Miracle-dz/UniFAR-FTUs huggingface dataset:
Users' performance in lab and non-lab enviornments through online usability testing: A case of evaluating the usability of digital academic libraries' websites

The factors related to the environment in which users operate may be of a vital importance when trying to understand how they experience a particular system. It is required that we find out how we can get to know those factors to investigate if they affect the users' performance in usability testing. An online usability study has emerged that can be attempted by a large, varied pool of users' anywhere with an Internet connection. Would the usage of an online usability study help to give comprehensive insight and an understanding of the whole user experience? That is especially interesting if the user operates remotely, as we are unaware of what the users might experience while performing the test (e.g., distractions and type of device used to attempt the test). Accordingly, a pilot study of ongoing research was conducted. An identical online usability-testing tool (Loop 11) through which to apply the online usability study was used in two environments: unrestricted (the user's natural environment), and totally restricted (a simulated lab environment). Ten subjects completed the test in the restricted environment and 20 completed it in the unrestricted environment. All of the subjects were asked to perform predefined search tasks on digital libraries' websites. Their performance was analyzed and compared against the two different environments. The results showed that online usability testing is a feasible method to gain comprehensive insight into how users attempt usability testing in a non-lab environment. The results of whether different environments affect test performance show no valuable differences in most of the study's measurements. The test subjects were frequently multitask while they performed the usability testing in an unrestricted environment, but they were highly distracted if they personally interrupted. The results encourage the researcher to conduct a formal version of this study to further examine the learned lessons from the pilot study.
Model Pendekatan UTAUT2 Modifikasi pada Analisis Penerimaan dan Penggunaan Teknologi E-Government di Nusa Tenggara Barat

Penelitian ini mencoba menguji model yang telah dikembangkan dengan menkombinasikan model-model penerimaan teknologi TAM, UTAUT, UTAUT2 dan variabel tambahan. Uji kelayakan yang dilakukan mencoba untuk memberikan gambaran secara jelas variabel berpengaruh dalam penerimaan dan penggunaan teknologi e-government di Nusa Tenggara Barat. Hasil yang didapatkan dari uji T, Outer Loading dan Significant (Direct/ Indirect Test) pada metode Semantic Equation Model bahwa beberapa komponen tidak signifikan dan harus dibuang demi mendapatkan model terbaik dalam pendekatan penerimaan dan penggunaan teknologi e-Government. Hasil analisis memberikan gambaran bahwa variabel Performance Expectance, Habit and Experience dan Trust of Intermediary berpenga berpengaruh secara positif terhadap Behavioural Intention; dan variabel Facilitating Condition dan Behavioural Intention berpengaruh secara positif terhadap Usage Behaviour. Sedangkan variabel Effort Expectance, Social Influence, Hedonic Motivation, Price Value dan Trust of Internet tidak berpengaruh secara langsung (indirect).
Joint source-channel coding with one-bit ADC front end

This paper considers the zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel with a one-bit analog-to-digital converter (ADC) front end. The optimization of the encoder and decoder is tackled under both the mean squared error (MSE) distortion and the outage distortion criteria with an average power constraint. For MSE distortion, the optimal transceiver is identified over the space of symmetric encoders. This result demonstrates that the linear encoder, which is optimal with a full-precision front end, approaches optimality only in the low signal-to-noise ratio (SNR) regime; while, digital transmission is optimal in the high SNR regime. For the outage distortion criterion, the structure of the optimal encoder and decoder are obtained. In particular, it is shown that the encoder mapping is piecewise constant and can take only two opposite values when it is non-zero.
Characters’ Politeness Strategies in Giving Command: Should Translators Keep Them?

Politeness strategies have been studied from various angles. In literary works, they can be used as a device to frame characterisation. However, in recent times only a few studies have investigated the association of politeness strategies with characterisation as seen from the translation perspective. This article discusses the result of an investigation on how far the translation of politeness markers in giving commands has contributed to the framing of certain characterisation in literary works. A Pragmatic approach is used in this qualitative research to analyse the translation of politeness markers from English to Indonesian. Objective data were collected through purposive sampling from Dan Brown’s novel Deception Point and its two Indonesian versions to obtain information as to which techniques produce better translation quality in both translations. Then, affective data were collected through Focus Group Discussions. The results show that the translation of politeness markers contributed to the characterisation. It was found that established equivalence, variation, and explicitation techniques employed to the translation of politeness markers contributed to the maintenance of characterisation and the translation quality. Meanwhile, addition, reduction, and literal translation techniques altered the characterisations and therefore, decreased the translation quality. This implies that translators should consider politeness and characterisation in translating commands. Keywords: characterisation; literary translation; politeness markers; translation; translation techniques
Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery

Low-Rank Tensor Recovery (LRTR), the higher order generalization of Low-Rank Matrix Recovery (LRMR), is especially suitable for analyzing multi-linear data with gross corruptions, outliers and missing values, and it attracts broad attention in the fields of computer vision, machine learning and data mining. This paper considers a generalized model of LRTR and attempts to recover simultaneously the low-rank, the sparse, and the small disturbance components from partial entries of a given data tensor. Specifically, we first describe generalized LRTR as a tensor nuclear norm optimization problem that minimizes a weighted combination of the tensor nuclear norm, the l1-norm and the Frobenius norm under linear constraints. Then, the technique of Alternating Direction Method of Multipliers (ADMM) is employed to solve the proposed minimization problem. Next, we discuss the weak convergence of the proposed iterative algorithm. Finally, experimental results on synthetic and real-world datasets validate the efficiency and effectiveness of the proposed method.
myAgile: A XP-based Method for Modern Programming Education

This work presents the "myAgile" method that integrates the industry-hailed extreme programming (XP) method with someuniversity programming courses. The goal is to build a XP-based modern programming education. A Java grade system project has been designed for students to practice "myAgile". And, an experiment of the project is being conducted. In the long run, it is expected that some programming courses maybe redesigned based on this work to meet the industrial need.
A discontinuous recurrent neural network with predefined time convergence for solution of linear programming

The aim of this paper is to introduce a new recurrent neural network to solve linear programming. The main characteristic of the proposed scheme is its design based on the predefined-time stability. The predefined-time stability is a stronger form of finite-time stability which allows the a priori definition of a convergence time that does not depend on the network initial state. The network structure is based on the Karush-Kuhn-Tucker (KKT) conditions and the KKT multipliers are proposed as sliding mode control inputs. This selection yields to an one-layer recurrent neural network in which the only parameter to be tuned is the desired convergence time. With this features, the network can be easily scaled from a small to a higher dimension problem. The simulation of a simple example shows the feasibility of the current approach.
Interrogating innocence: “Childhood” as exclusionary social practice

Within the contemporary US context, the construct of childhood innocence is a powerful social myth that structures children’s social relations and culture and informs their rights and status in society. In this article, I interrogate the construct of childhood innocence to examine how it operates as an exclusionary form of social practice. By examining the emotional investments and social tensions that have shaped concepts of childhood, which define who is entitled to innocence and what it means to “belong” with/in childhood, I reveal how the doctrine of innocence has operated to maintain White supremacy. I explore the implications of a construct of childhood that works against the agency and dignity of most children by perpetuating silence about social injustices to illustrate the need for a reconceptualization of childhood that acknowledges and prioritizes the human rights of all children.
Surface Reconstruction and Application of Subdivision

This paper describes a Butterfly subdivision surfaces method which was structured by dense and unorganized triangle mesh. In this paper, using improved QEM algorithm to construct the control meshes in mesh simplification, then, using a modified Butterfly subdivision surfaces method produces subdivision surfaces to get good approximation of the initial meshes. Also describes the construction of a continuous multi-resolution model and its application in the network transmission.
A Longitudinal Study Revisiting the Notion of Early Number Sense: Algebraic Arithmetic AS a Catalyst for Number Sense Development

ABSTRACT The aim of this study was to propose a new conceptualization of early number sense. Six-year-old students’ (n = 204) number sense was tracked from the beginning of Grade 1 through the beginning of Grade 2. Data analysis suggested that elementary arithmetic, conventional arithmetic, and algebraic arithmetic contributed to the latent construct early number sense, and the invariance of the model over time was validated empirically. Algebraic arithmetic represents the dimension of early number sense that moves beyond conventional arithmetic and encompasses an abstract understanding of the relations between numbers. A parallel process growth model showed that the three components of number sense adopt a linear growth rate. A structural model showed that the growth rate of the algebraic arithmetic component has a direct effect on the growth rate of conventional arithmetic, and subsequently the growth rate of conventional arithmetic predicts the growth rate of elementary arithmetic.
Interferon γ–independent Rejection of Interleukin 12–transduced Carcinoma Cells Requires CD4+ T Cells and Granulocyte/Macrophage Colony–stimulating Factor

We analyzed the ability of interferon (IFN)-γ knockout mice (GKO) to reject a colon carcinoma transduced with interleukin (IL)-12 genes (C26/IL-12). Although the absence of IFN-γ impaired the early response and reduced the time to tumor onset in GKO mice, the overall tumor take rate was similar to that of BALB/c mice. In GKO mice, C26/IL-12 tumors had a reduced number of infiltrating leukocytes, especially CD8 and natural killer cells. Analysis of the tumor site, draining nodes, and spleens of GKO mice revealed reduced expression of IFN- inducible protein 10 and monokine induced by γ-IFN. Despite these defects, GKO mice that rejected C26/IL-12 tumor, and mice that were primed in vivo with irradiated C26/IL-12 cells, showed the same cytotoxic T lymphocyte activity but higher production of granulocyte/macrophage colony–stimulating factor (GM-CSF) as compared with control BALB/c mice. Treatment with monoclonal antibodies against GM-CSF abrogated tumor regression in GKO but not in BALB/c mice. CD4 T lymphocytes, which proved unnecessary or suppressive during rejection of C26/IL-12 cells in BALB/c mice, were required for tumor rejection in GKO mice. CD4 T cell depletion was coupled with a decline in GM-CSF expression by lymphocytes infiltrating the tumors or in the draining nodes, and with the reduction and disappearance of granulocytes and CD8 T cells, respectively, in tumor nodules. These results suggest that GM-CSF can substitute for IFN-γ in maintaining the CD8–polymorphonuclear leukocyte cross-talk that is a hallmark of tumor rejection.
Postoperative evaluation of moyamoya disease with perfusion-weighted MR imaging: initial experience.

BACKGROUND AND PURPOSE Encephaloduroarteriosynangiosis (EDAS) has become the main treatment for moyamoya disease, a chronically progressive cerebrovascular occlusive disease in children. We aimed to assess the utility of perfusion-weighted MR imaging for evaluating hemodynamic changes before and after EDAS. METHODS Thirteen patients with angiographically confirmed moyamoya disease who underwent EDAS were investigated, and results were compared with those of a control group (n = 5). Perfusion MR imaging was performed before and after EDAS by using a T2*-weighted contrast material-enhanced technique. Relative cerebral blood volume (rCBV) and time to peak enhancement (TTP) maps were calculated. Relative ratios of rCBV and TTP in the middle cerebral artery (MCA) and basal ganglia were measured and compared with those of the posterior cerebral artery (PCA). Changes in hemodynamic parameters between pre- and post-EDAS perfusion maps were investigated. RESULTS The mean rCBV ratio of MCA to PCA in the patient group was slightly higher than that in the control group, without statistical significance. All 13 patients showed a delayed TTP in the MCA before EDAS compared with the control group (P =.0006), and the TTP after EDAS was significantly reduced (P =.0002). In the basal ganglia, shortening of the TTP was demonstrated before EDAS, but no significant change was observed after EDAS. CONCLUSION Perfusion-weighted MR imaging can be applied for evaluating postoperative changes in cerebral blood flow in moyamoya disease. Shortening of the TTP in the MCA of the hemisphere operated on is a marker for the development of collateral circulation from the external carotid artery to the internal carotid artery.
Collaborative Research Project on Ultra-Low-Power Data-Driven Networking System

Abstract Power consumption will be one of the most crucialissues to realize both future VLSI chips and communicationenvironments. This research project proposed in this paper isaiming at developing a data-driven networking system by whichthe coming networking environment can be achieved with ultra-low-power consumption 1/100 to 1/1000 of the present. To real-ize the objectives, this project is planning to proceed from twoapproaches by ultimately utilizing passive data-driven princi-ple. One approach is from the processor platform, that is, data-driven chip multi-processor platform based on self-timed elasticpipeline. And the other is from the networking scheme, that is,ad hoc networking scheme. As for the platform approach, basedon rich experience so far on data-driven processor, we proposea novel architecture including chip multi-processor core withhighly effective self-timed elastic pipeline. As for the network-ing scheme, this paper shows our proposal can reduce the num-ber of control packets that results in reduction of power con-sumption.
Adaptive texture-color based background subtraction for video surveillance

Texture and color are two primitive forms of features that can be used to describe a scene. While conventional local binary pattern (LBP) texture based background subtraction performs well on texture rich regions, it fails to detect uniform foreground objects in large uniform background. As such, color information can be used to complement texture feature. In this study, we propose to incorporate local color feature based on Improved Hue, Luminance, and Saturation (IHLS) color space and introduce an adaptive scheme that automatically adjusts the weight between texture and color similarities based on the pixel's local properties: texture uniformity and color saturation. Experiments on eight challenging sequences demonstrate the effectiveness of the proposed method compared to the state-of-the-art algorithms.
Solution architecture for detecting and preventing fraud in real time

Fraud has been an issue since the very beginnings of commerce. Today, as business moved into the online era, this topic has become a major issue in e-commerce. In this paper, we introduce a solution architecture for detection and preventing fraud in real time by using an event-based system called SARI (sense and respond infrastructure). We present the architecture and components for a real-time fraud management solution which can be easily adapted to the business needs of domain experts and business users. The SARI system provides functions to monitor customer behavior as well as it can steer and optimize customer processes in real time. For illustrating our approach, we show fraud scenarios of an online gambling service provider.
A non-parametric regression approach for missing value imputation in microarray

Microarray experiments often generate data sets with multiple missing expression values. Estimating these missing values is very important since they affect biological applications and many multivariate statistical analyses. A limitation of the existing estimating methods is that they assume the relations between genes to be linear. However, that is not always the case. In this paper, we propose a new method based on non-parametric regression combined with nearest neighbor approach, referred to as NPRA, which can capture both linear and non-linear relations between both genes and arrays. A comparative study of the imputation methods was performed on several public datasets, and our proposed method NPRA, exhibits competitive performance when compared to other methods over various datasets and percentage of missing values.
Adult Vaccination Strategies for the Control of Pertussis in the United States: An Economic Evaluation Including the Dynamic Population Effects

Background Prior economic evaluations of adult and adolescent vaccination strategies against pertussis have reached disparate conclusions. Using static approaches only, previous studies failed to analytically include the indirect benefits derived from herd immunity as well as the impact of vaccination on the evolution of disease incidence over time. Methods We assessed the impact of different pertussis vaccination strategies using a dynamic compartmental model able to consider pertussis transmission. We then combined the results with economic data to estimate the relative cost-effectiveness of pertussis immunization strategies for adolescents and adults in the US. The analysis compares combinations of programs targeting adolescents, parents of newborns (i.e. cocoon strategy), or adults of various ages. Results In the absence of adolescent or adult vaccination, pertussis incidence among adults is predicted to more than double in 20 years. Implementing an adult program in addition to childhood and adolescent vaccination either based on 1) a cocoon strategy and a single booster dose or 2) a decennial routine vaccination would maintain a low level of pertussis incidence in the long run for all age groups (respectively 30 and 20 cases per 100,000 person years). These strategies would also result in significant reductions of pertussis costs (between −77% and −80% including additional vaccination costs). The cocoon strategy complemented by a single booster dose is the most cost-effective one, whereas the decennial adult vaccination is slightly more effective in the long run. Conclusions By providing a high level of disease control, the implementation of an adult vaccination program against pertussis appears to be highly cost-effective and often cost-saving.
Human Capital and the Quality of Education in a Poverty Trap Model

This paper presents a model of a poverty trap that is caused by an unequal initial income and human capital distribution and differences in the quality of education between children from more and less advantaged social sectors. Under certain conditions, the economy converges to a situation with three stable and simultaneous equilibria, two of which constitute poverty traps, lowering the economy's current and steady-state aggregate output level as well as its growth rate. The model suggests that a policy oriented towards equalizing the quality of education would, in the long run, have the potential to reduce initial inequalities.
The Formulation of Bacteriophage in a Semi Solid Preparation for Control of Propionibacterium acnes Growth

Aims To isolate and characterise phage which could lyse P. acnes and to formulate the phage into a delivery form for potential application in topical treatment of acne infection. Methods and Results Using standard phage isolation techniques, ten phage capable of lysing P. acnes were isolated from human skin microflora. Their genomes showed high homology to previously reported P. acnes phage. These phage were formulated into cetomacrogol cream aqueous at a concentration of 2.5x108 PFU per gram, and shown to lyse underlying P. acnes cells grown as lawn cultures. These phage formulations remained active for at least 90 days when stored at four degrees Celsius in a light protected container. Conclusions P. acnes phage formulated into cetomacrogol cream aqueous will lyse surrounding and underlying P. acnes bacteria, and are effective for at least 90 days if stored appropriately. Significance and Impact of the Study There are few reports of phage formulation into semi solid preparations for application as phage therapy. The formulation method described here could potentially be applied topically to treat human acne infections. The potential exists for this model to be extended to other phage applied to treat other bacterial skin infections.
Adaptive Split Transmission for Video Streams in Wireless Mesh Networks

Wireless mesh networks hold great promise in the wireless transmission of video flows, particularly if the problem of providing sufficient network capacity can be addressed. For this reason, schemes which help to address this difficulty in capacity-limited wireless networks are of great interest. This paper presents a novel and simple algorithm, adaptive split transmission algorithm, for achieving real-time, and quality-guaranteed video transmission in wireless mesh networks. The algorithm utilizes the unused capacities of multiple channels rather than trying to transmit the flow over just one overloaded channel. The flow is efficiently split into several sub-flows in a capacity-aware manner, each sub-flow then being transmitted through different channels in parallel. The adaptive split transmission algorithm controls flows dynamically in response to changes in the states of the available channels, thereby avoiding the overloading of any one channel. We evaluate the algorithm through simulations. The results show that the adaptive split transmission algorithm achieves synchronized, quality-guaranteed, and real-time wireless video transmission. The proposed algorithm can be used for interactive real-time wireless video applications without changing current wireless hardware, MAC protocols and upper-layer protocols.