Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Owner’s Risk Allocation and Contractor’s Role Behavior in a Project: A Parallel-mediation Model

Risk allocation decisions are of critical importance in project management. The present study proposes an explanation for how risk allocation in a contract motivates a contractor to cooperate with a project owner. Theories of risk allocation and trust were used to motivate the research. Using a survey methodology, we collected data concerning 124 construction projects in China. We found that risk allocation influenced the contractor’s role behavior through the contractor’s feeling of being trusted but not the contractor’s trust in the owner. Feeling of being trusted partially mediated the effect of risk allocation on the contractor’s in-role (i.e., contractual) behavior and fully mediated the effect on extra-role behavior. The study introduces a social and psychological view of the impacts of risk allocation to the project and engineering management literature. We contribute to theory by arguing and demonstrating the mediating effect of trust on the relationship between risk allocation and contractor behavior. From a practical standpoint, we conclude that contractual risk allocation has a significant impact on building a trusting relationship between owners and contractors and that contractors who feel trusted perform both contractually mandated actions and actions external to the contract more diligently, resulting in the likelihood of improved outcomes for both parties.     

Broadband bowtie belt nanoantennas

In this article, we study a linear array of bowtie nanoantennas placed between two metallic strips that can work from 800 to 1420 nm (600 nm linewidth), with an electric field enhancement factor close to 20. We study the dynamical change of the position of the electric field enhancement amongst different elements in the array and, at the same time, the effects of dispersion on the scalability of the array elements. A systematic analysis and methodology to produce an array that can operate over a large bandwidth whilst maintaining the electric field enhancement without significant variation is provided.     

Simulation of a Terahertz Laser in the Bloch Oscillation Mode

Technical Physics Letters - Possible designs of a terahertz laser that use the effect of Bloch oscillations in SiC natural superlattices have been considered. It has been proposed to use as a...     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation.

In this paper, implementation of the Benchmark Simulation Model No 2 (BSM2) within Matlab-Simulink is presented. The BSM2 is developed for plant-wide WWTP control strategy evaluation on a long-term basis. It consists of a pre-treatment process, an activated sludge process and sludge treatment processes. Extended evaluation criteria are proposed for plant-wide control strategy assessment. Default open-loop and closed-loop strategies are also proposed to be used as references with which to compare other control strategies. Simulations indicate that the BM2 is an appropriate tool for plant-wide control strategy evaluation.     

HIGHER PLANT BIOMARKERS IN PALEOGENE CRUDE OILS FROM THE YUFUTSU OIL-AND GASFIELD AND OFFSHORE WILDCATS, JAPAN

Geochemical investigation of Paleogene oils from the onshore Yufutsu oil- and gasfield, southern Hokkaido, and from two nearby offshore wells, revealed the presence of numerous biomarkers of higher plant origin. Biomarkers in the oils belong to different groups of both angiosperm and gymnosperm origin; they include bicyclic sesquiterpanes, diterpanes, and triterpanes and their aromatized counterparts, which suggests a terrestrial origin for the oils. The oils were characterized as having a high wax content, a low content of organosulphur compounds, a high pristane/phytane ratio, and a low C₂₇/(C₂₇+C₂₉) sterane ratio.
Although the oils from on- and offshore Southern Hokkaido are similar in their geochemical composition, notable differences were observed in the biomarker signature of both saturate and aromatic fractions. The oils from the offshore wells appeared to have a greater abundance of higher plant biomarkers compared to those from the Yufutsu field, suggesting an enrichment in higher plant components. Differences in biomarker fingerprint could not be linked to the maturity effect, since the oils appeared to be of similar maturity levels, corresponding to the late stage of the oil window (0.9–1.2%, Rc). The differences in the biomarker signatures between the oils from the Yufutsu field and the offshore wells are likely to be due to facies variations in source organic matter, resulting from differences in the quantity and quality of land plant input.