Synergistic Effects of Polybenzimidazole and Aramide on Enhancing Flame-Retardancy and Solubility

Aromatic and functional polymers with processibility derived from biobased starting materials are prerequisite considering sustainable society. Poly(2,5-benzimidazole)s are rigid-rod polymers to show ultrahigh thermal stability such as flame retardance, while usually suffer from poor solubility. Here, poly(benzimidazole-co-amide)s are synthesized from two biobased monomers, 3,4-diaminobenzoic acid and a semirigid comonomer, 4-aminohydrocinnamic acid. The copolymers with an amide composition of 80 mol% and higher are soluble in widely used polar solvents to fabricate the films keeping high flame retardance, which is comparable with popular high-performance polymers such as aromatic polyimides, polyetheretherketone, polyphenylene sulfide, etc.     

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Journal of Intelligent Manufacturing - In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size,...     

Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition

Interpretation of images and videos containing humans interacting with different objects is a daunting task. It involves understanding scene/event, analyzing human movements, recognizing manipulable objects, and observing the effect of the human movement on those objects. While each of these perceptual tasks can be conducted independently, recognition rate improves when interactions between them are considered. Motivated by psychological studies of human perception, we present a Bayesian approach which integrates various perceptual tasks involved in understanding human-object interactions. Previous approaches to object and action recognition rely on static shape/appearance feature matching and motion analysis, respectively. Our approach goes beyond these traditional approaches and applies spatial and functional constraints on each of the perceptual elements for coherent semantic interpretation. Such constraints allow us to recognize objects and actions when the appearances are not discriminative enough. We also demonstrate the use of such constraints in recognition of actions from static images without using any motion information.     

Software Architectures for Reducing Priority Inversion and Non-determinism in Real-time Object Request Brokers

There is increasing demand to extend Object RequestBroker (ORB) middleware to support distributed applications withstringent real-time requirements. However, conventional ORB implementations,such as CORBA ORBs, exhibit substantial priority inversion andnon-determinism, which makes them unsuitable for applicationswith deterministic real-time requirements. This paper providestwo contributions to the study and design of real-time ORB middleware.First, it illustrates empirically why conventional ORBs do notyet support real-time quality of service. Second, it evaluatesconnection and concurrency software architectures to identifystrategies that reduce priority inversion and non-determinismin real-time CORBA ORBs. The results presented in this paperdemonstrate the feasibility of using standard OO middleware likeCORBA to support certain types of real-time applications overthe Internet.     

A review of particle swarm optimization and its applications in Solar Photovoltaic system

Particle swarm optimization is a stochastic optimization, evolutionary and simulating algorithm derived from human behaviour and animal behaviour as well. Special property of particle swarm optimization is that it can be operated in continuous real number space directly, does not use gradient of an objective function similar to other algorithms. Particle swarm optimization has few parameters to adjust, is easy to implement and has special characteristic of memory. Paper presents extensive review of literature available on concept, development and modification of Particle swarm optimization. This paper is structured as first concept and development of PSO is discussed then modification with inertia weight and constriction factor is discussed. Issues related to parameter tuning, dynamic environments, stagnation, and hybridization are also discussed, including a brief review of selected works on particle swarm optimization, followed by application of PSO in Solar Photovoltaics.     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Kinetic Modelling of Colour Degradation in Tomato Puree (Lycopersicon esculentum L.)

The kinetics of colour (measured as Hunter ‘a’ value) degradation in tomato puree (Lycopersicon esculentum L.) has been studied over a temperature range of 50–120 °C (isothermal condition), and also during normal open pan cooking, pressure cooking and cooking in a newly developed and patented fuel-efficient ‘EcoCooker’ (non-isothermal condition). The degradation of colour as measured by Hunter ‘a’ value was found to follow first order kinetics. The temperature dependence of degradation was adequately modelled by Arrhenius equation. A mathematical model has been developed using the isothermal parameters obtained to predict correctly the losses of red colour from the time–temperature data of non-isothermal heating/processing method. The results obtained indicate a colour degradation of similar magnitude in all the three modes of cooking used in the study.     

Linear circuits: a measurement‐based approach

This paper proposes a new measurement‐based approach that can solve synthesis problems in unknown linear circuits. The method makes use of a small number of measurements to determine the functional dependency of any circuit signal or variable on any set of design variables. Once the functional dependency is obtained, the design requirements can be applied to find the design parameter values. The results are described for linear direct current and alternating current circuits. Copyright © 2013 John Wiley & Sons, Ltd.     

R&D appropriability and planned obsolescence: empirical evidence from wheat breeding in the UK (1960-1995)

Plant breeders face a unique appropriation problem—plantsare reproducible, genetic information is heritable and seedscan be multiplied. The paper uses varietal age as a proxy fordurability to examine planned obsolescence strategies in UKwheat breeding. Market-weighted age fell from 13 years (1960s)to 5.5 years (1990s). This fall is on account of increased varietalproliferation and breeding strategies that focus on incrementalproductivity improvements (i.e. increased efficiency) and narrowand limited disease resistance (i.e. reduced durability).