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Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables

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Journal of Business Economics 2022年第4期92卷 675-706页

作者： Rausch, Theresa Maria Albrecht, Tobias Baier, Daniel University of Bayreuth Universitätsstraße 30 Bayreuth 95447 Germany FIM Research Center University of Bayreuth and Project Group Business & Information Systems Engineering of the Fraunhofer FIT Bayreuth Germany

Modern call centers require precise forecasts of call and e-mail arrivals to optimize staffing decisions and to ensure high customer satisfaction through short waiting times and the availability of qualified agents. In the dynamic environment of multi-channel customer contact, organizational decision-makers often rely on robust but simplistic forecasting methods. Although forecasting literature indicates that incorporating additional information into time series predictions adds value by improving model performance, extant research in the call center domain barely considers the potential of sophisticated multivariate models. Hence, with an extended dynamic harmonic regression (DHR) approach, this study proposes a new reliable method for call center arrivals’ forecasting that is able to capture the dynamics of a time series and to include contextual information in form of predictor variables. The study evaluates the predictive potential of the approach on the call and e-mail arrival series of a leading German online retailer comprising 174 weeks of data. The analysis involves time series cross-validation with an expanding rolling window over 52 weeks and comprises established time series as well as machine learning models as benchmarks. The multivariate DHR model outperforms the compared models with regard to forecast accuracy for a broad spectrum of lead times. This study further gives contextual insights into the selection and optimal implementation of marketing-relevant predictor variables such as catalog releases, mail as well as postal reminders, or billing cycles. © 2021, The Author(s).

关键词： Call center arrivals Customer relationship management Dynamic harmonic regression Forecasting Machine learning Time series analysis

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Calibration of Fiber-Optic Time Synchronization System over 800km

Calibration of Fiber-Optic Time Synchronization System over ...

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2023 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium, EFTF/IFCS 2023

作者： Dong, Jiameng Wang, Zhaohui Zhang, Rui Yu, Song Luo, Bin Guo, Hong School of Electronic Engineering State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China School of Electronics Center for Quantum Information Technology Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks Beijing China

ISBN: (纸本)9798350311426

Due to the excellent performance in accuracy and stability, fiber-optic time synchronization is becoming a key technology in the field of time-frequency metrology. And the accuracy of fiber-optic time synchronization system mainly depends on asymmetry calibration. Here we study the calibration of time synchronization system over 800km laboratory fiber link. Asymmetry caused by chromatic dispersion, bidirectional EDFAs, sending and receiving devices are investigated. After calibration, the residual of clock difference between two sites is 56.80ps, and the timing jitter is 33.91ps. By further optimizing the whole system and the method of calibration, a system with accuracy better than 50ps over thousands of kilometers fiber link is expected to be obtained in the future. © 2023 IEEE.

关键词： accuracy asymmetry calibration fiber link time synchronization system

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QoS Prediction Model of Cloud Services Based on Deep Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 564-566页

作者： WenJun Huang PeiYun Zhang YuTong Chen MengChu Zhou Yusuf Al-Turki Abdullah Abusorrah Nanjing University of Information Science&Technology School of Computer and SoftwareNanjingChina IEEE New Jersey Institute of Technology Helen and John C.Hartmann Department of Electrical and Computer EngineeringNewarkUSA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Dear editor,This letter presents a deep learning-based prediction model for the quality-of-service(QoS)of cloud ***,to improve the QoS prediction accuracy of cloud services,a new QoS prediction model is proposed,which is based on multi-staged multi-metric feature fusion with individual *** multi-metric features include global,local,and individual *** results show that the proposed model can provide more accurate QoS prediction results of cloud services than several state-of-the-art methods.

关键词： services Services individual

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Enhanced Multi-Agent Proximal Policy Optimization for Multi-UAV Target Offensive-Defensive Decision 42

Enhanced Multi-Agent Proximal Policy Optimization for Multi-...

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42nd Chinese Control Conference, CCC 2023

作者： Zheng, Yifan Xin, Bin Jiao, Keming Zhao, Zhixin Wang, Yuyang Zhao, Yunming School of Electronics and Information Engineering Tongji University Shanghai201804 China School of Automation Beijing Institute of Technology Beijing100081 China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789887581543

Autonomous collaborative decision-making is the key technology to achieve large-scale unmanned combat. Focus on the problem of multiple unmanned aerial vehicles' cooperative decision in target offensive and defensive combat, a multi-agent deep reinforcement learning (MADRL) based decision framework is proposed in this paper. Firstly, the simulation environment with a high-fidelity fixed-wing motion model is built. Secondly, to address the issue of high-dimension state space and credit assignment under a multi-agent environment, an enhanced multi-agent proximal policy optimization with mean-field counterfactual advantage (MAPPO - MFCOA) is proposed. Finally, the results of simulation experiments will verify the performance of the proposed approach. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Reinforcement learning

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Managing the Inner Workings of Collective Intelligence Approaches for Wicked Problems – An Assessment Model and Evaluation

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Communications of the Association for information systems 2023年 52卷 1-1页

作者： Gimpel, Henner Laubacher, Robert Schoch, Manfred Parak, Dominik Wöhl, Moritz University of Hohenheim FIM Research Center for Information Management Fraunhofer Institute for Applied Information Technology FIT Branch Business & Information Systems Engineering Germany Center for Collective Intelligence Massachusetts Institute of Technology United States Dominik Parak University of Augsburg Germany University of Augsburg FIM Research Center for Information Management Fraunhofer Institute for Applied Information Technology FIT Branch Business & Information Systems Engineering Germany

Ill-defined and complex problems that affect multiple stakeholders with potentially conflicting perspectives are often referred to as wicked problems. The utilization of collective intelligence (CI) via web-based platforms is a promising approach for addressing such wicked problems. The management of these information systems would benefit from evidence-based decision support regarding facilitation and improvement efforts. However, to date, there is no suitable model to guide such efforts. Existing approaches address specific applications or cover certain assessment areas but do not provide a holistic perspective. Meanwhile, research offers substantial insights into best practices for addressing wicked problems and running CI applications. This paper develops an assessment model comprising five central success dimensions for information systems that address wicked problems. Their subdimensions and associated measurement metrics allow for evidence-driven facilitation and improvement of CI applications for wicked problems. Apart from the model’s capability to improve future runs and processes, it also offers the potential to provide immediate insights for facilitation efforts during runtime. The model was validated with a platform dealing with the assessment of risks presented by global climate change. This evaluation generated strong evidence for the model’s applicability and usefulness. © 2023 by the Association for information systems.

关键词： information systems

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Micromesh reinforced strain sensor with high stretchability and stability for full-range and periodic human motions monitoring

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InfoMat 2024年第4期6卷 124-139页

作者： Haidong Liu Chang Liu Jinan Luo Hao Tang Yuanfang Li Houfang Liu Jingzhi Wu Fei Han Zhiyuan Liu Jianhe Guo Rongwei Tan Tian-Ling Ren Yancong Qiao Jianhua Zhou School of Biomedical Engineering Shenzhen Campus of Sun Yat-sen UniversityShenzhenGuangdongthe People's Republic of China Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province School of Biomedical EngineeringSun Yat-sen UniversityGuangzhouthe People's Republic of China School of Integrated Circuits and Beijing National Research Center for Information Science and Technology(BNRist) Tsinghua UniversityBeijingthe People's Republic of China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences(CAS)Shenzhenthe People's Republic of China Guangdong Engineering Technology Research Center of Implantable Medical Polymer Shenzhen Lando Biomaterials Co.Ltd.Shenzhenthe People's Republic of China

The development of strain sensors with high stretchability and stability is an inevitable requirement for achieving full-range and long-term use of wearable electronic ***,a resistive micromesh reinforced strain sensor(MRSS)with high stretchability and stability is prepared,consisting of a laser-scribed graphene(LSG)layer and two styrene-block-poly(ethylene-ran-butylene)-block-poly-styrene micromesh layers embedded in *** micromesh reinforced structure endows the MRSS with combined characteris-tics of a high stretchability(120%),excellent stability(with a repetition error of 0.8%after 11000 cycles),and outstanding sensitivity(gauge factor up to 2692 beyond 100%).Impressively,the MRSS can still be used continauously within the working range without damage,even if stretched to 300%.Furthermore,compared with different structure sensors,the mechanism of the MRSS with high stretchability and stability is ***'s more,a multilayer finite element model,based on the layered structure of the LSG and the morphology of the cracks,is proposed to investigate the strain sensing behavior and failure mechanism of the ***,due to the outstanding performance,the MRSS not only performes well in monitoring full-range human motions,but also achieves intelligent recognitions of various respiratory activities and ges-tures assisted by neural network algorithms(the accuracy up to 94.29%and 100%,respectively).This work provides a new approach for designing high-performance resistive strain sensors and shows great potential in full-range and long-term intelligent health management and human-machine interac-tions applications.

关键词： flexible strain sensor excellent stretchability and stability layered laser-scribed graphene micromesh reinforced structure multilayer finite element model

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Unlocking enhanced photo-Fenton,night-Fenton,and photocatalytic activities of dual Z-scheme MoS_(2)/WO_(3-x)/Ag_(2)S core-shell structure via defect engineering

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Journal of Materials Science & Technology 2024年第30期197卷 160-170页

作者： Muhammad Abbas Kashif Hussain Navid Hussain Shah Mubashar Ilyas Rabia Batool M.Ashfaq Ahmad Yanyan Cui Yaling Wang Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China THz Technical Research Center Shenzhen Key Laboratory of Micro-Nano Photonic Information TechnologyKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen UniversityTHz Technical Research Center of Shenzhen UniversityShenzhen 518060China Key Laboratory of Clusters Science of Ministry of Education School of Chemistry Beijing Institute of TechnologyBeijing 100081China Department of Physics University of LahoreLahorePakistan CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety National Center for Nanoscience and Technology of ChinaBeijing 100190China Department of Physics COMSATS University IslamabadLahore CampusLahorePakistan

Memory catalysis and conventional Fenton reactions are intended to counteract prevailing energy and environmental crises;however,poor performance and the need for UV irradiation question their ***,we demonstrate defect-engineered,dual Z-scheme MoS_(2)/WO_(3-x)/Ag_(2)S exhibiting enhanced photo-Fenton(PFR),night-Fenton(NFR),and photocatalytic activities(PR)against tetracycline(TC)and Rhodamine B(RhB).Defects enable the catalyst to store ample electrons just like metals,which play a vi-tal role by exciting H2 O2 during Fenton *** removed 91.54%,76.43%,and 83.39%TC(40 mg L^(-1))in 100 min and registered degradation rate constants of 0.05379,0.02858,and 0.04133 min^(-1)against RhB(20 mg L^(-1))during PFR,NFR,and PR *** total organic carbon(TOC)removal rates reached 58.56%and 60.88%during TC and RhB degradations in PFR,*** and Liquid EPR analy-sis shows it can excite H_(2)O_(2)to carry Fenton reactions with and without *** demonstrates wide pH adaptability and tremendous potential to simultaneously counter energy and environmental crises.

关键词： Fenton reaction Photolysis Core-shell Dual Z-scheme TC WO_(3-x)

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An Intelligent Deterministic Scheduling Method for Ultralow Latency Communication in Edge Enabled Industrial Internet of Things

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IEEE Transactions on Industrial Informatics 2023年第2期19卷 1756-1767页

作者： Lu, Yinzhi Yang, Liu Yang, Simon X. Hua, Qiaozhi Sangaiah, Arun Kumar Guo, Tan Yu, Keping School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada Computer School Hubei University of Arts and Science Xiangyang441000 China Future Technology Research Center National Yunlin University of Science and Technology Douliu City64002 Taiwan Graduate School of Science and Engineering Hosei University Tokyo184-8584 Japan Riken Center for Advanced Intelligence Project Riken Tokyo103-0027 Japan

Edge enabled Industrial Internet of Things (IIoT) platform is of great significance to accelerate the development of smart industry. However, with the dramatic increase in real-time IIoT applications, it is a great challenge to support fast response time, low latency, and efficient bandwidth utilization. To address this issue, time sensitive network (TSN) is recently researched to realize low latency communication via deterministic scheduling. To the best of our knowledge, the combinability of multiple flows, which can significantly affect the scheduling performance, has never been systematically analyzed before. In this article, we first analyze the combinability problem. Then, a noncollision theory based deterministic scheduling (NDS) method is proposed to achieve ultralow latency communication for the time-sensitive flows. Moreover, to improve bandwidth utilization, a dynamic queue scheduling (DQS) method is presented for the best-effort flows. Experiment results demonstrate that NDS/DQS can well support deterministic ultralow latency services and guarantee efficient bandwidth utilization. © 2005-2012 IEEE.

关键词： Bandwidth

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Bacterial population dynamics and biosafety assessment in a closed Bioregenerative Life Support System during the “Lunar Palace 365” experiment

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Science China Life Sciences 2025年

作者： Yuming Fu Yueying Lu Jianlou Yang Hong Liu Key Laboratory of Biomechanics and Mechanobiology (Beihang University) Ministry of EducationKey Laboratory of Innovation and Transformation of Advanced Medical DevicesMinistry of Industry and Information TechnologyNational Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering)School of Biological Science and Medical EngineeringBeihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang University International Joint Research Center of Aerospace Biotechnology&Medical Engineering Beihang University School of Sport Management Shandong Sport University Innovation Center for Medical Engineering&Engineering Medicine Hangzhou International Innovation InstituteBeihang University

Our study investigates the dynamic variation of bacterial populations within the Bioregenerative Life Support System(BLSS), a critical component for sustainable habitats in extraterrestrial environments supporting human survival. We utilized the ground-based BLSS test platform, referred to as “Lunar Palace 1”(LP1), to examine bacterial dynamics in an ecosystem integrating plant production, human cultivation, and equipment maintenance. Our findings reveal distinct bacterial compositions among crew members and functional areas within the LP1 system while preserving temporal stability across the 370-day experiment. Importantly, we observed a low abundance of potential pathogens, minimal antibiotic resistance, and negligible impact of the isolated bacterial strains on equipment materials, suggesting favorable biosafety attributed to plant integration. Our work enhances the understanding of microbial communities in BLSS and underscores the importance of incorporating green plants to bolster environmental biosafety and sustainability in long-term space exploration missions.

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A Novel Multi-Modal Deep Learning Method for Fish's Appetite Detection

A Novel Multi-Modal Deep Learning Method for Fish's Appetite...

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2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： D'Sky, Agape Syafalni, Infall Sutisna, Nana Hariyanto, Hadi Adiono, Trio Sumiarsih, Eni School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia University Center of Excellence on Microelectronics Bandung Institute of Technology Indonesia Telkom University Department of Information Systems Indonesia University of Riau Department of Water Resource Management Indonesia

ISBN: (纸本)9798350381290

In aquaculture, feeding cost usually takes a lot from the total budget. However, a significant portion of the feed often gets uneaten by the fish. To overcome this problem, many ways have been developed using artificial intelligence to detect fish's appetite levels. In this paper, a deep learning model using multi-modal sensors is implemented to detect fish's appetite level based on its visual and the aquarium's water movement. We propose the combination R(2+1)D-CNN and 1D-ANN to process the sensor data, in the form of video streams and accelerometer signals, respectively. Based on the result, this model significantly increases the accuracy of the inference (from 86.71% to 91.84% testing accuracy) without adding many learning parameters (from 1,777,186 to 1,833,008 parameters), compared to the model using a single-modal deep learning model with the camera. © 2023 IEEE.

关键词： Fish

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