Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting ant colony algorithms to seismic faults detection

Seismic fault extracting is a time consuming task that can be aided by image enhancement of fault areas. The recent literature addresses this task by using ant colony optimization (ACO) algorithms to highlight the fault edges. This work proposes improvements to current state of the art methods by revisiting and/or reincorporating classic aspects of ACO, such as ant distribution, pheromone evaporation and deposition, not previously considered in this seismic fault enhancement scenario.The proposed approach arrives at good results presenting images with little noise and great localization of fault edges.
Coaxial Networks for 5G Fronthaul

In this paper, we present an investigation about the potential of coaxial networks for 5G fronthaul. The study is motivated since some countries have a big coaxial infrastructure that could potentially be used for 5G applications. In this context, we propose here a fronthaul scheme with analog radio over coaxial cables and evaluate the maximum number of antennas that can be employed in such a system assuming a predefined signal-to-noise ratio condition. The results indicate that this solution is able to meet the high capacity requirements of 5G, with the additional benefits of low latency and low cost.
Reputation-based framework for high integrity sensor networks

The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes. We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes. We are currently developing a system within this framework where we employ a Bayesian formulation, specifically a beta reputation system, for reputation representation, updates and integration. We will explain the reasoning behind our design choices, analyzing their pros & cons. We conclude the paper by verifying the efficacy of this system through some preliminary simulation results.
Model exploration with temporal logic query checking

A temporal logic query is a temporal logic formula with placeholders. Given a model, a solution to a query is a set of assignments of propositional formulas to placeholders, such that replacing the placeholders with any of these assignments results in a temporal logic formula that holds in the model. Query checking, first introduced by William Chan \citechan00, is an automated technique for finding solutions to temporal logic queries. It allows discovery of the temporal properties of the system and as such may be a useful tool for model exploration and reverse engineering.This paper describes an implementation of a temporal logic query checker. It then suggests some applications of this tool, ranging from invariant computation to test case generation, and illustrates them using a Cruise Control System.
Supporting network evolution and incremental deployment with XIA

eXpressive Internet Architecture (XIA) [1] is an architecture that natively supports multiple communication types and allows networks to evolve their abstractions and functionality to accommodate new styles of communication over time. XIA embeds an elegant mechanism for handling unforeseen communication types for legacy routers. In this demonstration, we show that XIA overcomes three key barriers in network evolution (outlined below) by (1) allowing end-hosts and applications to start using new communication types (e.g., service and content) before the network supports them, (2) ensuring that upgrading a subset of routers to support new functionalities immediately benefits applications, and (3) using the same mechanisms we employ for 1 and 2 to incrementally deploy XIA in IP networks.
Association between physical activity, occupational sitting time and mortality in a general population: An 18-year prospective survey in Tanushimaru, Japan

Aims It is well known that a decline in physical activity is associated with an increase of all-cause death including cardiovascular events and cancer. Few studies have examined the association between occupational sitting time and mortality. Therefore, we investigated this issue in a general population. Methods Physical activity and occupational sitting time were measured using the Baecke physical activity questionnaire in 1999. The questionnaire generated indices in three physical activity categories: work, sport and leisure-time. A total physical activity index was calculated by adding these three indices. The Baecke physical activity questionnaire was able to evaluate occupational sitting time. Hazard ratios and 95% confidence intervals (CIs) were calculated using Cox's proportional hazard regression models. Results We enrolled a total of 1680 participants, who were followed up for 15.9 ± 3.8 years. The final follow-up rate was 93%. During the follow-up period, 397 subjects died. A significant inverse association (p < 0.0001) was found between physical activity and mortality after adjustment for age and sex. Compared with lower levels of physical activity, the adjusted hazard ratio for mortality at higher levels of physical activity was 0.85 (95% CI: 0.78–0.92). Longer occupational sitting time was also significantly associated with higher mortality (p < 0.01). The adjusted hazard ratio for mortality at longer occupational sitting time was 1.16 (95% CI: 1.05–1.27). These findings were observed in males, but not in females. Conclusions Our data demonstrated that higher levels of physical activity are associated with a reduced risk of cancer and cardiovascular death. Further, longer occupational sitting time is associated with increased mortality.
The RWTH Aachen University Filtering System for the WMT 2018 Parallel Corpus Filtering Task

This paper describes the submission of RWTH Aachen University for the De→En parallel corpus filtering task of the EMNLP 2018 Third Conference on Machine Translation (WMT 2018). We use several rule-based, heuristic methods to preselect sentence pairs. These sentence pairs are scored with count-based and neural systems as language and translation models. In addition to single sentence-pair scoring, we further implement a simple redundancy removing heuristic. Our best performing corpus filtering system relies on recurrent neural language models and translation models based on the transformer architecture. A model trained on 10M randomly sampled tokens reaches a performance of 9.2% BLEU on newstest2018. Using our filtering and ranking techniques we achieve 34.8% BLEU.
Lexical Similarity Between Argument and Parameter Names: An Empirical Study

Identifiers chosen by programmers convey rich semantic information that could be exploited to enhance program analysis for various software engineering tasks, e.g., anomaly detection, argument recommendation, and code completion. However, such information has not yet been fully exploited, and little is known about its properties. In this paper, we carry out an empirical study to investigate the lexical similarity between the actual argument and the formal parameter names in method invocations. By analyzing actual arguments and formal parameters from 127 Java applications and 30 open-source C applications, we observe a number of interesting and valuable findings concerning the distribution of similarity, reasons for dissimilarity, and so on. Such findings have been exploited to facilitate argument-related software engineering tasks, i.e., anomaly detection and code completion.
A Multi-Objective Ant Colony System Algorithm for Virtual Machine Placement in Traffic Intense Data Centers

Virtual machine (VM) placement can meet different kinds of performance targets in data centers. As a result, it has become one of the most critical operations in data centers. In this paper, we investigate the VM placement problem for cloud applications, which have intense bandwidth requirements. In this kind of applications, all VMs communicate with a single designated point. The work of predecessors focuses on the revenue of communications in the network, and tries to find a good solution composed of the best fitted VMs. However, in their work, where to place the selected VMs is not important and has no effect on their objective, and this may cause high power consumption. We formulate the problem as a bin packing problem, which is strictly NP-hard. Then, we propose a multi-objective Ant Colony System (ACS) algorithm which is called ACS-BVMP. The goal is to obtain Pareto optimal solution set, which can simultaneously maximize the revenue of communications and minimize the power consumption of PMs. The proposed algorithm is tested with some instances from the literature. Its solution set is compared with two existing multi-objective algorithms and three single-objective algorithms. The results show that our proposed algorithm outperforms the above algorithms.
The MLLP-UPV German-English Machine Translation System for WMT18

This paper describes the statistical machine translation system built by the MLLP research group of Universitat Politècnica de València for the German→English news translation shared task of the EMNLP 2018 Third Conference on Machine Translation (WMT18). We used an ensemble of Transformer architecture–based neural machine translation systems. To train our system under “constrained” conditions, we filtered the provided parallel data with a scoring technique using character-based language models, and we added parallel data based on synthetic source sentences generated from the provided monolingual corpora.
Solving the missing node problem using structure and attribute information

An important area of social networks research is identifying missing information which is not explicitly represented in the network, or is not visible to all. Recently, the Missing Node Identification problem was introduced where missing members in the social network structure must be identified. However, previous works did not consider the possibility that information about specific users (nodes) within the network could be useful in solving this problem. In this paper, we present two algorithms: SAMI-A and SAMI-N. Both of these algorithms use the known nodes' specific information, such as demographic information and the nodes' historical behavior in the network. We found that both SAMI-A and SAMI-N perform significantly better than other missing node algorithms. However, as each of these algorithms and the parameters within these algorithms often perform better in specific problem instances, a mechanism is needed to select the best algorithm and the best variation within that algorithm. Towards this challenge, we also present OASCA, a novel online selection algorithm. We present results that detail the success of the algorithms presented within this paper.
An Augmentation of Fuzziness to Randomness in Project Evaluation

Net present value is the traditional approach to evaluate the financial viability of projects including large ones. Unfortunately, the NPV may mislead decision makers for two reasons. First, it does not take into consideration managerial flexibility which is the ability of decision-makers to react to upcoming information related to some uncertain events in a way that may change the project design and planning. Randomness based on standard deviation is usually utilized to accommodate such flexibility. Second, the NPV calculation relies on some fuzzy variables that are subject to imprecision or ambiguity such as the characteristics of the project cash flow and investment cost. The variability of these errors can also be represented in the volatility of the model. In such scenario, volatility would be randomness as well as fuzziness based. Researchers in the field propose to use project Investment and Project cost as fuzzy variables. We argue in this paper that both of these factors can be embedded in the randomness-based volatility factor. This paper investigates the use of the volatility factor as fuzzy parameter in a Real options approach to evaluate projects. Hence, the overall ambiguity would be represented in a combination of randomness as well as fuzziness to achieve acceptable evaluations.
The TALP-UPC Machine Translation Systems for WMT18 News Shared Translation Task

In this article we describe the TALP-UPC research group participation in the WMT18 news shared translation task for Finnish-English and Estonian-English within the multi-lingual subtrack. All of our primary submissions implement an attention-based Neural Machine Translation architecture. Given that Finnish and Estonian belong to the same language family and are similar, we use as training data the combination of the datasets of both language pairs to paliate the data scarceness of each individual pair. We also report the translation quality of systems trained on individual language pair data to serve as baseline and comparison reference.
Overexpression of ASIC1A in the nucleus accumbens of rats potentiates cocaine‐seeking behavior

Acid‐sensing ion channels (ASICs) are abundantly expressed in the nucleus accumbens core (NAcore), a region of the mesolimbocortical system that has an established role in regulating drug‐seeking behavior. Previous work shows that a single dose of cocaine reduced the AMPA‐to‐NMDA ratio in Asic1a−/− mice, an effect observed after withdrawal in wild‐type mice, whereas ASIC1A overexpression in the NAcore of rats decreases cocaine self‐administration. However, whether ASIC1A overexpression in the NAcore alters measures of drug‐seeking behavior after the self‐administration period is unknown. To examine this issue, the ASIC1A subunit was overexpressed in male Sprague‐Dawley rats by injecting them with adeno‐associated virus, targeted at the NAcore, after completion of 2 weeks of cocaine or food self‐administration. After 21 days of homecage abstinence, rats underwent a cue‐/context‐driven drug/food‐seeking test, followed by extinction training and then drug/food‐primed, cued, and cued + drug/food‐primed reinstatement tests. The results indicate that ASIC1A overexpression in the NAcore enhanced cue‐/context‐driven cocaine seeking, cocaine‐primed reinstatement, and cued + cocaine‐primed reinstatement but had no effect on food‐seeking behavior, indicating a selective effect for ASIC1A in the processes underlying extinction and cocaine‐seeking behavior.
Tilde’s Parallel Corpus Filtering Methods for WMT 2018

The paper describes parallel corpus filtering methods that allow reducing noise of noisy “parallel” corpora from a level where the corpora are not usable for neural machine translation training (i.e., the resulting systems fail to achieve reasonable translation quality; well below 10 BLEU points) up to a level where the trained systems show decent (over 20 BLEU points on a 10 million word dataset and up to 30 BLEU points on a 100 million word dataset). The paper also documents Tilde’s submissions to the WMT 2018 shared task on parallel corpus filtering.
Compound pesticide controlled release system based on the mixture of poly(butylene succinate) and PLA

Abstract Controlled release system has been widely developed and utilised in agriculture to optimise efficacy and minimise environmental pollution. Here, the azoxystrobin and difenoconazole compound pesticide microsphere was constructed by the solvent evaporation method. Blending poly (butylene succinate) (PBS) and poly (lactic acid) (PLA) as shells, in order to increase its entrapment efficiency and match the goal of complex synergism. The resulting microsphere processes high entrapment efficiency with a mean diameter of 7.2 μm. Acute toxicity suggested microsphere on zebrafish was moderate toxicity. Comparative studies revealed that the microsphere had a longer period of sustained release than difenoconazole–azoxystrobin (5:8) 32.5% w/v suspension concentrate (SC). In addition, the concentration ratio of active ingredients closed to the optimum compound stoichiometry, which can achieve the objective of improving the efficacy of the pesticides. These results demonstrated that such a compound pesticide microsphere delivery system may be a considerable potential for further exploration.
Towards an Integrated Geographic Routing Approach using Estimated Sensors Position in WSNs

Geographic routing protocols have been developed to increase the effectiveness and the usefulness of wireless sensor networks in many emerging applications. In these protocols, the routing decision, at each sensor node, is based only on the positions of the destination node and forwarding node's neighbors. However, these protocols are based on exact sensors position, assuming that sensors are equipped with a geographic positioning or a localization-based technique. Recently, several techniques, such DV-Hop, have been proposed for estimating sensors' positions. This paper introduces an integrated geographic routing protocol by integrating both sensors' position estimation and geographic routing techniques. We have mainly combined DV-Hop for estimating sensors position and the greedy perimeter stateless protocol for data forwarding and routing. Simulations have been carried out and results are reported to show the efficiency of the proposed hybrid geographic routing protocol in WSNs.
Revisiting 25 years of system motivation explanation for system justification from the perspective of social identity model of system attitudes.

Do the disadvantaged have an autonomous system justification motivation that operates against their personal and group interests? System justification theory (SJT; Jost & Banaji, 1994, Br. J. Soc. Psychol, 33, 1) proposes that they do and that this motivation helps to (1) reduce cognitive dissonance and associated uncertainties and (2) soothe the pain that is associated with knowing that one's group is subject to social inequality. However, 25 years of research on this system justification motivation has given rise to several theoretical and empirical inconsistencies. The present article argues that these inconsistencies can be resolved by a social identity model of system attitudes (SIMSA; Owuamalam, Rubin, & Spears, 2018, Curr. Dir. Psychol. Sci, 27, 91). SIMSA assumes that instances of system justification are often in alignment with (rather than opposed to) the interests of the disadvantaged. According to SIMSA, the disadvantaged may support social systems (1) in order to acknowledge social reality, (2) when they perceive the wider social system to constitute a superordinate ingroup, and (3) because they hope to improve their ingroup's status through existing channels in the long run. These propositions are corroborated by existing and emerging evidence. We conclude that SIMSA offers a more coherent and parsimonious explanation for system justification than does SJT.
Testing a Web-Based Interactive Comic Tool to Decrease Obesity Risk Among Minority Preadolescents: Protocol for a Pilot Randomized Control Trial

Background Childhood obesity is a public health crisis, particularly in low-income, minority populations in the United States. Innovative and technology-enhanced interventions may be an engaging approach to reach at-risk youth and their parents to improve dietary behaviors and feeding practices. However, such tools are limited, especially ones that are theory-based; co-developed with user-centered approaches; tailored to low-income, minority preadolescents; and include parent-focused content. Objective The objectives of this study include assessing the feasibility and acceptability and exploring the potential impact of the Intervention INC (Interactive Nutrition Comics for urban, minority preadolescents) Web-based tool, which is focused on decreasing childhood obesity risk in black/African American and Latino children aged 9 to 12 years. Methods Intervention INC is underpinned by the narrative transportation theory, social cognitive theory, and health belief model, and it was co-developed by children and parents from the intended population. The child component consists of a 6-chapter interactive nutrition comic optimized for use on tablet devices, a goal-setting and self-assessment feature, and weekly text/email messages and reminders. The parental component consists of 6 Web-based newsletters, access to the child comic, and weekly text/email messages and reminders. The tool was evaluated using a pilot, single-blind, 2-group randomized controlled study design. Child-parent dyads were randomized to either the experimental or comparison group and assigned to a targeted behavior (increase fruit/vegetable or water intake) based on initial screening questions. Data were collected at 4 time points: baseline (T1), intervention midpoint (T2), intervention endpoint (T3), and 3 months postintervention (T4). Primary measures comprise usage, usability, and feasibility of the Web-based tool. Secondary measures comprise dietary knowledge, preferences, and intake and anthropometric measures (for child) and feeding practices and home food environment (for parent). Results Study enrollment was completed in November 2017. A total of 89 child-parent dyads were randomized to either the experimental (n=44) or comparison (n=45) group. Data analysis is currently being conducted. Conclusions This study aims to implement and assess an innovative approach to deliver health messages and resources to at-risk minority preadolescents and their parents. If found to be acceptable, engaging, feasible, and a potential approach to improve dietary behaviors, a full-fledged randomized controlled trial will be conducted to assess its efficacy and potential impact. Trial Registration ClinicalTrials.gov NCT03165474; https://clinicaltrials.gov/ct2/show/NCT03165474 (Archived by WebCite at http://www.webcitation.org/73122IjgP) International Registered Report Identifier (IRRID) RR1-10.2196/10682
Discourse-Related Language Contrasts in English-Croatian Human and Machine Translation

We present an analysis of a number of coreference phenomena in English-Croatian human and machine translations. The aim is to shed light on the differences in the way these structurally different languages make use of discourse information and provide insights for discourse-aware machine translation system development. The phenomena are automatically identified in parallel data using annotation produced by parsers and word alignment tools, enabling us to pinpoint patterns of interest in both languages. We make the analysis more fine-grained by including three corpora pertaining to three different registers. In a second step, we create a test set with the challenging linguistic constructions and use it to evaluate the performance of three MT systems. We show that both SMT and NMT systems struggle with handling these discourse phenomena, even though NMT tends to perform somewhat better than SMT. By providing an overview of patterns frequently occurring in actual language use, as well as by pointing out the weaknesses of current MT systems that commonly mistranslate them, we hope to contribute to the effort of resolving the issue of discourse phenomena in MT applications.