Carbohydrate content of potato (Solanum tuberosum L.) tubers treated with Isopropyl-N (3-chlorophenyl) carbamate under different storage conditions

Post harvest application of Isopropyl-N (3-chlorophenyl) carbamate considerably reduced the degradation of starch when potato tubers were stored in an evaporative cooling chamber. The starch degraded at a faster rate when tubers were kept under refrigerated and room storage conditions.     

Thermal degradation of cellulose and its phosphorylated products in air and nitrogen

The thermal degradation of cellulose and its phosphorylated products (phosphates, diethylphosphate, and diphenylphosphate) were studied in air and nitrogen by differential thermal analysis and dynamic thermogravimetry from ambient temperature to 750°C. From the resulting data various thermodynamic parameters were obtained following the methods of Broido and Freeman and Carroll. The values of E_a for decomposition for phosphorylated cellulose were found to be in the range 55–138 kJ mol^?1 in air and 85–152 kJ mol^?1 in nitrogen and depended upon the percent of phosphorus contents in the samples. The mass spectrum of cellobiose phosphate indicated the absence of the molecular ion, indicating that the compound was thermally unstable. The IR spectra of the pyrolysis residues of cellulose phosphate gave indication of formation of a compound having C?O and P?O groups. A fire retardancy mechanism for the thermal degradation of cellulose phosphate has been proposed.     

Selected physical characteristics of polystyrene/high density polyethylene composites prepared from virgin and recycled materials

Mixtures of polystyrene and high density polyethylene were injection molded from recycled and virgin polymers to generate cocontinuous structures. The mechanical properties of these blends were evaluated to assess their conformance to rule of mixtures behavior in general and to identify areas of synergy or incompatibility in specific. Flexural and tensile data for recycled blends showed that generally the properties are not additive, except in a cocontinuous region of composition near 35/65 PS/HDPE that has been identified previously for recycled materials. Analysis of crystallinity in the HDPE phase of these blends by differential scanning calorimetry indicates a marked reduction in the level of HDPE crystallinity at the 35/65 PS/HDPE composition. Similar blends of virgin PS/HDPE polymer do not show the differing regions of incompatibility and synergy illustrated by the recycled materials, but rather show approximate conformance to the rule of mixtures. Furthermore, the virgin blends show virtually no crystallinity suppression and a more pronounced T_g shift in the polystyrene compared to recycled materials. Detailed characterization of the recycled materials in terms of polymer and particulate impurities should improve understanding of these differences and perhaps provide direction for obtaining enhanced synergistic behavior in virgin polymer blends. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

EGIS'92

Announcement

EGIS'92 Third European Conference on Geographical Information Systems at the Park Hilton in Munich Germany, March 23–26, 1992     

Learning Noise-Assisted Robust Image Features for Fine-Grained Image Retrieval

Fine-grained image search is one of the most challenging tasks in computer vision that aims to retrieve similar images at the fine-grained level for a given query image. The key objective is to learn discriminative fine-grained features by training deep models such that similar images are clustered, and dissimilar images are separated in the low embedding space. Previous works primarily focused on defining local structure loss functions like triplet loss, pairwise loss, etc. However, training via these approaches takes a long training time, and they have poor accuracy. Additionally, representations learned through it tend to tighten up in the embedded space and lose generalizability to unseen classes. This paper proposes a noise-assisted representation learning method for fine-grained image retrieval to mitigate these issues. In the proposed work, class manifold learning is performed in which positive pairs are created with noise insertion operation instead of tightening class clusters. And other instances are treated as negatives within the same cluster. Then a loss function is defined to penalize when the distance between instances of the same class becomes too small relative to the noise pair in that class in embedded space. The proposed approach is validated on CARS-196 and CUB-200 datasets and achieved better retrieval results (85.38% recall@1 for CARS-196% and 70.13% recall@1 for CUB-200) compared to other existing methods.     

A Biologically-Inspired Micro Aerial Vehicle

This paper introduces a novel framework for the design, modeling and control of a Micro Aerial Vehicle (MAV). The vehicle’s conceptual design is based on biologically-inspired principles and emulates a dragonfly (Odonata–Anisoptera). We have taken inspiration from the flight mechanism features of the dragonfly and have developed indigenous designs in creating a novel version of a Flapping Wing MAV (FWMAV). The MAV design incorporates a complex mechanical construction and a sophisticated multi-layered, hybrid, linear/non-linear controller to achieve extended flight times and improved agility compared to other rotary wing and FWMAV Vertical Take Off and Landing (VTOL) designs. The first MAV prototype will have a ballpark weight including sensor payload of around 30 g. The targeted lifting capability is about twice the weight. The MAV features state of the art sensing and instrumentation payload, which includes integrated high-power on-board processors, 6DoF inertial sensors, 3DoF compasses, GPS, embedded camera and long-range telemetry capability. A 3-layer control mechanism has been developed to harness the dynamics and attain complete navigational control of the MAV. The inner-layer is composed of a ‘quad hybrid-energy controller’ and two higher layers are at present, implementing a linear controller; the latter will be replaced eventually with a dynamic adaptive non-linear controller. The advantages of the proposed design compared to other similar ones include higher energy efficiency and extended flight endurance. The design features elastic storage and re-use of propulsion energy favoring energy conservation during flight. The design/modeling of the MAV and its kinematics & dynamics have been tested under simulation to achieve desired performance. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance and reconnaissance in cluster and swarm formations. The efficacy of the design is demonstrated through a simulation environment. The dynamics are verified through simulations and a general linear controller coupled with an energy based non-linear controller is shown to operate the vehicle in a stable regime. In accordance with specified objectives a prototype is being developed for flight-testing and demonstration purposes.     

Common-input models for multiple neural spike-train data

Recent developments in multi-electrode recordings enable the simultaneous measurement of the spiking activity of many neurons. Analysis of such multineuronal data is one of the key challenge in computational neuroscience today. In this work, we develop a multivariate point-process model in which the observed activity of a network of neurons depends on three terms: (1) the experimentally-controlled stimulus; (2) the spiking history of the observed neurons; and (3) a hidden term that corresponds, for example, to common input from an unobserved population of neurons that is presynaptic to two or more cells in the observed population. We consider two models for the network firing-rates, one of which is computationally and analytically tractable but can lead to unrealistically high firing-rates, while the other with reasonable firing-rates imposes a greater computational burden. We develop an expectation-maximization algorithm for fitting the parameters of both the models. For the analytically tractable model the expectation step is based on a continuous-time implementation of the extended Kalman smoother, and the maximization step involves two concave maximization problems which may be solved in parallel. The other model that we consider necessitates the use of Monte Carlo methods for the expectation as well as maximization step. We discuss the trade-off involved in choosing between the two models and the associated methods. The techniques developed allow us to solve a variety of inference problems in a straightforward, computationally efficient fashion; for example, we may use the model to predict network activity given an arbitrary stimulus, infer a neuron's ring rate given the stimulus and the activity of the other observed neurons, and perform optimal stimulus decoding and prediction. We present several detailed simulation studies which explore the strengths and limitations of our approach.     

Multi-stage deep probabilistic prediction for travel demand

Applied Intelligence - Accurate demand prediction is an essential component of any decision support system for smart vehicle dispatching. However, predicting real time demand at the...     

Strategies for the construction sector in the information technology era

The construction industries in many countries are starting to consider seriously the strategic use of information technology (IT). The use of information technology in construction is extending beyond the stage of piecemeal application for improving the efficiency of discrete operations by individual organizations to the advanced stage where IT is applied strategically in commercial enterprises, government agencies and professional institutions. Progress in construction in this regard appears to lag behind that in most other sectors of the economy. This paper considers the nature and the background of this progression in construction by examining proposals by Earl (1989) of nine basic prerequisites to the IT era which make a strategic approach timely. Each prerequisite is outlined and how it has been met in other sectors of the economy considered. The extent to which these prerequisites apply in construction and the scope for their application in the near future are examined. It is argued that all organizations involved in construction will ultimately have to think strategically about their use of IT, and how some are already doing so is described.

In discussing the factors which hinder the strategic application of IT in construction, the nature of the design and construction processes and initiatives that may be necessary to overcome the perceived problems are examined in detail. The strategies that are evolving at a national level in Singapore are outlined.