scholarly journals How the Duration of the Learning Period Affects the Performance of Random Gradient Selection Hyper-Heuristics

2020 ◽  
Vol 34 (03) ◽  
pp. 2376-2383
Author(s):  
Andrei Lissovoi ◽  
Pietro Oliveto ◽  
John Alasdair Warwicker
Keyword(s):  
Local Search ◽  
Search Space ◽  
Black Box ◽  
Benchmark Function ◽  
Low Level ◽  
Expected Time ◽  
Realistic Problem ◽  
Different Characteristics ◽  
The Impact

Recent analyses have shown that a random gradient hyper-heuristic (HH) using randomised local search (RLSk) low-level heuristics with different neighbourhood sizes k can optimise the unimodal benchmark function LeadingOnes in the best expected time achievable with the available heuristics, if sufficiently long learning periods τ are employed. In this paper, we examine the impact of the learning period on the performance of the hyper-heuristic for standard unimodal benchmark functions with different characteristics: Ridge, where the HH has to learn that RLS1 is always the best low-level heuristic, and OneMax, where different low-level heuristics are preferable in different areas of the search space. We rigorously prove that super-linear learning periods τ are required for the HH to achieve optimal expected runtime for Ridge. Conversely, a sub-logarithmic learning period is the best static choice for OneMax, while using super-linear values for τ increases the expected runtime above the asymptotic unary unbiased black box complexity of the problem. We prove that a random gradient HH which automatically adapts the learning period throughout the run has optimal asymptotic expected runtime for both OneMax and Ridge. Additionally, we show experimentally that it outperforms any static learning period for realistic problem sizes.

Impact of Chatbot in Transforming the Face of Retailing- An Empirical Model of Antecedents and Outcomes

2019 ◽  
Vol 12 ◽  
Author(s):  
Kumari Anshu ◽  
Loveleen Gaur ◽  
Arun Solanki
Keyword(s):  
Research Work ◽  
Shopping Behavior ◽  
Model Framework ◽  
Shopping Experience ◽  
The Face ◽  
Strongly Agree ◽  
Different Characteristics ◽  
Work Done ◽  
The Impact ◽  
Self Administered Questionnaire

Chatbot has emerged as a significant resolution to the swiftly growing customer caredemands in recent times. Chatbot has emerged as one of the biggest technological disruption. Simply speaking, it is a software agent facilitating interaction between computers and humans in natural language. So basically, it is a simulated, intellectual dialogue agent functional in a range of consumer engagement circumstances. It is the easiest and simplest means enable interaction between the retailers and the customers. </p><p> • Purpose- Most of the research work done in this field is concerned with their technical aspects. The recent research on chatbot pay little attention to the impact it is creating on users’ experience. Through this work, author is making an effort to know the customer-oriented impact that the chatbot bear on the shoppers. The purpose of this study is to develop and empirically test a framework that identify the customer oriented attributes of chatbot and impact of these attributes on customers. </p><p> • Objectives- The study intends to bridge the gap between concepts and actual attributes and applications on the subject of Chatbot. The following research objectives can address the various aspects of Chatbot affecting the different characteristics of consumers shopping behaviors: a) Identify the various attributes of chatbot that bears an impression on consumer shopping behavior. b) Evaluate the impact of chatbot on consumer shopping behavior that leads to the development of chatbot usage and adoption among the customer. </p><p> • Design/Methodology/Approach – For the purpose of analysis, author has administered Factor analysis and Multiple regression using SPSS version 23 for identification of various attributes of Chatbot and knowing their impact on shoppers. A self-administered questionnaire from the review of literature is developed. Industry experts in the field of retailing and academician evaluate the questionnaire. Primary information from the respondents is gathered using this questionnaire. The questionnaire comprises of Likert scale on a scale of 1 to 5 where 1 stands for strongly disagree and 5 stands for strongly agree. Data is collected from 126 respondents, out of which 111 respondents were finally considered for study and analysis purpose. </p><p> • Findings – The empirical results show that the study identifies various attributes of chatbot like Trust, Usefulness, Satisfaction, Readiness to Use and Accessibility. It is also found that chatbot is really influencing the customers in providing them with shopping experience, which can be very helpful to the businesses for increasing the sales and creating repurchase intention among the customers. </p><p> • Originality/value – The recent research on chatbot pay little attention to the impact it is creating on customers who are actually interacting with it on regular basis. The research paper extends information for understanding and appreciating the customer oriented attributes of artificially intelligent Chatbot. In this regard, the author has developed a model framework and proposed the attributes identified. Through the work, author is also making an effort to test empirically the impact of the identified attributes on the shoppers.

Incentivizing Peace

2018 ◽  
Author(s):  
Jaroslav Tir ◽  
Johannes Karreth
Keyword(s):  
World War Ii ◽  
Civil Wars ◽  
Full Scale ◽  
Armed Conflicts ◽  
East Timor ◽  
Low Level ◽  
Self Interest ◽  
The World ◽  
Economic Tools ◽  
The Impact

Civil wars are one of the most pressing problems facing the world. Common approaches such as mediation, intervention, and peacekeeping have produced some results in managing ongoing civil wars, but they fall short in preventing civil wars in the first place. This book argues for considering civil wars from a developmental perspective to identify steps to assure that nascent, low-level armed conflicts do not escalate to full-scale civil wars. We show that highly structured intergovernmental organizations (IGOs, e.g. the World Bank or IMF) are particularly well positioned to engage in civil war prevention. Such organizations have both an enduring self-interest in member-state peace and stability and potent (economic) tools to incentivize peaceful conflict resolution. The book advances the hypothesis that countries that belong to a larger number of highly structured IGOs face a significantly lower risk that emerging low-level armed conflicts on their territories will escalate to full-scale civil wars. Systematic analyses of over 260 low-level armed conflicts that have occurred around the globe since World War II provide consistent and robust support for this hypothesis. The impact of a greater number of memberships in highly structured IGOs is substantial, cutting the risk of escalation by over one-half. Case evidence from Indonesia’s East Timor conflict, Ivory Coast’s post-2010 election crisis, and from the early stages of the conflict in Syria in 2011 provide additional evidence that memberships in highly structured IGOs are indeed key to understanding why some low-level armed conflicts escalate to civil wars and others do not.

scholarly journals Time Granularity Impact on Propagation of Disruptions in a System-of-Systems Simulation of Infrastructure and Business Networks

2021 ◽  
Vol 18 (8) ◽  
pp. 3922
Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann
Keyword(s):  
Recovery Time ◽  
System Of Systems ◽  
Future Research ◽  
Business Networks ◽  
Simulation Experiments ◽  
Huge Impact ◽  
High Level ◽  
Systems Simulation ◽  
Different Characteristics ◽  
The Impact

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

scholarly journals Simulation of Energy Absorption Performance of the Couplers in Urban Railway Vehicles during a Heavy Collision

Machines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 91
Author(s):  
Sunghyun Lim ◽  
Yong-hyeon Ji ◽  
Yeong-il Park
Keyword(s):  
Reaction Force ◽  
Crash Test ◽  
Railway Vehicle ◽  
Buffer System ◽  
Railway Vehicles ◽  
Hydraulic Shock Absorber ◽  
Coupling Buffer ◽  
Absorption Performance ◽  
Different Characteristics ◽  
The Impact

Railway vehicles are generally operated by connecting several vehicles in a row. Mechanisms connecting railway vehicles must also absorb front and rear shock loads that occur during a train’s operation. To minimize damage, rail car couplers are equipped with a buffer system that absorbs the impact of energy. It is difficult to perform a crash test and evaluate performance by applying a buffer to an actual railway vehicle. In this study, a simulation technique using a mathematical buffer model was introduced to overcome these difficulties. For this, a model of each element of the buffer was built based on the experimental data for each element of the coupling buffer system and a collision simulation program was developed. The buffering characteristics of a 10-car train colliding at 25 km/h were analyzed using a developed simulator. The results of the heavy collision simulation showed that the rubber buffer was directly connected to the hydraulic shock absorber in a solid contact state, and displacement of the hydraulic buffer hardly occurred despite the increase in reaction force due to the high impact speed. Since the impact force is concentrated on the vehicle to which the collision is applied, it may be appropriate to apply a deformation tube with different characteristics depending on the vehicle location.

scholarly journals Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

2020 ◽  
Vol 20 (8) ◽  
pp. 5019-5033 ◽  
Author(s):  
Yuning Xie ◽  
Gehui Wang ◽  
Xinpei Wang ◽  
Jianmin Chen ◽  
Yubao Chen ◽  
...  
Keyword(s):  
Atmospheric Aerosols ◽  
Ammonia Concentration ◽  
Historical Record ◽  
Molar Ratio ◽  
Effective Control ◽  
Nitrate Content ◽  
Chinese Government ◽  
Low Level ◽  
The Impact ◽  
Pollution Episodes

Abstract. The Chinese government has exerted strict emission controls to mitigate air pollution since 2013, which has resulted in significant decreases in the concentrations of air pollutants such as SO2. Strict pollution control actions also reduced the average PM2.5 concentration to the low level of 39.7 µg m−3 in urban Beijing during the winter of 2017. To investigate the impact of such changes on the physiochemical properties of atmospheric aerosols in China, we conducted a comprehensive observation focusing on PM2.5 in Beijing during the winter of 2017. Compared with the historical record (2014–2017), SO2 decreased to the low level of 3.2 ppbv in the winter of 2017, but the NO2 level was still high (21.4 ppbv in the winter of 2017). Accordingly, the contribution of nitrate (23.0 µg m−3) to PM2.5 far exceeded that of sulfate (13.1 µg m−3) during the pollution episodes, resulting in a significant increase in the nitrate-to-sulfate molar ratio. The thermodynamic model (ISORROPIA II) calculation results showed that during the PM2.5 pollution episodes particle pH increased from 4.4 (moderate acidic) to 5.4 (more neutralized) when the molar ratio of nitrate to sulfate increased from 1 to 5, indicating that aerosols were more neutralized as the nitrate content elevated. Controlled variable tests showed that the pH elevation should be attributed to nitrate fraction increase other than crustal ion and ammonia concentration increases. Based on the results of sensitivity tests, future prediction for the particle acidity change was discussed. We found that nitrate-rich particles in Beijing at low and moderate humid conditions (RH: 20 %–50 %) can absorb twice the amount of water that sulfate-rich particles can, and the nitrate and ammonia with higher levels have synergetic effects, rapidly elevating particle pH to merely neutral (above 5.6). As moderate haze events might occur more frequently under abundant ammonia and nitrate-dominated PM2.5 conditions, the major chemical processes during haze events and the control target should be re-evaluated to obtain the most effective control strategy.

scholarly journals Monitoring of the Impact of Lithium Nitrate on the Alkali–aggregate Reaction Using Acoustic Emission Methods

Materials ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 20
Author(s):  
Justyna Zapała-Sławeta ◽  
Grzegorz Świt
Keyword(s):  
Acoustic Emission ◽  
Initial Reaction ◽  
Lithium Nitrate ◽  
Acoustic Emission Method ◽  
Emission Method ◽  
Acoustic Activity ◽  
Initial Stage ◽  
Chemical Admixture ◽  
Different Characteristics ◽  
The Impact

The study analyzed the possibility of using the acoustic emission method to analyse the reaction of alkali with aggregate in the presence of lithium nitrate. Lithium nitrate is a chemical admixture used to reduce adverse effects of corrosion. The tests were carried out using mortars with reactive opal aggregate, stored under the conditions defined by ASTM C227. The acoustic activity of mortars with a corrosion inhibitor was referred to linear changes and microstructure of specimens in the initial reaction stages. The study found a low acoustic activity of mortars with lithium nitrate. Analysis of characteristic parameters of acoustic emission signals, combined with the observation of changes in the microstructure, made it possible to describe the corrosion processes. As the reaction progressed, signals with different characteristics were recorded, indicating aggregate cracking at the initial stage of the reaction, followed by cracking of the cement paste. The results, which were referred to the acoustic activity of reference mortars, confirmed that the reaction of opal aggregate with alkali was mitigated in mortars with lithium nitrate, and the applied acoustic emission method enabled the detection and monitoring of ASR progress.

scholarly journals A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans

2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever
Keyword(s):  
Large Scale ◽  
Cold Front ◽  
Conveyor Belt ◽  
Low Level ◽  
Scale Parameters ◽  
Convective Clouds ◽  
Cold Fronts ◽  
Surface Front ◽  
High Level ◽  
The Impact

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.

scholarly journals The Impact of Forcing Datasets on the High-Resolution Simulation of Tropical Storm Ivan (2004) in the Southern Appalachians

2012 ◽  
Vol 140 (10) ◽  
pp. 3300-3326 ◽  
Author(s):  
Xiaoming Sun ◽  
Ana P. Barros
Keyword(s):  
High Resolution ◽  
Global Analysis ◽  
Surface Wind ◽  
Tropical Storm ◽  
Southern Appalachians ◽  
Low Level ◽  
Simulated Precipitation ◽  
Forced Simulation ◽  
The Impact ◽  
Resolution Simulation

Abstract The influence of large-scale forcing on the high-resolution simulation of Tropical Storm Ivan (2004) in the southern Appalachians was investigated using the Weather Research and Forecasting model (WRF). Two forcing datasets were employed: the North American Regional Reanalysis (NARR; 32 km × 32 km) and the NCEP Final Operational Global Analysis (NCEP FNL; 1° × 1°). Simulated fields were evaluated against rain gauge, radar, and satellite data; sounding observations; and the best track from the National Hurricane Center (NHC). Overall, the NCEP FNL forced simulation (WRF_FNL) captures storm structure and evolution more accurately than the NARR forced simulation (WRF_NARR), benefiting from the hurricane initialization scheme in the NCEP FNL. Further, the performance of WRF_NARR is also negatively affected by a previously documented low-level warm bias in NARR. These factors lead to excessive precipitation in the Piedmont region, delayed rainfall in Alabama, as well as spatially displaced and unrealistically extreme rainbands during its passage over the southern Appalachians. Spatial filtering of the simulated precipitation fields confirms that the storm characteristics inherited from the forcing are critical to capture the storm’s impact at local places. Compared with the NHC observations, the storm is weaker in both NARR and NCEP FNL (up to Δp ~ 5 hPa), yet it is persistently deeper in all WRF simulations forced by either dataset. The surface wind fields are largely overestimated. This is attributed to the underestimation of surface roughness length over land, leading to underestimation of surface drag, reducing low-level convergence, and weakening the dissipation of the simulated cyclone.

Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

2021 ◽  
Author(s):  
Luke J. LeBel ◽  
Brian H. Tang ◽  
Ross A. Lazear
Keyword(s):  
New York ◽  
High Resolution ◽  
Wind Shear ◽  
Model Simulation ◽  
Wrf Model ◽  
Severe Weather ◽  
Streamwise Vorticity ◽  
Low Level ◽  
Severe Convection ◽  
The Impact

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

scholarly journals Impact of enriched analyses on regional numerical forecasts over southeastern South America during SALLJEX

2014 ◽  
Vol 29 (3) ◽  
pp. 315-330
Author(s):  
Yanina García Skabar ◽  
Matilde Nicolini
Keyword(s):  
Data Assimilation ◽  
South America ◽  
Atmospheric Modeling ◽  
South American ◽  
The South ◽  
Low Level ◽  
Positive Effects ◽  
Accumulated Rainfall ◽  
Low Level Jet ◽  
The Impact

During the warm season 2002-2003, the South American Low-Level Jet Experiment (SALLJEX) was carried out in southeastern South America. Taking advantage of the unique database collected in the region, a set of analyses is generated for the SALLJEX period assimilating all available data. The spatial and temporal resolution of this new set of analyses is higher than that of analyses available up to present for southeastern South America. The aim of this paper is to determine the impact of assimilating data into initial fields on mesoscale forecasts in the region, using the Brazilian Regional Atmospheric Modeling System (BRAMS) with particular emphasis on the South American Low-Level Jet (SALLJ) structure and on rainfall forecasts. For most variables, using analyses with data assimilated as initial fields has positive effects on short term forecast. Such effect is greater in wind variables, but not significant in forecasts longer than 24 hours. In particular, data assimilation does not improve forecasts of 24-hour accumulated rainfall, but it has slight positive effects on accumulated rainfall between 6 and 12 forecast hours. As the main focus is on the representation of the SALLJ, the effect of data assimilation in its forecast was explored. Results show that SALLJ is fairly predictable however assimilating additional observation data has small impact on the forecast of SALLJ timing and intensity. The strength of the SALLJ is underestimated independently of data assimilation. However, Root mean square error (RMSE) and BIAS values reveal the positive effect of data assimilation up to 18-hours forecasts with a greater impact near higher topography.

Sign in / Sign up

Export Citation Format

Share Document