Thematische Bibliographien / Extreme user / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Extreme user“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

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Lee, Seoung Eun and 김승인. "Mobile Fitness Application’s User Experience Study - Analytic focus on Extreme users -." Journal of Digital Design 14, no. 3 (2014): 769–77. http://dx.doi.org/10.17280/jdd.2014.14.3.076.

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Basak, A., and S. T. Roy. "Visual Ergonomics for Colourblindness: Applying Universal Design Principles in Graphical User Interface to Provide Affordance to the Colourblind Users." Proceedings of the Design Society 2 (May 2022): 2055–66. http://dx.doi.org/10.1017/pds.2022.208.

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AbstractWith evolution of Graphical User Interface, the access to the computer interface was expanded to cater to the extreme user categories by providing accessibility features and making the computer interface more inclusive. One such extreme user category is colourblind, which has a special accessibility requirement from the GUI. This paper studies the iconography of the Microsoft Windows operating system interface with an objective to develop an inclusive icon design solution that is visually ergonomic for colourblind users to include them as a mainstream user category in a computer interface.

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Johansson, Stefan, Per-Olof Hedvall, Mia Larsdotter, Thomas P. Larsson, and Catharina Gustavsson. "Co-Designing with Extreme Users: A Framework for User Participation in Design Processes." Scandinavian Journal of Disability Research 25, no. 1 (2023): 418–30. http://dx.doi.org/10.16993/sjdr.952.

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Cheng, Zhi Gang, Jie Fan, Xiunian Jing, and Li Lu. "Sub-millikelvin station at Synergetic Extreme Condition User Facility." Chinese Physics B 27, no. 7 (2018): 070702. http://dx.doi.org/10.1088/1674-1056/27/7/070702.

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Gamage, Dilrukshi, Indika Perera, and Shantha Fernando. "Exploring MOOC User Behaviors Beyond Platforms." International Journal of Emerging Technologies in Learning (iJET) 15, no. 08 (2020): 161. http://dx.doi.org/10.3991/ijet.v15i08.12493.

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MOOC user behavior is generally studied using the data collected within platform interactions in the learning system or via outside social media platforms. It is important to understand the root causes of anomalies in MOOCs, such as the 80% attrition, less interactions within platforms and what causing the reflected behaviors beyond platforms. We study MOOC student behaviors outside the platform using ethnographic methods, mainly focusing on diary study and interviews. Two groups, 11 extreme users who have completed many MOOCs and 10 who never completed MOOC have been used to collect data. The log sheets data and interviews were analyzed using the Epistemic Network Analysis (ENA) method to explore if there is a significance between these 2 groups and other qualitative comparisons to explore behavioral patterns. Our results indicated 4 behavioral patterns with insights into a significant level of learner's habits between extreme and novice users’ behaviors leading to completion or dropping. This reflects the design gaps of MOOC platforms and based on the behavioral patterns, we provide recommendations to meet the learners' needs.

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Sim, Kok Swee, Desmond Teck Kiang Kho, Mohsen Esmaeilinia, Yang Lee, and Chung Sheng Ee. "Graphic User Interface for Extreme Level Eliminating Adaptive Histogram Equalization." Journal of Image and Graphics 4, no. 1 (2016): 42–45. http://dx.doi.org/10.18178/joig.4.1.42-45.

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Mantoro, Teddy, Akeem Olowolayemo, Sunday O. Olatunji, Media A. Ayu, and Abu Osman. "Extreme learning machine for user location prediction in mobile environment." International Journal of Pervasive Computing and Communications 7, no. 2 (2011): 162–80. http://dx.doi.org/10.1108/17427371111146446.

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Lwambuka, Ladislaus, and Primus V. Mtenga. "Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition." Advances in Civil Engineering 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/390359.

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This paper presents a practical approach for prioritization of bridge maintenance within a given bridge network. The maintenance prioritization is formulated as a multiobjective optimization problem where the simultaneous satisfaction of several conflicting objectives includes minimization of maintenance costs, maximization of bridge deck condition, and minimization of traffic disruption and associated user costs. The prevalence of user cost during maintenance period is twofold; the first case refers to the period of dry season where normally the traffic flow is diverted to alternative routes usually resurfaced to regain traffic access. The second prevalence refers to the absence of alternative routes which is often the case in the least developed countries; in this case the user cost referred to results from the waiting time while the traffic flow is put on hold awaiting accomplishment of the maintenance activity. This paper deals with the second scenario of traffic closure in the absence of alternative diversion routes which in essence results in extreme user cost. The paper shows that the multiobjective optimization approach remains valid for extreme cases of user costs in the absence of detour roads as often is the scenario in countries with extreme poor road infrastructure.

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Li, Yuancheng, Yaqi Cui, and Xiaolong Zhang. "User Power Behavior Similarity Clustering Based on Unsupervised Extreme Learning Machine Algorithm." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 5 (2020): 641–49. http://dx.doi.org/10.2174/2352096512666191004130655.

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Background: Advanced Metering Infrastructure (AMI) for the smart grid is growing rapidly which results in the exponential growth of data collected and transmitted in the device. By clustering this data, it can give the electricity company a better understanding of the personalized and differentiated needs of the user. Objective: The existing clustering algorithms for processing data generally have some problems, such as insufficient data utilization, high computational complexity and low accuracy of behavior recognition. Methods: In order to improve the clustering accuracy, this paper proposes a new clustering method based on the electrical behavior of the user. Starting with the analysis of user load characteristics, the user electricity data samples were constructed. The daily load characteristic curve was extracted through improved extreme learning machine clustering algorithm and effective index criteria. Moreover, clustering analysis was carried out for different users from industrial areas, commercial areas and residential areas. The improved extreme learning machine algorithm, also called Unsupervised Extreme Learning Machine (US-ELM), is an extension and improvement of the original Extreme Learning Machine (ELM), which realizes the unsupervised clustering task on the basis of the original ELM. Results: Four different data sets have been experimented and compared with other commonly used clustering algorithms by MATLAB programming. The experimental results show that the US-ELM algorithm has higher accuracy in processing power data. Conclusion: The unsupervised ELM algorithm can greatly reduce the time consumption and improve the effectiveness of clustering.

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Chua, Tat-Seng, Huanbo Luan, Maosong Sun, and Shiqiang Yang. "NExT: NUS-Tsinghua Center for Extreme Search of User-Generated Content." IEEE Multimedia 19, no. 3 (2012): 81–87. http://dx.doi.org/10.1109/mmul.2012.39.

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Qasaimeh, Malik, and Alain Abran. "Extending Extreme Programming User Stories to Meet ISO 9001 Formality Requirements." Journal of Software Engineering and Applications 04, no. 11 (2011): 626–38. http://dx.doi.org/10.4236/jsea.2011.411074.

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Park, Jun Hong. "A Study on User Experience and Perception of Vehicle Interior Space Focusing on the extreme user interview." Korea Institute of Design Research Society 5, no. 4 (2020): 382–93. http://dx.doi.org/10.46248/kidrs.2020.4.382.

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Røiseland, Asbjørn. "User Choice – Blessing or Curse?" Scandinavian Journal of Public Administration 20, no. 4 (2016): 27–51. http://dx.doi.org/10.58235/sjpa.v20i4.14914.

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Based in an analysis of elderly care and primary school, the article discusses and explores marketization and especially user choice as a type of democratic participation in Swedish and Norwegian local government. Empirical data include surveys among Swedish and Norwegian citizens and case studies in four municipalities. The analysis shows that having a choice regarding service delivery is considered a significant means of influencing policies among the citizens in the two countries. Comparing the two policy sectors leads to a conclusion that user choice is developing as a means of influence in both sectors, but most important in primary school, and more developed in Sweden compared to Norway. The case studies aim to explore and illustrate the reasoning about choice and democracy among local leaders. This analysis clearly illustrates how the conceptual relation between marketization and democracy varies to an almost extreme extent among local government leaders in Sweden and Norway.

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Wang Jun, 王君, 王丽萍 Wang Liping, 金春水 Jin Chunshui, 苗亮 Miao Liang, and 谢耀 Xie Yao. "Extreme Ultraviolet Lithography Objective Design Based on Grouping and Graphical User Interface." Acta Optica Sinica 35, no. 12 (2015): 1211001. http://dx.doi.org/10.3788/aos201535.1211001.

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Foley, Michael, and Nicholas Loveday. "Comparison of Single-Valued Forecasts in a User-Oriented Framework." Weather and Forecasting 35, no. 3 (2020): 1067–80. http://dx.doi.org/10.1175/waf-d-19-0248.1.

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Abstract We compare single-valued forecasts from a consensus of numerical weather prediction models to forecasts from a single model across a range of user decision thresholds and sensitivities, using the relative economic value framework, and present this comparison in a new graphical format. With the help of a simple linear error model, we obtain theoretical results and perform synthetic calculations to gain insights into how the results relate to the characteristics of the different forecast systems. We find that multimodel consensus forecasts are more beneficial for users interested in decisions near the climatological mean, due to their reduced spread of errors compared to the constituent models. Single model forecasts may present greater benefit for users sensitive to extreme events if the forecasts have smaller conditional biases than the consensus forecasts and hence better resolution of such events. The results support use of consensus averaging approaches for single-valued forecast services in typical conditions. However, it is hard to cater for all user sensitivities in more extreme conditions. This underscores the importance of providing probability-based services for unusual conditions.

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Azarby, Sahand, and Arthur Rice. "User Performance in Virtual Reality Environments: The Capability of Immersive Virtual Reality Systems in Enhancing User Spatial Awareness and Producing Consistent Design Results." Sustainability 14, no. 21 (2022): 14129. http://dx.doi.org/10.3390/su142114129.

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Spatial decision-making in different virtual environments may vary based on the levels of spatial awareness experienced within Virtual Reality (VR) systems. Features and characteristics of VR systems may act as facilitators or distractors of spatial awareness, which can result in extreme variations in user spatial decisions. This research explored the capability of an Immersive Virtual Reality Interactive Environment (IVRIE) and a desktop-based VR (DT system) in reducing extreme variations in spatial decisions and inconsistent design results. Users’ spatial decisions, performance, and design results in both systems were studied regarding the impact of these two systems’ features on users, including the sense of immersion, types of interaction, and usage of eye-level view in spatial designs. The design results produced in both systems were compared considering the types of enclosure, surface texture, scale, and spatial function. Descriptive and inferential statistical comparisons and testing using quantitative and qualitative data were applied to determine participants’ performance regarding the production of spatial outliers in each system. The results showed that IVRIE was more effective than the DT system fostering a consistency of space sizes and reducing outliers.

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Bhatia, Siddharth, Arjit Jain, and Bryan Hooi. "ExGAN: Adversarial Generation of Extreme Samples." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (2021): 6750–58. http://dx.doi.org/10.1609/aaai.v35i8.16834.

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Mitigating the risk arising from extreme events is a fundamental goal with many applications, such as the modelling of natural disasters, financial crashes, epidemics, and many others. To manage this risk, a vital step is to be able to understand or generate a wide range of extreme scenarios. Existing approaches based on Generative Adversarial Networks (GANs) excel at generating realistic samples, but seek to generate typical samples, rather than extreme samples. Hence, in this work, we propose ExGAN, a GAN-based approach to generate realistic and extreme samples. To model the extremes of the training distribution in a principled way, our work draws from Extreme Value Theory (EVT), a probabilistic approach for modelling the extreme tails of distributions. For practical utility, our framework allows the user to specify both the desired extremeness measure, as well as the desired extremeness probability they wish to sample at. Experiments on real US Precipitation data show that our method generates realistic samples, based on visual inspection and quantitative measures, in an efficient manner. Moreover, generating increasingly extreme examples using ExGAN can be done in constant time (with respect to the extremeness probability τ), as opposed to the O(1/τ) time required by the baseline approach.

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BILGRAM, VOLKER, ALEXANDER BREM, and KAI-INGO VOIGT. "USER-CENTRIC INNOVATIONS IN NEW PRODUCT DEVELOPMENT — SYSTEMATIC IDENTIFICATION OF LEAD USERS HARNESSING INTERACTIVE AND COLLABORATIVE ONLINE-TOOLS." International Journal of Innovation Management 12, no. 03 (2008): 419–58. http://dx.doi.org/10.1142/s1363919608002096.

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Corporate innovation management geared to long-term success calls for a strategy to grow innovations into a substantial competitive advantage. This, however, coincides with an enormous failure-rate at the market, especially in the field of breakthrough innovations. Hence, in recent times, companies are trying to alleviate the risk of lacking user-acceptance through opening their innovation processes to external actors, particularly customers. The method of integrating lead users is determined by the effective and systematic identification of leading-edge customers, which is considered to be a critical phase within this approach. With the arrival of Web 2.0 applications, there is a huge potential to improve these selection processes. Our research into online communities and weblogs scrutinised the search criteria in an online environment and revealed the following characteristics as crucial factors for the online identification of lead users: being ahead of a market trend, high expected benefits, user expertise and motivation, extreme user needs as well as opinion leadership and an online commitment.

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Gayathri Devi, B., and V. Pattabiraman. "Optimized Extreme Learning Clustering and Orthogonally Projected User Grouping for Online Social Networks." Optical Memory and Neural Networks 29, no. 1 (2020): 44–55. http://dx.doi.org/10.3103/s1060992x20010087.

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Raviselvam, Sujithra, Dongwook Hwang, Bradley Camburn, Karen Sng, Katja Hölttä-Otto, and Kristin L. Wood. "Extreme-user conditions to enhance design creativity and empathy- application using visual impairment." International Journal of Design Creativity and Innovation 10, no. 2 (2022): 75–100. http://dx.doi.org/10.1080/21650349.2021.2024093.

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Chakravarthy, D. Gowtham, and S. Kannimuthu. "Extreme Gradient Boost Classification Based Interesting User Patterns Discovery for Web Service Composition." Mobile Networks and Applications 24, no. 6 (2019): 1883–95. http://dx.doi.org/10.1007/s11036-019-01385-6.

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Semma, Andi Bahtiar, Muh Saerozi, Kusrini Kusrini, Abdul Syukur, and Achmad Maimun. "An Extreme Programming Approach to Streamlining Thesis Writing." International Journal on Advanced Science, Engineering and Information Technology 13, no. 6 (2023): 2308–13. http://dx.doi.org/10.18517/ijaseit.v13i6.18701.

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Thesis writing is a significant challenge for many university students, often leading to substantial stress, confusion, and distress. Despite numerous studies to reduce academic stress, a specific solution for thesis writing has yet to be identified. This study introduces Penamasy, a thesis writing management system designed to address this issue. Penamasy was developed using the Extreme Programming (XP) methodology, effectively addressing the rapidly changing demands of university students in an academic environment. The result was a user-friendly app delivered promptly and met the needs of students. The study consisted of three research cycles, including user requirements, release planning, and acceptance tests, followed by an extended user acceptance test with students and promoters from three universities. Results indicated a positive response, with 79.6% of respondents expecting a more systematic and fuller online thesis writing experience, enabling them to complete their theses promptly. In conclusion, Penamasy provides a solution for university students facing the stress and difficulties of thesis writing. By streamlining the process and offering a systematic approach, students can focus on their research with confidence in the control of their writing process. Nevertheless, this study can be used as a guide in resolving students' academic stress and many other pragmatic problems that occur, especially in an educational environment. Future studies should involve users choosing UI component libraries, performance evaluation, and possible workflows.

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Hersani, Rizal, Kurniawan Kurniawan, Saputra Langgang Pangestu, Mas Edi, and Nadiya Nur Wahyunita. "Perancangan Sistem Informasi Rekomendasi Buku Dengan Metode Extreme Programming." J-SISKO TECH (Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD) 5, no. 2 (2022): 293. http://dx.doi.org/10.53513/jsk.v5i2.5857.

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Pada project ini penulis memegang tanggung jawab menyelesaikan Project Share Ur Book dimana website tersebut terdapat terdapat menu Home Page, Detail Book Page, Favorite Book Page. Pembuatan website Front-End Web ini dibuat menggunakan HTML, CSS, JavaScript, dan Node.js, dan di desain menggunakan framework Bootstrap. Pengerjaannya dilakukan dengan menerapkan materi yang diajarkan oleh Dicoding seperti Mobile First Approach, PWA, dan lain-lain. Hasil dari pembuatan proyek ini adalah sebuah Front-End Web yang berfungsi untuk menampilkan list buku sebagai referensi bagi user. Misi dari project penulis supaya bisa bermanfaat untuk para literasi buku agar mereka mudah menemukan rekomendasi buku bacaan. website ini dapat memposting review buku user, mencari rekomendasi buku, membaca review buku dari user lain, dan memberikan tanggapan terhadap review user lain. Penelitian ini bertujuan untuk menciptakan sebuah aplikasi berbasis web dengan menggunakan metode Extreme Programming (XP) yang bermanfaat sebagai wadah dalam mencari rekomendasi buku dan juga referensi buku sebagai bahan bacaan.

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Wanti, Linda Perdana, Fadillah Fadillah, Ganjar Ndaru Ikhtiagung, and Ilham Aditya Pangestu. "Implementasi Extreme programming Pada Website Marketplace Lapak Petani Online." Infotekmesin 12, no. 1 (2021): 50–58. http://dx.doi.org/10.35970/infotekmesin.v12i1.427.

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The use of information technology to improve people’s welfare has been implemented in various lines of life, including selling agricultural products through the marketplace to expand marketing and increase sales figures. Marketplace built based on the website using extreme programming (XP) method. The selection of extreme programming for marketplace development is tailored to all user needs and system requirements because website development is done in a relatively short time and many changes occur during website development. The stages of the extreme programming method are carried out in several iterations to get feedback from the end-users who are used in the website improvement process so that at the end of the iteration process the website developed is in accordance with the needs of the end-user. The output generated from this research is the farmer’s stall marketplace website that is used to market agricultural products from the Cilacap Holtikultura Farmers Association (PHC).

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Bin saif, Nouf, Mashael Almohawes, and Nor Shahida Mohd Jamail. "The impact of user involvement in software development process." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 354. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp354-359.

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<p>In software development process, user can take part in any phase of the process, depending on what model is being applied. Lack of user involvement can result in a poorly designed solution, or even a solution that conflicts with user’s needs. This review paper presents the impact of user involvement in software development process. In this study, different software development processes will be reviewed, show where the user usually gets involved in different models such as: Structural (Waterfall, V-model) and incremental (Scrum-extreme programming XP). As each model differs from the other, each of them has a different perspective of where user should take part and where they should not. This can be an asset that helps project managers, and leaders to develop suitable strategies to follow in their projects.</p>

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Jung, Hyelan. "Preliminary Research for Korean Twitter User Analysis Focusing on Extreme Heavy User’s Twitter Log." Journal of the HCI Society of Korea 5, no. 1 (2010): 37. http://dx.doi.org/10.17210/jhsk.2010.05.5.1.37.

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Jia, Susan, and Banggang Wu. "User Generated Information on Mobile Channels With More Concise Reviews and More Extreme Ratings." IEEE Access 7 (2019): 83495–503. http://dx.doi.org/10.1109/access.2019.2924335.

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Choobineh, Moein, Andrew Speake, Maxwell Harris, Paulo Cesar Tabares-Velasco, and Salman Mohagheghi. "End-User-Aware Community Energy Management in a Distribution System Exposed to Extreme Temperatures." IEEE Transactions on Smart Grid 10, no. 4 (2019): 3753–64. http://dx.doi.org/10.1109/tsg.2018.2834572.

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Luo, Xiong, Changwei Jiang, Weiping Wang, Yang Xu, Jenq-Haur Wang, and Wenbing Zhao. "User behavior prediction in social networks using weighted extreme learning machine with distribution optimization." Future Generation Computer Systems 93 (April 2019): 1023–35. http://dx.doi.org/10.1016/j.future.2018.04.085.

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Lu, Chung-Cheng, and Hani S. Mahmassani. "Modeling User Responses to Pricing." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (2008): 124–35. http://dx.doi.org/10.3141/2085-14.

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In a previous contribution, the authors showed how to incorporate user heterogeneity in determining equilibrium route choices in a network in response to pricing. Presented here is a generalization of that framework to incorporate joint consideration of route and departure time as well as heterogeneity in a wider range of behavioral characteristics. A multicriterion simultaneous route and departure time user equilibrium (MSRDUE) model is presented, along with a simulation-based algorithm intended for practical network applications. The model explicitly considers heterogeneous users with different values of time (VOTs) and values of (early or late) schedule delay (VOESDs or VOLSDs) in their joint choice of departure times and paths characterized by a set of trip attributes that include travel time, out-of-pocket cost, and schedule delay cost. The problem is formulated as an infinite-dimensional variational inequality problem and solved by a column generation-based algorithmic framework that embeds (a) an extreme nondominated alternative-finding algorithm to obtain the VOT, VOESD, and VOLSD breakpoints that define multiple user classes and the associated least trip cost (joint departure time and path) alternative for each user class; (b) a traffic simulator to capture traffic flow dynamics and determine travel costs experienced; and (c) a path-swapping multiclass alternative flow-updating scheme to solve the restricted multiclass SRDUE problem defined by a subset of feasible alternatives. Application to an actual network illustrates the properties of the algorithm and underscores the importance of capturing user heterogeneity and temporal shifts in the appraisal of dynamic pricing schemes.

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Hussein, Abdirahman Abdikarim, and Didem Kıvanç Türeli. "Hybrid Beamforming for Multi User Massive MIMO Systems." Orclever Proceedings of Research and Development 2, no. 1 (2023): 50–58. http://dx.doi.org/10.56038/oprd.v2i1.246.

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The increasing demand in wireless communications for enhanced spectral efficiency (SE) and throughput makes massive multiple input multiple output (MIMO) a great choice for meeting those demands by using a vast set of antennas. Despite the advantages of massive MIMO, to implement such systems comes with a huge price tag and consumes a lot of power. Hybrid beamforming (HBF) architecture has drawn considerable attention in the past few years, by significantly decreasing the amount of employed radio frequency (RF) chains and combining high dimensional analog beamforming (ABF) using phase shifters (PS) together with low dimensional digital beamforming (DBF). However, because of the extreme energy consumption and hardware complexity, traditional precoding designs are difficult to implement. In this paper, two HBF techniques are proposed to address the above issue. (i) low complexity precoding known as phased zero forcing (PZF) precoding, which controls phase only in the RF domain (ii) singular value decomposition (SVD) based optimal unconstrained precoding, that can be implemented on inexpensive RF components.

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Irfan, Bahar, Michael Garcia Ortiz, Natalia Lyubova, and Tony Belpaeme. "Multi-modal Open World User Identification." ACM Transactions on Human-Robot Interaction 11, no. 1 (2022): 1–50. http://dx.doi.org/10.1145/3477963.

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User identification is an essential step in creating a personalised long-term interaction with robots. This requires learning the users continuously and incrementally, possibly starting from a state without any known user. In this article, we describe a multi-modal incremental Bayesian network with online learning, which is the first method that can be applied in such scenarios. Face recognition is used as the primary biometric, and it is combined with ancillary information, such as gender, age, height, and time of interaction to improve the recognition. The Multi-modal Long-term User Recognition Dataset is generated to simulate various human-robot interaction (HRI) scenarios and evaluate our approach in comparison to face recognition, soft biometrics, and a state-of-the-art open world recognition method (Extreme Value Machine). The results show that the proposed methods significantly outperform the baselines, with an increase in the identification rate up to 47.9% in open-set and closed-set scenarios, and a significant decrease in long-term recognition performance loss. The proposed models generalise well to new users, provide stability, improve over time, and decrease the bias of face recognition. The models were applied in HRI studies for user recognition, personalised rehabilitation, and customer-oriented service, which showed that they are suitable for long-term HRI in the real world.

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Anggreni, Ni Komang Ayu Sri, Nyoman Putra Putra Sastra, and Dewa Made Wiharta. "Literatur Review Perbandingan Metode Pengembangan Design thinking dengan Extreme Programming." Majalah Ilmiah Teknologi Elektro 22, no. 2 (2023): 171. http://dx.doi.org/10.24843/mite.2023.v22i02.p03.

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With the development of applications, both through the web and mobile, applications cannot be separated from human-computer interaction. The ease of using the application is the target of developers to attract users' interest. In this era of globalization, website applications and mobile platforms are the mostly used for public branding. Application are used to deliver message through visuals from the appearance of the application. This is inseparable from the User Interface and User Experience. In today pratice, UI/UX designers mostly favor attractive visuals over the essence and purpose of creating a website, creating deviaton at UI/UX theory, design element, and color. it is necessary to design a UI / UX in order to application is attractive and the purpose of making the application is in line with expectations. There are several approaches to application design, one of which is Design thinking and Extreme Programming. This research aims to compare the Design thinking approach with Extreme Programming where the test obtained based on a literature review concluded that Design thinking has advantages in approaching potential users while Extreme Programming is less focused on potential users.

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Dyer, Gilliss, Cindy Bolme, and Siegfried Glenzer. "Seventh User Workshop on High-Power Lasers at the Linac Coherent Light Source." Instruments 4, no. 2 (2020): 13. http://dx.doi.org/10.3390/instruments4020013.

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We report on a seventh annual workshop in a series focused on science realized by the combination of hard X-ray free electron lasers with high power optical lasers, hosted at the SLAC National Accelerator Laboratory in Menlo Park, CA. Members from the user community of the Matter in Extreme Conditions (MEC) endstation of the Linac Coherent Light Source (LCLS) and other scientists met with local scientists to discuss developments at LCLS and MEC and related facilities, including experimental results and future plans.

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Ferdiana, Ridi, Paulus Insap Santoso, Lukito Edi Nugroho, and Ahmad Ashari. "USER STORY SOFTWARE ESTIMATION:A SIMPLIFICATION OF SOFTWARE ESTIMATION MODEL WITH DISTRIBUTED EXTREME PROGRAMMING ESTIMATION TECHNIQUE." JUTI: Jurnal Ilmiah Teknologi Informasi 9, no. 1 (2011): 41. http://dx.doi.org/10.12962/j24068535.v9i1.a67.

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Shevnina, Elena, and Andrey Silaev. "The probabilistic hydrological MARCS<sup>HYDRO</sup> (the MARkov Chain System) model: its structure and core version 0.2." Geoscientific Model Development 12, no. 7 (2019): 2767–80. http://dx.doi.org/10.5194/gmd-12-2767-2019.

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Abstract. The question of the environmental risks of social and economic infrastructure has recently become apparent due to an increase in the number of extreme weather events. Extreme runoff events include floods and droughts. In water engineering, extreme runoff is described in terms of probability and uses methods of frequency analysis to evaluate an exceedance probability curve (EPC) for runoff. It is assumed that historical observations of runoff are representative of the future; however, trends in the observed time series show doubt in this assumption. The paper describes a probabilistic hydrological MARCSHYDRO (the MARkov Chain System) model that can be applied to predict future runoff extremes. The MARCSHYDRO model simulates statistical estimators of multi-year runoff in order to perform future projections in a probabilistic form. Projected statistics of the meteorological variables available in climate scenarios force the model. This study introduces the new model's core version and provides a user guide together with an example of the model set-up in a single case study. In this case study, the model simulates the projected EPCs of annual runoff under three climate scenarios. The scope of applicability and limitations of the model's core version 0.2 are discussed.

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Bahrudin, Ida Aryanie, Mohd Ezree Abdullah, Rafizah Mohd Hanifa, Noordiana Kassim, and Rosfuzah Roslan. "Challenges of Gathering User Requirement in eXtreme Programming Project: A Case Study of Highway Construction Monitoring System." Key Engineering Materials 594-595 (December 2013): 511–15. http://dx.doi.org/10.4028/www.scientific.net/kem.594-595.511.

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The successfulness of a software development project is not only based on the tools and the technology used but also really depends on how the developed software meets the end user requirements. Involving end user as an active member of software development team, one of the popular agile methods known as eXtreme Programming (XP) had been selected as the software development methodology. This paper is focused on one of the main practices called on-site customer. The project under study is a web based Highway Construction Monitoring System (HIGHCONS). Challenges related to its implementation throughout the development process and also the suitable solutions in facing the challenges were also considered.

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Felberg, Tatjana, and Ljiljana Šarić. "Chocolate, identity, and extreme speech online." FLEKS - Scandinavian Journal of Intercultural Theory and Practice 7, no. 1 (2021): 15–25. http://dx.doi.org/10.7577/fleks.4168.

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In this article the phrase “extreme speech” is used to encompass both hate speech and impoliteness. Legislation against hate speech has been passed in many countries, while work on defining phenomena related to hate speech is still ongoing. As a rule, there is no legislation prohibiting impoliteness, and thus impoliteness is often perceived as a less serious verbal offence. There is, however, a grey zone between the two phenomena, which depends on contextual factors that must be constantly explored. In this article, we explore the gray zone between hate speech and impoliteness by looking at user-generated posts commenting on seemingly uncontroversial topics such as giving chocolate to children. The context we explore is the political relationship between Croatia and Serbia, two neighboring countries in the southwest Balkans with a history of recent military conflicts that ended in 1995. The relationship between these two countries can still be described as periodically troubled. The comments we analyze were posted on two online newspapers, the Croatian Jutarnji list and the Serbian Večernje novosti. Using impoliteness theory and Critical Discourse Analysis framework we identify and analyze various linguistic means that serve as extreme speech triggers, connect them to relevant contexts and highlight the grey zone that exist between hate speech and impoliteness. Our findings show that, in their discussions, the posters used a number of linguistic means for constructing national identities that at times resulted in extreme speech. The posters often targeted individual co-posters first and very quickly moved on to target ethnic groups, thus fluctuating between impoliteness and hate speech.

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Mahdani, Resty, Tinika Yaumi, Yuda Syahidin, and Yuyun Yunengsih. "TATA KELOLA REKAM MEDIS BERBASIS ELEKTRONIK DALAM PEMBUATAN LAPORAN POLIKLINIK PASIEN RAWAT JALAN MENGGUNAKAN METODE AGILE." Jurnal Indonesia : Manajemen Informatika dan Komunikasi 4, no. 3 (2023): 1050–60. http://dx.doi.org/10.35870/jimik.v4i3.315.

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This study aims to determine the governance of electronic-based medical records in making outpatient polyclinic reports using the agile method. The research method used is qualitative research with a descriptive approach. After analyzing the needs of the polyclinic reporting system, this study presents the steps of implementing the agile method of extreme programming. By using this method, a system that is adaptable, responsive, and focused on user needs can be developed. The results show that the use of the agile extreme programming method in the development of an electronic-based medical record system provides significant benefits. The process of planning, designing, coding, testing, and releasing is done iteratively and collaboratively. With this approach, the system can be continuously improved and adjusted to meet changing user needs and priorities. By describing the system design flowmap, context diagram, DFD and ERD to visualize the relationship between the components in the system that provides a systematic description of the stages of the report generation process. In conclusion, electronic-based medical record governance in making outpatient polyclinic reports using the agile extreme programming method is an effective and efficient approach. By combining the advantages of agile and extreme programming methods, an adaptive and responsive system can be developed.

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Wang, Wenle, Wentao Xiong, Jing Wang, et al. "A User Purchase Behavior Prediction Method Based on XGBoost." Electronics 12, no. 9 (2023): 2047. http://dx.doi.org/10.3390/electronics12092047.

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With the increasing use of electronic commerce, online purchasing users have been rapidly rising. Predicting user behavior has therefore become a vital issue based on the collected data. However, traditional machine learning algorithms for prediction require significant computing time and often produce unsatisfactory results. In this paper, a prediction model based on XGBoost is proposed to predict user purchase behavior. Firstly, a user value model (LDTD) utilizing multi-feature fusion is proposed to differentiate between user types based on the available user account data. The multi-feature behavior fusion is carried out to generate the user tag feature according to user behavior patterns. Next, the XGBoost feature importance model is employed to analyze multi-dimensional features and identify the model with the most significant weight value as the key feature for constructing the model. This feature, together with other user features, is then used for prediction via the XGBoost model. Compared to existing machine learning models such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Back Propagation Neural Network (BPNN), the eXtreme Gradient Boosting (XGBoost) model outperforms with an accuracy of 0.9761, an F1 score of 0.9763, and a ROC value of 0.9768. Thus, the XGBoost model demonstrates superior stability and algorithm efficiency, making it an ideal choice for predicting user purchase behavior with high levels of accuracy.

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Arnbjerg-Nielsen, K., P. Harremoës, and P. S. Mikkelsen. "Dissemination of regional rainfall analysis in design and analysis of urban drainage at un-gauged locations." Water Science and Technology 45, no. 2 (2002): 69–74. http://dx.doi.org/10.2166/wst.2002.0029.

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A research program in Denmark on statistical modelling of rainfall has resulted in a model for regional distribution of rainfall extremes. The results show that extreme rainfalls critical to the hydraulic function of urban drainage systems and the pollution discharge are subject to a significant regional variation of extreme rainfalls throughout the country. This has implications for design and analysis of all practical problems related to urban drainage, since the rainfall data so far recommended as input to engineering analyses underestimates the problems. Consequently, the Danish Water Pollution Control Committee has issued a statement recommending a new engineering practice. The dissemination of the research results proved to be difficult due to lack of understanding of the concepts of the new paradigm by practitioners. The traditional means of communication was supplemented by user-friendly spreadsheets and easy access to rainfall data as well as giving courses on the new paradigm. This has eased the implementation of the new concepts greatly.

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Ridho, Muhammad Rosyid, Nur Fajri Azhar, and Tegar Palyus Fiqar. "Pengembangan Sistem Informasi Manajemen Bahan Baku Makanan dan Penggajian Karyawan Berbasis Website Menggunakan Metode Extreme Programming." SPECTA Journal of Technology 6, no. 3 (2023): 316–28. http://dx.doi.org/10.35718/specta.v6i3.758.

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Toko Kanas Kitchen merupakan salah satu toko yang bergerak pada bidang makanan dan minuman yang berlokasi pada kota Balikpapan. Saat ini semua proses pendataan bahan baku dan penggajian karyawan masih dicatat manual yang mengakibatkan keterlambatan dalam pencatatan. Oleh karena itu, pada penelitian ini mengusulkan Pengembangan Sistem Informasi Manajemen Bahan Baku Makanan dan Penggajian Karyawan Berbasis Website. Pengembangan sistem informasi manajemen bahan baku dan penggajian karyawan menggunakan framework Laravel dan basis data MySQL, dan menerapkan metode Extreme Programming. Adapun tahapan dalam Extreme Programming mulai dari perencanaan, perancangan, pengkodean, dan pengujian. Terdapat beberapa fitur pada penelitian ini yaitu, fitur bahan baku, fitur kehadiran karyawan, dan fitur penggajian karyawan. Dalam pelaksanaan perancangan sistem informasi manajemen bahan baku dan penggajian karyawan didapatkan user stories dari hasil wawancara kebutuhan sistem yang berjumlah 35 user stories, lalu dilanjutkan dalam membuat perancangan desain database dan use case diagram. Dalam penyelesaian pengembangan website sistem informasi manajemen bahan baku dan penggajian karyawan dengan jumlah 35 user stories dan diimplementasikan sebanyak 5 iterasi. Metode extreme programming dapat diimplementasikan pada penelitian pengembangan sistem manajemen bahan baku dan penggajian karyawan. Hasil dari penelitian aplikasi Sistem Informasi Manajemen Bahan Baku Makanan dan Penggajian Karyawan dibuktikan dengan hasil dari pengujian dengan metode unit testing dan dapat dijalankan sesuai dengan memenuhi user acceptance test.

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Mahoney, Kelly, Chesley McColl, Douglas M. Hultstrand, William D. Kappel, Bill McCormick, and Gilbert P. Compo. "Blasts from the Past: Reimagining Historical Storms with Model Simulations to Modernize Dam Safety and Flood Risk Assessment." Bulletin of the American Meteorological Society 103, no. 2 (2022): E266—E280. http://dx.doi.org/10.1175/bams-d-21-0133.1.

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Abstract Accurate estimation of the potential “upper limit” for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical upper limit of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk. This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits that were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today.

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Dewi, Ika Parma, Rizkayeni Marta, Daniel Rinaldi, Afif Rahman Riyanda, and Yose Indarta. "Penerapan Extreme Programming Dalam Perancangan Sistem Informasi Praktik Industri Berbasis Website." Journal of Information System Research (JOSH) 4, no. 1 (2022): 277–84. http://dx.doi.org/10.47065/josh.v4i1.2328.

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The development of information technology makes all activities that used to run offline become online. The purpose of this study is to (1) Design and build a website-based Industrial Practice information system in the Information Technology Education Study Program, (2) Help students to find out information before or after Industrial Practice, (3) Assist admins in providing information, and lecturers in terms of assessment and guidance in the implementation of Industrial Practices. The development of this research uses the Extreme Programming method which has several stages, namely Requirements, Planning, Design, Coding, and Testing. The tests used in this study were internal testing, external testing and user acceptance test (UAT) testing. Internal testing uses browser testing and functionality testing, external testing uses blackbox testing and user acceptance test (UAT) testing uses iteration testing with the aim of testing the functionality of the menus in the application that are running well. The results of this study conclude that a website has been successfully built that can help study programs, both lecturers and students by 75%, (2) Assist study programs in managing student data in terms of registration of Industrial Practices and assessment of Industrial Practices, (3) The system can provide information related to the place of practice, practice scores, guidance information, and the overall average score of students who have done industrial practice.

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Muh. Fahmi Rustan, Hasriani, and Nuralamsah Zulkarnaim. "VISUALISASI DATA AKREDITASI PROGRAM STUDI BERBASIS WEB MENGGUNAKAN EXTREME PROGRAMMING." Jurnal Informatika Teknologi dan Sains 4, no. 4 (2022): 413–20. http://dx.doi.org/10.51401/jinteks.v4i4.2143.

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Status akreditasi suatu program studi ditentukan oleh banyak data yang dapat menunjang kriteria penilaian. Ketersediaan data tentu mendukung banyaknya informasi yang dapat diperoleh sehingga akan menjadi lebih mudah jika data dikumpulkan dalam satu sistem akreditasi. Namun tidak mudah untuk memahami informasi atau masalah yang terjadi dari data yang tidak terstruktur.Untuk itu, dibutuhkan suatu penyajian informasi yang singkat dan menarik pada pada sistem akreditasi. Hal ini dapat diwujudkan melalui visualisasi data yang dengannya suatu informasi dapat diperoleh dengan mengekspolarasi data, memahami data, dan mengkomunikasikan data. Penelitian ini bertujuan mengembangkan sistem akreditasi program studi yang berfokus pada kriteria pendidikan yang dilengkapi dengan visualisasi data yang dapat membantu dalam analisis data sehingga user atau pengambil kebijakan mampu mengambil keputusan dengan tepat. Dengan memanfaatkan metode Extreme Programming(XP), penelitian ini menghasilkan sistem akreditasi program studi yang dilengkapi dengan visualisasi data yang mampu menyajikan tampilan data yang efektif dan menarik. Hasil ini juga dapat mempermudah user dalam mengambil keputusan terkait upaya pencapaian akreditasi program studi.

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Borowiec, Marcin, and Tomasz Rak. "Advanced Examination of User Behavior Recognition via Log Dataset Analysis of Web Applications Using Data Mining Techniques." Electronics 12, no. 21 (2023): 4408. http://dx.doi.org/10.3390/electronics12214408.

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As web systems based on containerization increasingly attract research interest, the need for effective analytical methods has heightened, with an emphasis on efficiency and cost reduction. Web client simulation tools have been utilized to further this aim. While applying machine learning (ML) methods for anomaly detection in requests is prevalent, predicting patterns in web datasets is still a complex task. Prior approaches incorporating elements such as URLs, content from web pages, and auxiliary features have not provided any satisfying results. Moreover, such methods have not significantly improved the understanding of client behavior and the variety of request types. To overcome these shortcomings, this study introduces an incremental approach to request categorization. This research involves an in-depth examination of various established classification techniques, assessing their performance on a selected dataset to determine the most effective model for classification tasks. The utilized dataset comprises 8 million distinct records, each defined by performance metrics. Upon conducting meticulous training and testing of multiple algorithms from the CART family, Extreme Gradient Boosting was deemed to be the best-performing model for classification tasks. This model outperforms prediction accuracy, even for unrecognized requests, reaching a remarkable accuracy of 97% across diverse datasets. These results underline the exceptional performance of Extreme Gradient Boosting against other ML techniques, providing substantial insights for efficient request categorization in web-based systems.

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Jiang, Xuhao, Weimin Tan, Tian Tan, Bo Yan, and Liquan Shen. "Multi-Modality Deep Network for Extreme Learned Image Compression." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (2023): 1033–41. http://dx.doi.org/10.1609/aaai.v37i1.25184.

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Image-based single-modality compression learning approaches have demonstrated exceptionally powerful encoding and decoding capabilities in the past few years , but suffer from blur and severe semantics loss at extremely low bitrates. To address this issue, we propose a multimodal machine learning method for text-guided image compression, in which the semantic information of text is used as prior information to guide image compression for better compression performance. We fully study the role of text description in different components of the codec, and demonstrate its effectiveness. In addition, we adopt the image-text attention module and image-request complement module to better fuse image and text features, and propose an improved multimodal semantic-consistent loss to produce semantically complete reconstructions. Extensive experiments, including a user study, prove that our method can obtain visually pleasing results at extremely low bitrates, and achieves a comparable or even better performance than state-of-the-art methods, even though these methods are at 2x to 4x bitrates of ours.

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Lin, Xialing, Kenneth A. Lachlan, and Patric R. Spence. "Exploring extreme events on social media: A comparison of user reposting/retweeting behaviors on Twitter and Weibo." Computers in Human Behavior 65 (December 2016): 576–81. http://dx.doi.org/10.1016/j.chb.2016.04.032.

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Shao, Zhifei, Meng Joo Er, and Ning Wang. "An Efficient Leave-One-Out Cross-Validation-Based Extreme Learning Machine (ELOO-ELM) With Minimal User Intervention." IEEE Transactions on Cybernetics 46, no. 8 (2016): 1939–51. http://dx.doi.org/10.1109/tcyb.2015.2458177.

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