Search results for: workflow scheduling

Authors: Danjuma Moudu Momoh

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Participation in sports is of immense benefit to the soundness of individual mental and social wellness, particularly among youngsters. The 1980’s and 1990’s compared to 2000’s witnessed great involvement of youngsters in school games arising from the high administrative supports attached to sports. Previous studies in an attempt to increase youngster’s participation in sports had focused more on other factors rather than on administrative factors. This study, therefore, investigated the importance of administrative factors (availability of facilities, availability of equipment, funding, scheduling of sports programme and administrative style of school principals) on students’ sports participation in private and public secondary schools in Kwara State, Nigeria. Descriptive survey research design using validated and structured questionnaire, was adopted. Stratified random sampling technique was used to pick the students both male and female. A total of two thousand five hundred and sixty participants were involved in the study. A reliable coefficient of r=0.82 was obtained for the instruments using Cronbach Alpha. Data were analyzed using multiple regressions to test the hypotheses at 00.5 significant levels. At the end of the study, it was discovered that the relative contributions of administrative factors among the students were: availability of facilities (β=0.314), availability of equipment (β=0.444), funding (β=0.301), scheduling of sports programme (β=0.447), made relative contributions to the dependent variable, administrative style of school principal (β=0.077) did not make significant but minimal contribution to the student’s sports participation.

Keywords: administrative determinants, secondary school students, physical activity, sports participation

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Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

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Authors: Tzu-Yang Lin, Chuan-Ching Sue

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Sleep mechanisms are commonly used to ensure the energy efficiency of each optical network unit (ONU) that concerns a single class delay constraint in the Ethernet Passive Optical Network (EPON). How long the ONUs can sleep without violating the delay constraint has become a research problem. Particularly, we can derive an analytical model to determine the optimal sleep time of ONUs in every cycle without violating the maximum class delay constraint. The bandwidth allocation considering such optimal sleep time is called Green Bandwidth Allocation (GBA). Although the GBA mechanism guarantees that the different class delay constraints do not violate the maximum class delay constraint, packets with a more relaxed delay constraint will be treated as those with the most stringent delay constraint and may be sent early. This means that the ONU will waste energy in active mode to send packets in advance which did not need to be sent at the current time. Accordingly, we proposed a QoS-aware GBA using a novel intra-ONU scheduling to control the packets to be sent according to their respective delay constraints, thereby enhancing energy efficiency without deteriorating delay performance. If packets are not explicitly classified but with different packet delay constraints, we can modify the intra-ONU scheduling to classify packets according to their packet delay constraints rather than their classes. Moreover, we propose the switchable ONU architecture in which the ONU can switch the architecture according to the sleep time length, thus improving energy efficiency in the QoS-aware GBA. The simulation results show that the QoS-aware GBA ensures that packets in different classes or with different delay constraints do not violate their respective delay constraints and consume less power than the original GBA.

Keywords: Passive Optical Networks, PONs, Optical Network Unit, ONU, energy efficiency, delay constraint

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Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

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Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

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Authors: B. Kriheli, E. Levner, T. C. E. Cheng, C. T. Ng

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During the last decades, research interest in planning, scheduling, and control of emergency response operations, especially people rescue and evacuation from the dangerous zone of marine accidents, has increased dramatically. Until the survivors (called ‘targets’) are found and saved, it may cause loss or damage whose extent depends on the location of the targets and the search duration. The problem is to efficiently search for and detect/rescue the targets as soon as possible with the help of intelligent mobile robots so as to maximize the number of saved people and/or minimize the search cost under restrictions on the amount of saved people within the allowable response time. We consider a special situation when the autonomous mobile robots (AMR), e.g., unmanned aerial vehicles and remote-controlled robo-ships have no operator on board as they are guided and completely controlled by on-board sensors and computer programs. We construct a mathematical model for the search process in an uncertain environment and provide a new fast algorithm for scheduling the activities of the autonomous robots during the search-and rescue missions after an accident at sea. We presume that in the unknown environments, the AMR’s search-and-rescue activity is subject to two types of error: (i) a 'false-negative' detection error where a target object is not discovered (‘overlooked') by the AMR’s sensors in spite that the AMR is in a close neighborhood of the latter and (ii) a 'false-positive' detection error, also known as ‘a false alarm’, in which a clean place or area is wrongly classified by the AMR’s sensors as a correct target. As the general resource-constrained discrete search problem is NP-hard, we restrict our study to finding local-optimal strategies. A specificity of the considered operational research problem in comparison with the traditional Kadane-De Groot-Stone search models is that in our model the probability of the successful search outcome depends not only on cost/time/probability parameters assigned to each individual location but, as well, on parameters characterizing the entire history of (unsuccessful) search before selecting any next location. We provide a fast approximation algorithm for finding the AMR route adopting a greedy search strategy in which, in each step, the on-board computer computes a current search effectiveness value for each location in the zone and sequentially searches for a location with the highest search effectiveness value. Extensive experiments with random and real-life data provide strong evidence in favor of the suggested operations research model and corresponding algorithm.

Keywords: disaster management, intelligent robots, scheduling algorithm, search-and-rescue at sea

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Authors: Yiu K. C. Jacky, Tang S. K. Eric, W. Y. Tsang, C. Y. Li, C. K. Leung

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Objectives : (1) To enhance the competence of nurses on using IPMOE for drug administration; (2) To ensure the transition on implementation of IPMOE in safer and smooth way hospital-wide. Methodology: (1) Well-structured Governance: To make provision for IPMOE implementation, multidisciplinary governance structure at Corporate and Local levels are well established. (2) Staff Engagement: A series of staff engagement events were conducted including Staff Forum, IPMOE Hospital Visit, Kick-off Ceremony and establishment of IPMOE Webpage for familiarizing the forthcoming implementation with frontline staff. (3) Well-organized training program: from Workshop to Workplace Two different IPMOE training programs were tailor-made which aimed at introducing the core features of administration module. Fifty-five identical training classes and six train-the-trainer workshops were organized at 2-3Q 2015. Lending Scheme on IPMOE hardware for hands-on practicing was launched and further extended the training from workshop to workplace. (4) Standard Guidelines and Workflow: the related workflow and guidelines are developed which facilitates users to acquire the competence towards IPMOE and fully familiarize with the standardized contingency plan. (5) Facilities and Equipment: The installations of IPMOE hardware were promptly arranged for rollout. Besides, IPMOE training venue was well-established for staff training. (6) Risk Management Strategy: UCH Medication Safety Forum is organized in December 2015 for sharing “Tricks & Tips” on IPMOE which further disseminate at webpage for arousal of medication safety. Hospital-wide annual audit on drug administration was planned to figure out the compliance and deliberate the rooms for improvement. Results: Through the comprehensive training plan, over 1,000 UCH nurses attended the training program with positive feedback. They agreed that their competence on using IPMOE was enhanced. By the end of November 2015, 28 wards (over 1,000 Inpatient-bed) involving departments of M&G, SUR, O&T and O&G have been successfully rolled out IPMOE in 5-month. A smooth and safe transition of implementation of IPMOE was achieved. Eventually, we all get prepared for embedding IPMOE into daily nursing and work altogether for medication safety at UCH.

Keywords: drug administration, inpatient medication order entry system, medication safety, nursing informatics

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

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Authors: Laura Florez

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The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

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Authors: Samantha Meyerholz

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MSKCC offers patients cutting edge cancer care with the highest quality standards. However, many patients and industry members do not realize that the operations of the Immunology Histology Lab (IHC) are the backbone for carrying out this mission. The IHC lab manufactures blocks and slides containing critical tissue samples that will be read by a Pathologist to diagnose and dictate a patient’s treatment course. The lab processes 200 requests daily, leading to the generation of approximately 2,000 slides and 1,100 blocks each day. Lab material is transported through labeling, cutting, staining and sorting manufacturing stations, while being managed by multiple techs throughout the space. The quality of the stain as well as wait times associated with processing requests, is directly associated with patients receiving rapid treatments and having a wider range of care options. This project aims to improve slide request turnaround time for rush and non-rush cases, while increasing the quality of each request filled (no missing slides or poorly stained items). Rush cases are to be filled in less than 24 hours, while standard cases are allotted a 48 hour time period. Reducing turnaround times enable patients to communicate sooner with their clinical team regarding their diagnosis, ultimately leading faster treatments and potentially better outcomes. Additional project goals included streamlining tech and material workflow, while reducing waste and increasing efficiency. This project followed a DMAIC structure with emphasis on lean and ergonomic principles that could be integrated into an evolving lab culture. Load times and batching processes were analyzed using process mapping, FMEA analysis, waste analysis, engineering observation, 5S and spaghetti diagramming. Reduction of lab technician movement as well as their body position at each workstation was of top concern to pathology leadership. With new equipment being brought into the lab to carry out workflow improvements, screen and tool placement was discussed with the techs in focus groups, to reduce variation and increase comfort throughout the workspace. 5S analysis was completed in two phases in the IHC lab, helping to drive solutions that reduced rework and tech motion. The IHC lab plans to continue utilizing these techniques to further reduce the time gap between tissue analysis and cancer care.

Keywords: engineering, ergonomics, healthcare, lean

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Authors: Pornpote Nusen, Manop Kaewmoracharoen

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In recent years, there was an observable shift in fully developed countries from constructing new buildings to modifying existing buildings. The issue was that although an effective instrument like BIM (Building Information Modeling) was well developed for constructing new buildings, it was not widely used to renovate old buildings. BIM was accepted as an effective means to overcome common managerial problems such as project delay, cost overrun, and poor quality of the project life cycle. It was recently introduced in Thailand and rarely used in a renovation project. Today, in Thailand, BIM is mostly used for creating aesthetic 3D models and quantity takeoff purposes, though it can be an effective tool to use as a project management tool in planning and scheduling. Now the governmental sector in Thailand begins to recognize the uses of using BIM to manage a construction project, but the knowledge about the BIM implementation to governmental construction projects is underdeveloped. Further studies need to be conducted to maximize its advantages for the governmental sector. An educational extra large governmental building of 17,000 square-meters was used in this research. It is currently under construction for a two-year renovation project. BIM models of the building for the exterior and interior areas were created for the whole five floors. Then 4D BIM with combination of 3D BIM plus time was created for planning and scheduling. Three focus groups had been done with executive committee, contractors, and officers of the building to discuss the possibility of usage and usefulness of BIM approach over the traditional process. Several aspects were discussed in the positive sides, especially several foreseen problems, such as the inadequate accessibility of ways, the altered ceiling levels, the impractical construction plan created through a traditional approach, and the lack of constructability information. However, for some parties, the cost of BIM implementation was a concern, though, this study believes, its uses outweigh the cost.

Keywords: building information modeling, extra large building, governmental building renovation, project management, renovation, 4D BIM

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Authors: James Forren

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This research paper details a recent demonstrator project in which digital form found textile structures were built by human craftspersons wearing augmented reality (AR) head-worn displays (HWDs). The project utilized a wet-state natural fiber / cementitious matrix composite to generate minimal bending shapes in tension which, when cured and rotated, performed as minimal-bending compression members. The significance of the project is that it synthesizes computational structural simulations with visually guided handcraft production. Computational and physical form-finding methods with textiles are well characterized in the development of architectural form. One difficulty, however, is physically building computer simulations: often requiring complicated digital fabrication workflows. However, AR HWDs have been used to build a complex digital form from bricks, wood, plastic, and steel without digital fabrication devices. These projects utilize, instead, the tacit knowledge motor schema of the human craftsperson. Computational simulations offer unprecedented speed and performance in solving complex structural problems. Human craftspersons possess highly efficient complex spatial reasoning motor schemas. And textiles offer efficient form-generating possibilities for individual structural members and overall structural forms. This project proposes that the synthesis of these three modalities of structural problem-solving – computational, human, and material - may not only develop efficient structural form but offer further creative potentialities when the respective intelligence of each modality is productively leveraged. The project methodology pertains to its three modalities of production: 1) computational, 2) human, and 3) material. A proprietary three-dimensional graphic statics simulator generated a three-legged arch as a wireframe model. This wireframe was discretized into nine modules, three modules per leg. Each module was modeled as a woven matrix of one-inch diameter chords. And each woven matrix was transmitted to a holographic engine running on HWDs. Craftspersons wearing the HWDs then wove wet cementitious chords within a simple falsework frame to match the minimal bending form displayed in front of them. Once the woven components cured, they were demounted from the frame. The components were then assembled into a full structure using the holographically displayed computational model as a guide. The assembled structure was approximately eighteen feet in diameter and ten feet in height and matched the holographic model to under an inch of tolerance. The construction validated the computational simulation of the minimal bending form as it was dimensionally stable for a ten-day period, after which it was disassembled. The demonstrator illustrated the facility with which computationally derived, a structurally stable form could be achieved by the holographically guided, complex three-dimensional motor schema of the human craftsperson. However, the workflow traveled unidirectionally from computer to human to material: failing to fully leverage the intelligence of each modality. Subsequent research – a workshop testing human interaction with a physics engine simulation of string networks; and research on the use of HWDs to capture hand gestures in weaving seeks to develop further interactivity with rope and chord towards a bi-directional workflow within full-scale building environments.

Keywords: augmented reality, cementitious composites, computational form finding, textile structures

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Yenesew Mengiste Yihun, Abraham Mehari Haile, Teklu Erkossa, Bart Schultz

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Teff (Eragrostic tef) is a staple food in Ethiopia. The local and international demand for the crop is ever increasing pushing the current price five times compared with that in 2006. To meet this escalating demand increasing production including using irrigation is imperative. Optimum application of irrigation water, especially in semi-arid areas is profoundly important. AquaCrop model application in irrigation water scheduling and simulation of water productivity helps both irrigation planners and agricultural water managers. This paper presents simulation and evaluation of AquaCrop model in optimizing the yield and biomass response to variation in timing and rate of irrigation water application. Canopy expansion, canopy senescence and harvest index are the key physiological processes sensitive to water stress. For full irrigation water application treatment there was a strong relationship between the measured and simulated canopy and biomass with r2 and d values of 0.87 and 0.96 for canopy and 0.97 and 0.74 for biomass, respectively. However, the model under estimated the simulated yield and biomass for higher water stress level. For treatment receiving full irrigation the harvest index value obtained were 29%. The harvest index value shows generally a decreasing trend under water stress condition. AquaCrop model calibration and validation using the dry season field experiments of 2010/2011 and 2011/2012 shows that AquaCrop adequately simulated the yield response to different irrigation water scenarios. We conclude that the AquaCrop model can be used in irrigation water scheduling and optimizing water productivity of Teff grown under water scarce semi-arid conditions.

Keywords: AquaCrop, climate smart agriculture, simulation, teff, water security, water stress regions

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Authors: Ming Liu, Zhihui Sun, Xiaoning Zhang

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This paper studies a deterministic container transportation problem, jointly optimizing the berth allocation, quay crane assignment and yard storage allocation at container ports. The problem is formulated as an integer program to coordinate the decisions. Because of the large scale, it is then transformed into a set partitioning formulation, and a framework of branchand- price algorithm is provided to solve it.

Keywords: branch-and-price, container terminal, joint scheduling, maritime logistics

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Authors: Hemin Yuan, Yun Wang, Xiangchun Wang

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Gas hydrate is drawing attention due to the fact that it has an enormous amount all over the world, which is almost twice the conventional hydrocarbon reserves, making it a potential alternative source of energy. It is widely distributed in permafrost and continental ocean shelves, and many countries have launched national programs for investigating the gas hydrate. Gas hydrate is mainly explored through seismic methods, which include bottom simulating reflectors (BSR), amplitude blanking, and polarity reverse. These seismic methods are effective at finding the gas hydrate formations but usually contain large uncertainties when applying to invert the micro-scale petrophysical properties of the formations due to lack of constraints. Rock physics modeling links the micro-scale structures of the rocks to the macro-scale elastic properties and can work as effective constraints for the seismic methods. A number of rock physics models have been proposed for gas hydrate modeling, which addresses different mechanisms and applications. However, these models are generally not well classified, and it is confusing to determine the appropriate model for a specific study. Moreover, since the modeling usually involves multiple models and steps, it is difficult to determine the source of uncertainties. To solve these problems, we summarize the developed models/methods and make four classifications of the models according to the hydrate micro-scale morphology in sediments, the purpose of reservoir characterization, the stage of gas hydrate generation, and the lithology type of hosting sediments. Some sub-categories may overlap each other, but they have different priorities. Besides, we also analyze the priorities of different models, bring up the shortcomings, and explain the appropriate application scenarios. Moreover, by comparing the models, we summarize a general workflow of the modeling procedure, which includes rock matrix forming, dry rock frame generating, pore fluids mixing, and final fluid substitution in the rock frame. These procedures have been widely used in various gas hydrate modeling and have been confirmed to be effective. We also analyze the potential sources of uncertainties in each modeling step, which enables us to clearly recognize the potential uncertainties in the modeling. In the end, we explicate the general problems of the current models, including the influences of pressure and temperature, pore geometry, hydrate morphology, and rock structure change during gas hydrate dissociation and re-generation. We also point out that attenuation is also severely affected by gas hydrate in sediments and may work as an indicator to map gas hydrate concentration. Our work classifies rock physics models of gas hydrate into different categories, generalizes the modeling workflow, analyzes the modeling uncertainties and potential problems, which can facilitate the rock physics characterization of gas hydrate bearding sediments and provide hints for future studies.

Keywords: gas hydrate, rock physics model, modeling classification, hydrate morphology

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

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Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: Nijanthan Mohan, Rolf Gross, Fabian Theis

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The conventional method used in the construction industries often resulted in significant rework since most of the decisions were taken onsite under the pressure of project deadlines and also due to the improper information flow, which results in ineffective coordination. However, today’s architecture, engineering, and construction (AEC) stakeholders demand faster and accurate deliverables, efficient buildings, and smart processes, which turns out to be a tall order. Hence, the building information modelling (BIM) concept was developed as a solution to fulfill the above-mentioned necessities. Even though BIM is successfully implemented in most of the world, it is still in the early stages in Germany, since the stakeholders are sceptical of its reliability and efficiency. Due to the huge capital requirement, the small and medium-sized construction companies are still reluctant to implement BIM workflow in their projects. The purpose of this paper is to analyse the opportunities and obstacles to implementing BIM for prefabrication. Among all other advantages of BIM, pre-fabrication is chosen for this paper because it plays a vital role in creating an impact on time as well as cost factors of a construction project. The positive impact of prefabrication can be explicitly observed by the project stakeholders and participants, which enables the breakthrough of the skepticism factor among the small scale construction companies. The analysis consists of the development of a process workflow for implementing prefabrication in building construction, followed by a practical approach, which was executed with two case studies. The first case study represents on-site prefabrication, and the second was done for off-site prefabrication. It was planned in such a way that the first case study gives a first-hand experience for the workers at the site on the BIM model so that they can make much use of the created BIM model, which is a better representation compared to the traditional 2D plan. The main aim of the first case study is to create a belief in the implementation of BIM models, which was succeeded by the execution of offshore prefabrication in the second case study. Based on the case studies, the cost and time analysis was made, and it is inferred that the implementation of BIM for prefabrication can reduce construction time, ensures minimal or no wastes, better accuracy, less problem-solving at the construction site. It is also observed that this process requires more planning time, better communication, and coordination between different disciplines such as mechanical, electrical, plumbing, architecture, etc., which was the major obstacle for successful implementation. This paper was carried out in the perspective of small and medium-sized mechanical contracting companies for the private building sector in Germany.

Keywords: building information modelling, construction wastes, pre-fabrication, small and medium sized company

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Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

Procedia PDF Downloads 75

Authors: Elham Koohikerade, Silvio Jose Gumiere

Abstract:

In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

Procedia PDF Downloads 35

Authors: Nur Faridatull Syafinaz Ahmad Tajudin

Abstract:

A hospital is a setting where individuals who are ill or injured are treated and cared for by doctors and nurses. Sanatoriums are settings where people can receive treatment and rest, particularly when recovering from a protracted illness. According to the report, hospitals are primarily designed to meet the needs of medical personnel by maximising their functionality and workflow. Hospitals frequently do a poor job of determining the patients' physical and emotional requirements and expectations. The literature on hospital design has recently focused more on the seeming need to "humanise" medical facilities. Despite the popularity of this design objective, "humanising" a space has hardly ever been defined or critically examined. The term "humanistic design" covered a broad range of design elements and designer interpretations. In reality, the hospital's layout and design the hospital may have a massive effect on patients' feel experience things and heal.

Keywords: hospital retrofitting, hospital design, humanising hospital, spatial design

Procedia PDF Downloads 109

Authors: C. Rekha, G. N. Krishnamurthy

Abstract:

This paper attempts to develop a different approach for key scheduling algorithm which uses both Blowfish and AES algorithms. The main drawback of Blowfish algorithm is, it takes more time to create the S-box entries. To overcome this, we are replacing process of S-box creation in blowfish, by using key dependent S-box creation from AES without affecting the basic operation of blowfish. The method proposed in this paper uses good features of blowfish as well as AES and also this paper demonstrates the performance of blowfish and new algorithm by considering different aspects of security namely Encryption Quality, Key Sensitivity, and Correlation of horizontally adjacent pixels in an encrypted image.

Keywords: AES, blowfish, correlation coefficient, encryption quality, key sensitivity, s-box

Procedia PDF Downloads 216

Authors: Maroua Sbiti, Karim Beddiar, Djaoued Beladjine, Romuald Perrault

Abstract:

Productivity is decreasing in construction compared to the manufacturing industry. It seems that the sector is suffering from organizational problems and have low maturity regarding technological advances. High international competition due to the growing context of globalization, complex projects, and shorter deadlines increases these challenges. Field employees are more exposed to coordination problems than design officers. Execution collaboration is then a major issue that can threaten the cost, time, and quality completion of a project. Initially, this paper will try to identify field professional requirements as to address building management process weaknesses such as the unreliability of scheduling, the fickleness of monitoring and inspection processes, the inaccuracy of project’s indicators, inconsistency of building documents and the random logistic management. Subsequently, we will focus our attention on providing solutions to improve scheduling, inspection, and hours tracking processes using emerging lean tools and field mobility applications that bring new perspectives in terms of cooperation. They have shown a great ability to connect various field teams and make informations visual and accessible to planify accurately and eliminate at the source the potential defects. In addition to software as a service use, the adoption of the human resource module of the Enterprise Resource Planning system can allow a meticulous time accounting and thus make the faster decision making. The next step is to integrate external data sources received from or destined to design engineers, logisticians, and suppliers in a holistic system. Creating a monolithic system that consolidates planning, quality, procurement, and resources management modules should be our ultimate target to build the construction industry supply chain.

Keywords: lean, last planner system, field mobility applications, construction productivity

Procedia PDF Downloads 106

Authors: Julie Delany

Abstract:

To thrive in today’s digital climate, it is vital that organisations adopt new technology and prepare for rising digital trends. This proves more difficult in government where, traditionally, people lack change readiness. While individuals may have a desire to work smarter, this does not necessarily mean embracing technology. This paper discusses the rollout of an application into a small department of highly experienced nurses. The goal was to both streamline the department's workflow and provide a platform for gathering essential business metrics. The biggest challenges were adoption and motivating the nurses to change their routines and learn new computer skills. Two-thirds struggled with the change, and as a result, some jeopardised the validity of the business metrics. In conclusion, there are lessons learned and recommendations for similar projects.

Keywords: change ready, information technology, end-user, iterative method, rollout plan, data analytics

Procedia PDF Downloads 136

Authors: S. Hameed, S. Anwer, M. Saad, M. Saady

Abstract:

For autonomic recovery with server virtualization, a cogent plan that includes recovery techniques and backups with virtualized servers can be developed instead of assigning an idle server to backup operations. In addition to hardware cost reduction and data center trail, the disaster recovery plan can ensure system uptime and to meet objectives of high availability, recovery time, recovery point, server provisioning, and quality of services. This autonomic solution would also support disaster management, testing, and development of the recovery site. In this research, a workflow plan is proposed for supporting disaster recovery with virtualization providing virtual monitoring, requirements engineering, solution decision making, quality testing, and disaster management. This recovery model would make disaster recovery a lot easier, faster, and less error prone.

Keywords: autonomous intelligence, disaster recovery, cloud computing, server virtualization

Procedia PDF Downloads 156

Authors: Eyosiyas Aga

Abstract:

The development of information communication technology has transformed the paper-based mapping and land registration processes to a computerized and networked system. The computerization and networking of real property information system play a vital role in good governance and sustainable development of emerging countries through cost effective, easy and accessible service delivery for the customer. The efficient, transparent and sustainable real property system is becoming the basic infrastructure for the urban development thus improve the data management system and service delivery in the organizations. In Ethiopia, the real property administration is paper based as a result, it confronted problems of data management, illegal transactions, corruptions, and poor service delivery. In order to solve this problem and to facilitate real property market, the implementation of web-based real property updating system is crucial. A web-based real property updating is one of the automation (computerizations) methods to facilitate data sharing, reduce time and cost of the service delivery in real property administration system. In additions, it is useful for the integration of data onto different information systems and organizations. This system is designed by combining open source software which supported by open Geo-spatial consortium. The web-based system is mainly designed by using open source software with the help of open Geo-spatial Consortium. The Open Geo-spatial Consortium standards such as the Web Feature Service and Web Map Services are the most widely used standards to support and improves web-based real property updating. These features allow the integration of data from different sources, and it can be used to maintain consistency of data throughout transactions. The PostgreSQL and Geoserver are used to manage and connect a real property data to the flex viewer and user interface. The system is designed for both internal updating system (municipality); which is mainly updating of spatial and textual information, and the external system (customer) which focus on providing and interacting with the customer. This research assessed the potential of open source web applications and adopted this technology for real property updating system in Ethiopia through simple, cost effective and secured way. The system is designed by combining and customizing open source software to enhance the efficiency of the system in cost effective way. The existing workflow for real property updating is analyzed to identify the bottlenecks, and the new workflow is designed for the system. The requirement is identified through questionnaire and literature review, and the system is prototype for the study area. The research mainly aimed to integrate human resource with technology in designing of the system to reduce data inconsistency and security problems. In additions, the research reflects on the current situation of real property administration and contributions of effective data management system for efficient, transparent and sustainable urban development in Ethiopia.

Keywords: cadaster, real property, sustainable, transparency, web feature service, web map service

Procedia PDF Downloads 259

Authors: Max Moleke

Abstract:

Manufacturing industries are faced with different types of problems. One of the most important role of controlling and monitoring a production process is to actually determine how to deal with unforeseen disruption when they arise. A majority of manufacturing tern to spend huge amount of money in order to meet up with their customers requirements and demand but due to instabilities within the manufacturing process, this objectives and goals are difficult to be achieved. In this research, we have developed a feedback control system that can minimize instability within the manufacturing system in order to boost the system output and productivity.

Keywords: disruption, scheduling, manufacturing, instability

Procedia PDF Downloads 322

Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

Abstract:

Urban structures will be used more intensively in the future through redensification or new planned districts with high building densities. Especially, to achieve positive energy balances like requested for Positive Energy Districts (PED) the single use of roofs is not sufficient for dense urban areas. However, the increasing share of window significantly reduces the facade area available for use in PV generation. Through the use of PV technology at other building components, such as external venetian blinds, onsite generation can be maximized and standard functionalities of this product can be positively extended. While offering advantages in terms of infrastructure, sustainability in the use of resources and efficiency, these systems require an increased optimization in planning and control strategies of buildings. External venetian blinds with PV technology require an intelligent control concept to meet the required demands such as maximum power generation, glare prevention, high daylight autonomy, avoidance of summer overheating but also use of passive solar gains in wintertime. Today, geometric representation of outdoor spaces and at the building level, three-dimensional geometric information is available for planning with Building Information Modeling (BIM). In a research project, a web application which is called HELLA DECART was developed to provide this data structure to extract the data required for the simulation from the BIM models and to make it usable for the calculations and coupled simulations. The investigated object is uploaded as an IFC file to this web application and includes the object as well as the neighboring buildings and possible remote shading. This tool uses a ray tracing method to determine possible glare from solar reflections of a neighboring building as well as near and far shadows per window on the object. Subsequently, an annual estimate of the sunlight per window is calculated by taking weather data into account. This optimized daylight assessment per window provides the ability to calculate an estimation of the potential power generation at the integrated PV on the venetian blind but also for the daylight and solar entry. As a next step, these results of the calculations as well as all necessary parameters for the thermal simulation can be provided. The overall aim of this workflow is to advance the coordination between the BIM model and coupled building simulation with the resulting shading and daylighting system with the artificial lighting system and maximum power generation in a control system. In the research project Powershade, an AI based control concept for PV integrated façade elements with coupled simulation results is investigated. The developed automated workflow concept in this paper is tested by using an office living lab at the HELLA company.

Keywords: BIPV, building simulation, optimized control strategy, planning tool

Procedia PDF Downloads 102

Authors: Prashant Shrivastava

Abstract:

The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

Procedia PDF Downloads 315