Miracle-dz/UniFAR-FTUs huggingface dataset:
Face recognition based on collaborative image similarity assessment

In this paper, we propose an innovative approach for face recognition based on collaborative image similarity assessment (CISA). In the proposed method, the test sample is first represented by a linear combination of all the training samples for each face class. The classification task is then conducted using the similarity measures including structure similarity index measure (SSIM), root mean square (RMS), and similarity assessment value (SAV). Since CISA is only one phase, it is computationally efficient when comparing with the method of two-phase test sample sparse representation (TPTSR). To verify the performance of face classification, two popular face databases of the ORL and FERET are used. Results show that CISA is comparable with TPTSR on the classification rates for ORL database. However, CISA greatly outperforms TPTSR on the evaluation of the FERET database. Moreover, only 276.4ms on an average is required for CISA in the classification of each test sample but it needs 800.8ms for TPTSR.
Association of Polymorphisms in Mitofusin-2 Gene with Type 2 Diabetes in Han Chinese

MFN2 and ESRRA are candidate genes involved in the pathogenesis of T2D. Five tag-SNPs in MFN2 gene and three in ESRRA gene were selected and genotyped with TaqMan or PCR-RFLP method in stage 1 populations (555 patients with T2D and 649 control subjects) and stage 2 populations (546 patients with T2D versus 419 control subjects) in Han Chinese. And combining our published data, we estimated the interactions between genetic variants in the MFN2, ESRRA, and PGC-1α genes on the T2D risk using MDR. rs873458 (G > A) and rs2878677 (C > T) in MFN2 gene were significantly associated with T2D (P = 0.005 and 0.01) in stage 1 populations, and the association of other SNPs with T2D was not found. In stage 2 populations, we further confirmed the association between rs2878677 and T2D (P = 0.01). Combining the two stage populations, the data supported more significant effect of rs873458 and rs2878677 on T2D risk (P = 0.003 and 0.0001). A-C-G-T-C and G-T-C-T-C in MFN2 had significant association with T2D (P = 0.007 and 0.009). The present study also provided the evidence that MFN2 had interactions with PGC-1α (P < 0.0001) or ESRRA (P < 0.0001). This study suggested a role of MFN2 polymorphism in the risk of T2D; however, further studies are needed.
Extraction and classification of rhetorical sentences of experimental technical paper based on section class

An extraction process of rhetorical sentences has become one of the problems in the study of automatic text summarization with a rhetorical sentence basis. Rhetorical sentence with high accuracy will be needed for producing a good summary. To improve the accuracy, this paper proposes a method in how to extract rhetorical sentences from experimental papers according to their category. The four main categories of experimental papers include problem, data, method, and result. Moreover, this paper proposes a section class as feature. We also calculated the frequency occurrence of rhetorical sentence in every section class. In our evaluation, we used tree algorithms including Naive Bayes, SVM and Decision Tree. Generally the SVM algorithm is proven to be better than the two other algorithms because the difference in value of the section class and non-section class feature is more reasonable. Overall, the rhetorical sentence extraction using section class has a better performance compared to those without class section.
Distributed Learning Environments and Social Software: In Search for a Framework of Design

This chapter discusses how the construction of an adequate design and intervention framework for distributed learning environments might be approached. It proposes that activity theory has some interesting concepts and perspectives to offer in this regard. In addition, it discusses the concept of affordance, understood as perceived possibilities for action, and its potential consequences for learning environment design. Furthermore, some current technical and conceptual challenges for the implementation and maintenance of distributed learning environments are addressed. The authors consider their text as a proposal for a necessary reorientation and a call for contributions to the search for an adequate design and intervention framework for distributed learning environments.
Research of Printed Matter Flaws Inspection Based on Improved K-Means and PCA

This paper presents a new approach for inspection of printed matter flaws based on K-mean clustering (KM) and principal component analysis (PCA). PCA is a method that can transform the original data that contains more vectors and some different correlative relationships between these vectors into a new one that contains fewer vectors and disrelated relationships between these vectors, while keeping the most information of the original data. First the PCA is used to obtain the best description features over the entire image which can reduce the dimension of the image and numeration, and then the reduced image data is identified by K-means clustering. The algorithm have a strong global searching capacity and avoids the local minimum problems. At the same time, it's no longer a large degree dependent on the initialization values. The results show that the method is more effective.
Towards Web-based Requirements Management a Case Study in a Distributed Software Development Organisation towards Web-based Requirements Management – a Case Study in a Distributed Software Development Organisation Computer Science and Engineering Tik-121 User Interfaces and Usability Table of Conten

II HELSINKI UNIVERSITY OF TECHNOLOGY ABSTRACT OF MASTER’S THESIS Author: Title of the thesis: Date: 7.1. 2002 Mikael Johnson Towards Web-based Requirements Management – a Case Study in a Distributed Software Development Organisation Number of Pages: 89 Department: Professorship: Computer Science and Engineering Tik-121 User Interfaces and Usability Supervisor and Instructor: Professor Marko Nieminen When user-centred design (UCD) methods are introduced in product development, the design is evaluated throughout the project with users. The user evaluation results in a large number of functional and non-functional requirements, which need to be managed to let the user needs drive the design. This master’s thesis presents the first part of the TEKES-funded VIKSU-research project that was created by Helsinki University of Technology and Teamware Group with the aim of developing a virtual desktop that guides a UCD process and supports distributed software development. The focus is set on Teamware’s requirement management (RM) process , which is examined from the viewpoint of Requirements Engineering (RE). The widely accepted approach for IT development in general, the UCD approach (ISO 13407) is applied in this thesis, as well as by Teamware. The product development work at Teamware is also examined looking through the glasses of Activity Theory, which precepts activity, action, and operation influenced the methods used. Analysing existing web-based RM tools, it was found that they do not support distributed multi-site software development, which implies that a RM tool would only be a partial and local solution for the requirements coordinator at Teamware. However, even if the RM tools develop, they might not fully support the requirement review meeting at Teamware, since the meeting also makes strategic product decisions. This implies that the Teamware RM process cannot be studied from the viewpoint of RE alone. It needs to be studied as a part of the product development process, and as the interaction between management, marketing, sales, and development. The new information model that was developed in this thesis to support the Teamware RM process divided the requirements into user needs and solutions, reflecting the idea that user requirements should be grouped by the context of use, while functional requirements should be grouped by the product components. However, through the four research questions in this thesis, it became clear that it is not reasonable to continue the VIKSU-project by constructing a web-based RM component for the virtual desktop. Instead, it could be viable to put the RM component in its context by defining the concept of the virtual desktop starting from the larger framework of product development.
LEXICALL: Lexicon Construction for Foreign Language Tutoring

Abstract : We focus on the problem of building large repositories of lexical conceptual structure (LCS) representations for verbs in multiple languages. One of the main results of this work is the definition of a relation between broad semantic classes and LCS meaning components. Our acquisition program LEXICALL takes, as input, the result of previous work on verb classification and thematic grid tagging, and outputs LCS representations for different languages. These representations have been ported into English, Arabic and Spanish lexicons, each containing approximately 9000 verbs. We are currently using these lexicons in an operational foreign language tutoring and machine translation.
A relaxing multi-constraint routing algorithm by considering QoS metrics priority for wired network

To find a path satisfying multi-constrained QoS metrics in packet switching network is a very challenging problem. The problem of finding such feasible paths is known as an NP-complete problem. In this work, we propose a solution to the afore-mentioned problem by relaxing the multi-constrained QoS routing using the significance level of QoS metrics. Our proposed algorithm adopts the nonlinear cost function and relaxing look-ahead concept: to put into account the QoS metrics' priority. The performance of our proposed algorithm is evaluated by simulation using MATLAB in terms of Success Ratio of finding the feasible paths and Computational Complexity. According to the simulation results, it is obvious that our proposed algorithm is superior to the existing algorithm (H_MCOP) in terms of Success Ratio, but inferior in terms of Computational Complexity. However, the Computational Complexity of our proposed algorithm is still within the acceptable level (1-2 ms for 100-node network).
Codeword stabilized quantum codes: Algorithm and structure

The codeword stabilized (CWS) quantum code formalism presents a unifying approach to both additive and nonadditive quantum error-correcting codes [IEEE Trans. Inf. Theory 55, 433 (2009)]. This formalism reduces the problem of constructing such quantum codes to finding a binary classical code correcting an error pattern induced by a graph state. Finding such a classical code can be very difficult. Here, we consider an algorithm which maps the search for CWS codes to a problem of identifying maximum cliques in a graph. While solving this problem is in general very hard, we provide three structure theorems which reduce the search space, specifying certain admissible and optimal ((n,K,d)) additive codes. In particular, we find that the re does not exist any ((7,3,3)) CWS code though the linear programming bound does not rule it out. The complexity of the CWS-search algorithm is compared with the contrasting method introduced by Aggarwal and Calderbank [IEEE Trans. Inf. Theory 54, 1700 (2008)].
A competing risks analysis of exit for Spanish manufacturing firms

Firms may exit the market in several ways, mainly through merger, acquisition, voluntary liquidation and bankruptcy, and each form of exit is likely to be caused by different factors (Schary, 1991). This paper explores the determinants of different exit routes. Using a sample of Spanish manufacturing firms for the period 1990-2000, we estimate a competing risks proportional hazard model to identify the factors leading firms to exit the market through (the mutually precluding events of) liquidation and acquisition. Our results show the existence of a sharp difference between the determinants of the different forms of exit in terms of firm and industry characteristics, mainly in relation to age and size.
A ROBUST CLUSTERING TECHNIQUE FOR MULTI-SPECTRAL SATELLITE IMAGES

A robust clustering technique is developped for multi-spectral satellite images. The observed image data are assumed to come from a mixture of multi-variate normal densities and the number of densities is assumed to be known. In the clustering technique the parameters of the densities are tentatively estimated by a multi-dimensional histogram and the minimum distance clustering method. Using the tentative estimates as the initial values, the EM (Expectation and Maximization) algorithm improves the parameters of the mixture of densities recursively. Image classification is carried out by the conventional maximum likelihood method with the parameters estimated by the EM algorithm. The proposed method is robust for noises and gives stable classification results, because no random selection is used for the initial parameter estimation. The performance of the algorithm is demonstrated by computer simulations and an experimental result of Landsat image classification is presented.
Adult Learner Career Trajectories: Vocational Self-Concept Development in CalWORKs Community College Students

Abstract:Given the size of the adult student population and the student affairs focus on career development in traditional age students, the purpose of this qualitative study was to explore career development and the vocational self-concept (VSC) in 48 California community college welfare-to-work students. Findings suggest the importance of congruence between student roles and other life roles – as well as the importance of sustained relationships with community college staff, as this was closely associated with VSC development. These sustained relationships are most beneficial when they help participants develop resistance strategies against messages that could damage their self-concepts. Theoretically, our findings call for differentiation between work and career, and show how VSC develops in some adult students, a process heretofore missing from the career literature. Knowing how students have been socialized to think about themselves, understanding if they can participate in career decision-making, and what their responsibilities in out-of-college contexts are is key to helping students find congruence and/or cope with incongruence stemming from balancing multiple life roles.
Projection-Based Utility Mining with an Efficient Indexing Mechanism

In this paper, we propose an efficient mining approach which adopts an indexing mechanism to speed up the execution efficiency and reduce the memory requirement in the utility mining process. Besides, a pruning strategy is designed to reduce the number of unpromising itemsets for mining. The experimental results also show the performance of the proposed approach is better than that of traditional two-phase utility mining algorithm under different parameters.
Existence of a 2D Torus in a Continuous-Time Model of a Liquidity Trap

The main purpose of this study is to show the existence of a 2D torus in a macrodynamic model of a liquidity trap. The model developed here has two steadystate points: a targeted steady state and a liquidity trap. When a 2D torus exists around a targeted steady state, an economy will keep fluctuating on a torus and never reach the state, unless the variables jump. We develop an analysis using the continuous-time New Keynesian dynamic general equilibrium model proposed by Benhabib et al. (2003). Although their model takes the form of “money in the production function,” we reconstruct it into the more typical “money in the utility function. ” JEL Classification: E32; E52
Delay bound and reliable data forwarding for wireless sensor networks

Some emerging applications of wireless sensor networks (WSNs) are time-critical, and in such scenarios data must be reliably delivered within a delay bound. A common approach to provide this strict delivery performance is to devise a medium access control (MAC) protocol, leading to the current plethora of MAC protocols in WSNs. In contrast to this traditional approach, we propose an alternative solution that exploits an existing MAC protocol called SNC-MAC along with a new network dimensioning method. The solution is an effective modular framework that defines the complete process of how to dimension and construct a wireless sensor network to meet strict data delivery requirements. This framework is evaluated using measurements in a real WSN deployment. The evaluation shows that measured message transfer delays are always below the delay bounds calculated by the dimensioning method while high message transfer reliability is achieved. The framework thus can enable delay bound and reliable data forwarding for time-critical applications in WSNs.
Quality Relevant Data-Driven Modeling and Monitoring of Multivariate Dynamic Processes: The Dynamic T-PLS Approach

In data-based monitoring field, the nonlinear iterative partial least squares procedure has been a useful tool for process data modeling, which is also the foundation of projection to latent structures (PLS) models. To describe the dynamic processes properly, a dynamic PLS algorithm is proposed in this paper for dynamic process modeling, which captures the dynamic correlation between the measurement block and quality data block. For the purpose of process monitoring, a dynamic total PLS (T-PLS) model is presented to decompose the measurement block into four subspaces. The new model is the dynamic extension of the T-PLS model, which is efficient for detecting quality-related abnormal situation. Several examples are given to show the effectiveness of dynamic T-PLS models and the corresponding fault detection methods.
Gene Ontology Based Clustering Analysis for Functionally Linked Genes and Cross-Species Comparison for SSR Biomarkers

Molecular biomarkers are important and commonly used as classification features for detecting function performances of target genes and distinguishing characteristics of different species or strains. As expeditious development in Next Generation Sequencing technologies, whole genome sequencing delivers a comprehensive view and new insights for novel species. However, utilization of whole genome sequences to discover genetic biomarkers for specific functional gene groups still possess many challenges. To solve this problem, we utilized Gene Ontology definitions and Ensembl orthologous information to decide a set of associated functional genes according to user's query keywords. Then, previously assembled NGS contigs were matched against the selected gene set from model species, and an SSR searching algorithm and a cross-species comparison mechanism were performed to reveal potential polymorphic SSR biomarkers. Each identified SSR would be annotated and classified by important attributes, such as lengths, genetic locations, fundamental repeat patterns, tolerant rates of retrieved SSRs. The developed system could identify novel SSR biomarkers for a specified functional gene group regarding conserved and unique features between the query and the target model species, and which could facilitate biologists in finding potential markers for elucidating biological functions and distinguishable features of a novel species.
The Path of Exchange Rate and FDI Inflows for EAC Countries, Is it a Great Worry for Investors?

This paper analyzes the path of Exchange rate and FDI inflows by investigating their relationship following Granger Causality test. There is no worry for Foreign Investors but a great worry for EAC countries as two stage least square (2SLS) estimates for GARCH(1, 1) and Standard Deviation approaches provide evidence. Granger causality and Co integration tests provide evidence on the bi directional causality and long run relationship between Exchange rate volatility and FDI inflows. Exchange rate volatility has positive and significant effect on FDI inflows for EAC countries and vice versa is true.
A Neural Network Approach to the Optimal Combination of Product Color Design

This paper presents a neural network (NN) approach to determining the best matching colors for a given product image in product design. With a wide variety of forms and colors on the market, mobile phones are used in an experimental study to illustrate the approach. 33 representative mobile phones and 50 commonly used colors are used as experimental samples to examine how product color affects a product image perceived by consumers. Four NN models are built with different hidden neurons to examine how a particular combination of mobile phone form and color matches the simple-complex image. The performance evaluation result shows that the number of hidden neurons has no significant effect on the predictive ability of the NN models. The NN models can be used to construct a product color database for supporting design decisions on product colors for matching a desirable product image.
Efficacy of elaborated semantic features analysis in Aphasia: a quasi-randomised controlled trial

ABSTRACT Background: Word finding difficulty is one of the most common features of aphasia. Semantic Features Analysis (SFA) directly aims to improve word finding in people with aphasia. Evidence from systematic reviews suggests that SFA leads to positive outcomes, yet the evidence comprises single case studies and case series. There is a need to evaluate the efficacy of SFA in controlled group studies/trials. Aims: To evaluate the efficacy of Elaborated Semantic Feature Analysis (ESFA) for word finding in people with aphasia. We investigated: (a) the efficacy of ESFA versus a delayed therapy/control, (b) the efficacy of two therapy approaches – individual versus a combination of individual and group therapy. Methods and procedures: We ran a multi-centre, quasi-randomised controlled trial, nested in a larger study (Thales-Aphasia). Participants were recruited from community settings. They had to be people with aphasia due to stroke at least four months post-onset. Participants were randomized to individual vs combination vs delayed therapy/control groups. Both therapy groups had 3 h of ESFA per week for 12 weeks. Delayed therapy/control group had no intervention for 12 weeks and were then randomized to either individual or combination therapy. The primary outcome was confrontation naming. Secondary outcomes were the Boston Naming Test, Discourse, the Functional Assessment of Communication Skills for adults (ASHA–FACS), the Stroke and Aphasia Quality of Life scale (SAQOL-39g), the General Health Questionnaire-12 item, and the EQ-5D. Outcomes and Results: Of the 72 participants of the Thales-Aphasia project, 58 met eligibility criteria for speech-language therapy and 39 were allocated to ESFA. The critical p-value was adjusted for multiple comparisons (.005). For the therapy versus control comparison, there was a significant main effect of time on the primary outcome (p < .001, η2p = .42) and a significant interaction effect (p = .003, η2p = .21). An interaction effect for the SAQOL-39g (p = .015, η2p = .11) and its psychosocial domain (p = .013, η2p = .12) did not remain significant after Bonferroni adjustment. For the individual versus combination ESFA comparison, there were significant main effects of time on the primary outcome (p < .001, η2p = .49), the BNT (p < .001, η2p = .29) and the ASHA-FACS (p = .001, η2p = .18). Interaction and group effects were not significant. Conclusion: Though underpowered, this study provides evidence on the efficacy of ESFA to improve word finding in aphasia, with gains similar in the two therapy approaches.
A wide-range frequency synthesizer using a compensated phase-rotating technique for digital TV tuners

Fabricated in a 0.18-µm CMOS technology, a wide-range fractional-N frequency synthesizer with a phase-compensated technique is presented. While using a 630–960 MHz LC-type VCO, the synthesizer can provide the range of 55 to 960 MHz with a band-selecting structure to satisfy the ATSC applications. Using the phase-rotating concept, the synthesizer can achieve the fractional functionality, instead of the conventional ΔΣ interpolation. The measured results show phase noise is −123 dBc/Hz at 1-MHz offset. The lock time is below 6 µs from 640 MHz to 930 MHz.