Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Method for License Plate Detection

License plate detection plays an important role in vehicle license plate recognition for intelligent transport systems. This paper presents a robust method for license plate detection. As we observed, license plate area contains rich corner points’ information. The whole procedure is as follows: (1) Extract the interesting points using Harris corner detector in enhanced car image. (2) Cluster the corner points and apply outlier detection to every cluster. (3) Merge the clusters close to each other and use the gradient information to find the proper block in which the license plate area is enclosed. (4) Train a simple cascade classifier to classify the blocks into two categories: The area possibly containing license plate and those not. (5) Detect the plate region by the rectangle window. Experimental results demonstrate the robustness and the generality of our method.
Liking the (Funny) Messenger: The Influence of News Parody Exposure, Mirth, and Predispositions on Media Trust

ABSTRACT This article features a multi-study research effort (Study 1 N = 331; Study 2 N = 317) examining how predispositions toward a humor source and the perceived humor (i.e., mirth) of a related comedic message can, together, influence media trust-based expectations. Noting the revered status and cultural prominence of various news parody show hosts, this article proposes that feelings of favorability for a news parody humor source (for example, Jon Stewart or John Oliver) can translate into positive perceptions of the press upon exposure to news parody messages. Drawing from principles of the heuristic-systemic information processing model (HSM) and affective disposition theory, the study findings indicate that one’s affective disposition toward a news parody source can have an indirect effect on media trust, as mediated by a feeling of mirth. Upon conducting a test of moderated mediation, the effect is demonstrated to be conditioned by one’s news parody orientation. That is, affective disposition’s mediated effect is most pronounced among those who are least inclined to see news parody as a legitimate/appropriate source of news. Ultimately, this exploratory research contributes to a more nuanced understanding of how news parody programming may influence perceptions of the news media as an institutional entity.
Designing Repeatable Self-Healing into Cementitious Materials

Designing self-healing into cementitious materials can open a new world of opportunities for resilient concrete infrastructure under service loading conditions. The self-healing process should be robust as well as repeatable, allowing for self-repair after multiple damage events. The repeatability poses great challenges when self-healing strategies mainly rely on the formation of low-strength calcium carbonate healing product, complicated by the localized cracking behavior of cementitious materials. This study aims at formulating a new cementitious material system with designed physical and chemical characteristics that favour repeatable self-healing. Advanced experimental methods, coupled with micromechanics theory, are adopted to probe and design repeatable self-healing into cementitious materials.
TUTA1 at the NTCIR-10 Intent Task

In NTCIR-10, we participated in the subtask of Subtopic Mining. We classify test topics into two types: role-explicit topic and roleimplicit topic. According to the topic type, we devise different approaches to perform subtopic mining. Specifically, for roleexplicit topics, we propose an approach of modifier graph based subtopic mining. The key idea is that: The modifier graph corresponding to a role-explicit topic is decomposable into clusters with strong intra-cluster interaction and relatively weak inter-cluster interaction. Each modifier cluster intuitively reveals a possible subtopic. For role-implicit topics that generally express single information needs, we directly generate the ranked list through semantic similarities leveraging on lexical ontologies. The evaluation results show that our best Chinese subtopic mining run gets the first position among all the runs in terms of # D nDCG . However, our English subtopic mining runs show a poor performance, which is planned to be further improved in our future work.
Cognitive Underpinnings of Institutional Persistence and Change: A Framing Perspective

We integrate the predictions of prospect theory, the threat-rigidity hypothesis, and institutional theory to suggest how patterns of institutional persistence and change depend on whether decision makers view environmental shifts as potential opportunities for or threats to gaining legitimacy. We argue that in the event that decision makers face ambiguity in their reading of the environment, they initiate decoupled substantive and symbolic actions that simultaneously accommodate the predictions of prospect theory and the threat-rigidity hypothesis.
Application of the Modified Fractal Signature Method for Terrain Classification from Synthetic Aperture Radar Images

In this paper the Modified Fractal Signature method is applied to real Synthetic Aperture Radar images provided to our research group by SET 163 Working Group on SAR radar techniques. This method uses the blanket technique to provide useful information for SAR image classification. It is based on the calculation of the volume of a blanket, corresponding to the image to be classified, and then on the calculation of the corresponding Fractal Area curve and Fractal Dimension curve of the image. The main idea concerning this proposed technique is the fact that different terrain types encountered in SAR images yield different values of Fractal Area curves and Fractal Dimension curves, upon which classification of different types of terrain is possible. As a result, a classification technique for five different terrain types, i.e. urban, suburban, rural, mountain and sea, is presented in this paper.
Scenario-aware dataflow: Modeling, analysis and implementation of dynamic applications

Embedded multimedia and wireless applications require a model-based design approach in order to satisfy stringent quality and cost constraints. The Model-of-Computation (MoC) should appropriately capture system dynamics, support analysis and synthesis, and allow low-overhead model-driven implementations. This combination poses a significant challenge. The Scenario-Aware DataFlow (SADF) MoC has been introduced to address this challenge. This paper surveys SADF, and compares dataflow MoCs in terms of their ability to capture system dynamics, their support for analysis and synthesis, and their implementation efficiency.
Species Identification of Ten Common Farm Animals Based on Mitochondrial 12S rRNA Gene Polymorphisms

Bio-techniques such as genetic manipulation, marker-assisted selection, and identity test have largely facilitated the modern animal production practices. In the present study, we established a reliable and cost-effective molecular method of species identification for common farm animals. We first (re-)analyzed 179 mitochondrial 12S rRNA gene sequences of ten farm animal species to determine the intra-species and species-specific variations. The PCR-RFLP method was subsequently designed to identify these species by using endonucleases BshNI, ScaI, AluI, and BfaI. The poultry and livestock species were first discriminated by one double-digestion of both BshNI and ScaI, which generated different fragment patterns (325 bp and 115 bp for poultry vs. 364 bp and 76 bp for livestock). The ten species could be further discerned according to species-specific restriction pattern by subjecting to digestion of AluI and BfaI, respectively. Our approach would be more reliable by taking the intra-species variations into consideration and could be applied to species identity test, commercial fraud, and wildlife crime.
A Deep Web Data Integration Model for Pervasive Computing

Pervasive computing demands to integrate all kinds of data, but with the rapid development of Web, there are more and more Web databases behind the query forms. It becomes imperative to provide an integrated query engine over Web databases under pervasive computing environments. In this paper, using house domain of Chinese environment as an example, we propose a more effective technique to perform this task. Our frame is called DWDE. Using Domain Ontology the process of Deep Web data integration is simplified, which only includes three modules, that is Query Interfaces Integration, Web Database Selection and Data Merger. It can get data rapidly and accurately from web databases. It adds three modules for pervasive computing, Interest Degree Manage, Demands Acquirement and Data Presentation. Using these modules, DWDE can combine a Deep Web data integration system into pervasive computing environments seamlessly, and provide better services to the users.
Ecologies of Preferences with Envy as an Antidote to Risk-Aversion in Bargaining

Models have been put forward recently that seem to be successful in explaining apparently anomalous experimental results in the Ultimatum Game, where responders reject positive offers. While imparting fixed preference orders to fully rational agents, these models depart from traditional models by assuming preferences that take account not only of the material payoff to oneself, but also of that which is given to others. However, they leave open the question of how an agent’s economic survival is helped by a preference order that advises him to leave money on the table. Our answer is that, indeed, doing so does not help. But that the same envious preference order that ill advises in some circumstances to reject an “insultingly” small offer, advises well in other circumstances, when it helps the same agent to overcome his risk-aversion and to offer a risky, tough offer that yields him a higher expected dollar gain. We show the existence of population distributions where the two effects exactly balance out across different preference types. These distributions are asymptotically stable, stationary, and inefficient, in which different preferences are represented, and where, as commonly observed in an Ultimatum Game, positive offers are made, of which some are rejected with positive probability. Our theory yields new testable hypotheses.
Streamlined Genome Engineering with a Self-Excising Drug Selection Cassette

A central goal in the development of genome engineering technology is to reduce the time and labor required to produce custom genome modifications. Here we describe a new selection strategy for producing fluorescent protein (FP) knock-ins using CRISPR/Cas9-triggered homologous recombination. We have tested our approach in Caenorhabditis elegans. This approach has been designed to minimize hands-on labor at each step of the procedure. Central to our strategy is a newly developed self-excising cassette (SEC) for drug selection. SEC consists of three parts: a drug-resistance gene, a visible phenotypic marker, and an inducible Cre recombinase. SEC is flanked by LoxP sites and placed within a synthetic intron of a fluorescent protein tag, resulting in an FP–SEC module that can be inserted into any C. elegans gene. Upon heat shock, SEC excises itself from the genome, leaving no exogenous sequences outside the fluorescent protein tag. With our approach, one can generate knock-in alleles in any genetic background, with no PCR screening required and without the need for a second injection step to remove the selectable marker. Moreover, this strategy makes it possible to produce a fluorescent protein fusion, a transcriptional reporter and a strong loss-of-function allele for any gene of interest in a single injection step.
Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals.
Oxcarbazepine-loaded polymeric nanoparticles: development and permeability studies across in vitro models of the blood–brain barrier and human placental trophoblast

Encapsulation of antiepileptic drugs (AEDs) into nanoparticles may offer promise for treating pregnant women with epilepsy by improving brain delivery and limiting the transplacental permeability of AEDs to avoid fetal exposure and its consequent undesirable adverse effects. Oxcarbazepine-loaded nanoparticles were prepared by a modified solvent displacement method from biocompatible polymers (poly(lactic-co-glycolic acid) [PLGA] with or without surfactant and PEGylated PLGA [Resomer® RGPd5055]). The physical properties of the developed nanoparticles were determined with subsequent evaluation of their permeability across in vitro models of the blood–brain barrier (hCMEC/D3 cells) and human placental trophoblast cells (BeWo b30 cells). Oxcarbazepine-loaded nanoparticles with encapsulation efficiency above 69% were prepared with sizes ranging from 140–170 nm, polydispersity indices below 0.3, and zeta potential values below -34 mV. Differential scanning calorimetry and X-ray diffraction studies confirmed the amorphous state of the nanoencapsulated drug. The apparent permeability (Pe) values of the free and nanoencapsulated oxcarbazepine were comparable across both cell types, likely due to rapid drug release kinetics. Transport studies using fluorescently-labeled nanoparticles (loaded with coumarin-6) demonstrated increased permeability of surfactant-coated nanoparticles. Future developments in enzyme-prodrug therapy and targeted delivery are expected to provide improved options for pregnant patients with epilepsy.
PScore: A Framework for Enhancing Privacy Awareness in Online Social Networks

The phenomenal increase in the use of social media in recent years has raised a number of issues related to privacy. In this paper, we propose a framework for raising the awareness of Online Social Network (OSN) users with respect to the information about them that is disclosed and that can be inferred by OSN service operators as well as by third parties that can access their data. This framework takes the form of a semantic, hierarchical scoring structure, that enables users to easily browse over different privacy-related aspects of their presence in a social network. Contrary to previous privacy scoring approaches, the proposed framework provides a finer and more intuitive organization of privacy information. Importantly, it also takes into account both information that is explicitly mentioned in users' shared content, as well as implicit information, that may be inferred from it. We make available an open source implementation of the framework.
In Silico Identification and Experimental Validation of Insertion–Deletion Polymorphisms in Tomato Genome

Comparative analysis of the genome sequences of Solanum lycopersicum variety Heinz 1706 and S. pimpinellifolium accession LA 1589 using MUGSY software identified 145 695 insertion–deletion (InDel) polymorphisms. A selected set of 3029 candidate InDels (≥2 bp) across the entire tomato genome were subjected to PCR validation, and 82.4% could be verified. Of 2272 polymorphic InDels between LA 1589 and Heinz 1706, 61.6, 45.2, and 31.6% were polymorphic in 8 accessions of S. pimpinellifolium, 4 accessions of S. lycopersicum var. cerasiforme, and 10 varieties of S. lycopersicum, respectively. Genetic distance was 0.216 in S. pimpinellifolium, 0.202 in S. lycopersicum var. cerasiforme, and 0.108 in S. lycopersicum. The data suggested a reduction of genetic variation from S. pimpinellifolium to S. lycopersicum var. cerasiforme and S. lycopersicum. Cluster analysis showed that the 8 accessions of S. pimpinellifolium were in one group, whereas 4 accessions of S. lycopersicum var. cerasiforme and 10 varieties of S. lycopersicum were in the same group.
BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs

MOTIVATION Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50. RESULTS We propose a measure for quantitative assessment of genome assembly and annotation completeness based on evolutionarily informed expectations of gene content. We implemented the assessment procedure in open-source software, with sets of Benchmarking Universal Single-Copy Orthologs, named BUSCO. AVAILABILITY AND IMPLEMENTATION Software implemented in Python and datasets available for download from http://busco.ezlab. org. CONTACT evgeny.zdobnov@unige.ch SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Decomposed radio access network over deployed passive optical networks using coherent optical OFDM transceivers

In this paper, it is proposed to take advantage of the deployed passive optical network (PON) infrastructure by overlaying a decomposed radio access network (RAN) using a very dense WDM. Coherent optical orthogonal frequency-division multiplexing technology is investigated for achieving the desired narrow channel spacings while minimizing the impact on the performance of legacy equipment. A practical implementation is evaluated using simulations. Within the analyzed configurations, a trade-off is found between time-division multiplexed (TDM)-PON and RAN performance. The optimum balance is found for additional losses in the TDM-PON path of less than 1 dB, ensuring simultaneous service to a maximum of 145 metro cells together with the PON customers and within a reach of 24 km.
An ILP-based Worst-case Performance Analysis Technique for Distributed Real-time Embedded Systems

Finding a tight upper bound of the worst-case response time in a distributed real-time embedded system is a very challenging problem since we have to consider execution time variations of tasks, jitter of input arrivals, scheduling anomaly behavior in a multi-tasking system, all together. In this paper, we translate the problem as an optimization problem and propose a novel solution based on ILP (Integer Linear Programming). In the proposed technique, we formulate a set of ILP formulas in a compositional way for modeling flexibility, but solve the problem holistically to achieve tighter upper bounds. To mitigate the time complexity of the ILP method, we perform static analysis based on a scheduling heuristic to reduce the number of variables and confine the variable ranges. Preliminary experiments with the benchmarks used in the related work and a real-life example show promising results that give tight bounds in an affordable solution time.
Adaptive spectrum sensing for cognitive radios: An experimental approach

In order to avoid packet collisions in wireless communications, cognitive radio users require spectrum sensing to increase their awareness. Spectrum sensing methods must show good performance with low complexity, particularly in low-power wireless sensor networks. Motivated by the non-continuous signal patterns observed from realistic signals, an adaptive spectrum sensing algorithm that exploits information on the primary user traffic is proposed. The proposed method is based on a modified energy detector, which incorporates an estimate on the primary user occupancy. The performance of the proposed adaptive method is shown based on real ZigBee signal data obtained from a commercial transmitter, and a Universal Software Radio Peripheral (USRP) device where the spectrum sensing algorithms are executed. Our results show that this method is mostly useful in high occupancy environments with limited available free spaces. Knowledge on the primary user occupancy helps us to reduce the chance of having packet collisions and retransmissions based on a single spectrum occupation parameter, without additional statistical information. Furthermore, it allows us to decrease and adapt the spectrum sensing observation time to maintain a target performance, in terms of probability of detection and false alarm.
Investigations on the use of morpheme level features in Language Models for Arabic LVCSR

A major challenge for Arabic Large Vocabulary Continuous Speech Recognition (LVCSR) is the rich morphology of Arabic, which leads to high Out-of-vocabulary (OOV) rates, and poor Language Model (LM) probabilities. In such cases, the use of morphemes rather than full-words is considered a better choice for LMs. Thereby, higher lexical coverage and less LM perplexities are achieved. On the other side, an effective way to increase the robustness of LMs is to incorporate features of words into LMs. In this paper, we investigate the use of features derived for morphemes rather than words. Thus, we combine the benefits of both morpheme level and feature rich modeling. We compare the performance of stream-based, class-based and Factored LMs (FLMs) estimated over sequences of morphemes and their features for performing Arabic LVCSR. A relative reduction of 3.9% in Word Error Rate (WER) is achieved compared to a word-based system.
Domain and Language Independent Feature Extraction for Statistical Text Categorization

A generic system for text categorization is presented which uses a representative text corpus to adapt the processing steps: feature extraction, dimension reduction, and classification. Feature extraction automatically learns features from the corpus by reducing actual word forms using statistical information of the corpus and general linguistic knowledge. The dimension of feature vector is then reduced by linear transformation keeping the essential information. The classification principle is a minimum least square approach based on polynomials. The described system can be readily adapted to new domains or new languages. In application, the system is reliable, fast, and processes completely automatically. It is shown that the text categorizer works successfully both on text generated by document image analysis - DIA and on ground truth data.
Differential Privacy for Probabilistic Systems ∗

Differential privacy is a promising approach to privacy-preserving data analysis. There is now a well-developed theory of differentially private functions. Despite recent work on implementing database systems that aim to provide differential privacy and distributed systems that use differential privacy as a basis for higher level security properties, there is no formal theory of differential privacy for systems. In this paper, we formulate precise definitions of differential privacy within a formal model of probabilistic systems, relate these definitions to the original definitions, and develop a proof technique based on an unwinding relation for establishing that a given system achieves this privacy definition. We illustrate the proof technique on a representative example motivated by an implemented system.