Relevant bibliographies by topics / Group-query

Academic literature on the topic 'Group-query'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Group-query"

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Deng, Ke, Shazia Sadiq, Xiaofang Zhou, Hu Xu, Gabriel Pui Cheong Fung, and Yansheng Lu. "On Group Nearest Group Query Processing." IEEE Transactions on Knowledge and Data Engineering 24, no. 2 (February 2012): 295–308. http://dx.doi.org/10.1109/tkde.2010.230.

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Haryanto, Anasthasia Agnes, David Taniar, and Kiki Maulana Adhinugraha. "Group Reverse kNN Query optimisation." Journal of Computational Science 11 (November 2015): 205–21. http://dx.doi.org/10.1016/j.jocs.2015.09.006.

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Shan, Jing, Derong Shen, Tiezheng Nie, Yue Kou, and Ge Yu. "Searching overlapping communities for group query." World Wide Web 19, no. 6 (December 2, 2015): 1179–202. http://dx.doi.org/10.1007/s11280-015-0378-5.

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Li, Yafei, Rui Chen, Lei Chen, and Jianliang Xu. "Towards Social-Aware Ridesharing Group Query Services." IEEE Transactions on Services Computing 10, no. 4 (July 1, 2017): 646–59. http://dx.doi.org/10.1109/tsc.2015.2508440.

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Lukasiewicz, Thomas, Maria Vanina Martinez, Gerardo I. Simari, and Oana Tifrea-Marciuska. "Ontology-Based Query Answering with Group Preferences." ACM Transactions on Internet Technology 14, no. 4 (December 17, 2014): 1–24. http://dx.doi.org/10.1145/2677207.

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Sharma, Anjali, and Ajay Kr. Singh. "CBIR through CDH using Query by Group." International Journal of Computer Trends and Technology 28, no. 1 (October 25, 2015): 21–27. http://dx.doi.org/10.14445/22312803/ijctt-v28p106.

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Zhou, Yinglian, and Jifeng Chen. "Time Series Geographic Social Network Dynamic Preference Group Query." International Journal of Information Systems in the Service Sector 13, no. 4 (October 2021): 18–39. http://dx.doi.org/10.4018/ijisss.2021100102.

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Driven by experience and social impact of the new life, user preferences continue to change over time. In order to make up for the shortcomings of existing geographic social network models that often cannot obtain user dynamic preferences, a time-series geographic social network model was constructed to detect user dynamic preferences, a dynamic preference value model was built for user dynamic preference evaluation, and a dynamic preferences group query (DPG) was proposed in this paper . In order to optimize the efficiency of the DPG query algorithm, the UTC-tree index user timing check-in record is designed. UTC-tree avoids traversing all user check-in records in the query, accelerating user dynamic preference evaluation. Finally, the DPG query algorithm is used to implement a well-interacted DPG query system. Through a large number of comparative experiments, the validity of UTC-tree and the scalability of DPG query are verified.
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Liu, Jia, Wei Chen, Ziyang Chen, Lin Liu, Yuhong Wu, Kaiyu Liu, Amar Jain, and Yasser H. Elawady. "Optimized Query Algorithms for Top- K Group Skyline." Wireless Communications and Mobile Computing 2022 (January 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/3404906.

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Skyline query is a typical multiobjective query and optimization problem, which aims to find out the information that all users may be interested in a multidimensional data set. Multiobjective optimization has been applied in many scientific fields, including engineering, economy, and logistics. It is necessary to make the optimal decision when two or more conflicting objectives are weighed. For example, maximize the service area without changing the number of express points, and in the existing business district distribution, find out the area or target point set whose target attribute is most in line with the user’s interest. Group Skyline is a further extension of the traditional definition of Skyline. It considers not only a single point but a group of points composed of multiple points. These point groups should not be dominated by other point groups. For example, in the previous example of business district selection, a single target point in line with the user’s interest is not the focus of the research, but the overall optimality of all points in the whole target area is the final result that the user wants. This paper focuses on how to efficiently solve top- k group Skyline query problem. Firstly, based on the characteristics that the low levels of Skyline dominate the high level points, a group Skyline ranking strategy and the corresponding SLGS algorithm on Skyline layer are proposed according to the number of Skyline layer and vertices in the layer. Secondly, a group Skyline ranking strategy based on vertex coverage is proposed, and corresponding VCGS algorithm and optimized algorithm VCGS+ are proposed. Finally, experiments verify the effectiveness of this method from two aspects: query response time and the quality of returned results.
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Yang, De-Nian, Yi-Ling Chen, Wang-Chien Lee, and Ming-Syan Chen. "On social-temporal group query with acquaintance constraint." Proceedings of the VLDB Endowment 4, no. 6 (March 2011): 397–408. http://dx.doi.org/10.14778/1978665.1978671.

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Liu, Yongshan, Xiang Gong, Dehan Kong, Tianbao Hao, and Xiaoqi Yan. "Research on Group Reverse Farthest Neighbour Query Algorithm." Journal of Physics: Conference Series 1624 (October 2020): 042011. http://dx.doi.org/10.1088/1742-6596/1624/4/042011.

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Dissertations / Theses on the topic "Group-query"

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Mahendiran, Aravindan. "Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/25430.

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Twitter has become a popular data source in the recent decade and garnered a significant amount of attention as a surrogate data source for many important forecasting problems. Strong correlations have been observed between Twitter indicators and real-world trends spanning elections, stock markets, book sales, and flu outbreaks. A key ingredient to all methods that use Twitter for forecasting is to agree on a domain-specific vocabulary to track the pertinent tweets, which is typically provided by subject matter experts (SMEs). The language used in Twitter drastically differs from other forms of online discourse, such as news articles and blogs. It constantly evolves over time as users adopt popular hashtags to express their opinions. Thus, the vocabulary used by forecasting algorithms needs to be dynamic in nature and should capture emerging trends over time. This thesis proposes a novel unsupervised learning algorithm that builds a dynamic vocabulary using Probabilistic Soft Logic (PSL), a framework for probabilistic reasoning over relational domains. Using eight presidential elections from Latin America, we show how our query expansion methodology improves the performance of traditional election forecasting algorithms. Through this approach we demonstrate how we can achieve close to a two-fold increase in the number of tweets retrieved for predictions and a 36.90% reduction in prediction error.
Master of Science
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Shen, Qiong Mao. "Group nearest neighbor queries /." View abstract or full-text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20SHEN.

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Dumas, Menjivar Marlon. "TEMPOS : une plate-forme pour le développement d'applications temporelles au dessus de SGBD à objets." Phd thesis, Université Joseph Fourier (Grenoble), 2000. http://tel.archives-ouvertes.fr/tel-00006741.

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Les données temporelles sont présentes dans de nombreuses applications utilisant des Systèmes de Gestion de Bases de Données (SGBD). Aussi, la plupart de ces systèmes offrent des types correspondant aux concepts de date et de durée, grâce auxquels il est possible de modéliser des associations temporelles simples, comme par exemple la date de naissance ou l'âge d'une personne. Toutefois, à quelques nuances près, aucun de ces systèmes n'offre des abstractions dédiées à la modélisation d'associations temporelles plus complexes, telles que l'historique du salaire d'un employé, ou la séquence d'annotations attachées à une vidéo. Dès lors, ces associations doivent être codées au travers de constructeurs de type tels que ''liste'' et ''n-uplet'', et la sémantique de ce codage doit être intégrée dans la logique des programmes applicatifs, accroissant par là leur complexité. Pour combler ces lacunes, des extensions dites ''temporelles'' de modèles et de langages pour Bases de Données ont été proposées. Cette thèse analyse et unifie les contributions de ces travaux, dans le but de les intégrer dans une extension temporelle du standard pour SGBD à objets de l'ODMG. Le résultat est une plate-forme logicielle baptisée TEMPOS, fondée sur trois modèles de sophistication croissante : un modèle du temps, un modèle d'historiques et un modèle d'objets et de propriétés temporels. Ce dernier fournit des fonctionnalités facilitant la transformation de bases de données conformes à l'ODMG en des bases de données temporelles. à partir de ces trois modèles, des extensions des langages de spécification de schéma et d'interrogation de l'ODMG sont définies. Enfin, un outil de visualisation basé sur un nouveau paradigme de navigation interactive au travers d'objets temporels est développé. L'ensemble des propositions sont formalisées, implantées au dessus d'un SGBD commercial, et validées par des études de cas.
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Stehura, Igor. "Návrh testů komunikace se skupinovým adresováním v IP." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235947.

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This masters thesis is about mutlicast. There are explained 2nd and 3th layers of the ISO/OSI model multicast addressing. Routers in a network use multicast routing protocols to optimally route multicast packet through the network, this is also in this project. These multicast protocols are DVMRP, protocol PIM in his two modes, PIM Sparse Mode and PIM Dense Mode. Protocol DVMRP uses protocol IGMP, which is described as well. At practical section of this masters thesis is presented connections, by which tests was executed.
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Chang, Yu-Tu, and 張玉圖. "An Efficient Skyline Query Algorithm for Path Group." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/j4qngb.

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碩士
逢甲大學
資訊工程學系
104
In recent years the skyline path query has been used very effectively in many business areas like logistics and transportation. A path group consists of a set of paths which cover all user interesting nodes. It’s useful for planning logistic routes or individual case visiting paths for social workers . Given a starting node s, a set of k interesting nodes and the cardinality of path group c, the skyline path group query retrieves a set of non-dominated path groups from a road network, where each edge has multi-dimension costs. Each path group includes all interesting nodes and meets the constraint of path group cardinality. Computing the skyline path group query is quite complex due to the extensive dominance test with path group tuples. This paper proposes an efficient approach for computing skyline path groups. The core of our method is pruning those path group sets that can’t become outstanding tuples while generating path groups. As shown in our experimental evaluation, we narrow down the search space and improve process time.
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Chen, Yi-Ling, and 陳怡伶. "Efficient Link Prediction and Group Query in Social Networks." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/01584524839096799042.

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博士
國立臺灣大學
電機工程學研究所
105
As the development and popularization of social networking websites, many recommendation systems tend to leverage the information in social networks to provide helpful suggestions for users, and a great deal of research studies on social network analysis are thereby motivated. Recently, the sizes of social networks have been increasing rapidly, and this growth results in a significant increase in the computational cost of the sophisticated recommendations. The huge size and complexity of social networks create a considerable burden for recommendation systems while processing the information from social networks to provide suggestions. Therefore, in this dissertation, we study three important recommendation problems in social networks and aim to improve their efficiency. First, we focus on the relationship between two users and study the link prediction problem in large-scale networks. During the link prediction, numerous feature values need to be calculated and then combined to make recommendations, and the computational cost grows quickly as the network size becomes larger. Some previous studies involving network processing attempt to lower the computational cost by reducing the network size via sparsification. However, sparsification might remove important information and hurt the prediction accuracy. To address this issue, we propose a framework called Diverse Ensemble of Drastic Sparsification (DEDS), which constructs ensemble classifiers with good accuracy while keeping the prediction time short. DEDS includes various sparsification methods that are designed to preserve different measures of a network. Therefore, DEDS can generate sparsified networks with significant structural differences and increase the diversity of the ensemble classifier, which is key to improving prediction performance. Second, we extend the scope from the relationship between two users to the relationship among a group of users, and study the social group query problem with its applications in activity planning. Considering social links among all users to recommend a mutually acquainted group of attendees for an activity is an NP-hard problem. In addition to finding a group of attendees familiar with each other, selecting an activity period available to all is also essential for activity planning. Therefore, we need to further consider the available time of users, which makes the problem even harder due to the complexity of social connectivity and the diversity of user schedules. In this dissertation, we propose the Social-Temporal Group Query (STGQ) to find suitable time and attendees with minimum total social distance. We design two algorithms, SGSelect and STGSelect, which include various effective pruning strategies to substantially reduce running time. Experimental results indicate that SGSelect and STGSelect are significantly more efficient than baseline approaches. We also conduct a user study to compare the proposed approach with manual activity coordination. The results show that our approach obtains higher quality solutions with less coordination effort, thereby increasing users'' willingness to organize activities. Finally, we study the consecutive group query problem to support a sequence of recommendations. When planning an activity, it is difficult for a user to specify all the conditions right at once to find the perfect group of attendees and time. Fortunately, with the aforementioned social-temporal group query, it is easy for the user to tune the parameters to find alternative recommendations. As users may iteratively adjust query parameters to fine tune the results, we further propose Consecutive Social Group Query (CSGQ) to support such needs. Envisaging that exploiting the intermediate solutions of previous queries may improve processing of the succeeding queries, we design a new tree structure, namely, Accumulative Search Tree, which caches the intermediate solutions of historical queries in a compact form for reuse. To facilitate efficient lookup, we further propose a new index structure, called Social Boundary, which effectively indexes the intermediate solutions required for processing each CSGQ with specified parameters. According to the experimental results, with the caching mechanisms, processing time of consecutive queries can be further reduced considerably.
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Huang, Chih-Chung, and 黃治中. "Group-by and Order-by Query Processing for XML data." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/06026324499597081893.

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碩士
國立臺灣海洋大學
資訊工程學系
97
In this thesis, we discuss the performance of processing Group-By queries over XML data. We consider the query with mutiple by expressions or nested structures, and can have Having and Rank constraints. We design two indexes. The first one is based on the value of elements with same tags, called Value-Index. The second one is called Master Entity Index. It is used to retrieve the data for each returned clause. We design a special structure called ABList, to facilitate the grouping process. We have performed a series of experiments to evaluate the performance of the proposed approach. We also contrast with a well-know system. The experimental results show that our system is more efficient when the query has less grouping clauses.
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wei, kat ming, and 闕銘威. "An Opinion Mining Approach Based on Localized Social Group and Query Expansion." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/07906177749304063162.

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碩士
逢甲大學
資訊工程學系
104
A great deal of research has attempted to find information from the increasing use of social networks. Research indicates that using social network to analyze event occurrence may be faster and have a wider range than government published information. Based on observations, we have designed a system that can easily switch between events and find out the most suitable data collection social group, keywordlist and classification feature combination. Different types of events keyword-lists will grow following event occurrence. Based on the experiment on event detention flooding, we conclude that our approach can detect the flooding precisely. For event detection, we hope to obtain more detailed information, including occurrence time, locations, degrees of disasters, among other factors, but most of the time we could not place them in a single post. With the system characteristics and results, we can compose the missing information, and allow the analysis results to have more flexible usage.
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Chen, Yanzhi. "Efficient and robust image ranking for object retrieval." Thesis, 2013. http://hdl.handle.net/2440/90334.

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This thesis focuses on efficient and effective object retrieval from an unlabelled collection of images. The goal of object retrieval is to, given a query image depicting an object, return the dataset images containing that same object, quickly and accurately. Due to its simplicity and efficiency, it is common to use a “Bag-of-Words” (BoW) model in which each image is represented as a weighted vector of quantised features, known as visual words. Although the BoW retrieval system is efficient, the extraction and quantisation of local image features introduces errors into the retrieval results. We build our retrieval system on the BoW model, proposing three kinds of method to improve the retrieval accuracy: i) refinement of BoW image representation; ii) refinement of image similarity; iii) retrieval result re-ranking. Firstly, a visual thesaurus structure is proposed to discover the spatial relatedness of visual words. Based on these, a spatial expansion method is able to enrich the original query with those spatially related visual words (enriched by a general thesaurus) and spatially related foreground words (enriched by an object-based thesaurus). Therefore, the BoW image representation is improved. The second contribution improves the standard image similarity used in the BoW retrieval system such that the similarity between query/dataset images is better described. We do this by a cross-word image matching scheme, such that matching features mapped to different visual words are able to contribute to the similarity score. Thirdly, we also aim at efficient result re-ranking methods to improve the initial retrieval results. We present two re-ranking methods in this thesis. A context based re-ranking method is based on the analysis of correlated subsets of image dataset, called “contexts”. Images that share contexts are weakly correlated to each other, and should therefore mutually influence each other’s ranking. The initial ranking scores are refined by this contextual information. We also present a ranking verification method that is able to extract a set of reliable query relevant images from the retrieved results and thus can be applied in a number of object retrieval applications. Note that neither method needs to recover low level feature information or prior knowledge from the dataset. Instead, they utilize ranking information during run time. We also revisit the definition of the object retrieval problem and propose a group-query method, in which the query is a collection of images depicting the same object instead of a single query image used in the traditional “query-by-example” methods.
Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2013
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Books on the topic "Group-query"

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Library of Congress. Copyright Office, ed. In answer to your query: Group registration of published photographs. [Washington, D.C: U.S. Copyright Office, 2004.

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Boudreau, Joseph F., and Eric S. Swanson. Templates, the standard C++ library, and modern C++. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0017.

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This chapter is devoted to programming techniques which rely on the C++ template mechanism. This mechanism, which is the basis of a computing style known as generic programming, allows whole families of functions and classes to be easily written. It is described early in the chapter. A host of extremely useful template functions and classes is universally available in the C++ standard library, including container classes (vector, list, set, and map) and algorithms used to sort, shuffle, and otherwise manipulate or query their contents. The chapter closes with an introduction to the newer constructs of modern C++: smart pointers, lambda functions, the auto keyword, range-based for loops, and more. An application to group theory is explored in the exercises.
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Book chapters on the topic "Group-query"

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Ahmad, Sabbir, Rafi Kamal, Mohammed Eunus Ali, Jianzhong Qi, Peter Scheuermann, and Egemen Tanin. "The Flexible Group Spatial Keyword Query." In Lecture Notes in Computer Science, 3–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68155-9_1.

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Cholvy, Laurence. "Flexible Query-Answering in a Group of Databases." In Flexible Query Answering Systems, 141–61. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6075-3_8.

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Wang, Yi, Fan Xia, and Aoying Zhou. "Group-Scope Query and Its Access Method." In Web Technologies and Applications, 552–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29253-8_49.

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Lukasiewicz, Thomas, Maria Vanina Martinez, Gerardo I. Simari, and Oana Tifrea-Marciuska. "Group Preferences for Query Answering in Datalog+/- Ontologies." In Lecture Notes in Computer Science, 360–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40381-1_28.

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Xu, Jin, Lan Yao, and Fuxiang Gao. "Group Signature Based Trace Hiding in Web Query." In Big Data Computing and Communications, 503–11. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22047-5_41.

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Yao, Kai, Jianjun Li, Guohui Li, and Changyin Luo. "Efficient Group Top-k Spatial Keyword Query Processing." In Web Technologies and Applications, 153–65. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45814-4_13.

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Damaschke, Peter, and Azam Sheikh Muhammad. "Randomized Group Testing Both Query-Optimal and Minimal Adaptive." In SOFSEM 2012: Theory and Practice of Computer Science, 214–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27660-6_18.

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Ekomie, Hermann B., Kai Yao, Jianjun Li, Guohui Li, and Yanhong Li. "Group Top-k Spatial Keyword Query Processing in Road Networks." In Lecture Notes in Computer Science, 395–408. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64468-4_30.

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Singhal, Mayank, and Suman Banerjee. "Envy-Free Trip Planning in Group Trip Planning Query Problem." In Lecture Notes in Networks and Systems, 212–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14314-4_21.

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Buchmann, Alejandro P., and Ming-Chuan Wu. "Supporting Group-By and Pipelining in Bitmap-Enabled Query Processors." In SOFSEM’99: Theory and Practice of Informatics, 249–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-47849-3_14.

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Conference papers on the topic "Group-query"

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Deng, Ke, Hu Xu, Shazia Sadiq, Yansheng Lu, Gabriel Pui Cheong Fung, and Heng Tao Shen. "Processing Group Nearest Group Query." In 2009 IEEE 25th International Conference on Data Engineering (ICDE). IEEE, 2009. http://dx.doi.org/10.1109/icde.2009.186.

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Xu, Hu, Yansheng Lu, and Zhicheng Li. "Continuous Group Nearest Group Query on Moving Objects." In 2010 Second International Workshop on Education Technology and Computer Science. IEEE, 2010. http://dx.doi.org/10.1109/etcs.2010.66.

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Li, Xiang, and Ling Feng. "Context-aware group top-k query." In 2012 Seventh International Conference on Digital Information Management (ICDIM). IEEE, 2012. http://dx.doi.org/10.1109/icdim.2012.6360135.

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Chen, Xiaoying, Chong Zhang, Yanli Hu, Bin Ge, and Weidong Xiao. "Temporal Social Network: Group Query Processing." In 2016 27th International Workshop on Database and Expert Systems Applications (DEXA). IEEE, 2016. http://dx.doi.org/10.1109/dexa.2016.047.

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Liu, Dan, and Wenjun Xie. "Spatial Range Query on Group P2P Networks." In 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing (NSWCTC). IEEE, 2009. http://dx.doi.org/10.1109/nswctc.2009.380.

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Ma, Hanchao, Sheng Guan, Christopher Toomey, and Yinghui Wu. "Diversified Subgraph Query Generation with Group Fairness." In WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3488560.3498525.

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Zhang, Haoran, Dongpu Sun, Fahu Ji, Mingqiu Xu, Shang Gao, and Yang Xu. "Group Visible Nearest Surrounder Query in Obstacle Space." In 2019 IEEE International Conference on Computer Science and Educational Informatization (CSEI). IEEE, 2019. http://dx.doi.org/10.1109/csei47661.2019.8939019.

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Chandrasekaran, Ramji, Harsh Nilesh Pathak, and Tae Yano. "Deep Neural Query Understanding System at Expedia Group." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378495.

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Luk, Ming-Hay, Man Lung Yiu, and Eric Lo. "Group-by skyline query processing in relational engines." In Proceeding of the 18th ACM conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1645953.1646138.

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Liu, Kai, Tianyi Wu, Cong Liu, and Guodong Guo. "Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/166.

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Recently, Transformers have shown promising performance in various vision tasks. To reduce the quadratic computation complexity caused by each query attending to all keys/values, various methods have constrained the range of attention within local regions, where each query only attends to keys/values within a hand-crafted window. However, these hand-crafted window partition mechanisms are data-agnostic and ignore their input content, so it is likely that one query maybe attend to irrelevant keys/values. To address this issue, we propose a Dynamic Group Attention (DG-Attention), which dynamically divides all queries into multiple groups and selects the most relevant keys/values for each group. Our DG-Attention can flexibly model more relevant dependencies without any spatial constraint that is used in hand-crafted window based attention. Built on the DG-Attention, we develop a general vision transformer backbone named Dynamic Group Transformer (DGT). Extensive experiments show that our models can outperform the state-of-the-art methods on multiple common vision tasks, including image classification, semantic segmentation, object detection, and instance segmentation.
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Reports on the topic "Group-query"

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Katzir, Nurit, James Giovannoni, Marla Binzel, Efraim Lewinsohn, Joseph Burger, and Arthur Schaffer. Genomic Approach to the Improvement of Fruit Quality in Melon (Cucumis melo) and Related Cucurbit Crops II: Functional Genomics. United States Department of Agriculture, January 2010. http://dx.doi.org/10.32747/2010.7592123.bard.

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Background: Genomics tools for enhancement of melon research, with an emphasis on fruit, were developed through a previous BARD project of the PIs (IS -333-02). These included the first public melon EST collection, a database to relay this information to the research community and a publicly available microarray. The current project (IS-3877- 06) aimed to apply these tools for identification of important genes for improvement of melon (Cucumis melo) fruit quality. Specifically, the research plans included expression analysis using the microarray and functional analyses of selected genes. The original project objectives, as they appeared in the approved project, were: Objective 1: Utilization of a public melon microarray developed under the existing project to characterize melon transcriptome activity during the ripening of normal melon fruit (cv. Galia) in order to provide a basis for both a general view of melon transcriptome activity during ripening and for comparison with existing transcriptome data of developing tomato and pepper fruit. Objective 2: Utilization of the same public melon microarray to characterize melon transcriptome activity in lines available in the collection of the Israeli group, focusing on sugar, organic acids and aroma metabolism, so as to identify potentially useful candidates for functional analysis and possible manipulation, through comparison with the general fruit development profile resulting from (1) above. Objective 3: Expansion of our existing melon EST database to include publicly available gene expression data and query tools, as the US group has done with tomato. Objective 4: Selection of 6-8 candidate genes for functional analysis and development of DNA constructs for repression or over-expression. Objective 5: Creation of transgenic melon lines, or transgenic heterologous systems (e.g. E. coli or tomato), to assess putative functions and potential as tools for molecular enhancement of melon fruit quality, using the candidate gene constructs from (4).
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2

Khan, Mahreen. Public Financial Management and Transitioning out of Aid. Institute of Development Studies, September 2022. http://dx.doi.org/10.19088/k4d.2022.145.

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This rapid review found an absence of literature focused specifically on measuring the impact of PFM and governance systems in countries that have transitioned from aid, by moving up the income ladder. However, there are a few academic publications and a limited number of studies by multilateral, such as the World Bank, that examine the role of PFM and governance systems in countries that are transitioning or have moved away from aid. However, the importance of public financial management (PFM) and governance systems in development is well established and seen as a pre-requisite for economic growth. To effectively transition from aid, most low-income countries (LICs) need to upgrade their PFM and governance systems to meet the different scale, resources, accountability mechanisms, and capacity-building requirements of a middle-income country (MIC). The absence of the above empirical evidence may be due to the complexity of measuring the impact of PFM reforms as the results are non-linear, difficult to isolate from other policies to establish causality, and manifest in a longer time frame. However, through comparative country studies, the consequences of deficient PFM and governance have been well documented. So impaired budgetary planning, implementation, and reporting, limited fiscal transparency, weak accountability mechanisms, resource leakage, and inefficient service delivery are well recognised as detrimental to economic growth and development. The literature on transitioning countries focuses predominantly on the impact of aid withdrawal on the social sector, where comparative qualitative data is easier to obtain and the effects are usually more immediate, visible, and may even extend to global health outcomes, such as in AIDS prevention programmes. Thus, tracking the progress of donor-assisted social sector programmes is relatively easier than for PFM and governance reforms. The literature is more abundant on the overall lessons of transitions from aid both for country governments and donors. The key lessons underscore the importance of PFM and governance systems and mechanisms to a successful transition up the income ladder: Planning for transition should be strategic, detailed and specifically geared to mitigate against risks, explicitly assessing the best mix of finance options to mitigate the impact of aid reduction/withdrawal on national budgets. The plan must be led by a working group or ministry and have timelines and milestones; Where PFM and governance is weak transition preparation should include strengthening PFM especially economic and fiscal legislation, administration, and implementation; Stakeholders such as donor partners (DPs) and NGOs should participate in the planning process with clear, open, and ongoing communication channels; Political and economic assessments in the planning and mid-term phases as well as long-term monitoring and evaluation should be instituted; Build financial, technical, and management capacity throughout the plan implementation This helpdesk report draws on academic, policy, and grey sources from the previous seven years rather than the usual K4D five-year window, to account for the two-year disruption of COVID-19. As cross-country studies on PFM and governance are scarce, a few older studies are also referenced to ensure a comprehensive response to the query. The report focuses on low-income countries transitioning from aid due to a change in status to lower-middle-income countries.
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