Miracle-dz/UniFAR-FTUs huggingface dataset:
Fingerprint Recognition with Identical Twin Fingerprints

Fingerprint recognition with identical twins is a challenging task due to the closest genetics-based relationship existing in the identical twins. Several pioneers have analyzed the similarity between twins' fingerprints. In this work we continue to investigate the topic of the similarity of identical twin fingerprints. Our study was tested based on a large identical twin fingerprint database that contains 83 twin pairs, 4 fingers per individual and six impressions per finger: 3984 (83*2*4*6) images. Compared to the previous work, our contributions are summarized as follows: (1) Two state-of-the-art fingerprint identification methods: P071 and VeriFinger 6.1 were used, rather than one fingerprint identification method in previous studies. (2) Six impressions per finger were captured, rather than just one impression, which makes the genuine distribution of matching scores more realistic. (3) A larger sample (83 pairs) was collected. (4) A novel statistical analysis, which aims at showing the probability distribution of the fingerprint types for the corresponding fingers of identical twins which have same fingerprint type, has been conducted. (5) A novel analysis, which aims at showing which finger from identical twins has higher probability of having same fingerprint type, has been conducted. Our results showed that: (a) A state-of-the-art automatic fingerprint verification system can distinguish identical twins without drastic degradation in performance. (b) The chance that the fingerprints have the same type from identical twins is 0.7440, comparing to 0.3215 from non-identical twins. (c) For the corresponding fingers of identical twins which have same fingerprint type, the probability distribution of five major fingerprint types is similar to the probability distribution for all the fingers' fingerprint type. (d) For each of four fingers of identical twins, the probability of having same fingerprint type is similar.
FIN10K: A Web-based Information System for Financial Report Analysis and Visualization

In this demonstration, we present FIN10K, a web-based information system that facilitates the analysis of textual information in financial reports. The proposed system has three main components: (1) a 10-K Corpus, including an inverted index of financial reports on Form 10-K, several numerical finance measures, and pre-trained word embeddings; (2) an information retrieval system; and (3) two data visualizations of the analyzed results. The system can be of great help in revealing valuable insights within large amounts of textual information. The system is now online available at http: //clip.csie. org/10K/.
Novel approach for real time detection and classification based on template matching in video

In this paper, we present a new approach for the detection and classification of real time road signs from video. The proposed system is composed of two processing stages: detection and classification signs. The system has detected road signs by color and shape feature of segmentation color in HSV color space, especially red and blue. The detected signs are then classified by method template matching, such as circular, squared and triangular shapes. The road signs are classified in one of the following categories by Combining color and information about shape: danger, obligation, prohibition or information. As proposed system input is a video with a resolution of 1360×800 pixels. For detection phase road signs, has a high detection performance up to 92 % and for classification is rated 96% in our experiments. The proposed system also proves to be reliable and suitable for real-time processing.
PKU-IDM @TRECVID2011 CBCD: Content-Based Copy Detection with Cascade of Multimodal Features and Temporal Pyramid Matching

Content-based copy detection (CBCD) is drawing increasing attention from both academia and industry as an alternative technology to watermarking for video identification and copyright protection. In this paper, we pre-sent a comprehensive method for detecting copies subjected to complicated transformations in a large video corpus. Basically, two core techniques are employed by our method. One is multimodal feature representation organized in a cascade architecture, which exploits the complementary characteristics of audio features, global and local visual features to keep robust to a wide range of transformations and meanwhile preserves efficiency as far as possible. The other is Temporal Pyramid Matching (TPM), which fuses frame-level similarity search re-sults into sequence-level matching results. We have submitted two runs, i.e. “PKU-IDM.m. balanced.cascade” & “PKU-IDM.m. nofa.cascade”. Official results demonstrate that the proposed approach achieved excellent NDCR and competitive Mean F1 at the cost of median Processing Time.
Formal verification of reconfigurable cores

We show how a formal verification methodology can complement conventional verification for the development of FPGA-based cores. As FPGAs become larger, there is a greater reliance on shrink-wrapped intellectual property. In particular, customers expect rigorous verification of the cores that they purchase. We report on positive experience of using formal verification to facilitate the development of real cores. We then show how formal verification has a special role to play during the dynamic reconfiguration of cores.
Face Recognition Using 3 D and 2 D Data

We have collected a large data set of iris images, intentionally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek. We have modified the iris segmentation stage of the algorithm to improve recognition performance, and experimentally verified the improvement using the collected dataset.
Circuit techniques for reducing the effects of op-amp imperfections: autozeroing, correlated double sampling, and chopper stabilization

In linear IC's fabricated in a low-voltage CMOS technology, the reduction of the dynamic range due to the dc offset and low frequency noise of the amplifiers becomes increasingly significant. Also, the achievable amplifier gain is often quite low in such a technology, since cascoding may not be a practical circuit option due to the resulting reduction of the output signal swing. In this paper, some old and some new circuit techniques are described for the compensation of the amplifier's most important nonideal effects including the noise (mainly thermal and 1/f noise), the input-referred dc offset voltage as well as the finite gain resulting in a nonideal virtual ground at the input.
Community Structure of Denitrifiers, Bacteria, and Archaea along Redox Gradients in Pacific Northwest Marine Sediments by Terminal Restriction Fragment Length Polymorphism Analysis of Amplified Nitrite Reductase (nirS) and 16S rRNA Genes

ABSTRACT Steep vertical gradients of oxidants (O2 and NO3−) in Puget Sound and Washington continental margin sediments indicate that aerobic respiration and denitrification occur within the top few millimeters to centimeters. To systematically explore the underlying communities of denitrifiers,Bacteria, and Archaea along redox gradients at distant geographic locations, nitrite reductase (nirS) genes and bacterial and archaeal 16S rRNA genes (rDNAs) were PCR amplified and analyzed by terminal restriction fragment length polymorphism (T-RFLP) analysis. The suitablility of T-RFLP analysis for investigating communities of nirS-containing denitrifiers was established by the correspondence of dominant terminal restriction fragments (T-RFs) of nirS to computer-simulated T-RFs ofnirS clones. These clones belonged to clusters II, III, and IV from the same cores and were analyzed in a previous study (G. Braker, J. Zhou, L. Wu, A. H. Devol, and J. M. Tiedje, Appl. Environ. Microbiol. 66:2096–2104, 2000). T-RFLP analysis ofnirS and bacterial rDNA revealed a high level of functional and phylogenetic diversity, whereas the level of diversity ofArchaea was lower. A comparison of T-RFLPs based on the presence or absence of T-RFs and correspondence analysis based on the frequencies and heights of T-RFs allowed us to group sediment samples according to the sampling location and thus clearly distinguish Puget Sound and the Washington margin populations. However, changes in community structure within sediment core sections during the transition from aerobic to anaerobic conditions were minor. Thus, within the top layers of marine sediments, redox gradients seem to result from the differential metabolic activities of populations of similar communities, probably through mixing by marine invertebrates rather than from the development of distinct communities.
Discrimination of Motion Direction in a Robot Using a Phenomenological Model of Synaptic Plasticity

Recognizing and tracking the direction of moving stimuli is crucial to the control of much animal behaviour. In this study, we examine whether a bio-inspired model of synaptic plasticity implemented in a robotic agent may allow the discrimination of motion direction of real-world stimuli. Starting with a well-established model of short-term synaptic plasticity (STP), we develop a microcircuit motif of spiking neurons capable of exhibiting preferential and nonpreferential responses to changes in the direction of an orientation stimulus in motion. While the robotic agent processes sensory inputs, the STP mechanism introduces direction-dependent changes in the synaptic connections of the microcircuit, resulting in a population of units that exhibit a typical cortical response property observed in primary visual cortex (V1), namely, direction selectivity. Visually evoked responses from the model are then compared to those observed in multielectrode recordings from V1 in anesthetized macaque monkeys, while sinusoidal gratings are displayed on a screen. Overall, the model highlights the role of STP as a complementary mechanism in explaining the direction selectivity and applies these insights in a physical robot as a method for validating important response characteristics observed in experimental data from V1, namely, direction selectivity.
UBML participation to CLEF eHealth IR challenge 2015: Task 2

This paper describes the participation of UBML, a team composed with members of the Department of Computer Science, Uni- versity of Botswana, to the biomedical information retrieval challenge proposed in the framework of CLEF eHealth 2015 Task 2. For this rst participation, we are evaluating the eectiveness of two dierent query expansion strategies when searching for health related content on the web. In particular, we deploy pseudo relevance feedback, where the orig- inal query is expanded with additional terms selected from the local col- lection (collection being searched). In another approach, we deploy the collection enrichment approach, where the original query is expanded with additional terms from an external collection (collection not being searched). We test the generality of our results by using two dierent methods for selecting the expansion terms. In particular, we used the Kullback-Liebler Divergence and the Bose-Einstein 1 (Bo1) model to select the expansion terms. Our result show that we can improve the re- trieval eectiveness of our system by expanding the original query with additional terms from a local collection. Furthermore, our results suggest that, when using an external collection to expand the original query, it is important to select the expansion terms from a health related external collection when searching for health related content on the web.
Consistent Map Building by a mobile robot euipped with stereo sensor and lrf

This paper presents an efficient map building technique for indoor mobile robot navigation based on laser range finder and binocular stereo vision sensors. To effectively incorporate different sensors and deal with measurement uncertainty involved in environment perception, this article presents a local map integration approach in which Bayesian filter based dynamic occupancy grid map modeling techniques are employed. The adopted method is discussed in the context of mobile robot Simultaneous Localization and Map-Building (SLAM). In SLAM routine, the integrated local map is utilized as observation input, and Rao-Blackwellized Particle Filter (RBPF) is used for refining location estimation and generating accurate global map. Advantages of our proposal are validated by real experimental results carried on Pioneer robot.
Automatic detection and recognition of traffic signs

Automatic detection of road sign is a challenging but demanding job. A new approach namely automatic detection and recognition of traffic signs (ADRTS) considering color segmentation, moment invariants, and neural networks has been proposed in this paper. Experimental result proves the superior performance in the detection and recognition of road signs. Computational time complexity is also quite low that makes it applicable for the real time system.
Modelling Planning and Interaction in the Framework of Human Cooperative Problem Solving

This article deals with a human model of cooperative problem solving based on a psychological experimentation.Ourmain goal is to improve the design of openmultiagent systems able to interact with human beings.Weaim at analyzing, modelling and simulating human capabilities of planning and interacting in a cooperative problem solving context. Our planning model uses the BDI concepts extended with the notions of phases, states of mind, strategies and tactics. Our interaction model is twofold: 1) it is based on the Speech Act theory to represent the utterances; 2) it uses a discourse model, represented by timed automata, to describe the dynamics of human conversations. This paper goes on to present an original architecture called BDIggy where interaction and planning are linked homogeneously.
An Anomaly Detection Model for Ultra Low Powered Wireless Sensor Networks Utilizing Attributes of IEEE 802.15.4e/TSCH

The rapid growth in sensors, low-power integrated circuits, and wireless communication standards has enabled a new generation of applications based on ultra-low powered wireless sensor networks. These are employed in many environments including health-care, industrial automation, environmental monitoring and intelligent transportation. Furthermore, a significant portion of low powered data requires a certain type of security that offers higher availability, confidentiality and data integrity. The objective of this work is to investigate the feasibility of using attributes of IEEE 802.15. 4e/TSCH and machine learning techniques to determine traffic anomalies in ultra-low powered wireless networks. Several factors including the sample size, noise influence, classification algorithm and model aging process are investigated against prediction accuracy and other performance indicators. The experiments have demonstrated that machine learning models trained using carefully selected input features and adequate training data are able to detect traffic anomalies of low powered wireless networks with remarkable accuracy (over 95 percent), while keeping the false positive and negative rates to minimum.
Limited intra-word transition codes: an energy-efficient bus encoding for LCD display interfaces

We propose a class of low-power codes, called Limited Intra-Word Transition (LIWT) codes, suitable for the digital interface to Liquid Crystal Displays (LCD). The proposed technique exploits the existing inter-pixel correlation of typical images, by transmitting an encoded representation of the difference between adjacent pixels. Since all standard LCD transmission protocols are serial, the LIWT specifically targets the minimization of intra-word transitions. The application of the encoding to a series of standard images resulted in transitions savings over 60% on average with respect to two standard TMDS and LVDS protocols.
Expert predictions of changes in vegetation condition reveal perceived risks in biodiversity offsetting

Biodiversity offsetting typically involves the trade of certain losses of habitat with uncertain future conservation benefits. Predicting the latter requires estimates of two outcomes; the biodiversity losses without conservation management (averted loss), and the biodiversity gains with conservation management (management gain). However, because empirical data to inform these estimates are limited, they are normally guided by expert opinion, often derived via unstructured methods without consideration of uncertainty. Here we used a structured elicitation with 29 experts to gather estimates of averted loss and management gain at offset sites. We used two methods; (i) experts estimated change in an aggregate biodiversity value (vegetation condition) and; (ii) experts provided probabilistic estimates of change for individual vegetation condition attributes, such as the richness and cover of plant growth forms. On average, experts predicted there would be only modest improvements with conservation management, yet uncertainty and variation among experts was large; in some cases, conservation benefits were not predicted. Estimates of change in vegetation condition suggested that benefits were from both averted loss and management gains and were thought to most likely arise in cases where starting condition was low to moderate. Similar patterns were observed for individual vegetation condition attributes, with management gains, relative to a reference, tending to be negatively correlated with starting value. Our study finds that: (i) on average, gains at offset sites are expected to be small, (ii) at many sites, experts do not believe gains can be obtained, and (iii) experts’ opinions can be divergent resulting in elevated levels of uncertainty. The potential for losses under conservation management highlights the need to: identify those components of biodiversity most likely to benefit from conservation management; better understand those situations when offset obligations are most likely to be met and conversely those situations with higher risk; and further develop offset mechanisms that encourage early or prior gains. These findings together with the global proliferation of biodiversity offsetting, provide a strong imperative to improve empirical data and investment in long-term, site-based monitoring of biodiversity outcomes at offset sites.
Integration of Transcriptional Repression and Polycomb-Mediated Silencing of WUSCHEL in Floral Meristems

The zinc-finger protein KNUCKLES integrates transcriptional repression with polycomb-mediated silencing of the floral stem cell determinant WUSCHEL. Arabidopsis (Arabidopsis thaliana) floral meristems terminate after the carpel primordia arise. This is achieved through the temporal repression of WUSCHEL (WUS), which is essential for stem cell maintenance. At floral stage 6, WUS is repressed by KNUCKLES (KNU), a repressor directly activated by AGAMOUS. KNU was suggested to repress WUS through histone deacetylation; however, how the changes in the chromatin state of WUS are initiated and maintained to terminate the floral meristem remains elusive. Here, we show that KNU integrates initial transcriptional repression with polycomb-mediated stable silencing of WUS. After KNU is induced, it binds to the WUS promoter and causes eviction of SPLAYED, which is a known activator of WUS and can oppose polycomb repression. KNU also physically interacts with FERTILIZATION-INDEPENDENT ENDOSPERM, a key polycomb repressive complex2 component, and mediates the subsequent deposition of the repressive histone H3 lysine 27 trimethylation for stable silencing of WUS. This multi-step silencing of WUS leads to the termination of floral stem cells, ensuring proper carpel development. Thus, our work describes a detailed mechanism for heritable floral stem cell termination in a precise spatiotemporal manner.
Individualized decision aid for diverse women with lupus nephritis (IDEA-WON): A randomized controlled trial

Background Treatment decision-making regarding immunosuppressive therapy is challenging for individuals with lupus. We assessed the effectiveness of a decision aid for immunosuppressive therapy in lupus nephritis. Methods and findings In a United States multicenter, open-label, randomized controlled trial (RCT), adult women with lupus nephritis, mostly from racial/ethnic minority backgrounds with low socioeconomic status (SES), seen in in- or outpatient settings, were randomized to an individualized, culturally tailored, computerized decision aid versus American College of Rheumatology (ACR) lupus pamphlet (1:1 ratio), using computer-generated randomization. We hypothesized that the co-primary outcomes of decisional conflict and informed choice regarding immunosuppressive medications would improve more in the decision aid group. Of 301 randomized women, 298 were analyzed; 47% were African-American, 26% Hispanic, and 15% white. Mean age (standard deviation [SD]) was 37 (12) years, 57% had annual income of <$40,000, and 36% had a high school education or less. Compared with the provision of the ACR lupus pamphlet (n = 147), participants randomized to the decision aid (n = 151) had (1) a clinically meaningful and statistically significant reduction in decisional conflict, 21.8 (standard error [SE], 2.5) versus 12.7 (SE, 2.0; p = 0.005) and (2) no difference in informed choice in the main analysis, 41% versus 31% (p = 0.08), but clinically meaningful and statistically significant difference in sensitivity analysis (net values for immunosuppressives positive [in favor] versus negative [against]), 50% versus 35% (p = 0.006). Unresolved decisional conflict was lower in the decision aid versus pamphlet groups, 22% versus 44% (p < 0.001). Significantly more patients in the decision aid versus pamphlet group rated information to be excellent for understanding lupus nephritis (49% versus 33%), risk factors (43% versus 27%), medication options (50% versus 33%; p ≤ 0.003 for all); and the ease of use of materials was higher in the decision aid versus pamphlet groups (51% versus 38%; p = 0.006). Key study limitations were the exclusion of men, short follow-up, and the lack of clinical outcomes, including medication adherence. Conclusions An individualized decision aid was more effective than usual care in reducing decisional conflict for choice of immunosuppressive medications in women with lupus nephritis. Trial registration Clinicaltrials.gov, NCT02319525.
Model-Based Segmentation of Cloud Structures In Satellite Image Sequences

Meteorological image sequences acquired with remote sensing devices contain huge amounts of available data featuring the temporal evolution of highly deformable and complex structures. In this study is presented a robust and effective model-based segmentation procedure for approximating highly deformable cloud structures. The whole image sequence may be viewed as a 3D data set, but the classical techniques for performing 3D segmentation are not meaningful here, because cloud structures are not shapes in the classical sense. The model-based segmentation presented here uses level-sets controlled by particle systems. A specific energy formulation is introduced, permitting the use of robust conjugate gradient techniques. The model is validated on a real meteorological image sequence. We outline the generalizations of the this particle system to perform image analysis tasks on truly 3D images.