• Title/Summary/Keyword: short-term tasks

Search Result 93, Processing Time 0.026 seconds

A Dynamic Buffer Allocation and Substitution Scheme for Efficient Buffer Management (효율적인 버퍼 관리를 위한 동적 버퍼 할달 및 버퍼 교체 기법)

  • Kim, Hyoung-Jin;Ra, In-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.9 no.1
    • /
    • pp.128-133
    • /
    • 2005
  • Respond time and processing rate representing how many tasks can be done during an unit time in a client/server environment are generally use for measuring the performance of computers. In this paper, we suggest a window buffer managing scheme based on a window with many of short-term sliced slots where a media stream is allocated and deallocated into them so that it can maximize the utilization ration of the limited buffer on a multimedia server. And we also propose a buffer substitution scheme for reducing I/O times of a multimedia server by counting re-reference time point about a used block and then it can be reused by the next consecutive media stream.

Solar Energy Prediction using Environmental Data via Recurrent Neural Network (RNN을 이용한 태양광 에너지 생산 예측)

  • Liaq, Mudassar;Byun, Yungcheol;Lee, Sang-Joon
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2019.10a
    • /
    • pp.1023-1025
    • /
    • 2019
  • Coal and Natural gas are two biggest contributors to a generation of energy throughout the world. Most of these resources create environmental pollution while making energy affecting the natural habitat. Many approaches have been proposed as alternatives to these sources. One of the leading alternatives is Solar Energy which is usually harnessed using solar farms. In artificial intelligence, the most researched area in recent times is machine learning. With machine learning, many tasks which were previously thought to be only humanly doable are done by machine. Neural networks have two major subtypes i.e. Convolutional neural networks (CNN) which are used primarily for classification and Recurrent neural networks which are utilized for time-series predictions. In this paper, we predict energy generated by solar fields and optimal angles for solar panels in these farms for the upcoming seven days using environmental and historical data. We experiment with multiple configurations of RNN using Vanilla and LSTM (Long Short-Term Memory) RNN. We are able to achieve RSME of 0.20739 using LSTMs.

The Integration of Adaptive Elements into High-Rise Structures

  • Weidner, Stefanie;Steffen, Simon;Sobek, Werner
    • International Journal of High-Rise Buildings
    • /
    • v.8 no.2
    • /
    • pp.95-100
    • /
    • 2019
  • Whilst most research focuses on the reduction of operative energy use in buildings, the aspect of which (and how many) materials are used is often neglected and poorly explored. However, considering the continuous growth of the global population and the limited availability of resources, it is clear that focusing on operative energy alone is too short-sighted. The tasks lying ahead for architects and engineers cannot be accomplished with conventional methods of construction. With a share of 50-60% of global resource consumption, the building industry has a decisive impact on our environment. If business as usual continues, resources will be significantly depleted in a matter of decades. Therefore, researchers of the University of Stuttgart are investigating the concept of adaptivity as a promising method for saving resources in the built environment. The term adaptivity in the context of building structures was first introduced by Werner Sobek. It describes a method where sensors, actuators and control units are implemented in systems or facades in order to oppose physical impacts in an ideal way. The applicability of this method will be verified on an experimental high-rise building at the University campus in Stuttgart. Thus, this paper describes this innovative research project and depicts the concept of adaptivity in high-rise structures. Furthermore, it gives an overview of potential actuation concepts and the interdisciplinary challenges behind them.

DeepPTP: A Deep Pedestrian Trajectory Prediction Model for Traffic Intersection

  • Lv, Zhiqiang;Li, Jianbo;Dong, Chuanhao;Wang, Yue;Li, Haoran;Xu, Zhihao
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.15 no.7
    • /
    • pp.2321-2338
    • /
    • 2021
  • Compared with vehicle trajectories, pedestrian trajectories have stronger degrees of freedom and complexity, which poses a higher challenge to trajectory prediction tasks. This paper designs a mode to divide the trajectory of pedestrians at a traffic intersection, which converts the trajectory regression problem into a trajectory classification problem. This paper builds a deep model for pedestrian trajectory prediction at intersections for the task of pedestrian short-term trajectory prediction. The model calculates the spatial correlation and temporal dependence of the trajectory. More importantly, it captures the interactive features among pedestrians through the Attention mechanism. In order to improve the training speed, the model is composed of pure convolutional networks. This design overcomes the single-step calculation mode of the traditional recurrent neural network. The experiment uses Vulnerable Road Users trajectory dataset for related modeling and evaluation work. Compared with the existing models of pedestrian trajectory prediction, the model proposed in this paper has advantages in terms of evaluation indicators, training speed and the number of model parameters.

Costs Stemming from Tax Systems: Tax Compliance Costs

  • Mehmet, NAR
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.10 no.2
    • /
    • pp.267-280
    • /
    • 2023
  • The relationship between the state and taxation starts from the establishment of the state. The most important element is the concept of "tax compliance". Tax compliance can be considered as the harmony of state-society relations. However, the concept of tax non-compliance occurs when taxpayers do not fulfill their tax-related tasks as required. Tax noncompliance is just one of the costs that occur in tax systems, and is named "tax compliance cost" in the literature. This study focuses on tax compliance costs because tax compliance costs are the ones taxpayers are personally obliged to deal with. For this purpose, the study investigates costs accruing from tax systems, including efficiency, planning, application, and compliance costs. According to the analysis results, it was concluded that the main reason for fraud in the tax systems is high compliance costs and that tax compliance directly impacts social wealth. Besides, the existence of conditions conducive to tax evasion and tax avoidance in a country, short-term tax policies, belief in the unfairness and inequality of tax systems, inadequacy of audits conducted by tax authorities, insufficiency of pressure and deterrence mechanisms, constantly changing legislation, and the attitudes and perceptions regarding the illegitimacy of the government determine tax compliance.

Bivariate Oscillation Model for Surrogating Climate Change Scenarios in the LCRR basin

  • Lee, Taesam;Ouarda, Taha;Ahn, Yujin
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2021.06a
    • /
    • pp.69-69
    • /
    • 2021
  • From the unprecedented 2011 spring flood, the residens reside by Lake Champlain and Richelieu River encountered enormous damages. The International Joint Committee (IJC) released the Lake Champlain-Richelieu River (LCRR) Plan of Study (PoS). One of the major tasks for the PoS is to investigate the possible scenarios that might happen in the LCRR basin based on the stochastic simulation of the Net Basin Supplies that calculates the amount of flow into the lake and the river. Therefore, the current study proposed a novel apporach that simulate the annual NBS teleconnecting the climate index. The proposed model employed the bivariate empirical decomposition to contamporaneously model the long-term evolution of nonstationary oscillation embeded in the annual NBS and the climate signal (here, Artic Oscillation: AO). In order to represent the variational behavior of NBS correlation structure along with the temporal revolution of the climate index, a new nonstationary parameterization concept is proposed. The results indicate that the proposed model is superior performance in preserving long and short temporal correlation. It can even preserve the hurst coefficient better than any other tested models.

  • PDF

Development of a Short-term Rainfall Forecasting Model Using Weather Radar Data (기상레이더 자료를 이용한 단시간 강우예측모형 개발)

  • Kim, Gwang-Seob; Kim, Jong-Pil
    • Journal of Korea Water Resources Association
    • /
    • v.41 no.10
    • /
    • pp.1023-1034
    • /
    • 2008
  • The size and frequency of the natural disaster related to the severe storms are increased for recent decades in all over the globe. The damage from natural disasters such as typhoon, storm and local severe rainfall is very serious in Korea since they are concentrated on summer season. These phenomena will be more frequent in the future because of the impact of climate change related to increment of $CO_2$ concentration and the global warming. To reduce the damage from severe storms, a short-range precipitation forecasting model using a weather radar was developed. The study was conducted as following four tasks: conversion three-dimensional radar data to two-dimensional CAPPI(Constant Altitude Plan Position Indicator) efficiently, prediction of motion direction and velocity of a weather system, estimation of two-dimensional rainfall using operational calibration. Results demonstrated that two-dimensional estimation using weather radar is useful to analyze the spatial characteristics of local storms. If the precipitation forecasting system is linked to the flood prediction system, it should contribute the flood management and the mitigation of flood damages.

A Study on Policy for the Introduction of BIM in Architectural Service Industry (건축서비스산업 BIM 도입 및 활용을 위한 중장기 정책제안)

  • Kim, Yong Jun;Kim, Hong-Su;Back, Min-Suk
    • Korean Journal of Computational Design and Engineering
    • /
    • v.21 no.4
    • /
    • pp.363-377
    • /
    • 2016
  • The introduction of the BIM into the architectural service industry is currently not being conducted smoothly. The purpose of this research is to, considering the current state of the market, establish long-term strategies that will enable the BIM to successfully settle. The survey has been conducted in target of architects in order to understand pending issues. Additionally, the articles regarding BIM have been researched for the purpose of better understanding the current societal demands. Indicated by survey results, the architects agree to a certain extent upon the need of BIM for architectural designs, yet also express concerns that the BIM introduction does not guarantee betterment in efficiency. The problematic aspects of BIM introduction that have already been discussed in some policy-related studies include a multitude of complicated issues that are unable to be resolved within a short period of time: underdeveloped BIM infra, the limit of BIM software itself, political issues regarding licensing and lack of social awareness. Based on the issues mentioned above, three main areas of focus along with their respective practical strategies and tasks have been designated. Finally, this research has analyzed the current situation and its issues along with the political solutions of 12 projects, amongst which include the standard for plan drawings, licensing system improvement, cost standard and BIM introduction support. Finally this research has analyzed the current situations and its' issues along with the political solutions of 12 projects, amongst them are the standard for plan drawings, licensing system improvement, cost standard and BIM introduction support.

Video Highlight Prediction Using GAN and Multiple Time-Interval Information of Audio and Image (오디오와 이미지의 다중 시구간 정보와 GAN을 이용한 영상의 하이라이트 예측 알고리즘)

  • Lee, Hansol;Lee, Gyemin
    • Journal of Broadcast Engineering
    • /
    • v.25 no.2
    • /
    • pp.143-150
    • /
    • 2020
  • Huge amounts of contents are being uploaded every day on various streaming platforms. Among those videos, game and sports videos account for a great portion. The broadcasting companies sometimes create and provide highlight videos. However, these tasks are time-consuming and costly. In this paper, we propose models that automatically predict highlights in games and sports matches. While most previous approaches use visual information exclusively, our models use both audio and visual information, and present a way to understand short term and long term flows of videos. We also describe models that combine GAN to find better highlight features. The proposed models are evaluated on e-sports and baseball videos.

Quantitative Exposure Assessment of Various Chemical Substances in a Wafer Fabrication Industry Facility

  • Park, Hyun-Hee;Jang, Jae-Kil;Shin, Jung-Ah
    • Safety and Health at Work
    • /
    • v.2 no.1
    • /
    • pp.39-51
    • /
    • 2011
  • Objectives: This study was designed to evaluate exposure levels of various chemicals used in wafer fabrication product lines in the semiconductor industry where work-related leukemia has occurred. Methods: The research focused on 9 representative wafer fabrication bays among a total of 25 bays in a semiconductor product line. We monitored the chemical substances categorized as human carcinogens with respect to leukemia as well as harmful chemicals used in the bays and substances with hematologic and reproductive toxicities to evaluate the overall health effect for semiconductor industry workers. With respect to monitoring, active and passive sampling techniques were introduced. Eight-hour long-term and 15-minute short-term sampling was conducted for the area as well as on personal samples. Results: The results of the measurements for each substance showed that benzene, toluene, xylene, n-butyl acetate, 2-methoxy-ethanol, 2-heptanone, ethylene glycol, sulfuric acid, and phosphoric acid were non-detectable (ND) in all samples. Arsine was either "ND" or it existed only in trace form in the bay air. The maximum exposure concentration of fluorides was approximately 0.17% of the Korea occupational exposure limits, with hydrofluoric acid at about 0.2%, hydrochloric acid 0.06%, nitric acid 0.05%, isopropyl alcohol 0.4%, and phosphine at about 2%. The maximum exposure concentration of propylene glycol monomethyl ether acetate (PGMEA) was 0.0870 ppm, representing only 0.1% or less than the American Industrial Hygiene Association recommended standard (100 ppm). Conclusion: Benzene, a known human carcinogen for leukemia, and arsine, a hematologic toxin, were not detected in wafer fabrication sites in this study. Among reproductive toxic substances, n-butyl acetate was not detected, but fluorides and PGMEA existed in small amounts in the air. This investigation was focused on the air-borne chemical concentrations only in regular working conditions. Unconditional exposures during spills and/or maintenance tasks and by-product chemicals were not included. Supplementary studies might be required.