User-centred design (UCD) has been developed as a useful and effective design approach for designing interactive systems. However, some researchers point out that UCD methods created for the developed world imply assu...
ISBN:
(纸本)9783031645754;9783031645761
User-centred design (UCD) has been developed as a useful and effective design approach for designing interactive systems. However, some researchers point out that UCD methods created for the developed world imply assumptions that make them difficult to use in the developing world. The paper presents a systematic literature review focused on user-centered design initiatives for development in rural areas. A comprehensive analysis of 190 publications was conducted in order to systematically and critically examine existing design studies. The results support results from previous reviews and provide deeper insights into existing challenges and underlying assumptions and attitudes.
In contemporary applications of data analysis, data series similarity search holds great significance. A substantial body of research design data series indices for exact similarity search. The iSAX family, employing ...
ISBN:
(纸本)9789819755684;9789819755691
In contemporary applications of data analysis, data series similarity search holds great significance. A substantial body of research design data series indices for exact similarity search. The iSAX family, employing iSAX sketch to represent a SAX collection, stands as a pivotal research direction. However, we find a critical flaw in the iSAX sketch that its representation of SAX collections leads to a significant deterioration in the lower bound distance, thereby impacting the pruning efficiency and search performance of the index. To address the limitation, we propose a novel sketch, called bSAX. bSAX, by leveraging boundary information from SAX summarizations, offers a tighter lower bound distance than iSAX. Moreover, we design a novel index for data series, with a cost model involving compressed information loss. Conducting comprehensive experimental comparisons, we validate the superior performance of bSAX in the similarity search.
In the realm of network, finding top-K influential vertices in data streams is a fundamental problem. Among these, Katz centrality serves as a valuable metric in the analysis of graph. Nevertheless, the computation of...
ISBN:
(纸本)9789819772377;9789819772384
In the realm of network, finding top-K influential vertices in data streams is a fundamental problem. Among these, Katz centrality serves as a valuable metric in the analysis of graph. Nevertheless, the computation of Katz centrality demands substantial resources. Therefore, this paper introduces an innovative approach to estimate top-K temporal Katz centrality. To achieve this, we propose a data structure called TAS-PFAH. It consists of a filter and a Count Sketch. The Count Sketch employs the tug-of-war principle to provide an unbiased estimation of vertices. Concurrently, the filter serves as a repository for the vertices, dynamically maintaining the foremost K vertices in temporal graph. It is implemented by a min-heap structure accelerated by an auxiliary hash table to ensure O(1) lookup time cost. The introduction of filter not only enhances the rate of enquiring vertex which has high temporal Katz centrality, but also reduces the noise of other vertices which recorded in the Count Sketch. Because the combination of filter and sketch, our algorithm achieves high accuracy with limited memory.
The Internet of Things rapid growth poses privacy and security challenges for the traditional key storage methods. Physical Unclonable Functions offer a potential solution but require secure fuzzy extractors to ensure...
ISBN:
(纸本)9783031547690;9783031547706
The Internet of Things rapid growth poses privacy and security challenges for the traditional key storage methods. Physical Unclonable Functions offer a potential solution but require secure fuzzy extractors to ensure reliable replication. This paper introduces X-Lock, a novel and secure computational fuzzy extractor that addresses the limitations faced by traditional solutions in resource-constrained IoT devices. X-Lock offers a reusable and robust solution, effectively mitigating the impacts of bias and correlation through its design. Leveraging the preferred state of a noisy source, X-Lock encrypts a random string of bits that can be later used as seed to generate multiple secret keys. To prove our claims, we provide a comprehensive theoretical analysis, addressing security considerations, and implement the proposed model. To evaluate the effectiveness and superiority of our proposal, we also provide practical experiments and compare the results with existing approaches. The experimental findings demonstrate the efficacy of our algorithm, showing comparable memory cost (approximate to 2.4 KB for storing 5 keys of 128 bits) while being 3 orders of magnitude faster with respect to the state-of-the-art solution (0.086 ms against 15.51 s).
The convergence of traditional craftsmanship and cutting-edge digital technologies has sparked a revolution in the realm of modern visual design, particularly in the context of traditional Chinese patterns. This essay...
ISBN:
(纸本)9783031609039;9783031609046
The convergence of traditional craftsmanship and cutting-edge digital technologies has sparked a revolution in the realm of modern visual design, particularly in the context of traditional Chinese patterns. This essay explores the intersection of User Cognitive Ergonomics and digital methodologies, drawing inspiration from a wealth of research that spans speculative artefacts, body-to-pattern relationships, bespoke parametric blocks, global influences, and the evolution of pattern practices. The goal is to illuminate the transformative potential of User Cognitive Ergonomics considerations in the digital realm, emphasizing a harmonious blend of tradition and innovation.
Affective computing involves examining and advancing systems and devices capable of identifying, comprehending, processing, and emulating human emotions, sentiment, politeness and personality characteristics. This is ...
ISBN:
(纸本)9783031560682;9783031560699
Affective computing involves examining and advancing systems and devices capable of identifying, comprehending, processing, and emulating human emotions, sentiment, politeness and personality characteristics. This is an ever-expanding multidisciplinary domain that investigates how technology can contribute to the comprehension of human affect, how affect can influence interactions between humans and machines, how systems can be engineered to harness affect for enhanced capabilities, and how integrating affective strategies can revolutionize interactions between humans and machines. Recognizing the fact that affective computing encompasses disciplines such as computerscience, psychology, and cognitive science, this tutorial aims to delve into the historical underpinnings and overarching objectives of affective computing, explore various approaches for affect detection and generation, its practical applications across diverse areas, including but not limited to social good (like persuasion, therapy and support, etc.), address ethical concerns, and outline potential future directions.
3D scene stylization aims to generate artistically rendered images from various viewpoints within a 3D space while ensuring style consistency regardless of the viewing angle. Traditional 2D methods usually used in thi...
ISBN:
(纸本)9783031723346;9783031723353
3D scene stylization aims to generate artistically rendered images from various viewpoints within a 3D space while ensuring style consistency regardless of the viewing angle. Traditional 2D methods usually used in this field struggle with maintaining this consistency when applied to 3D environments. To address this issue, we propose a novel approach named ControlNeRF, which employs a customized conditional diffusion model, ControlNet, and introduces latent variables, obtaining a stylized appearance throughout the scene solely driven by text. Specifically, this text-driven approach effectively overcomes the inconveniences associated with using images as style cues, and it not only achieves a high degree of stylistic consistency across various viewpoints but also produces high-quality images. We have conducted rigorous testing on ControlNeRF with diverse styles, which has confirmed these outcomes. Our approach not only advances the field of 3D scene stylization but also opens new possibilities for artistic expression and digital imaging.
We present a new, practical algorithm for computing the determinant of a non-singular dense, uniform matrix over Z;the aim is to achieve better practical efficiency, which is always at least as good as currently known...
ISBN:
(纸本)9783031645280;9783031645297
We present a new, practical algorithm for computing the determinant of a non-singular dense, uniform matrix over Z;the aim is to achieve better practical efficiency, which is always at least as good as currently known methods. The algorithm uses randomness internally, but the result is guaranteed correct. The main new idea is to use a modular HNF in cases where the Pauderis-Storjohann HCOL method performs poorly. The algorithm is implemented in OSCAR 1.0.
Bayesian optimization has gained widespread adoption in database knob tuning due to its theoretical advantages in balancing exploration and exploitation. Yet, a significant drawback of existing Bayesian optimization-b...
ISBN:
(纸本)9789819777068;9789819777075
Bayesian optimization has gained widespread adoption in database knob tuning due to its theoretical advantages in balancing exploration and exploitation. Yet, a significant drawback of existing Bayesian optimization-based approaches is typically their failure to incorporate domain knowledge related to databases when searching for the optimal configuration. This limitation often leads to the recommendation of low-utility configurations that violate domain knowledge, thereby affecting its tuning efficiency. To address this issue, we propose DKTune, which seamlessly integrates Bayesian optimization with domain-specific database knowledge. DKTune leverages the inherent dominant relationships between database knobs to enhance the surrogate model used in Bayesian optimization. Additionally, it considers constraint relationships between knobs, competitive interactions among knobs, and the dynamic characteristic of knobs to assist the acquisition function in evaluating the utility of each configuration. We evaluated DKTune on two popular open-source database systems, and the experimental results demonstrate that DKTune significantly improves the efficiency of database knob tuning and the final tuning results.
We present NADA, a Network Attached Deep learning Accelerator. It provides a flexible hardware/software framework for training deep neural networks on ethernet-based FPGA clusters. The NADA hardware framework instanti...
ISBN:
(纸本)9783031661457;9783031661464
We present NADA, a Network Attached Deep learning Accelerator. It provides a flexible hardware/software framework for training deep neural networks on ethernet-based FPGA clusters. The NADA hardware framework instantiates a dedicated entity for each layer in a model. Features and gradients flow through these entities in a tightly pipelined manner. From a compact description of a model and target cluster, the NADA software framework generates specific configuration bitstreams for each particular FPGA in the cluster. We demonstrate the scalability and flexibility of our approach by mapping an example CNN onto a cluster consisting of three up to nine Intel Arria 10 FPGAs. To verify NADAs effectiveness for commonly used networks, we train MobileNetV2 on a six-node cluster. We address the inherent incompatibility of the tightly pipelined layer parallel approach with batch normalization by using online normalization instead.
暂无评论