E&M services and energy consumption, predicting the operation of E&M systems, benchmarking the building performance, and prioritizing assets and energy management opportunities. The intelligent power quality and energy management system comprises four elements, namely the Integrated Building Performance Map, Building Performance Dashboard, Power Quality Analysis, and Energy Performance Analysis. It provides predictive operation sequence of E&M systems response to the built environment and building activities. The system collects the live operating conditions of E&M systems over time to identify abnormal system performance, predict failure trends and alert users before anticipating system failure. The actionable insights collected can also be used for system design enhancement in future. This paper will illustrate how intelligent power quality and energy management system provides operation and energy profile to optimize the building performance and actionable insights to revitalize an existing building into a smart building. The system is driving building performance optimization and supporting in developing Hong Kong into a suitable smart city to be admired.

Keywords: intelligent buildings, internet of things technologies, big data analytics, predictive operation and maintenance, building performance

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Authors: Kaddour Fellague Mohammed

Abstract:

The world has seen in recent years, significant developments affected various aspects of life and influenced the different types of institutions, thus was born a new world is a world of globalization, which dominated the scientific revolution and the tremendous technological developments, and that contributed to the re-formation of human resources in contemporary organizations, and made patterns new regulatory and at the same time raised and strongly values and new ideas, the organizations have become more flexible, and faster response to consumer and environmental conditions, and exceeded the problem of time and place in the framework of communication and human interaction and use of advanced information technology and adoption mainly mechanism in running its operations , focused on performance and based strategic thinking and approach in order to achieve its strategic goals high degrees of superiority and excellence, this new reality created an increasing need for a new type of human resources, quality aims to renew and aspire to be a strategic player in managing the organization and drafting of various strategies, think globally and act locally, to accommodate local variables in the international markets, which began organizations tend to strongly as well as the ability to work under different cultures. Human resources management of the most important management functions to focus on the human element, which is considered the most valuable resource of the Department and the most influential in productivity at all, that the management and development of human resources Tattabra a cornerstone in the majority of organizations which aims to strengthen the organizational capacity, and enable companies to attract and rehabilitation of the necessary competencies and are able to keep up with current and future challenges, human resources can contribute to and strongly in achieving the objectives and profit organization, and even expand more than contribute to the creation of new jobs to alleviate unemployment and achieve full operation, administration and human resources mean short optimal use of the human element is available and expected, where he was the efficiency and capabilities, and experience of this human element, and his enthusiasm for the work stop the efficiency and success in reaching their goals, so interested administration scientists developed the principles and foundations that help to make the most of each individual benefit in the organization through human resources management, these foundations start of the planning and selection, training and incentives and evaluation, which is not separate from each other, but are integrated with each other as a system systemic order to reach the efficient functioning of the human resources management and has been the organization as a whole in the context of development sustainable.

Keywords: configuration, training, development, human resources, operating

Procedia PDF Downloads 433