Four-dimensional worldwide atmospheric models: ANYPT and ANYRG

Computer programs read magnetic-tape data bases and computer meteorological profiles for any position, time, and height (from zero to 25 km). System assists in analyses of distortion of information obtained from aircraft-mounted or spacecraft-mounted electromagnetic sensors

Study of permeability characteristics of membranes Quarterly report

Permeability characteristics of cation-exchange membranes based on transport measurement

Designing supply chains resilient to nonlinear system dynamics

Purpose: To propose an analytical framework for the design of supply chains that are resilient to nonlinear system dynamics. For this purpose, it is necessary to establish clearly elucidated performance criteria that encapsulate the attributes of resilience. Moreover, by reviewing the literature in nonlinear control engineering, this work provides a systematic procedure for the analysis of the impact of nonlinear control structures on systems behaviour. Design/method/approach: The Forrester and APIOBPCS models are used as benchmark supply chain systems. Simpli�cation and nonlinear control theory techniques, such as low order modelling, small perturbation theory and describing functions, are applied for the mathematical analysis of the models. System dynamics simulations are also undertaken for cross-checking results and experimentation. Findings: Optimum solutions for resilience yield increased production on-costs. Inventory redundancy has been identi�ed as a resilience building strategy but there is a maximum resilience level that can be achieved. A methodological contribution has also been provided. By using nonlinear control theory more accurate linear approximations were found for reproducing nonlinear models, enhancing the understanding of the system dynamics and actual transient responses. Research limitations/implications: This research is limited to the dynamics of single-echelon supply chain systems and focus has been given on the analysis of individual nonlinearities. Practical Implications: Since that the resilience performance trades-o� with production, inventory and transportation on-costs, companies may consider to adjust the control parameters to the resilience `mode' only when needed. Moreover, if companies want to invest in additional capacity in order to become more resilient, manufacturing processes should be prioritised. Originality/value: This research developed a framework to quantitatively assess supply chain resilience. Moreover, due consideration of capacity constraint has been given by conducting in-depth analyses of systems nonlinearities

Investigating sustained oscillations in nonlinear production and inventory control models

Even in a deterministic setting, nonlinearities can yield unexpected dynamic behaviours in a production and inventory control system, such as sustained oscillations or limit cycles. Describing function in combination with simulation is used to analyse the effect of discontinuous nonlinearities on the system responses. Utilising a nonlinear production and inventory control model, we investigate the occurrence of limit cycles and propose a technique to predict their amplitude, frequency and stability and to control such oscillations. Findings suggest that, even for an autonomous production and inventory control system, limit cycles do occur and this periodic behaviour occurs due to non-negativity constraint in the ordering rule. Moreover, we demonstrate the potential of the describing function method to provide insight into the impact of system constraints and therefore facilitate a more effective system design. This paper fills a gap in the literature on nonlinear supply chain dynamics by expanding and complementing the sparse recent research in this area. Most previous studies have either focused on linear mathematical models or relied on simulation, which greatly limit the relevancy and/or rigour of the published results

Positive intergroup contact modulates fusiform gyrus activity to black and white faces.

In this study, we investigated the effect of intergroup contact on processing of own- and other-race faces using functional Magnetic Resonance Imaging (fMRI). Previous studies have shown a neural own-race effect with greater BOLD response to own race compared to other race faces. In our study, white participants completed a social-categorization task and an individuation task while viewing the faces of both black and white strangers after having answered questions about their previous experiences with black people. We found that positive contact modulated BOLD activity in the right fusiform gyrus (rFG) and left inferior occipital gyrus (lIOC), regions associated with face processing. Within these regions, higher positive contact was associated with higher activity when processing black, compared to white faces during the social categorisation task. We also found that in both regions a greater amount of individuating experience with black people was associated with greater activation for black vs. white faces in the individuation task. Quantity of contact, implicit racial bias and negatively valenced contact showed no effects. Our findings suggest that positive contact and individuating experience directly modulate processing of out-group faces in the visual cortex, and illustrate that contact quality rather than mere familiarity is an important factor in reducing the own race face effect

IOBPCS based models and decoupling thinking

The inventory and order based production control system (IOBPCS) is mainly a model of a forecast driven production system where the production decision is based on the forecast in combination with the deviation between target inventory and actual inventory. The model has been extended in various directions by including e.g. WIP feedback but also by interpreting the inventory as an order book and hence representing a customer order driven system. In practice a system usually consists of one forecast driven subsystem in tandem with a customer order driven subsystem and the interface between the two subsystems is represented by information flows and a stock point associated with the customer order decoupling point (CODP). The CODP may be positioned late in the flow, as in make to stock systems, or early, as in make to order systems, but in any case the model should be able to capture the properties of both subsystems in combination. A challenge in separating forecast driven from customer order driven is that neither the inventory nor the order book should be allowed to take on negative values, and hence non-linearities are introduced making the model more difficult to solve analytically unless the model is first linearized. In summary the model presented here is based on two derivatives of IOBPCS that are in tandem, and interfaces between them related to where the demand information flow is decoupled and the position of the CODP

Identifying the causes of the bullwhip effect by exploiting control block diagram manipulation with analogical reasoning

Senior managers when solving problems commonly use analogical reasoning, allowing a current ‘target problem’ situation to be compared to a valid previous experienced ‘source problem’ from which a potential set of ‘candidate solutions’ may be identified. We use a single-echelon of the often-quoted Forrester (1961) production-distribution system as a case ‘target model’ of a complex production and inventory control system that exhibits bullwhip. Initial analogical reasoning based on ‘surface similarity’ would presuppose a classic control engineering ‘source model’ consisting of a phase-lag feedback system for which it is difficult to derive the transfer function. Simulation alone would have to be relied on to mitigate the bullwhip effect. By using z-transform block diagram manipulation, the model for a single-echelon, consisting of 17 difference equations with five feedback loops is shown to have exact analogy to Burns and Sivazlian’s (1978) second order system that has no feedback. Therefore, this more appropriate ‘source model’ is based on a deeper understanding of the ‘behavioural similarities’ which indicates that the bullwhip effect is not in the case of the ‘target model’ due to feedback control but due to a first-order derivative, ‘phase advance’, term in the feed forward numerator path. Hence a more appropriate 'candidate solution' can be found via the use of a 'recovery' filter. An interdisciplinary framework for exploiting control engineering block diagram manipulation, utilising analogical reasoning, in a practical setting is presented, as is an example in a contemporary supply chain setting