Strategy In Different Conditions Research Articles

Incorporating users’ adaptive behaviors into multi-objective optimization of shading devices: A case study of an office room in Qingdao

Users' adaptive behaviors significantly affect the indoor environment and energy use. Neglecting them would introduce considerable uncertainty in the computer simulation results and lead to suboptimal or even invalid energy-efficiency solutions in optimization. To address this issue, we abstracted and simplified three user behavior patterns, including adjustment of operable shading devices, switching on/off artificial lighting, and opening windows for natural ventilation by a brief literature review. We then developed a new simulation approach that incorporates these behavior patterns and applied it to optimize the exterior fixed solar shade design of a south-facing office room in Qingdao as an example. The baseline model was established and validated in both daylight and energy simulations. The results demonstrate that the addition of user behavior models has a significant impact on both illuminance and load simulation results. The evaluation of each shading solution under the traditional approach and the newly-developed approach shows considerable differences, leading to the selection of different optimal solutions. Ultimately, the 0.6-meter-long type 8 (horizontal sunshade combined with vertical triangular panels on both sides) and 0.7-meter-long type 4 (double-sided vertical shading) were selected as the optimal solution using the traditional approach and new approach, respectively. This research offers valuable insights into the user behavior pattern and uses a shading optimization example to demonstrate the significant impact of incorporating adaptive behavior mechanisms on simulation and optimization results. The approach established in this paper has the potential to be extended to other solutions, being conducive to the study of refined building efficiency strategies for different conditions.

Segmenting Agri-Input Market in Odisha

There has been a significant transformation in social, physical and economic infrastructure. This has consequently changed the attitude and behavior of consumers/farmers. Farmers have shifted substantially toward consumerism, particularly over the past decade. This drastic and rapid change in the Indian agriculture sector has compelled agribusiness firms to continually adapt their marketing strategies to add & retain customers and increase the customer lifetime value. To maximize the efficiency and effectiveness of their market interventions, marketers have been segmenting their customers in numerous ways with its own set of advantages and disadvantages. Our study proposes and evaluates a new approach to agri-input market segmentation based on the farmer buying behavior - Brand loyalty, price sensitivity and response to market interventions. The study included farmers (marginal, small, medium and large) from different social, geographical and agro-climatic regions. The findings of the study would useful for the agri-input suppliers/marketers for developing better marketing mix strategies for different conditions of market and production orientations.

Fast filling strategy of type III on-board hydrogen tank based on time-delayed method

In order to study the fast filling problem of the type III on-board hydrogen tank, a 3D computational fluid dynamics (CFD) simulation model is proposed. Several simulation calculations are completed to simulate the fast filling process under different initial conditions. In order to control the temperature rise during the fast filling process, the effects of different mass flow rates are studied. Based on the control of mass flow rate, various time-delayed filling strategies for different conditions are proposed to meet the requirement of shortening the filling time as much as possible without exceeding the maximum temperature limit. It is found that if the delay duration is determined, how the filling time is allocated has little effect on the final temperature rise. The proposed strategy can complete the filling within 155s in a general environment, which saves 62% of the time compared with the filling with constant mass flow rate. This research provides the theoretical basis and technical support for mass flow control strategies of fast filling in the hydrogen refueling stations and has guiding significance for the actual filling process of large-capacity hydrogen tanks.

The Coopetitive Behavior

This article aims at presenting a new strategic thinking, that is a revolution compared to the classic readings on competition and cooperation. Through our reading on the subject, we aim at understanding and uncovering the overlap that can exist between the competitive and the cooperative behavior. From the state of the art on the subject, we extracted variety of examples where coopetition as concept was mobilized. This allowed us to demonstrate the use of this strategy in different conditions and scenarios. Finally, we concluded that competition and cooperation can no longer be considered as antonyms, due to companies' internal and external challenges and the possible achievement of common or personal objectives through a combination, resulting in a hybrid behavior.

Detection Strategy Against Restricted SSDF Attack With Potential Interaction Assistance

This paper investigates the malicious users (MUs) detection problem against restricted spectrum sensing data falsification (RSSDF) attack in cooperative spectrum sensing (CSS) network. We consider a CSS network with non-ideal reporting channels, in which there are two kinds of secondary users (SUs): interactive SUs (ISUs) and non-interactive SUs (NSUs). We simplify the interaction process among ISUs with proper assumptions and formulate the impact of non-ideal reporting channels on falsified data. Based on the traditional probability SSDF attack on M-ary quantized data, we generalize the attack model by considering the restriction on attack magnitude. To detect ISUs, we construct a detection architecture with ISUs partitioned into groups of two and perform distributed detection by proposed interaction-based detection algorithm. For the detection of NSUs and undetected ISUs, we further propose a semi-supervised fuzzy c-means-based (SSFCM-based) detection algorithm with potential interaction assistance. Simulation results demonstrate the validity of the proposed theorems. In addition, we illustrate the detection performance of the proposed strategy in different conditions and show the superiority of the proposed strategy over other detection algorithms.

Amphetamine Use in the Elderly: A Systematic Review of the Literature.

Objective:To systematically review the literature on the therapeutic use of amphetamine, lisdexamfetamine and methylphenidate in elderly population with and without dementia.Methods:We conducted two researches on the PubMed, Scopus and Embase using the keywords (“elderly”) AND (“amphetamine” OR “methylphenidate” OR “lisdexamfetamine”) and then (“Alzheimer” OR “dementia”) AND (“amphetamine” OR “methylphenidate” OR “lisdexamfetamine”).Results:Twenty-nine papers met all the eligibility criteria. The results are encouraging as 81.5% of the studies showed clinical improvement of the investigated condition.Conclusion:Amphetamines and methylphenidate are probably effective strategies for different conditions in the elderly population. However, further studies are needed to provide more robust evidence on efficacy, dosage and safety for this population.

A Separated Adaptive Control Strategy for Different Conditions Based on Flexible Dynamics Equation of Robot Manipulator

A Separated Adaptive Control Strategy for Different Conditions Based on Flexible Dynamics Equation of Robot Manipulator

A modular approach to learning manipulation strategies from human demonstration

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is complex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly we record a human performing a task that requires an adaptive control strategy in different conditions, i.e. different task contexts. We then perform modular decomposition of the control strategy, using phases of the recorded actions to guide segmentation. Each module represents a part of the strategy, encoded as a pair of forward and inverse models. All modules contribute to the final control policy; their recommendations are integrated via a system of weighting based on their own estimated error in the current task context. We validate our approach by demonstrating it, both in a simulation for clarity, and on a real robot platform to demonstrate robustness and capacity to generalise. The robot task is opening bottle caps. We show that our approach can modularize an adaptive control strategy and generate appropriate motor commands for the robot to accomplish the complete task, even for novel bottles.

Applying hybrid learning approach to RoboCup's strategy

RoboCup (Robot world cup tournament) soccer game is a competitive game that has become a popular research domain in recent years since it involves a complex system for the behavior of multiple agents. In this paper, a hybrid approach, case-based reasoning genetic algorithm (CBR-GA) is applied to the soccer game for providing better strategies. By using CBR-GA, the soccer robots can obtain the suitable strategies for different conditions and store the related experiences, which may be reused in the future. Rule-based reasoning (RBR) will be employed to create a new strategy for the soccer robots when CBR-GA cannot provide a suitable one. A multi-agent learning system, constructed by combining case-based reasoning genetic algorithm with RBR strategy (CGRS), is implemented on the latest WrightEagle simulation platform that is released in 2011. In the CGRS system, two kinds of agent, namely “coach agent” and “movement agent”, are designed for the soccer game. The coach agent is responsible for deciding on the strategy goal and assigning tasks to the movement agents. Every movement agent will then execute its respective task for achieving the strategy goal. Better basic skills will facilitate the movement agents to execute more effectively the assigned tasks or plans; hence, many basic skills are designed for training the movement agents. To increase learning efficiency, the strategy cycle time is reduced with a suitable case base. To validate the effectiveness of the proposed approach, our soccer team played with the WrightEagle soccer team which has remained in the top two positions in simulation 2d in recent years. Our team gradually gets higher winning frequency in 50 rounds. Furthermore, a comparison experiment shows that the proposed approach has higher winning frequency than other methods including CBR-GA, CBR-RBR and RBR. Finally, the proposed approach is also found to have better learning mechanisms than other learning approaches in soccer game.

Reconstruction for Defects of the Lower Lip After Tumor Ablation

The lip carcinoma, which frequently affects the lower lip, is one of the most common cancers of the head and neck region composing 25% to 30% of all oral cancers. The accepted method of therapy for lip cancer is surgical excision and reconstruction. The repair should satisfy 2 fundamental requirements: to achieve appropriate aesthetic quality and to conserve labial function. Currently, a wide range of reconstructive procedures have been developed. The objective of the study was to summarize the clinical experience of reconstruction for lower lip defects to facilitate the selection of a proper reconstructive strategy for different conditions in clinical practice. We performed a retrospective analysis of 43 patients who had undergone a standardized reconstructive approach based on the literature published and our own experience over the past 4 years. Over an average period of 7.5 months' follow-up, recurrences or major complications did not happen, and most patients were satisfied with their functional and aesthetical outcome. Focusing on the location and the width of the defects of lower lip, a table has been exhibited to orient the surgeons to select a suitable reconstructive procedure for each patient. Successful reconstruction of all defects can be attained, if as many surgical procedures as possible have been mastered, and a more proper means used.

Soil water content on drip irrigated cotton: comparison of measured and simulated values obtained with the Hydrus 2-D model

Crop irrigation with subsurface drip (SDI) is increasing in the semiarid Texas High Plains (THP). Information on drip-tubing positioning, irrigation strategies, and wetted soil area is needed to increase rainwater effectiveness when well capacities are inadequate to meet full irrigation requirements. Time and resources necessary to test SDI strategies for different conditions through field experimentation is too large. However, a mechanistic model such as Hydrus-2D can quantify the effect of different installation geometries and irrigation strategies. Our objective was to experimentally validate the Hydrus-2D in an Amarillo soil in THP so that the model can be used to evaluate different irrigation frequency and timing strategies for SDI cotton. Results showed that Hydrus-2D simulated volumetric soil water content within ±3% of measured values, and simulation bias represented the smaller portion of the simulation error, indicating that the model can be used to evaluate irrigation strategies.

SOURCING CONFIGURATION FOR PRODUCT MASS CUSTOMIZATION

Modularity has been recognized as a vital factor to implement mass customization, it has strong relation with product architecture, product development process and supply chains. The characteristics of different types of modularity (i.e. component swapping/sharing modularity, fit-to-cut/bus modularity and component combination modularity) and their impacts on component sourcing are analyzed. An evolution diagram is presented to illustrate how the level of customization affects the type of modularity. Furthermore, the relationships among the customer order discoupling point, the variety and volume of product and module, and the level of mass customization are discussed. Then, according to different ratios of product volume to product variety, two types of product customization are defined , namely, the high and the low degree of customization. Based on cases study of automobile, hydraulic press, machine tool and domestic appliance, the proper type of modularity and corresponding component sourcing strategy in different conditions of customization are summarized. Finally, the relationship between the identification level of modules and supplier resource planning, out-sourcing decision-making is analyzed, and then a roadmap of implementing mass customization considering component sourcing is given.