Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time Multi-process Tracing Decoder Architecture

Tracing is a form of logging by recording the execution information of programs. Since a large amount of data must be created and decoded in real time, a tracer composed mainly of dedicated hardware is widely used. Intel® PT records all information related to software execution from each hardware thread. When the execution of the corresponding software is completed, the accurate program flow can be indicated through the recorded trace data. The hardware trace program can be integrated into the operating system, but in the case of the Windows system, the kernel is not disclosed so tight integration is not achieved. Also, in a Windows environment, it can only trace a single process and do not provide a way to trace multiple process streams. In this paper, we propose a way of extending the PT trace program in order to overcome this shortcoming by supporting multi-process stream tracing in Windows environment.
Infrastructure-Independent Indoor Localization and Navigation

In the absence of any global positioning infrastructure for indoor environments, research on supporting human indoor localization and navigation trails decades behind research on outdoor localization and navigation. The major barrier to broader progress has been the dependency of indoor positioning on environment-specific infrastructure and resulting tailored technical solutions. Combined with the fragmentation and compartmentalization of indoor environments, this poses significant challenges to widespread adoption of indoor location-based services. This article puts aside all approaches of infrastructure-based support for human indoor localization and navigation and instead reviews technical concepts that are independent of sensors embedded in the environment. The reviewed concepts rely on a mobile computing platform with sensing capability and a human interaction interface (“smartphone”). This platform may or may not carry a stored map of the environment, but does not require in situ internet access. In this regard, the presented approaches are more challenging than any localization and navigation solutions specific to a particular, infrastructure-equipped indoor space, since they are not adapted to local context, and they may lack some of the accuracy achievable with those tailored solutions. However, only these approaches have the potential to be universally applicable.
RAMT

Recently a class of new in-vehicle technologies based on off-the-shelf mobile devices have been developed to improve driving safety and experience. For instance, wearables like the smartwatches are utilized to monitor the action of the driver and detect possible secondary tasks. Moreover, wearables can allow a driver to use gesture for in-vehicle controls, reducing distractions to driving. The accuracy of these systems can be significantly improved by tracking the real-time attitude of mobile devices. This paper proposes a novel system called Real-time Attitude and Motion Tracking (RAMT) that can enable a mobile device to accurately learn the coordinate system of a moving vehicle, and hence track its attitude and motion in real time. RAMT consists of a series of lightweight algorithms to sense the vehicle's movement and calculate the device's attitude. It provides a solution for trajectory-based gesture recognition. We have implemented RAMT on a smartphone and a smartwatch and evaluated the performance in 10 real driving trips. Our results show that the overall error of the coordinate system alignment is around 5° for the smartphone and 10° for the smartwatch, and over 84% of customized hand gestures can be accurately recognized with the result of RAMT. A video demo of RAMT is available at https://youtu.be/9rZp7HxyRts.
Mulsemedia DIY: A Survey of Devices and a Tutorial for Building Your Own Mulsemedia Environment

Multisensory experiences have been increasingly applied in Human-Computer Interaction (HCI). In recent years, it is commonplace to notice the development of haptic, olfactory, and even gustatory displays to create more immersive experiences. Companies are proposing new additions to the multisensory world and are unveiling new products that promise to offer amazing experiences exploiting mulsemedia—multiple sensorial media—where users can perceive odors, tastes, and the sensation of wind blowing against their face. Whilst researchers, practitioners and users alike are faced with a wide range of such new devices, relatively little work has been undertaken to summarize efforts and initiatives in this area. The current article addresses this shortcoming in two ways: first, by presenting a survey of devices targeting senses beyond that of sight and hearing and, second, by describing an approach to guide newcomers and experienced practitioners alike to build their own mulsemedia environment, both in a desktop setting and in an immersive 360° environment.
Analysis of Spatial Distribution of China's station-free bike-sharing by Clustering Algorithms

Recently, the unbalanced spatial distribution and low utilization rate of the sharing bicycles have caused a serious impact on urban traffic. This study aims to use four clustering algorithms, including k-means clustering algorithm (KM), ant colony clustering algorithm (ACO), fuzzy c-means clustering algorithm (FCM) and mean shift clustering algorithm (MS), to analyze the data of five different density gradients. By analyzing the relationship between the density of bicycle distribution and geographical location, we can get the characteristics of the spatial distribution of shared traffic resources. In this paper, Experimental results have compared the performance of the four clustering algorithms and obtained the best algorithm for the spatial data of China's station-free bike-sharing system.
Genetic Algorithm Applied to the Time-Series Landing Flight Path and Control Optimization of a Supersonic Transport

A genetic algorithm (GA) which is a meta-heuristic approach was applied to optimize the landing flight path of a delta-winged supersonic transport (SST). However, at low speeds, particularly during take-off and landing, a complex flowfield surrounds the delta wing. This phenomenon requires time-series control optimization that yields an optimum control sequence by aerodynamic - flight dynamics with high-fidelity computational fluid dynamics to evaluate the flight path with the complex flowfield. To this end, we presented an efficient flight simulation based on Kriging-model-assisted aerodynamic estimation to carry out the global optimization via a GA. After establishing the efficient aerodynamics-flight dynamics optimization, we constructed the design of the flight and control sequence for the time-series optimization of an effective SST landing. Several solutions that provide an allowable SST landing performance, along with the knowledge on optimum flight and control sequence, are presented herein.
Machine Learning Methods for Estimating the Excitation Point on a Plucked String of a Classical Guitar

The classical guitar is described as a "miniature orchestra" due to the various tone colors that it can produce. One parameter that can control the timbre on the guitar is the excitation point on the string. In this study, a machine learning model was built to determine the excitation point on the string given an audio signal. It was noted that including the mel-frequency cepstral coefficients in the feature set yields outstanding performance. Furthermore, principal component analysis can be used to reduce the dimensions without sacrificing much on performance. Among three well-known algorithms, it was observed that the multi-layer perceptron yields the best performance in terms of classification and regression. Lastly, the models were trained and tested on different subjects and it was noted that each subject has a unique model of its own since different subjects have different physiological parameters that can affect the produced guitar tone.
A Survey on Collecting, Managing, and Analyzing Provenance from Scripts

Scripts are widely used to design and run scientific experiments. Scripting languages are easy to learn and use, and they allow complex tasks to be specified and executed in fewer steps than with traditional programming languages. However, they also have important limitations for reproducibility and data management. As experiments are iteratively refined, it is challenging to reason about each experiment run (or trial), to keep track of the association between trials and experiment instances as well as the differences across trials, and to connect results to specific input data and parameters. Approaches have been proposed that address these limitations by collecting, managing, and analyzing the provenance of scripts. In this article, we survey the state of the art in provenance for scripts. We have identified the approaches by following an exhaustive protocol of forward and backward literature snowballing. Based on a detailed study, we propose a taxonomy and classify the approaches using this taxonomy.
Architecture-Aware Approximate Computing

Deliberate use of approximate computing has been an active research area recently. Observing that many application programs from different domains can live with less-than-perfect accuracy, existing techniques try to trade off program output accuracy with performance-energy savings. While these works provide point solutions, they leave three critical questions regarding approximate computing unanswered, especially in the context of dropping/skipping costly data accesses: (i) what is the maximum potential of skipping (i.e., not performing) data accesses under a given inaccuracy bound? ; (ii) can we identify the data accesses to drop randomly, or is being architecture aware (i.e., identifying the costliest data accesses in a given architecture) critical? ; and (iii) do two executions that skip the same number of data accesses always result in the same output quality (error)? This paper first provides answers to these questions using ten multithreaded workloads, and then, motivated by the negative answer to the third question, presents a program slicing-based approach that identifies the set of data accesses to drop such that (i) the resulting performance/energy benefits are maximized and (ii) the execution remains within the error (inaccuracy) bound specified by the user. Our slicing-based approach first uses backward slicing and then forward slicing to decide the set of data accesses to drop. Our experimental evaluations using ten multithreaded workloads show that, when averaged over all benchmark programs we have, 8.8% performance improvement and 13.7% energy saving are possible when we set the error bound to 2%, and the corresponding improvements jump to 15% and 25%, respectively, when the error bound is raised to 4%.
Adaptive nonlinear suppression of interference

A signal processing technique designed to suppress interference in direct sequence spread spectrum receiving systems is described. The basic idea is to optimize the detection process dynamically in the presence of current interference. This is accomplished by estimating the statistics of the interference and then using this information to derive a nonlinear transform to apply to the signal-plus-noise. As the statistics of the interference change, the measured distributions and the resulting transformations do so also. This adaptation is open-loop, thus avoiding convergence problems. It is concluded that large improvements (tens of dB) can be achieved for a wider range of interference modulations than can be handled by any previously realized technique known to the author. <<ETX>>
From Hack to Elaborate Technique—A Survey on Binary Rewriting

Binary rewriting is changing the semantics of a program without having the source code at hand. It is used for diverse purposes, such as emulation (e.g., QEMU), optimization (e.g., DynInst), observation (e.g., Valgrind), and hardening (e.g., Control flow integrity enforcement). This survey gives detailed insight into the development and state-of-the-art in binary rewriting by reviewing 67 publications from 1966 to 2018. Starting from these publications, we provide an in-depth investigation of the challenges and respective solutions to accomplish binary rewriting. Based on our findings, we establish a thorough categorization of binary rewriting approaches with respect to their use-case, applied analysis technique, code-transformation method, and code generation techniques. We contribute a comprehensive mapping between binary rewriting tools, applied techniques, and their domain of application. Our findings emphasize that although much work has been done over the past decades, most of the effort was put into improvements aiming at rewriting general purpose applications but ignoring other challenges like altering throughput-oriented programs or software with real-time requirements, which are often used in the emerging field of the Internet of Things. To the best of our knowledge, our survey is the first comprehensive overview on the complete binary rewriting process.
Position Paper: Progressive Memory Safety for WebAssembly

WebAssembly (Wasm) is a low-level platform-independent bytecode language. Today, developers can compile C/C++ to Wasm and run it everywhere, at almost native speeds. Unfortunately, this compilation from C/C++ to Wasm also preserves classic memory safety vulnerabilities, such as buffer overflows and use-after-frees. New processor features (e.g., tagged memory, pointer authentication, and fine grain capabilities) are making it increasingly possible to detect, mitigate, and prevent such vulnerabilities with low overhead. Unfortunately, Wasm JITs and compilers cannot exploit these features. Critical high-level information---e.g., the size of an array---is lost when lowering to Wasm. We present MS-Wasm, an extension to Wasm that bridges this gap by allowing developers to capture low-level C/C++ memory semantics such as pointers and memory allocation in Wasm, at compile time. At deployment time, Wasm compilers and JITs can leverage these added semantics to enforce different models of memory safety depending on user preferences and what hardware is available on the target platform. This way, MS-Wasm offers a range of security-performance trade-offs, and enables users to move to progressively stronger models of memory safety as hardware evolves.
Naming Content on the Network Layer

The Information-Centric Network (ICN) paradigm is a future Internet approach aiming to tackle the Internet architectural problems and inefficiencies, by swapping the main entity of the network architecture from hosts to content items. In ICN, content names play a central role: Each content gets a unique name at the network layer, and this name is used for routing the content over the network. This paradigm change potentially enables a future Internet with better performance, reliability, scalability, and suitability for wireless and mobile communication. It also provides new intrinsic means to deal with some popular attacks on the Internet architecture, such as denial of service. However, this new paradigm also represents new challenges related to security that need to be addressed, to ensure its capability to support current and future Internet requirements. This article surveys and summarizes ongoing research concerning security aspects of ICNs, discussing vulnerabilities, attacks, and proposed solutions to mitigate them. We also discuss open challenges and propose future directions regarding research in ICN security.
A novel ring-oscillator with a very small process and temperature variation

This paper describes a new ring-oscillator circuit, the conversion gain of which has only a 92% variation with all process variations over the temperature range of 0/spl deg/ to 100/spl deg/C. The operating range of the oscillator is 180 to 380 MHz. The circuit uses a 3-stage ring-oscillator for low speed conditions and a 4-stage oscillator for high speed conditions. The division between low and fast conditions is based on the transconductance of the MOS-transistors. The oscillator has also a process and temperature dependent control current. The circuit has been designed with a standard 0.5 /spl mu/m CMOS-process.
Joint Transceiver Design for Fully-Duplex Cloud-Access DEINs

With the rapid development of communication technology, the demand of rate of communication network is higher and higher, and the problem of energy consumption is becoming more and more serious. Data and Energy Integrated communication Networks (DEINs) can simultaneously transmit information and energy for the terminal, which greatly improves the convenience of the terminal and makes devices without batteries possible in future. This paper studies the joint design of transceivers in a full-duplex cloud access number-integrated network. The system model considers both upstream and downstream users. Considering the need for joint resource allocation for system uplink and downlink, full-duplex technology and self-interference caused by full-duplex technology are considered into the system. The optimization goal of this problem is to minimize the total power consumption under the uplink and downlink SINR and EH constraints. For this non-convex optimization problem, An algorithm combining ZF beamforming and MRT beamforming is proposed. In the hybrid beamforming algorithm, the zero-forcing (ZF) beamformer and MRT beamformer are linearly combined, which simplifies the optimization of the downlink beam vector to the optimization of the combination ratio. The proposed algorithm is simulated. Simulation results show that the power consumed in the half-duplex scenario is higher than that in the full duplex scenario. The time spent in the hybrid beamforming algorithm does not change with the increase in the number of RRH antennas.
Simulation for Agglomeration Effect of Internet Crowdfunding Model

Crowdfunding has become an important channel for the transformation of innovation achievements. Exploring the healthy and rapid development of crowdfunding is a hot of academic research. This paper simulates the agglomeration effect in the development of crowdfunding mode through multi-agent system. And this paper findsthat properly supporting superior enterprises or high-quality projects and concentrating resources to stimulate innovation and transformation, are beneficial to improve the whole development level of the crowdfunding system without reducing the stability of the system operation.
Initial Thoughts on Cybersecurity And Reproducibility

Cybersecurity, which serves to protect computer systems and data from malicious and accidental abuse and changes, both supports and challenges the reproducibility of computational science. This position paper explores a research agenda by enumerating a set of two types of challenges that emerge at the intersection of cybersecurity and reproducibility: challenges that cybersecurity has in supporting the reproducibility of computational science, and challenges cybersecurity creates for reproducibility of computational science.
MAC: Measuring the Impacts of Anomalies on Travel Time of Multiple Transportation Systems

Urban anomalies have a large impact on passengers' travel behavior and city infrastructures, which can cause uncertainty on travel time estimation. Understanding the impact of urban anomalies on travel time is of great value for various applications such as urban planning, human mobility studies and navigation systems. Most existing studies on travel time have been focused on the total riding time between two locations on an individual transportation modality. However, passengers often take different modes of transportation, e.g., taxis, subways, buses or private vehicles, and a significant portion of the travel time is spent in the uncertain waiting. In this paper, we study the fine-grained travel time patterns in multiple transportation systems under the impact of urban anomalies. Specifically, (i) we investigate implicit components, including waiting and riding time, in multiple transportation systems; (ii) we measure the impact of real-world anomalies on travel time components; (iii) we design a learning-based model for travel time component prediction with anomalies. Different from existing studies, we implement and evaluate our measurement framework on multiple data sources including four city-scale transportation systems, which are (i) a 14-thousand taxicab network, (ii) a 13-thousand bus network, (iii) a 10-thousand private vehicle network, and (iv) an automatic fare collection system for a public transit network (i.e., subway and bus) with 5 million smart cards.
Device and Circuit Level Performance Analysis of a New Nanoscale DGJL MOSFET Design Using an Accurate Numerical Computation

This paper shows a new Double Gate Junctionless (DGJL) MOSFET design based on both highly doped drain/source extensions and gate material engineering. The device electrical behavior at the nanoscale level is investigated using an accurate numerical computation based on TCAD simulation provided by ATLAS 2D simulator, where quantum confinement effects and the modified drift-diffusion transport model that takes into account SCEs are included. Circuit performance parameters are also developed incorporating the impact of dual-material gate engineering and highly doped extension regions. The effect of the proposed design amendments on the performance of the common source single stage amplifier circuit based on DGJL MOSFET is also performed, where the proposed design exhibits an outstanding capability for offering improved amplifier properties. In order to analyze the characteristics and circuit performance of the device, we have adopted mixed mode simulation under Silvaco environment for the implementation of the inverter circuit. Based on the numerical, outcomes satisfactory results are recorded in comparison with the conventional nanoscale junctionless design.
Research on Interface Design of Air Conditioning Intelligent APP Based on User Experience

In order to improve the current air-conditioning APP interface, the function is simple and simple, the operation convenience is insufficient, and the interface is not beautiful. Through the research and analysis of user needs, the primary and secondary requirements are obtained, and the user experience is taken as the main consideration of APP interface design. At the same time, the intelligent and minimalist design principles are integrated into the interface design, and the prototype design of the interface is completed. According to the user's functional experience evaluation of the design prototype, perfect the design prototype and product development design, and finally test the product satisfaction. Overall user satisfaction increased from 72% to 81%. Conclusion The intelligent air conditioner APP basically meets the design requirements, especially the monitoring of energy consumption.
Analysis of Ant Colony Optimization on a Dynamically Changing Optical Burst Switched Network with Impairments

The ability of an Ant Colony Optimization (ACO) algorithm to adapt on a dynamical network is considered. A previous ACO implementation which was tested on a static Optical Burst Switched (OBS) network with impairments has been altered to be simulated on a dynamic network where network links are brought online or offline. The factors affecting the adaptability of an ACO algorithm is studied and a solution to mitigate some of these factors is proposed. This paper shows that the chosen Pheromone Function is the greatest factor affecting an ACO's adaptability during a change and that other factors such as topology and magnitude of change has little to no affect on its adaptability. In an attempt to improve the ACO's adaptability during a change in its network, a sliding window Pheromone Function is proposed and tested yielding positive results.