Miracle-dz/UniFAR-FTUs huggingface dataset:
ML decoding via mixed-integer adaptive linear programming

Linear programming (LP) decoding was introduced by Feldman et al. (IEEE Trans. Inform. Theory Mar. 2005) as a novel way to decode binary low-density parity-check codes. Taghavi and Siegel (Proc. ISIT 2006) describe a computationally simplified decoding approach they term "adaptive" LP decoding. Adaptive LP decoding starts with a sub-set of the LP constraints, and iteratively adds violated constraints until an optimum of the original LP is found. Usually only a tiny fraction of the original constraints need to be reinstated, leading to huge efficiency gains compared to ordinary LP decoding. Here we describe a modification of the adaptive LP decoder that results in a maximum likelihood (ML) decoder. Whenever the adaptive LP decoder returns a pseudo-codeword rather than a codeword, we add an integer constraint on the least certain symbol of the pseudo-codeword. For certain codes, and especially in the high-SNR (error floor) regime, only a few integer constraints are required to force the resultant mixed-integer LP to the ML solution. We demonstrate that our approach can efficiently achieve the optimal ML decoding performance on a (155,64) LDPC code introduced by Tanner et al.
A Novel Learning Method for Elman Neural Network Using Local Search

Elman Neural Network (ENN) have been efficient identification tool in many areas since they have dynamic memories. However, the local minima problem usually occurs in the process of the learning because of the employed back propagation algorithm. In this paper, we propose a novel learning method for ENN by introducing adaptive learning parameter into the traditional local search algorithm. The proposed learning network requires less memory and it is able to overcome the disadvantages of the gradient descent. Meanwhile it is also able to accelerates the speed of the convergence and avoid the local minima problem in a certain extent. We apply the new method to the Boolean Series Prediction Questions to demonstrate its validity. Simulation results show that the proposed algorithm has a better ability to find the global minimum than back propagation algorithm within reasonable time.
Manipulation of FASTQ data with Galaxy

Summary: Here, we describe a tool suite that functions on all of the commonly known FASTQ format variants and provides a pipeline for manipulating next generation sequencing data taken from a sequencing machine all the way through the quality filtering steps. Availability and Implementation: This open-source toolset was implemented in Python and has been integrated into the online data analysis platform Galaxy (public web access: http://usegalaxy.org; download: http://getgalaxy.org). Two short movies that highlight the functionality of tools described in this manuscript as well as results from testing components of this tool suite against a set of previously published files are available at http://usegalaxy.org/u/dan/p/fastq Contact: james.taylor@emory.edu; anton@bx.psu. edu Supplementary information: Supplementary data are available at Bioinformatics online.
NET Institute* www.NETinst.org

This paper proposes approximate variational inference methods for estimation of a strategic model of social interactions. Players interact in an exogenous network and sequentially choose a binary action. The utility of an action is a function of the choices of neighbors in the network. I prove that the interaction process can be represented as a potential game and it converges to a unique stationary equilibrium distribution. However, exact inference for this model is infeasible because of a computationally intractable likelihood, which cannot be evaluated even when there are few players. To overcome this problem, I propose variational approximations for the likelihood that allow approximate inference. This technique can be applied to any discrete exponential family, and therefore it is a general tool for inference in models with a large number of players. The methodology is illustrated with several simulated datasets and compared with MCMC methods.
Many holes in hindley-milner

We implement statically-typed multi-holed contexts in OCaml using an underlying algebraic datatype augmented with phantom types. Existing approaches require dynamic checks or more complex type systems. In order to support concatenation we use two type parameters to represent the number of holes in a context as the difference between two Peano numbers. In order to support plugging a context with contexts of different arity we introduce a datatype of lists of contexts of length n with a total of m holes. Further, we extend our representation to allow holes to be marked with additional type information. As an example, we use these marks to implement statically-typed multi-holed XHTML contexts. We take advantage of Garrigue's relaxed value restriction.
Time-space Evolution of Desertification Land in Northern China

It was disclosed by former researches that the desertification land in northern China developed at rate of \{1 560\} km2 per year from late of 1950s to middle of 1970s, and till late of 1970s the already desertified land had reached 17.6×104 km2, the light degree and potential desertification lands had reached 15.8 104 km2; During the following ten years the developing rate was up to \{2 100\} km2 per year, and till late of 1980s the already desertified land had reached 33.3×104 km2. In order to further disclose the status and developing trend of desertification land in China from then on and provide dependable bases for the strategy making of desertification control, another field investigation and monitoring with remote sensing to the desertification status in 256×104 km2 area of Northern China was conducted in 2000. The results showed that the total desertified land area had increased to 38.576×104 km2 from 33.895×104 km2 in 1987 , among which the light degree and potential desertification land was 13.93×104 km2, occupied 36.1% of the total; the middle degree was 9.977×104 km2, occupied 25.9%; the serious was 7.907×104 km2, occupied 20.51%; the very serious was 6.756×104 km2, occupied 17.5%. The developing rate of desertification land was further raised to \{3 500\} km2 per year during 1990s. In details, although the desertification in part of agricultural and agro\|pastoral areas inversed distinctly, the area of desertification land in desert steppe and steppe desert continuously extended and the degree intensified.
On the Invariance of Ant Colony Optimization on the Invariance of Ant Colony Optimization

The information provided is the sole responsibility of the authors and does not necessarily reflect the opinion of the members of IRIDIA. The authors take full responsibility for any copyright breaches that may result from publication of this paper in the IRIDIA – Technical Report Series. IRIDIA is not responsible for any use that might be made of data appearing in this publication. Abstract Ant colony optimization (ACO) is a promising metaheuristic and a great amount of research has been devoted to its empirical and theoretical analysis. Recently, with the introduction of the hyper-cube framework [1], Blum and Dorigo have explicitly raised the issue of the invariance of ACO algorithms to transformation of units. They state [1] that the performance of ant colony optimization depends on the scale of the problem instance under analysis. In this paper, we show that the ACO internal state—commonly referred to as the pheromo-ne—indeed depends on the scale of the problem at hand. Nonetheless, we formally prove that this does not affect the sequence of solutions produced by the three most widely adopted algorithms belonging to the ACO family: ant system, MAX–MIN ant system, and ant colony system. For these algorithms, the sequence of solutions does not depend on the scale of the problem instance under analysis. Moreover, we introduce three new ACO algorithms, the internal state of which is independent of the scale of the problem instance considered. These algorithms are obtained as minor variations of ant system, MAX–MIN ant system, and ant colony system. We formally show that these algorithms are functionally equivalent to their original counterparts. That is, for any given instance, these algorithms produce the same sequence of solutions as the original ones.
Specification and evaluation of an assessment engine for educational games

Educational games are highly engaging, motivating and they offer many advantages as a supplementary tool for education. However, the development of educational games is very complex, essentially because of its multidisciplinary aspect. Fully integrating assessment is challenging and the games created are too often distributed as blackboxes; unmodifiable by the teachers and not providing much insight about the gameplays. We propose an assessment engine, EngAGe, to overcome these issues. EngAGe is used by both developers and educators. It is designed to separate game and assessment. Developers use it to easily integrate assessment into educational games and teachers can then modify the assessment and visualise learning analytics via an online interface. This paper focuses on EngAGe’s benefits for games developers. It presents a quantitative evaluation carried out with 36 developers (7 experienced and 29 students). Findings were very positive: every feature of the engine was rated useful and EngAGe received a usability score of 64 using the System Usability Scale. A Mann-Whitney U test showed a significant difference in usability (Z=-3.34, p<0.002) between novice developers (mean=56) and experienced developers (mean=71) but none in terms of usefulness. This paper concludes that developers can use EngAGe effectively to integrate assessment and learning analytics in educational games. all 13 game development teams from the defined their games using the proposed DSL. The usability evaluation returned a SUS score of 64, which corresponds to a “Good” score. Developers found both the DSL and the web services overall useful, however, the study has highlighted some areas that need improvement, such as the learning curve involved in using the engine. These findings suggest that EngAGe can be used efficiently and effectively by developers when creating educational games. Another study was carried out with (Chaudy & Connolly, 2018) to evaluate the learning analytics dashboard of the engine and the visual editor that educators can use to modify a game’s assessment. A tutorial was also be given to them and a post-questionnaire collected information about usability and usefulness. The educators’ opinions towards educational games as an assessment tool was monitored to determine if the use of EngAGe influences it. Findings were overall very positive with educators rating the system useful and easy to use. Their trust toward using a game for assessment before and after using EngAGe also improved significantly.
ToBI-Team of Bielefeld : The Human-Robot Interaction System for RoboCup @ Home 2011

The Team of Bielefeld (ToBI) was founded in 2009. The robocup activities are embedded in a long-term research history towards human-robot interaction with laypersons in regular home environments. The robocup@home competition is an important benchmark and milestone for the overall research goal. For robocup 2011, the team concentrates on mixed-initiative scenarios, sophisticated scene understanding methods including semantically annotated maps, and an easy to use programming environment.
Constraint Consensus Concentration for Identifying Disjoint Feasible Regions in Nonlinear Programs

It is usually not known in advance whether a nonlinear set of constraints has zero, one, or multiple feasible regions. Further, if one or more feasible regions exist, their locations are usually unknown. We propose a method for exploring the variable space quickly using Constraint Consensus to identify promising areas that may contain a feasible region. Multiple Constraint Consensus solution points are clustered to identify regions of attraction. A new inter-point distance frequency distribution technique is used to determine the critical distance for the single linkage clustering algorithm, which in turn determines the estimated number of disjoint feasible regions. The effectiveness of multistart global optimization is increased due to better exploration of the variable space, and efficiency is also increased because the expensive local solver is launched just once near each identified feasible region. The method is demonstrated on a variety of highly nonlinear models.
Ghost Signals: Verifying Termination of Busy-Waiting

Programs for multiprocessor machines commonly perform busy-waiting for synchronization. We propose a separation logic using so-called ghost signals to modularly verify termination of such programs under fair scheduling. Intuitively spoken, ghost signals lift the runtime concept of wait-notify synchronization to the verification level and allow a thread to busy-wait for an event $X$ while another thread promises to trigger $X$.
NeSF: Neural Shading Field for Image Harmonization

Image harmonization aims at adjusting the appearance of the foreground to make it more compatible with the background. Due to a lack of understanding of the background illumination direction, existing works are incapable of generating a realistic foreground shading. In this paper, we de-compose the image harmonization into two sub-problems: 1) illumination estimation of background images and 2) rendering of foreground objects. Before solving these two sub-problems, we ﬁrst learn a direction-aware illumination descriptor via a neural rendering framework, of which the key is a Shading Module that decomposes the shading ﬁeld into multiple shading components given depth information. Then we design a Background Illumination Estimation Module to extract the direction-aware illumination descriptor from the background. Finally, the illumination descriptor is used in conjunction with the neural rendering framework to generate the harmonized foreground image containing a novel harmonized shading. Moreover, we construct a photo-realistic synthetic image harmonization dataset that contains numerous shading variations by image-based lighting. Extensive experiments on this dataset demonstrate the effectiveness of the proposed method. Our dataset and code will be made publicly available.
A Cost-Effective Model-Based Approach for Developing ISO 26262 Compliant Automotive Safety Related Applications

As cars and planes have become more sophisticated — delivering smarter functionality and higher performance — they include more electronic components. In turn, this means more lines of embedded software code that monitors, manages and controls these electronics. Because automobiles and aircraft represent mission-critical applications, a single flaw in this embedded software code could endanger the safety of thousands of passengers. Not only is manually testing and verifying this code prohibitively expensive and time-consuming, but it is also prone to error. That is why leaders in many industries — including automotive, aerospace, transportation, energy and health care — rely on ANSYS SCADE, a model-based development environment for critical embedded software. The SCADE solution suite from ANSYS includes SCADE Test, a complete testing environment for test case creation and management, automatic test case execution on both hosts and targets, coverage measurement, and management of test results. New capabilities in SCADE Test are making it even easier, faster and more affordable to verify and test embedded code. By achieving structural coverage — also known as code coverage — and model coverage in one simple step, SCADE Test streamlines the process of regulatory compliance and software verification, providing a significant competitive edge for those engineering teams that choose to leverage this capability.
Boosting Image and Video Compression via Learning Latent Residual Patterns Supplementary Materials

In this supplementary material, we present more qualitative results of our method for improving the visual quality of compressed video and image. Additional example results for improving compressed videos are shown in Figure 1. Please also check the short video clip provided in the supplementary material to see our results, where we directly stack the frames sampled from the original and resultant videos to form it. The left part of the video clip is the compressed frames, and the right part is the reconstructed results produced by our proposed method. In terms of image compression, we also provide more example results on ILSVRC, as shown in Figure 2 for JPEG2000, Figure 3 for BPG and Figure 4 for DL-based compression [2] respectively.
Private and Scalable Personal Data Analytics using a Hybrid Edge-Cloud Deep Learning

We are observing an increasing presence of cyber-physical systems and their associated data around us. While the ability to collect, collate, and analyze the vast amount of rich information from smartphones, IoT devices, and urban sensors can be beneficial to the users and the industry, this process has led to a number of challenges ranging from performing efficient and meaningful analytics on the generated big data, to privacy challenges associated with the inferences made from these data due to ubiquitous nature of connected devices. In this paper, we discuss novel edge-computing methods to improve the scalability and privacy of user-centered analytics. We present a hybrid framework where edge devices and resources centered around the user can complement the cloud for providing privacy-aware, yet accurate and efficient analytics. We present early evaluations of the proposed framework on a number of exemplar applications, and discuss the broader implications of such approaches.
Seems to Be Low, but Is it Really Poor? Need for Cohort and Comparative Studies to Clarify the Performance of Deep Neural Networks

TO THE EDITOR Although deep learning‒based algorithms demonstrate excellent results (Brinker et al., 2019; Esteva et al., 2017; Haenssle et al., 2018; Liu et al., 2020; Tschandl et al., 2019) for a trained task, uncertainty concerns exist even for an easy task. The accuracy demonstrated in previous studies may not be reproduced when the test environment changes (Cook, 2019; Han et al., 2019; Liu et al., 2019; Zech et al., 2018). Therefore, external tests must be performed, and the model must be improved by reflecting the feedback. The top-1 accuracy of our algorithm for the International Skin Imaging Collaboration dataset is low (39%), as reported by NavarreteeDechent et al. (2020). However, in this letter, we explain why we should not conclude that the algorithm’s performance is poor on the basis of only this result. First, for an accurate assessment of the diagnostic performance of the algorithm, a cross-sectional or comparative study with respect to dermatologists is a better design than a small case study because in a small case study, the selected population cannot represent the population that the test will be applied to in the clinical setting (Chassé and Fergusson, 2019). The performance of an algorithm can be overestimated or underestimated according to given test sets; therefore, it should be evaluated in comparison with the performance of dermatologists. A cohort study, where all cases in a certain clinical
Design and implementation of fuzzy logic controller for level control

This paper includes the design and implementation of a fuzzy logic controller for level control system to overcome the limitations of the conventional controllers. Mostly preferred controller is a Proportional Integral Derivative (PID) controller which has fixed control parameters. Selection of wrong parameters in a PID design results into uncontrollable process. But fuzzy logic controller is a rule based. These rules are designed on the basis of heuristic information provided by an operator. Process model is identified and used for the design of Proportional Integral (PI) and fuzzy controllers by using MATLAB. To evaluate the performance of both the controllers, it is tested on a real time system with the help of Real Time Workspace (RTW) module of a MATLAB. From real time results it is understood that, fuzzy controller provides more stable and improved output for level control. Even fuzzy controller has ability to remove overshoot which is present in PI controller. Also it requires less settling time than PI controller. Hence fuzzy control system is more relevant control strategy to control the level.
SWORD - South West Open Research SWORD - South West Open Research

—The growth of electronic devices in connected vehicles and their connections to the untrusted network, present unprecedented exposure to attacks. Therefore, a reliable and efﬁcient cyber security framework is mandatory to protect vehicular networks against the cyber attackers. Thereby, we propose a cyber defense framework based on a hierarchical cooperative game to secure legitimate vehicles from attacks. In the proposed hierarchical game, there are two kinds of players, the head agent and secondary agents that cooperate between each other to detect, predict and react efﬁciently against suspected attacks. The Intrusion Detection System (IDS), Intrusion Prediction System (IPS), and Intrusion Reaction System (IRS) represent the secondary players, where their strategies are to carry out the detection, prediction and reaction actions, respectively. The Intrusion Decision Agent (IDA) is the head player and is responsible for making decisions in launching the strategies of IDS, IPS and IRS players. The secondary and head agents are to collaborate in order to decrease the false positive and false negative rates, while minimizing the processing delay and overhead. Numerical results show that, our cyber defense game requires low communications overhead and low delay to achieve low false positive and false negative rates as compared to the current intrusion detection and prediction frameworks.
Sharing encountered information: digital libraries get a social life

As part of a more extensive study of reading-related practices, we have explored how people share information they encounter in their everyday reading as a complement to the more traditional digital library focus on sharing intentionally retrieved materials. In twenty contextual interviews in home and workplace settings, we investigated how people encounter and save published material in the form of paper and electronic clippings. We found that sharing forms a significant use for, encountered materials. Furthermore, the function of these clippings extends far beyond a simple exchange of content to inform the recipient; in fact, the content itself may have little immediate value to the recipient. We also found the practice to be ubiquitous: all of our participants had both shared clippings with others and received them themselves. Specifically, This work reports on: (1) how sharing encountered items fits into the broader spectrum of clipping practices; (2) the function and value of the shared information; and (3) the social role of sharing the encountered information. We conclude that from a technological standpoint, we should think beyond an email model for sharing encountered information and, from a social perspective, we should attend to how sharing this sort of material contributes to the strength of social ties outside of a traditional information needs framework.