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Full-Text Articles in Entire DC Network
Efficient 3d Dental Identification Via Signed Feature Histogram And Learning Keypoint Detection, Zhiyuan Zhang, Sim Heng Ong, Xin Zhong, Kelvin W. C. Foong
Efficient 3d Dental Identification Via Signed Feature Histogram And Learning Keypoint Detection, Zhiyuan Zhang, Sim Heng Ong, Xin Zhong, Kelvin W. C. Foong
Research Collection School Of Computing and Information Systems
Current methods of dental identification are mainly based on 2D dental radiographs which suffer from speed and accuracy limitations. In this paper, we present an efficient dental identification approach based on 3D dental models. We propose a novel shape descriptor, the Signed Feature Histogram (SFH), which is highly discriminative and can be easily computed to describe the local surface. Based on the SFH, a learning keypoint detection method is adopted to accurately detect the desired keypoints on both antemortem (AM) and postmortem (PM) models. For a given PM model, the optimal initial alignment to the AM model to be matched …
Context-Aware Advertisement Recommendation For High-Speed Social News Feeding, Yuchen Li, Dongxiang Zhang, Ziquan Lan, Kian-Lee Tan
Context-Aware Advertisement Recommendation For High-Speed Social News Feeding, Yuchen Li, Dongxiang Zhang, Ziquan Lan, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Social media advertising is a multi-billion dollar market and has become the major revenue source for Facebook and Twitter. To deliver ads to potentially interested users, these social network platforms learn a prediction model for each user based on their personal interests. However, as user interests often evolve slowly, the user may end up receiving repetitive ads. In this paper, we propose a context-aware advertising framework that takes into account the relatively static personal interests as well as the dynamic news feed from friends to drive growth in the ad click-through rate. To meet the real-time requirement, we first propose …
Modeling Autobiographical Memory In Human-Like Autonomous Agents, Di Wang, Ah-Hwee Tan, Chunyan Miao
Modeling Autobiographical Memory In Human-Like Autonomous Agents, Di Wang, Ah-Hwee Tan, Chunyan Miao
Research Collection School Of Computing and Information Systems
Although autobiographical memory is an important part of the human mind, there has been little effort on modeling autobiographical memory in autonomous agents. With the motivation of developing human-like intelligence, in this paper, we delineate our approach to enable an agent to maintain memories of its own and to wander in mind. Our model, named Autobiographical Memory-Adaptive Resonance Theory network (AM-ART), is designed to capture autobiographical memories, comprising pictorial snapshots of one’s life experiences together with the associated context, namely time, location, people, activity, and emotion. In terms of both network structure and dynamics, AM-ART coincides with the autobiographical memory …
#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber
#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber
Research Collection School Of Computing and Information Systems
Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
Research Collection School Of Computing and Information Systems
Software ecosystems as a paradigm for large-scale software development encompass a complex mix of technical, business, and social aspects. While significant research has been conducted to understand both the technical and business aspects, the social aspects of software ecosystems are less well understood. To close this gap, this paper presents the results of an empirical study aimed at understanding the influence of social aspects on developers’ participation in software ecosystems. We conducted 25 interviews with mobile software developers and an online survey with 83 respondents from the mobile software development community. Our results point out a complex social system based …
Overcoming Open Source Project Entry Barriers With A Portal For Newcomers, Igor Steinmacher, Tayana U. Conte, Christoph Treude, Marco Aurélio Gerosa
Overcoming Open Source Project Entry Barriers With A Portal For Newcomers, Igor Steinmacher, Tayana U. Conte, Christoph Treude, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Community-based Open Source Software (OSS) projects are usually self-organized and dynamic, receiving contributions from distributed volunteers. Newcomer are important to the survival, long-term success, and continuity of these communities. However, newcomers face many barriers when making their first contribution to an OSS project, leading in many cases to dropouts. Therefore, a major challenge for OSS projects is to provide ways to support newcomers during their first contribution. In this paper, we propose and evaluate FLOSScoach, a portal created to support newcomers to OSS projects. FLOSScoach was designed based on a conceptual model of barriers created in our previous work. To …
Augmenting Api Documentation With Insights From Stack Overflow, Christoph Treude, Martin P. Robillard
Augmenting Api Documentation With Insights From Stack Overflow, Christoph Treude, Martin P. Robillard
Research Collection School Of Computing and Information Systems
Software developers need access to different kinds of information which is often dispersed among different documentation sources, such as API documentation or Stack Overflow. We present an approach to automatically augment API documentation with “insight sentences” from Stack Overflow— sentences that are related to a particular API type and that provide insight not contained in the API documentation of that type. Based on a development set of 1,574 sentences, we compare the performance of two state-of-the-art summarization techniques as well as a pattern-based approach for insight sentence extraction. We then present SISE, a novel machine learning based approach that uses …
Are You Charlie Or Ahmed? Cultural Pluralism In Charlie Hebdo Response On Twitter, Jisun An, Haewoon Kwak, Yelena Mejova, Sonia Alonso Saenz De Oger, Braulio Gomez Fortes
Are You Charlie Or Ahmed? Cultural Pluralism In Charlie Hebdo Response On Twitter, Jisun An, Haewoon Kwak, Yelena Mejova, Sonia Alonso Saenz De Oger, Braulio Gomez Fortes
Research Collection School Of Computing and Information Systems
We study the response to the Charlie Hebdo shootings of January 7, 2015 on Twitter across the globe. We ask whether the stances on the issue of freedom of speech can be modeled using established sociological theories, including Huntington’s culturalist Clash of Civilizations, and those taking into consideration social context, including Density and Interdependence theories. We find support for Huntington’s culturalist explanation, in that the established traditions and norms of one’s “civilization” predetermine some of one’s opinion. However, at an individual level, we also find social context to play a significant role, with non-Arabs living in Arab countries using #JeSuisAhmed …
Modeling Human-Like Non-Rationality For Social Agents, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann
Modeling Human-Like Non-Rationality For Social Agents, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann
Research Collection School Of Computing and Information Systems
Humans are not rational beings. Deviations from rationality in human thinking are currently well documented [25] as non-reducible to rational pursuit of egoistic benefit or its occasional distortion with temporary emotional excitation, as it is often assumed. This occurs not only outside conceptual reasoning or rational goal realization but also subconsciously and often in certainty that they did not and could not take place ‘in my case’. Non-rationality can no longer be perceived as a rare affective abnormality in otherwise rational thinking, but as a systemic, permanent quality, ’a design feature’ of human cognition. While social psychology has systematically addressed …
An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan
An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Activities of Daily Living (ADLs) refer to activities performed by individuals on a daily basis. As ADLs are indicatives of a person’s habits, lifestyle, and well being, learning the knowledge of people’s ADL routine has great values in the healthcare and consumer domains. In this paper, we propose an autonomous agent, named Agent for Spatia-Temporal Activity Pattern Modeling (ASTAPM), being able to learn spatial and temporal patterns of human ADLs. ASTAPM utilises a self-organizing neural network model named Spatiotemporal - Adaptive Resonance Theory (ST-ART). ST-ART is capable of integrating multimodal contextual information, involving the time and space, wherein the ADL …
A Graph-Based Semantics Workbench For Concurrent Asynchronous Programs, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt
A Graph-Based Semantics Workbench For Concurrent Asynchronous Programs, Claudio Corrodi, Alexander Heußner, Christopher M. Poskitt
Research Collection School Of Computing and Information Systems
A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by Scoop—a concurrent object-oriented message-passing language—which has seen multiple semantics proposed and implemented over its evolution. We propose a “semantics workbench” with fully and semi-automatic tools for Scoop, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a …
Semantic Visualization With Neighborhood Graph Regularization, Tuan Minh Van Le, Hady W. Lauw
Semantic Visualization With Neighborhood Graph Regularization, Tuan Minh Van Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Visualization of high-dimensional data, such as text documents, is useful to map out the similarities among various data points. In the high-dimensional space, documents are commonly represented as bags of words, with dimensionality equal to the vocabulary size. Classical approaches to document visualization directly reduce this into visualizable two or three dimensions. Recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. While aiming for a good fit between the model parameters and the observed data, previous approaches have not considered the local consistency among data instances. We …
What Makes A Music Track Popular In Online Social Networks?, Jing Ren, Jialie Shen, Robert John Kauffman
What Makes A Music Track Popular In Online Social Networks?, Jing Ren, Jialie Shen, Robert John Kauffman
Research Collection School Of Computing and Information Systems
Tens of thousands of music tracks are uploaded to the Internet every day through social networks that focus on music and videos, as well as portal websites. While some of the content has been popular for decades, some tracks that have just been released have been completely ignored. So what makes a music track popular? Can we predict the popularity of a music track before it is released? In this research, we will focus on an online music social network, Last.fm, and investigate three key factors of a music track that may have impact on its popularity. They include: the …
Mapping Information Systems Student Skills To Industry Skills Framework, Shankararaman, Venky, Gottipati Swapna
Mapping Information Systems Student Skills To Industry Skills Framework, Shankararaman, Venky, Gottipati Swapna
Research Collection School Of Computing and Information Systems
SFIA skills framework is widely popular among education institutions and ICT industries. The framework provides ICT skills profiles which can be a valuable resource that supports the career planning of a student. However, currently a student does not have a method or approach to exploit the SFIA framework to align his or her competencies that he or she has acquired during the education program, to the skills defined in the SFIA framework. In this paper, we present a solution model for generating a skills report based on individual's competencies and experiences. In particular, we focus on Information Systems students' profiles. …
Not You Too? Distilling Local Contexts Of Poor Cellular Network Performance Through Participatory Sensing, Huiguang Liang, Ido Nevat, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Not You Too? Distilling Local Contexts Of Poor Cellular Network Performance Through Participatory Sensing, Huiguang Liang, Ido Nevat, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Research Collection School Of Computing and Information Systems
Cellular service subscribers are increasingly reliant on cellular data services for all kinds of mobile applications. Oftentimes, when subscribers experience frustratingly high network delays and timeouts, they like to know whether their experiences are shared by other users nearby. The question that is often asked is essentially this: “is it just me, or do others around me face the same problem?” In this paper, we describe how we use Tattle, a distributed real-time participatory sensing and monitoring framework, to glean network performance information from users nearby. Tattle relies on recent advances in peer-to-peer device networking, such as Wi-Fi Direct, Bluetooth …
Olps: A Toolbox For On-Line Portfolio Selection, Bin Li, Doyen Sahoo, Hoi, Steven C. H.
Olps: A Toolbox For On-Line Portfolio Selection, Bin Li, Doyen Sahoo, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
On-line portfolio selection is a practical financial engineering problem, which aims to sequentially allocate capital among a set of assets in order to maximize long-term return. In recent years, a variety of machine learning algorithms have been proposed to address this challenging problem, but no comprehensive open-source toolbox has been released for various reasons. This article presents the first open-source toolbox for "On-Line Portfolio Selection" (OLPS), which implements a collection of classical and state-of-the-art strategies powered by machine learning algorithms. We hope that OLPS can facilitate the development of new learning methods and enable the performance benchmarking and comparisons of …
Persentiment: A Personalized Sentiment Classification System For Microblog Users, Kaisong Song, Ling Chen, Wei Gao, Shi Feng, Daling Wang, Chengqi Zhang
Persentiment: A Personalized Sentiment Classification System For Microblog Users, Kaisong Song, Ling Chen, Wei Gao, Shi Feng, Daling Wang, Chengqi Zhang
Research Collection School Of Computing and Information Systems
Microblogging services are playing increasingly important roles in our daily life today. It is useful for microblog users to instantly understand the sentiment of a large number of microblogs posted by their friends and make appropriate response. Despite considerable progress on microblog sentiment classification, most of the existing works ignore the influence of personal distinctions of different microblog users on the sentiments they convey, and none of them has provided real-world personalized sentiment classification systems. Considering personal distinctions in sentiment analysis is natural and necessary as different people have different language habits, personal characters, opinion bias and so on. In …
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Smokey: Ubiquitous Smoking Detection With Commercial Wifi Infrastructures, Xiaolong Zheng, Jiliang Wang, Longfei Shangguan, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous smoking detection. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, which leverages the patterns smoking leaves on WiFi signals to identify the smoking activity even in the non-line-of-sight and through-wall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detection based motion acquisition method …
Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Tuning By Turning: Enabling Phased Array Signal Processing For Wifi With Inertial Sensors, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Research Collection School Of Computing and Information Systems
Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …
Knowledge Cluster Development Through Connectivity: Examples From Southeast Asia, Hans-Dieter Evers, Thomas Menkhoff
Knowledge Cluster Development Through Connectivity: Examples From Southeast Asia, Hans-Dieter Evers, Thomas Menkhoff
Research Collection School Of Computing and Information Systems
Whereas since the 1990s national and regional planners saw the creation of knowledge clusters as a panacea for gaining a competitive advantage to propel a region or country into a higher stage of industrial development, recent research suggests that connectivity (e.g. through broadband penetration or joint research connections with collaborators elsewhere) is one of the enablers for socio-economic development. This paper will draw on the results of studies on knowledge clusters in Southeast Asian countries (Malaysia, Brunei, Singapore) as well as the relevant current literature to ask the question, whether knowledge clusters really contribute to regional development and if yes, …
From Classification To Quantification In Tweet Sentiment Analysis, Wei Gao, Fabrizio Sebastiani
From Classification To Quantification In Tweet Sentiment Analysis, Wei Gao, Fabrizio Sebastiani
Research Collection School Of Computing and Information Systems
entiment classification has become a ubiquitous enabling technology in the Twittersphere, since classifying tweets according to the sentiment they convey towards a given entity (be it a product, a person, a political party, or a policy) has many applications in political science, social science, market research, and many others. In this paper, we contend that most previous studies dealing with tweet sentiment classification (TSC) use a suboptimal approach. The reason is that the final goal of most such studies is not estimating the class label (e.g., Positive, Negative, or Neutral) of individual tweets, but estimating the relative frequency (a.k.a. “prevalence”) …
On Effective Location-Aware Music Recommendation, Zhiyong Cheng, Jialie Shen
On Effective Location-Aware Music Recommendation, Zhiyong Cheng, Jialie Shen
Research Collection School Of Computing and Information Systems
Rapid advances in mobile devices and cloud-based music service now allow consumers to enjoy music any-time and anywhere. Consequently, there has been an increasing demand in studying intelligent techniques to facilitate context-aware music recommendation. However, one important context that is generally overlooked is user's venue, which often includes surrounding atmosphere, correlates with activities, and greatly influences the user's music preferences. In this article, we present a novel venue-aware music recommender system called VenueMusic to effectively identify suitable songs for various types of popular venues in our daily lives. Toward this goal, a Location-aware Topic Model (LTM) is proposed to (i) …
A Framework For Evaluating Energy Sustainability Efforts In Maritime Terminal Operations, Kar Way Tan, Members Of Green Transformation Lab
A Framework For Evaluating Energy Sustainability Efforts In Maritime Terminal Operations, Kar Way Tan, Members Of Green Transformation Lab
Research Collection School Of Computing and Information Systems
Environmental sustainability at ports has been getting more attention from port operators and port regulators. GHG emissions associated with operations and search for clean energy sources are some issues that are continuously monitored and urgently addressed at leading ports across the world. Singapore port, one of the busiest in the world, is no exception. In the planning for the Singapore’s next generation port, this study helps to provide a framework to learn, evaluate and monitor sustainability initiatives in maritime terminal operations for Singapore and selected international ports.
When Peculiarity Makes A Difference: Object Characterisation In Heterogeneous Information Networks, Wei Chen, Feida Zhu, Lei Zhao, Xiaofang Zhou
When Peculiarity Makes A Difference: Object Characterisation In Heterogeneous Information Networks, Wei Chen, Feida Zhu, Lei Zhao, Xiaofang Zhou
Research Collection School Of Computing and Information Systems
A central task in heterogeneous information networks (HIN) is how to characterise an entity, which underlies a wide range of applications such as similarity search, entity profiling and linkage. Most existing work focus on using the main features common to all. While this approach makes sense in settings where commonality is of primary interest, there are many scenarios as important where uncommon and discriminative features are more useful. To address the problem, a novel model COHIN (Characterize Objects in Heterogeneous Information Networks) is proposed, where each object is characterized as a set of feature paths that contain both main and …
Mycompetencies: Competency Tracking Mobile Application For Is Students, Gottipati Swapna, Shankararaman, Venky
Mycompetencies: Competency Tracking Mobile Application For Is Students, Gottipati Swapna, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
The overall aim of learning outcomes and competency based education is to improve the efficiency and effectiveness of higher education. It's important to track regularly student's competency acquisition so that the faculty can improve the teaching delivery and adapt the content accordingly. Student based self-assessment of competency tracking on a weekly basis aids faculty to intervene in course delivery process for effective teaching and learning experience. It also helps students to have a better understanding of their competency levels and accordingly prepare for weekly sessions. To enable students to self-assess the competencies in more structured format, there is a need …
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Research Collection School Of Computing and Information Systems
Proper collection of Household Hazardous Waste (HHW) is an important action to support environmental sustainability. We investigate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions, as they relate to participation in HHW collection programs. We find two factors that influence household informedness: the provision of public education about HHW and environmental quality information. We conducted an empirical study on HHW collection in California to obtain statistical evidence on the effect of these factors on the amount of HHW collected. The findings of this policy analytics study improve our understanding of …
Lightsense: Exploiting Smart Bulbs For Practical Multimodal Localization, Huynh Nguyen, Archan Misra, Youngki Lee
Lightsense: Exploiting Smart Bulbs For Practical Multimodal Localization, Huynh Nguyen, Archan Misra, Youngki Lee
Research Collection School Of Computing and Information Systems
Visible Light Positioning (VLP) is an exciting new approach but has to overcome considerable challenges before it becomes practical. In particular, the line-of-sight requirement which imports the constraint on the working condition of VLP and can not be solved by the VLP itself. This paper develops techniques to allow VLP to be augmented with traditional WI-FI approach by leveraging the WI-FI enabled smart bulbs which are now widely available. Those Smart bulbs offer several intriguing properties: a very dense deployment (roughly every 2 meters apart), ability to act as sensors that continually provide Wi-Fi signal strength measurements. We utilize these …
Where Am I? Characterizing And Improving The Localization Performance Of Off-The-Shelf Mobile Devices Through Cooperation, Huiguang Liang, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Where Am I? Characterizing And Improving The Localization Performance Of Off-The-Shelf Mobile Devices Through Cooperation, Huiguang Liang, Hyong S. Kim, Hwee-Pink Tan, Wai-Leong Yeow
Research Collection School Of Computing and Information Systems
We are increasingly reliant on cellular data services for many types of day-to-day activities, from hailing a cab, to searching for nearby restaurants. Geo-location has become a ubiquitous feature that underpins the functionality of such applications. Network operators can also benefit from accurate mobile terminal localization in order to quickly detect and identify location-related network performance issues, such as coverage holes and congestion, based on mobile measurements. Current implementations of mobile localization on the wildly-popular Android platform depend on either the Global Positioning System (GPS), Android's Network Location Provider (NLP), or a combination of both. In this paper, we extensively …
Large Scale Online Kernel Learning, Jing Lu, Hoi, Steven C. H., Jialei Wang, Peilin Zhao, Zhi-Yong Liu
Large Scale Online Kernel Learning, Jing Lu, Hoi, Steven C. H., Jialei Wang, Peilin Zhao, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online …
Rate Distortion Balanced Data Compression In Wireless Sensor Networks, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Rate Distortion Balanced Data Compression In Wireless Sensor Networks, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world data sets and compared with conventional methods for temporal and spatial data compression. The …