• Title/Summary/Keyword: Two-phase Approach

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Electric Arc Furnace Voltage Flicker Mitigation by Applying a Predictive Method with Closed Loop Control of the TCR/FC Compensator

  • Kiyoumarsi, Arash;Ataei, Mohhamad;Hooshmand, Rahmat-Allah;Kolagar, Arash Dehestani
    • Journal of Electrical Engineering and Technology
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    • v.5 no.1
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    • pp.116-128
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    • 2010
  • Modeling of the three phase electric arc furnace and its voltage flicker mitigation are the purposes of this paper. For modeling of the electric arc furnace, at first, the arc is modeled by using current-voltage characteristic of a real arc. Then, the arc random characteristic has been taken into account by modulating the ac voltage via a band limited white noise. The electric arc furnace compensation with static VAr compensator, Thyristor Controlled Reactor combined with a Fixed Capacitor bank (TCR/FC), is discussed for closed loop control of the compensator. Instantaneous flicker sensation curves, before and after accomplishing compensation, are measured based on IEC standard. A new method for controlling TCR/FC compensator is proposed. This method is based on applying a predictive approach with closed loop control of the TCR/FC. In this method, by using the previous samples of the load reactive power, the future values of the load reactive power are predicted in order to consider the time delay in the compensator control. Also, in closed loop control, two different approaches are considered. The former is based on voltage regulation at the point of common coupling (PCC) and the later is based on enhancement of power factor at PCC. Finally, in order to show the effectiveness of the proposed methodology, the simulation results are provided.

The Development of a Computer-Assisted HACCP Program for the Microbiological Quality Assurance in Hospital Foodservice Operations (병원급식의 미생물적 품질보증을 위한 HACCP 전산프로그램의 개발)

  • Kwak, Tong-Kyung;Ryu, Kyung;Choi, Seong-Kyung
    • Journal of the Korean Society of Food Culture
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    • v.11 no.1
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    • pp.107-121
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    • 1996
  • This study was carried out to develop the computer-assisted Hazard Analysis and Critical Control Point (HACCP) program for a systematic approach to the identification, assessment and control of hazards for foodservice manager to assure the microbiological quality of food in hospital foodservice operations. Sanitation practices were surveyed and analyzed in the dietetic department of 4 hospitals. Among them, one 762-bed general hospital was selected as standard model to develop computer-assisted HACCP program. All data base files and processing programs were created by using Foxpro package for easy access of HACCP concept. HACCP program was developed based on the methods suggested by NACMCF, IAMFES and Bryan. This program consisted of two parts: the pre-stage for HACCP study and the implementation stage of the HACCP system. 1. Pre-stage for HACCP study includes the selection of menu item, the development of the HACCP recipe, the construction of a product flow diagram, and printing the HACCP recipe and a product flow diagram. A menu item for HACCP study can be selected from the menu item lists classified by cooking methods. HACCP recipe includes ingredients, their amount and cooking procedure. A flow diagram is constructed based on the HACCP recipe. The HACCP recipe and a product flow diagram are printed out. 2. Implementation of HACCP study includes the identification of microbiological hazards, the determination of critical control points, the establishment of control methods of each hazard, and the complementation of data base file. Potentially hazardous ingredients are determined and microbiological hazards are identified in each phase of the product flow. Critical control points (CCPs) are identified by applying CCP decision trees for ingredients and each process stage. After hazards and CCPs are identified, criteria, monitoring system, corrective action plan, record-keeping system and verification methods are established. When the HACCP study is complemented, HACCP study result forms are printed out. HACCP data base file can be either added, corrected or deleted.

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Symbol recognition using vectorial signature matching for building mechanical drawings

  • Cho, Chi Yon;Liu, Xuesong;Akinci, Burcu
    • Advances in Computational Design
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    • v.4 no.2
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    • pp.155-177
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    • 2019
  • Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

Bright Light Therapy in the Morning or at Mid-Day in the Treatment of Non-Seasonal Bipolar Depressive Episodes (LuBi): Study Protocol for a Dose Research Phase I / II Trial

  • Geoffroy, Pierre Alexis;El Abbassi, El Mountacer Billah;Maruani, Julia;Etain, Bruno;Lejoyeux, Michel;Amad, Ali;Courtet, Philippe;Dubertret, Caroline;Gorwood, Philip;Vaiva, Guillaume;Bellivier, Frank;Chevret, Sylvie
    • Psychiatry investigation
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    • v.15 no.12
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    • pp.1188-1202
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    • 2018
  • Objective This study protocol aims to determine, using a rigorous approach in patients with bipolar disorder (BD) and non-seasonal major depressive episode (MDE), the characteristics of bright light therapy (BLT) administration (duration, escalation, morning and mid-day exposures) depending on the tolerance (hypomanic symptoms). Methods Patients with BD I or II and treated by a mood stabilizer are eligible. After 1 week of placebo, patients are randomized between either morning or mid-day exposure for 10 weeks of active BLT with glasses using a dose escalation at 7.5, 10, 15, 30 and 45 minutes/day. A further follow-up visit is planned 6 months after inclusion. Patients will be included by cohorts of 3, with at least 3 days of delay between them, and 1 week between cohorts. If none meet a dose limiting toxicity (DLT; i.e hypomanic symptoms), the initiation dose of the next cohort will be increased. If one patient meet a DLT, an additionnal cohort will start at the same dose. If 2 or 3 patients meet a DLT, from the same cohort or from two cohorts at the same dose initiation, the maximum tolerated dose is defined. This dose escalation will also take into account DLTs observed during the intra-subject escalation on previous cohorts, with a "Target Ceiling Dose" defined if 2 DLTs occured at a dose. Discussion Using an innovative and more ergonomic device in the form of glasses, this study aims to better codify the use of BLT in BD to ensure a good initiation and tolerance.

Behavior of a Shape Memory Alloy Actuator with Composite Strip and Spring (복합재료 스트립과 스프링을 갖는 형상기억합금 작동기의 거동)

  • Heo, Seok;Hwang, Do-Yeon;Choi, Jae-Won;Park, Hoon-Cheol;Goo, Nam-Seo
    • Composites Research
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    • v.22 no.2
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    • pp.37-42
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    • 2009
  • This paper presents an experimental approach to design a bending-type actuator by using a shape memory alloy wire (SMA), composite strip, and spring. The SMA wire is attached to two edges of the bent strip to apply pre-stress to the SMA wire. The spring is used to provide recovery force right after actuation of the SMA wire. To investigate thermo-mechanical characteristics of the SMA wire, a series of DSC tests have been conducted and tensile tests under various levels of pre-stress and input power have been performed. Based on the measured properties of the SMA wire, bending-type actuators are designed and tested for different combination of strip, number of springs, and input power. It has been found that a bending-type actuator with a proper combination shows fast actuation performance and low power consumption.

Mobile Robot Localization in Geometrically Similar Environment Combining Wi-Fi with Laser SLAM

  • Gengyu Ge;Junke Li;Zhong Qin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.5
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    • pp.1339-1355
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    • 2023
  • Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

A Novel Two-Stage Training Method for Unbiased Scene Graph Generation via Distribution Alignment

  • Dongdong Jia;Meili Zhou;Wei WEI;Dong Wang;Zongwen Bai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.12
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    • pp.3383-3397
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    • 2023
  • Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

Investigation of the behavior of an RC beam strengthened by external bonding of a porous P-FGM and E-FGM plate in terms of interface stresses

  • Zahira Sadoun;Riadh Bennai;Mokhtar Nebab;Mouloud Dahmane;Hassen Ait Atmane
    • Structural Monitoring and Maintenance
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    • v.10 no.4
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    • pp.315-337
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    • 2023
  • During the design phase, it is crucial to determine the interface stresses between the reinforcing plate and the concrete base in order to predict plate end separation failures. In this work, a simple theoretical study of interface shear stresses in beams reinforced with P-FGM and E-FGM plates subjected to an arbitrarily positioned point load, or two symmetrical point loads, was presented using the linear elastic theory. The presence of pores in the reinforcing plate distributed in several forms was also taken into account. For this purpose, we analyze the effects of porosity and its distribution shape on the interracial normal and shear stresses of an FGM beam reinforced with an FRP plate under different types of load. Comparisons of the proposed model with existing analytical solutions in the literature confirm the feasibility and accuracy of this new approach. The influence of different parameters on the interfacial behavior of reinforced concrete beams reinforced with functionally graded porous plates is further examined in this parametric study using the proposed model. From the results obtained in this study, we can say that interface stress is significantly affected by several factors, including the pores present in the reinforcing plate and their distribution shape. Additionally, we can conclude from this study that reinforcement systems with composite plates are very effective in improving the flexural response of reinforced RC beams.

IFC Data Schema Extension for Railway Track Facility Management

  • Zeru Liu;Wuhao Huang;Hejun Xu;Sining Li;Jung In Kim
    • International conference on construction engineering and project management
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    • 2024.07a
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    • pp.550-557
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    • 2024
  • Railway track facility management (FM) is an intricate and multifaceted discipline that necessitates precise data management and scheduling for ensuring the safety and efficiency of railway operations. Although the Industry Foundation Classes (IFC) version 4.3 has incorporated railway infrastructure into its data schema, it still falls short in catering to the specialized needs of track FM. This paper presents an exhaustive extension to the IFC schema, specifically designed to address the challenges and complexities inherent in railway track FM. A two-step approach was employed in the development of this extension. The initial phase involves the development of a Unified Modeling Language (UML)-based conceptual model, encapsulating four pivotal elements: "component" for track asset and condition identification, "action" for the related tasks during track FM, "resource" for required materials and equipment as well as involved actors, and "operation" for track operation information capturing. This conceptual model serves as an intricate blueprint, offering a comprehensive structure for various FM facets. Thus, the proposed IFC extension is developed and aligned consistently with the conceptual model, forming an integrated, interoperable data management framework that can be easily adapted into the openBIM environment. The efficacy and applicability of the proposed extension are substantiated through real-world case studies, thereby demonstrating its capability to significantly enhance data visualization, interoperability, and overall decision-making in railway track FM.

A hybrid algorithm for the synthesis of computer-generated holograms

  • Nguyen The Anh;An Jun Won;Choe Jae Gwang;Kim Nam
    • Proceedings of the Optical Society of Korea Conference
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    • 2003.07a
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    • pp.60-61
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    • 2003
  • A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

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