Search results for: aircrew scheduling

Authors: George Oliveira, Luana D. Fronza, Luiza Medeiros, Patricia D. M. Plentz

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The research presented in this article is part of a wide project that proposes a scheduling system for multi-robots in intelligent warehouses employing multi-robot path-planning (MPP) and multi-robot task allocation (MRTA) to reconcile multiple restrictions (task delivery time, task priorities, charging capacity, and robots battery capacity). We present the software component capable of interconnecting an open streaming processing architecture and robot operating system (ROS), ensuring communication and message exchange between robots and the environment in which they are inserted. Simulation results show the good performance of our proposed technique for connecting ROS and streaming platforms.

Keywords: complex distributed systems, mobile robots, smart warehouses, streaming platforms

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Authors: Robert Pellerin, Michel Gamache, Remi Trudeau, Nathalie Perrier

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The context of large engineering projects is particularly favorable to the appearance of engineering changes and contractual modifications. These elements are potential causes for claims. In this paper, we investigate one of the critical components of the claim management process: the calculation of the impacts of changes in terms of losses of productivity due to the need to accelerate some project activities. When project changes are initiated, delays can arise. Indeed, project activities are often executed in fast-tracking in an attempt to respect the completion date. But the acceleration of project execution and the resulting rework can entail important costs as well as induce productivity losses. In the past, numerous methods have been proposed to quantify the duration of delays, the gains achieved by project acceleration, and the loss of productivity. The calculation related to those changes can be divided into two categories: direct cost and indirect cost. The direct cost is easily quantifiable as opposed to indirect costs which are rarely taken into account during the calculation of the cost of an engineering change or contract modification despite several research projects have been made on this subject. However, proposed models have not been accepted by companies yet, nor they have been accepted in court. Those models require extensive data and are often seen as too specific to be used for all projects. These techniques are also ignoring the resource constraints and the interdependencies between the causes of delays and the delays themselves. To resolve this issue, this research proposes a simulation model that mimics how major engineering changes or contract modifications are handled in large construction projects. The model replicates the use of overtime in a reactive scheduling mode in order to simulate the loss of productivity present when a project change occurs. Multiple tests were conducted to compare the results of the proposed simulation model with statistical analysis conducted by other researchers. Different scenarios were also conducted in order to determine the impact the number of activities, the time of occurrence of the change, the availability of resources, and the type of project changes on productivity loss. Our results demonstrate that the number of activities in the project is a critical variable influencing the productivity of a project. When changes occur, the presence of a large number of activities leads to a much lower productivity loss than a small number of activities. The speed of reducing productivity for 30-job projects is about 25 percent faster than the reduction speed for 120-job projects. The moment of occurrence of a change also shows a significant impact on productivity. Indeed, the sooner the change occurs, the lower the productivity of the labor force. The availability of resources also impacts the productivity of a project when a change is implemented. There is a higher loss of productivity when the amount of resources is restricted.

Keywords: engineering changes, indirect costs overtime, productivity, scheduling, simulation

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Authors: Salman Ali Nisar, Koshi Suzuki

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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.

Keywords: construction project management, critical path method, project scheduling, precedence diagram method

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Authors: Seyed Kian Haji Seyed Javadi, Aisan Nouri

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Patient satisfaction in dental care is shaped by experiences throughout the treatment journey. Challenges such as fear, lack of trust and poor communication can impact patient contentment and willingness to seek dental care. This narrative review explores these issues and presents innovative solutions to address them by searching PubMed and Scopus data sources. It examines factors affecting patient satisfaction and adherence across three phases—before, during and after treatment—emphasizing the roles of effective communication, payment and follow-up systems, appointment scheduling, welcoming reception and the treatment environment. The factors discussed in this study motivate patients to return for routine check-ups and preventive care, even if their initial visit was for an emergency.

Keywords: patient satisfaction, dentistry, dental access, dental care services

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Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: air pollution, AODV, re-scheduling, WSNs

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Authors: Wesley H. Brewer, John C. Sanford

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SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

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Authors: G. Hubert, S. Aubry

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The earth is constantly bombarded by cosmic rays that can be of either galactic or solar origin. Thus, humans are exposed to high levels of galactic radiation due to altitude aircraft. The typical total ambient dose equivalent for a transatlantic flight is about 50 μSv during quiet solar activity. On the contrary, estimations differ by one order of magnitude for the contribution induced by certain solar particle events. Indeed, during Ground Level Enhancements (GLE) event, the Sun can emit particles of sufficient energy and intensity to raise radiation levels on Earth's surface. Analyses of GLE characteristics occurring since 1942 showed that for the worst of them, the dose level is of the order of 1 mSv and more. The largest of these events was observed on February 1956 for which the ambient dose equivalent rate is in the orders of 10 mSv/hr. The extra dose at aircraft altitudes for a flight during this event might have been about 20 mSv, i.e. comparable with the annual limit for aircrew. The most recent GLE, occurred on September 2017 resulting from an X-class solar flare, and it was measured on the surface of both the Earth and Mars using the Radiation Assessment Detector on the Mars Science Laboratory's Curiosity Rover. Recently, Hubert et al. proposed a GLE model included in a particle transport platform (named ATMORAD) describing the extensive air shower characteristics and allowing to assess the ambient dose equivalent. In this approach, the GCR is based on the Force-Field approximation model. The physical description of the Solar Cosmic Ray (i.e. SCR) considers the primary differential rigidity spectrum and the distribution of primary particles at the top of the atmosphere. ATMORAD allows to determine the spectral fluence rate of secondary particles induced by extensive showers, considering altitude range from ground to 45 km. Ambient dose equivalent can be determined using fluence-to-ambient dose equivalent conversion coefficients. The objective of this paper is to analyze the GCR and SCR impacts on ambient dose equivalent considering a high number statistic of world-flight paths. Flight trajectories are based on the Eurocontrol Demand Data Repository (DDR) and consider realistic flight plan with and without regulations or updated with Radar Data from CFMU (Central Flow Management Unit). The final paper will present exhaustive analyses implying solar impacts on ambient dose equivalent level and will propose detailed analyses considering route and airplane characteristics (departure, arrival, continent, airplane type etc.), and the phasing of the solar event. Preliminary results show an important impact of the flight path, particularly the latitude which drives the cutoff rigidity variations. Moreover, dose values vary drastically during GLE events, on the one hand with the route path (latitude, longitude altitude), on the other hand with the phasing of the solar event. Considering the GLE occurred on 23 February 1956, the average ambient dose equivalent evaluated for a flight Paris - New York is around 1.6 mSv, which is relevant to previous works This point highlights the importance of monitoring these solar events and of developing semi-empirical and particle transport method to obtain a reliable calculation of dose levels.

Keywords: cosmic ray, human dose, solar flare, aviation

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Authors: Chris Nelson

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Quality and excellence are qualitative topics that are usually addressed based on knowledge and past experience from leadership and those in charge of the organization. The significance of this study is to highlight the differences and similarities between these two mindsets and how an operational staff can most appropriately use them in the workplace. Quality and excellence are two words that are talked about a lot in the manufacturing world. Buzzwords such as operational excellence, quality controls, and efficiencies are discussed in the boardroom as well on the shop floor. These terms are used quite frequently and with good reasons. When a person visits their favorite local restaurant, They go because 1) they like the food and 2) the people are some of the greatest individuals to be around. With that in mind, they know they always put out quality food. They do not always go because the quality of the food is far superior than other restaurants. But the quality of ingredients always meets their expectations. When they compare them to the term excellence, they are disappointed. The food never looks like the pictures on the menu. But when have you ever been to a restaurant where the food looks the same as on the menu? For them, when evaluating which buzzword to use as a guiding star, its simple: excellence. The corporation can accomplish these goals by operating at a standard that far exceeds customer’s wants and needs.

Keywords: industrial engineering, innovation, management and technology, logistics and scheduling, six sigma

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Authors: Elmabruk Laias

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IEEE Standard 802.16 provides QoS (Quality of Service) for the applications such as Voice over IP, video streaming and high bandwidth file transfer. With the ability of broadband wireless access of an IEEE 802.16 system, a WiMAX TDD frame contains one downlink subframe and one uplink subframe. The capacity allocated to each subframe is a system parameter that should be determined based on the expected traffic conditions. a proper resource allocation scheme for packet transmissions is imperatively needed. In this paper, we present a new resource allocation scheme, called additional bandwidth yielding (ABY), to improve transmission efficiency of an IEEE 802.16-based network. Our proposed scheme can be adopted along with the existing scheduling algorithms and the multi-priority scheme without any change. The experimental results show that by using our ABY, the packet queuing delay could be significantly improved, especially for the service flows of higher-priority classes.

Keywords: IEEE 802.16, WiMAX, OFDMA, resource allocation, uplink-downlink mapping

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Authors: Gagandeep Kaur

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Cloud computing uses various computing resources such as CPU, memory, processor etc. which is used to deliver service over the network and is one of the emerging fields for large scale distributed computing. In cloud computing, execution of large number of tasks with available resources to achieve high performance, minimal total time for completion, minimum response time, effective utilization of resources etc. are the major research areas. In the proposed research, an algorithm has been proposed to achieve high performance in load balancing and resource utilization. The proposed algorithm is used to reduce the makespan, increase the resource utilization and performance cost for independent tasks. Further scheduling metrics based on algorithm in cloud computing has been proposed.

Keywords: resource utilization, response time, load balancing, performance cost

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Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin

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In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.

Keywords: binary cat swarm optimization, binarization methods, metaheuristic, set covering problem

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Tarek Taha Kandil

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In higher education, the use of automated grading systems is on the rise, automating the assessment of students' work and providing practical feedback. Sustainable Grader Scope addresses the environmental impact of these computational tasks. This system uses an AI-powered algorithm and is designed to minimize grading process emissions. It reduces carbon emissions through energy-efficient computing and carbon-conscious scheduling. Students submit their computational workloads to the system, which evaluates submissions using containers and a distributed infrastructure. A carbon-conscious scheduler manages workloads across global campuses, optimizing emissions using real-time carbon intensity data. This ensures the university stays within government-set emission limits while tracking and reducing its carbon footprint.

Keywords: sustainability, green graders, digital sustainable grader scope, environmental responsibility; higher education.

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Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

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This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: hill climbing algorithm, integrated system, mobile web-based, student information system

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Authors: Mohammed Aljoma, Eblal Zakzok

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Safety is a science that seeks to protect and avoid humans from risks in any field and prevent losses in properties and lives as much as possible. On the other hand, occupational safety goals aim to protect workers from risks which can occur during work execution. The main purpose of occupational safety is to ultimately protect people, properties and the environment by reducing accidents and injuries that may cause losses and damages. To achieve this goal, we must remove the direct and indirect reasons which cause accidents and injuries; some of the reasons of accidents are the unsafe cases and inept behavior or both of them. This research focuses on the manner of providing instant protection from the very first beginning to people, properties and the environment by: -Inserting safety demands in the planning and designing works by identifying risk levels in every task of the project, -Using a new risk managing system or modifying or changing a previously-used one.

Keywords: planning, scheduling, risk management, project duration, site safety

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Authors: V. S. S. Kumar, B. Vikram, G. C. S. Reddy

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Time and cost are the two critical objectives of construction project management and are not independent but intricately related. Trade-off between project duration and cost are extensively discussed during project scheduling because of practical relevance. Generally when the project duration is compressed, the project calls for an increase in labor and more productive equipments, which increases the cost. Thus, the construction time-cost optimization is defined as a process to identify suitable construction activities for speeding up to attain the best possible savings in both time and cost. As there is hidden tradeoff relationship between project time and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of compressing the schedule. Different combinations of duration and cost for the activities associated with the project determine the best set in the time-cost optimization. Therefore, the contractors need to select the best combination of time and cost to perform each activity, all of which will ultimately determine the project duration and cost. In this paper, the fuzzy set theory is used to model the uncertainties in the project environment for time-cost trade off analysis.

Keywords: fuzzy sets, uncertainty, qualitative factors, decision making

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Authors: Samia Kouki

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Solving NP-hard combinatorial optimization problems by exact search methods, such as Branch-and-Bound, may degenerate to complete enumeration. For that reason, exact approaches limit us to solve only small or moderate size problem instances, due to the exponential increase in CPU time when problem size increases. One of the most promising ways to reduce significantly the computational burden of sequential versions of Branch-and-Bound is to design parallel versions of these algorithms which employ several processors. This paper describes a parallel Branch-and-Bound algorithm called GALB for solving the classical permutation flowshop scheduling problem as well as its implementation on a Grid computing infrastructure. The experimental study of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.

Keywords: grid computing, permutation flow shop problem, branch and bound, load balancing

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Authors: Wanatchapong Kongkaew

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This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.

Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness

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Authors: Omar Ramzi Jasim, Jalal Sultan Ashour

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Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problems in operation and it can potentially lead to poor customer satisfaction. In this paper, a hybrid evolutionary algorithm (ICA-GA) is presented, which integrates the merits of both imperialist competitive algorithm (ICA) and genetic algorithm (GA) for solving multi-objective MPS problems. In the presented algorithm, the colonies in each empire has be represented a small population and communicate with each other using genetic operators. By testing on 5 production scenarios, the numerical results of ICA-GA algorithm show the efficiency and capabilities of the hybrid algorithm in finding the optimum solutions. The ICA-GA solutions yield the lower inventory level and keep customer satisfaction high and the required overtime is also lower, compared with results of GA and SA in all production scenarios.

Keywords: master production scheduling, genetic algorithm, imperialist competitive algorithm, hybrid algorithm

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Authors: Vaibhav Singh Rajput, Ravi Kumar Jatoth, Nagu Bhookya, Bhasker Boda

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In this paper proportional, integral, derivative (PID) controller is used to control the pitch angle of the aircraft when the elevation angle is changed or modified. The pitch angle is dependent on elevation angle; a change in one corresponds to a change in the other. The PID controller helps in restricted change of pitch rate in response to the elevation angle. The PID controller is dependent on different parameters like Kp, Ki, Kd which change the pitch rate as they change. Various methodologies are used for changing those parameters for getting a perfect time response pitch angle, as desired or wished by a concerned person. While reckoning the values of those parameters, trial and guessing may prove to be futile in order to provide comfort to passengers. So, using some metaheuristic techniques can be useful in handling these errors. Hybrid GA-PSO is one such powerful algorithm which can improve transient and steady state response and can give us more reliable results for PID gain scheduling problem.

Keywords: pitch rate, elevation angle, PID controller, genetic algorithm, particle swarm optimization, phugoid

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Authors: G. Santamato, M. Solazzi, A. Frisoli

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Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: pantograph models, phase plots, structural health monitoring, damage detection

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Authors: Seyed Mahdi Jameii, Arash Nikdel, Seyed Mohsen Jameii

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Energy efficiency is an important issue in the field of Wireless Sensor Networks (WSNs). So, minimizing the energy consumption in this kind of networks should be an essential consideration. Sleep/wake scheduling mechanism is an efficient approach to handling this issue. In this paper, we propose a Genetic Algorithm-based Sleep-Wake up Area Coverage protocol called GA-SWAC. The proposed protocol puts the minimum of nodes in active mode and adjusts the sensing radius of each active node to decrease the energy consumption while maintaining the network’s coverage. The proposed protocol is simulated. The results demonstrate the efficiency of the proposed protocol in terms of coverage ratio, number of active nodes and energy consumption.

Keywords: wireless sensor networks, genetic algorithm, coverage, connectivity

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Authors: Hamed Sarbazy, Zohre Gholipour Haftkhani, Ali Safari, Pejman Hosseiniun

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Scientific and industrial progress in the past two decades has resulted in energy distribution systems based on power electronics, as an enabling technology in various industries and building management systems can be considered. Grading and standardization module power electronics systems and its use in a distributed control system, a strategy for overcoming the limitations of using this system. The purpose of this paper is to investigate strategies for scheduling and control structure of standard modules is a power electronic systems. This paper introduces the classical control methods and disadvantages of these methods will be discussed, The hierarchical control as a mechanism for distributed control structure of the classification module explains. The different levels of control and communication between these levels are fully introduced. Also continue to standardize software distribution system control structure is discussed. Finally, as an example, the control structure will be presented in a DC distribution system.

Keywords: application management, hardware management, power electronics, building blocks

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Authors: Kaddi Mohammed, A. Benatiallah, D. Benatiallah

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Data grid is a technology that has full emergence of new challenges, such as the heterogeneity and availability of various resources and geographically distributed, fast data access, minimizing latency and fault tolerance. Researchers interested in this technology address the problems of the various systems related to the industry such as task scheduling, load balancing and replication. The latter is an effective solution to achieve good performance in terms of data access and grid resources and better availability of data cost. In a system with duplication, a coherence protocol is used to impose some degree of synchronization between the various copies and impose some order on updates. In this project, we present an approach for placing replicas to minimize the cost of response of requests to read or write, and we implement our model in a simulation environment. The placement techniques are based on a cost model which depends on several factors, such as bandwidth, data size and storage nodes.

Keywords: response time, query, consistency, bandwidth, storage capacity, CERN

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Authors: Md. Ahsan Ayub, Kazi A. Kalpoma, Humaira Tasnim Proma, Syed Mehrab Kabir, Rakib Ibna Hamid Chowdhury

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Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework.

Keywords: arc consistency (AC), backjumping algorithm (BJ), backtracking algorithm (BT), constraint satisfaction problem (CSP), forward checking (FC), least constrained values (LCV), maintaining arc consistency (MAC), minimum remaining values (MRV), N-Queens problem

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Authors: Fatmanur Avar, Kubra G. Kostepen, Seda Lafci

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In today’s world, technological innovations have brought out entirely new business understanding. Companies operating in logistics have become more flexible to business trends such as digitalization, innovation, sustainability, flexibility, and productivity. Through the arrival of the fourth industrial revolution called as industry 4.0 approach, the logistics concepts have been redefined. By adopting automated planning and scheduling, organizing and controlling systems such as Transportation Management System (TMS), Enterprise Resource Planning (ERP), warehouse control systems, it will be possible for businesses to be ahead of logistics process. In this research, the aim is to reveal the effects of logistics 4.0 applications for a third party logistics service provider (3PL) located in Turkey. Also, the impacts of logistics 4.0 on key performance indicators (KPI) are examined under the scope of the study. As a methodology, a semi-structured interview is conducted with a global 3PL company and data collected from interviews is analyzed with content analysis. At the end of the analysis, it is presented the effects of logistics 4.0 applications on logistics activities of the company. Limitations and suggestions are also offered.

Keywords: key performance indicators, KPI, logistics activities, logistics 4.0, 3PL

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Authors: Adrian Morris, Rodney Phillips, Mattia Tabacchi

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Minimizing construction noise and vibration impacts is a key challenge for major infrastructure projects in urban environments. Before commencing construction works, Construction Noise and Vibration Management Plan (CNVMP) and Construction Noise and Vibration Impact Statements (CNVIS) are required to be prepared and submitted to the relevant government authorities for review and approval. However, the assessment of potential impacts from work activities at pre-approval stage may be inaccurate as works methodology and scheduling are yet to be determined. In response, noise and vibration management tools have been developed to refine and supplement the CNVIS as works progress. These tools have been successfully implemented in major infrastructure projects allowing contractors to plan and assess construction works in a cost effective and timely manner. As a result, noise and vibration management tools have been incorporated into management plans and are increasingly required by regulators.

Keywords: noise management, environmental noise, infrastructure projects, construction, vibration, cost effective

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Authors: Ajaykumar Kambekar, Nikita Kalantri

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Due to faster urbanization; developing nations will have to look forward towards establishing new planned cities those are environmentally friendly. Due to growth in Information and Communication Technology (ICT), it is evident that the rise of smart cities is witnessed as a promising trend for future growth; however, technology alone cannot make a city as a smart city. Cities must use smart systems to enhance the quality of life of its citizens and to achieve sustainable growth. Recent trends in technology may offer some indication towards harnessing our cities potential as the new engines of sustainable growth. To overcome the problems of mega-urbanization, new concept of smart cities has been introduced. The current research aims to reduce the knowledge gap in urban planning by exploring the concept of smart cities considering sustainability as a major focus. The aim of this paper is to plan for an entire smart city. The paper analyses sustainable development and identifies the key factors for the creation of future smart cities. The study also emphasizes the use of advanced planning and scheduling software such as Microsoft Project (MSP).

Keywords: urbanization, planned cities, information and communication technology, sustainable growth

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Authors: Sanele E. Nene L., Lia M. Hewitt

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Background: Artificial intelligence (AI) has a high value in healthcare, various applications have been developed for the efficiency of clinical operations, such as appointment/surgery scheduling, diagnostic image analysis, prognosis, prediction and management of specific ailments. Purpose: The purpose of this study was to explore, describe, contrast, evaluate, and develop the various leadership strategies as a conceptual framework, applied by public health Operational Managers (OMs) to embrace AI benefits, with the aim to improve the healthcare system in a public hospital. Design and Method: A qualitative, exploratory, descriptive and contextual research design was followed and a descriptive phenomenological approach. Five phases were followed to conduct this study. Phenomenological individual interviews and focus groups were used to collect data and a phenomenological thematic data analysis method was used. Findings and conclusion: Three themes surfaced as the experiences of AI by the OMs; Positive experiences related to AI, Management and leadership processes in AI facilitation, and Challenges related to AI.

Keywords: ambivalence, embracing, Artificial intelligence, public hospital

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Authors: J. Nisar, S. Halim

Abstract:

The additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activity in Precedence Diagram Method (PDM) provides a more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in the PDM network will have an anomalous effect on the critical path and the project completion date. In this study, we classified the critical activities in two groups i.e., 1. activity on single critical path and 2. activity on multi-critical paths, and six classes i.e., normal, reverse, neutral, perverse, decrease-reverse and increase-normal, based on their effects on project duration in PDM. Furthermore, we determined the maximum float of time by which the duration each type of critical activities can be changed without effecting the project duration. This study would help the project manager to clearly understand the behavior of each critical activity on critical path, and he/she would be able to change the project duration by shortening or lengthening activities based on project budget and project deadline.

Keywords: construction management, critical path method, project scheduling network, precedence diagram method

Procedia PDF Downloads 224