Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing traffic flow using quantum annealing and classical machine learning

Quantum annealing algorithms belong to the class of meta-heuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum processing units (QPUs) produced by D-Wave Systems [1], have been subject to multiple analyses in research, with the aim of characterizing the technology’s usefulness for optimization and sampling tasks [2–15]. In this paper, we present a real-world application that uses quantum technologies. Specifically, we show how to map certain parts of the realworld traffic flow optimization problem to be suitable for quantum annealing. We show that time-critical optimization tasks, such as continuous redistribution of position data for cars in dense road networks, are suitable candidates for quantum applications. Due to the limited size and connectivity of current-generation D-Wave QPUs, we use a hybrid quantum and classical approach to solve the traffic flow problem. ∗Corresponding author: florian.neukart@vw.com 1 ar X iv :1 70 8. 01 62 5v 1 [ qu an tph ] 4 A ug 2 01 7
A Comprehensive Methodology for Extracting Signal from Social Media Text Using Natural Language Processing and Machine Learning

There has been increasing interest in using data from social media, search engines, and other web sources for predictive analytics in many different domains. Although using these datasets in different context has shown significant promise, mounting evidence suggests that many of the results being produced could be misrepresented because of the loosely structured textual data and noise caused by anomalous media spikes and use of misleading terms and phases. We introduce a novel and efficient framework combining natural language processing (NLP) and machine learning classification techniques to extract signal from social media text. Our methodology was tested using two different large real world datasets from social media and resulted in an overall accuracy of 88% and high per-class precision and recall. The methodology described in this paper can be used for a variety of purposes to yield improved analyses of social media and web text with a view to enabling improved predictions.
A new simulated annealing algorithm for terminal allocation

In this paper, we focus on studying the capability of Simulated Annealing Arithmetic for optimizing the terminal allocation problems in communications network. They take advantage of the best characteristic of the two effective scheduling strategies Round Robin and Shortest Distance based on local information at the terminal in the communications network. The effectiveness of the Simulated Annealing Arithmetic, where some cooling strategies are used, is passed judgment by comparing system performance under different terminal allocation algorithms including Round Robin and Short Distance. Key-Words: Terminal Allocation; Simulated Annealing Arithmetic; Communications Network System
Designing an Interactive and Visual Environment for Term Paper Grading Support System in Higher Education

The author has already developed and evaluated a term paper grading assistance map. The map was designed to visualize scores graded for term papers assigned to a class at the university level or the equivalent. The map is a new visualization technique to show the amount of words and word use. This paper introduces prototype system of an assistance map using singular value decomposition technique for grading term papers and proposed five core ideas to improve that system's use.
SAT-Based Testing of Diagnosability and Predictability of Centralized and Distributed Discrete Event Systems

—In the general framework of safety analysis, diagnos-ability of a system, i.e., the guarantee to surely identify any fault in a ﬁnite delay after its occurrence, based on the available observations, is a key property to be veriﬁed at design stage. Diagnosability analysis of discrete event systems received a lot of attentions in the past twenty years, ﬁrstly in the centralized, then in the distributed case. In particular, a satisﬁability-based approach was proposed in 2007 in the centralized case. We extend in this work this approach to cover also distributed discrete event systems, by handling both observable and unobservable synchronous communication events at the same time. Then, we adapt the method to analyze, in both centralized and distributed cases, fault predictability, a stronger property than diagnosability, which guarantees that any fault can be correctly predicted before its occurrence, based on observations. We provide experimental results for both diagnosability and predictability.
VLSI block placement with directional graphs based on the new non-slicing representation

This paper describes a novel non-slicing floorplan representation. The designed representation of blocks differ from existing ones for low requirements allocated to the volume of the memory used. The time required to decode a representation, i.e. construction of its layout, is O(n). The described operations of conversion of the structure of a graph of representation is utilized in a genetic algorithm. The transparency of the geometrical relationships for the operations of conversion of the graph makes finding the final decision more effective.
A class-object model for program transformations

The recent expert programmers who have been forced to develop large and complicated programs have strong desire to write “good codes” from the viewpoints of both runtime efficiency and understandability, and they expect a translator to generate a good code just to fit their own needs if possible. This fitting usually requires complicated customization of the translator which could only be done by the experienced compiler experts, and the programmers cannot reflect their ideas on the translators so easily, especially when the programmer’s demands to the quality of practical programming tools are severe. These situations lead us to the necessity to develop a more flexible approach by which the specific programmers can reflect their experience and knowledge on the translators by themselves. The technology that enables the reuse of larger software components have become available with the emergence of the object-oriented paradigm, which have widened the applicability of reusable code pieces. However, the class-based objectoriented modularization cannot always encapsulate every design decisions perfectly; especially when they crosscut the module structure of a program, code pieces crosscutting a program tangle with other codes and scatter over the entire program; hence, class-based modularization is eventually violated. This kind of violation may happen modern network programming involving distribution or security issues. This thesis addresses how to solve these crosscutting problems without losing object-oriented framework’s appearance or runtime performance. To cope with both of these two problems, transformational system is to be used to embed the crosscutting code among the entire program automatically and hide the scattered code from the appearance. Runtime performance can be achieved so that the transformational approaches could inherently produce only the necessary and elaborate code based on the expert programmer’s experiences. For this purpose, we propose a class-object model for transforming object-oriented programs, and develop powerful transformational systems not only for compiler experts but also for object-oriented programming experts. The proposed class-object model is the abstract data model representing the logical structure of an object-oriented program and its logical alternations. In order to ease the description, the transforma-
Inverting recurrent neural networks for internal model control of nonlinear systems

In this paper, we show how a set of recently derived theoretical results for recurrent neural networks can be applied to the production of an internal model control system for a nonlinear plant. The results include determination of the relative order of a recurrent neural network and invertibility of such a network. A closed loop controller is produced without the need to retrain the neural network plant model. Stability of the closed-loop controller is also demonstrated.
A Frequency Analysis of Light Transport: from Theory to Implementation

The simulation of complex light effects such as depth-of-field, motion blur or scattering in participating media requires a tremendous amount of computation. But the resulting pictures are often blurry. We claim that those regions should be computed sparsely to reduce their cost. To do so, we propose a method covariance tracing that estimates the local variations of a signal. This method is based on a extended frequency analysis of light transport and permits to build efficient algorithms that distribute the cost of low frequency parts of the simulation of light transport. This thesis presents an improvement over the frequency analysis of local light-fields introduced by Durand et al. [2005]. We add into this analysis of light transport operations such as rough refractions, motion and participating media effects. We further improve the analysis of previously defined operations to handle non-planar occlusions of light, anisotropic BRDFs and multiple lenses. We present covariance tracing, a method to evaluate the covariance matrix of the local light-field spectrum on a per light-path basis. We show that covariance analysis is defined for all the defined Fourier operators. Furthermore, covariance analysis is compatible with Monte Carlo integration making it practical to study distributed effects. We show the use of covariance tracing with various applications ranging from motion blur and depth-of-field adaptive sampling and filtering, photon mapping kernel size estimation and adaptive sampling of volumetric effects.
Exploring the Nature of Order Generating Rules

Organization theorists have begun to draw on developments in complexity theory to redirect the literature on organizational transformation and strategic change towards notions of emergence. Useful contributions have been offered on the ways in which emergent order arises from the repeated application of simple sets of order generating rules in so called complex adaptive systems. This paper explores the nature of such (organizational) order generating rules and the ways in which they shape transformation processes. The authors adopt a mode 2 approach, operating at the interface of organization science and design methodology. First, a complexity based framework for organizational change is described, suggesting that transformation can be viewed as an emergent process, accessed and influenced through three interacting gateways – order generating rules, far-from-equilibrium conditions and feedback processes. This framework is used to examine two cases of organizational change. The paper then proceeds to compare these cases and theorize about the nature of rules. Finally, rules are considered in terms of how they arise as well as their objects, and a number of propositions for further research are suggested.
Design and Implementation of an Efficient and Scalable Software Distributed Shared Memory System

This thesis presents the design and implementation of our novel hybrid software DSM system. We call our system hybrid home-based EAC (HHEAC) since the system implements our novel exclusive access consistency model (EAC) based on the hybrid protocol of the homeless and home-based protocols. HHEAC guarantees only that shared variables inside a critical section are up to date before the accesses. Other shared variables outside a critical section are guaranteed to be up to date after the next barrier synchronisation. Our home-based DSM implementation is different from the previous implementations in that a home node does not receive any diffs from non-home nodes until the next barrier synchronisation. It is also different in that during a lock synchronisation required diffs are prefetched before the critical section, which reduces not only data traffic but also page faults inside the critical section. We also present a diff integration technique that can further unnecessary data traffic during lock synchronisation. This technique is especially effective in reducing data traffic for migratory applications. Finally, we develop a home migration technique that solves the wrong home assignment problem in the home-based protocol. Our technique is different from others in that an optimum home node is decided before updating a home node. To evaluate our system, we performed various experiments with well-known benchmark applications, including a novel parallel neural network application. The performance evaluation shows that HHEAC is more scalable than
Formal Description and Analysis of a Bounded Retransmission Protocol

This paper reports about the formal specification and verification of a Bounded Retransmission Protocol (BRP) used by Philips in one of its products. We started with the descriptions of the BRP service (i.e., external behaviour) and protocol written in the mu-CRL language by Groote and van de Pol. After translating them in the LOTOS language, we performed verifications by model-checking using the CADP (CAESAR/ALDEBARAN) toolbox. The models of the LOTOS descriptions were generated using the CAESAR compiler (by putting bounds on the data domains) and checked to be branching equivalent using the ALDEBARAN tool. Alternately, we formulated in the ACTL temporal logic a set of safety and liveness properties for the BRP protocol and checked them on the corresponding model using our XTL generic model-checker.
Automotive user interfaces for the support of non-driving-related activities

Driving a car has changed a lot since the first car was invented. Today, drivers do not only maneuver the car to their destination but also perform a multitude of additional activities in the car. This includes for instance activities related to assistive functions that are meant to increase driving safety and reduce the driver’s workload. However, since drivers spend a considerable amount of time in the car, they often want to perform non-driving-related activities as well. In particular, these activities are related to entertainment, communication, and productivity. The driver’s need for such activities has vastly increased, particularly due to the success of smart phones and other mobile devices. As long as the driver is in charge of performing the actual driving task, such activities can distract the driver and may result in severe accidents. Due to these special requirements of the driving environment, the driver ideally performs such activities by using appropriately designed in-vehicle systems. The challenge for such systems is to enable flexible and easily usable non-driving-related activities while maintaining and increasing driving safety at the same time. The main contribution of this thesis is a set of guidelines and exemplary concepts for automotive user interfaces that offer safe, diverse, and easy-to-use means to perform non-driving-related activities besides the regular driving tasks. Using empirical methods that are commonly used in human-computer interaction, we investigate various aspects of automotive user interfaces with the goal to support the design and development of future interfaces that facilitate non-driving-related activities. The first aspect is related to using physiological data in order to infer information about the driver’s workload. As a second aspect, we propose a multimodal interaction style to facilitate the interaction with multiple activities in the car. In addition, we introduce two concepts for the support of commonly used and demanded non-driving-related activities: For communication with the outside world, we investigate the driver’s needs with regard to sharing ride details with remote persons in order to increase driving safety. Finally, we present a concept of time-adjusted activities (e.g., entertainment and productivity) which enable the driver to make use of times where only little attention is required. Starting with manual, non-automated driving, we also consider the rise of automated driving modes.
A Framework of Hypergraph-Based Data Placement Among Geo-Distributed Datacenters

Data-intensive applications need to address the problem of properly placing the set of data items in geo-distributed storage nodes. Traditional techniques use the hashing method to achieve the load balance among nodes such as those used in Hadoop and Cassandra, but are not efficient for the requests reading multiple data items in one transaction, especially when the source locations of requests are also distributed. Some recent papers proposed the managed data placement schemes for online social networks, but have a limited scope of applications due to their focuses. We propose a general hypergraph-based data placement framework, which considers both the performance metrics related to the co-location of associated data and those related to the exact location of fulfilling each requested data item. In the framework, we present the methods to convert the optimization objectives into hypergraph models and employ a hypergraph partitioning to efficiently partition the set of data items and place them in distributed nodes. Further, we extend the scheme into replica placement where we need to find multiple locations to place the replicas of the same data item. Through extensive experiments based on trace-based datasets, we evaluate the performance of the proposed framework and demonstrate its effectiveness.
Information distribution systems and information distribution method

Providing a three dimensional variable information distribution server comprising: attribute information of the main storage device attribute information storing three-dimensional variable; backbone main storage means (backbone) is a variable storing a fixed portion; parameter master storage device for storing parameters; login attribute information and management the attribute information management means; a logged variable backbone backbone registration device; variable parameter registration device registration parameter; generating a main storage device and the reference parameter skeleton master storage device and provide a means to provide variable three variables. Thus, according to the present invention can be easily changed to provide information distribution system of the three-dimensional data variables.
Impact of Scheduling and Buffer Sizing on TCP Performance over IMT-Advanced

IMT-Advanced is gaining much attention as the next-generation mobile communication technology. In this study, we evaluate the TCP throughput performance of mobile users competing on an IMT-Advanced shared downlink via a network simulation by using realistic environmental parameters. Our focus is on evaluating the impact of two basic types of timefrequency scheduling in which not only a time-varying wireless condition is used but also a frequency-block-dependent wireless condition of each user is exploited using various buffer sizes at radio base stations and various user moving speeds. We investigated the subtle tension between the scheduling, buffer sizing, and user moving speed for the TCP throughput. Our results imply that more TCP awareness is necessary for sharing the large bandwidth of IMT-Advanced downlinks more efficiently. Keywords-IMT-Advanced, TCP throughput, MaxCIR scheduler, Proportional Fair scheduler
Informed Anytime Search for Continuous Planning Problems

Informed Anytime Search for Continuous Planning Problems Jonathan D. Gammell Doctor of Philosophy Graduate Department of Aerospace Science and Engineering University of Toronto 2017 Navigating uncontrolled dynamic environments is a major challenge in robotics. Success requires solving many different technical problems and path planning is a key component of most autonomous solutions. Path planning is the task of finding a path through the environment that allows a robot to reach its desired position. This path must avoid obstacles and be executable by the robot while often also reducing a specified cost (e.g., path length). The difficulty of meeting these requirements reliably and quickly in continuous state spaces has made path planning an active area of research in robotics. Two popular path planning approaches are informed graph-based search and anytime sampling-based planning. Informed graph-based searches, such as A*, are efficient but use a priori approximations of the problem domain. If these approximations are chosen incorrectly, then the algorithms may be unable to find a (suitable) solution or take a prohibitively long time to do so. Anytime sampling-based planners, such as RRT*, continuously improve their approximations of the problem domain but perform inefficient searches. These searches simultaneously search the entire problem domain and can become prohibitively expensive in large or high-dimensional planning problems, such as when planning for high-DOF manipulation arms. This thesis demonstrates how planning in continuous planning problems can be improved by unifying the informed graph-based search and anytime sampling-based planning approaches. It investigates various ways to use heuristics to focus and order the search of almost-surely asymptotically optimal sampling-based planners. The theoretical and experimental advantages of this informed anytime sampling-based search are demonstrated through the planning algorithms, Informed RRT*, Batch Informed Trees (BIT*), and Sorted RRT* (SORRT*).
Computing models for networks of tiny objects

In this work, we consider computing models for networks of tiny objects suchas wireless sensor networks. We focus on the population protocols, a pairwise computationalmodel introduced by Angluin et al. where the tiny objects are represented byanonymous, passively mobile, finite state agents forming asynchronous networks. Weestablish two comparative studies between the population protocol model (and its extensions)and the two following ones: tasks with graph relabeling systems, and anonymousasynchronous message passing. These studies aim to establish possible mappings betweenthe population protocols and these two models. We then focus on the scheduling of thepairwise interactions in population protocols. We propose the HS Scheduler, a new probabilistic1-central scheduler based on randomized handshakes. Compared to the existingschedulers, this scheduler allows to more than one pair of agents to communicate simultaneously.We prove that this scheduler is fair with probability 1. We thereafter presentanalyses of the complexity of the stabilization time of some protocols running under thescheduling of the Random Scheduler and the HS Scheduler, and over different topologiesof the interaction graph. We prove that these two schedulers are time equivalent withComputing Models for Networks of Tiny Objects iiirespect to these protocols when the interaction graph is complete, however computationsunder the HS Scheduler stabilize faster when the interaction graph is random. We then introducethe Protocol Aware HS Scheduler, a slightly modifed version of the HS Schedulerthat takes into account the states of the agents and allows termination in some protocols.We also prove that this scheduler is fair with probability 1. We present analyses of thetime complexity of some protocols running under the scheduling of the Protocol AwareHS Scheduler and over dfferent structures of the interaction graph. We implement thedifferent scenarios in ViSiDiA, and validate through simulations our theoretical results.