This study presents a novel reverse forming (RevF) operation scheme to enhance the multi-bit programming reliability of analog resistive random-access memory (RRAM), which is essential for advancing computing-in-memor...
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This study presents a novel reverse forming (RevF) operation scheme to enhance the multi-bit programming reliability of analog resistive random-access memory (RRAM), which is essential for advancing computing-in-memory (CIM) technology. The proposed RevF method uses a series of progressively intensified RESET operations following the initial forming process. The RevF scheme significantly strengthens the unstable conductive filaments (CF) at the bottom of the HfO2 resistive switching layer (RSL) and reduces excessive oxygen ions in the TaOx thermal enhanced layer (TEL). Array-level experimental evaluations on a fully integrated 128Kb RRAM chip showcase a 3-fold reduction in the post-programming conductance instability (i.e., relaxation effect), as quantified by the relative deviation (RD), and a 10(6)-fold enhancement in the retention time. To further verify the effectiveness and advantage of the RevF scheme, a classical denoising diffusion probabilistic model (DDPM) is implemented, yielding significantly enhanced image quality compared to the conventional operation scheme.
Dependently typed programming languages have become increasingly relevant in recent years. They have been adopted in industrial strength programming languages and have been extremely successful as the basis for theore...
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The graph theory is one of the fundamental structures in computerscience used to model various scientific and engineering problems. Many problems within the graph theory are categorized as NP-hard and NP-complete. On...
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The graph theory is one of the fundamental structures in computerscience used to model various scientific and engineering problems. Many problems within the graph theory are categorized as NP-hard and NP-complete. One such problem is the minimum dominating set (MDS) problem, which seeks to identify the minimum possible subsets in a graph such that every other node in the subset is directly connected to a node in this subset. Due to its inherent complexity, developing an efficient polynomial-time method to address the MDS problem remains a significant challenge in graph theory. This paper introduces a novel algorithm that utilizes a centrality measure known as the Malatya Centrality to effectively address the MDS problem. The proposed algorithm, called the Malatya Dominating Set Algorithm (MDSA), leverages centrality values to identify dominating sets within a graph. It extends the Malatya centrality by incorporating a second-level centrality measure, which enhances the identification of dominating nodes. Through a systematic and algorithmic approach, these centrality values are employed to pinpoint the elements of the dominating set. The MDSA uniquely integrates greedy and dynamic programming strategies. At each step, the algorithm selects the most optimal (or near-optimal) node based on the centrality values (greedy approach) while updating the neighboring nodes' criteria to influence subsequent decisions (dynamic programming). The proposed algorithm demonstrates efficient performance, particularly in large-scale graphs, with time and space requirements scaling proportionally with the size of the graph and its average degree. Experimental results indicate that our algorithm outperforms existing methods, especially in terms of time complexity when applied to large datasets, showcasing its effectiveness in addressing the MDS problem.
Students’ computational thinking and programming skills may grow due to collaborative programming. But as the researchers have noted, students frequently do not use metacognition to manage their cognitive activities ...
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Real-time stereo matching with high accuracy is a dynamic research topic;it is attractive in diverse computer vision applications. This paper presents a stereo-matching algorithm that produces high-quality disparity m...
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Real-time stereo matching with high accuracy is a dynamic research topic;it is attractive in diverse computer vision applications. This paper presents a stereo-matching algorithm that produces high-quality disparity map while maintaining real-time performance. The proposed stereo-matching method is based on three per-pixel difference measurements with adjustment elements. The absolute differences and the gradient matching are combined with a colour-weighted extension of complete rank transform to reduce the effect of radiometric distortion. The disparity calculation is realized using improved dynamic programming that optimizes along and across all scanlines. It solves the inter-scanline inconsistency problem and increases the matching accuracy. The proposed algorithm is implemented on parallel high-performance graphic hardware using the Compute Unified Device Architecture to reach over 240 million disparity evaluations per second. The processing speed of our algorithm reaches 98 frames per second on 240 x 320-pixel images and 32 disparity levels. Our method ranks fourth in terms of accuracy and runtime for quarter-resolution images in the Middlebury stereo benchmark.
It is challenging to retain computing students through their first stage of undergraduate education. Attrition is high, with many transferring courses or dropping out. This poster explores preliminary findings from an...
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ISBN:
(纸本)9798400701399
It is challenging to retain computing students through their first stage of undergraduate education. Attrition is high, with many transferring courses or dropping out. This poster explores preliminary findings from an action research project improving continuation in first-stage undergraduate computing. Five years of data from Falmouth University's Games Academy in the UK suggest improvement in first-stage retention from 66.6% in 2017-18 to 91.2% in 2021-22. Findings support prior work on pair programming, media computation, and peer instruction. However, they also highlight the benefits of collaborative learning facilitated by faculty and informed by learning analytics. Peer reviews and pre-submission clinics, student advisor follow-ups, and retrieval via synoptic assessment also contributed to the improvement.
Generalizing work of Kunnemann, Paturi, and Schneider [ICALP 2017], we study a wide class of high-dimensional dynamic programming (DP) problems in which one must find the shortest path between two points in a high-dim...
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ISBN:
(纸本)9783959773096
Generalizing work of Kunnemann, Paturi, and Schneider [ICALP 2017], we study a wide class of high-dimensional dynamic programming (DP) problems in which one must find the shortest path between two points in a high-dimensional grid given a tensor of transition costs between nodes in the grid. This captures many classical problems which are solved using DP such as the knapsack problem, the airplane refueling problem, and the minimal-weight polygon triangulation problem. We observe that for many of these problems, the tensor naturally has low tensor rank or low slice rank. We then give new algorithms and a web of fine-grained reductions to tightly determine the complexity of these problems. For instance, we show that a polynomial speedup over the DP algorithm is possible when the tensor rank is a constant or the slice rank is 1, but that such a speedup is impossible if the tensor rank is slightly super-constant (assuming SETH) or the slice rank is at least 3 (assuming the APSP conjecture). We find that this characterizes the known complexities for many of these problems, and in some cases leads to new faster algorithms.
In the realm of computerscience education, the demand for diverse and challenging programming exercises continues to grow. This paper presents an innovative approach to address this demand by introducing an automatic...
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This article investigates the collision-free control problem for multi-agent systems. For such multi-agent systems, it is the typical situation where conventional methods using either the usual centralized model predi...
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The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery *** reach a balance between green transportation and competitive edg...
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The advancement of autonomous technology makes electric-powered drones an excellent choice for flexible logistics services at the last mile delivery *** reach a balance between green transportation and competitive edge,the collaborative routing of drones in the air and trucks on the ground is increasingly invested in the next generation of delivery,where it is particularly reasonable to consider customer time windows and time-dependent travel times as two typical time-related factors in daily *** this paper,we propose the Vehicle Routing Problem with Drones under Time constraints(VRPD-T)and focus on the time constraints involved in realistic scenarios during the delivery.A mixed-integer linear programming model has been developed to minimize the total delivery completion ***,to overcome the limitations of standard solvers in handling large-scale complex issues,a space-time hybrid heuristic-based algorithm has been developed to effectively identify a high-quality *** numerical results produced from randomly generated instances demonstrate the effectiveness of the proposed algorithm.
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