Miracle-dz/UniFAR-FTUs huggingface dataset:
Constrained Control of Linear Systems Subject to Combinations of Intersections and Unions of Concave Constraints

The explicit reference governor (ERG) is an add-on unit that provides constraint handling capabilities to pre-stabilized systems. In particular, the ERG acts on the reference of the pre-stabilized system in such a way that, even for large transients, constraints are satisfied. A standard way to build an ERG is to translate state and input constraints into a constraint on the value of the Lyapunov function associated to the currently applied reference. The main challenge of this approach is the determination of the largest reference-dependent Lyapunov level set that ensures constraint satisfaction. In general, the optimization problem to compute such a level set is non-convex. This letter proposes a novel systematic approach for designing an ERG for linear systems subject to combinations of intersections and unions of concave constraints. More precisely, first, it is shown that the solution of the stated non-convex problem can be approximated by solving multiple convex problems (one convex optimization problem for each constraint) and then suitably combining their solutions. Then, since these convex problems do not admit a closed-form solution, a virtual continuous-time system is proposed to estimate their solutions. Finally, an upper-bound for the estimation error is provided analytically, and a procedure is proposed to increase the robustness of the ERG against estimation errors. The effectiveness of the proposed scheme is demonstrated on a simulated case study.
Adoption of PERILIPIN as a unifying nomenclature for the mammalian PAT-family of intracellular lipid storage droplet proteins

The PAT family of proteins has been identified in eukaryotic species as diverse as vertebrates, insects, and amebazoa. These proteins share a highly conserved sequence organization and avidity for the surfaces of intracellular, neutral lipid storage droplets. The current nomenclature of the various members lacks consistency and precision, deriving more from historic context than from recognition of evolutionary relationship and shared function. In consultation with the Mouse Genomic Nomenclature Committee, the Human Genome Organization Genomic Nomenclature Committee, and conferees at the 2007 FASEB Conference on Lipid Droplets: Metabolic Consequences of the Storage of Neutral Lipids, we have established a unifying nomenclature for the gene and protein family members. Each gene member will incorporate the root term PERILIPIN (PLIN), the founding gene of the PAT family, with the different genes/proteins numbered sequentially.
Invited Paper: Edge and Fog Computing: Vision and Research Challenges

Recently, the wide adoption of Internet of Things (IoT) devices has introduced new challenges that the current cloud-centric approach must overcome. The high-latency obtained from sending daily massive volumes of generated data to the cloud, for further processing, is insufficient to meet the stringent requirements of emerging IoT applications. As a consequence, researchers have introduced new paradigms, like edge and fog computing, with the purpose of extending cloud capabilities closer to the edge of the network. This extension of the cloud enables IoT applications to be deployed in the proximity of sensors, adding new benefits like fast response time and better security and privacy. In this paper, we discuss in detail both paradigms based on their individual characteristics and use cases. Furthermore, we explain what future challenges, i.e., resource management, security and privacy, and network management, researches must solve to enable the adoption in society. Finally, we present our vision regarding a smart city scenario in which users have the possibility of customizing their environment as they desire, by seamlessly downloading applications on a personal edge network.
A 12.5-Gb/s 4.8-mW Full-Rate CDR with Low-Power Sample-and-Hold Linear Phase Detector

This paper presents a low-power low-jitter full-rate linear phase detector based clock and data recovery circuit (CDR). The proposed sample-and-hold linear phase detector (SHLPD) can reduce the complexity of the conventional SHLPD to save power consumption. This CDR is designed and implemented in 40-nm CMOS process with 0.9-V supply. The simulation results show that it can operate at data rate of 12.5 Gb/s with the power consumption of 4.8 mW. The simulated peak-to-peak jitter of the recovered data and clock is 4.96 ps and 4.64 ps, respectively, with 12.5-Gb/s input data rate.
Video to Text Study using an Encoder-Decoder Networks Approach

The automatic generation of video description is currently a topic of interest in computer vision due to applications such as web indexation, video description for people with visual disabilities, among others. In this work we present a Neural Network architecture Encoder-Decoder. First, a Convolutional Neural Network 3D extracts the features of the input video. Then, an Long Short-Term Memory decodes the vector to automatically generate the description of the video. To perform the training and testing we use the Microsoft Video Description Corpus data set (MSVD). Evaluate the performance of our system using the challenge of COCO Image Captioning Challenge. We obtain as results 0.3984, 0.2941 and 0.5052 for the BLEU, METEOR and CIDEr metrics respectively. Competitive results compared with certificates in the bibliography.
Potential role of miR-139-5p in cancer diagnosis, prognosis and therapy

MicroRNAs (miRNAs) are short non-coding RNAs that regulate the expression of protein-coding genes by partially binding to specific target sites of mRNAs. miRNAs perform important functions in complicated cellular biological processes and their abnormal expression is involved in various disorders, including cancer. Among the miRNAs, differential expression of miR-139-5p serves a significant role in tumorigenesis, metastasis and recurrence, thus suggesting that it may potentially be used as a promising biomarker for cancer diagnosis, prognosis and therapy. miR-139-5p is expected to serve as a biomarker to eventually be implemented in a clinical setting. In the present review, we focus on the importance of miR-139-5p in cancer, summarize the association between miR-139-5p expression level and diagnosis and prognosis, and discuss the potential therapeutic implications for the future.
Trajectories and Camera Motion Compensation in Aerial Videos

This paper presents a method for trajectory extraction in videos acquired with a slightly moving camera. Trajectories are initialized at Shi-Tomasi [1] feature points and tracked thanks to the Lucas-Kanade [2] algorithm from the openCV library [3]. New feature points are regularly introduced to compensate for track losses and to handle newly appeared objects. A simple and fast method for camera motion compensation has been implemented, using the fact that near static scene points undergo an equal translation between any two images. Local histograms of displacement normally exhibit a clear peak since our application considers scenes with relatively few moving targets. These peaks designate which tracks and thus which points are best to estimate the homographies representing motion between frames of the sequence. Tracking results for pedestrian and vehicles with camera motion compensation are shown and discussed for two test cases with different environment, scenario and different video quality. The usefulness of camera motion compensated trajectories is demonstrated by an example of target classification based on track maximal speed and possible hotspot detection from long track pauses.
Pitch Synchronized Relative Phase with Peak Error Detection For Noise-robust Speaker Recognition

In conventional speaker identification methods based on mel-frequency cepstral coefficients (MFCCs), phase information is ignored. Recent studies have shown that phase information contains speaker dependent characteristics, and it is effective for speaker recognition. In this paper, we propose a pitch synchronized relative phase information for speaker identification in noisy environments. To mitigate the affect of noise on pseudo pitch synchronized relative phase information extraction, a peak error detection using an autocorrelation based algorithm was proposed. Experiments were conducted using the JNAS (Japanese Newspaper Article Sentence) database. The pitch synchronized relative phase information with peak error detection based method achieved a relative speaker identification error reduction rate of 23.9% compared to the conventional phase information (that is pitch non-synchronized relative phase). By combining the proposed method with MFCC, the speaker identification rate was improved from 55.0% (MFCC) to 76.9%.
A Method for Discovering and Obtaining Company Hot Events from Internet News

With the rapid development and popularization, Internet is becoming the most convenient way to publish and obtain information, which causes an extremely increasing quantity and variety of data. It is difficult to find out potentially valuable information from these data, which is the primary problem of data mining. Mining company hot events from Internet news can effectively reflect how its business works. Thus, we propose a method for discovering and obtaining hot events from Internet news. In the proposed method, we use Gaussian kernel to update clustering center instead of global cluster to modify Single-Pass clustering algorithm. It is a dynamic incremental clustering algorithm which does not need to initialize the number of clusters. Then, Top-N hot events can be obtained through the clustering centers. Experimental comparison shows that the improved algorithm has higher clustering efficiency than the classic algorithm. Case studies from Shanghai pilot free-trade zone (FTZ) also show the effectiveness of our proposed method.
NUS-HLT Spoken Lyrics and Singing (SLS) Corpus

Despite speech-to-singing (STS) voice conversion has been widely studied, a large database for this task has not been constructed yet. We present a new Spoken Lyrics and Singing (SLS) corpus developed at NUS-HLT that can be useful for STS. In this work, the details of this database is reported that contains 3,058 utterances of 90 English songs from 10 professional singers collected in a recording studio environment. The spoken lyrics corresponding to the songs are also recorded from the singers to create the database, which we refer to as NUS-HLT SLS corpus. A comparison of spoken lyrics and singing speech from different speakers and the challenges associated with STS are discussed. We then highlight a few potential applications where this corpus can be used for future studies.
The effect of mating behavior and temperature variation on the critical population density of a freshwater copepod

At low density, population growth rates of dioecious zooplankton depend on the encounter rate of potential mates, resulting in a demographic Allee effect and a critical density for population establishment and persistence. Empirical evidence confirms a critical density for the calanoid copepod Hesperodiatomus shoshone, but existing estimates of the critical density span an order of magnitude. Combining three‐dimensional video analysis of mating behavior with life history data from natural populations we estimated H. shoshone critical density to be 0.44–1.44 m−3. The critical density was highly dependent on body size, primarily as a result of the latter's influence on swimming speed. Swimming speed also depended on temperature, increasing > 25% as temperature increased from 5°C to 16°C. Rapid swimming (1.25–2.4 cm s−1) and the ability to follow pheromone trails greatly improved the ability of H. shoshone to find mates. The large effect of temperature on mating behavior means that environmental variation can have a major effect on critical density and indicates that recovery or colonization events may be more likely to succeed in warmer lakes and/or warmer years. Considering the potential for critical densities to vary with environmental conditions is important for understanding how these thresholds determine population establishment and persistence in sexually reproducing aquatic organisms and other populations subject to Allee effects.
Understanding the unbalanced-voltage problem in wind turbine generation

Most wind turbines are equipped with line-connected induction generators. Induction generators are very attractive as wind turbine generators due to their low cost, ruggedness, and the need for little or no maintenance. At constant frequency, the induction generator operates in a small range of speeds and, therefore, it operates with a small range of slips with respect to synchronous speed. Compared to a synchronous generator, an induction generator provides lower stiffness, thus alleviating the mechanical stress. In a weak power system network, an unbalanced load at the distribution lines can cause unbalanced voltage conditions. If an induction generator is connected to an unbalanced voltage, the resulting stator current will be unbalanced. The unbalanced current creates unequal heating (hot spots) on the stator winding. The heat may increase the winding temperature, which degrades the insulation of the winding, i.e., the life expectancy of the winding. Unbalanced currents also create torque pulsation on the shaft resulting in audible noise and extra mechanical stress. This paper explores the unbalanced voltage problem in an induction generator. The levels of unbalance and the loads are varied. Experimental and predicted results are presented in this paper.
Winter Wheat Production Potential Simulation in Central and Southern Hebei Based on Process Model

In this paper, for the four research sites, Sanhe, Dingxing, Gaocheng and Quzhou, in central and southern Hebei, crop growth simulation model method is applied and five major varieties' temperature and light production potential and rain-fed production potential in 49 years from 1959 to 2007 are simulated. The results show that temperature and light production potentials of Han 6172 and Shixin 828 are higher than those of the other three varieties, and the production potentials of temperature and light from high to low are Gaocheng, Quzhou, Dingxing and Sanhe. There are significant differences in production potential of temperature and light among different varieties and different years in various sites. However there is no significant difference in the interaction between sites and varieties. Taking natural precipitation as water source, production potential difference in different years is very significant. Sites and varieties have great influence on the potential of rain-fed production. Therefore, it is necessary to select wheat varieties suitable for local natural conditions under rain-fed condition.
Unusable Spoken Response Detection with BLSTM Neural Networks

Voice biometrics has been applied to enhance the security of spoken language proficiency tests and ensure valid test scores by detecting fraudulent activity. These methods can, however, be triggered by certain distortions, including background noise and adjacent test-takers, resulting in false positive alarms. In this paper, a two-layer bi-directional LSTM RNN model is employed to detect these distorted (unusable) responses and a sub-sampling method is applied to reduce the difficulties of model training caused by very long input sequence and imbalanced training data. The system is evaluated on a corpus that was collected from an assessment of English language proficiency around the world. Results show that our approach significantly outperforms two baselines: a Gaussian mixture model (GMM) classifying frame-level features and an AdaBoost classifier operating on i-vectors. Our system’s F-score in unusable response detection is 0.60 compared to 0.43 and 0.49 for the two baseline systems.
An artifact for client-side cryptographic operations

Nowadays one of the web browsers constraints is their limited capacity for interaction with end-user physical cryptographic devices, such as smart cards and cryptographic tokens. For this reason, in this article, we present an artifact that provides to web applications the ability to perform asymmetric cryptographic operations on the client-side using these devices. The artifact, designed as a service, presents two functions: (1) creation of electronic signatures of electronic documents and (2) electronic authentication of users into websites. It was designed with the purpose of allowing web developers to perform integrations in a simple and fast way. Through an empirical evaluation, in a controlled experiment, short-time integration was evidenced, confirming its potential usefulness for web developers.
Multi-subject Continuous Emotional States Monitoring by Using Convolutional Neural Networks

Tracking of emotional states is very important for building intelligent systems, to have an efficient human-machine interaction and have a better understanding of human behavior. Nevertheless, most of the state-of-the-art works in emotion recognition employ complex algorithms, which are difficult to implement in real-time on devices with low computational resources. This work emphasizes on fast and effective techniques in order to efficiently recognize facial expressions. In this regard, we propose a fast face recognition model based on Local Binary Pattern operator and a straightforward Convolutional Neural Network for emotion classification. The results of our recognition system show an accuracy of 66.5% in the FER2013 wild dataset, which is near to state-of-the-art techniques but uses by far less computational resources.
Automatic Image Annotation Using Random Projection in a Conceptual Space Induced from Data

The main drawback of a detailed representation of visual content, whatever is its origin, is that significant features are very high dimensional. To keep the problem tractable while preserving the semantic content, a dimensionality reduction of the data is needed. We propose the Random Projection techniques to reduce the dimensionality. Even though this technique is sub-optimal with respect to Singular Value Decomposition its much lower computational cost make it more suitable for this problem and in particular when computational resources are limited such as in mobile terminals. In this paper we present the use of a “conceptual” space, automatically induced from data, to perform automatic image annotation. Images are represented by visual features based on color and texture and arranged as histograms of visual terms and bigrams to partially preserve the spatial information [1]. Using a set of annotated images as training data, the matrix of visual features is built and dimensionality reduction is performed using the Random Projection algorithm. A new unannotated image is then projected into the dimensionally reduced space and the labels of the closest training images are assigned to the unannotated image itself. Experiments on large real collection of images showed that the approach, despite of its low computational cost, is very effective.
An Efficient Negative Correlation Gravitational Search Algorithm

Gravitational search algorithm (GSA) is known as an effective optimization algorithm based on population. To further improve the performance of GSA, taking the combination of diversified search mechanisms into consideration would be a constructive solution for increasing the possibility of obtaining global optimum. In the meantime, the negative correlation search (NCS) algorithm has proven its ability of maintaining diversity effectively to develop the population. Thus, with such inspiration, an improved gravitational search algorithm based on negative correlation learning is proposed in this paper. While gravitational search conducts exploitation in the search space, negative correlation fulfills exploration by encouraging discrepant search behaviors to increase the optimization accuracy. The superiority of the proposed algorithm is demonstrated with experimental results based on several benchmark functions in comparison with its component algorithms.
A 76-81GHz High-linearity CMOS Receiver Front-end for Automotive Radar

a 76-81 GHz receiver (Rx) front-end is implemented in 65-nm COMS for automotive radar. The front-end consists of a low noise amplifier (LNA), an interstage network with two-stage transformer, and a mixer core with transconductance (Gm) stage and quad-switch. Flyback transformer-feedback technique is adopted for the three-stage common source (CS) LNA. Traditional Gilbert-mixer is improved by inset a transformer balun between Gm stage and switch stage. Therefore, high-linearity performance can be achieved. The Rx front-end consumes 22mW and the input 1dB compression point (P1dB) is - 15.5 dBm at 80 GHz. The conversion gain (CG) is 8.5-11.5 dB at 76-81 GHz, while noise figure is 7.2-8.7 dB. The chip size is only 0.23 mm2 excluding PADs.
APRImora: A Semantic Architecture for Patterns Reuse

Software patterns are computing artifacts used to document knowledge that may be reused during software development process. There are several types of patterns, such as analysis, design, and architectural, among others. Design patterns are the most well known by designers, but many of them are described in books and scientific papers, a recurring way of documenting patterns that limits their reuse potential. Aiming to not only minimize this limitation but also provide ways of recovering contextualized knowledge in these patterns, the present paper presents the architecture APRImora, an extension based on Semantic Web of the Analysis Patterns Reuse Infrastructure (APRI). In this architecture, the patterns are documented by metadata defined as application profiles of the Dublin Core standard and stored in the RDF format, allowing them to be discovered by search engines. The APRImora architecture helps designers discover and reuse software patterns based on semantic relations, which favors their dissemination and reuse.
Retrieval of Facial Images Re-rendered with Natural Aging Effect using Child Facial Image and Age

We represent face progression and face regression on the children face image dataset containing 8581 faces images in the age group [2 : 20] years. This dataset contains 4789 and 3792 images of boys and girls respectively. To generate the images we have used a generative approach such that we don't require pair models (more than 2 images of a person with age difference of 1 or more). In addition to regression and progression, we have compared the ground truth with the regressed or progressed images. These progressed or regressed images can be used to trace and identify children lost at the young age as a victim of child trafficking or abduction.