| 1. |
- Blanch, Krister, 1991
(författare)
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Beyond-application datasets and automated fair benchmarking
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. Instead of focusing on a specific application, beyond-application datasets instead look at capturing high-quality, high-volume data from a highly kinematic environment, for the purpose of aiding algorithm development and testing in general. Algorithm benchmarking is a cornerstone of autonomous systems development, and allows developers to demonstrate their results in a comparative manner. However, most benchmarking systems allow developers to use their own hardware or select favourable data. There is also little focus on run time performance and consistency, with benchmarking systems instead showcasing algorithm accuracy. By combining both beyond-application dataset generation and methods for fair benchmarking, there is also the dilemma of how to provide the dataset to developers for this benchmarking, as the result of a high-volume, high-quality dataset generation is a significant increase in dataset size when compared to traditional perception datasets. This thesis presents the first results of attempting the creation of such a dataset. The dataset was built using a maritime platform, selected due to the highly dynamic environment presented on water. The design and initial testing of this platform is detailed, as well as as methods of sensor validation. Continuing, the thesis then presents a method of fair benchmarking, by utilising remote containerisation in a way that allows developers to present their software to the dataset, instead of having to first locally store a copy. To test this dataset and automatic online benchmarking, a number of reference algorithms were required for initial results. Three algorithms were built, using the data from three different sensors captured on the maritime platform. Each algorithm calculates vessel odometry, and the automatic benchmarking system was utilised to show the accuracy and run-time performance of these algorithms. It was found that the containerised approach alleviated data management concerns, prevented inflated accuracy results, and demonstrated precisely how computationally intensive each algorithm was.
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| 2. |
- Zhang, Kewei, et al.
(författare)
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Protecting GNSS Open Service-Navigation Message Authentication against Distance-Decreasing Attacks
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- As the security of global navigation satellite systems (GNSS) for civilian usage is increasingly important, navigation message authentication (NMA) significantly improves resilience to spoofing attacks. However, not all attacks can be effectively countered: a strong variant of replay/relay attacks, distance-decreasing (DD) attacks, can shorten pseudorange measurements, without manipulating the cryptographically protected navigation message, thus manipulating the position, velocity, and time solution undetected. First, we discuss how DD attacks can tamper with GNSS signals, demonstrating the attack effectiveness on a recorded Galileo signal. DD attacks might introduce bit errors to the forged signals, but the adversary can keep this error rate very low with proper attack parameter settings. Then, based on our mathematical model of the prompt correlator output of the tracking phase at the victim receiver, we find that the correlator output distribution changes in the presence of DD attacks. This leads us to apply hypothesis testing to detect DD attacks, notably a Goodness of Fit (GoF) test and a generalized likelihood ratio test (GLRT), depending on the victim’s knowledge on the DD attacks. Monte Carlo simulations are used to evaluate the detection probability and the receiver operating characteristic (ROC) curves for two tests, for different adversary configuration and noise settings. Then, we evaluate the effectiveness of the GoF and GLRT tests with a synthesized DD signal. Both tests can detect DD attacks with similar performance in high signal-to-noise ratio (SNR) environments. The GLRT detection probability is approximately 20% higher than that of the GoF test in low SNR environments.
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| 3. |
- Ribeiro, Luis, et al.
(författare)
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Industrial Agents for the Fast Deployment of Evolvable Assembly Systems
- 2015. - 1st ed.
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Ingår i: Industrial Agents. - Amsterdam, Netherlands : Elsevier. - 9780128003411 ; , s. 301-321, s. 301-322
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Bokkapitel (refereegranskat)abstract
- The current manufacturing scenario is characterized by high market unpredictability. Agility is therefore a central challenge for modern companies that need to understand and be proactive towards their product offer in respect to “what is offered, when it is offered, where, how and by whom” (Brown & Bessant 2003).The “what” and the “when” are particularly relevant to the research in emerging paradigms as they account for variety, customization and volume; and timing, speed and seasonality (Brown & Bessant 2003).In this scenario, several design approaches and models have been proposed in the last decade to enable re-configurability and subsequently enhance the companies’ ability to adjust their offer in nature and time.From a paradigmatic point of view research has concentrated on the organizational structure of the shop-floor and the associated controls aspects. Concepts like Reconfigurable Manufacturing Systems (RMS) (Koren & Shpitalni 2010) and Fractal Factories (FF) (Montreuil 1999) support the physical construction of production systems by regulating their layout and making a few assumptions on their logical organization. On the other hand, concepts like Bionic Manufacturing Systems (BMS)(Ueda 1992), Holonic Manufacturing Systems (HMS)(Van Brussel et al. 1998), Evolvable Assembly Systems (Ribeiro et al. 2010) essentially provide the theoretical guidelines for the logical/computational organization of the system (see (Tharumarajah 1996) for a comparison between BMS, HMS and FF and (Setchi & Lagos 2004) for the rationale supporting the shift from Dedicated Lines to Flexible Manufacturing System and finally RMS).While these paradigms provide the conceptual framework and the main design guidelines their actual interpretation and implementation has led to a wider set of architectures (Monostori, Váncza & Kumara 2006; Leitão 2009; Parunak 2000; Pěchouček & Mařík 2008).These architectures align the high-level principles with the technological offer and limitations while seeking to address the re-configurability requirements of (Mehrabi, Ulsoy & Koren 2000; Rösiö & Säfsten 2013):module mobility – modules are easy and quick to move and install;“diagnosability” – it is quick to identify the sources of quality and reliability problems;“integrability” – modules are easy to integrate into the rest of the system.“convertibility” – it is easy and quick to switch between existing products and it is easy to adapt the system to future products;scalability – it is easy to enlarge and downsize the production system;“automatibility” – a dynamic level of automation is enabled;modularity – all system elements are designed to be modular;customization – the capability and flexibility of the production system is designed according to the products to be produced in the system.Instant deployment, as addressed in the present chapter directly addresses mobility, “integrability”, “convertibility”, scalability and customization. Mechatronic modularity is a prerequisite and is enforced by the proposed architecture and the considered modular design. “Diagnosability” was not specifically tackled.In this context, the chapter analyses the agent-based architecture related with the Instantly Deployable Evolvable Assembly System (IDEAS) project that is inspired by the Evolvable Assembly System (EAS) paradigm (Ribeiro et al. 2010) as a mechanism to enable fast deployment of mechatronic modules. EAS advocates the use of process-oriented modules and envisions the production system as a collection of processes and the associated interacting agents.The architecture and the related test cases are used to draw the main lessons learned in respect to technological and conceptual implications.In this context, the remainder of this text is organized as follows: section 1.1 discusses the main deployment challenges, section 1.2 details the reference architecture and associated concepts, section 1.3 presents the principal implementation decisions, section 1.4 features the main lessons learned, sections 1.5 discusses the benefits of the proposed approach and finally section 1.6 reflects on the main conclusions.
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| 4. |
- Fredenberg, Erik, 1979-
(författare)
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Spectral Mammography with X-Ray Optics and a Photon-Counting Detector
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Early detection is vital to successfully treating breast cancer, and mammography screening is the most efficient and wide-spread method to reach this goal. Imaging low-contrast targets, while minimizing the radiation exposure to a large population is, however, a major challenge. Optimizing the image quality per unit radiation dose is therefore essential. In this thesis, two optimization schemes with respect to x-ray photon energy have been investigated: filtering the incident spectrum with refractive x-ray optics (spectral shaping), and utilizing the transmitted spectrum with energy-resolved photon-counting detectors (spectral imaging). Two types of x-ray lenses were experimentally characterized, and modeled using ray tracing, field propagation, and geometrical optics. Spectral shaping reduced dose approximately 20% compared to an absorption-filtered reference system with the same signal-to-noise ratio, scan time, and spatial resolution. In addition, a focusing pre-object collimator based on the same type of optics reduced divergence of the radiation and improved photon economy by about 50%. A photon-counting silicon detector was investigated in terms of energy resolution and its feasibility for spectral imaging. Contrast-enhanced tumor imaging with a system based on the detector was characterized and optimized with a model that took anatomical noise into account. Improvement in an ideal-observer detectability index by a factor of 2 to 8 over that obtained by conventional absorption imaging was found for different levels of anatomical noise and breast density. Increased conspicuity was confirmed by experiment. Further, the model was extended to include imaging of unenhanced lesions. Detectability of microcalcifications increased no more than a few percent, whereas the ability to detect large tumors might improve on the order of 50% despite the low attenuation difference between glandular and cancerous tissue. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.
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| 5. |
- Yanggratoke, Rerngvit, 1983-
(författare)
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Data-driven Performance Prediction and Resource Allocation for Cloud Services
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cloud services, which provide online entertainment, enterprise resource management, tax filing, etc., are becoming essential for consumers, businesses, and governments. The key functionalities of such services are provided by backend systems in data centers. This thesis focuses on three fundamental problems related to management of backend systems. We address these problems using data-driven approaches: triggering dynamic allocation by changes in the environment, obtaining configuration parameters from measurements, and learning from observations. The first problem relates to resource allocation for large clouds with potentially hundreds of thousands of machines and services. We developed and evaluated a generic gossip protocol for distributed resource allocation. Extensive simulation studies suggest that the quality of the allocation is independent of the system size for the management objectives considered.The second problem focuses on performance modeling of a distributed key-value store, and we study specifically the Spotify backend for streaming music. We developed analytical models for system capacity under different data allocation policies and for response time distribution. We evaluated the models by comparing model predictions with measurements from our lab testbed and from the Spotify operational environment. We found the prediction error to be below 12% for all investigated scenarios.The third problem relates to real-time prediction of service metrics, which we address through statistical learning. Service metrics are learned from observing device and network statistics. We performed experiments on a server cluster running video streaming and key-value store services. We showed that feature set reduction significantly improves the prediction accuracy, while simultaneously reducing model computation time. Finally, we designed and implemented a real-time analytics engine, which produces model predictions through online learning.
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| 6. |
- Bengtsson, Lars, 1963
(författare)
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Mikrodatorteknik
- 1995
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- Första delen behandlar Microchips "Base-line"-kretsar och andra delen behandlar "Midrange"-kretsarna. De flesta funktioner belyses med konstruktionsexempel. Exempel och övningar är mycket hårdvarunära och boken behandlar konstruktion av mikrodatorer från grunden. Boken är avsedd för kurser i mikrodatorteknik på högskolan eller annan högre teknisk utbildning, men kan även användas som självstudiematerial eftersom de flesta exempel ges med detaljerade och verifierade lösningar av såväl hård- som mjukvaran. Tidigare erfarenhet av assemblerprogrammering är inte nödvändig men grundläggande kunskaper i digitalteknik förutsätts. Boken kan med fördel också läsas av rutinerade assemblerprogrammerare som vill veta hur prestanda hos de nya RISC-baserade PIC-controllerna står sig i konkurrensen med de mer etablerade enchipscontrollerna, t ex HC11 och 8751, som bygger på traditionell CISC-arkitektur.
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| 7. |
- Lian, Mengke, et al.
(författare)
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What Can Machine Learning Teach Us about Communications
- 2018
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Ingår i: IEEE International Symposium on Information Theory - Proceedings. - 2157-8095. ; 15 January 2019
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Konferensbidrag (refereegranskat)abstract
- Rapid improvements in machine learning over the past decade are beginning to have far-reaching effects. For communications, engineers with limited domain expertise can now use off-the-shelf learning packages to design high-performance systems based on simulations. Prior to the current revolution in machine learning, the majority of communication engineers were quite aware that system parameters (such as filter coefficients) could be learned using stochastic gradient descent. It was not at all clear, however, that more complicated parts of the system architecture could be learned as well. In this paper, we discuss the application of machine-learning techniques to two communications problems and focus on what can be learned from the resulting systems. We were pleasantly surprised that the observed gains in one example have a simple explanation that only became clear in hindsight. In essence, deep learning discovered a simple and effective strategy that had not been considered earlier.
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| 8. |
- Ivanov, Mikhail, 1986, et al.
(författare)
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Unequal Error Protection in Coded Slotted ALOHA
- 2016
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Ingår i: IEEE Wireless Communications Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2162-2345 .- 2162-2337. ; 5:5, s. 536-539
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Tidskriftsartikel (refereegranskat)abstract
- We analyze the performance of coded slotted ALOHA systems for a scenario where users have different error protection requirements and correspondingly can be divided into user classes. The main goal is to design the system so that the requirements for each class are satisfied. To that end, we derive analytical error floor approximations of the packet loss rate for each class in the finite frame length regime, as well as the density evolution in the asymptotic case. Based on this analysis, we propose a heuristic approach for the optimization of the degree distributions to provide the required unequal error protection. In addition, we analyze the decoding delay for users in different classes and show that better protected users experience a smaller average decoding delay.
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| 9. |
- Zhang, Kewei
(författare)
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Secure GNSS-based Positioning and Timing : Distance-Decreasing attacks, fault detection and exclusion, and attack detection with the help of opportunistic signals
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With trillions of devices connected in large scale systems in a wired or wireless manner, positioning and synchronization become vital. Global Navigation Satellite System (GNSS) is the first choice to provide global coverage for positioning and synchronization services. From small mobile devices to aircraft, from intelligent transportation systems to cellular networks, and from cargo tracking to smart grids, GNSS plays an important role, thus, requiring high reliability and security protection. However, as GNSS signals propagate from satellites to receivers at distance of around 20 000 km, the signal power arriving at the receivers is very low, making the signals easily jammed or overpowered. Another vulnerability stems from that civilian GNSS signals and their specifications are publicly open, so that anyone can craft own signals to spoof GNSS receivers: an adversary forges own GNSS signals and broadcasts them to the victim receiver, to mislead the victim into believing that it is at an adversary desired location or follows a false trajectory, or adjusts its clock to a time dictated by the adversary. Another type of attack is replaying GNSS signals: an adversary transmits a pre-recorded GNSS signal stream to the victim receiver, so that the receiver calculates an erroneous position and time. Recent incidents reported in press show that the GNSS functionalities in a certain area, e.g., Black Sea, have been affected by cyberattacks composed of the above-mentioned attack types. This thesis, thus, studies GNSS vulnerabilities and proposes detection and mitigation methods for GNSS attacks, notably spoofing and replay attacks. We analyze the effectiveness of one important and powerful replay attack, the so-called Distance-decreasing (DD) attacks that were previously investigated for wireless communication systems, on GNSS signals. DD attacks are physical layer attacks, targeting time-of-flight ranging protocols, to shorten the perceived as measured distance between the transmitter and receiver. The attacker first transmits an adversary-chosen data bit to the victim receiver before the signal arrives at the attacker; upon receipt of the GNSS signal, the attacker estimates the data bit based on the early fraction of the bit period, and then switches to transmitting the estimate to the victim receiver. Consequently, the DD signal arrives at the victim receiver earlier than the genuine GNSS signals would have, which in effect shortens the pseudorange measurement between the sender (satellite) and the victim receiver, consequently, affecting the calculated position and time of the receiver. We study how the DD attacks affect the bit error rate (BER) of the received signals at the victim, and analyze its effectiveness, that is, the ability to shorten pseudorange measurements, on different GNSS signals. Several approaches are considered for the attacker to mount a DD attack with high probability of success (without being detected) against a victim receiver, for cryptographically unprotected and protected signals. We analyze the tracking output of the DD signals at the victim receiver and propose a Goodness of Fit (GoF) test and a Generalized Likelihood Ratio Test (GLRT) to detect the attacks. The evaluation of the two tests shows that they are effective, with the result being perhaps more interesting when considering DD attacks against Galileo signals that can be cryptographically protected. Moreover, this thesis investigates the feasibility of validating the authenticity of the GNSS signals with the help of opportunistic signals, which is information readily available in modern communication environments, e.g., 3G, 4G and WiFi. We analyze the time synchronization accuracy of different technologies, e.g., Network Time Protocol (NTP), WiFi and local oscillator, as the basis for detecting a discrepancy with the GNSS-obtained time. Two detection approaches are proposed and one testbench is designed for the evaluation. A synthesized spoofing attack is used to verify the effectiveness of the approaches. Beyond attack detection, we develop algorithms to detect and exclude faulty signals, namely the Clustering-based Solution Separation Algorithm (CSSA) and the Fast Multiple Fault Detection and Exclusion (FM-FDE). They both utilize the redundant available satellites, more than the minimum a GNSS receiver needs for position and time offset calculation. CSSA adopts data clustering to group subsets of positions calculated with different subsets of available satellites. Basically, these positions, calculated with subsets not containing any faulty satellites, should be close to each other, i.e., in a dense area; otherwise they should be scattered. FM-FDE is a more efficient algorithm that uses distances between positions, calculated with fixed-size subsets, as test statistics to detect and exclude faulty satellite signals. As the results show, FM-FDE runs faster than CSSA and other solution-separation fault detection and exclusion algorithms while remaining equally effective.
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| 10. |
- Khanzadi, M Reza, 1983, et al.
(författare)
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Calculation of the Performance of Communication Systems from Measured Oscillator Phase Noise
- 2014
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Ingår i: IEEE Transactions on Circuits and Systems I: Regular Papers. - 1549-8328 .- 1558-0806. ; 61:5, s. 1553-1565
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Tidskriftsartikel (refereegranskat)abstract
- Oscillator phase noise (PN) is one of the major problems that affect the performance of communication systems. In this paper, a direct connection between oscillator measurements, in terms of measured single-side band PN spectrum, and the optimal communication system performance, in terms of the resulting error vector magnitude (EVM) due to PN, is mathematically derived and analyzed. First, a statistical model of the PN, considering the effect of white and colored noise sources, is derived. Then, we utilize this model to derive the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an EVM bound for the system performance. Based on our analysis, it is found that the influence from different noise regions strongly depends on the communication bandwidth, i.e., the symbol rate. For high symbol rate communication systems, cumulative PN that appears near carrier is of relatively low importance compared to the white PN far from carrier. Our results also show that 1/f^3 noise is more predictable compared to 1/f^2 noise and in a fair comparison it affects the performance less.
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