OpenRaiser/Intern-Atlas huggingface dataset:
Building Airflow Monitoring and Control using Wireless Sensor Networks for Smart Grid Application
Venue: arXiv cs.SY 2016
Year: 2016

The electricity grid is crucial to our lives. House- holds and institutions count on it. In recent years, the sources of energy have become less and less available and they are driving the price of electricity higher and higher. It has been estimated that 40% of power is spent in residential and institutional buildings. Most of this power is absorbed by space cooling and heating. In modern buildings, the HVAC (heating, ventilation, and air conditioning) system is centralised and operated by a department usually called the central plant. The central plant produces chilled water and steam that is then consumed by the building AHUs (Air Handling Units) to maintain the buildings at a comfortable temperature. However, the heating and cooling model does not take into account human occupancy. The AHU within the building distributes air according to the design parameters of the building ignoring the occupancy. As a matter of fact, there is a potential for optimization lowering consumption to utilize energy efficiently and also to be able to adapt to the changing cost of energy in a micro-grid environment. This system makes it possible to reduce the consumption when needed minimizing impact on the consumer. In this study, we will show, through a set of studies conducted at the University of Houston, that there is a potential for energy conservation and efficiency in both the buildings and the central plant. We also present a strategy that can be undertaken to meet this goal. This strategy, airflow monitoring and control, is tested in a software simulation and the results are presented. This system enables the user to control and monitor the temperature in the individual rooms according the locals needs.
Curating Transient Population in Urban Dynamics System
Venue: arXiv cs.SI 2016
Year: 2016

For past several decades, research efforts in population modelling has proven its efficacy in understanding the basic information about residential and commercial areas, as well as for the purposes of planning, development and improvement of the community as an eco-system. More or less, such efforts assume static nature of population distribution, in turn limited by the current ability to capture the dynamics of population change at a finer resolution of space and time. Fast forward today, more and more people are becoming mobile, traveling across borders impacting the nuts and bolts of our urban fabric. Unfortunately, our current efforts are being surpassed by the need to capture such transient population. It is becoming imperative to identify and define them, as well as measure their dynamics and interconnectedness. In this work, we intend to research urban population mobility patterns, gauge their transient nature, and extend our knowledge of their visited locations. We plan to achieve this by designing and developing novel methods and using VGI data that models and characterizes transient population dynamics.
Phase diagram of matrix compressed sensing
Venue: arXiv cs.IT 2016
Year: 2016

In the problem of matrix compressed sensing we aim to recover a low-rank matrix from few of its element-wise linear projections. In this contribution we analyze the asymptotic performance of a Bayes-optimal inference procedure for a model where the matrix to be recovered is a product of random matrices. The results that we obtain using the replica method describe the state evolution of the recently introduced P-BiG-AMP algorithm. We show the existence of different types of phase transitions, their implications for the solvability of the problem, and we compare the results of the theoretical analysis to the performance reached by P-BiG-AMP. Remarkably the asymptotic replica equations for matrix compressed sensing are the same as those for a related but formally different problem of matrix factorization.
A Local Density-Based Approach for Local Outlier Detection
Venue: arXiv cs.AI 2016
Year: 2016

This paper presents a simple but effective density-based outlier detection approach with the local kernel density estimation (KDE). A Relative Density-based Outlier Score (RDOS) is introduced to measure the local outlierness of objects, in which the density distribution at the location of an object is estimated with a local KDE method based on extended nearest neighbors of the object. Instead of using only $k$ nearest neighbors, we further consider reverse nearest neighbors and shared nearest neighbors of an object for density distribution estimation. Some theoretical properties of the proposed RDOS including its expected value and false alarm probability are derived. A comprehensive experimental study on both synthetic and real-life data sets demonstrates that our approach is more effective than state-of-the-art outlier detection methods.
Subspace Estimation and Decomposition for Hybrid Analog-Digital Millimetre-Wave MIMO systems
Venue: arXiv cs.IT 2016
Year: 2016

In this work, we address the problem of channel estimation and precoding / combining for the so-called hybrid millimeter wave (mmWave) MIMO architecture. Our proposed channel estimation scheme exploits channel reciprocity in TDD MIMO systems, by using echoing, thereby allowing us to implement Krylov subspace methods in a fully distributed way. The latter results in estimating the right (resp. left) singular subspace of the channel at the transmitter (resp. receiver). Moreover, we also tackle the problem of subspace decomposition whereby the estimated right (resp. left) singular subspaces are approximated by a cascade of analog and digital precoder (resp. combiner), using an iterative method. Finally we compare our scheme with an equivalent fully digital case and conclude that a relatively similar performance can be achieved, however, with a drastically reduced number of RF chains - 4 ~ 8 times less (i.e., massive savings in cost and power consumption).
Iterative Partial Rounding for Vertex Cover with Hard Capacities
Venue: arXiv cs.DS 2016
Year: 2016

We provide a simple and novel algorithmic design technique, for which we call iterative partial rounding, that gives a tight rounding-based approximation for vertex cover with hard capacities (VC-HC). In particular, we obtain an $f$-approximation for VC-HC on hypergraphs, improving over a previous results of Cheung et al (SODA 2014) to the tight extent. This also closes the gap of approximation since it was posted by Chuzhoy and Naor in (FOCS 2002). We believe that our rounding technique is of independence interests when hard constraints are considered. Our main technical tool for establishing the approximation guarantee is a separation lemma that certifies the existence of a strong partition for solutions that are basic feasible in an extended version of the natural LP.
A Dissipative Systems Theory for FDTD with Application to Stability Analysis and Subgridding
Venue: arXiv cs.CE 2016
Year: 2016

This paper establishes a far-reaching connection between the Finite-Difference Time-Domain method (FDTD) and the theory of dissipative systems. The FDTD equations for a rectangular region are written as a dynamical system having the magnetic and electric fields on the boundary as inputs and outputs. Suitable expressions for the energy stored in the region and the energy absorbed from the boundaries are introduced, and used to show that the FDTD system is dissipative under a generalized Courant-Friedrichs-Lewy condition. Based on the concept of dissipation, a powerful theoretical framework to investigate the stability of FDTD methods is devised. The new method makes FDTD stability proofs simpler, more intuitive, and modular. Stability conditions can indeed be given on the individual components (e.g. boundary conditions, meshes, embedded models) instead of the whole coupled setup. As an example of application, we derive a new subgridding method with material traverse, arbitrary grid refinement, and guaranteed stability. The method is easy to implement and has a straightforward stability proof. Numerical results confirm its stability, low reflections, and ability to handle material traverse.
Undecidable Cases of Model Checking Probabilistic Temporal-Epistemic Logic (Extended Abstract)
Venue: arXiv cs.LO 2016
Year: 2016

We investigate the decidability of model-checking logics of time, knowledge and probability, with respect to two epistemic semantics: the clock and synchronous perfect recall semantics in partially observed discrete-time Markov chains. Decidability results are known for certain restricted logics with respect to these semantics, subject to a variety of restrictions that are either unexplained or involve a longstanding unsolved mathematical problem. We show that mild generalizations of the known decidable cases suffice to render the model checking problem definitively undecidable. In particular, for a synchronous perfect recall, a generalization from temporal operators with finite reach to operators with infinite reach renders model checking undecidable. The case of the clock semantics is closely related to a monadic second order logic of time and probability that is known to be decidable, except on a set of measure zero. We show that two distinct extensions of this logic make model checking undecidable. One of these involves polynomial combinations of probability terms, the other involves monadic second order quantification into the scope of probability operators. These results explain some of the restrictions in previous work.
PRESAGE: Protecting Structured Address Generation against Soft Errors
Venue: arXiv cs.SE 2016
Year: 2016

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any address computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.
A new trace bilinear form on cyclic $\mathbb{F}_q$-linear $\mathbb{F}_{q^t}$-codes
Venue: arXiv cs.IT 2016
Year: 2016

Let $\mathbb{F}_q$ be a finite field of cardinality $q$, where $q$ is a power of a prime number $p$, $t\geq 2$ an even number satisfying $t \not\equiv 1 \;(\bmod \;p)$ and $\mathbb{F}_{q^t}$ an extension field of $\mathbb{F}_q$ with degree $t$. First, a new trace bilinear form on $\mathbb{F}_{q^t}^n$ which is called $Δ$-bilinear form is given, where $n$ is a positive integer coprime to $q$. Then according to this new trace bilinear form, bases and enumeration of cyclic $Δ$-self-orthogonal and cyclic $Δ$-self-dual $\mathbb{F}_q$-linear $\mathbb{F}_{q^t}$-codes are investigated when $t=2$. Furthermore, some good $\mathbb{F}_q$-linear $\mathbb{F}_{q^2}$-codes are obtained.
How many subsets of edges of a directed multigraph can be represented as trails?
Venue: arXiv cs.DM 2016
Year: 2016

For each subset of edges of a (directed multi-) graph, one may determine whether the edges can be represented as a trail. I prove that the fraction trail-representable subsets of edges is at most $O(\sqrt{\log m}/\sqrt{m})$, where $m$ is the number of edges, and show by example that the upper bound is nearly tight.
A spectral-spatial fusion model for robust blood pulse waveform extraction in photoplethysmographic imaging
Venue: arXiv cs.CV 2016
Year: 2016

Photoplethysmographic imaging is a camera-based solution for non-contact cardiovascular monitoring from a distance. This technology enables monitoring in situations where contact-based devices may be problematic or infeasible, such as ambulatory, sleep, and multi-individual monitoring. However, extracting the blood pulse waveform signal is challenging due to the unknown mixture of relevant (pulsatile) and irrelevant pixels in the scene. Here, we design and implement a signal fusion framework, FusionPPG, for extracting a blood pulse waveform signal with strong temporal fidelity from a scene without requiring anatomical priors (e.g., facial tracking). The extraction problem is posed as a Bayesian least squares fusion problem, and solved using a novel probabilistic pulsatility model that incorporates both physiologically derived spectral and spatial waveform priors to identify pulsatility characteristics in the scene. Experimental results show statistically significantly improvements compared to the FaceMeanPPG method ($p<0.001$) and DistancePPG ($p<0.001$) methods. Heart rates predicted using FusionPPG correlated strongly with ground truth measurements ($r^2=0.9952$). FusionPPG was the only method able to assess cardiac arrhythmia via temporal analysis.
Simulation Results on Selector Adaptation in Behavior Trees
Venue: arXiv cs.RO 2016
Year: 2016

Behavior trees (BTs) emerged from video game development as a graphical language for modeling intelligent agent behavior. However as initially implemented, behavior trees are static plans. This paper adds to recent literature exploring the ability of BTs to adapt to their success or failure in achieving tasks. The "Selector" node of a BT tries alternative strategies (its children) and returns success only if all of its children return failure. This paper studies several means by which Selector nodes can learn from experience, in particular, learn conditional probabilities of success based on sensor information, and modify the execution order based on the learned iformation. Furthermore, a "Greedy Selector" is studied which only tries the child having the highest success probability. Simulation results indicate significantly increased task performance, especially when frequentist probability estimate is conditioned on sensor information. The Greedy selector was ineffective unless it was preceded by a period of training in which all children were exercised.
Penambahan emosi menggunakan metode manipulasi prosodi untuk sistem text to speech bahasa Indonesia
Venue: arXiv cs.SD 2016
Year: 2016

Adding an emotions using prosody manipulation method for Indonesian text to speech system. Text To Speech (TTS) is a system that can convert text in one language into speech, accordance with the reading of the text in the language used. The focus of this research is a natural sounding concept, the make "humanize" for the pronunciation of voice synthesis system Text To Speech. Humans have emotions / intonation that may affect the sound produced. The main requirement for the system used Text To Speech in this research is eSpeak, the database MBROLA using id1, Human Speech Corpus database from a website that summarizes the words with the highest frequency (Most Common Words) used in a country. And there are 3 types of emotional / intonation designed base. There is a happy, angry and sad emotion. Method for develop the emotional filter is manipulate the relevant features of prosody (especially pitch and duration value) using a predetermined rate factor that has been established by analyzing the differences between the standard output Text To Speech and voice recording with emotional prosody / a particular intonation. The test results for the perception tests of Human Speech Corpus for happy emotion is 95 %, 96.25 % for angry emotion and 98.75 % for sad emotions. For perception test system carried by intelligibility and naturalness test. Intelligibility test for the accuracy of sound with the original sentence is 93.3%, and for clarity rate for each sentence is 62.8%. For naturalness, accuracy emotional election amounted to 75.6 % for happy emotion, 73.3 % for angry emotion, and 60 % for sad emotions. ----- Text To Speech (TTS) merupakan suatu sistem yang dapat mengonversi teks dalam format suatu bahasa menjadi ucapan sesuai dengan pembacaan teks dalam bahasa yang digunakan.
Compression of Neural Machine Translation Models via Pruning
Venue: arXiv cs.AI 2016
Year: 2016

Neural Machine Translation (NMT), like many other deep learning domains, typically suffers from over-parameterization, resulting in large storage sizes. This paper examines three simple magnitude-based pruning schemes to compress NMT models, namely class-blind, class-uniform, and class-distribution, which differ in terms of how pruning thresholds are computed for the different classes of weights in the NMT architecture. We demonstrate the efficacy of weight pruning as a compression technique for a state-of-the-art NMT system. We show that an NMT model with over 200 million parameters can be pruned by 40% with very little performance loss as measured on the WMT'14 English-German translation task. This sheds light on the distribution of redundancy in the NMT architecture. Our main result is that with retraining, we can recover and even surpass the original performance with an 80%-pruned model.
A Harmonic Potential Approach For Simultaneous Planning And Control Of A Generic UAV Platform
Venue: arXiv cs.RO 2016
Year: 2016

Simultaneous planning and control of a large variety of unmanned aerial vehicles (UAVs) is tackled using the harmonic potential field (HPF) approach. A dense reference velocity field generated from the gradient of an HPF is used to regulate the velocity of the UAV concerned in a manner that would propel the UAV to a target point while enforcing the constraints on behavior that were a priori encoded in the reference field. The regulation process is carried-out using a novel and simple concept called the: virtual velocity attractor (VVA). The combined effect of the HPF gradient and the VVA is found able to yield an efficient, easy to implement, well-behaved and provably-correct context-sensitive control action that suits a wide variety of UAVs. The approach is developed and basic proofs of correctness are provided along with simulation results.
Probabilistic Construction and Analysis of Seminormalized Hadamard Matrices
Venue: arXiv cs.DM 2016
Year: 2016

Let o be a 4k-length column vector whose all entries are 1s, with k a positive integer. Let V={v_i} be a set of semi-normalized Hadamard (SH)-vectors, which are 4k-length vectors whose 2k entries are -1s and the remaining 2k are 1s. We define a 4k-order QSH (Quasi SH)-matrix, Q, as a 4kx4k matrix where the first column is o and the remaining ones are distinct v_i in V. When Q is orthogonal, it becomes an SH-matrix H. Therefore, 4k-order SH-matrices can be built by enumerate all possible Q from every combination of v_i, then evaluate the orthogonality of each one of them. Since such exhaustive method requires a large amount of computing resource, we can employ probabilistic algorithms to construct H, such as, by Random Vector Selection (RVS) or the Orthogonalization by Simulated Annealing (OSA) algorithms. We demonstrate the constructions of low-order SH-matrices by using these methods. We also analyze some probabilistic aspects of the constructions, including orthogonal probability p between a pair of randomly selected SH-vectors, the existence probability p_H|Q that a randomly generated Q is in fact an SH-matrix H, and address the discrepancy of the distribution between the known number of SH-matrix with expected number derived from the probabilistic analysis.
On Approximate Dynamic Programming with Multivariate Splines for Adaptive Control
Venue: arXiv cs.LG 2016
Year: 2016

We define a SDP framework based on the RLSTD algorithm and multivariate simplex B-splines. We introduce a local forget factor capable of preserving the continuity of the simplex splines. This local forget factor is integrated with the RLSTD algorithm, resulting in a modified RLSTD algorithm that is capable of tracking time-varying systems. We present the results of two numerical experiments, one validating SDP and comparing it with NDP and another to show the advantages of the modified RLSTD algorithm over the original. While SDP requires more computations per time-step, the experiment shows that for the same amount of function approximator parameters, there is an increase in performance in terms of stability and learning rate compared to NDP. The second experiment shows that SDP in combination with the modified RLSTD algorithm allows for faster recovery compared to the original RLSTD algorithm when system parameters are altered, paving the way for an adaptive high-performance non-linear control method.
Coalgebraic Trace Semantics for Buechi and Parity Automata
Venue: arXiv cs.LO 2016
Year: 2016

Despite its success in producing numerous general results on state-based dynamics, the theory of coalgebra has struggled to accommodate the Buechi acceptance condition---a basic notion in the theory of automata for infinite words or trees. In this paper we present a clean answer to the question that builds on the "maximality" characterization of infinite traces (by Jacobs and Cirstea): the accepted language of a Buechi automaton is characterized by two commuting diagrams, one for a least homomorphism and the other for a greatest, much like in a system of (least and greatest) fixed-point equations. This characterization works uniformly for the nondeterministic branching and the probabilistic one; and for words and trees alike. We present our results in terms of the parity acceptance condition that generalizes Buechi's.
Probabilistic Reasoning in the Description Logic ALCP with the Principle of Maximum Entropy (Full Version)
Venue: arXiv cs.AI 2016
Year: 2016

A central question for knowledge representation is how to encode and handle uncertain knowledge adequately. We introduce the probabilistic description logic ALCP that is designed for representing context-dependent knowledge, where the actual context taking place is uncertain. ALCP allows the expression of logical dependencies on the domain and probabilistic dependencies on the possible contexts. In order to draw probabilistic conclusions, we employ the principle of maximum entropy. We provide reasoning algorithms for this logic, and show that it satisfies several desirable properties of probabilistic logics.
Modeling and Predicting DNS Server Load
Venue: arXiv cs.PF 2016
Year: 2016

The DNS relies on caching to ensure high scalability and good performance. In optimizing caching, TTL adjustment provides a means of balancing between query load and TTL-dependent performances such as data consistency, load balancing, migration time, etc. To gain the desired balance, TTL adjustment depends on predictions of query loads under alternative TTLs. This paper proposes a model of DNS server load, which employs the uniform aggregate caching model to simplify the complexity of modeling clients' requests and their caching. A method of predicting DNS server load is developed using that model. The prediction method is solely based on the unilateral measurements or observations at authoritative servers. Without reliance on lots of multi-point measurements nor distributed measuring facilities, the method is best suited for DNS authoritative operators. The proposed model and prediction method are validated through extensive simulations. Finally, global sensibility analysis is conducted to evaluate the impacts of measurement uncertainties or errors on the predictions.