Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Training of Random Mapping for Data Quantization

Data quantization learns encoding results of data with certain requirements, and provides a broad perspective of many real-world applications to data handling. Nevertheless, the results of encoder is usually limited to multivariate inputs with the random mapping, and side information of binary codes are hardly to mostly depict the original data patterns as possible. In the literature, cosine based random quantization has attracted much attentions due to its intrinsic bounded results. Nevertheless, it usually suffers from the uncertain outputs, and information of original data fails to be fully preserved in the reduced codes. In this work, a novel binary embedding method, termed adaptive training quantization (ATQ), is proposed to learn the ideal transform of random encoder, where the limitation of cosine random mapping is tackled. As an adaptive learning idea, the reduced mapping is adaptively calculated with idea of data group, while the bias of random transform is to be improved to hold most matching information. Experimental results show that the proposed method is able to obtain outstanding performance compared with other random quantization methods.
A method of stereo obstacle detection based on image symmetrical move

A stereo obstacle detection method based on images symmetrical move and cell partition is presented in this paper. This algorithm gets each cell's optimum offset by calculating the minimum non-similarity of cell, and merges Cell of Interests (COIs) to calculate obstacles in the most probably obstacle regions, and gives information of these obstacles. The paper introduces the perspective projection model at first, and then gives two conclusions which are the basic of the algorithm, the part of cell partition and cell optimum offset calculation are presented. Finally, algorithm performance tested by experiment on the test vehicle JJUV-I is shown in the paper.
Full-Text and Structural Indexing of XML Documents on B+-Tree

XML query processing is one of the most active areas of database research. Although the main focus of past research has been the processing of structural XML queries, there are growing demands for a full-text search for XML documents. In this paper, we propose XICS (XML Indices for Content and Structural search), which aims at high-speed processing of both full-text and structural queries in XML documents. An important design principle of our indices is the use of a B+-tree. To represent the structural information of XML trees, each node in the XML tree is labeled with an identifier. The identifier contains an integer number representing the path information from the root node. XICS consist of two types of indices, the COB-tree (COntent B+-tree) and the STB-tree (STructure B+-tree). The search keys of the COB-tree are a pair of text fragments in the XML document and the identifiers of the leaf nodes that contain the text, whereas the search keys of the STB-tree are the node identifiers. By using a node identifier in the search keys, we can retrieve only the entries that match the path information in the query. The STB-tree can filter nodes using structural conditions in queries, while the COB-tree can filter nodes using text conditions. We have implemented a COB-tree and an STB-tree using GiST and examined index size and query processing time. Our experimental results show the efficiency of XICS in query processing.
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver

Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing optimization packages often leads to long training time and unsatisfactory results. In this paper, we develop CRFOPT, a general CRF training package, to improve the efficiency and quality for training CRFs. We propose two improved versions of the forward-backward algorithm that exploit redundancy and reduce the time by several orders of magnitudes. Further, we propose an exponential transformation that enforces sufficient step sizes for quasi-Newton methods. The technique improves the convergence quality, leading to better training results. We evaluate CRF-OPT on a gene prediction task on pathogenic DNA sequences, and show that it is faster and achieves better prediction accuracy than both the HMM models and the original CRF model without exponential transformation.
An Ensemble Approach to Intrusion Detection Based on Improved Multi-Objective Genetic Algorithm

There exist some issues in current intrusion detection algorithms such as unbalanced detection performance on different types of attacks, and redundant or useless features that will lead to the complexity of detection model and degradation of detection accuracy. This paper presents an ensemble approach to intrusion detection based on improved multi-objective genetic algorithm. The algorithm generates the optimal feature subsets, which achieve the best trade-off between detection rate and false positive rate through an improved MOGA. And the most accurate and diverse base classifiers are selected to constitute the ensemble intrusion detection model by selective ensemble approach. The experimental results show that the algorithm can solve the feature selection problem of intrusion detection effectively. It can also achieve balanced detection performance on different types of attacks while maintaining high detection accuracy.
Micro-CT Based Experimental Liver Imaging Using a Nanoparticulate Contrast Agent: A Longitudinal Study in Mice

Background Micro-CT imaging of liver disease in mice relies on high soft tissue contrast to detect small lesions like liver metastases. Purpose of this study was to characterize the localization and time course of contrast enhancement of a nanoparticular alkaline earth metal-based contrast agent (VISCOVER ExiTron nano) developed for small animal liver CT imaging. Methodology ExiTron nano 6000 and ExiTron nano 12000, formulated for liver/spleen imaging and angiography, respectively, were intravenously injected in C57BL/6J-mice. The distribution and time course of contrast enhancement were analysed by repeated micro-CT up to 6 months. Finally, mice developing liver metastases after intrasplenic injection of colon carcinoma cells underwent longitudinal micro-CT imaging after a single injection of ExiTron nano. Principal Findings After a single injection of ExiTron nano the contrast of liver and spleen peaked after 4–8 hours, lasted up to several months and was tolerated well by all mice. In addition, strong contrast enhancement of abdominal and mediastinal lymph nodes and the adrenal glands was observed. Within the first two hours after injection, particularly ExiTron nano 12000 provided pronounced contrast for imaging of vascular structures. ExiTron nano facilitated detection of liver metastases and provided sufficient contrast for longitudinal observation of tumor development over weeks. Conclusions The nanoparticulate contrast agents ExiTron nano 6000 and 12000 provide strong contrast of the liver, spleen, lymph nodes and adrenal glands up to weeks, hereby allowing longitudinal monitoring of pathological processes of these organs in small animals, with ExiTron nano 12000 being particularly optimized for angiography due to its very high initial vessel contrast.
Designing cabinets: Presidential politics and cabinet instability in Latin America

This paper proposes and tests a theory about the strategic use of cabinet appointments by executives in presidential systems. The theory argues that cabinet turnover plays a crucial role in bargaining between the legislature and the executive over policy. In the context of fixed terms, the power to change the cabinet allows presidents to face unexpected shocks and use cabinet rotation to adjust their governments to new political and policy environments. This resource is even more important when presidents’ formal authority is weaker and when their political support and popularity decrease. I use data on cabinet changes in twelve Latin American countries between 1982 and 2003 to test the main arguments of the theory.
An Empirical Study on the Relationship among Software Design Quality , Development Effort , and Governance in Open Source Projects

The relationship among software design quality, development effort, and governance practices is a traditional research problem. However, the extent to which consolidated results on this relationship remain valid for open source (OS) projects is still an open research problem. An emerging body of literature contrasts the view of OS as an alternative to proprietary software and explains that there exists a continuum between closed and OS projects. This paper takes this perspective and hypothesizes that, as projects approach the OS end of the continuum, governance becomes less formal. In turn, a less formal governance is hypothesized to require a higher quality code as a means to facilitate coordination among developers by making the structure of code explicit and observable and, at the same time, facilitate quality by removing the pressure of deadlines from contributors. However, a less formal governance is also hypothesized to increase development effort due to a more cumbersome coordination overhead. The verification of research hypotheses is based on empirical data from a sample of 75 major OS projects. Empirical evidence supports our hypotheses and suggests that software design quality, mainly measured as coupling and inheritance, per se does not increase development effort, but represents an important managerial variable to implement the more open governance approach that characterizes OS projects, which, in turn, increases development effort.
Mobilization and Margination of Bone Marrow Gr-1high Monocytes during Subclinical Endotoxemia Predisposes the Lungs toward Acute Injury1

The specialized role of mouse Gr-1high monocytes in local inflammatory reactions has been well documented, but the trafficking and responsiveness of this subset during systemic inflammation and their contribution to sepsis-related organ injury has not been investigated. Using flow cytometry, we studied monocyte subset margination to the pulmonary microcirculation during subclinical endotoxemia in mice and investigated whether marginated monocytes contribute to lung injury in response to further septic stimuli. Subclinical low-dose i.v. LPS induced a rapid (within 2 h), large-scale mobilization of bone marrow Gr-1high monocytes and their prolonged margination to the lungs. With secondary LPS challenge, membrane TNF expression on these premarginated monocytes substantially increased, indicating their functional priming in vivo. Zymosan challenge produced small increases in pulmonary vascular permeability, which were markedly enhanced by the preadministration of low-dose LPS. The LPS-zymosan-induced permeability increases were effectively abrogated by pretreatment (30 min before zymosan challenge) with the platelet-activating factor antagonist WEB 2086 in combination with the phosphatidylcholine-phospholipase C inhibitor D609, suggesting the involvement of platelet-activating factor/ceramide-mediated pathways in this model. Depletion of monocytes (at 18 h after clodronate-liposome treatment) significantly attenuated the LPS-zymosan-induced permeability increase. However, restoration of normal LPS-induced Gr-1high monocyte margination to the lungs (at 48 h after clodronate-liposome treatment) resulted in the loss of this protective effect. These results demonstrate that mobilization and margination of Gr-1high monocytes during subclinical endotoxemia primes the lungs toward further septic stimuli and suggest a central role for this monocyte subset in the development of sepsis-related acute lung injury.
Effects of Religious Participation on Social Inclusion and Existential Well-Being Levels of Muslim Refugees and Immigrants in Turkey

ABSTRACT Being a refugee or immigrant brings many difficulties that can detrimentally affect well-being. Participation in social life and feeling included in the host country can play an important role on well-being. This article aims to investigate the effects of religious participation and social inclusion on well-being levels of refugees and immigrants. Data were collected from 97 participants who were enrolled in voluntary Turkish language courses for refugees in Istanbul. Results of path analysis indicated that religious participation enhanced the level of social inclusion and social inclusion fostered existential well-being. Although religious participation demonstrated no direct effects on existential well-being, it showed a significant and positive indirect effect through social inclusion. Results of difference tests indicated that participants with higher level of education attended to religious activities significantly more often and their existential well-being and social inclusion levels were higher as well. Results also demonstrated that social inclusion scores of high attenders (to religious activities) were significantly higher.
A testbed for integrated fault diagnosis and cyber security investigation

The protection of Critical Infrastructures represents a fundamental topic of interest for the modern societies. The testing in real scenarios is hard to achieve due to the severe interdependence between these critical systems and the human well-being. The paper is devoted to introduce a low-cost testbed developed to emulate a Critical Infrastructure as complex cyber-physical system. Moreover, it proposes an approach to identify cyber threats exploiting both cyber and physical behavior of the system. Specifically, common tools from model based fault diagnosis and intrusion detection are applied to determine incipient threats and support for the operator in decision making. All the hardware and software developed are implemented in an open-source fashion in order to share investigation resources with the scientific community.
Graph Based Computational Model for Computing Semantic Similarity

Finding semantic similarity between two natural language entities considered a challenging task in the field of natural language processing. Accuracy of presently existing semantic similarity computational methods is still very far from what humans would perceive. In this paper, we present a new approach of measuring semantic similarity/distance between concepts/words by considering all senses instead of using one most common sense of concepts in WordNet hierarchy. Our proposed approach considers not only the semantic distance between two concepts/words but also considers feature information of WordNet graph. When tested on benchmark data set of words pair similarity ratings, the proposed approach performs better than other semantic similarity computational models for ambiguous words/concepts (which has more than one sense). Proposed approach gives the highest correlation coefficient value with human similarity judgments based benchmark data set.
Theory of Regular M-band Wavelet Bases Theory of Regular M-band Wavelet Bases

This paper constructs K-regular M-band orthonormal wavelet bases. K-regularity of the wavelet basis is known to be useful in numerical analysis applications and in image coding using wavelet techniques. Several characterizations of K-regularity and their importance are described. An explicit formula is obtained for all minimal length M-band scaling lters. A new state-space approach to constructing the wavelet lters from the scaling lters is also described. When M-band wavelets are constructed from unitary lter banks they give rise to wavelet tight frames in general (not orthonormal bases). Conditions on the scaling lter so that the wavelet bases obtained from it is orthonormal is also described.
Prospective relationship between maternal depressive symptoms and asthma morbidity among inner-city African American children.

OBJECTIVE To examine prospective relationships between caregiver's depressive symptoms and child asthma morbidity among inner-city African American families. METHODS Phone surveys were conducted 6 months apart with 262 African American mothers of children with asthma. Cross-lagged structural path analysis was used for data analyses. RESULTS Using goodness-of-fit indices, the final model for asthma symptoms had a good fit to the data. Time 1 (T1) maternal depressive symptoms predicted T2 child asthma symptoms (beta =.16, p <.01); however, T1 asthma symptoms did not predict T2 maternal depressive symptoms (beta =.03, non-significant). In contrast, in the final model for emergency department (ED) visits there was no predictive association between maternal depressive symptoms and ED visits. CONCLUSION Maternal depressive symptoms may have a detrimental effect on child asthma morbidity among inner-city African American families, rather than vice versa. Ameliorating maternal depressive symptoms may result in better asthma outcomes for inner-city children.
Probabilistic Procedure Cloning for High-Performance Systems

For many scientific and engineering applications efficient compilation of Fortran 90 code is of paramount importance in order to exploit computing power of high performance systems. Fortran 90 subroutine calls can cause serious performance losses if copy-in/copy-out argument passing has to be applied. We present an interprocedural cloning algorithm that prevents redundant argument copying. Our approach is novel with respect to utilizing probabilistic data-flow analysis, which allows us to identify profitable procedure clones, to control code growth by a parameterizable threshold, and to create multiple calls of procedure clones even for single call-sites. On high-performance systems experimental results illustrate the importance and effectivity of this kind of optimization. Keywords— Procedure Cloning, Fortran 90, Probabilistic Data-Flow Analysis.
The Concurrent Roles of Self Esteem and Social Support as Mediators between Personality and Life Satisfaction

The study seeks to discover the concurrent mediating effect of self-esteem and social support between personality traits and life satisfaction. A Structural Equation Modelling (SEM) was performed to determine the model of relationship on personality, social support, self-esteem, and life satisfaction. The Confirmatory Factor Analysis (CFA) has achieved the fitness index requirement on the measurement model. The results show that Personality significantly affects Life Satisfaction. The result for Social Support shows it was partially mediated the relationship between Personality and Life Satisfaction. The result also shows that Self-Esteem partially mediates the relationship between Personality and Life Satisfaction. By understanding their life satisfaction; it can forecast and promote longevity, survival and suicide risk prevention; it may accordingly promote good health and greater academic success among the students. In turn, it contributes to the existing body of knowledge in the area of SWB, specifically the life satisfaction among students in Malaysians universities. The administrator, academicians, counsellors, and parents are the group of people that benefit a lot on the outcome of this study. Keywords—mediation, life satisfaction, personality traits, selfesteem, social support
A Novel Adaptive Neuro Fuzzy Inference System Based CPU Scheduler for Multimedia Operating System

In this paper we propose a novel CPU Scheduler based on Adaptive Neuro Fuzzy Inference System (ANFIS), to support the execution of multimedia applications along with conventional applications in multimedia operating system. Adaptive Neuro-Fuzzy Inference System (ANFIS) can be used to solve highly non-linear dynamic problems. This paper shows how an ANFIS can be used to optimize CPU scheduling in multimedia operating system. This adaptive intelligent scheduler should be considered as middle layer software, aware of current available resources. This scheduler takes decision based on the past experiences. We have used ANFIS architecture, which is able to cluster the data distributed in a multi dimensional input space using a set of fuzzy rules. A simulator is developed in Matlab 7.2. 0.232 and the performance of the proposed scheduler is evaluated against the existing algorithms. It is demonstrated that, the proposed scheduler is able to optimize various CPU scheduling parameters as well as resource utilization.
On-Wafer Measurement Errors Due to Unwanted Radiations on High-Q Inductors

This paper investigates the disagreements that may occur between on-wafer measurements and electromagnetic (EM) simulations of high-Q inductive devices. Such disagreements are highlighted on a planar spiral inductor and a 3-D solenoid which exhibit measured maximum Q-factors of 27 and 35, respectively, while 42 and 45 were expected from EM simulations. Both devices are fabricated on high-resistivity substrates. A radiative interaction is identified between RF probe and inductive device under test. By using EM simulations, extra-losses associated with this parasitic effect are fully modeled through the calculation of radiation and dissipation related Q-factors. Adjustments of on-wafer probe setup are proposed to reduce this parasitic effect. Finally, the 3-D solenoid inductor is characterized using a new experimental fixture, and the maximum Q of 45 predicted by EM simulation is retrieved.
Molecular simulation of oligo-glutamates in a calcium-rich aqueous solution: insights into peptide-induced polymorph selection

The presence of oligopeptides often has a drastic impact on the nucleation and crystal growth of calcium-containing minerals. Molecular simulation of complexes of peptides with Ca2+ ions can give mechanistic insight into how the pre-alignment of ions from solution by additives may steer the crystallization of calcium rich minerals into different polymorphs. We exploit advanced molecular modeling techniques to sample and analyze the complex multidimensional configurational space of aqueous solutions of oligo-glutamate and Ca2+ ions. We find that glutamate oligomers induce the formation of patterns in the associated Ca2+ ions in solution, which can serve as templates for the growth of different calcium oxalate pseudopolymorphs – depending on the peptide length, in excellent agreement with experimental observations. Glutamate decamers prestructure the Ca2+ ions in remarkable correspondence with typical distances in calcium oxalate dihydrate. These are distinct from those in calcium oxalate trihydrate which typically grows in the absence of peptide or in the presence of shorter glutamate oligomers such as pentamers.
The announcement effects of regional tourism industrial policy

Hainan Island has a rich diversity of tourism resources. China’s central government recognized this and announced a national policy to promote Hainan Island as a first-rate international tourist destination on December 31, 2009. The authors explore the effects of the announcement using an event studies approach. The results with and without considering the clustering issue show that, first, the averages of cumulative abnormal returns are not different from 0 prior to the announcement and, second, the cumulative abnormal returns of the Hainan board continuously rose over trading days after the announcement of a regional tourism industrial policy. These findings indicate that regional tourism industrial policy is valuable not only to the tourism industry in the destination region but also to other industries in that region.
Chinese semantic parsing based on dependency graph and feature structure

Labeling corpus with Feature Structure is a new attempt to incorporate large-scale semantic descriptions and semantic parsing. In this paper, we propose Dependency Graph Theory and Feature Structure Theory to resolve the semantic parsing of Chinese phrases and sentences, and have built a large-scale Chinese labeling corpus using Feature Structure. Feature Structure can represent the semantic relations of words in Chinese sentences more clearly and accurately.