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关键词： Synchronization   Performance evaluation   Batteries   IEEE 802   11 Standard   Computer science   Asia   Monitoring   IEEE 802   11ba   wake-up radio (WUR)   wake-up frames   PHY   MAC operations   the Internet of Things   energy efficiency  

摘要： Featuring a long operation time to avoid frequent battery replacements, highly energy-efficient radios have shown their pivotal functions for low-power and battery-driven devices in supporting manifold Internet-of-Things (IoT) services. To this end, prolific systems for highly energy-efficient radios have been widely deployed, but they impose a critical challenge of sacrificed data rates to preclude the applications that both require high energy efficiency and high data rates. Recently, this challenge has driven the concept of equipping two radio-chains on a low-power device, known as the primary connectivity radio (PCR) and companion connectivity radio (CCR). The PCR supports high data rate transmissions, and switches to the sleeping mode when no data should be received. In this case, the CCR stays awake to monitor traffic, and wakes up the PCR when data requiring to be received arrives. However, to practice such a concept, sophisticated operations in the physical (PHY) layer and medium access control (MAC) layers are required. Consequently, the IEEE 802.11 Task Group "ba" (TGba) has been formed to launch the normative works since 2017. In the normative development, the most challenging issue lies in the design of a new frame structure especially the preamble sequence, by which the CCR in a station (STA) can efficiently synchronize with an access point (AP) and the PCR can be promptly waken up when an AP wishes to transmit data to an STA. To comprehend such a crucial foundation for the next generation low-power IoT devices, this paper provides comprehensive knowledge of state-of-the-art PHY/MAC operations of IEEE 802.11ba. Most importantly, a preamble sequence design for synchronization is further proposed for the new frames supported in IEEE 802.11ba. Through comprehensively evaluating the performance of different designs (in terms of data rate configuration and synchronization sequences), we justify the outstanding performance of the proposed design in terms of t

关键词： Social network services   Australia   Psychology   Computer science   Recommender systems   Business   Sociology   Context-aware   data sparsity problem   online social networks   pair-wise trust prediction   trust   trust relations   time-aware  

摘要： Level of Trust can determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for measuring trust in Online Social Networks (OSNs), including social spammer detection, fake news detection, retweet behaviour detection and recommender systems. Trust prediction is the process of predicting a new trust relation between two users who are not currently connected. In applications of trust, trust relations among users need to be predicted. This process faces many challenges, such as the sparsity of user-specified trust relations, the context-awareness of trust and changes in trust values over time. In this paper, we analyse the state-of-the-art in pair-wise trust prediction models in OSNs, classify them based on different factors, and propose some future directions for researchers interested in this field.

关键词： Mathematics   Artificial intelligence   Computer science  

摘要： Advancements in parallel processing and high-speed networking have opened an avenue for real-time processing of machine learning algorithms, an avenue which was previously computationally infeasible. Machine learning classifiers and computer vision algorithms have seen deployment in increasingly critical applications. All the success has led to the commercial deployment of critical technologies containing machine learning classifiers (e.g. self-driving cars). The problem with this rapid adoption is the limited acknowledgment of the need for or discussion about securing autonomous machine learning systems against attacks. In the mid-2010s, some researchers published methods for attacking machine learning classifiers, which would cause them to misclassify inputs. Research on machine learning attacks has gained traction, making appearances in publications for the Association of Computing Machinery and Black Hat Conferences. The purpose of this research was to analyze how easily machine learning classifiers fail unintentionally and how easily they can be broken intentionally by compounding the methods of past works into an implemented attack on machine learning classifiers. The research found that standard machine learning classifiers on bona fide data sets can be broken with simple attacks, for which strong security is lacking. The research also found that the defense against attack relies on a weak assumption that a spatial distinction between malicious input and acceptable input exists. Based on these findings, this research recommended limiting the use of autonomous classifiers in critical applications. Keywords: Cybersecurity, Dr. Donnie Wendt, Machine Learning Classifiers, Computer Vision, Carlini and Wagner, Black-box Attacks, Critical Applications,

关键词： Computer science  

摘要： Return oriented programming (ROP) attacks have been studied for many years, but they are usually still constructed manually. The existing tools to synthesize ROP exploits automatically, such as ROPGadget and angrop, are very limited by their ad-hoc design: they rely on matching fixed patterns and assembling gadgets in fixed ways. We propose a new method, PEACE, that uses symbolic execution and partial-order planning to assemble gadgets more flexibly. Our method incrementally selects gadgets to address a need in the partially-constructed exploit, and infers ordering constraints over those gadgets based on their effects. This approach enables PEACE to create exploits for many more binaries than existing tools. By creating a more flexible and powerful ROP attack generation tool, we hope to raise awareness of how much code is vulnerable

关键词： Information technology   Computer science  

摘要： Much of the information created today is scattered throughout books, magazines, web pages, academic papers, and other documents that cannot be directly queried in a structured way. To address this challenge, people are building structured knowledge bases to make this information more accessible. The process of populating knowledge bases from unstructured inputs is called knowledge base construction (KBC). Through KBC, we can make troves of valuable information more accessible. However, existing KBC systems have limited abilities to handle input data from a wide variety of formats, including unstructured text, tables, and figures, contained within highly variable file structures. This data heterogeneity makes automated, scalable KBC difficult to achieve in real-world scenarios. This dissertation focuses on automating and scaling the complex process of building KBC systems from heterogeneous data. In particular, we study both knowledge distillation and representation from richly formatted data, where information is expressed via combinations of textual, structural, tabular, and visual cues, as well as novel techniques for making these processes feasible in practice. This dissertation consists of two parts. In the first part, we aim to discover the fundamental building blocks of KBC from richly formatted data. We present Fonduer, a KBC system enabling extraction of information from richly formatted data. Fonduer automatically models richly formatted data and allows both users and machines to systematically retrieve all of a document's multimodal information in a programmatic way. This information can formalize multimodal signals for both training data generation via weak supervision and for augmenting deep learning models with multimodal features to perform task learning. In the second part of this dissertation, we study how building knowledge bases can be made feasible in practice. We investigate two crucial parts of Fonduer's pipeline: training data generation and ta

关键词： Computer engineering   Electrical engineering   Computer science  

摘要： The continued scaling of integrated circuits (ICs) introduces complex interactions between layout features, which can lead to manufacturability issues that reduce yield. In recent years, foundries have increased capital expenditures and time to inspect and review equipment for process control and yield improvement. One strategy is the use of test structures to identify sources of yield loss early in the development of a new manufacturing process. However, the aggressive scaling of feature dimensions, the integration of new materials, and the increase in structural complexity in modern technologies has challenged the capabilities of conventional test structures. To help address these challenges, a new logic test chip, called the Carnegie Mellon Logic Characterization Vehicle (CM-LCV), has been developed. It is based on the insight that the manufacturing process is sensitive only to the physical features of a design (i.e., its physical layout), and not the logic functionality the layout implements. This provides the freedom to select a logical functionality and structure that maximizes testability and diagnosability, and a layout implementation that has physical features that will be manufactured in the actual product designs. To be specific, the CM-LCV utilizes a two-dimensional array of functional unit blocks (FUBs) that each implement an innovative functionality. Composability within this FUB array is demonstrated for fault coverage, logical and physical design features, and fault distinguishability. Particularly, three design methodologies that leverage composability to adapt the FUB array to incorporate three layout demographics automatically are presented. The three layout demographics represent the physical features of the actual production design, including 1) layout geometries within the each individual standard cell, 2) the layout geometries of the standard-cell neighborhoods, and 3) layout geometries that connect the standard cells. Experiments demonstrate

关键词： Computer science  

摘要： Microservice architectures have gained prominence in recent years for building large-scale industrial distributed systems. However, microservice architectures make the usage of replay debugging, a powerful technique for finding root causes of faults, very challenging because of the polyglot (written in several languages) services, large accumulated state of services, and tight latency limits imposed by long hop-chains. This work attempts to provide a framework for enabling replay debugging in production microservice applications. We study 25 real-world faults in microservice systems collected from diverse sources, categorize these faults by fault symptoms, and create 15 application agnostic mutation operators for microservices. We then propose a language agnostic replay debugging framework for microservice applications that uses a distributed tracing system to record network requests and enables replay of those requests on cloned service containers running in a debug environment. A key component of this framework is an anomaly detector that uses span-level and container-level monitoring to detect fault symptoms found in our study and localizes faults to trace level so that faulty traces can be easily replayed to find the root cause. An open-source microservices application injected successively with the mutation operators is used for an evaluation that shows that our framework is upto an order of magnitude lighter-weight than language-specific recording tools such as Chrome DevTools or VisualVM and can help in finding root causes of 9 out of 15 mutations at a line or function level.

关键词： Neurosciences   Computer science  

摘要： One of the greatest scientific challenges of this century is to understand how the brain produces behavior. In this regard, information theory has emerged as one of the main theoretical frameworks that allow us to study neural information processing at all spatial and temporal scales. However, most work in this domain involves studying the brain in isolation without taking into consideration the body, the environment and the interaction between them. The goal of this dissertation is to advance our understanding of the neural basis of behavior by incorporating the environment into the information-theoretic analyses. Specifically, using computational models, I demonstrate that including the environment and agent-environment interaction in our study helps better understand three prominent phenomena of adaptive behavior, namely predictive coding, multifunctionality, and multiagent interaction. Under predictive coding, besides demonstrating that the environment is a source of predictive information, I present a framework based on Partial Information Decomposition to disentangle the source of information encoded in a neural network: extrinsically provided by the environment versus intrinsically generated in the neural network. Under multifunctionality, besides demonstrating that environmental feedback alone can drive multiple behaviors in the same sensorimotor system, I provide proof-of-concept about the extent to which neural resources can be reused across tasks; the same neural activity can produce multiple behaviors in an embodied agent. Finally, under multiagent interaction, I show that mutual interaction with other agents can result in neural dynamics that are qualitatively different from neural dynamics achievable in one-way interaction or isolation. Altogether, I show that informational structure either provided by the environment or acquired via agent-environment interaction shapes neural information encoding as well as ongoing neural dynamics in a way that can on

关键词： Computer science  

摘要： With the ever-growing need for connectivity in this era of smart and autonomous systems, we are observing an extensive use of network services. The increasing use of cyber technology, however, leads to the proliferation of security threats. Therefore, it is essential to design a secure and resilient architecture for networked systems. Moreover, due to the diversified cyber usages as well as security requirements, adaptive and ad-hoc networking solutions are increasingly being adopted. While adaptive networking provides many flexibilities, it requires to be properly (re)configured considering the changed context and dependability aspects. Organizations are seeking more reliable and automated design strategies that can meet the operational goals and security requirements within the budget and capability constraints, which is a multi-objective and combinatorially hard constraint satisfaction problem. This dissertation addresses this problem by proposing a suite of network synthesis techniques using formal methods that can automatically synthesize network configurations satisfying the given requirements. This research considers three configuration synthesis problems that cover different security and resiliency perspectives of the automated design of adaptive networked systems. The first problem addresses the configuration synthesis for a network functions virtualization (NFV)-based network concerning a security objective that requires the appropriate deployment of virtual network functions (VNFs) on physical servers. The second problem studies the automated synthesis of incremental deployment plans for software-defined networking (SDN) compatible switches. Here, we choose the context of enabling security and resiliency for a communication network in a smart grid. The objective of the third problem is to ensure resilient communication for a collaborative network of unmanned aerial vehicles (UAVs), maintaining in-flight constraints and mission requirements. To solve the p

关键词： Business administration   Health sciences   Computer science  

摘要： Managing medical device monitoring processes is challenging and lacks a realtime, life cycle tracking strategy to reduce adverse medical events and revision costs for hospital administrators, physicians, and patients. Understanding the malfunctions of medical devices for cardiac and orthopedic patients could save lives and reduce hospital liability. Grounded in the business process reengineering conceptual framework, the purpose of this single qualitative case study was to explore strategies hospital managers used to redesign the implant recall surveillance process at one hospital in Pennsylvania. The 5 participants selected successfully implemented a medical device surveillance process that reduced adverse medical events and revision costs. Data were collected using semistructured interviews and a review of relevant medical device surveillance workflow documents. The 4 themes that emerged from a thematic analysis were effective data communication process, central data repository integration, continuous process improvement, and end-to-end surveillance process. A key recommendation for hospital administrators, physicians, and managers is to use blockchain distributed ledger technology to assess device identification challenges as part of the surveillance process to reduce health risks. The implication for positive social change includes the potential to improve the quality of life for medical device recipients who may spend less on healthcare services.