Automatic Quality Inspection of Bakery Products Based on Shape and Color Information

基于形状和颜色信息的烘焙产品的自动质量检测

Babar Khan,韩芳*,王直杰,Ather Iqbal

（东华大学 信息科学与技术学院,上海 201620）

创新点说明：

利用支持向量机和基于生物启发式HMAX模型的形状辨识器与RGB对抗颜色通道辨识器集成而形成一种有效的智能分类系统,并将其用于烘焙产品的质量检测。

研究目的：

本文要对烘焙产品进行更有效的质量检测,需要提出一种智能方法。

研究方法：

本文采用了支持向量机、基于生物启发式HMAX模型的形状辨识器与RGB对抗颜色通道辨识器集成,形成一种高级自动分类系统,对烘焙产品根据其形状和颜色（烘焙时间）进行对应分类。

结果：

利用本文方法对烘焙产品进行质量检测的结果与其它方法相比较,发现本文提出的基于生物启发的机器视觉系统运行更加精确和有效,同时发现采用One Versus One支持向量机和Directed Acyclic Graph支持向量机可以得到最大的分类精确率。本文方法对饼干形状和颜色的辨识分别达到了95%和100%的分类精确率。同时,算法稳定。

结论：

本文方法因其更加可靠和精确可用于代替现有的烘焙产品检测方法。

关键词：烘焙产品质量检测,计算机视觉,HMAX, 对抗颜色通道,RGB颜色辨识器,支持向量机

     

Single phase multi color emitting Ca2LuTaO6: Dy3+/Eu3+ double perovskite oxide phosphors

The trivalent rare-earth (RE³⁺) doped phosphors show tremendous achievement in narrow band multicolor line emission for various applications. However, the 4f–4f absorption transition of these ions is forbidden in UV and blue light excitation. Usually, a sensitizer having spin allowed transition was used as a co-dopant to excite these ions via the energy transfer phenomenon. Another approach promisingly using to excite these ions by efficient energy transfer from the intrinsic emission of the Ca₂LuTaO₆ double perovskite phosphors host lattice. Phosphors of Ca₂LuTaO₆ with double perovskite structure were synthesized by using a high-temperature solid-state reaction method. The produced Ca₂LuTaO₆ double perovskite phosphors show an intrinsic broad band emission centered at 424 nm under the excitation of 313 nm UV light. The origin of this broad band blue emission was deeply investigated by using computation and experimental approaches. The trivalent activator Dy³⁺ and Eu³⁺ were doped is a single and co-dopant in the produced Ca₂LuTaO₆ phosphors to check their excitation in UV and near-UV spectral region. X-ray diffraction and scanning electron microscopy were used to investigate the structure and phase analysis. Various characterizations such as photoluminescence excitation, emission, and CIE chromaticity coordinates were measured which illustrate the potential of Dy³⁺ and Eu³⁺ activated Ca₂LuTaO₆ double perovskite phosphors for narrow band multicolor line emission for various applications.     

Fabrication of co-PVDF/modacrylic/SiO2 nanofibrous membrane: Composite separator for safe and high performance lithium-ion batteries

Highly porous free-standing co-poly(vinylidene fluoride)/modacrylic/SiO₂ nanofibrous membrane was developed using electrically-assisted solution blow spinning method. The performance and the potential of the membrane as a lithium-ion battery separator were investigated. The addition of modacrylic enhanced the solution spinnability that resulted in defect-free membranes. Moreover, the presence of modacrylic enhanced the dimensional and thermal stabilities, while the addition of hydrophilic SiO₂ nanoparticle enhanced both mechanical property and ionic conductivity. Combustion test results illustrated that the presence of modacrylic provide flame retarding property over a set of different polymeric-based membranes. Electrochemical performance results showed that the developed membrane can increase the battery capacity compared with the commercial separator.     

Performance tuning of glass fiber/epoxy composites through interfacial modification upon integrating with dendrimer functionalized graphene oxide

In this study, glass fiber/epoxy composites were interfacially tailored by introducing polyamidoamine (PAM) dendrimer functionalized graphene oxide (GO) into epoxy matrix. Two different composites each containing varying loading fraction (0.5, 1.0, and 1.5 wt%) of GO and GO-PAM were fabricated via hot press processing. Composites were evaluated for interlaminar shear strength (ILSS), dynamic mechanical properties and thermal conductivity. The inclusion of 1.5 wt% GO-PAM resulted ~57.3%, ~42.7%, and ~54% enhancement in ILSS, storage modulus and thermal conductivity, respectively. Almost, ~71% reduction in coefficient of thermal expansion was also observed at same GO-PAM loading. Moreover, higher glass transition temperature was observed with GO-PAM addition. GO-PAM substantially improved fiber/matrix interfacial adhesion, which was witnessed through scanning electron microscopy. The enhanced thermo-mechanical performance was attributed to interfacial covalent interactions engendered by ring opening reaction between epoxy and amine moieties of PAM dendrimers. These multiscale composites with extraordinary functional properties can outperform conventional counterparts with improved reliability and performance.     

Molybdenum and tungsten coatings for x- ray targets obtained through the low-pressure plasma spraying process

Low-pressure plasma spraying under an argon atmosphere was employed to deposit molybdenum and tungsten coatings on different metallic, ceramic, and composite substrates. Molybdenum coatings ob-tained through this technique presented a homogeneous structure with an average porosity of about 17 %. These coatings exhibited adhesion greater than 40 MPa on molybdenum and grey cast iron (FT25) substrates. No adhesion was observed on an A1N surface regardless of the preheating temperature and/or surface preparation. Adhesion on AIN-Mo (AM25) composite substrate, containing 25 % dispersed metal-lic phase by volume, showed intermediate results. Tungsten coatings exhibited porosity between 10 to 12% and a typical lamellar structure. The adhesion of tungsten coatings on molybdenum and FT25 sub-strates was around 40 MPa.     

Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment

Cloud computing is an emerging technology in which information technology resources are virtualized to users in a set of computing resources on a pay‐per‐use basis. It is seen as an effective infrastructure for high performance applications. Divisible load applications occur in many scientific and engineering applications. However, dividing an application and deploying it in a cloud computing environment face challenges to obtain an optimal performance due to the overheads introduced by the cloud virtualization and the supporting cloud middleware. Therefore, we provide results of series of extensive experiments in scheduling divisible load application in a Cloud environment to decrease the overall application execution time considering the cloud networking and computing capacities presented to the application's user. We experiment with real applications within the Amazon cloud computing environment. Our extensive experiments analyze the reasons of the discrepancies between a theoretical model and the reality and propose adequate solutions. These discrepancies are due to three factors: the network behavior, the application behavior and the cloud computing virtualization. Our results show that applying the algorithm result in a maximum ratio of 1.41 of the measured normalized makespan versus the ideal makespan for application in which the communication to computation ratio is big. They show that the algorithm is effective for those applications in a heterogeneous setting reaching a ratio of 1.28 for large data sets. For application following the ensemble clustering model in which the computation to communication ratio is big and variable, we obtained a maximum ratio of 4.7 for large data set and a ratio of 2.11 for small data set. Applying the algorithm also results in an important speedup. These results are revealing for the type of applications we consider under experiments. The experiments also reveal the impact of the choice of the platforms provided by Amazon on the performance of the applications under study. Considering the emergence of cloud computing for high performance applications, the results in this paper can be widely adopted by cloud computing developers. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimized unequal error protection of embedded video bitstream using adaptive-hierarchical QAM

In this paper, a reliable video communication system using adaptive Hierarchical QAM (HQAM) is designed to provide optimized unequal error protection (UEP) to embedded video bitstreams. Based on the relative importance of bits, video bitstream is partitioned into two priorities, namely High Priority (HP) and Low Priority (LP) substreams. Then, the optimal value of modulation (or hierarchical) parameter (α) of HQAM, which controls the relative error protection of these substreams, is selected from a pre-designed look-up table. The proposed system adapts itself by adapting the optimal α according to the varying channel condition, without changing the modulation level. This is in contrast to conventional WiMAX and LTE systems, in which dynamic switching among multiple modulations is used to adapt the varying channel conditions. This paper proposes HQAM with adaptive α as an alternative to the multiple modulation schemes. Moreover, for fixed average transmission power, receiver demodulates symbols without the knowledge of α. In order to further improve the video quality and to reduce the effects of erroneously received LP bits, the proposed system uses another level of adaptation, in which received LP bits are adaptively considered or discarded, before decoding the video, depending on the channel conditions (or optimized α). Simulation results show that proposed system can achieve significant improvement in the video quality compared to QAM based EEP scheme and non-adaptive HQAM.     

Using model transformation to refactor use case models based on antipatterns

Use Case modeling is a popular technique for documenting functional requirements of software systems. Refactoring is the process of enhancing the structure of a software artifact without changing its intended behavior. Refactoring, which was first introduced for source code, has been extended for use case models. Antipatterns are low quality solutions to commonly occurring design problems. The presence of antipatterns in a use case model is likely to propagate defects to other software artifacts. Therefore, detection and refactoring of antipatterns in use case models is crucial for ensuring the overall quality of a software system. Model transformation can greatly ease several software development activities including model refactoring. In this paper, a model transformation approach is proposed for improving the quality of use case models. Model transformations which can detect antipattern instances in a given use case model, and refactor them appropriately are defined and implemented. The practicability of the approach is demonstrated by applying it on a case study that pertains to biodiversity database system. The results show that model transformations can efficiently improve quality of use case models by saving time and effort.     

Modeling of microstrip antennas using neural networks techniques: A review

Artificial neural networks modeling have recently acquired enormous importance in microwave community especially in analyzing and synthesizing of microstrip antennas (MSAs) due to their generalization and adaptability features. A trained neural model estimates response very fast, which is nearly equal to its measured and/or simulated counterpart. Thus, it completely bypasses the repetitive use of conventional models as these models need rediscretization for every minor changes in the geometry, which itself is a time‐consuming exercise. The purpose of this article is to review this emerging area comprehensively for both analyzing and synthesizing of the MSAs. During reviewing process, some untouched cases are also observed, which are essentially required to be resolved for antenna designers. Unique and efficient neural networks‐based solutions are suggested for these cases. The proposed neural approaches are validated by fabricating and characterizing of the prototypes too. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:747–757, 2015.