Miracle-dz/UniFAR-FTUs huggingface dataset:
The Moderating Roles of Income and Age in Mobile Commerce Application

Mobile commerce is becoming a major aspect of our human endeavors with the advancements in wireless technology and services. This article examines key factors that influence mobile commerce adoption, and the moderating roles of age and income. The conceptual framework is underpinned on an extended technology acceptance model. The survey data was collected from participants selected from Malaysia. The analysis was based on 260 valid responses, and the findings reveal that age and income moderate perceptions on behavioral intention to adopt mobile commerce. Different age groups exhibit different perceptions. Further, cost and social influence become more important as age increases, while perceived usefulness becomes more significant as age decreases. In addition, perceived usefulness emerges as the most important factor for participants earning low income, and social influence is the most important factor for participants earning high income. Surprisingly, high-income earners indicate that cost is an important factor. The contributions to research and practice including suggestions for future studies are discussed.
Grid-HSI : Using Grid Computing to Enable a Hyperspectral Imaging Testbed

Hyperspectral imagery analysis demand large input data sets, as well as great time of processing and memory capacity. Parallel computers can accelerate the performance of these applications. The potential for massive parallel CPU capacity is one of the most attractive features of a grid. This paper provides a short description of previous software tools have been developed to enable Grid Computing, and then performance analysis tools . Last section is dedicated for description of the prototype for a computational Grid testbed future work.
The Effect of Organizational Support and Self Efficacy on the Usage Intention of E-Learning System in Hospital

This purpose of the study is to develop the usage intention model of E-Learning systems. A survey of 1071 samples of six teaching hospitals in Taiwan shows that the effects of organizational support and self efficacy on usage intention are mediated by perceived ease of use and perceived useful. According to the statistical results, the proposed model fits very well for the samples. Besides, both organizational support and self efficacy are important antecedents of perceived ease of use and perceived useful. In addition, perceived ease of use has the most influence on usage intention, followed by perceived useful, organizational support, and self efficacy. Further investigation reveals that organizational support and self efficacy have both direct and indirect influences on usage intention. This research can provide E-Learning designers and managers of the hospital with the implication that we must focus not only on the technological aspect (perceived ease of use and perceived useful), but also on the social psychological aspect (organizational support and self efficacy).
On the evaluation of modular polynomials

We present two algorithms that, given a prime ell and an elliptic curve E/Fq, directly compute the polynomial Phi_ell(j(E),Y) in Fq[Y] whose roots are the j-invariants of the elliptic curves that are ell-isogenous to E. We do not assume that the modular polynomial Phi_ell(X,Y) is given. The algorithms may be adapted to handle other types of modular polynomials, and we consider applications to point counting and the computation of endomorphism rings. We demonstrate the practical efficiency of the algorithms by setting a new point-counting record, modulo a prime q with more than 5,000 decimal digits, and by evaluating a modular polynomial of level ell = 100,019.
Preparation and Characterization of In Situ Polymerized Cyclic Butylene Terephthalate and its Composites

A fatal disadvantage of continuously reinforced thermoplastic composites is the high melt viscosity of the matrix which hampers impregnation. However, the melt viscosity of low molecular weight CBT resin can reach extremely low value, which simplifies impregnation and enables the use of thermoset production methods. The thermal analysis, rheological analysis and mechanical property on the polymerization and crystallization of CBT into poly (cyclic butylene terephthalate) (PCBT) at different ratios of catalyst were investigated in this paper. The continuous glass fiber (GF) reinforced PCBT composite with over 70% fiber volume content was prepared via in situ polymerization, and the mechanical property of the PCBT was studied. The best impregnation time was decreased and the degree of crystallinity was increased respectively with catalyst fraction increasing. The tensile/flexural strength and modulus of PCBT resin and GF/PCBT composites were enhanced when the catalyst fraction increased from 0.3% to 0.6%.
SPIDER: software for protein identification from sequence tags with de novo sequencing error

For the identification of novel proteins using MS/MS, de novo sequencing software computes one or several possible amino acid sequences (called sequence tags) for each MS/MS spectrum. Those tags are then used to match, accounting amino acid mutations, the sequences in a protein database. If the de novo sequencing gives correct tags, the homologs of the proteins can be identified by this approach and software such as MS-BLAST is available for the matching. However, de novo sequencing very often gives only partially correct tags. The most common error is that a segment of amino acids is replaced by another segment with approximately the same masses. We developed a new efficient algorithm to match sequence tags with errors to database sequences for the purpose of protein and peptide identification. A software package, SPIDER, was developed and made available on Internet for free public use. This work describes the algorithms and features of the SPIDER software.
Enhanced cellular uptake of aminosilane-coated superparamagnetic iron oxide nanoparticles in mammalian cell lines

Purpose To compare the cellular uptake efficiency and cytotoxicity of aminosilane (SiO2-NH2)-coated superparamagnetic iron oxide (SPIO@SiO2-NH2) nanoparticles with three other types of SPIO nanoparticles coated with SiO2 (SPIO@SiO2), dextran (SPIO@dextran), or bare SPIO in mammalian cell lines. Materials and methods Four types of monodispersed SPIO nanoparticles with a SPIO core size of 7 nm and an overall size in a range of 7–15 nm were synthesized. The mammalian cell lines of MCF-7, MDA-MB-231, HT-29, RAW264.7, L929, HepG2, PC-3, U-87 MG, and mouse mesenchymal stem cells (MSCs) were incubated with four types of SPIO nanoparticles for 24 hours in the serum-free culture medium Dulbecco’s modified Eagle’s medium (DMEM) with 4.5 μg/mL iron concentration. The cellular uptake efficiencies of SPIO nanoparticles were compared by Prussian blue staining and intracellular iron quantification. In vitro magnetic resonance imaging of MSC pellets after SPIO labeling was performed at 3 T. The effect of each SPIO nanoparticle on the cell viability of RAW 264.7 (mouse monocyte/macrophage) cells was also evaluated. Results Transmission electron microscopy demonstrated surface coating with SiO2-NH2, SiO2, and dextran prevented SPIO nanoparticle aggregation in DMEM culture medium. MCF-7, MDA-MB-231, and HT-29 cells failed to show notable iron uptake. For all the remaining six cell lines, Prussian blue staining and intracellular iron quantification demonstrated that SPIO@ SiO2-NH2 nanoparticles had the highest cellular uptake efficiency. SPIO@SiO2-NH2, bare SPIO, and SPIO@dextran nanoparticles did not affect RAW 264.7 cell viability up to 200 μg Fe/mL, while SPIO@SiO2 reduced RAW 264.7 cell viability from 10 to 200 μg Fe/mL in a dose-dependent manner. Conclusion Cellular uptake efficiency of SPIO nanoparticles depends on both the cell type and SPIO surface characteristics. Aminosilane surface coating enhanced the cellular uptake efficiency without inducing cytotoxicity in a number of cell lines.
The query-flow graph: model and applications

Query logs record the queries and the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to search engine results. Mining the wealth of information available in the query logs has many important applications including query-log analysis, user profiling and personalization, advertising, query recommendation, and more. In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior. Intuitively, in the query-flow graph a directed edge from query qi to query qj means that the two queries are likely to be part of the same "search mission". Any path over the query-flow graph may be seen as a searching behavior, whose likelihood is given by the strength of the edges along the path. The query-flow graph is an outcome of query-log mining and, at the same time, a useful tool for it. We propose a methodology that builds such a graph by mining time and textual information as well as aggregating queries from different users. Using this approach we build a real-world query-flow graph from a large-scale query log and we demonstrate its utility in concrete applications, namely, finding logical sessions, and query recommendation. We believe, however, that the usefulness of the query-flow graph goes beyond these two applications.
Approximate Satisfiability and Equivalence

Inspired by property testing, we relax the classical satisfiability UvDashF between a finite structure U of a class K and a formula F, to a notion of epsiv-satisfiability UvDashepsiv F, and the classical equivalence F1equivF2 between two formulas F1 and F2, to epsiv-equivalence F1equivepsivF2 for epsiv>0. We consider the class of strings and trees with the edit distance with moves, and show that these approximate notions can be efficiently decided. We use a statistical embedding of words (resp. trees) into lscr1, which generalizes the original Parikh mapping, obtained by sampling O(f(epsiv)) finite samples of the words (resp. trees). We give a tester for equality and membership in any regular language, in time independent of the size of the structure. Using our geometrical embedding, we can also test the equivalence between two regular properties on words, defined by monadic second order formulas. Our equivalence tester has polynomial time complexity in the size of the automaton (or regular expression), for a fixed epsiv, whereas the exact version of the equivalence problem is PSPACE-complete. Last, we extend the geometric embedding, and hence the tester algorithms, to infinite regular languages and to context-free languages. For context-free languages, the equivalence tester has an exponential time complexity, whereas the exact version is undecidable
A Keystroke Dynamics Based System for User Identification

On-the-fly keyboard user authorization is certainly an interesting option for standard security procedures for high-security computer systems. Unauthorized access to logged-in workstation could threaten the security of data and systems. Conventional authorization methods (passwords, fingerprint scans) verify user identity only during logging process, leaving system vulnerable to user replacement afterwards. Procedures overcoming this peril are often invasive (constant visual monitoring) or uncomfortable (frequent identity verification with user cooperation). A possible solution for constant authorization without these drawbacks is to identify the keyboard user while typing. The approach we propose is based on two extracted keystrokes features: 'flight' and 'dwell'. We have tested the suggested solutions on individual group resembling a medium-sized company. The obtained results are promising.
A self tuning PID controller using Wavelet Networks

In this paper a self tuning adaptive PID control scheme for nonlinear systems is proposed using wavelet networks. The auto tuner consists of a discrete PID controller and a proposed new wavelet network structure called dynamic wavelet network (DWN). The DWN consists of a static feedforward wavelet network in cascade with an autoregressive moving average (ARMA) model. The learning strategy for the wavelet network and PID controller is based on gradient descent. A recursive algorithm is developed to update the weights of the DWN and the parameters of the ARMA model. The performance of the proposed controller is demonstrated via extensive numerical simulations. The results are applied to a typical servomechanism with an input saturation as a hard nonlinearity, showing the feasibility of the proposed adaptive control system.
Implementation of Systems Redesign: Approaches to Spread and Sustain Adoption

The widespread gap between evidence and practice for clinical and preventive services argues for a deeper understanding of effective quality improvement (QI) and system change. Using implementation and system redesign sciences, we have developed and used an effective strategy to enable robust implementation of QI initiatives, including clinical practice bundles, within a health care setting. Our program, which applies Lean and systems engineering methodologies, is specifically designed to exploit the five characteristics of effective innovations, as outlined by Berwick. This strategy has been applied in over 21 hospitals (six hospital systems) throughout the State of Indiana and is currently being used as part of the Radically Reducing methicillinresistant Staphylococcus aureus (MRSA) initiative funded by the Agency for Healthcare Research and Quality (AHRQ). The benefits of the process redesign activities are detailed at the business level through a business case analysis. Additionally, benefits at the personal level are quantified through workflow analysis (prior to and following the interventions). The intervention strategy is integrated into the current quality framework for each organization to ensure compatibility with existing organizational programs. Our staff engagement, training, and educational programs make systems engineering methodologies and principles readily accessible to frontline staff. Additionally, each project session requires immediate application of tools and techniques. This article will discuss our implementation strategy, provide examples of Lean and systems engineering tool applications, and provide an assessment of spread adoption and sustainability as a function of this implementation strategy.
A distributed mapping control of identifiers and locators for future mobile Internet

The future Internet will be evolved to mobile-oriented environments, and thus the mobility support is a key issue in the design of future Internet. This paper proposes a distributed identifier-locator mapping system (DMS) for the future mobile-oriented Internet environment, which is designed on the identifier-locator (ID-LOC) separation principle. The proposed DMS scheme is implemented over Linux platform by using the OpenFlow and Click Router software modules. From experimentations over the real testbed network of Korea Research Education Network (KOREN), we can see that the proposed DMS scheme can effectively perform the mobility management operations for mobile Internet hosts. For performance comparison, we can see that the proposed DMS scheme reduces the signaling delays for mobility management, including ID-LOC mapping update/query and data delivery, compared with the existing mobility control schemes, Proxy Mobile IP (PMIP).
Fatty acid reesterification but not oxidation is increased by oral contraceptive use in women.

We evaluated the hypothesis that fatty acid reesterification would be increased during rest and exercise in the midluteal menstrual cycle phase and during oral contraceptive use, when ovarian hormone concentrations are high, compared with the early follicular phase. Subjects were eight moderately active, weight-stable, eumenorrheic women (24.8 +/- 1.2 yr, peak oxygen consumption = 42.0 +/- 2.3 ml.kg(-1). min(-1)) who had not taken oral contraceptives for at least 6 mo. Plasma free fatty acid (FFA) kinetics were assessed in the 3-h postprandial state by continuous infusion of [1-(13)C]palmitate and [1,1,2,3,3-(2)H]glycerol during 90 min of rest and 60 min of exercise at 45% and 65% peak oxygen consumption in the early follicular and midluteal menstrual cycle phases and during the inactive- and high-dose phases following 4 mo of oral contraceptive use. Plasma FFA rates of appearance, disappearance, and oxidation increased significantly from rest to exercise with no differences noted between menstrual cycle or oral contraceptive phases or exercise intensities. Compared with either menstrual cycle phase, oral contraceptive use resulted in an increase in plasma-derived fatty acid reesterification and a decrease in the proportion of plasma FFA rate of disappearance that was oxidized at rest and during exercise. Endogenous and exogenous synthetic ovarian hormones do not exert a measurable influence on plasma FFA turnover or oxidation at rest or during moderate-intensity exercise in the 3-h postprandial state when carbohydrate use predominates. The increase in whole body lipolytic rate during exercise noted previously with oral contraceptive use is not matched by an increase in fatty acid oxidation and results in an increase in reesterification. Synthetic ovarian hormones contained in oral contraceptives increase lipolytic rate, but fatty acid oxidation during exercise is determined by exercise intensity and its metabolic and endocrine consequences.
Spectral energy transmission method for crack depth estimation under various mix proportions of concrete

The amount and magnitude of absorption and scattering of stress waves in concrete, mainly due to internal friction and aggregate inclusions, may be different when the concrete mix proportion varies. In this study, the surface wave spectral energy transmission method is proposed for the estimation of crack depth in concrete structures, in which the effect of the concrete mix proportion on measurements of self-compensated surface wave transmission functions (TRFs) and surface wave spectral energy transmission ratios (SETRs) is investigated and a relationship between the crack depth and the SETR has been determined from experimental data on various concrete specimens with different mix proportions and different crack depths using a regression analysis. In the results, it is found that the self-compensated surface wave TRFs are very sensitive to both concrete mix proportions and crack depths. However, SETR is not much affected by the concrete mix proportion but very sensitive to the crack depth. Therefore, the spectral energy transmission method can be effectively used for crack depth estimation in concrete structures regardless of their material mix proportions.
Micron: An Actively Stabilized Handheld Tool for Microsurgery

We describe the design and performance of a handheld actively stabilized tool to increase accuracy in microsurgery or other precision manipulation. It removes involuntary motion, such as tremor, by the actuation of the tip to counteract the effect of the undesired handle motion. The key components are a 3-degree-of-freedom (DOF) piezoelectric manipulator that has a 400-μm range of motion, 1-N force capability, and bandwidth over 100 Hz, and an optical position-measurement subsystem that acquires the tool pose with 4-μm resolution at 2000 samples/s. A control system using these components attenuates hand motion by at least 15 dB (a fivefold reduction). By the consideration of the effect of the frequency response of Micron on the human visual feedback loop, we have developed a filter that reduces unintentional motion, yet preserves the intuitive eye-hand coordination. We evaluated the effectiveness of Micron by measuring the accuracy of the human/machine system in three simple manipulation tasks. Handheld testing by three eye surgeons and three nonsurgeons showed a reduction in the position error of between 32% and 52%, depending on the error metric.
Hierarchical Topic Models for Image Categorization

We propose hierarchical topic model for the image categorization task. Motivated by standard topic models such as PLSA and LDA, and augmented with prior knowledge extracted from WordNet, our model explicitly specifies the latent topics with emphasis on their semantic relationships. The proposed model offers several advantages over current approaches in the literature. The latent topic model complements the purely datadriven methods with prior knowledge. The hierarchical tree structure has the capability of learning a reasonably good model from few training data, by cross learning from closely related topics. Inference then provides a better understanding of the generative model and the underlying semantic concepts captured from low-level visual features. Further, the tree topology has the effect to naturally eliminate the notorious nonidentifiability in mixture models of multinomials. For model fitting, we use the EM algorithm to find the MAP estimation of model parameters. We conduct a set of experiments to validate these contributions, and encouraging results are reported.
CofiFab

This paper presents CofiFab, a coarse-to-fine 3D fabrication solution, combining 3D printing and 2D laser cutting for cost-effective fabrication of large objects at lower cost and higher speed. Our key approach is to first build coarse internal base structures within the given 3D object using laser cutting, and then attach thin 3D-printed parts, as an external shell, onto the base to recover the fine surface details. CofiFab achieves this with three novel algorithmic components. First, we formulate an optimization model to compute fabricatable polyhedrons of maximized volume, as the geometry of the internal base. Second, we devise a new interlocking scheme to tightly connect the laser-cut parts into a strong internal base, by iteratively building a network of nonorthogonal joints and interlocking parts around polyhedral corners. Lastly, we optimize the partitioning of the external object shell into 3D-printable parts, while saving support material and avoiding overhangs. Besides cost saving, these components also consider aesthetics, stability and balancing. Hence, CofiFab can efficiently produce large objects by assembly. To evaluate CofiFab, we fabricate objects of varying shapes and sizes, and show that CofiFab can significantly outperform previous methods.
Episodic skeletal-plan refinement based on temporal data

ONCOCIN is a medical expert system that extends the skeletal-planning technique to an applciation area where the history of past events and the duration of actions are important. The system's knowledge base is designed to reflect a hierarchical model of the domain, and its control and inference mechanisms encourage a mixed-initiative style of interaction between the computer and the user.