Journal articles: 'Aggregation Platform'

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Bray, Natasha. "A platform for probing protein-aggregation inhibitors." Nature Reviews Drug Discovery 15, no. 2 (January 29, 2016): 85. http://dx.doi.org/10.1038/nrd.2016.8.

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Dai, Zhihuang, and Michael J. Scott. "Effective Product Family Design Using Preference Aggregation." Journal of Mechanical Design 128, no. 4 (October 11, 2005): 659–67. http://dx.doi.org/10.1115/1.2197835.

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The development of product families, groups of products that share a common platform, is one way to provide product variety while keeping design and production costs low. The design of a product platform can be formulated as a multicriteria optimization problem in which the performances of individual products trade off against each other and against the objective of platform standardization. The problem is often solved in two stages: one to determine the values of the shared platform variables and a second to optimize the product family members with respect to specific targets. In the first stage, it is common to target the mean and variability of performance when fixing the values of platform variables. This paper contributes three new methods for platform development. The new methods are demonstrated on an electric motor example from the platform design literature, and the results are compared to those from existing methods. First, a preference aggregation method is applied to aggregate the multiple objectives into a single overall objective function. On the example problem, this approach gives superior results to existing techniques. Second, an alternative method that targets the minimum and maximum of the range of performance across the platform, instead of the mean and standard deviation, is proposed and shown to succeed where the existing method may fail. Third, a single-stage optimization approach which solves for both platform and nonplatform variables in a single pass is presented. This method delivers notably superior performance on the example problem but will, in general, incur greater computational expense.

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Cunha, David, Pedro Neves, and Pedro Sousa. "PaaS manager: A platform-as-a-service aggregation framework." Computer Science and Information Systems 11, no. 4 (2014): 1209–28. http://dx.doi.org/10.2298/csis130828028c.

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The advent of Cloud Computing opened new opportunities in several areas, namely in the application development processes. As consequence, nowadays, PaaS (Platform-as-a-Service) service model allows simpler and flexible deployment strategies of applications, avoiding the need for dedicated networks, servers, storage, and other services. Within this context, several PaaS providers exist in the market, but each one having specific characteristics, proprietary technologies and Application Programming Interfaces (APIs). Based on such assumptions, this work addresses the challenge of devising a PaaS aggregation solution with the objective of unifying the information and management processes of applications created in PaaS environments. The proposed solution, denominated as PaaS Manager, take the form of a PaaS API aggregator aiming to struggle the existing lock-in in the PaaS market. In this perspective, this paper describes the specification, development and test of the proposed PaaS Manager solution. As result of this framework, end-users are able to select the most appropriate PaaS platform for an application, interacting with any supported vendor through a unique deployment and management interface.

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Wang, Fang Fang, Xiu Yuan Zhang, and Gang Wang. "Study on Urban Rail Transit Platform Aggregation Passenger." Applied Mechanics and Materials 253-255 (December 2012): 1812–15. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1812.

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It is the basis for increasing attraction of rail transit and maximizing the attraction of public transport to focus on summarizing the pattern and experience of growing rail passenger flow, and studying the characteristics of trip assignment. This paper studied specifically on the passenger assembling of the urban rail transit platform, and designed the calculation methods about assembling passengers on platform through the analysis of passenger flow characteristics. Based on the specific situation of the subway of Beijing south station, this paper analyzed the assembling of platform and obtained assembling data under different conditions. The result shows that, in order to smooth the assembling of platform, we could reduce the train arrival time-gap, stagger the up and down train’s arrival time and increase their arrival time-gap in a proper way.

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YU, Hui. "PCP: P2P-based computing resource sharing and aggregation platform." Journal of Computer Applications 29, no. 10 (December 17, 2009): 2647–51. http://dx.doi.org/10.3724/sp.j.1087.2009.02647.

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Xu, Youwei, Shengqun Tang, Yan Yang, Yang Xu, and Ling Li. "Development and research on the internet resources aggregation platform." Wuhan University Journal of Natural Sciences 12, no. 2 (March 2007): 243–48. http://dx.doi.org/10.1007/s11859-006-0029-x.

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KAO, BEN, and RON KATRIEL. "SUBSAMPLED MODEL AGGREGATION." International Journal on Artificial Intelligence Tools 14, no. 03 (June 2005): 385–97. http://dx.doi.org/10.1142/s0218213005002168.

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There has been a recent push for a new framework of learning, due in part to the availability of storage, networking and the abundance of very large datasets. This framework argues for parallelized learning algorithms that can operate on a distributed platform and have the ability to terminate early in the likely event that data size is too inundating. Methods described herein propose a subsampled model aggregation technique based on the bagging algorithm. It is capable of significant run-time reduction with no loss in modeling performance. These claims were validated with a variety of base-learning algorithms on large web and newswire datasets.

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Tarabichi, Yasir, Adam Frees, Steven Honeywell, Courtney Huang, Andrew M. Naidech, Jason H. Moore, and David C. Kaelber. "The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform." ACI Open 05, no. 01 (January 2021): e36-e46. http://dx.doi.org/10.1055/s-0041-1731004.

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Abstract Objective Learning healthcare systems use routinely collected data to generate new evidence that informs future practice. While implementing an electronic health record (EHR) system can facilitate this goal for individual institutions, meaningfully aggregating data from multiple institutions can be more empowering. Cosmos is a cross-institution, single EHR vendor-facilitated data aggregation tool. This work aims to describe the initiative and illustrate its potential utility through several use cases. Methods Cosmos is designed to scale rapidly by leveraging preexisting agreements, clinical health information exchange networks, and data standards. Data are stored centrally as a limited dataset, but the customer facing query tool limits results to prevent patient reidentification. Results In 2 years, Cosmos grew to contain EHR data of more than 60 million patients. We present practical examples illustrating how Cosmos could further efforts in chronic disease surveillance (asthma and obesity), syndromic surveillance (seasonal influenza and the 2019 novel coronavirus), immunization adherence and adverse event reporting (human papilloma virus and measles, mumps, rubella, and varicella vaccination), and health services research (antibiotic usage for upper respiratory infection). Discussion A low barrier of entry for Cosmos allows for the rapid accumulation of multi-institutional and mostly de-duplicated EHR data to power research and quality improvement queries characteristic of learning healthcare systems. Limitations are being vendor-specific, an “all or none” contribution model, and the lack of control over queries run on an institution's healthcare data. Conclusion Cosmos provides a model for within-vendor data standardization and aggregation and a steppingstone for broader intervendor interoperability.

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Fomba, Soumana, Pascale Zarate, Marc Kilgour, Guy Camilleri, Jacqueline Konate, and Fana Tangara. "A Recommender System Based on Multi-Criteria Aggregation." International Journal of Decision Support System Technology 9, no. 4 (October 2017): 1–15. http://dx.doi.org/10.4018/ijdsst.2017100101.

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Recommender systems aim to support decision-makers by providing decision advice. We review briefly tools of Multi-Criteria Decision Analysis (MCDA), including aggregation operators, that could be the basis for a recommender system. Then we develop a multi-criteria recommender system, STROMa (SysTem of RecOmmendation Multi-criteria), to support decisions by aggregating measures of performance contained in a performance matrix. The system makes inferences about preferences using a partial order on criteria input by the decision-maker. To determine a total ordering of the alternatives, STROMa uses a multi-criteria aggregation operator, the Choquet integral of a fuzzy measure. Thus, recommendations are calculated using partial preferences provided by the decision maker and updated by the system. An integrated web platform is under development.

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Jariwala, Vivaksha, Himanshu Patel, Parth Patel, and Devesh C. Jinwala. "Integrity and Privacy Preserving Secure Data Aggregation in Wireless Sensor Networks." International Journal of Distributed Systems and Technologies 5, no. 3 (July 2014): 77–99. http://dx.doi.org/10.4018/ijdst.2014070104.

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Data aggregation based on in-network processing is useful in improving the communications overhead in Wireless Sensor Networks (WSNs) by reducing the overall number of packets communicated to the base station. However, due to the fusion of data items sourced at different nodes into a single one, the security of the aggregated data as well as that of the aggregating node, demands critical investigation. This paper observes that though there have been substantial numbers of research attempts recently in proposing techniques for secure data aggregation, there is still a need for a coherent, integrated framework for secure data aggregation. It proposes such an integrated framework for secure data aggregation in this paper. The proposed framework implements a secure data aggregation protocol, offering the attributes viz. confidentiality, privacy, authentication, robustness, as well as data integrity using a defined data aggregation topology. In addition to that, the proposed framework is based on a zero configuration protocol that supports a generation of a defined aggregation topology and a key exchange procedure. This work supports the framework with detailed security analysis and performance evaluation on TinyOS platform using TOSSIM as the base simulator. Through humble observations, this is an unique attempt that integrates the support for security features, topology generation and key management in a single, secure data aggregation protocol; substantiating the proposal with elaborate experimental evaluation, too.

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KODAMA, Yuki, Makoto MIZUKAWA, and Yoshinobu ANDO. "2P1-H11 Development of sensor data aggregation platform for KUKANCHI." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2008 (2008): _2P1—H11_1—_2P1—H11_3. http://dx.doi.org/10.1299/jsmermd.2008._2p1-h11_1.

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Saunders, Janet C., Lydia M. Young, Rachel A. Mahood, Matthew P. Jackson, Charlotte H. Revill, Richard J. Foster, D. Alastair Smith, Alison E. Ashcroft, David J. Brockwell, and Sheena E. Radford. "An in vivo platform for identifying inhibitors of protein aggregation." Nature Chemical Biology 12, no. 2 (December 14, 2015): 94–101. http://dx.doi.org/10.1038/nchembio.1988.

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Bartolozzi, Alfredo, Salvatore Favuzza, Mariano Ippolito, Diego La Cascia, Eleonora Riva Sanseverino, and Gaetano Zizzo. "A New Platform for Automatic Bottom-Up Electric Load Aggregation." Energies 10, no. 11 (October 25, 2017): 1682. http://dx.doi.org/10.3390/en10111682.

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Saccomanno, F. F., K. C. Chong, and S. A. Nassar. "Geographic Information System Platform for Road Accident Risk Modeling." Transportation Research Record: Journal of the Transportation Research Board 1581, no. 1 (January 1997): 18–26. http://dx.doi.org/10.3141/1581-03.

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Road accident risk assessment requires a thorough understanding of both the vehicle accident involvement process and the severity of resultant injuries. A geographic information system (GIS) platform is especially suited to this type of problem because it provides an efficient system of linking a large number of disparate data bases, it provides a spatial referencing system for reporting output at different levels of aggregation, it allows input of both historical and statistical accident experience in estimating accident risk at different locations and times, and it allows controls on a myriad of risk factors explaining variations in accident involvement and injury severity. A GIS-based accident risk model developed for the Ontario highway network is described. The model provides estimates of accident risk at four levels of spatial aggregation as specified by the user: networkwide, route-specific, route-section-specific and site-specific.

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Jain, Shubha, Sarpras Swain, Lopamudra Das, Sarita Swain, Lopamudra Giri, Anand Kumar Kondapi, and Harikrishnan Narayanan Unni. "Microfluidic Protein Imaging Platform: Study of Tau Protein Aggregation and Alzheimer’s Drug Response." Bioengineering 7, no. 4 (December 13, 2020): 162. http://dx.doi.org/10.3390/bioengineering7040162.

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Tau protein aggregation is identified as one of the key phenomena associated with the onset and progression of Alzheimer’s disease. In the present study, we performed on-chip confocal imaging of tau protein aggregation and tau–drug interactions using a spiral-shaped passive micromixing platform. Numerical simulations and experiments were performed in order to validate the performance of the micromixer design. We performed molecular modeling of adenosine triphosphate (ATP)-induced tau aggregation in order to successfully validate the concept of helical tau filament formation. Tau aggregation and native tau restoration were realized using an immunofluorescence antibody assay. The dose–response behavior of an Alzheimer’s drug, methylthioninium chloride (MTC), was monitored on-chip for defining the optimum concentration of the drug. The proposed device was tested for reliability and repeatability of on-chip tau imaging. The amount of the tau protein sample used in our experiments was significantly less than the usage for conventional techniques, and the whole protein–drug assay was realized in less than two hours. We identified that intensity-based tau imaging could be used to study Alzheimer’s drug response. In addition, it was demonstrated that cell-free, microfluidic tau protein assays could be used as potential on-chip drug evaluation tools for Alzheimer’s disease.

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Maningo, Jose Martin Z., Ryan Rhay P. Vicerra, Laurence A. Gan Lim, Edwin Sybingco, Elmer P. Dadios, and Argel A. Bandala. "Smoothed Particle Hydrodynamics Approach to Aggregation of Quadrotor Unmanned Aerial Vehicle Swarm." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 2 (March 15, 2017): 181–88. http://dx.doi.org/10.20965/jaciii.2017.p0181.

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This paper uses a fluid mechanics approach to perform swarming aggregation on a quadrotor unmanned aerial vehicle (QUAV) swarm platform. This is done by adapting the Smoothed Particle Hydrodynamics (SPH) technique. An algorithm benchmarking is conducted to see how well SPH performs. Simulations of varying set-ups are experimented to compare different algorithms with SPH. The position error of SPH is 30% less than the benchmark algorithm when a target enclosure is introduce. SPH is implemented using Crazyflie quadrotor swarm. The aggregation behavior exhibited successfully in the said platform.

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Li, Zhong Kai, Xiu Rong Li, and Zhen Cai Zhu. "Scalable Platform Robust Reconfiguration Method with Sensitivity Analysis and Fuzzy Clustering." Applied Mechanics and Materials 52-54 (March 2011): 1026–31. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1026.

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For improving the quick responses and instances quality in platform based product family design, a scalable platform reconfiguration method using sensitivity analysis and fuzzy clustering is proposed with robust design theory. The possible platform constants and scaling variables sets are divided by design variable sensitivity analysis firstly, during which multiple performances are aggregated by preference aggregation to ease the sensitivity for total product. Then the performance preference, robust deviation and constraint violation changes caused by constant sharing are clustered by fuzzy c-means algorithm (FCM) to reasonably plan the constant multiple platforms sharing strategy. A fuzzy percentage index is introduced in FCM to determine the optimal cluster number in fuzzy clustering. Finally the instances deviated from platform are optimized to set scaling variables. The efficiency and effectiveness of proposed method is illustrated by the optimization of scalable capacitor-run single-phase induction motor families, and the results are compared against previous work.

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Sebastian, Kevin, Abhin Babu, Jeswin Thomas, Chris Thomas, and Jayakrishna V. "Marqur - A Social Platform for Location-based Content Aggregation and Discussion." EAI Endorsed Transactions on Creative Technologies 7, no. 25 (December 18, 2020): 167289. http://dx.doi.org/10.4108/eai.30-11-2020.167289.

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Johnson, Litty, Maria Galini Faidra Angelerou, Bhanu Teja Surikutchi, Stephanie Allen, Mischa Zelzer, and Maria Marlow. "Low Molecular Weight Nucleoside Gelators: A Platform for Protein Aggregation Inhibition." Molecular Pharmaceutics 16, no. 1 (November 29, 2018): 462–67. http://dx.doi.org/10.1021/acs.molpharmaceut.8b01013.

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Kawska, Agnieszka, Patrick Duchstein, Oliver Hochrein, and Dirk Zahn. "From Ion Aggregation to Nanocrystal (Self-)Organization: a Transferable Simulation Platform." Zeitschrift für anorganische und allgemeine Chemie 634, no. 11 (September 2008): 2017. http://dx.doi.org/10.1002/zaac.200870020.

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Nechifor, Alexandru, Mihaela Albu, Richard Hair, and Vladimir Terzija. "A flexible platform for synchronized measurements, data aggregation and information retrieval." Electric Power Systems Research 120 (March 2015): 20–31. http://dx.doi.org/10.1016/j.epsr.2014.11.008.

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Tokareva, Victoria. "Optimization of request processing times for a heterogeneous data aggregation platform." Journal of Physics: Conference Series 1740 (January 2021): 012058. http://dx.doi.org/10.1088/1742-6596/1740/1/012058.

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Cappelli, Andrea, Marco Paolino, Annalisa Reale, Vincenzo Razzano, Giorgio Grisci, Germano Giuliani, Alessandro Donati, et al. "Hyaluronan-based graft copolymers bearing aggregation-induced emission fluorogens." RSC Advances 8, no. 11 (2018): 5864–81. http://dx.doi.org/10.1039/c7ra12543g.

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Blasio, Emiliana De, and Lorenzo Viviani. "Platform Party between Digital Activism and Hyper-Leadership: The Reshaping of the Public Sphere." Media and Communication 8, no. 4 (October 8, 2020): 16–27. http://dx.doi.org/10.17645/mac.v8i4.3230.

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The so-called crisis of representation has formed the theoretical framework of many studies on media and democracy of the past thirty years. Many researches have highlighted the crisis of legitimacy and credibility of the ‘traditional’ parties (Katz & Mair, 2018) and communication was considered, at the same time, one of the causes of acceleration towards post-representative politics (Keane, 2013) but also an indispensable tool for re-connecting citizens to politics. Various phenomena have developed within this framework: a) the birth of political aggregations as a result of mobilization in the digital ecosystem; b) the development of digital platforms for democratic participation; c) the birth of parties defined as ‘digital’ or ‘platform’; and d) the growing centrality of digital political activism, both as a phenomenon within the digital communicative ecosystem (also in the context of social media) and as a result of the transformation of social movements. This article studies the role of platform parties as a space for the emergence of authoritarian tendencies (hyper-leadership) but also as an organizational opportunity for the development of new forms of digital activism. In particular, the article presents a research on the use of digital platforms (and their political and organizational consequences) by political parties in Italy, France, and Spain. The study shows the relationships between the evolution of digital ecosystems and the way in which political organization is organised, also highlighting how the new forms of mobilization and aggregation have opened up different yet interconnected public spaces.

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S., Vimal, and Srivatsa S K. "A Reliable Peer-to-Peer Platform for Adding New Node Using Trust Based Model." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2017): 3515. http://dx.doi.org/10.11591/ijece.v7i6.pp3515-3520.

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In order to evaluate the trustworthiness of participating peers in unstructured peer-to-peer networks, Reputation aggregation methods are used in this method. Each and every peer of the network will collect the local scores of each transaction and will compute global scores by aggregating all the local scores with the help of global scores, each individual peer can interact with its suitable peers. But the existing method will not consider the score of the new peer. In this condition, requests are handled by existing peers who leads to failure in downloading process. To rectify this, NP-TRUST model is used to distribute the request to all peers including the newly joined peers. The proposed method is compared with gossip and DFR-TRUST model in Transaction Success rate and variation in file request.

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Heileman, K. L., and M. Tabrizian. "Dielectric spectroscopy platform to measure MCF10A epithelial cell aggregation as a model for spheroidal cell cluster analysis." Analyst 142, no. 9 (2017): 1601–7. http://dx.doi.org/10.1039/c6an02156e.

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Sun, Xiuxia, Yan Qiao, Wenhua Li, Yiyao Sui, Yiyan Ruan, and Jianxi Xiao. "A graphene oxide-aided triple helical aggregation-induced emission biosensor for highly specific detection of charged collagen peptides." Journal of Materials Chemistry B 8, no. 28 (2020): 6027–33. http://dx.doi.org/10.1039/d0tb00476f.

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Bhaumik, Shubhra Kanti, Yoti Shankar Patra, and Supratim Banerjee. "High affinity heparin detection by multivalent supramolecular polymers through aggregation induced emission." Chemical Communications 56, no. 66 (2020): 9541–44. http://dx.doi.org/10.1039/d0cc03644g.

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Wang, Ruyan, Shiqi Zhang, Zhigang Yang, Puning Zhang, Dapeng Wu, Yongling Lu, and Alexander Fedotov. "Private Data Aggregation Based on Fog-Assisted Authentication for Mobile Crowd Sensing." Security and Communication Networks 2021 (September 22, 2021): 1–12. http://dx.doi.org/10.1155/2021/7354316.

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In mobile crowd sensing (MCS), the cloud as a single sensing platform undertakes a large number of communication tasks, leading to the reduction of sensing task execution efficiency and the risk of loss and leakage of users’ private data. In this paper, we propose a spatial ciphertext aggregation scheme with collaborative verification of fog nodes. Firstly, the cloud and fog collaboration architecture is constructed. Fog nodes are introduced for data validation and slices transmission, reducing computing cost on the sensing platform. Secondly, a multipath transmission method of slice data is proposed, in which the user identity and data are transmitted anonymously by the secret sharing method, and the data integrity is guaranteed by hash chain authentication. Finally, a spatial data aggregation method based on privacy protection is presented. The ciphertext aggregation calculation of the sensing platform is realized through Paillier homomorphic encryption, and the problem of insufficient data coverage in the sensing region is solved by the position-based weight interpolation method. The security analysis demonstrates that the scheme can achieve the expected security goal. The simulation results show the feasibility and effectiveness of the proposed scheme.

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Li, Yao, Wei Huang, Juan Yong, Shuaidan Huang, Yujie Li, Yang Liu, and Dayu Wu. "Aggregation-induced ratiometric emission and mechanochromic luminescence in a pyrene-benzohydrazonate conjugate." New Journal of Chemistry 42, no. 15 (2018): 12644–48. http://dx.doi.org/10.1039/c8nj01379a.

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Disha, Poonam Kumari, Manoj K. Nayak, and Parveen Kumar. "An electrochemical biosensing platform for progesterone hormone detection using magnetic graphene oxide." Journal of Materials Chemistry B 9, no. 26 (2021): 5264–71. http://dx.doi.org/10.1039/d1tb00380a.

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A facile and label-free electrochemical approach based on magnetic graphene oxide nanomaterials with a large surface to volume ratio and less susceptible to aggregation proved promising in developing highly sensitive and selective sensing of progesterone.

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Zhao, Shuaiguo, Po-Hsun Huang, Heying Zhang, Joseph Rich, Hunter Bachman, Jennifer Ye, Wenfen Zhang, et al. "Fabrication of tunable, high-molecular-weight polymeric nanoparticles via ultrafast acoustofluidic micromixing." Lab on a Chip 21, no. 12 (2021): 2453–63. http://dx.doi.org/10.1039/d1lc00265a.

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An acoustofluidic platform is developed to synthesize high-molecular-weight polymeric nanoparticles in a size- and structure-controlled manner, while eliminating polymer aggregation within the microchannel.

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Liang, Yu, and Wu. "Air-Conditioning Resource Management and Control Method based on Cloud Platform for Wind Power Consumption." Processes 7, no. 7 (July 19, 2019): 467. http://dx.doi.org/10.3390/pr7070467.

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Air-conditionings have energy storage functions. Through reasonable aggregation control, the output tracking can be implemented for wind power with stronger fluctuation to enhance its utilization rate. Cloud technology and intelligent appliances enable the appliance vendor to implement information interaction with the air-conditioning through cloud platforms to realize flexible regulation. In this paper, a management and control method of air-conditioning based on cloud platform is established. Based on this structure, the air-conditionings are divided into several aggregation groups according to the similarity of parameters, and each group completes the consumption task collaboratively. The consumption evaluation model of the air-conditioning group is established. On this basis, the allocation problem on consumption task for the aggregated group is constructed to implement the optimal solution under the condition of guaranteeing the degree of completion and user comfort. Each group implements the control for air-conditioning inside the group through the sliding mode control model. The simulation experiment verifies that the algorithm can effectively follow the output of clean energy, while intervening less in the air-conditioning operation.

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Bernard, Abigail B., Chien-Chi Lin, and Kristi S. Anseth. "A Microwell Cell Culture Platform for the Aggregation of Pancreatic β-Cells." Tissue Engineering Part C: Methods 18, no. 8 (August 2012): 583–92. http://dx.doi.org/10.1089/ten.tec.2011.0504.

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Cui, Yun, Myoungjin Kim, Jongjin Jung, Khongmin Kwon, Baul Kim, Ilkyeun Ra, and Hanku Lee. "Customized Recommendation System Based on Rule Matrix in SaaS Aggregation Service Platform." Advanced Science Letters 23, no. 12 (December 1, 2017): 12769–74. http://dx.doi.org/10.1166/asl.2017.10896.

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Ayadi, Hana, Nadia Hamani, Lyes Kermad, and Mounir Benaissa. "Novel Fuzzy Composite Indicators for Locating a Logistics Platform under Sustainability Perspectives." Sustainability 13, no. 7 (April 1, 2021): 3891. http://dx.doi.org/10.3390/su13073891.

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The purpose of this paper is to help decision-makers choose the location of a logistics platform with sustainability perspectives. This study presents a compensatory and partially compensatory approach to build composite indicators, using mainly fuzzy multi-criteria decision-making methods. In the first instance, the fuzzy full consistency method (F-FUCOM) was used to calculate the weight of the criteria and sub-criteria. In the second instance, two aggregation methods, namely the fuzzy multi-attribute ideal-real comparative analysis (F-MAIRCA) and the fuzzy preference ranking organization method for enrichment evaluation (F-PROMETHEE), were used to rank the location of a logistics platform. The novelty of the work lays in studying the impact of limited sustainability and weak sustainability on the location of a logistics platform. In this respect, the aggregation of various sustainability criterion in fuzzy compensatory and partially compensatory composite indicators is an innovative and interesting approach used to locate a logistics platform. The obtained results show that economic sustainability is the most important criterion for the selection of a logistics platform, followed by the environmental criterion. Obviously, the F-MAIRCA and F-PROMETHEE methods provided the same ranking orders. Finally, sensitivity analyses were performed to validate the robustness of the proposed approach.

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Yamaguchi, Akinobu, Takao Fukuoka, Ryohei Hara, Kazuhisa Kuroda, Ryo Takahashi, and Yuichi Utsumi. "On-chip integration of novel Au electrode with a higher order three-dimensional layer stack nanostructure for surface-enhanced Raman spectroscopy." RSC Advances 5, no. 89 (2015): 73194–201. http://dx.doi.org/10.1039/c5ra10728h.

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We develop a novel in situ surface-enhanced Raman spectroscopy (SERS) platform with three-dimensional nanostructure gold electrodes using the competitive self-assembly between dielectrophoresis and convective aggregation.

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Yang, Ying, Yinlong Zhou, Shuxin Wang, Xueyan Wang, Xuan Liu, Anjian Xie, Yuhua Shen, and Manzhou Zhu. "A structurally precise AgxAu25−x nanocluster based cancer theranostic platform with tri-targeting/in situ O2-generation/aggregation enhanced fluorescence imaging/photothermal–photodynamic therapies." Chemical Communications 56, no. 68 (2020): 9842–45. http://dx.doi.org/10.1039/d0cc02946g.

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Guo, Jingjing, Shimin Hu, Wenwen Luo, Rongrong Hu, Anjun Qin, Zujin Zhao, and Ben Zhong Tang. "A novel aggregation-induced emission platform from 2,3-diphenylbenzo[b]thiophene S,S-dioxide." Chemical Communications 53, no. 9 (2017): 1463–66. http://dx.doi.org/10.1039/c6cc09892d.

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Larsson, Stefan. "Putting trust into antitrust? Competition policy and data-driven platforms." European Journal of Communication 36, no. 4 (July 13, 2021): 391–403. http://dx.doi.org/10.1177/02673231211028358.

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Anti-competitive notions, it seems, are increasingly informing the critical debate on a data-driven economy organised into scalable digital platforms. Issues of market definitions, how to value personal data on multisided platforms, and how to detect and regulate misuses of dominant positions have become key nomenclature on the battlefield of addressing fairness in our contemporary digital societies. This article looks at the central themes for this special issue on governing trust in European platform societies through the lens of contemporary developments in the field of competition law. Three main questions are addressed: (1) To what extent are the platforms’ own abilities to govern their infrastructures, that is, to be de facto regulators over both human behaviour and market circumstances, a challenge for contemporary competition regulation? (2) In what way is the collection, aggregation, or handling of consumers’ data of relevance for competition? (3) How can the particular European challenges of governing US-based digital platforms more broadly be understood in terms of the relationship between transparency and public trust? Of particular relevance – and challenge – here are the platforms’ abilities to govern their infrastructures, albeit through automated moderation, pricing or scalable data handling. It is argued that this aspect of coded, and possibly autonomously adapting, intra-platform governance, poses significant anti-competitive challenges for supervisory authorities, with possible negative implications for consumer autonomy and wellbeing as well as platform-dependent other companies.

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Xiao, Qin. "Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining." Ingénierie des systèmes d information 25, no. 5 (November 10, 2020): 645–53. http://dx.doi.org/10.18280/isi.250512.

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The traditional knowledge service systems have nonuniform data structures. Some data are structured, while some are semi-structured and even non-structured. Big data technology helps to optimize the integration and retrieval of the massive data on library and information (L&I), making it possible to classify the resources and optimize the configuration of L&I resource platforms according to user demand. Therefore, this paper introduces the new information service model of big data resources and knowledge services to the processing of L&I data. Firstly, the data storage structure and relationship model of the L&I resource platform were established, and used to sample and integrate the keywords of resource retrieval. Next, an L&I resource classification model was constructed based on support vector machine (SVM), and applied to extract and quantify the attributes of the keywords of resource retrieval. After that, a knowledge aggregation model was developed for a complex network of multiple L&I resource platforms. Experimental results demonstrate the effectiveness of the proposed knowledge aggregation model. The research findings provide a reference for the application of data mining in resource classification.

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Prusti, Banchhanidhi, and Manab Chakravarty. "Disparity in piezofluorochromism for twisted mono-carbazole-based AIEgens resulting from interchanging electron-rich substituents: effect of coplanarity on twisted π-conjugates." Materials Advances 2, no. 5 (2021): 1752–59. http://dx.doi.org/10.1039/d0ma00933d.

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Newly established carbazole-based aggregation-induced emission-active fluorogens are recognized with piezo-fluorochromic features that vary with the effect of planarity. Suitable probe is demonstrated as a platform for rewritable optical recording.

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Everett, AG, ST Szedlmayer, and BJ Gallaway. "Movement patterns of red snapper Lutjanus campechanus based on acoustic telemetry around oil and gas platforms in the northern Gulf of Mexico." Marine Ecology Progress Series 649 (September 10, 2020): 155–73. http://dx.doi.org/10.3354/meps13448.

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Offshore oil and gas platforms in the northern Gulf of Mexico are known aggregation sites for red snapper Lutjanus campechanus. To examine habitat use and potential mortality from explosive platform removals, fine-scale movements of red snapper were estimated based on acoustic telemetry from March 2017 to July 2018. Study sites in the northern Gulf of Mexico, USA, included one platform off coastal Alabama (30.09°N, 87.88°W) and 2 platforms off Louisiana (28.81°N, 91.97°W; 28.92°N, 93.15°W). Red snapper (n = 59) showed a high affinity for platforms, with most (94%) positions being recorded within 95 m of the platforms. Home range areas were correlated with water temperature and inversely correlated with dissolved oxygen concentrations. During summer and fall, red snapper used larger areas and many fish (54%) emigrated from their platforms but most (83%) returned in ≤3 d. Site fidelity for red snapper was 31% yr-1 and residency time was 7 mo, but the probability-of-presence at platforms was 70% after 1 yr, indicating the importance of platforms for this species. Overall fishing mortality was high for platforms (F = 0.86, 95% CL = 0.47-1.40), but since the stock is managed on a quota basis this high mortality should have little effect on total stock abundance. Thus, platforms can still provide an important habitat for red snapper, and consideration of area use patterns, fishing mortality and environmental factors can reduce red snapper mortality when scheduling explosive platform removals. As such, the present study indicates that an optimum time for explosive removal would be in late summer after the red snapper fishing season is completed.

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Jankov, Dimitrije, Binhang Yuan, Shangyu Luo, and Chris Jermaine. "Distributed numerical and machine learning computations via two-phase execution of aggregated join trees." Proceedings of the VLDB Endowment 14, no. 7 (March 2021): 1228–40. http://dx.doi.org/10.14778/3450980.3450991.

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When numerical and machine learning (ML) computations are expressed relationally, classical query execution strategies (hash-based joins and aggregations) can do a poor job distributing the computation. In this paper, we propose a two-phase execution strategy for numerical computations that are expressed relationally, as aggregated join trees (that is, expressed as a series of relational joins followed by an aggregation). In a pilot run, lineage information is collected; this lineage is used to optimally plan the computation at the level of individual records. Then, the computation is actually executed. We show experimentally that a relational system making use of this two-phase strategy can be an excellent platform for distributed ML computations.

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Chang, Chia-Chen, Chie-Pein Chen, Chen-Yu Chen, and Chii-Wann Lin. "DNA base-stacking assay utilizing catalytic hairpin assembly-induced gold nanoparticle aggregation for colorimetric protein sensing." Chemical Communications 52, no. 22 (2016): 4167–70. http://dx.doi.org/10.1039/c6cc01238h.

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A label-free and enzyme-free colorimetric sensing platform for the amplified detection of fibronectin was developed based on an ingenious combination of catalytic hairpin assembly and a base stacking hybridization-based gold nanoparticle aggregation strategy.

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Ren, Zong Qiang, and Hong Bin Zhang. "Networking Agglomeration Effect of E-Commerce Platform in Industry Clusters." Applied Mechanics and Materials 631-632 (September 2014): 1140–44. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1140.

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Agglomeration effect of e-commerce platform based on industry clusters is demonstrated from locus of social networks with Ucinet 6.0. An industry zone of electrical manufacturing districts in China is investigated to describe the evolution of structure based on e-commerce platform from emergence to aggregation. The result shows that based on e-commerce platform, small world features of industry clusters are obvious with shorter distance and higher clustering coefficient, and resources flow and configuration is faster than before. E-commerce platform can diversify the nature of clustering with high heterogeneity and betweenness. However, the sharply increased network centralization would indicate control advantages for third-party of e-commerce firms, even monopoly.

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Jiang, Xing, Abigail J. Halmes, Giuseppe Licari, John W. Smith, Yang Song, Edwin G. Moore, Qian Chen, Emad Tajkhorshid, Chad M. Rienstra, and Jeffrey S. Moore. "Multivalent Polymer–Peptide Conjugates: A General Platform for Inhibiting Amyloid Beta Peptide Aggregation." ACS Macro Letters 8, no. 10 (September 30, 2019): 1365–71. http://dx.doi.org/10.1021/acsmacrolett.9b00559.

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Wang, Qi, ZhongShi Zhang, Xiaotong Zhang, and Qing Zhao. "The Resource Aggregation and Integration Platform for Shared Development of the Direct Bank." Journal of Physics: Conference Series 1187, no. 5 (April 2019): 052026. http://dx.doi.org/10.1088/1742-6596/1187/5/052026.

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Li, Junwei, Yuan Li, Carrie Y. K. Chan, Ryan T. K. Kwok, Hongkun Li, Pavel Zrazhevskiy, Xiaohu Gao, Jing Zhi Sun, Anjun Qin, and Ben Zhong Tang. "An Aggregation-Induced-Emission Platform for Direct Visualization of Interfacial Dynamic Self-Assembly." Angewandte Chemie 126, no. 49 (October 31, 2014): 13736–40. http://dx.doi.org/10.1002/ange.201408757.

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Li, Junwei, Yuan Li, Carrie Y. K. Chan, Ryan T. K. Kwok, Hongkun Li, Pavel Zrazhevskiy, Xiaohu Gao, Jing Zhi Sun, Anjun Qin, and Ben Zhong Tang. "An Aggregation-Induced-Emission Platform for Direct Visualization of Interfacial Dynamic Self-Assembly." Angewandte Chemie International Edition 53, no. 49 (October 31, 2014): 13518–22. http://dx.doi.org/10.1002/anie.201408757.

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Journal articles on the topic 'Aggregation Platform'

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