A New Scheme and Microstructural Model for 3D Full 5-directional Braided Composites

AbstractThree-dimensional(3D) braided composites are a kind of advanced ones and are used in the aeronautical and astronautical fields more widely. The advantages, usages, shortages and disadvantages of 3D braided composites are analyzed, and the possible approach of improving the properties of the materials is presented, that is, a new type of 3D full 5-directional braided composites is developed. The methods of making this type of preform are proposed. It is pointed out that the four-step braiding which is the most possible to realize industrialized production almost has no effect on the composites'properties. By analyzing the simulation model, the advantages of the material compared with the 3D 4-di- rectional and 5-directional materials are presented. Finally, a microstructural model is analyzed to lay the foundation for the future theoretical analysis of these composites

Semantic-aware Consistency Network for Cloth-changing Person Re-Identification

Cloth-changing Person Re-Identification (CC-ReID) is a challenging task that aims to retrieve the target person across multiple surveillance cameras when clothing changes might happen. Despite recent progress in CC-ReID, existing approaches are still hindered by the interference of clothing variations since they lack effective constraints to keep the model consistently focused on clothing-irrelevant regions. To address this issue, we present a Semantic-aware Consistency Network (SCNet) to learn identity-related semantic features by proposing effective consistency constraints. Specifically, we generate the black-clothing image by erasing pixels in the clothing area, which explicitly mitigates the interference from clothing variations. In addition, to fully exploit the fine-grained identity information, a head-enhanced attention module is introduced, which learns soft attention maps by utilizing the proposed part-based matching loss to highlight head information. We further design a semantic consistency loss to facilitate the learning of high-level identity-related semantic features, forcing the model to focus on semantically consistent cloth-irrelevant regions. By using the consistency constraint, our model does not require any extra auxiliary segmentation module to generate the black-clothing image or locate the head region during the inference stage. Extensive experiments on four cloth-changing person Re-ID datasets (LTCC, PRCC, Vc-Clothes, and DeepChange) demonstrate that our proposed SCNet makes significant improvements over prior state-of-the-art approaches. Our code is available at: https://github.com/Gpn-star/SCNet.Comment: Accepted by ACM MM 202

The Tissue Response and Degradation of Electrospun Poly( ε

Due to the advantage of controllability on the mechanical property and the degradation rates, electrospun PCL/PTMC nanofibrous scaffold could be appropriate for vascular tissue engineering. However, the tissue response and degradation of electrospun PCL/PTMC scaffold in vivo have never been evaluated in detail. So, electrospun PCL/PTMC scaffolds with different blend ratios were prepared in this study. Mice subcutaneous implantation showed that the continuous degradation of PCL/PTMC scaffolds induced a lasted macrophage-mediated foreign body reaction, which could be in favor of the tissue regeneration in graft

Pengembangan Media Pembelajaran Fisika Berupa Buletin Dalam Bentuk Buku Saku Untuk Pembelajaran Fisikakelas VIII Materi Gaya Ditinjau Dari Minat Baca Siswa

Tujuan dari penelitian ini untuk mengembangkan media pembelajaran berupa buletin dalam bentuk buku saku untuk pembelajaran Fisika kelas VIII pada materi Gaya ditinjau dari aspek materi, konstruk, dan bahasa serta minat baca siswa. Penelitian ini termasuk penelitian pengembangan yang menggunakan metode Research and Development (R&D). Penelitian ini menggunakan model pengembangan model prosedural yaitu model yang bersifat deskriptif yang menunjukkan tahapan-tahapan yang harus diikuti untuk menghasilkan produk berupa media pembelajaran.Jenis data yang diperoleh bersifat kualitatif dan kuantitatif yaitu angket dan wawancara. Teknik analisis data yang digunakan adalah analisis deskriptif kualitatif dan kuantitatif. Hasil penelitian menunjukkan bahwa media pembelajaran yang dikembangkan berupa buletin Fisika dalam bentuk buku saku memiliki kriteria sangat baik berdasarkan penilaian dari ahli materi, ahli bahasa Indonesia, dan ahli media memberikan rata-rata penilaian sebesar 86,56%. Media pembelajaran yang dikembangkan juga memiliki kriteria sangat baik bila ditinjau dari peningkatan minat baca siswa. Hal ini terbukti pada hasil angket minat baca awal dan akhir yang diberikan kepada siswa yang memberikan rata-rata peningkatan sebesar 11,13%. Selain itu juga dianalisis dengan menggunakan uji-t berpasangan terhadap data masing-masing kelompok uji coba untuk mengetahui signifikansi dari peningkatan minat baca siswa. Untuk uji coba perorangan diperoleh hasil perhitungan thitung = 6,957 > ttabel = 1,943 dan nilai Sig. = 0,001 < 0,05 yang berarti sangat signifikan. Untuk kelompok kecil didapatkan hasil perhitungan bahwa thitung = 7,848 > ttabel = 1,725 dan nilai Sig. = 0,000 < 0,05 yang berarti sangat signifikan. Untuk kelompok besar juga didapatkan hasil perhitungan bahwa thitung = 20,214 > ttabel = 1,725 dan nilai Sig. = 0,000 < 0,05 yang berarti sangat signifikan. Simpulan dari penelitian ini adalah media pembelajaran berupa buletin dalam bentuk buku saku memiliki kriteria sangat baik bila ditinjau dari aspek materi, konstruk, dan bahasa serta minat baca siswa

SFHG-YOLO: A Simple Real-Time Small-Object-Detection Method for Estimating Pineapple Yield from Unmanned Aerial Vehicles

The counting of pineapple buds relies on target recognition in estimating pineapple yield using unmanned aerial vehicle (UAV) photography. This research proposes the SFHG-YOLO method, with YOLOv5s as the baseline, to address the practical needs of identifying small objects (pineapple buds) in UAV vision and the drawbacks of existing algorithms in terms of real-time performance and accuracy. Field pineapple buds are small objects that may be detected in high density using a lightweight network model. This model enhances spatial attention and adaptive context information fusion to increase detection accuracy and resilience. To construct the lightweight network model, the first step involves utilizing the coordinate attention module and MobileNetV3. Additionally, to fully leverage feature information across various levels and enhance perception skills for tiny objects, we developed both an enhanced spatial attention module and an adaptive context information fusion module. Experiments were conducted to validate the suggested algorithm’s performance in detecting small objects. The SFHG-YOLO model exhibited significant gains in assessment measures, achieving [email protected] and [email protected]:0.95 improvements of 7.4% and 31%, respectively, when compared to the baseline model YOLOv5s. Considering the model size and computational cost, the findings underscore the superior performance of the suggested technique in detecting high-density small items. This program offers a reliable detection approach for estimating pineapple yield by accurately identifying minute items

Green roof development knowledge map: A review of visual analysis using CiteSpace and VOSviewer

Green roofs are generally acknowledged as environmentally sustainable roof systems with several environmental, economic, and social benefits, as well as an effective and practical strategy for mitigating the negative consequences of urbanization. In this paper, we used CiteSpace and VOSviewer bibliometric software for visual analysis, citation analysis, co-authorship network, co-citation analysis, and keyword analysis for descriptive statistics on 3986 articles on “green roofs” published in the Web of Science core database since 2000. Descriptive statistics were used for citation analysis, co-authorship network, co-citation analysis, and keyword analysis. According to a review of green roofing-related research literature, (1) Through analysis from three dimensions of country, institution, and author, it was found that China, the United States, and Italy ranked among the top three countries in terms of green roof publication volume; All but three of the top 10 institutions in terms of publications are from China and all are from developed countries; A large-scale collaborative network has not yet formed among authors. (2) Through keyword clustering analysis, it was found that “green roof,” “performance,” and “UHI” were the three keywords with the highest frequency. The research direction of this theme mainly includes five primary themes: rainwater management, urban biodiversity, building energy efficiency, alleviating urban heat islands and improving air quality, sustainable development, and public health. Through keyword hot words, it is found that the frequency of occurrence is relatively high, mainly involving energy conservation, alleviating urban heat islands, biodiversity, and sustainable development. The research on sustainable development, its impact on urban microclimate, and air quality remains a hot topic through keyword highlighting. (3) Co-citation analysis was used to identify the most influential journals, highly cited publications, and authors. (4) Three potential study objectives have been identified: synergistic development with other green infrastructures from an urban planning standpoint, localized research on green roofs, and photovoltaic green roofs

runtime verification of data-centric properties in service based systems

For service-based systems which are composed of multiple independent stakeholders, correctness cannot be ascertained statically. Continuous monitoring is required to assure that runtime behavior of the systems complies with specified properties. However, most existing work considers only the temporal constraints of messages exchanged between services, ignoring the actual data contents inside the messages. As a result, it is difficult to validate some dynamic properties such as how message data of interest is processed between different participants. To address this issue, this paper proposes an efficient, online monitoring approach to dynamically analyze data-centric properties in service-based systems. By introducing Par-BCL - a Parametric Behavior Constraint Language for Web services - various data-centric properties can be specified and monitored. To keep runtime overhead low, we statically analyze the monitored properties to generate parameter state machine, and combine two different indexing mechanisms to optimize the monitoring. The experiments show that the proposed approach is efficient. © 2012 Springer-Verlag.For service-based systems which are composed of multiple independent stakeholders, correctness cannot be ascertained statically. Continuous monitoring is required to assure that runtime behavior of the systems complies with specified properties. However, most existing work considers only the temporal constraints of messages exchanged between services, ignoring the actual data contents inside the messages. As a result, it is difficult to validate some dynamic properties such as how message data of interest is processed between different participants. To address this issue, this paper proposes an efficient, online monitoring approach to dynamically analyze data-centric properties in service-based systems. By introducing Par-BCL - a Parametric Behavior Constraint Language for Web services - various data-centric properties can be specified and monitored. To keep runtime overhead low, we statically analyze the monitored properties to generate parameter state machine, and combine two different indexing mechanisms to optimize the monitoring. The experiments show that the proposed approach is efficient. © 2012 Springer-Verlag

runtime monitoring of data-centric temporal properties for web services

IEEE; IEEE Computer Society (CS); TC-SVC; IBM; SAPRuntime monitoring of Web service compositions has been widely acknowledged as a significant approach to understand and guarantee the quality of services. However, existing runtime monitoring solutions consider only the constraints on the sequence of messages exchanged between partner services and ignore the actual data contents inside the messages. As a result, it is difficult to monitor some dynamic properties such as how message data of interest is processed between different participants. To address this issue, we propose an efficient, non-intrusive online monitoring approach to dynamically analyze data-centric properties for service-oriented applications involving multiple participants. By introducing Par-BCL - a Parametric Behavior Constraint Language for web services - to define monitoring parameters, various data-centric temporal behavior properties for Web services can be specified and monitored. This approach broadens the monitored patterns to include not only message exchange orders, but also the data contents bound to the parameters. To reduce runtime overhead, we statically analyze the monitored properties to generate parameter state machine from the event pattern automata to optimize monitoring. The experiments show that our solution is efficient and promising. © 2011 IEEE

specification and monitoring of data-centric temporal properties for service-based systems

Service-based systems operate in a very dynamic environment. To guarantee functional and non-functional objective at runtime, an adaptation mechanism is usually expected to monitor software changes, make appropriate decisions, and act accordingly. However, existing runtime monitoring solutions consider only the constraints on the sequence of messages exchanged between partner services and ignore the actual data contents inside the messages. As a result, it is difficult to monitor some dynamic properties such as how message data of interest is processed between different participants. To address this issue, we propose an efficient, non-intrusive online monitoring approach to dynamically analyze data-centric properties for service-oriented applications involving multiple participants. By introducing Par-BCL - a Parametric Behavior Constraint Language for Web services - to define monitoring parameters, various data-centric temporal behavior properties for Web services can be specified and monitored. This approach broadens the monitored patterns to include not only message exchange orders, but also data contents bound to the parameters. To reduce runtime overhead, we statically analyze the monitored properties and combine two different indexing mechanisms to optimize monitoring. The experiments show that our solution is efficient and promising. © 2012 Elsevier Inc. All rights reserved