WISK, a workload-aware learned index that combines spatial and keyword queries to efficiently retrieve objects. It integrates spatial and textual indexes and considers query workload information.

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\"COPY LINK HERE ; https:\/\/getpdf.readbooks.link\/1852333758\n\nget [PDF] Download The Earth in Context: A Guide to the Solar System (Springer-Praxis Series in Astronomy and Space Sciences) | The Earth in Context: A Guide to the Solar System (Springer-Praxis Series in Astronomy and Space Sciences)

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This research focuses on a system, known as ATPP, based on deep marked temporal point processes, designed for predicting mobile app usage patterns. By leveraging deep reinforcement learning frameworks and context-aware modules, the system aims to predict the next app a user will open, along with its

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The ID-AWARE Project aims to enhance mental health services in schools by increasing awareness, providing training for personnel, and connecting youth and families to needed support. Funded by a federal grant, the project focuses on creating healthier school environments and implementing evidence-ba

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Understanding context is crucial in discourse analysis as it helps interpret the meaning of words based on physical, social, and psychological factors, as well as the temporal and spatial dimensions of communication. Three key types of context include situational, background knowledge, and co-textua

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You need to feel secure and at ease both inside and outside of your home these days. If you are not aware, you are making your home's safety less of a priority by installing cheap locks and security systems that make it simpler for burglars to break in! If you've already had a break-in, you are awar

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Ignatian Pedagogy, rooted in the Jesuit tradition, focuses on holistic education by emphasizing Context, Experience, Reflection, Action, and Evaluation. This approach aims to create compassionate and socially aware learners who contribute positively to society. By personalizing learning and promotin

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In this drama study session, we delve into the features of drama texts, the meta-language of drama, and the context of the play "Tally's Blood" by Ann Marie Di Mambro. We learn to define dramatic terminology, create and follow stage directions, and write a summary of the play's context. The images p

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Memory content-sharing detection and tracking are crucial aspects that should be built as separate services. ConCORD, a distributed system, efficiently tracks memory content across entities like VMs and processes, reducing memory footprint size and enhancing performance. The implementation involves

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Pragmatics and Deixis are crucial aspects of language understanding, as explored by George Yule. Pragmatics focuses on the use of language in context, while Deixis involves pointing via language to convey meaning based on the immediate context. Deictic expressions play a significant role in face-to-

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The four types of grammars are General, Context-Sensitive, Context-Free, and Linear grammars, each recognizing a specific set of languages. Chomsky Hierarchy categorizes these grammars into four levels, indicating subsets of languages they can recognize. Context-free grammars have specific productio

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Describing necessary enhancements to enable Time-Aware Scheduling in IEEE 802.11be for time-sensitive applications. The focus is on aligning with the 802.1Qbv standard to address latency, jitter, and reliability issues, presenting a structured outline of requirements and configurations essential for

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This presentation sheds light on the pervasive issue of sexual assault in the military, emphasizing the need for a gender-aware approach to uproot the culture of abuse. It outlines the alarming statistics, challenges traditional perceptions, and discusses proposed solutions, highlighting the importa

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Context-Free Languages and Grammars (CFLs & CFGs) are essential in theoretical computer science, providing a framework for recognizing non-regular languages. This content explores the distinction between regular and context-free languages, delves into the construction of language recognizers using c

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PipeSwitch introduces fast pipelined context switching for deep learning applications, aiming to enable GPU-efficient multiplexing of multiple DL tasks with fine-grained time-sharing. The goal is to achieve millisecond-scale context switching overhead and high throughput, addressing the challenges o

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Explore the importance of context in understanding Bible stories and church teachings, including discussions on Magisterium, Sacred Tradition, and the role of the Church in interpreting scripture. Learn how context enhances our comprehension of religious texts and traditions. Delve into examples hig

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This information highlights the process of honoring the desire of neurologically-aware patients to donate organs after circulatory death. It discusses the referral, legal authorization, triggers for consideration, and ethical aspects involved in approaching and discussing organ donation with the pat

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Explore the CLOVE framework, a congestion-aware load balancing approach at the virtual edge, addressing issues faced by previously proposed schemes. It operates in data centers using ECMP routing, with a focus on vSwitch implementations for efficient traffic distribution.

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Addressing memory latency challenges in irregular GPGPU applications, this study explores techniques like warp-aware memory scheduling and GPU memory controller optimization to reduce DRAM latency divergence. The research delves into the impact of SIMD lanes, coalescers, and warp-aware scheduling on

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This paper discusses the implementation of an orchestrated scheduling and prefetching mechanism for GPGPUs to enhance system performance by improving IPC and overall warp scheduling policies. It presents a prefetch-aware warp scheduler proposal aiming to make a simple prefetcher more capable, result

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This work explores the intersection of man and machine in countering malicious communication in social networks, focusing on fact-checking in political discussions. The research investigates the need for technology to verify the accuracy of public figures' statements, considering the thriving field

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Explore the concept of accuracy-aware program transformations led by Sasa Misailovic and collaborators at MIT CSAIL. The research focuses on trading accuracy for energy and performance, harnessing approximate computing, and applying automated transformations in program optimization. Discover how to

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PipeSwitch is a solution that enables fast and efficient context switching for deep learning applications, aiming to multiplex multiple DL apps on GPUs with minimal latency. It addresses the challenges of low GPU cluster utilization, high context switching overhead, and drawbacks of existing solutio

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Push beyond traditional NLP models like logistic regression and PCFG with approximation-aware training. Explore factor graphs, BP algorithm, and fancier models to improve predictions. Learn how to tweak algorithms, tune parameters, and build custom models for machine learning in NLP.

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Fairbanks North Star Borough School District is committed to promoting social and emotional learning, trauma-informed practices, and student empowerment through initiatives like AK-RISES, PROJECT AWARE, and the Crisis Response Team. With a focus on literacy, school climate, attendance, and staff sup

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High data rate sensors and compute-intensive tasks put immense pressure on mobile devices, leading to the need for innovative solutions like cloudlets and stateful cloning of VMs. Swift actions such as fetching state on-demand, utilizing multicasting for parallelism, and optimizing resource usage ar

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Erasure coding is a fault-tolerance technique used in modern data centers to minimize data redundancy and increase reliability. This paper explores practical updates in erasure coding, highlighting the challenges of high update penalties and proposing cross-rack-aware strategies to mitigate cross-ra

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The demand for healthcare services continues to rise, necessitating the use of Medical Cyber-Physical Systems (MCPS) for high-quality care. Existing medical devices lack precision in alarming and fail to provide diagnostic information about patients' conditions. This project proposes a method to bui

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This research paper discusses the challenges in tracking database provenance and proposes a system, GProM, that computes provenance for database operations. It highlights the importance of exchanging provenance information between systems and the limitations of current relational database systems in

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GPS-enabled devices have made it possible to track human location history, offering insight into individual behaviors and preferences. This paradigm explores modeling techniques, challenges, and motivations for mining location data to predict and personalize user experiences. The framework presented

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This project focuses on detecting malware within signal/sensor systems using a Generative Adversarial Network (GAN) approach. By training on normal system behavior and generating fake malware-like samples, the system can effectively identify anomalies without relying on signature-based methods. The

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Understanding the significance of context in machine translation is crucial for improving accuracy and disambiguating word sense. This research delves into the impact of target-side context for discriminative models in statistical machine translation, showcasing how context influences model performa

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This study by Xin Qi, Qing Yang, David T. Nguyen, Gang Zhou, and Ge Peng from the College of William and Mary focuses on reducing data usage in video chats on smartphones. The research explores methods such as reducing frame rate, context-aware frame rate adaption, and frame interpolation to maintai

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This research by Dr. Yu Zheng aims to estimate travel time on road networks instantly using historical and current trajectories generated by vehicles. The methodology involves a context-aware tensor decomposition approach, optimal concatenation, and frequent trajectory pattern mining to address chal

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This study focuses on optimizing Back-End-of-Line (BEOL) interconnect stack geometry in advanced nodes for improved performance and energy efficiency. It explores the motivations, background, and potential benefits of Design-Aware Manufacturing (DAM) and Manufacturing-Aware Design (MAD) methodologie

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This content delves into the significance and process of trigger data analysis in the context of ATLAS software tutorials. It covers topics such as Trigger Execution, Trigger Configuration, and Trigger-Aware Analysis, providing detailed insights into how triggers are configured, data is prepared, an

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BlockDates is a tool designed to improve the extraction and interpretation of date information embedded in text narratives, particularly handling date ranges and varied formats efficiently. The tool utilizes a context-aware approach to accurately interpret single dates and date ranges, aiding organi

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Flash memory endurance can be significantly improved by implementing Write-Hotness Aware Retention Management (WARM) strategies, such as physically partitioning write-hot and write-cold pages and applying different policies to each group. This approach reduces the need for unnecessary refresh operat

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Exploring the intersection of database access control and data privacy, this paper delves into the implications of data privacy concerns on Database Management Systems (DBMS). It discusses the need for more than just access control mechanisms and highlights the evolving landscape of data publishing,

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This presentation discusses an efficient keyword-aware travel route recommendation system that leverages user-generated content and location-based social networks to provide diversified and representative travel routes. The system aims to address the challenge of restricting users to limited query o

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