Miracle-dz/UniFAR-FTUs huggingface dataset:
Real time google and live image search re-ranking

Nowadays, web-scale image search engines (e.g. Google, Live Image Search) rely almost purely on surrounding text features. This leads to ambiguous and noisy results. We propose to use adaptive visual similarity to re-rank the text-based search results. A query image is first categorized into one of several predefined intention categories, and a specific similarity measure is used inside each category to combine image features for re-ranking based on the query image. Extensive experiments demonstrate that using this algorithm to filter output of Google and Live Image Search is a practical and effective way to dramatically improve the user experience. A real-time image search engine is developed for on-line image search with re-ranking: http://mmlab.ie. cuhk.edu. hk/intentsearch
New SR Drive With Integrated Charging Capacity for Plug-In Hybrid Electric Vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance.
Traffic light detection with color and edge information

The concern of the intelligent transportation system rises and many driver support systems have been developed. In this paper, a fast method of detecting a traffic light in a scene image is proposed. By converting the color space from RGB to normalized RGB, some regions are selected as candidates of a traffic light. Then a method based on the Hough transform is applied to detect an exact region. Experimental results using images including a traffic light verifies the effectiveness of the proposed method.
Tunneling in III-V Nitrides

Tunnel diodes cater to a variety of applications ranging from memories to solar cells. We study the interband and intraband tunneling in III-V nitrides. The transmission coefficient is calculated for interband tunnel diode using WKB approximation by potential barrier method and E-k diagram. In order to get substantial amount of tunneling in resonant tunnel diodes from III-V nitrides we need flat band structure. We employ Vegard’s law along with bowing parameters to find polarization matched quaternary alloys which yield a flat band diagram at zero bias.
Mindfulness, job satisfaction and job performance: Mutualrelationships and moderation effect

Purpose of the article: This article examines the relationship between mindfulness, job satisfaction and job performance. Methodology/methods: We used a self-report job performance questionnaire, a job satisfaction scale from the Job Diagnostic Survey and the Czech version of the Five Facet Mindfulness Questionnaire. We excluded 8 items from the Five Facet Mindfulness Questionnaire Observing subscale following suggestions of other authors who measured mindfulness in a population without meditation experience. The sample consists of 241 Czech employees. We did not focused on employees with an experience with mindfulness training and/or meditation. Scientific aim: We examined the mutual relationships between all three variables while specifically focusing on mindfulness as a possible moderator in the relationship between job satisfaction and job performance. We also controlled the influence of neuroticism (NEO-FFI), job dynamicity and respondents’ sex. Findings: Job dynamicity, neuroticism and sex were weak predictors of job performance. Mindfulness had weak positive effect on job performance, too. However, mindfulness did not help to explain the variance in job performance beyond neuroticism, job dynamicity and sex. Mindfulness also had no relationship to job satisfaction. We did not find a significant relationship between job satisfaction and job performance and results did not support the hypothesis that mindfulness was a moderator of the relationship between job satisfaction and job performance. Conclusions: We extrapolate our findings to reflect on a potential utility of mindfulness training. For further research we would suggest exploring the relationship between mindfulness and job performance in an experiment using mindfulness training for individuals with a high level of neuroticism.
Music Cued Exercises for Motor and Non-Motor Signs in People with Dementia:Protocol for a Systematic Review

Background: Movement disorders and non-motor problems such as cognitive decline, anxiety, depression and behavioural problems, are common in people with dementia and can progress over time. Exercise coupled with music is a promising form of therapy designed to improve both the motor and non-motor manifestations of this debilitating neurological condition. Objectives: To present a protocol for a systematic review and critical analysis of the literature to answer the following questions: (i) Is music-cued exercise more effective than usual care for the treatment of motor and non-motor symptoms of dementia? (ii) What are the outcomes of music-cued exercise for people living with dementia? Methods: We provide the protocol for a systematic review and critical analysis of the literature using the PRISMA guidelines. Studies shall be reviewed that use music cued exercises aimed at improving the management of physical and non-physical problems associated with dementia. Eligibility criteria will be applied to the title and abstract of each citation as a first step followed by full text screening. Data extraction and quality appraisal are to be performed by two reviewers. Data sources: This protocol documents the comprehensive search strategy to be performed using MEDLINE, CINAHL, EMBASE, PSYCHINFO, PUBMED, SCOPUS and web of science databases. Science, technology and engineering databases will also be searched. Eligibility criteria: All study designs incorporating data will be included in this review. The following selection criteria shall be applied: • Participants will be people diagnosed with dementia, including Alzheimer’s disease, of any stage and severity, all ages, any range of co-morbidities, any medications. • Interventions will use rhythmic music with any physical exercise or rehabilitation program. • Outcomes shall include motor impairments such as gait, postural stability and general mobility. Studies considering non-motor signs such as anxiety, depression, behavioural disturbances and cognitive decline will also be included. Results: Evidence will be built from this review regarding the effectiveness of using music-cued exercises to optimise physical abilities and improve non-motor disorders in people with dementia. Conclusions: This protocol paper documents the methods that we shall use for a forthcoming systematic review. The knowledge obtained from the review will provide guidance to people with dementia, caregivers and clinicians by clarifying the strength of the evidence for music-cued movement rehabilitation.
RNA-CODE: A Noncoding RNA Classification Tool for Short Reads in NGS Data Lacking Reference Genomes

The number of transcriptomic sequencing projects of various non-model organisms is still accumulating rapidly. As non-coding RNAs (ncRNAs) are highly abundant in living organism and play important roles in many biological processes, identifying fragmentary members of ncRNAs in small RNA-seq data is an important step in post-NGS analysis. However, the state-of-the-art ncRNA search tools are not optimized for next-generation sequencing (NGS) data, especially for very short reads. In this work, we propose and implement a comprehensive ncRNA classification tool (RNA-CODE) for very short reads. RNA-CODE is specifically designed for ncRNA identification in NGS data that lack quality reference genomes. Given a set of short reads, our tool classifies the reads into different types of ncRNA families. The classification results can be used to quantify the expression levels of different types of ncRNAs in RNA-seq data and ncRNA composition profiles in metagenomic data, respectively. The experimental results of applying RNA-CODE to RNA-seq of Arabidopsis and a metagenomic data set sampled from human guts demonstrate that RNA-CODE competes favorably in both sensitivity and specificity with other tools. The source codes of RNA-CODE can be downloaded at http://www.cse. msu.edu/~chengy/RNA_CODE.
A Gabor direct fractional-step LDA algorithm for face recognition

Recently, a direct fractional-step linear discriminant analysis (DF-LDA) algorithm was proposed and successfully applied to face recognition (FR). However, the classification performance of DFT-LDA is degraded by the limitations of the direct linear discriminant analysis (D-LDA) used in DF-LDA. We describe a novel DF-LDA to solve this problem, and based on this novel DF-LDA, a novel Gabor DF-LDA (GDF-LDA), which directly applies the novel DF-LDA to the high-dimensional augmented Gabor feature vectors (AGFV) derived from the Gabor wavelet representation of face images, has been proposed for FR. The GDF-LDA not only is robust to facial variations, but also overcomes the limitations of the previous DF-LDA. The comparative results on the ORL database show that the GDF-LDA is more effective than existing FR methods.
Semi-supervised Learning Using Incremental Polynomial Classifier and Extreme Value Theory

The data in many real-world applications are streamed continuously which causes a variety of problems, e.g. Infinitely long data streams, concept drift, on-line or real-time classification and noise or outlier samples. To overcome these problems, the classifier should be updated continuously and it should have the ability to detect outliers. Since the size of the data set is growing with the duration of the data stream, the classifier should be updated incrementally without storing the whole training set. We present a polynomial classifier that efficiently detects the outliers using the extreme value theory in combination with confidence band intervals derived from regression techniques. All parameters are updated incrementally without requiring the old data. This approach makes the classifier suitable for on-line classification, since the processing time of the update is negligible with respect to the time required for processing the full training data set. In contrast to other novelty detection algorithms which work only with one-class systems, the proposed method can be applied in multi-class systems. The proposed algorithm is evaluated on an unbalanced multi-class gesture database. A comparison of the proposed method with the support vector data description classifier shows that it has superior properties.
Going Beyond Scrum Disciplined Agile Delivery By

today’s Scrum vision of agile so ware development to a disciplined agile solu on delivery. It begins with a brief overview of the agile so ware development movement and its implica ons. We then overview the Scrum method with its associated benefi ts and drawbacks, and then how to move beyond Scrum to a full delivery process framework called Disciplined Agile Delivery (DAD). DAD is a governed, hybrid approach that provides a solid foundaon from which to scale agile solu on delivery within enterprise-class organiza ons. The steps to do this are:
Design of Compact Directional Couplers for UWB Applications

This paper presents a simple design method for a class of compact couplers, which offer coupling in the range of 3-10 dB over an ultra-wide frequency band from 3.1 to 10.6 GHz. The proposed couplers are formed by two elliptically shaped microstrip lines, which are broadside coupled through an elliptically shaped slot. Their design is demonstrated for a 3-, 6-, and 10-dB coupling assuming a 0.508-mm-thick Rogers RO4003C substrate. Results of simulation and measurements show that the designed devices exhibit a coupling of 3plusmn1 dB, 6plusmn1.4 dB and 10plusmn1.5 dB across the 3.1-10.6-GHz band. This ultra-wideband coupling is accompanied by isolation and return loss in the order of 20 dB or better. The manufactured devices including microstrip ports occupy an area of 25 mm times 15 mm
Evaluation of User Interests with a Cloud Model

The main problems to represent the qualitative concept of "interest" lie in not only fuzziness but also randomness. Cloud model is a model of the uncertain transition between qualitative concept and its quantitative representation. Cloud model can describe randomness and fuzziness in a unified way. This paper analyzes which of the observed user behaviors can be taken as a source of implicit feedback to capture user interests. This paper provides a model based cloud theory for analyzing the correlation between user behaviors and user interests. The experiment shows the benefits of effectiveness, efficiency and flexibility of cloud model for expressing interests. Keywords-cloud model; user interests; uncertainty; qualitative; quantitative
Interaction effects of reward scheme and identity on budgetary slack: the perspective of morality

This research was basically to develop and examine the budgetary slack behavior with two different theories, namely agency theory and moral identity theory. Assumption of agency theory, self-interested behavior, explain how the behavior of budgetary slack arguments do. In many researchs, budgetary slack in research is perceived by many unethical acts, but in fact the budgetary slack is still being done. The development of non-instrumental research literature explains that procedural justice, distribution and identity become non istrumental argument which reduces the tendency of budgetary slack behavior. Moral dilemmas occured when someone is in the decision-making process that provides opportunities for the receipt of benefits. The need for a good identity, social identification, can control the self-interested behavior. Moral identity is the basis of social identification that is used by individuals to define themselves as individuals who own good moral identity. Cognitive theory and socio-cognitive theory explains how the moral behavior of individuals is formed, will be used to explain the formation of positive behavior of individuals when they are in a state of moral dilemmas. Internalization and symbolization are dimensions of moral identity measurement used in the development of hypotheses in this research. This research uses experimental methods to the preparation of the budget framework that gives tritmen for reward schemes and moral identity measure to explain the tendency of the individual performing the budgetary. GLM is used to provide empirical evidence of the reward system and the interaction effect of moral identity on behavior subject budgetary slack Keyword: Reward Scheme, Budgetary Slack and Moral Identity
DNA Vaccine Delivered by a Needle-Free Injection Device Improves Potency of Priming for Antibody and CD8+ T-Cell Responses after rAd5 Boost in a Randomized Clinical Trial

Background DNA vaccine immunogenicity has been limited by inefficient delivery. Needle-free delivery of DNA using a CO2-powered Biojector® device was compared to delivery by needle and syringe and evaluated for safety and immunogenicity. Methods Forty adults, 18–50 years, were randomly assigned to intramuscular (IM) vaccinations with DNA vaccine, VRC-HIVDNA016-00-VP, (weeks 0, 4, 8) by Biojector® 2000™ or needle and syringe (N/S) and boosted IM at week 24 with VRC-HIVADV014-00-VP (rAd5) with N/S at 1010 or 1011 particle units (PU). Equal numbers per assigned schedule had low (≤500) or high (>500) reciprocal titers of preexisting Ad5 neutralizing antibody. Results 120 DNA and 39 rAd5 injections were given; 36 subjects completed follow-up research sample collections. IFN-γ ELISpot response rates were 17/19 (89%) for Biojector® and 13/17 (76%) for N/S delivery at Week 28 (4 weeks post rAd5 boost). The magnitude of ELISpot response was about 3-fold higher in Biojector® compared to N/S groups. Similar effects on response rates and magnitude were observed for CD8+, but not CD4+ T-cell responses by ICS. Env-specific antibody responses were about 10-fold higher in Biojector-primed subjects. Conclusions DNA vaccination by Biojector® was well-tolerated and compared to needle injection, primed for greater IFN-γ ELISpot, CD8+ T-cell, and antibody responses after rAd5 boosting. Trial Registration ClinicalTrials.gov NCT00109629
On Characterizing Network Hierarchy

Our previous work in topology characterization and hierarchy [1] introduced a hierarchy metric to explore the hierarchical structure in various networks. This metric is non-intuitive and complicated. In this paper, we propose a simpler and more natural metric for measuring network hierarchy. This simpler metric uses slightly different criteria in selecting backbone links than the more complicated one. Nevertheless, the network classifications according to both metrics agree with each other. Furthermore, we have extended the hierarchy analysis to examine path characteristics and found that the hierarchical nature of degree-based networks better resembles the hierarchy of the Internet at the AS level than at the routerlevel.
Implementation Software and Hardware for Face Detection

The analysis of the video represents a significant evolution in the field of computer • vision, especially in the field of video surveillance. This area seeks to detect the presence of some form, some edge . this is the problem of detection. Among the objects that can be detected in this area face detection. Face detection in a fixed image without special hypothesis is a difficult problem due to the high variability of the shape to detect. Many techniques of detection and face recognition have been developed in recent years and many of which are very efficient. Among these methods, we find the method of Viola and Jones were studied in this work. The aim of our work is to study this method to implement on the CPU with C / C + +, then acceleration was presented with OpenCV. Subsequently, a second implementation in FPGA was presented Keywords— Face detection, method of Viola/Jones, C/C++, OpenCV, FPGA.
Finite-State Transducer Toolkit for Faster ASR

The Automatic Speech Recognition (ASR) – the process of converting spoken words to computer-intelligible information, also known as speech-to-text, or speech recognition – is used for control of various devices (i.e. car, computer, mobile phone, etc.). The most popular algorithms implemented in these architectures are based on statistical methods Hidden Markov Models (HMM). There is a hierarchy, which sorts elementary stages of speech recognition. Elementary levels can be represented by weighted finite state transducers. Thus by using some FSM toolkit (i.e. AT&T FSM toolkit), we are able to obtain a common method how to optimize this automata and compose into the recognition network. Main usage of the FSM toolkit for the Czech language has not been used by now. This work explores feasibility of AT&T FSM toolkit used together with HTK for the Czech language and compares results in the speed of recognizers based on the FSM and results obtained using just HTK toolkit.
Anthropomorphism and Intentionality Improve Memory for Events

Several studies have explored the determinants of anthropomorphism: the tendency to endow nonhuman agents with human features, goals, and intentions. Less is known of the cognitive benefits that may arise from anthropomorphism. Following research in narrative comprehension, we explored how the attribution of human-like features and intentional goals to nonhuman agents might benefit memory for events. Experiments 1 and 2 demonstrated that anthropomorphic descriptions and intentional goals independently contributed to improved narrative memory. A third experiment revealed that these effects were mediated by participants' attributions of agency. We conclude that anthropomorphic descriptions and intentional behavior jointly support a schematic framework for remembering events.
Differentiation of Human Neural Progenitor Cells in Functionalized Hydrogel Matrices

Abstract Hydrogel-based three-dimensional (3D) scaffolds are widely used in the field of regenerative medicine, translational medicine, and tissue engineering. Recently, we reported the effect of scaffold formation on the differentiation and survival of human neural progenitor cells (hNPCs) using PuraMatrix™ (RADA-16) scaffolds. Here, we were interested in the impact of PuraMatrix modified by the addition of short peptide sequences, based on a bone marrow homing factor and laminin. The culture and differentiation of the hNPCs in the modified matrices resulted in an approximately fivefold increase in neuronal cells. The examination of apoptotic and necrotic cells, as well as the level of the anti-apoptotic protein Bcl-2, indicates benefits for cells hosted in the modified formulations. In addition, we found a trend to lower proportions of apoptotic or necrotic neuronal cells in the modified matrices. Interestingly, the neural progenitor cell pool was increased in all the tested matrices in comparison to the standard 2D culture system, while no difference was found between the modified matrices. We conclude that a combination of elevated neuronal differentiation and a protective effect of the modified matrices underlies the increased proportion of neuronal cells.
Natural consequence of post-intervention stent malapposition, thrombus, tissue prolapse, and dissection assessed by optical coherence tomography at mid-term follow-up

Aims We performed this study to clarify natural consequences of abnormal structures (stent malapposition, thrombus, tissue prolapse, and stent edge dissection) after percutaneous coronary intervention (PCI). Methods and results Thirty-five patients treated with 40 drug-eluting stents underwent serial optical coherence tomography (OCT) imaging immediately after PCI and at the 8-month follow-up. Among a total of 73 929 struts in every frame, 431 struts (26 stents) showed malapposition immediately after PCI. Among these, 49 remained malapposed at the follow-up examination. The mean distance between the strut and vessel wall (S–V distance) of persistent malapposed struts on post-stenting OCT images was significantly longer than that of resolved malapposed struts (342 ± 99 vs. 210 ± 49 μm; P <0.01). Based on receiver-operating characteristic curve analysis, an S–V distance ≤260 µm on post-stenting OCT images was the corresponding cut-off point for resolved malapposed struts (sensitivity: 89.3%, specificity: 83.7%, area under the curve = 0.884). Additionally, 108 newly appearing malapposed struts were observed on follow-up OCT, probably due to thrombus dissolution or plaque regression. Thrombus was observed in 15 stents post-PCI. Serial OCT analysis revealed persistent thrombus in 1 stent, resolved thrombus in 14 stents, and late-acquired thrombus in 8 stents. Tissue prolapse observed in 38 stents had disappeared at the follow-up. All eight stent edge dissections were repaired at the follow-up. Conclusion Most cases of stent malapposition with a short S–V distance, thrombus, tissue prolapse, or minor stent edge dissection improved during the follow-up. These OCT-detected minor abnormalities may not require additional treatment.