Miracle-dz/UniFAR-FTUs huggingface dataset:
TITLE of the PROJECT : Binaural cues and spatial hearing in ecological environments

Spatial hearing underlies our ability to localize sound sources in our environment, and to listen in noisy conditions (the “cocktail party effect”), which are both degraded by hearing loss. This project addresses fundamental aspects of our understanding of spatial hearing in humans, by focusing on the analysis of ecological situations. Indeed, for methodological reasons, research on spatial hearing has focused largely on simplified experimental configurations, for example by considering point sources and by suppressing reflections on the ground. Contextual elements such as source width and ground reflections strongly affect the performance of leading models of sound localization, but the significance of this fact is difficult to assess because relatively little is known on human performance in ecological situations. This project aims at filling this gap by empirically measuring the distribution of binaural cues and human sound localization performance in ecological situations, in particular by including aspects that have been little explored, such as physical sound sources (vibrating objects as opposed to sounds played on speakers) and reflective grounds (grass, pavement). Thus, we propose to analyze the acoustical properties of natural hearing environments, and the influence of these properties on spatial hearing. This analysis will allow us to interpret the large body of experimental results in binaural psychophysics in an ecological context. The specific aims are: a) to measure binaural cues with physical sources (objects, as opposed to point sources) in ecological conditions (free field with natural surfaces, e.g. grass), and in particular to empirically estimate the distribution of binaural cues for a given source location; b) to measure human localization performance in ecological situations, and in particular to measure the sensitivity to various aspects of the ecological context (e.g. nature of the ground). c) to understand how much of human binaural psychophysics can be explained by natural statistics of binaural sounds (using Bayesian models), as opposed to specific physiological mechanisms and constraints (e.g. limits of phase locking of the auditory nerve). By investigating the aspects of binaural hearing that are critical in ecologically relevant situations, the project is expected to provide crucial information for the design of auditory prostheses and implants.
Optimizing Complex Interaction Dynamics in Critical Infrastructure with a Stochastic Kinetic Model

Emerging data that track the dynamics of large populations bring new potential for understanding human decision-making in a complex world and supporting better decision-making through the integration of continued partial observations about dynamics. However, existing models have difficulty with capturing the complex, diverse, evolving, and partially unknown dynamics in social networks, and with inferring system state from isolated observations about a tiny fraction of the individuals in the system. To solve real-world problems with a huge number of agents and system states and complicated agent interactions, we propose a stochastic kinetic model that captures complex decision-making and system dynamics using atomic events that are individually simple but together exhibit complex behaviors. As an example, we show how this model offers significantly better results for city-scale multi-objective driver route planning in significantly less time than models based on deep neural networks or co-evolution.
Controller Design Base on Servo State Feedback for Two-wheeled Balancing Robot

Abstract This paper presents the controller design for the two-wheeled balancing robot system. The proportionalderivative (PD) controller was designed to compare the performance with servo state feedback controller designed by pole placement technique. Both controllers are used to stabilize the two-wheeled balancing robot system. Simulation results show that servo state feedback design can stabilize the balancing robot. Moreover, the presence of its large deviation angle is also better than PD controller.
Matching of Meta-Expressions with Recursive Bindings

We focus automated reasoning on program calculi with reduction semantics (see e.g. [8]), in particular, lambda-calculi with call-by-need evaluation and letrec-expressions (consisting of a set of recursive bindings and a body to reference the bindings) modelling the core of lazy functional programming languages like Haskell (see [1, 6]). The meta-language LRSX [5] is designed for this purpose. It uses higher-order function symbols (as they also occur in approaches using higher-order abstract syntax [3]), has a letrec-construct letr, meta-variables for environments, expressions, variables and contexts. Its syntax (see Fig. 1) is parametrized over context classes K and (higher-order) function symbols F . A ground LRSX-expression (an LRS-expression) does not contain any meta-variable. Contexts are expressions with a hole [·] : HExpr. The semantics of meta-variables is straight-forward except for chain-variables Ch where Ch[x, s] of class K stands for x.d[s] or chains x.d1[(var x1)]; x1.d2[(var x2)]; . ; xn.dn[s] with fresh variables xi, and contexts d, di from the class K. As a motivation for chain-variables, consider the reduction rule letr x1=A1[x2], . , xn−1=An[xn], xn=(λy.s0) s1 in A [x1] → letr x1=A1[x2], . , xn−1=An[xn], xn=(letr y=s1 in s0) in A [x1]. It performs β-reduction with sharing at a needed position (where A,Ai are evaluation contexts) which is expressed by the informal notion x1=A1[x2], . , xn−1=An[xn] for a chain of bindings of arbitrary length. In LRSX the left hand side of the rule can be represented as letrE; Ch[X1, app (λY.S0)S1] inA[varX1] where Ch is a chain-variable of class A. The example also shows that the meta-syntax requires a notion of contexts and context classes. The rule letr E1 in letr E2 in s→ letr E1, E2 in s joins two nested letrec-environments. The rule requires that scoping is respected, i.e. let-bindings of E2 must not capture variables in E1. That is why we use so-called constrained expressions:
Efficiency of mass privatization vs. gradual privatization: Owner and seller effects on performance of companies in Slovenia

According to the recent World Bank comprehensive report on lessons learnt in the first ten years of economic transition from plan to market, the ideal privatization strategy is to transfer assets as rapidly as possible to concentrated owners through open, fair and transparent methods. However, the report admits that is difficult to achieve on a large scale in a short period as the privatization to diffuse owners and insiders is appealing on equity grounds, and in several countries this was the only way to make private ownership politically acceptable. The main issue then is whether these intermediate ways of privatization accelerate or retard the eventual takeover of the enterprise by the “right” kind of investors. Might it not have been preferable to keep the assets in state hands, waiting to identify and than sell the enterprises to viable strategic investors? The World Bank report goes further by saying “Navigating between continued state ownership with eroding control rights and a transfer to ineffective new private owners with an inadequate institutional framework is possibly one of the most difficult challenges confronting policymakers in charge of privatization. ”
Wind Energy , Transmission , and Production Costs : Does Increased Connectivity Help All ? ∗

We empirically examine the geographic variation in economic impacts of a significant electricity transmission capacity expansion project, the CREZ project in Texas, on the value of wind generation. Importantly, we extend the scope of canonical two-region trade models in economic theory onto multiple regions. We show that while, as predicted, the two regions directly affected by the expansion, the West and North zones, experience overall falling production costs and gains from trade, the marginal value of wind generation in the Houston zone declines post-CREZ. These effects are such that, across the region as a whole, the marginal value of wind with respect to production costs remains effectively the same before and after CREZ. Additionally, using machine learning classification techniques, we demonstrate that wind generation actually increases the likelihood of relatively higher prices in the Houston zone. These counter-intuitive generation cost and pricing patterns appear to be driven by changing power trade patterns and dynamic production constraints of thermal generators.
Strong Authentication without Tamper-Resistant Hardware and Application to Federated Identities

—Shared credential is currently the most widespread form of end user authentication with its convenience, but it is also criticized for being vulnerable to credential database theft and phishing attacks. While several alternative mechanisms are proposed to offer strong authentication with cryptographic challenge-response protocols, they are cumbersome to use due to the need of tamper-resistant hardware modules at user end. In this paper, we propose the ﬁrst strong authentication mechanism without the reliance on tamper-resistant hardware at user end. A user authenticates with a password-based credential via generating designated-veriﬁable authentication tokens. Our scheme is resistant to ofﬂine dictionary attacks in spite that the attacker can steal the password-protected credentials, and thus can be implemented on general-purpose devices. More speciﬁcally, we ﬁrst introduce and formalize the notion of Password-Based Credential (PBC), which models the resistance of ofﬂine attacks and the unforageability of authentication tokens even if attackers can see authentication tokens and capture password-wrapped credentials of honest users. We then present a highly-efﬁcient construction of PBC using a “randomize-then-prove” approach, and prove its security. The construction does not involve bilinear-pairings, and can be implemented with common cryptographic libraries for many platforms. We also present a technique to transform the PBC scheme to be publicly-veriﬁable, and present an application of PBC in federated identity systems to provide holder-of-key assertion mechanisms. Compared with current certiﬁcate-based approaches, it is more convenient and user-friendly, and can be used with the federation systems that employ privacy-preserving measures (e.g., Sign-in with Apple). We also implement the
SPATIO-TEMPORAL SEARCH LOG ANALYSIS

This work relates to the field of search log analysis. Applications for performing this type of analysis are rare, their development details, source code and documentation are not made available to the research community and they are restricted to work only with specific search logs. Having acknowledged this limitation and identified the existence of this gap in this field of research, this work has had the objective of planning, designing, developing and testing an open-source web application that is adaptable and capable of performing useful and relevant spatio-temporal analysis for a multitude of different search logs. It includes a number of innovative features as well as a combination of characteristics found in existing tools such as Google Trends and Google Zeitgeist but, unlike these, it is not restricted to a specific log. The application provides mechanisms to deliver information from different perspectives. It provides several overall log statistical measures as well as a set of custom perspectives created by a combination of three independent filters: the query level, the time period level and the location level.
Theory Development Via Replicated Simulations and the Added Value of Standards

: Using the agent-based model of Miller et al. (2012), which depicts how different types of individuals’ memory affect the formation and performance of organizational routines, we show how a replicated simulation model can be used to develop theory. We also assess how standards, such as the ODD (Overview, Design concepts, and Details) protocol and DOE (design of experiments) principles, support the replication, evalua-tion, and further analysis of this model. Using the verified model, we conduct several simulation experiments as examples of different types of theory development. First, we show how previous theoretical insights can be generalized by investigating additional scenarios, such as mergers. Second, we show the potential of replicated simulation models for theory refinement, such as analyzing in-depth the relationship between memory functions and routine performance or routine adaptation. of ( 50). The results show that are involved in the problem-solving though the This offers
Understanding and Improving Fully Autonomous Aerial Systems

Fully autonomous aerial systems (FAAS) ﬂy complex missions guided wholly by software. They are cheaper and safer than unmanned aerial systems piloted by humans; however, compute hardware and software settings affect where FAAS ﬂy and how quickly they complete missions. Poor choices slow down missions and use hardware inefﬁciently, increasing costs. This paper presents a model-driven approach to manage FAAS missions. We ﬂy real FAAS missions, pro-ﬁle compute and aircraft resource usage and model expected demands. However, proﬁling numerous hardware and software settings also inﬂates costs. We propose autonomy cubes: data structures that characterize whole ﬂight areas for FAAS missions. With autonomy cubes, we can proﬁle resource usage across settings without repeatedly ﬂying missions. We combine expected resource demands to model missions completed, i.e., mission throughput. We validated our model by creating FAAS, measuring mission throughput across many system settings and comparing to our model predictions. Our FAAS benchmarks execute realistic missions: autonomous photography, search and rescue, and agricultural scouting. And they use well-known software, e.g., A* Search and DJI ﬂight control. Our model predicted throughput with 4% error across mission, software and hardware settings. Competing approaches yielded 10–24% error. We used our model to study (1) GPU acceleration, scale up, and scale out, (2) onboard, edge and cloud computing, (3) energy and monetary budgets, and (4) software driven GPU management. We found that model-driven management can boost mission throughput by 10X and reduce costs by 87%.
Unsupervised software repositories mining and its application to code search

Software repositories are crucial resources for many software tasks, including code retrieval and annotation. Programming forums provide questions and answers (Q&A) from software developers, containing abundant code‐description posts for exchanging knowledge about programming issues. However, most posts provide personal opinions of users that are often not adequately confirmed or outdated. Mining software repositories in such open and unrestricted forums is challenging. Since the posts can be arbitrary and noisy, it is difficult to get unified labels for supervised noise elimination. Different from existing mining approaches, this paper proposes Code‐Description Mining Framework (CodeMF), an unsupervised framework to eliminate noisy posts and extract high quality software repositories from programming forums. CodeMF treats all social features of the posts as discrete‐time signals for kernel principal component analysis and further performs wavelet transform feature fusion to find the delicate changes (noises in temporal signals). We conduct comprehensive experiments on StackOverflow. Experimental results demonstrate that CodeMF can effectively reduce running time and improve precision via mining high‐quality software repositories for various programming languages, especially for the large‐scale codebases. To further illustrate the effect of CodeMF applied in software tasks, we introduce it to improve the performance of query‐expansion code search. Meanwhile, for SQL and C# programs, compared to the state‐of‐the‐art query‐expansion method QECK, the improvement of QECKCodeMF is 2% and 6% on Recall@10, and 4% and 14% on mean reciprocal rank, respectively.
Methods for localizing network link failures

—Most of today’s networks use Link Aggregated Group (LAG) to increase the bandwidth. A single physical link failure under LAG will reduce network capacity signiﬁcantly. Unfortunately, there are no standard protocols to localize link failure, especially to localize link failure at the physical layer. Some protocols, such as BFD and LACP, only work locally and do not distribute a notiﬁcation about the link failure. SNMP, OSPF, and IS-IS only work at the data-link layer. In this paper, we will evaluate and compare the methods to localize link failure in the presence of LAG. The methods can be classiﬁed into two mechanisms: correlated-paths probing and per-link monitoring. We ﬁrst implement per-link monitoring methods using Software Deﬁned Networking (SDN) and compare them with existing correlated-paths probing based on their scalability, latency, accuracy, ﬂexibility, and applicability. Our results show that there is no overall winner, but gives insight into which approach is best suited for which objectives.
Cornell Working Papers in Phonetics and Phonology 2019 Doing phonology in the age of big data *

The central question we address in this paper is how to do phonology in an emerging era of big data. The more specific question we explore is how to better use naturalistic corpus data to study phonology. We support the growing trends that are expanding the range of phenomena phonologists investigate, and enhancing the richness of detail with which investigations are conducted. Presenting case studies from English, Indonesian, and Romanian, we argue that the use of corpus data necessarily follows from the goals of the generative enterprise. At the same time, experimental and laboratory investigations are crucial to fully and systematically explore both phonological patterns and individual speaker differences, as we show with case studies of English, Italian, and Catalan. We advocate for an iterative model of phonological analysis integrating careful data elicitation with both corpus analysis and experimental methods.
PTX 3 Polymorphisms and Invasive Mold Infections after Solid Organ Transplantation

Donor PTX3 polymorphisms were shown to influence the risk of invasive aspergillosis among hematopoietic stem cell transplant recipients. Here, we show that PTX3 polymorphisms are independent risk factors for invasive mold infection among 1101 solid organ transplant recipients, thereby strengthening their role in mold infection pathogenesis and patient’s risk stratification. at Sital N tz B rn A G on M ay 8, 2015 http://cidrdjournals.org/ D ow nladed from
Switching Schemas: Do Effects of Mindless Interactions With Agents Carry Over to Humans and Vice Versa?

The Revised Ethopoeia Concept proposes that agents should activate human schema in the form of social expectations and rules. However, studies have demonstrated inconsistent reactions to agents and avatars, potentially due to the activation of a nonhuman schema that constrains people’s ability to mentally connect with agents. We first examined whether the schema activated during agent or avatar game play were consistent with and influenced a subsequent interaction with a human. Results suggested that schemas activated across consecutive interactions with an agent and then a human were incongruent, while avatars successfully influenced subsequent interactions with humans (i.e., prosocial behaviors) by evoking congruent schemas. A second experiment corroborated this by demonstrating a match between schemas activated during game play with agents and subsequent interactions with another human-like but nonhuman entity (i.e., artificial intelligence). Additional results and implications related to switching schemas in consecutive interactions with agents and humans are discussed.
50 Biped Footstep Planning

Summary. Planning footsteps before the actual walking motion is a way to ignore the dynamic complexity of bipedal walking in the motion planning process without losing the possibility to exploit the essential characteristic of walking: the fact that it relies on isolated contacts with the ground, and therefore provides the ability to traverse irregular or discontinuous terrain. The duality between a continuous environment and discrete sequences of contacts confers to footstep planning a hybrid nature and an interesting theoretical aspect, which adds up to its obvious practical interest. Well incorporated and efﬁcient footstep planning abilities would give humanoid robots a navigation autonomy allowing them to perform a great number of versatile tasks in unstructured environments. Many approaches have been considered to obtain efﬁcient footstep planning, for example using only a ﬁnite number of predeﬁned steps, or bounding boxes for fast collision checking. And for really reactive footstep planning, dynamics have to be put back into the equation, either by merging footstep planning with gait control, or by adaptively switching between different layers of planning. In this chapter, we give an overview of the main techniques that have been proposed and tested over the past 15 years.
HARMONIC MITIGATION AND REACTIVE COMPENSATION BY SRF/MCPWM CONTROL OF MLI-STATCOM IN POWER DISTRIBUTION NETWORK

Electric Power Quality is term which has captured increasing attention in Power Engineering in the recent years. Usually Power quality refers to maintaining a sinusoidal waveform of bus voltages at rated voltage and frequency. But due to Nonlinear loads, the harmonics and distortion current create reactive power problems. The harmonic voltage drops across the network impedance that affects power factor. This paper discus with a five-level diode clamped Multilevel Inverter based Distribution STATCOM (MLI-DSTATCOM) with Synchronous Reference Frame based control. The mathematical modelling of the control structure to the DSTATCOM, Nonlinear load and the modelling of 5 level Cascaded H Bridge Inverter with Phase shifted PWM technique is presented It is proved that the CHB based multilevel inverter mitigates the harmonics in the source current at distribution system. These harmonics are mitigating the Power Quality Enhancement in distributed system. Here the device called STATCOM is one of the FACTS Devices which can be used to mitigate the harmonics and reactive power compensation. In this paper we implement with SRF based STATCOM control. SRF theory is implemented for the generation of controlling reference current signals for controller of STATCOM. The Matlab\Simulink based model is developed and simulation results are found. The hardware is implemented and the results were compared with the simulated outputs. Keyword: Nonlinear loads, Harmonics, Distortion current, MLI-D-STATCOM, SRF, FACTS. 1.Introduction: International Journal of Pure and Applied Mathematics Volume 118 No. 2
Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms

Security indices are the main tools for evaluation of the status of financial markets. Moreover, a main part of the economy of any country is constituted of investment in stock markets. Therefore, investors could maximize the return of investment if it becomes possible to predict the future trend of stock market with appropriate methods. The nonlinearity and nonstationarity of financial series make their prediction complicated. This study seeks to evaluate the prediction power of machine‐learning models in a stock market. The data used in this study include the daily close price data of iShares MSCI United Kingdom exchange‐traded fund from January 2015 to June 2018. The prediction process is done through four models of machine‐learning algorithms. The results indicate that the deep learning method is better in prediction than the other methods, and the support vector regression method is in the next rank with respect to neural network and random forest methods with less error.